Medicine, Faculty of
Medicine, Department of
DSpace
UBCV
Huang, Kate
Doctor of Philosophy - PhD
University of British Columbia
Atrial fibrillation (AF) is a common arrhythmia linked to increased risk of stroke, heart failure, and death. In AF patients without known clinical risk factors, genetic factors are likely contributors to disease pathogenesis. Studies into the genetic risk factors of AF showed a strong association between truncating variants in the titin gene and increased risk of AF in structurally normal hearts. Titin truncating variants (TTNtv) are a well-established cause of dilated cardiomyopathy (DCM), and recent studies have also shown an increased risk of atrial and ventricular fibrillation (VF) in DCM patients with TTNtv. The effect of TTNtv on risk of AF compared to modifiable risk factors is unclear. Furthermore, the cellular effects of TTNtv in atrial and ventricular arrhythmias without dilated cardiomyopathy is unknown. The objectives of this dissertation were 1) to evaluate the association between titin variants and increased risk of AF compared to modifiable risk factors and 2) to examine the cellular effects of TTNtv identified in atrial and ventricular fibrillation patients without structural disease. We used genetic epidemiology approaches and data from UK Biobank to assess the risk of AF in titin variant carriers, and we used patient-specific induced pluripotent stem cell-derived atrial- and ventricular-like cardiomyocytes and engineered heart tissue constructs to model a TTNtv implicated in AF and VF. We demonstrated an additive effect between titin variant status and modifiable risk factors on the risk of AF. In the AF model, the TTNtv led to sarcomere disarray, reduced contractility, increased arrhythmogenicity, and transcriptional changes implicating substrate alterations. In the VF model, the TTNtv resulted in calcium transient shortening and impaired electrophysiological response to β-adrenergic stimulation. These findings highlight the utility of genetic testing to identify TTNtv carriers who are at increased risk of developing AF and the importance of clinical risk factor management to reduce AF risk. Furthermore, we provide evidence of functional abnormalities associated with TTNtv in vitro that implicate atrial myopathic remodelling as well as altered electrophysiology and β-adrenergic response in patient-specific models of AF and VF, respectively, that deepen our understanding of titinâs role in the pathogenesis of atrial and ventricular arrhythmias.
CONNECTING THE CLINIC TO THE BENCH: MODELLING THE FUNCTIONAL EFFECTS OF A TITIN VARIANT ASSOCIATED WITH ATRIAL AND VENTRICULAR ARRHYTHMIAS by Kate Huang B.Sc., The University of British Columbia, 2018 A DISSERTATION SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF DOCTOR OF PHILOSOPHY in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Experimental Medicine) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) May 2025 © Kate Huang, 2025 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the dissertation entitled: Connecting the clinic to the bench: modelling the functional effects of a titin variant associated with atrial and ventricular arrhythmias submitted by Kate Huang in partial fulfilment of the requirements for the degree of Doctor of Philosophy in Experimental Medicine Examining Committee: Dr. Liam Brunham, Associate Professor, Department of Medicine, University of British Columbia Supervisor Dr. Zachary Laksman, Assistant Professor, Department of Medicine and School of Biomedical Engineering, University of British Columbia Co-supervisor Dr. Pascal Bernatchez, Associate Professor, Department of Anesthesiology, Pharmacology and Therapeutics, University of British Columbia University Examiner Dr. Francis Lynn, Associate Professor, Department of Surgery and School of Biomedical Engineering, University of British Columbia University Examiner Dr. Wenbin Liang, Associate Professor, Department of Cellular and Molecular Medicine, University of Ottawa Heart Institute External Examiner Additional Supervisory Committee Members: Glen Tibbits, Professor, Departments of Biomedical Physiology and Kinesiology and Molecular Biology and Biochemistry, Simon Fraser University Supervisory Committee Member Fabio Rossi, Professor, Department of Medical Genetics and School of Biomedical Engineering, University of British Columbia Supervisory Committee Member iii Abstract Atrial fibrillation (AF) is a common arrhythmia linked to increased risk of stroke, heart failure, and death. In AF patients without known clinical risk factors, genetic factors are likely contributors to disease pathogenesis. Studies into the genetic risk factors of AF showed a strong association between truncating variants in the titin gene and increased risk of AF in structurally normal hearts. Titin truncating variants (TTNtv) are a well-established cause of dilated cardiomyopathy (DCM), and recent studies have also shown an increased risk of atrial and ventricular fibrillation (VF) in DCM patients with TTNtv. The effect of TTNtv on risk of AF compared to modifiable risk factors is unclear. Furthermore, the cellular effects of TTNtv in atrial and ventricular arrhythmias without dilated cardiomyopathy is unknown. The objectives of this dissertation were 1) to evaluate the association between titin variants and increased risk of AF compared to modifiable risk factors and 2) to examine the cellular effects of TTNtv identified in atrial and ventricular fibrillation patients without structural disease. We used genetic epidemiology approaches and data from UK Biobank to assess the risk of AF in titin variant carriers, and we used patient-specific induced pluripotent stem cell-derived atrial- and ventricular-like cardiomyocytes and engineered heart tissue constructs to model a TTNtv implicated in AF and VF. We demonstrated an additive effect between titin variant status and modifiable risk factors on the risk of AF. In the AF model, the TTNtv led to sarcomere disarray, reduced contractility, increased arrhythmogenicity, and transcriptional changes implicating substrate alterations. In the VF model, the TTNtv resulted in calcium transient shortening and impaired electrophysiological response to β-adrenergic stimulation. These findings highlight the utility of genetic testing to identify TTNtv carriers who are at increased risk of developing AF iv and the importance of clinical risk factor management to reduce AF risk. Furthermore, we provide evidence of functional abnormalities associated with TTNtv in vitro that implicate atrial myopathic remodelling as well as altered electrophysiology and β-adrenergic response in patient-specific models of AF and VF, respectively, that deepen our understanding of titinâs role in the pathogenesis of atrial and ventricular arrhythmias. v Lay Summary Atrial fibrillation, a common heart rhythm disorder that prevents the heart from pumping blood effectively, is linked to an increased risk of life-threatening diseases like stroke and heart failure. Genetic mutations in the titin protein were recently identified as a potential cause of atrial fibrillation and ventricular rhythm disorders. However, how titin mutations lead to rhythm disorders in individuals with healthy hearts is unclear. Here, we studied the risks of having titin mutations as well as its rhythm perturbing effects in atrial and ventricular patient stem cell-derived heart cells. We found that titin mutations increase the likelihood of having atrial fibrillation, especially in individuals with pre-existing conditions like high blood pressure. In heart cells, titin mutations can affect electrical signalling or force generation and could lead to rhythm disorders differently for each patient. These results improve our understanding of titin and its role in the development of abnormal heart rhythms. vi Preface The research described in this dissertation were identified, designed, performed, and analyzed by the author, Kate Huang, under the co-supervision of Drs. Zachary Laksman and Liam Brunham and the committee members Dr. Glen Tibbits and Dr. Fabio Rossi. The dissertation was written solely by the author with feedback from the supervisory committee members. Generative AI was not used for any aspects of this work. The dissertation draws from manuscripts published in peer-reviewed journals or in-preparation for submission. The contributions of all collaborators are described below. A version of Chapter 2 has been published in the Canadian Journal of Cardiology. Huang K, Trinder M, Roston TM, Laksman ZW, Brunham LR. The interplay between titin, polygenic risk and modifiable cardiovascular risk factors in atrial fibrillation. Can J Cardiol. 2021;37(6): 848-856. KH, MT, ZWL, and LRB conceived and designed the study. LRB obtained funding for the study. LRB and ZWL provided supervision for the study. KH (100%) analyzed the clinical data. MT processed and analyzed the genetic data. TMR provided input on data interpretation and future directions. KH (100%) performed statistical analyses, interpreted the results, and drafted the manuscript. All authors reviewed the manuscript. This study was approved by UK Biobank and the Clinical Research Ethics Board at the University of British Columbia (H18-02181). A version of Chapter 3 has been published in Circulation: Genomic and Precision Medicine. Huang K, Ashraf M, Rohani L, Luo Y, Sacayanan A, Huang H, Haegert A, Volik S, Sar F, LeBihan S, Liew J, Backx P, Roberts JD, Tibbits GF, Churko JM, Sanatani S, Collins C, vii Brunham LR, Laksman ZW. Atrial fibrillation related titin truncation is associated with atrial myopathy in patient-derived iPSC disease models. Circ Genom Precis Med. 2025:e004412 [online ahead of print]. ZWL, LRB, GFT, SS, and JDR conceptualized the study. ZWL, LRB, and PHB provided funding and resources for the cardiomyocyte monolayer and engineered heart tissue work. ZWL and LRB supervised the stem cell and stem cell-derived cardiomyocyte experiments. ZWL supervised the engineered heart tissue experiments. JMC provided resources for the acquisition and analysis of data from engineered heart tissue experiments. CC provided resources for RNA-seq experiments. KH (100%) designed and performed all cardiomyocyte monolayer experiments (differentiation, characterization, confocal imaging, and electrophysiology), analyzed data, and interpreted results. KH (100%) designed and performed stem cell genome-editing experiments under the supervision of HH. MA designed the optical mapping equipment, optimized electrophysiology experiments, and wrote the electrophysiology analysis software. AS designed the electrical stimulator. JMC provided critical input on the design of the engineered heart tissue model platform and contractility analysis. LR and YL generated engineered heart tissue constructs, performed tissue electrophysiology experiments, and analyzed data. YL (50%), AS (40%), and KH (10%) analyzed engineered heart tissue contractility data and interpreted results. KH (100%) performed Western blotting and analyzed results. AH, SV, FS, and SL performed library preparation, bulk RNA-sequencing, and data analysis at the Vancouver Prostate Centre Laboratory for Advanced Genome Analysis. SL supervised RNA-seq experiments and data analysis. KH (10%) analyzed and interpreted some RNA-sequencing data. HH supervised iPSC genome-editing experiments and provided protocols for the genome-editing experiments and analysis of RNA-sequencing data by KH. JL obtained study approval, consented patients, collected clinical data, and managed clinical data and viii samples. The induced pluripotent stem cells were reprogrammed by the BC Childrenâs Hospital Research Institute Tissue and Disease Modeling Core under the supervision of Dr. Francis Lynn. KH wrote the manuscript with input from all authors. KH, MA, and LR share co-first authorship. This study was approved by the University of British Columbia Childrenâs and Womenâs Research Ethics Board (H18-01465). The PERSONALIZE AF biobank was approved by the University of British Columbia Clinical Research Ethics Board (H15-02970). Chapter 4 contains unpublished data. ZWL, LRB, GFT, SS, and JDR conceptualized the study. KH designed and performed the experiments under the supervision of ZWL and LRB. The induced pluripotent stem cells were reprogrammed by the BC Childrenâs Hospital Research Institute Tissue and Disease Modeling Core under the supervision of Dr. Francis Lynn. This study was approved by the University of British Columbia Childrenâs and Womenâs Research Ethics Board (H18-01465). ix Table of Contents Abstract ......................................................................................................................................... iii Lay Summary .................................................................................................................................v Preface ........................................................................................................................................... vi Table of Contents ......................................................................................................................... ix List of Tables ................................................................................................................................xv List of Figures ............................................................................................................................ xvii List of Abbreviations ...................................................................................................................xx Acknowledgements ................................................................................................................... xxii Dedication ................................................................................................................................. xxiv Chapter 1: Introduction ................................................................................................................1 1.1 Titin in Healthy Hearts.....................................................................................................1 1.1.1 Cardiac Isoforms of Titin .........................................................................................1 1.1.2 Titin Imparts Passive Tension to Cardiac Tissue .....................................................3 1.1.3 Titin Acts as a Mechanosensor ................................................................................5 1.1.4 Titin Contributes to Sarcomere Assembly ...............................................................5 1.2 Titin Truncating Variants and Disease ............................................................................7 1.2.1 Prevalence of Titin Truncating Variants ..................................................................7 1.2.2 Titin-Associated Atrial and Ventricular Arrhythmias in Dilated Cardiomyopathy .8 1.2.3 Atrial Fibrillation and Ventricular Fibrillation ........................................................9 1.2.4 Titin and Increased Risk of Atrial or Ventricular Fibrillation ...............................12 x 1.3 Phenotypic and Functional Abnormalities in Titin-Associated Dilated Cardiomyopathy ........................................................................................................................................13 1.4 Advances in In Vitro Cardiac Disease Modelling ..........................................................16 1.4.1 Human Pluripotent Stem Cell-Derived Cardiomyocytes .......................................16 1.4.2 Directed Differentiation of hPSCs to Atrial-Like Cardiomyocytes .......................18 1.4.3 Engineered Heart Tissue Constructs ......................................................................20 1.5 Hypotheses and objectives .............................................................................................22 1.5.1 Research Significance ............................................................................................22 1.5.2 Hypotheses and Objectives ....................................................................................24 Chapter 2: The Interplay Between Titin, Polygenic Risk, and Modifiable Cardiovascular Risk Factors in Atrial Fibrillation ..............................................................................................27 2.1 Chapter Summary ..........................................................................................................27 2.2 Introduction ....................................................................................................................28 2.3 Methods..........................................................................................................................29 2.3.1 UK Biobank Cohort ...............................................................................................29 2.3.2 Definition of Phenotypic Disease and Procedures .................................................29 2.3.3 Identification of TTNv in UK Biobank Participants ..............................................30 2.3.4 Calculation of Polygenic Risk Score for AF ..........................................................31 2.3.5 Statistical Analysis .................................................................................................31 2.4 Results ............................................................................................................................32 2.4.1 UK Biobank Participant Characteristics ................................................................32 2.4.2 TTNv and Risk of AF or Other Cardiovascular Outcomes ...................................34 2.4.3 TTNv and Risk of AF-Associated Cardiovascular Outcomes ...............................36 xi 2.4.4 TTNv and Modifiable Risk Factors of AF .............................................................39 2.4.5 Polygenic Score and Modifiable Risk Factors of AF ............................................41 2.5 Discussion ......................................................................................................................44 Chapter 3: Atrial Fibrillation Related Titin Truncation is Associated with Atrial Myopathy in Patient-derived iPSC Disease Models ....................................................................................49 3.1 Chapter Summary ..........................................................................................................49 3.2 Introduction ....................................................................................................................50 3.3 Methods..........................................................................................................................51 3.3.1 Study Approval ......................................................................................................51 3.3.2 Patient Sequencing and Titin Variant Identification ..............................................51 3.3.3 iPSC Reprogramming and Characterization ..........................................................51 3.3.4 CRISPR/Cas9 Genome Editing .............................................................................52 3.3.5 iPSC-CM Differentiation .......................................................................................53 3.3.6 Flow Cytometry .....................................................................................................54 3.3.7 RT-qPCR................................................................................................................54 3.3.8 Optical Mapping of Voltage and Calcium Transients ...........................................55 3.3.9 Sarcomere Organization Analysis ..........................................................................56 3.3.10 SDS-Agarose Gel Electrophoresis and Western Blot ............................................56 3.3.11 iPSC-CM Expansion and Engineered Heart Tissue Construction .........................57 3.3.12 Contractile Force Measurements ...........................................................................59 3.3.13 Bulk RNA-seq and Analysis of Differential Expression and Splicing ..................59 3.3.14 Statistical Analysis .................................................................................................61 3.4 Results ............................................................................................................................61 xii 3.4.1 Atrial Fibrillation Patient iPSC Reprogramming and CRISPR/Cas9 Genome Editing ................................................................................................................................61 3.4.2 Assessing TTNtv using Cell Type-Specific iPSC-CM Models .............................63 3.4.3 TTNtv Increases Susceptibility to Pacing-Induced Arrhythmia in Atrial and Ventricular iPSC-CMs ...........................................................................................................67 3.4.4 TTNtv Impairs Sarcomere Structures in Atrial and Ventricular iPSC-CMs .........69 3.4.5 TTNtv Impairs Contractile Force Generation in Atrial EHTs ...............................73 3.4.6 Whole Transcriptome Sequencing Reveals Differential Splicing of Cardiac-Specific Genes as Well as Upregulation of Genes Involved in Cell Adhesion and Extracellular Matrix in TTNtv EHTs .....................................................................................75 3.5 Discussion ......................................................................................................................78 Chapter 4: TTNtv-Associated Ventricular Fibrillation Leads to Abnormal Electrophysiology and β-Adrenergic Response in Patient-Specific Ventricular iPSC-CMs 84 4.1 Chapter Summary ..........................................................................................................84 4.2 Introduction ....................................................................................................................85 4.3 Methods..........................................................................................................................86 4.3.1 Study Approval ......................................................................................................86 4.3.2 Patient Sequencing and Titin Variant Identification ..............................................86 4.3.3 iPSC Reprogramming and Characterization ..........................................................86 4.3.4 CRISPR/Cas9 Genome Editing .............................................................................87 4.3.5 iPSC-CM Differentiation .......................................................................................88 4.3.6 Flow Cytometry .....................................................................................................89 4.3.7 Optical Mapping of Voltage and Calcium Transients ...........................................89 xiii 4.3.8 Contractility Analysis using MUSCLEMOTION .................................................91 4.3.9 Statistical Analysis .................................................................................................91 4.4 Results ............................................................................................................................91 4.4.1 Ventricular Fibrillation Patient iPSC Reprogramming and Genome Editing ........91 4.4.2 Modelling the TTNtv in Atrial and Ventricular iPSC-CMs ..................................94 4.4.3 TTNtv Does Not Impair Contractility in iPSC-CMs .............................................97 4.4.4 TTNtv Impairs Calcium Transient Properties in Ventricular iPSC-CMs ..............99 4.4.5 TTNtv and the Risk of Pacing-Induced Arrhythmogenic Events in iPSC-CMs .102 4.4.6 TTNtv Impairs Response to Isoproterenol Treatment in Ventricular iPSC-CMs104 4.5 Discussion ....................................................................................................................106 Chapter 5: Conclusion ...............................................................................................................112 5.1 Summary ......................................................................................................................112 5.2 Limitations and Future Directions ...............................................................................115 5.3 Conclusions ..................................................................................................................117 References ...................................................................................................................................121 Appendices ..................................................................................................................................146 Appendix A ..............................................................................................................................146 A.1 Supplemental Tables ................................................................................................146 A.2 Supplemental Figures ...............................................................................................195 Appendix B ..............................................................................................................................200 B.1 Supplemental Tables ................................................................................................200 B.2 Supplemental Figures ...............................................................................................221 Appendix C ..............................................................................................................................229 xiv C.1 Supplemental Tables ................................................................................................229 C.2 Supplemental Figures ...............................................................................................233 xv List of Tables Table 2.1 Participant characteristics, without or with TTNv. ....................................................... 33 Table A.1 Disease and procedure definitions. ............................................................................ 146 Table A.2 Quality control measures for genetic data. ................................................................ 164 Table A.3 TTNv identified in UK Biobank participants. ............................................................ 166 Table A.4 Participant characteristics, without or with AF. ......................................................... 189 Table A.5 Participant characteristics, AF without or with TTNv. .............................................. 190 Table A.6 Adjusted hazard ratio (aHR) and 95% confidence interval (CI) for TTNv carriers versus non-carriers and disease risk since enrolment. ................................................................ 191 Table A.7 Stroke rates of AF patients without or with TTNv, grouped by CHA2DS2-VASc score < 2 and â¥ 2. ................................................................................................................................. 192 Table A.8 Risk of DCM or HF after AF following initial AF diagnosis. ................................... 193 Table A.9 Multivariate Cox regression analysis for the association between TTNv and modifiable risk factors and AF since enrolment. ........................................................................ 194 Table A.10 Adjusted hazard ratio (aHR) and 95% confidence interval (CI) for AF stratified by risk factor level and PRS group since enrolment. ....................................................................... 194 Table A.11 Power analysis results. ............................................................................................. 195 Table B.1 Custom CRISPR/Cas9 oligonucleotide sequences. ................................................... 200 Table B.2 CRISPR/Cas9 on-target editing efficiencies. ............................................................. 200 Table B.3 CRISPR/Cas9 predicted off-target sites. .................................................................... 201 Table B.4 Primer sequences. ....................................................................................................... 202 Table B.5 Participant characteristics at recruitment. .................................................................. 203 xvi Table B.6 Univariate linear regression of contractility measurements by genotype in beat rate-matched engineered heart tissues. ............................................................................................... 204 Table B.7 Significantly differentially spliced genes in atrial WT/TTNtv and isogenic WT/WT engineered heart tissues. ............................................................................................................. 205 Table B.8 Significantly differentially spliced genes in ventricular WT/TTNtv and isogenic WT/WT engineered heart tissues. ............................................................................................... 208 Table B.9 Significantly downregulated genes in atrial WT/TTNtv relative to isogenic WT/WT engineered heart tissues. ............................................................................................................. 211 Table B.10 Significantly upregulated genes in atrial WT/TTNtv relative to isogenic WT/WT engineered heart tissues. ............................................................................................................. 212 Table B.11 Significantly upregulated genes in ventricular WT/TTNtv relative to isogenic WT/WT engineered heart tissues. ............................................................................................... 218 Table C.1 Custom CRISPR/Cas9 oligonucleotide sequences. ................................................... 229 Table C.2 CRISPR/Cas9 on-target editing efficiencies. ............................................................. 229 Table C.3 CRISPR/Cas9 predicted off-target sites. .................................................................... 229 Table C.4 PCR genotyping primer sequences. ........................................................................... 230 Table C.5 Participant characteristics at recruitment. .................................................................. 231 Table C.6 Comparison of calcium transient durations in ventricular iPSC-CMs paced at 60 beats-per-minute. .................................................................................................................................. 231 xvii List of Figures Figure 1.1 Titin isoforms in the cardiac sarcomere. ....................................................................... 2 Figure 1.2 Generation of human induced pluripotent stem cells and cardiomyocytes. ................ 18 Figure 1.3 Engineered heart tissues. ............................................................................................. 20 Figure 2.1 Cumulative incidence of AF, HF, DCM, and composite outcomes. ........................... 34 Figure 2.2 Cumulative incidence of DCM, HF, and composite outcomes in AF patients. .......... 37 Figure 2.3 TTNv and modifiable risk factors of AF. .................................................................... 40 Figure 2.4 PRS and modifiable risk factors of AF. ....................................................................... 43 Figure 3.1 Patient iPSC reprogramming and CRISPR/Cas9 gene editing. ................................... 62 Figure 3.2 Differentiation of patient iPSCs to atrial and ventricular iPSC-CMs.......................... 64 Figure 3.3 Atrial and ventricular iPSC-CM mRNA expression. .................................................. 66 Figure 3.4 TTNtv increases the susceptibility of iPSC-CMs to pacing-induced arrhythmia. ...... 68 Figure 3.5 TTNtv iPSC-CMs exhibited disorganized sarcomere structures. ................................ 70 Figure 3.6 iPSC-CM gel electrophoresis and Western blot. ......................................................... 72 Figure 3.7 Atrial TTNtv EHTs displayed reduced contractile force compared to isogenic WT EHTs. ............................................................................................................................................ 74 Figure 3.8 Whole transcriptome differential gene expression of atrial and ventricular EHTs. .... 76 Figure 4.1 Ventricular fibrillation patient iPSC reprogramming and CRISPR/Cas9 gene editing........................................................................................................................................................ 93 Figure 4.2 Differentiation of ventricular fibrillation patient iPSCs to atrial and ventricular iPSC-CMs. .............................................................................................................................................. 95 Figure 4.3 Contraction amplitude analysis of iPSC-CM monolayers. ......................................... 98 xviii Figure 4.4 Ventricular TTNtv iPSC-CMs exhibit shorter calcium transient durations. ............. 100 Figure 4.5 Analysis of susceptibility to pacing-induced arrhythmia in atrial and ventricular iPSC-CMs. ............................................................................................................................................ 103 Figure 4.6 Ventricular TTNtv iPSC-CMs show altered electrophysiological response to isoproterenol. .............................................................................................................................. 105 Figure 5.1 Effects of the TTNtv in iPSC-CM models of atrial and ventricular fibrillation. ...... 118 Figure A.1 Locations of identified TTNv along the titin protein. ............................................... 196 Figure A.2 Cumulative incidence of DCM, HF, and composite events after an AF diagnosis. . 197 Figure A.3 Cumulative incidence of AF stratified by PRS group. ............................................. 198 Figure A.4 Risk of AF stratified by modifiable risk factor level and PRS group since enrolment...................................................................................................................................................... 199 Figure B.1 iPSC-CM electrophysiology characteristics. ............................................................ 221 Figure B.2 Atrial and ventricular EHT characterization. ............................................................ 222 Figure B.3 Contractile force generation in atrial and ventricular EHTs under paced conditions...................................................................................................................................................... 223 Figure B.4 Allele balance and titin isoform usage in EHTs. ...................................................... 224 Figure B.5 Differential splicing analysis of atrial EHTs. ........................................................... 226 Figure B.6 Differential splicing analysis of ventricular EHTs. .................................................. 228 Figure C.1 iPSC-CM flow cytometry gating strategy. ............................................................... 233 Figure C.2 Spontaneously beating iPSC-CM electrophysiology characteristics. ....................... 234 Figure C.3 Electrophysiological response to isoproterenol in iPSC-CMs .................................. 235 Figure C.4 Contraction analysis in iPSC-CMs treated with isoproterenol. ................................ 236 xix Figure C.5 Atrial fibrillation patient iPSC-derived TTNtv EHTs display comparable contractile force generation in response to isoproterenol stimulation as WT EHTs. ................................... 237 xx List of Abbreviations AF, atrial fibrillation aHR, adjusted hazard ratio APD, action potential duration CaTD, calcium transient duration CCE, composite cardiovascular event CI, confidence interval CS, current smoking cTnT, cardiac troponin T DCM, dilated cardiomyopathy DM, diabetes mellitus ECM, extracellular matrix EHT, engineered heart tissue EP, electrophysiology FDR, false discovery rate hESC, human embryonic stem cell HF, heart failure hPSC-CM, human pluripotent stem cell-derived cardiomyocyte HR, hazard ratio HTN, hypertension ICD-10, International Classification of Diseases, 10th Revision Ig, immunoglobulin xxi iPSC, induced pluripotent stem cell iPSC-CM, induced pluripotent stem cell-derived cardiomyocyte MLC2v, ventricular paralog of myosin light chain 2 OB, obesity OPCS-4, Office of Population Censuses and Surveys Classification of Interventions and Procedures, 4th Revision PRS, polygenic risk scores PSI, percentage spliced-in PVD, peripheral vascular disease TTN, titin TTNv, titin variant TTNtv, titin truncating variant VF, ventricular fibrillation WT, wild-type WT/TTNtv, heterozygous titin truncating variant xxii Acknowledgements I would like to express my gratitude to the many individuals and organizations who have made my research possible and have been instrumental in my development as a scientist. Thank you to my co-supervisors Dr. Zachary Laksman and Dr. Liam Brunham. I am sincerely grateful for your advice, expertise, and guidance. Thank you for encouraging me to pursue new interests and develop new skills in bioinformatics and clinical research, for being incredibly supportive of my various side quests and projects, and for always challenging me to be a better researcher and a better person. Thank you for teaching me important lessons on thinking big picture, failing early but failing forward, resiliency, effective communication, and leadership. Thank you to my supervisory committee members, Dr. Glen Tibbits and Dr. Fabio Rossi, for your mentorship, kindness, and intellectually stimulating discussions throughout the last few years. I would especially like to thank Dr. Glen Tibbits for his expertise on everything related to cardiac physiology and for providing me with the opportunity to befriend and collaborate with past and present members of the Tibbits Lab. I extend my thanks to Dr. Sanam Shafaat Talab, Mr. Marvin Gunawan, and Mr. Sarabjit Sangha for their technical support on cardiac differentiation. I am incredibly fortunate to have been surrounded by such an amazing, kind, and supportive group of people throughout my journey. I would like to thank past and present members of the Brunham Lab and Laksman Lab: Dr. Effimia Christidi, Dr. Haojun (Margaret) Huang, Dr. Mark xxiii Trinder, Dr. Diana Vikulova, Mr. Rylan McCallum, Ms. Linda Jackson, Dr. Eric Deng, Dr. Danielle Pinheiro Muller, Ms. Luba Cermakova, Ms. Nicol Vaizman, Dr. Shinya Iwase, Ms. Wendy Liang, Mr. Mishal Ashraf, Dr. Leili Rohani, Ms. Janet Liew, Ms. Yinhan (Hattie) Luo, Mr. Ardin Sacayanan, Dr. Sina Safabakhsh, Ms. Swetha Srinivasaraghavan, Ms. Ellie Leung, Mr. Raam Sivakumar, Ms. Georgia Donaldson-Barrio, Dr. Quynh Nguyen, Ms. Carol Shen, Dr. Jeremy Parker, and Dr. Tammy Ying, for their intellectual support and friendship. It has been a privilege to work with and learn alongside everyone. Thank you to the Stem Cell Network of Canada (ACCT-14), Canadian Institutes of Health Research Canada Graduate Scholarships Doctoral program (FBD-181543), and the University of British Columbia for their financial support of my PhD and research. Importantly, I would like to thank my family and friends for their endless support. Thank you for being willing to lend an ear and for being there for me through the good and the bad. Your patience, grace, love, and humour were huge contributors to the completion of this work. Finally, I would like to thank everyone at the Centre for Heart Lung Innovation, the Experimental Medicine Program at the University of British Columbia, the Faculty of Graduate and Postdoctoral Studies at the University of British Columbia, Compute Canada, and the University of British Columbia Advanced Research Computing platform for their support. Thank you to all the patients, study participants, and volunteers involved in the research described in this dissertation. xxiv Dedication To the patients, participants, families, and volunteers involved in this research. Thank you for your time and contributions which have made this work possible. Your participation will help advance our knowledge of heart rhythm disorders. 1 Chapter 1: Introduction 1.1 Titin in Healthy Hearts 1.1.1 Cardiac Isoforms of Titin The human heart is a vital organ in the circulatory system that delivers oxygenated blood through the body and deoxygenated blood to the lungs for reoxygenation. The beating of healthy hearts is initiated by sinoatrial nodal pacemaker cells which depolarize and transmit electrical signals through the atria to the atrioventricular node, bundle of His, Purkinje fibres, and ventricles, causing myocardial contraction. The link between action potential depolarization and cardiomyocyte contraction, termed excitation-contraction coupling, is a highly coordinated process involving ion channels in the plasma membrane and sarcoplasmic reticulum as well as structural sarcomere proteins. Dysfunctional ion channel or structural protein activity that disrupt this process can lead to specific cardiac pathophysiology, including arrhythmias and myopathies. Defects in structural proteins can lead to chamber dilation or hypertrophy, alter cardiac function and output, and contribute to the pathogenesis of structural cardiac diseases such as cardiomyopathies and heart failure. Titin is the largest protein expressed in the human body and is a critical structural protein in the heart. Since the discovery of titin in 1979,1 its functional role in the heart has been an area of growing interest due to its associations with cardiac diseases. Titin RNA transcripts undergo extensive alternative splicing to yield splice isoforms up to approximately 3.7 MDa in size.2 The main titin splice isoforms expressed in cardiac tissue are N2B (~3 MDa) and N2BA (~3.3 MDa), and the N-terminus to C-terminus of these isoforms span half a sarcomere from the Z-disk, where actin 2 filaments are anchored, to the M-band where adjacent myosin filaments are crosslinked (Figure 1.1). Figure 1.1 Titin isoforms in the cardiac sarcomere. Alternative splicing in the I-band region of titin yields various titin protein isoforms including the two principal cardiac isoforms N2B and N2BA as well as Novex-3 and Cronos. Reprinted with permission from Loescher and Hobbach et al., 2022.3 N2B is expressed at greater levels than N2BA in healthy adult hearts and both are incorporated into sarcomeres with each half containing six titin proteins.4,5 Other titin isoforms such as fetal 3 cardiac titin, Novex-3, and Cronos are also detectable in cardiac tissue.2,6â8 The N-terminal region of titin is anchored to the sarcomere Z-disk through interactions with α-actinin. The I-band region of titin overlaps the actin filaments in the sarcomere and is extensible due to the presence of tandem immunoglobulin (Ig)-like domains, a proline, glutamate, valine, and lysine (PEVK)-rich segment, and an N2B unique sequence.9 These impart a viscoelastic property to titin that allows it to act as a molecular spring. In contrast, A-band titin which overlaps the myosin filaments is significantly less extensible and consists of Ig-like domains and fibronectin type three domains that interact with thick filament proteins and myosin-binding protein C.10 M-band titin interacts with myomesin and contains an inactive pseudokinase.11 N2BA is larger and less stiff than N2B due to its longer tandem Ig-like domains and PEVK segment as well as the inclusion of an N2A element in the I-band region. Fetal cardiac titin resembles N2BA but contains longer tandem Ig-like domains in the I-band and requires even less force to extend. Expression of fetal cardiac titin decreases during cardiac development and switches to the N2BA and N2B isoforms. 1.1.2 Titin Imparts Passive Tension to Cardiac Tissue A key function of titin in the heart is the generation of passive force via its spring-like properties which restores stretched sarcomeres back to slack length. The proportion of N2BA:N2B incorporated into sarcomeres serves as a method of regulating passive stiffness across different regions of the heart. N2BA expression is significantly higher in the atria compared to ventricles,12 likely contributing to greater tissue compliancy. Titin isoform switching has been shown to occur in disease. For example, increased N2BA expression has been detected in hearts of dilated cardiomyopathy (DCM) patients and was associated with decreased passive tension.13 4 Another mechanism of regulating passive stiffness is through post-translation modifications of I-band titin. The N2B unique sequence is a phosphorylation target of protein kinases PKG, PKA, and PKD, ERK2 (extracellular signal-regulated kinase 2), and CaMKIIδ (calcium/calmodulin-dependent protein kinase II delta) while the PEVK element is targeted by PKCα (protein kinase C alpha), PKD, and CaMKIIÎ´.14â18 Phosphorylation of the N2B unique sequence reduces passive tension while phosphorylation of the PEVK element increases tension. The addition of negatively charged phosphate groups is hypothesized to decrease stiffness by increasing electrostatic repulsion within the N2B unique sequence which has a net negative charge and increase stiffness by increasing attractive forces within the positively charged PEVK element.3 Other post-translational modifications can also regulative passive stiffness, such as disulfide crosslinking of the N2B unique sequence (increases stiffness),19 S-glutathionylation of unfolded Ig-like domains (decreases stiffness),20 and acetylation of the PEVK element (increases stiffness).21 When cardiomyocytes are stretched, sarcomere lengths and passive tension increase, leading to increased active force generation due to increased calcium sensitivity in a process known as length-dependent activation. The exact mechanisms modulating calcium sensitivity in response to stretch are unclear.22 However, it has been proposed that sarcomere stretch disrupts the interactions between titin and myosin heads and promotes the transition of myosin heads from an âOFFâ state to an âONâ state, thus increasing myosin recruitment.23â25 In summary, titin imparts passive tension which is regulated by isoform switching or post-translational modifications in I-band titin and plays a role in tissue compliancy as well as active force generation. 5 1.1.3 Titin Acts as a Mechanosensor Mechanosensing properties of I-band titin have been observed. The N2B unique sequence interacts with several proteins, such as FHL2 in a stretch-dependent manner,26 and mediates hypertrophic signalling. In the absence of the N2B unique sequence, knockout mice fail to initiate a hypertrophic response to volume overload.27 The increased binding affinity between the N2B unique sequence to FHL2, a regulator of hypertrophic signalling, upon stretch raises the possibility that interactions between the N2B unique sequence and FHL2 contribute to hypertrophic signalling in response to volume overload.25 The N2A element has been observed to exhibit stretch-dependent interactions with the protease calpain-328 as well as CARP (cardiac ankyrin repeat protein),29 a regulator of NKX2.5 signalling.30 When stretched, CARP expression increases and co-localizes with myofibrils in fetal rat cardiomyocytes.29 Together, these studies indicate a role of titin in stretch-induced signalling. 1.1.4 Titin Contributes to Sarcomere Assembly Titin mediates the formation of sarcomeres and regulates the length of the thick filament.31â33 Chopra et al. demonstrated that sarcomere assembly initiates from protocostameres located at the cell periphery, beginning with the formation of Z-bodies (pre-cursors of Z-disks consisting of α-actinin and actin) followed by centripetal assembly of α-actinin-containing fibres as well as transverse assembly to later fuse with the centripetal fibres. Centripetal fibre nucleation, Z-body fusion, and directional α-actinin flow were disrupted in human induced pluripotent stem cell-derived cardiomyocytes (hPSC-CMs) with a titin truncating variant (TTNtv) in the A-band region of titin. In healthy sarcomeres, titin acts as a bridge between the α-actinin-containing Z-disk and myosin heavy chain β in the thick filament. Using CRISPR/Cas9 genome editing to 6 disrupt connections between titin and α-actinin or titin and myosin heavy chain β, Chopra et al. showed the absence of these interactions resulted in a significant reduction in force generation, absence of stable centripetal α-actinin fibres, and a significant decrease in sarcomere content, indicating a critical role of titin and titin-mediated force generation in sarcomere assembly. In addition to the full-length N2B and N2BA titin isoforms, the Cronos isoform also plays a role in sarcomere development. Cronos spans the distal Ig region, A-band, and the M-band. In the absence of Cronos expression, engineered heart tissue (EHT) constructs displayed reduced contractility and disorganized sarcomere structures compared to controls,32 indicating expression of N2B and N2BA isoforms alone is insufficient to form normal sarcomeres. In EHTs without N2B and N2BA, Cronos expression improved the sarcomere content compared to EHTs without Cronos. However, it was insufficient to restore sarcomere organization to levels back to normal. These findings indicate a critical role of the titin isoforms N2B, N2BA, and Cronos as well as the titin A-band in sarcomere assembly. Titin also contributes to sarcomere formation by regulating the length of the thick filament.33 The A-band region of titin contains 11 instances of an 11-domain super-repeat, and each super-repeat is similar in length to the spacing of myosin molecules on the thick filament. Knockout of these super-repeats in mice resulted in the shortening of thick filaments by distances that matched the length of the deleted super-repeats. In summary, the N2B, N2BA, and Cronos titin isoforms play a role in sarcomere formation. Titin acts as a bridge between sarcomere proteins to transmit force necessary for sarcomere assembly and acts as a âmolecular rulerâ to dictate thick filament length. 7 1.2 Titin Truncating Variants and Disease 1.2.1 Prevalence of Titin Truncating Variants Truncating variants in the titin gene have been associated with cardiac disorders, including cardiomyopathies and arrhythmias.34â39 Titin truncating variants (TTNtv) encompass frameshift, nonsense, and splice site variants that lead to predicted translation termination and/or protein truncation. While emerging evidence suggests a role of titin missense variants in cardiomyopathy,40,41 missense and non-truncating titin variants are typically excluded from analyses due to past studies indicating weak disease association and low enrichment in patient populations.9,10 The prevalence of TTNtv was initially estimated to be highly common in the general population at approximately 3%,34,42 presenting challenges in interpreting disease association and penetrance. However, these studies overestimated the prevalence of TTNtv by including non-pathogenic variants located in exons that are rarely incorporated into titin transcripts. Several exons are excluded from titin mRNA transcripts through alternative splicing and are less physiologically relevant to cardiac health due to their absence/low incorporation rates in the principal cardiac isoforms of titin or low/no expression in left ventricular cardiac tissue.43 The inclusion of such variants led to an overestimation of TTNtv prevalence in the general population in initial studies. More recent studies applied variant filtering criteria based on the percentage spliced-in (PSI) scores (e.g. >90%) of exons that variants were identified in.39,44 By restricting the analysis to TTNtv in high PSI exons, a re-evaluation of the prevalence of TTNtv suggested that rates were closer to 0.4-0.6% in general population cohorts such as Exome Aggregation Consortium, Geisinger MyCode Community Health Initiative, and UK Biobank.39,44,45 TTNtv are found at different frequencies across ancestral groups. Data from the Exome Aggregation Consortium indicated a significant difference across African (0.46%), 8 American (0.50%), European (0.27%), and Asian populations (East Asian: 0.37%; South Asian: 0.62%).45 Analysis of the All of Us cohort found similar rates in individuals with African or European ancestry at 0.4% and 0.5%, respectively.46 In 2021, loss-of-function titin variants were added to the American College of Medical Genetics and Genomics policy statement for reporting secondary findings in clinical exome and genome sequencing for its link to cardiomyopathy and risk of sudden death with preventable interventions available.47 American College of Medical Genetics and Genomics Secondary Findings v3.2 was subsequently published in 2023 to include guidance specifying the types of loss-of-function variants recommended for evaluation of pathogenicity and return of secondary findings.48 Frameshift and nonsense variants as well as splicing variants impacting exons with high PSI scores should be evaluated, and only pathogenic and likely pathogenic variants should be reported as secondary findings. As clinical and commercial genetic testing become more widespread, the number of individuals identified with a TTNtv is likely to increase. A better understanding of TTNtv, associated disease phenotypes, and disease mechanisms is needed to improve the interpretation of genetic findings, patient risk stratification, clinical management strategies, and development of novel therapies. 1.2.2 Titin-Associated Atrial and Ventricular Arrhythmias in Dilated Cardiomyopathy TTNtv are a well-known cause of DCM, accounting for 15-25% of DCM cases,34,43,49 and display incomplete penetrance (5%-10%).50,51 Several studies have shown that the presence of TTNtv in DCM is associated with worse clinical outcomes and arrhythmias. Patients with TTNtv display higher rates of progressive heart failure (defined as left ventricular assist device use, 9 heart transplant, heart failure, ventricular tachycardia/fibrillation, death, and/or left ejection fraction â¤ 20%), a greater frequency of left ventricular assist device implantation, and a lower rate of recovery from non-ischemic DCM compared to patients without TTNtv at five year follow-up.52 A greater frequency of patients with TTNtv experience complete left bundle branch block, non-sustained ventricular tachycardia,36 sustained ventricular tachycardia,43 as well as more severe left atrial dysfunction.53 Furthermore, TTNtv led to a 2.8-fold increase in the risk of life-threatening arrhythmias (defined as non-fatal ventricular fibrillation, haemodynamic unstable sustained ventricular tachycardia, and/or sustained ventricular tachycardia with appropriate ICD-shock) compared to DCM patients without TTNtv after a median follow-up period of 3.8 years.36 TTNtv have also been linked to a four-fold increase in the risk of developing new persistent atrial fibrillation (AF) as well as a five-fold increase in the risk of receiving defibrillator shock/anti-tachycardia pacing for ventricular tachycardia or ventricular fibrillation in non-ischemic DCM patients with defibrillator implants.37 In summary, TTNtv affect the heart beyond just the ventricles and are associated with atrial myopathic alterations as well as increased risk of atrial and ventricular arrhythmias. 1.2.3 Atrial Fibrillation and Ventricular Fibrillation AF is the most common clinically-diagnosed arrhythmia, affecting approximately 60 million people worldwide.54 AF is characterized by rapid, irregular rhythms in the atria which lead to ineffective atrial contraction. This causes blood to pool in the atria, especially in the left atrial appendage, which increases the likelihood of thrombus formation. Patients with AF experience poorer quality of life and are at increased risk of stroke, heart failure, and death.55â57 The prevalence of AF is expected to rise due to an aging global population with chronic risk factors, 10 imposing a significant healthcare and economic burden.58 Substantial efforts have been made to understand underlying disease mechanisms and identify risk factors of AF due to its high prevalence and associations with life-threatening conditions. While the exact causes of AF in a patient are often unclear, electrical abnormalities, such as spontaneous electrical activity, as well as structural alterations, such as chamber dilation or fibrosis that promote the maintenance of re-entry circuits, in atrial tissue are thought to contribute to the onset of AF.59 Altered ion currents, shortened refractoriness, sarcoplasmic reticulum calcium leak, and early/delayed-after depolarizations have been observed in AF. Furthermore, analysis of AF patient tissue indicated decreased expression and heterogeneous distribution of the atrial-specific gap junction protein Connexin 40 which can alter the conduction properties of atrial tissue.60 Together, these can increase the risk of spontaneous action potential depolarization on a vulnerable re-entrant substrate in the atria and contribute to arrhythmogenesis as well as disease persistence. AF can be categorized into four types based on the persistence of the episodes: paroxysmal, persistent, longstanding persistent, and permanent AF.61 Paroxysmal AF episodes are recurrent and last between 30 seconds to seven days. Persistent AF occurs if an episode lasts longer than seven days but less than one year while patients with longstanding persistent AF have an episode that exceeds one year. Permanent AF is said to occur in patients with a continuous AF episode and for which a therapeutic decision has been made to stop pharmacological or electrical cardioversion therapies to restore sinus rhythm. To manage AF, beta-blockers or non-dihydropyridine calcium channel blockers are often prescribed as first-line agents for rate control.61 AF patients may also receive antiarrhythmic drugs for rhythm control or nonpharmacological interventions such as cardioversion or ablation procedures. 11 A range of clinical and genetic risk factors can contribute to the pathogenesis of AF. To date, AF has been linked to several risk factors including hypertension, diabetes mellitus, excessive alcohol or drug use, and prior myocardial infarction or heart failure.62 Non-modifiable risk factors such as older age, male sex, and genetics have also been identified. Common variants have been associated with AF in genome-wide association studies, and the combined polygenic contributions of these common variants may also add to the risk of developing AF.63 It is hypothesized that genetic factors may be the primary drivers of disease pathogenesis in early-onset AF patients as well as lone AF patients who do not present with clinical comorbidities. Existing AF risk estimation tools such as CHARGE-AF rely solely on clinical risk factors,64 and the integration of monogenic or polygenic disease contributors could potentially improve risk prediction. Rare variants in sodium and potassium ion channel and cardiac signaling genes have been shown to cause autosomal dominant familial AF. A gain-of-function variant in the KCNQ1 gene which encodes a voltage-gated potassium channel (IKs) increased atrial refractoriness.65 Similarly, a frameshift variant in the NPPA gene encoding atrial natriuretic peptide led to increased protein activity and action potential and refractory period shortening.66 Variants in structural proteins such as myosin light chain 4 have also been implicated in early-onset AF with an autosomal dominant or recessive inheritance pattern.67,68 In a zebrafish model, a myosin light chain 4 missense variant led to structural alterations in the atria including sarcomere disorganization and atrial enlargement. These genetic variants affect cardiac action potential properties and contractile machinery, leading to electrophysiological and structural defects that can contribute to the pathogenesis of AF. 12 Ventricular fibrillation (VF) is a life-threatening arrhythmia that is a major cause of sudden cardiac arrest.69 VF cases are much less common compared to AF, making it challenging to determine its prevalence in the general population. The incidence rate of AF is approximately 322 per 100,000 person-years70 compared to 16.8-21.3 per 100,000 person-years for out-of-hospital sudden cardiac arrest with VF rhythms.71,72 VF causes the ventricles to quiver rapidly and erratically, preventing normal cardiac contraction and leading to a loss of cardiac output. Patients with VF may receive implantable cardioverter-defibrillators to restore their heart rate to sinus rhythm. Beta-blockers can be used to manage VF and reduce the risk of sudden cardiac death, and patients may be eligible for ablation procedures if they present with a detectable initiating substrate.73 Clinical risk factors such as a history of myocardial infarction, coronary artery disease, cardiomyopathy, heart failure, and electrolyte imbalance are associated with VF.73 Furthermore, genetic variants in cardiomyopathy or arrhythmia-associated genes74 such as TTN, MYL2, KCNQ1, and RYR2 as well as a risk haplotype of DPP6, a transmembrane protein that regulates the activity of the transient outwards potassium current Ito,75 have been identified in idiopathic VF patients without known risk factors. Understanding how clinical or genetic risk factors contribute to fundamental mechanisms of arrhythmogenesis, such as automaticity, triggered activity, and re-entry, could aid in the development of novel therapies and risk management strategies. 1.2.4 Titin and Increased Risk of Atrial or Ventricular Fibrillation Several genetic studies have demonstrated links between TTNtv and AF or VF. Recent rare variant association studies have linked TTNtv to increased risk of AF in the absence of prior cardiac defects like DCM or cardiac dysfunction.35,38 Choi et al. demonstrated that among early- 13 onset AF patients (onset before age 66), carriers of a loss-of-function titin variant experienced AF onset approximately 5 years earlier than non-carriers. Furthermore, these variants were present at significantly greater frequencies in early-onset AF patients compared to healthy controls. Similarly, the prevalence of TTNtv was significantly higher in a separate early-onset AF cohort (onset before age 40) compared to healthy controls.35 TTNtv were associated with multiple cardiac diseases including AF, VF, ventricular tachycardia, cardiac arrest, cardiomyopathy, and heart failure in a phenome-wide association study of the Geisinger MyCode Community Health Initiative.39 The associations to AF and atrial flutter, paroxysmal ventricular tachycardia, and cardiac dysrhythmias remained significant after adjustment for DCM, raising the possibility that TTNtv promote arrhythmogenesis through other mechanisms beyond typical DCM phenotypes. The association between titin and AF is further supported by evidence from genome-wide association studies across the globe that have linked AF to common variants in the titin gene region.76â78 Together, these genetic studies provide strong evidence linking TTNtv to the development of arrhythmias, including AF without structural disease and VF. The clinical consequences of TTNtv in arrhythmia as well as the underlying mechanisms of arrhythmogenesis remain unclear. Further studies on TTNtv and arrhythmia could improve patient risk stratification, clinical management, and patient outcomes. 1.3 Phenotypic and Functional Abnormalities in Titin-Associated Dilated Cardiomyopathy The effects of TTNtv at a cellular or tissue level have been studied primarily in ventricular tissue and DCM models due to the known associations between TTNtv and risk of DCM. Initial studies suggested that TTNtv do not promote DCM through protein haploinsufficiency due to 14 comparable levels of total titin mRNA expression in TTNtv carriers and non-carriers as well as the absence of detectable truncated titin protein in human hearts.43,79 More recent studies of human heart tissue showed decreased expression of wild-type titin protein,80,81 providing evidence of haploinsufficiency. Furthermore, truncated titin proteins have since been detected in both human tissues and hPSC-CM models of DCM80â82 and found to accumulate in the cytosol82 or become incorporated into sarcomeres.83 These findings indicate TTNtv may contribute to the pathogenesis of DCM through both protein haploinsufficiency and a dominant-negative âpoison peptideâ mechanism. Titin plays a critical role in sarcomere formation and, accordingly, TTNtv led to disorganized sarcomere structures, sarcomere deficiency, and contractile defects.31,81,82,84,85 At baseline, TTNtv myofibrils as well as hPSC-CM and engineered heart tissue models of DCM exhibited significantly weaker contractile force compared to wild-type controls.79,84,85 The electrophysiological effects of TTNtv have been assessed in a limited number of studies. TTNtv hPSC-CMs show greater beat rate variability,85 increased depolarization spike amplitudes, and decreased spike slopes compared to wild-type.82 Conflicting evidence exists on the effects of TTNtv on calcium transient properties. TTNtv have been shown to cause slower rates of cytosolic calcium rise and decay in hPSC-CMs treated with β-adrenergic stimulation, suggesting abnormal calcium handling properties.85 However, a different study showed calcium transient amplitudes and durations comparable to wild-type controls at baseline and after β-adrenergic stimulation.82 Nevertheless, both studies reported prolonged action potential durations in TTNtv hPSC-CMs. In human hearts, TTNtv led to decreased left ventricular mass and increased interstitial myocardial fibrosis.36 Similarly, Ahlberg et al. demonstrated that an N-terminal TTNtv in the I-band region resulted in increased atrial fibrosis and led to prolonged PR 15 intervals in a zebrafish model.35 Along with findings of left atrial dysfunction in DCM patient hearts, these results suggest that TTNtv may induce substrate remodelling and lead to electrophysiological alterations to promote the pathogenesis of atrial or ventricular arrhythmias. The effects of TTNtv on gene expression have been investigated in human tissue and ventricular hPSC-CM models of DCM.36,82 Analyses of endomyocardial biopsy samples from DCM patients with or without TTNtv showed an enrichment of genes related to mitochondrial dysfunction, oxidative stress, and cardiac fibrosis. In hPSC-CM samples, TTNtv downregulated the expression of genes related to cardiac excitation and conduction, contractility, and mitochondrial function. These transcriptional changes may partly underlie the contractile, electrophysiological, and fibrotic changes associated with TTNtv. Together, these studies indicate that TTNtv lead to a wide range of phenotypic and functional alterations including sarcomere defects, differential expression of electrophysiology, sarcomere, extracellular matrix, and metabolism genes, impaired electrophysiology and contractility, and increased fibrosis in models of DCM. Interestingly, a number of these defects have the potential to be arrhythmogenic.86 The main mechanisms of cardiac arrhythmias arise from spontaneous activity or altered conduction. In healthy conditions, sinoatrial pacemaker cells spontaneously depolarize which dictates the beat rate and rhythm of the heart. In disease, atrial and ventricular cells can exhibit spontaneous activity from ectopic foci if the resting membrane potential undergoes a positive shift towards the threshold potential. Triggered activity such as early-after depolarizations or delay-after depolarizations can cause atrial and ventricular cardiomyocytes to inappropriately depolarize. Early-after depolarizations are associated with action potential prolongation and occur due to 16 reactivation of ICa,L or INa during repolarization. Slowed clearance of cytosolic calcium may create favourable conditions for the formation of delayed-after depolarizations which can occur due to high concentrations of cytosolic calcium. Conduction abnormalities can also be caused by abnormal substrate anatomy or changes in tissue excitability which slow or block conduction. These factors can facilitate the formation of re-entry circuits, a major cause of atrial and ventricular arrhythmias. Tissue fibrosis observed in TTNtv-related DCM may impact conduction and create regions with poor excitability. Furthermore, changes in ion channel gene expression may alter the balance of ionic currents, impacting the resting membrane potential, tissue excitability, and action potential/calcium transient properties. While these findings may explain the increased risk of arrhythmias in DCM patients with TTNtv, whether TTNtv lead to these phenotypic and functional abnormalities in the pathogenesis of arrhythmias, especially in patients without a clinical diagnosis of DCM or heart failure, is unknown and requires further investigation. 1.4 Advances in In Vitro Cardiac Disease Modelling 1.4.1 Human Pluripotent Stem Cell-Derived Cardiomyocytes Advances in the stem cell research field have allowed researchers to culture human embryonic stem cells (hESCs),87 generate human induced pluripotent stem cell (iPSCs) lines,88 and perform directed differentiation to cardiomyocytes (Figure 1.2).89â91 Prior to the invention of hPSC-CM models, human cardiac disease research primarily relied on the use of animal models for in vivo studies and isolated cardiomyocytes or immortalized cell lines for in vitro experiments. Despite their utility, these methods have several disadvantages. hPSC-CM models are a major breakthrough in cardiac disease research since they circumvent critical challenges with using 17 small rodent models and primary cardiomyocyte samples, allowing researchers to investigate disease mechanisms and identify novel therapeutic targets in human-relevant contexts. Rodent models have much smaller heart sizes and exhibit species differences in gene/protein expression which impacts cardiac electrophysiology, including resting heart rates, action potential, and calcium handling properties.92,93 Theoretically, human primary cardiomyocytes are the gold standard cell type for in vitro cardiac disease modelling since they express human genes and proteins and retain patient-specific genetics. In practice, isolation and maintenance of primary cardiomyocytes is challenging due to low harvesting yields, poor cell viability, and instability in long-term culture.94,95 Primary cardiomyocyte samples can be difficult to obtain from healthy controls or patients, especially those with more mild cardiac disorders such as AF, and they cannot be efficiently expanded due to the low proliferative capacity of mature cardiomyocytes.96 In contrast to mature adult cardiomyocytes, hPSCs, including both hESCs and iPSCs, can be expanded due to their self-renewing properties and act as a theoretically infinite source of cells for differentiation into ectoderm, mesoderm, or endoderm lineages. iPSCs are generated through reprogramming of somatic cell types, such as peripheral blood mononuclear cells or skin fibroblasts, by expressing four transcription factors that are expressed in embryonic stem cells (Yamanaka factors: Oct3/4, Sox2, Klf4, and c-Myc; Figure 1.2).88 18 Figure 1.2 Generation of human induced pluripotent stem cells and cardiomyocytes. Human somatic cells are reprogrammed into induced pluripotent stem cells (iPSCs) which are differentiated into iPSC-derived cardiomyocytes for subsequent assays. Created with BioRender.com. iPSC indicates induced pluripotent stem cell. Since iPSC culture does not require the use of embryonic cells, it avoids the legal and ethical issues surrounding the use of hESCs and animal models in research. By mimicking cardiac developmental cues and modulating WNT pathway signalling, hPSCs can be differentiated into hPSC-CMs resembling fetal-like cardiomyocytes that express human genes and proteins. iPSCs and iPSC-CMs derived from patients carrying disease variants of interest can be used in patient-specific models that retain their genetic background. Furthermore, since hPSCs are amenable to genome editing, researchers can model specific variants by inserting disease variants in healthy controls lines or correcting variants in patient lines to generate isogenic controls. hPSC-CMs have been used to model arrhythmias and cardiomyopathies including AF,97 long QT syndrome,98â100 brugada syndrome,101 and DCM,85,102,103 demonstrating their utility across various cardiac diseases. In summary, hPSC-CMs offer several advantages over non-human models or human primary cardiomyocytes and are well suited for investigating cardiac disease and genetics in vitro. 1.4.2 Directed Differentiation of hPSCs to Atrial-Like Cardiomyocytes Atrial and ventricular cardiomyocytes exhibit differences in their electrophysiological and contractile properties. Compared to ventricular cardiomyocytes, atrial cells express lower levels of the potassium current IK1, leading to less negative resting membrane potentials, and 19 preferentially express potassium ion currents IKur and IK,Ach which produces more triangular-shaped action potentials with shorter durations.92 Atrial cardiomyocytes have less developed and heterogeneously distributed t-tubules structures compared to ventricular cardiomyocytes,104 possibly affecting the formation of dyads with L-type calcium channel and ryanodine receptor 2 and contributing to differences in calcium handling. Atrial cardiomyocytes also show lower myofibril densities (50% vs. 89%)105 and express cell type-specific sarcomere proteins involved in contraction, such as myosin light chains, α-myosin heavy chain, and myosin bind proteins C and H-like, which can contribute to different contractile properties like contraction/relaxation rates and kinetics compared to ventricular cardiomyocytes.106â110 These cell type differences highlight the importance of using appropriate models to investigate cardiac diseases or genetic variants, such as TTNtv, that have complex chamber-specific clinical phenotypes. Conventional hPSC-CM small molecule differentiation protocols produce a mixture of ventricular, atrial, and nodal cells with high ventricular abundance.90,111 This limits the applicability of hPSC-CM models in non-ventricular diseases such as AF. Methods to derive atrial-like hPSC-CMs have been recently published,112â115 allowing the generation of atrial and ventricular iPSC-CM models for chamber-specific disease modelling. These atrial differentiation approaches rely on retinoic acid supplementation to direct cardiac progenitors toward an atrial fate. Retinoic acid signalling is essential during embryonic development for the formation of functional hearts. Excess or deficient levels of retinoic acid can lead to morphological defects affecting atria size, ventricular trabeculation, and heart looping, or lethality.116 Atrial and ventricular cardiomyocytes arise from different mesoderm populations and retinoic acid signalling during mesoderm induction is required for atrial specification.113 By supplementing 20 the hPSC-CM differentiation media with retinoic acid shortly after mesoderm induction via WNT modulation, hPSCs can be effectively differentiated to atrial hPSC-CMs with atrial-specific transcriptional and proteomic profiles and functional properties distinct from ventricular hPSC-CMs.114 1.4.3 Engineered Heart Tissue Constructs hPSC-CM models present immature phenotypes compared to adult cardiac tissue that limit their utility. Recent advancements in tissue engineering have resulted in the generation of hPSC-CM-derived three-dimensional models with improved electrophysiological and contractile function. To date, three-dimensional hPSC-CMs, such as engineered heart tissues (EHTs), engineered heart myocardiums, cardiac microtissues, and cardiac biowires, have been employed to model a range of cardiac diseases including AF,117 long QT type 1,118 and TTNtv-related DCM.81,82,84 EHT constructs are created by casting hPSC-CMs in a fibrin-based solution around two flexible silicone posts to form rod-shaped tissues approximately 1 cm in length (Figure 1.3).119 Figure 1.3 Engineered heart tissues. hPSC-CMs are dissociated into single cells and mixed with fibrinogen and thrombin to form fibrin-based three-dimensional constructs. 21 The attachment of EHTs to flexible posts with known physical properties allows contractility to be quantified using imaging-based methods while the EHTs undergo auxotonic contraction. The displacement distance of the silicone posts, post length, radius, and its elastic modulus can be used to calculate contractile force, contraction/relaxation velocities, and contraction/relaxation times which are difficult to assess with hPSC-CM monolayers. Compared to hPSC-CMs, EHTs show organized sarcomeres, aligned cardiomyocytes, early signs of t-tubule formation, and increased expression of ion channel genes, such as CACNA1C, SCN2A, KCNH2, KCNJ5, KCNQ1, RYR2, NCX1.120,121 EHTs exhibit similar action potential shapes, amplitudes, maximum diastolic potentials, and maximal upstroke velocities compared to human left ventricular tissue of non-failing hearts.121 In addition, the ion channel genes SCN5A (INa), KCNQ1 (IKs), and KCNJ2 (IK1) are expressed in EHTs at similar levels to left ventricular tissue, suggesting improved electrophysiology compared to hPSC-CMs. EHTs are also responsive to electrical stimulation, positive and negative chronotropes, and positive and negative inotropes, such as ivabradine, isoproterenol, increased calcium concentration, or verapamil.120 Aside from atrial and ventricular hPSC-CMs, EHTs may be constructed from a mixture of hPSC-CMs, cardiac fibroblasts, and cardiac endothelial cells to create more complex co-culture models that incorporate various cells involved in disease.122 In summary, EHTs exhibit physiologically relevant morphological, electrophysiological, and contractile properties that make them well-suited models for investigating human cardiac diseases. 22 1.5 Hypotheses and objectives 1.5.1 Research Significance AF is the most common clinically diagnosed arrhythmia and has a high economic and healthcare burden. While multiple risk factors such as hypertension and diabetes are known to increase the risk of AF, the exact causes of AF are often unknown. There is a need to better understand genetic factors of arrhythmias, especially in patients without known clinical risk factors, to develop appropriate preventative strategies and treatments. Following the discovery of titin in cardiac and skeletal tissue, several genetic studies have demonstrated strong associations between TTNtv and cardiac diseases, particularly DCM. More recent studies on the clinical phenotypes and outcomes of DCM patients showed TTNtv are associated with increased risk of AF and life-threatening ventricular arrhythmias. Importantly, TTNtv have been linked to early-onset AF and lone AF in the absence of structural disease. These genetic studies provide strong evidence of increased risk of AF in TTNtv carriers. However, data on the interactions between genetic and clinical risk factors on the risk of AF are lacking. Furthermore, mechanistic data linking the findings of these genetic studies to disease pathogenesis are needed. Previous studies have assessed the effects of TTNtv at the cellular/tissue level and demonstrated alterations to sarcomere structure, contractility, and electrophysiology. In addition, titin haploinsufficiency and dominant-negative effects of truncated titin have both been reported. These studies were performed in DCM models using ventricular cells, leaving significant gaps in our understanding of TTNtv in arrhythmias without cardiomyopathy and the atria which has been understudied. This dissertation aims to assess the clinical and cellular effects of TTNtv on atrial and ventricular fibrillation in structurally normal hearts. This work will use a combination of 23 approaches to study the effects of TTNtv, including the analysis of genetic and clinical biobank data and the use of patient-specific atrial and ventricular hPSC-CM and EHT models. This work will investigate the association between loss-of-function titin variants and the risk of AF compared to modifiable risk factors. Data from UK Biobank, a large general population cohort with available genetic data and electronic health information, will be used to study the clinical effects of titin variants. This work will provide information on the risk of AF in patients without DCM or heart failure and the risk of AF in patients with both genetic and clinical risk factors. These findings could be used to improve risk prediction of AF in TTNtv carriers and improve modifiable risk factor management. This work will establish patient iPSC-CM models of a TTNtv identified in an early-onset AF patient and a VF patient to examine cell-type specific effects of the TTNtv on sarcomere structure, contractility, and electrophysiology. Patient-specific atrial and ventricular iPSC-CMs and EHTs will be used to study the TTNtv in physiologically relevant human in vitro models. This work has several important implications. The findings will provide information on the phenotypic and functional impact of TTNtv in the context of arrhythmias without cardiomyopathy which could improve patient risk stratification or inform the design of new therapies. This work could expand our understanding of genotype to phenotype correlations in TTNtv carriers. Lastly, the patient iPSC-CM and EHT models established here could be used to study other TTNtv or other genetic variants linked to arrhythmia. Together, the findings of this work will improve our understanding of TTNtv and the pathogenesis of atrial and ventricular arrhythmias. 24 1.5.2 Hypotheses and Objectives The central objectives of this dissertation are 1) to evaluate the association between titin variants and increased risk of AF compared to modifiable risk factors and 2) to examine the cellular effects of TTNtv identified in atrial and ventricular fibrillation patients with structurally normal hearts. Hypothesis and specific objectives: Hypothesis 1: Loss-of-function titin variants will increase the risk of AF in the general population despite the absence of structural heart disease, increase the risk of AF in individuals with modifiable risk factors, and lead to worse clinical outcomes in AF patients (Chapter 2). Specific objectives: a. To evaluate the risk of incident AF in titin variant carriers without a previous history of DCM or heart failure. b. To evaluate additive effects or interactions between titin variants and modifiable risk factors, including hypertension, diabetes, obesity, and smoking, on the risk of AF. c. To assess the risk of stroke as well as incident DCM, heart failure, and composite cardiovascular outcomes in AF patients with or without titin variants. Hypothesis 2: TTNtv will reduce the expression of full-length titin and lead to the expression of truncated titin, causing abnormal electrophysiology, sarcomere disarray, and contractile defects in patient-specific atrial iPSC-CM models of TTNtv-associated AF (Chapter 3). Specific objectives: 25 a. To establish atrial and ventricular patient-specific iPSC-CM models of a TTNtv identified in an AF patient. b. To evaluate titin protein expression in TTNtv iPSC-CM monolayers compared to isogenic wild-type controls using SDS-agarose gel electrophoresis and Western blot. c. To evaluate the action potential and calcium transient characteristics in TTNtv iPSC-CM monolayers compared to isogenic wild-type controls under baseline conditions. d. To assess the frequency of arrhythmogenic phenotypes induced by dynamic rapid pacing in TTNtv iPSC-CM monolayers compared to isogenic wild-type controls. e. To evaluate the sarcomere organization levels of TTNtv iPSC-CM monolayers compared to isogenic wild-type controls. f. To measure the contractility of TTNtv EHTs compared to isogenic wild-type controls under baseline conditions. g. To identify differential responses to the TTNtv in atrial cells compared to ventricular cells. Hypothesis 3: TTNtv will lead to contractile defects, abnormal electrophysiology, and impaired β-adrenergic response in patient-specific ventricular iPSC-CM models of TTNtv-associated VF (Chapter 4). a. To establish atrial and ventricular patient-specific iPSC-CM models of a TTNtv identified in a VF patient. b. To measure the contractility of TTNtv iPSC-CM monolayers compared to isogenic wild-type controls under baseline conditions and during β-adrenergic stimulation. 26 c. To evaluate the action potential and calcium transient characteristics in TTNtv iPSC-CM monolayers compared to isogenic wild-type controls under baseline conditions. d. To assess the frequency of arrhythmogenic phenotypes induced by dynamic rapid pacing in TTNtv iPSC-CM monolayers compared to isogenic wild-type controls. e. To evaluate the action potential and calcium transient characteristics in TTNtv iPSC-CMs during β-adrenergic stimulation compared to isogenic wild-type controls. f. To identify differential responses to the TTNtv in atrial cells compared to ventricular cells. 27 Chapter 2: The Interplay Between Titin, Polygenic Risk, and Modifiable Cardiovascular Risk Factors in Atrial Fibrillation 2.1 Chapter Summary Background: Common and rare variants, including those in the cardiac structural gene titin (TTN), have been implicated in the risk of developing atrial fibrillation (AF). However, the effect of genetic variants on risk of AF compared to established modifiable risk factors is unclear. The objective of this study was to evaluate the risk of AF and associated cardiovascular complications in TTN variant carriers and examine interactions between TTN variants or common variants and modifiable AF risk factors. Methods: We used whole exome sequencing data of 49,881 individuals and genotyping data of 408,572 individuals from UK Biobank to examine the associations of TTN variants, polygenic risk, and four risk factors (hypertension, diabetes, obesity, and smoking) with AF. Adjusted hazard ratios (aHR) were calculated using Cox proportional hazards models. Results: TTN variant carrier status was associated with a higher risk of AF (aHR, 2.10 [95% CI, 1.59â2.79]; P = 2.54x10-7) and higher risk of DCM in AF patients (aHR, 10.39 [95% CI, 5.31â20.33]; P = 8.37x10-12). We identified additive effects between TTN variants and polygenic risk with hypertension, diabetes, obesity, and smoking on the risk of AF. Conclusion: Genetic and modifiable cardiovascular risk factors contribute to the probability of developing AF. Our findings highlight the potential utility of incorporating data from targeted 28 sequencing or genotyping of common variants to further inform AF risk stratification and aggressive management of modifiable cardiovascular risk factors. 2.2 Introduction Atrial fibrillation (AF) is the most common arrhythmia worldwide with an incidence that is anticipated to increase over time.123 AF is associated with a poorer quality of life and an increased risk of ischemic stroke, heart failure (HF), and death.55â57 The management of AF imposes a significant economic and healthcare burden.124 As a result, substantial efforts have been made to identify the mechanisms and risk factors involved in the pathogenesis and maintenance of AF to improve patient outcomes. Genetic association studies have implicated common and rare genetic variants in the risk of developing AF.125,126 Of note, rare variant association studies have demonstrated a link between variants in titin (TTN) and early-onset AF as well as lone AF (cases where other cardiovascular diseases or known risk factors of AF are absent).35,38 Furthermore, variants in TTN are a well-established cause of dilated cardiomyopathy (DCM) and lead to increased risk of HF and death.44 However, less is known about the clinical implications of TTN variants (TTNv) on (1) pre-existing AF, (2) the risk of developing AF with and without a HF/DCM history and (3) the interplay between TTN and modifiable risk factors such as hypertension.62 Aside from rare variants such as those in TTN, polygenic factors involving variants in multiple genes can also impact the risk of AF and polygenic risk scores (PRS) for AF have been developed to assess the effects of multiple common variants on AF risk.63,127 However, few studies have investigated the combined contributions of genetic and clinical factors on the development of AF. 29 Here, we analyzed genotyping data, whole exome sequencing data and medical records of participants in UK Biobank to evaluate TTNv as a risk factor of AF and AF-related cardiovascular diseases, as well as interactions between TTNv, polygenic risk score, and four potentially modifiable risk factors of AF â hypertension, diabetes, obesity, and smoking status. 2.3 Methods 2.3.1 UK Biobank Cohort UK Biobank is a large prospective cohort study of over 500,000 participants with genotyping, exome, and health-related data.128 Participants aged 40 to 69 were recruited between 2006 and 2010. We utilized whole exome sequencing data of 49,881 participants129 as well as genotyping data of 408,572 participants of white British ancestry for this study. Participants with missing genotype measurements, mismatched genetic and reported sex, or requested withdrawal from the UK Biobank study were excluded. This study was approved by UK Biobank and the Clinical Research Ethics Board at the University of British Columbia (H18-02181). All participants provided written informed consent. 2.3.2 Definition of Phenotypic Disease and Procedures Disease events and operational procedures were identified from patient electronic health records of hospital admissions before and after enrolment in the UK Biobank study, automated diagnoses from 12-lead resting electrocardiograms, death registry data, and self-reported illnesses or procedures that occurred prior to enrolment. Self-reported events with unknown dates were excluded. Diseases and procedures from health records were defined by International 30 Classification of Diseases, 10th Revision (ICD-10) and Office of Population Censuses and Surveys Classification of Interventions and Procedures, 4th Revision (OPCS-4) codes (Appendix Table A.1). AF was defined as either AF or atrial flutter, and a composite cardiovascular disease (CVD) event was defined as the occurrence of HF, stroke, or all-cause death. Participants were censored at death, lost-to-follow-up, or the last date of follow-up (May 31, 2020), whichever came first. CHA2DS2-VASc scores were calculated using data upon entry into UK Biobank. Body-mass-index was calculated from height and weight measurements, and we defined obesity as body-mass-index â¥ 30 kg/m2. Participants with missing body-mass-index were excluded from this analysis. Smoking status of participants was obtained at enrolment. Participants were categorized as current smokers if they smoked on most days or occasionally while participants who were previous smokers or never smoked were categorized as non-current smokers. Participants who did not know their smoking status, did not answer, or had missing information in this field were excluded from this analysis. Combined genetic and modifiable risk factor analyses were restricted to participants with complete information on all four risk factors. 2.3.3 Identification of TTNv in UK Biobank Participants Sample and variant QC measures were performed as previously described.15 Additional variant filtering procedures are described in Appendix Table A.2. Exome functionally equivalent variant call files were annotated with SnpEff against the GRCh38 reference genome.130 dbNSFP and ClinVar annotations were added using SnpSift.131â134 Analysis was restricted to variants with high putative deleteriousness as assessed by SnpEff, including variants predicted to cause protein loss-of-function, disrupt protein-protein interactions, or protein structural interactions (Appendix 31 Table A.3; Appendix Figure A.1). Only variants found in TTN exons with percentage spliced-in (PSI) values â¥ 90% were included in analyses and are referred to as TTN variants (TTNv).43 2.3.4 Calculation of Polygenic Risk Score for AF Sample and variant QC measures were performed as previously described.128 Additional variant filtering procedures are described in Appendix Table A.2. We calculated weighted AF PRS for 408,572 participants of white British ancestry with genotyping data available. PRS were calculated using 6,539,979 out of 6,730,541 potential variants63 (http://kp4cd.org/dataset_downloads/mi) and the weighted formula Σ [βx * SNVx], where βx is the effect size and SNVx is the number of effect alleles at that locus (0, 1, or 2), with PLINK version 1.9.135 PRS were standardized through inverse normal transformation (mean of zero and standard deviation of one) and converted to percentiles. Participants were assigned to high PRS or low PRS groups using the 95th percentile as the cut-off. 2.3.5 Statistical Analysis Data were analyzed using R version 3.6.0 (www.r-project.org). Two-sided P-values with P < 0.05 were used to indicate statistical significance. Participant characteristics were compared using the Wilcoxon rank sum test for continuous variables and the Fisherâs exact test for categorial variables. Survival analyses were performed using the R package âSurvivalâ version 3.1-8. Hazard ratios were calculated using a stratified Cox proportional hazards (PH) model allowing different baseline hazards for males or females and adjusted for genotype measurement batch, first four principal components of ancestry, hypertension, diabetes, obesity, and current smoking. Cox PH models to assess risk of AF were additionally adjusted for DCM and HF while 32 models to assess risk of DCM were adjusted for AF and HF. Cox PH models to assess risk of HF or composite cardiovascular outcomes were additionally adjusted for DCM. For time-to-event analyses where time zero is the time at enrolment or earliest known AF event, Cox PH models were additionally adjusted for age of enrolment in UK Biobank. Cox PH models in PRS analyses were stratified by sex and UK Biobank assessment centre location and adjusted for age, genotype measurement batch, and the first four principal components of ancestry. Interactions between PRS and each risk factor were tested using the standardized PRS modeled as a continuous variable and the risk factor modeled as a categorical variable. 2.4 Results 2.4.1 UK Biobank Participant Characteristics We analyzed exome sequence data of 49,881 individuals and identified 417 unique variants in TTN in 874 (1.75%) individuals from UK Biobank. We removed 79 participants with missing genotype data, mismatched genetic and reported sex, or requested withdrawal from the UK Biobank study. After excluding variants in exons with PSI < 90% (189/417 variants excluded), 228 distinct TTNv with PSI â¥ 90% were identified across 337 (0.68%) participants. There were 179 loss-of-function (LOF) TTNv defined as frameshift variants, splice site variants, or nonsense variants identified across 228 (0.46%) participants while 49 TTNv predicted to interrupt protein contacts or structures were identified across 109 (0.22%) participants. Participant characteristics, including diagnoses and procedures during the follow-up period, stratified by TTNv status are shown in Table 2.1. 33 Table 2.1 Participant characteristics, without or with TTNv. Characteristic Without TTNv (n = 49545) With TTNv (n = 337) P-value Female sex 27022 (54.5%) 188 (55.8%) 0.66 Age at recruitment 56.6 ± 8.02 56.9 ± 8.13 0.96 Atrial fibrillation 3022 (6.1%) 51 (15.1%) <0.001 Angina 3359 (6.8%) 34 (10.1%) 0.022 Diabetes mellitus 4185 (8.4%) 38 (11.3%) 0.076 DCM 111 (0.2%) 12 (3.6%) <0.001 Heart failure 1191 (2.4%) 23 (6.8%) <0.001 Hypertension 17563 (35.4%) 117 (34.7%) 0.82 Myocardial infarction 1784 (3.6%) 9 (2.7%) 0.46 Stroke 1807 (3.6%) 13 (3.9%) 0.77 Thrombosis event 1374 (2.8%) 7 (2.1%) 0.62 Revascularization 2217 (4.5%) 12 (3.6%) 0.51 PVD 699 (1.4%) 3 (0.9%) 0.64 Values include events during follow-up and are presented as n (%) or mean ± SD. DCM indicates dilated cardiomyopathy; PVD, peripheral vascular disease; TTNv, titin variant. 34 The prevalence of AF, DCM, and HF were significantly greater in TTNv carriers. Participant characteristics stratified by AF status or by AF and TTNv carrier status are shown in Appendix Table A.4 and Appendix Table A.5, respectively. 2.4.2 TTNv and Risk of AF or Other Cardiovascular Outcomes The risk of AF and DCM were significantly greater in TTNv carriers compared to non-carriers, whereas the risk of HF or composite CVD event was not (Figure 2.1). Figure 2.1 Cumulative incidence of AF, HF, DCM, and composite outcomes. 35 Incidence of A, AF, B, HF, C, DCM, and D, composite cardiovascular disease events defined as HF, stroke, or death. The x-axis shows age in years where birth is time zero. AF indicates atrial fibrillation; CCE, composite cardiovascular disease event; DCM, dilated cardiomyopathy; HF, heart failure; TTNv, titin variants. The adjusted hazard ratio (aHR) for AF among TTNv carriers was 2.10 (95% CI, 1.59â2.79; P = 2.54x10-7) and 7.13 for DCM (95% CI, 3.88â13.11; P = 2.66x10-10). The aHRs for HF and a composite CVD event were 1.33 (95% CI, 0.87â2.04; P = 0.18) and 1.15 (95% CI, 0.86â1.54; P = 0.33), respectively. Since TTNv are associated with a higher risk of DCM, it is possible that TTNv carriers develop AF secondary to DCM and associated cardiac remodelling. To determine if the risk of AF in TTNv carriers is independent of DCM, we excluded participants with DCM and found that the risk of isolated AF remained statistically significant with an aHR of 2.21 (95% CI, 1.61â3.01; P = 6.98x10-7). The presence of related participants with familial AF linked to genes other than TTN may introduce bias. Therefore, we also assessed the association between TTNv and risk of AF in a subset of unrelated individuals. When participants with at least one first degree relative or ten or more third-degree relatives were removed from analyses, the risk of AF remained significantly elevated in TTNv carriers (aHR, 2.26 [95% CI, 1.64â3.11]; P = 5.26x10-7). Comparable results were observed when we assessed the risks of these diagnoses after enrolment among previously disease-free individuals (Appendix Table A.6). Furthermore, the risks of AF and DCM remained significant with larger aHRs when analyses were restricted to LOF TTNv only (Appendix Table A.6). 36 2.4.3 TTNv and Risk of AF-Associated Cardiovascular Outcomes We next assessed the risk of cardiovascular events in individuals with AF, with or without pathogenic variants in TTN. TTNv status was associated with a significantly greater risk of DCM but not of HF or composite CVD events (HF, stroke, and/or death) in these participants (Figure 2.2). 37 Figure 2.2 Cumulative incidence of DCM, HF, and composite outcomes in AF patients. 38 Incidence of A, DCM B, HF, and C, composite cardiovascular disease events defined as HF, stroke, or death. The x-axis shows age in years where birth is time zero. AF indicates atrial fibrillation; CCE, composite cardiovascular disease event; DCM, dilated cardiomyopathy; HF, heart failure; TTNv, titin variants. The aHR for DCM among TTNv carriers was 10.39 (95% CI, 5.31â20.33; P = 8.37x10-12) and for HF was 1.40 (95% CI, 0.86â2.30; P = 0.18). The aHR for a composite CVD event was 1.23 (95% CI, 0.81â1.85; P = 0.33) in TTNv carriers compared to non-carriers. To further assess if TTNv contribute to greater risk of stroke in participants with AF, we stratified participants by TTNv status and CHA2DS2-VASc score groups (Appendix Table A.7). We observed a numerically greater rate of stroke in TTNv carriers than non-carriers in the high stroke risk group (score â¥ 2) that did not reach statistical significance (stroke rates: 1.63 vs. 1.11; P = 0.59). In the low/moderate stroke risk group (score < 2), the rate of stroke per 100 person-years was 0.41 in TTNv carriers and 0.66 in non-carriers (P > 1). We also examined the risk of DCM, HF, or composite CVD events occurring after the initial diagnosis of AF among TTNv carriers and non-carriers (Appendix Figure A.2). There was a significant association between TTNv and risk of DCM after AF (aHR, 11.39 [95% CI, 5.10â25.45]; P = 3.04x10-9) and when 6- or 12-month blanking periods following initial AF diagnosis were imposed to account for the possibility of a concurrent AF/DCM diagnosis (Appendix Table A.8). TTNv was not significantly associated with risk of HF after AF (aHR, 1.38 [95% CI, 0.77â 39 2.46]; P = 0.28) nor a composite CVD event after AF (aHR, 1.29 [95% CI, 0.81â2.06]; P = 0.29). 2.4.4 TTNv and Modifiable Risk Factors of AF Hypertension, diabetes, obesity, and smoking are well-established modifiable risk factors of AF. These factors are associated with increased risk of AF in the UK Biobank cohort (Appendix Table A.9). We assessed the risk of AF in TTNv carriers or non-carriers, with or without hypertension, using participants with neither as the reference group (Figure 2.3A and 2.3E). 40 Figure 2.3 TTNv and modifiable risk factors of AF. 41 Incidence of AF stratified by TTNv carrier status and A, HTN, B, DM, C, OB, D, CS status since enrolment. The x-axis shows time to first AF event in years where time zero is the time at enrolment in UK Biobank. Adjusted hazard ratios (95% confidence intervals) for AF stratified by TTNv status and E, HTN, F, DM, G, OB, H, CS status. Log-rank trend tests were statistically significant (P < 0.0001 for HTN, DM, and OB, and P = 0.0001 for CS). AF indicates atrial fibrillation; CS, current smoker; DM, diabetes mellitus; HTN, hypertension; OB, obesity; TTNv, titin variants. Hypertension and TTNv status had a statistically significant, additive effect on the risk of AF (log-rank trend test P < 0.0001), with no evidence of interaction (P = 0.21). The aHR of AF was greatest among individuals with both TTNv and hypertension (aHR, 3.00 [95% CI, 1.80â5.02]; P = 2.66x10-5). We performed a similar analysis to assess the effect of TTNv in individuals with or without diabetes (Figure 2.3B and 2.3F) and observed an additive effect of TTNv and diabetes on risk of AF (log-rank trend test P < 0.0001), with no interaction (P = 0.69). We similarly observed additive effects between TTNv and obesity (Figure 2.3C and 2.3G) and TTNv and smoking (Figure 2.3D and 2.3H) on the risk of developing AF (log-rank trend tests P < 0.0001 and P = 0.0001), with no evidence of interactions (P = 0.74 and P = 0.15). 2.4.5 Polygenic Score and Modifiable Risk Factors of AF To assess the possible interaction between common single nucleotide polymorphisms and modifiable risk factors of AF, we calculated AF PRS for 408,572 participants in the UK Biobank study. The aHR for AF was 1.46 (95% CI, 1.45â1.48; P < 2x10-16) per standard deviation unit increase in PRS. Relative to participants with a low PRS (< 95th percentile), the aHR for AF was 42 2.42 (95% CI, 2.33â2.52; P < 2x10-16) for participants in the high PRS group (Appendix Figure A.3). We detected additive effects between PRS and modifiable risk factors on the risk of AF with no evidence of positive interactions. Relative to participants with a low PRS or without a risk factor, the risk of AF was significantly greater in participants with a high PRS and the presence of a modifiable risk factor (Figure 2.4). 43 Figure 2.4 PRS and modifiable risk factors of AF. 44 Incidence of AF stratified by PRS group and A, HTN, B, DM, C, OB, D, CS status since enrolment. The x-axis shows time to first AF event in years where time zero is the time at enrolment in UK Biobank. Adjusted hazard ratios (95% confidence intervals) for AF stratified by PRS group and E, HTN, F, DM, G, OB, H CS status. Log-rank trend tests were statistically significant (P < 0.0001). AF indicates atrial fibrillation; CS, current smoker; DM, diabetes mellitus; HTN, hypertension; OB, obesity; PRS, polygenic risk score. To further assess the contributions of PRS and modifiable risk factors on AF risk, we grouped participants into four risk groups based on the number of modifiable risk factors present: none, low (one risk factor), intermediate (two risk factors), and high (three or four risk factors). Relative to participants with low PRS and zero modifiable risk factors, high PRS was associated with greater risk of AF within each risk group (Appendix Table A.10; Appendix Figure A.4). The aHR for AF among participants with high PRS and zero modifiable risk factors (aHR, 2.50 [95% CI, 2.26â2.76]; P < 2x10-16) was lower than that of participants in the low PRS and intermediate risk group (aHR, 3.40 [95% CI, 3.26â3.55]; P < 2x10-16) or high risk group (aHR, 5.03 [95% CI, 4.78â5.30]; P < 2x10-16). 2.5 Discussion Here we investigated the role of TTNv as a risk factor of AF and related cardiovascular complications in individuals from the UK Biobank exome sequencing cohort.129 We corroborated the reported association between TTNv and risk of AF and DCM. In addition, the major findings of this study are that TTNv and polygenic risk exhibit additive effects with clinical risk factors for AF (hypertension, diabetes, obesity, and smoking), indicating that genetic 45 factors contribute to the development of AF beyond the effects of known modifiable AF risk factors. These findings highlight the critical importance of risk factor management, even in patients at high genetic risk for AF. We found that the presence of a TTNv was associated with a greater risk of AF and DCM. Our results are consistent with those from a recent study investigating TTNv in asymptomatic individuals in UK Biobank.44 In that study, TTNv were associated with increased risk of cardiovascular diseases, including AF, HF, DCM, all-cause mortality, or a composite of these events. TTNv are also a well-established cause of DCM and are present in approximately 15% of DCM cases.43 A study investigating TTNv and arrhythmia in DCM patients found an association with the development of persistent AF.37 Therefore, a possible explanation for the increased risk among TTNv carriers may be due to the development of AF after DCM and cardiac remodelling. We observed an increase in the risk of AF among TTNv carriers even after excluding participants with DCM, suggesting that TTNv may contribute to AF independent of DCM. However, this does not exclude the possibility that subclinical structural remodelling due to TTNv is contributing to the development of AF. Relatively little is known about the clinical consequences of carrying TTNv in the context of AF. In a subset of participants who developed AF, we found a significant association between TTNv status and a greater risk of DCM, suggesting potential benefits of close longitudinal cardiac follow-up such as monitoring for DCM in TTNv carriers and first-degree relatives who are potential carriers of TTNv. However, TTNv status was not significantly associated with increased risk of HF, a composite CVD event, death, or stroke. We did observe a statistically non- 46 significant but numerically greater rate of stroke in TTNv carriers with CHA2DS2-VASc score â¥ 2, but the stroke rates are lower than the expected stroke rates of AF patients in the high stroke risk CHA2DS2-VASc group136,137 and only one stroke event occurred in AF patients with TTNv and CHA2DS2-VASc score < 2. The lower observed stroke rates may be due to the relatively healthy population in UK Biobank.138 AF has been linked to several risk factors that could be potential targets in early preventative strategies.62,139,140 However, less is known about how genetic and clinical risk factors interact to contribute to AF risk. While the study was underpowered to detect significant interactions between TTNv and the modifiable risk factors, we found that the presence of TTNv further increased risk beyond established clinical risk factors for AF. A recent study investigating polygenic risk and clinical risk factor burden demonstrated that both contribute substantially to lifetime risk of AF.127 Here we show additive effects between PRS and individual risk factors in relation to AF. We also found that the risk of AF was lower in participants with high genetic risk and zero risk factors compared to those with low genetic risk and multiple risk factors, suggesting that risk factor management is important even in the presence of high genetic risk. These findings indicate that individuals with TTNv or high polygenic risk and first-degree relatives may benefit from close attention to AF risk factor management through medications or lifestyle changes such as increasing physical activity, quitting smoking, adopting a healthier diet, or receiving educational advice on lifestyle management in order to reduce the risk of AF.62,141,142 Furthermore, these findings highlight the potential benefits of incorporating genetic data for further refinement of AF risk stratification, early implementation of preventative strategies, and more personalized management of AF in at-risk individuals. 47 This study has limitations that should be considered. The definition of diseases and procedures relied on diagnosis codes and self-reported information. The prevalence of disease phenotypes such as DCM or stroke is lower compared to other study cohorts and is likely attributed to the âhealthy volunteerâ effect that has been previously reported with UK Biobank.138 We were unable to investigate the interaction between genetic factors and other clinical risk factors such as hyperthyroidism or valvular heart disease due to the limited number of participants with these conditions. The study was not sufficiently powered to assess interactions between TTNv and modifiable risk factors due to the lower disease prevalence and lower frequency of TTNv carriers within this study (Appendix Table A.11). Most participants in the UK Biobank study were of white British/European ancestry and the PRS analyses were restricted to participants of white British ancestry. While we did not exclude non-white or non-European individuals from the exome sequencing cohort, the results from this study regarding TTNv and disease risk may be less relevant to other populations. Additional studies investigating TTNv and polygenic risk in larger and more ethnically diverse cohorts are needed to assess the reproducibility and applicability of these findings. In conclusion, we identified that TTNv increases the risk of AF and DCM after AF. Importantly, we provide evidence of additive effects between TTNv and hypertension, diabetes, obesity, and smoking status as well as between polygenic risk and these modifiable factors on the risk of AF. These findings provide new insight into TTNv as a risk factor of AF and support the integration of genetic risk assessment with traditional clinical factors for patient risk stratification and 48 identification of individuals that may benefit from early preventative strategies targeting modifiable risk factors of AF. 49 Chapter 3: Atrial Fibrillation Related Titin Truncation is Associated with Atrial Myopathy in Patient-derived iPSC Disease Models 3.1 Chapter Summary Background: Protein truncating mutations in the titin gene are associated with increased risk of atrial fibrillation (AF). However, little is known regarding the underlying pathophysiology. Methods: We identified a heterozygous titin truncating variant (TTNtv) in a patient with unexplained early-onset AF and normal ventricular function. We generated patient-specific atrial- and ventricular-like induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs) and engineered heart tissue (EHT) to evaluate the impact of the TTNtv on electrophysiology, sarcomere structure, contractility, and gene expression. Results: We demonstrate that the TTNtv increases susceptibility to pacing-induced arrhythmia, promotes sarcomere disorganization, and reduces contractile force in atrial iPSC-CMs compared to their CRISPR/Cas9-corrected isogenic controls. In ventricular iPSC-CMs, this variant was associated with abnormal electrophysiology and sarcomere organization without a reduction in contractile force compared to their isogenic controls. RNA-seq revealed an upregulation of cell adhesion and extracellular matrix genes in the presence of the TTNtv for both atrial and ventricular EHTs. Conclusion: In a patient with unexplained AF, iPSC-CMs with a TTNtv showed structural and electrophysiological abnormalities in both atrial and ventricular models, while only atrial EHTs 50 demonstrated reduced contractility. The observed chamber-specific effect suggests that structural disorganization and reduced contractile function may be associated with atrial myopathy in the presence of truncated titin. 3.2 Introduction Atrial fibrillation (AF) is the most common clinical arrhythmia globally and is associated with significant morbidity and increased mortality.56,57,123 With advancements in our understanding of the genetic architecture of AF, loss-of-function truncations in the gene encoding titin (TTNtv) have been implicated in both patients with and without acquired risk factors.35,38 Titin is a key structural component of the sarcomere and has also been associated with dilated cardiomyopathy (DCM), arrhythmogenic cardiomyopathy, and ventricular arrhythmia.37,39,43 While recent studies of TTNtv have focused on ventricular cells, the identification of populations with unexplained AF, TTNtv, and structurally normal hearts suggests that TTNtv may have atrial-specific pathophysiologic consequences. In this study, we investigated the cellular effects of an AF-associated TTNtv that was identified in a patient with early-onset AF in the absence of structural heart disease using atrial and ventricular patient induced pluripotent stem cell-derived cardiomyocytes (iPSC-CMs), CRISPR/Cas9 genome editing, and engineered heart tissue (EHT). We demonstrate that TTNtv increases susceptibility to arrhythmia, alters sarcomere organization, decreases atrial contractility, and leads to transcriptional changes that implicate cardiac remodelling as an underlying contributor of arrhythmogenesis by TTNtv in vitro. 51 3.3 Methods 3.3.1 Study Approval This study was approved by the University of British Columbia Childrenâs and Womenâs Research Ethics Board (H18-01465). The PERSONALIZE AF biobank was approved by the University of British Columbia Clinical Research Ethics Board (H15-02970). All individuals provided written informed consent. 3.3.2 Patient Sequencing and Titin Variant Identification Participant recruitment was completed through the PERSONALIZE AF biobank in Vancouver, Canada.143 Whole exome sequencing and variant identification was performed as previously described.143 Briefly, genomic DNA was extracted using a Puregene DNA Blood Kit (Qiagen). Sequencing was performed using the SeqCap EZ Human Exome Library (Roche) and a NovaSeq 6000 sequencer (Illumina). Variants were filtered to those with a minor allele frequency <0.1% or missing in gnomAD. Variants with a Combined Annotation Dependent Depletion Phred score >20 were selected and additional variant annotations were performed using dbNSFP and/or Gemini. Only variants predicted to lead to protein loss-of-function, such as stop-gain, splice donor/acceptor, or frameshift variants, were selected. Targeted clinical genetic testing was performed by Blueprint Genetics. Mutation carrier status was further determined through targeted Sanger genotyping (Azenta/GENEWIZ). 3.3.3 iPSC Reprogramming and Characterization Peripheral blood mononuclear cells were isolated from patient blood samples and reprogrammed to iPSCs using the CytoTune-iPS 2.0 Sendai Reprogramming Kit (Thermo Fisher Scientific). 52 Genetic abnormalities were evaluated using the hPSC Genetic Analysis Kit (Stemcell Technologies) and pluripotency was assessed by immunofluorescent staining of TRA-1-60 and NANOG through confocal microscopy. Briefly, iPSCs were fixed with 4% paraformaldehyde for 20min at room temperature, permeabilized with 0.2% Triton X-100 in DPBS without Mg2+/Ca2+ for 15min at room temperature, and blocked overnight in 5% goat serum, 0.2% Triton X-100 in DPBS without Mg2+/Ca2+ at 4°C. Cells were stained with mouse anti-TRA-1-60 (Abcam; catalog ab16288; RRID:AB_778563) and rabbit anti-NANOG (Abcam; catalog ab21624; RRID:AB_446437) primary antibodies then incubated in goat anti-mouse AF488 (Abcam; catalog ab150113; RRID:AB_2576208) and goat anti-rabbit AF647 (Thermo Fisher Scientific; catalog A-21245; RRID:AB_2535813) secondary antibodies for 1hr at room temperature. Stained coverslips were mounted on glass slides using VectaShield Antifade Mounting Media with DAPI (Vector Laboratories) and sealed with clear nail polish. A Zeiss LSM 880 Confocal Microscope with a 20X objective and Zen 2.3 SP1 FP1 v14.0.9.201 were used to obtain maximum intensity projections of z-stack images. iPSCs were maintained in mTeSR1 media (Stemcell Technologies) on hESC-qualified Matrigel (Corning) or Geltrex (Thermo Fisher Scientific). 3.3.4 CRISPR/Cas9 Genome Editing CRISPR/Cas9 editing was performed using techniques adapted from published methods.144 We used CRISPR/Cas9 homology-directed repair to correct the heterozygous WT/TTNtv to WT/WT. Custom gRNA sequence design and off-target prediction were performed using CRISPOR v4.97145 and the CRISPR/Cas9 gRNA Design Checker (Integrated DNA Technologies). gRNA and 127-bp DNA donor template sequences were custom ordered from 53 Integrated DNA Technologies (Appendix Table B.1). The Cas9 nuclease and gRNA duplex (dual-tracrRNA:crRNA) were delivered as a ribonucleoprotein complex with the DNA donor template using a Nucleofector 2b Device and the Human Stem Cell Nucleofector Kit 1 (Lonza) following manufacturerâs instructions. Alt-R HDR Enhancer V1 was used to improve editing efficiency (Appendix Table B.2). Colonies were manually isolated, and genomic DNA were extracted using QuickExtract DNA Extraction Solution (Epicentre). PCR amplification products of the mutation site were used in restriction fragment length polymorphism assays with the AluI restriction enzyme (NEB) to screen for possible edited clones. Genotypes were confirmed through Sanger sequencing of the purified PCR products by Azenta/GENEWIZ. Off-target editing was assessed through PCR amplification and Sanger sequencing of the top five predicted sites (Appendix Table B.3). Heterozygous WT/TTNtv iPSCs that underwent the CRISPR/Cas9 editing process but retained the mutation were used as the isogenic control. 3.3.5 iPSC-CM Differentiation iPSCs were differentiated into ventricular-like iPSC-CMs through temporal modulation of WNT signalling.89,91,144 iPSCs were treated with CHIR99021 (Stemcell Technologies) for 24hrs (day 0-1) in RPMI 1640 with B27 minus insulin (Thermo Fisher Scientific) followed by IWP-2 (R&D Systems) for 48hrs (day 1-3). Media was refreshed every two days until day 7 and switched to RPMI 1640 with B27 with insulin. At day 10, iPSC-CMs underwent metabolic selection using RPMI 1640 with B27 without D-glucose (Thermo Fisher Scientific) supplemented with sodium L-lactate (Sigma-Aldrich) for 4-6 days. Following metabolic selection, iPSC-CMs were maintained in RPMI with B27 media for subsequent experiments. Atrial-like iPSC-CMs were generated as described above except RPMI 1640 with B27 minus insulin media was 54 supplemented with 0.75µM all-trans retinoic acid (Sigma-Aldrich) for 48hrs during days 3-5 of differentiation.114,115 Experiments were conducted by using iPSC-CMs >30 days in culture. 3.3.6 Flow Cytometry iPSC-CMs were dissociated into single cells by incubating in RPMI 1640 supplemented with 0.5U/ml Liberase TH (Sigma-Aldrich), 50 U/ml DNaseI (Sigma-Aldrich), and TrypLE (Thermo Fisher Scientific) at 37°C. Cells were fixed with 2% paraformaldehyde at room temperature and permeabilized with 0.5% Saponin, 2% FBS in DPBS without Mg2+/Ca2+. iPSC-CMs were stained with BV421-conjugated anti-cTnT antibody (BD Biosciences; catalog 565618; RRID:AB_2739306) and rabbit anti-MLC2v antibody (Abcam; catalog ab79935; RRID:AB_1952220) for 1hr then stained with an AF647-conjugated goat anti-rabbit secondary antibody (Thermo Fisher Scientific; catalog A-21245; RRID:AB_2535813) for 1hr. iPSCs were dissociated using TrypLE at 37°C and stained in parallel to serve as a negative cell type control for gating. Stained samples were run on a Gallios Flow Cytometer (Beckman Coulter) and analyzed using the Kaluza Analysis Software v2.1 (Beckman Coulter). 3.3.7 RT-qPCR RNA was extracted using an Illustra RNAspin Mini Isolation Kit (Cytiva). cDNA synthesis was performed using a cDNA Synthesis Kit (Applied Biological Materials) and then combined with primers (Integrated DNA Technologies; Appendix Table B.4) and PowerUp SYBR Green Master Mix. qPCR was performed using a QuantStudio 6 Pro Real-Time PCR System and analyzed using the Design and Analysis Software v2.4.3. Relative gene expression was calculated using the ÎCT method with GAPDH expression as the reference. 55 3.3.8 Optical Mapping of Voltage and Calcium Transients iPSC-CMs were seeded on Matrigel-coated plates at a seeding density of 2.6x105 cells/cm2. iPSC-CMs were co-stained with FluoVolt (Thermo Fisher Technologies) and Calbryte 630 AM (AAT Bioquest) in RPMI 1640 media supplemented with 0.02% pluronic F-127 (Thermo Fisher Technologies) and 1.25 μM probenecid (AAT Bioquest). iPSC-CMs were imaged in a stage-top incubator at 37°C and 20 second recordings were acquired at 10X, 200 frames per second using a Nikon Ti2-E microscope equipped with a pco.edge 4.2Q High QE sCMOS camera. Recordings for maximal upstroke velocity analysis were acquired at 1000 frames per second. Electrical stimulation was applied using carbon Pacing Electrodes (EHT Technologies) attached to a custom-built stimulator (biphasic 5ms pulse). The initial pacing frequency was set to a frequency closest to the spontaneous beat rate then increased stepwise by increments of 100ms per recording. The experiment was terminated when an arrhythmogenic event was observed or until the pacing frequency reached a cycle length of 200ms in atrial iPSC-CMs and 300ms in ventricular iPSC-CMs, whichever came first. An arrhythmogenic event was defined as the presence of early-after depolarizations, delayed-after depolarizations, alternans, missing/extra beats, or irregular rhythms in the voltage and/or calcium transient recording. Data were processed and analyzed using a custom-built Python analysis script. Electrophysiological parameters assessed included beat rate, action potential durations (80% repolarization, 50% repolarization, and 30% repolarization), calcium transient durations (80% repolarization, 50% repolarization, and 30% repolarization), and maximal upstroke velocity. Beat rate-correction was calculated using Bazettâs method: 56 ðð´ðð· àµ ð´ðð·à¶§ 60ðµððð¡ ððð¡ð 3.3.9 Sarcomere Organization Analysis iPSC-CMs were seeded at 30,000 cells per well and cultured for 21 days on Matrigel-coated micropatterned coverslips (Curi Bio) that have been demonstrated to improve cardiomyocyte maturity and sarcomere alignment.146 iPSC-CMs were fixed, permeabilized, and blocked as described above for immunofluorescence staining of iPSCs. iPSC-CMs were stained with mouse anti-α-actinin (Sigma-Aldrich; catalog A7811; RRID:AB_476766) and rabbit anti-titin M-line (MyoMedix; catalog TTN-9; RRID:AB_2734750) primary antibodies overnight at 4°C then incubated in goat anti-mouse AF488 (Abcam; catalog ab150113; RRID:AB_2576208) and goat anti-rabbit AF647 (Thermo Fisher Scientific; catalog A-21245; RRID:AB_2535813) secondaries for 1hr at room temperature. Stained coverslips were mounted on glass slides using VectaShield Antifade Mounting Media with DAPI and sealed with clear nail polish. Images were acquired with a 20X objective at 3X zoom using a Zeiss LSM 880 Confocal Microscope equipped with an AiryScan detector and Zen 2.3 SP1 FP1 v14.0.9.201. Images were acquired while blinded to the genotype of the iPSC-CMs. Sarcomere organization was quantified using scanning gradient Fourier transform147 in MATLAB vR2020b based on the percentage of myofibrils aligned within ±20° of the superior angle. 3.3.10 SDS-Agarose Gel Electrophoresis and Western Blot Sample harvesting, SDS-agarose gel electrophoresis, and Western blotting were performed according to published literature with some modifications.80,148,149 Atrial and ventricular iPSC- 57 CMs were lysed and harvested using titin sample buffer (8M urea, 2M thiourea, 3% SDS, 50mM tris (pH 6.8), 75 mM dithiothreitol, 0.05% w/v Orange G) supplemented with protease inhibitors. Protein lysates were stored at -80°C or immediately ran on a 1% SDS-agarose gel with Tris-Glycine-SDS running buffer (50mM Tris, 0.384M glycine, 0.1% SDS) for 6 hours at 16mA constant current. Proteins were transferred to PVDF membranes using CAPS buffer (10mM CAPS, pH 11, 0.1% SDS, 10mM 2-mercaptoethanol) at 40V constant voltage for 2 hours and 20min. The PVDF membrane was blocked overnight at 4°C with 5% w/v non-fat dry milk in TBST (25mM Tris, 0.15M NaCl, 0.05% Tween-20). The membrane was incubated with a rabbit anti-TTN N-terminus IgG polyclonal antibody (1:1,750 in blocking buffer; MyoMedix; catalog TTN-1;RRID:AB_3096923) for 1hr at room temperature, washed, incubated with a mouse anti-rabbit HRP-conjugated secondary antibody (1:20,000 in blocking buffer; Santa Cruz; catalog sc-2357; RRID:AB_628497) for 1hr at room temperature, then washed again. For all wash steps, PVDF membranes were washed with TBST 3 times for 10 minutes each at room temperature. Protein bands were visualized via chemiluminescence and imaged using a G:BOX gel documentation system (Genesys). For normalization, SDS-agarose gels were stained with Bio-Safe Coomassie Stain (Bio-Rad) overnight and destained with distilled water prior to imaging. Expression of T1 titin (N2BA and N2B isoforms) was normalized to myosin heavy chain expression. Densitometric analyses were performed using ImageJ version 1.54f. 3.3.11 iPSC-CM Expansion and Engineered Heart Tissue Construction iPSC-CMs were expanded following a published protocol.150 After metabolic selection, iPSC-CMs were dissociated and plated onto Matrigel- (Corning) or Geltrex- (Thermo Fisher Scientific) coated 6-well plates at 5x105 cells/well in RPMI 1640 with B27 and 10% knockout 58 serum replacement (Thermo Fisher Scientific). Cells were expanded by culturing in RPMI 1640 with B27 with 2 μM of CHIR99021 (Stemcell Technologies). Media was replaced daily for 6-7 days or until cells reached confluency. Expanded iPSC-CMs were dissociated for subsequent EHT construction. EHTs were generated in a fibrin-based hydrogel format according to the EHT Technologies product manual. Modifications were made to the composition of the hydrogel and the EHT culture media. DMEM and horse serum were replaced by RPMI 1640 basal medium, and B27 with insulin; The hydrogel was prepared by mixing the following components on ice: RPMI 1640, B27 with insulin, GlutaMAX (Thermo Fisher Scientific), water for injection, penicillin-streptomycin, ~1mg/mL of Matrigel and 5.4mg/mL of fibrinogen (Sigma-Aldrich). Cell mixtures were made by combining iPSC-CMs with the hydrogel, Y-27632 (Selleck Chemicals), and thrombin (Sigma-Aldrich). Polydimethylsiloxane racks were placed into the 2% agarose molds made in 24-well plates in preparation for EHT casting. A mixture of 1x106 iPSC-CMs was used to construct each EHT. After transferring iPSC-CMs into the agarose molds, the plate was then incubated at 37°C with 5% CO2 for 1hr to allow fibrinogen polymerization and formation of the tissue onto the polydimethylsiloxane racks. To dissociate the EHTs from the agarose mold, 500 μL of EHT culture medium was added before shaking the plate in all directions. After a 20-minute incubation at 37°C with 5% CO2, the newly formed EHTs were transferred to a new plate with 1.5mL of EHT maintenance media containing RPMI 1640 with B27 supplement, 33 μg/mL of aprotinin (Sigma-Aldrich), and 50U/mL of penicillin-streptomycin. Media changes were performed every other day and spontaneous contraction of the EHTs was observed a week post-casting. 59 3.3.12 Contractile Force Measurements EHTs were imaged in a stage-top incubator at 37°C using a 4X objective. Recordings were acquired using a Nikon Ti2-E microscope equipped with a pco.edge 4.2Q High QE sCMOS camera. A custom MATLAB-based program was used to determine the contractile force measurements by detecting tissue post deflection and converting the displacement distance into force. Background signals were removed using a low-pass filter. Using MATLAB's peak detection function, variables such as average contraction force, contraction velocity, relaxation velocity, contraction time (T1), relaxation time (T2), and resting time were extracted from the trace signal. Average contraction force is calculated by taking the average of all the peak amplitudes. Contraction and relaxation velocity are derived by dividing the 80% of maximum amplitude with T1 and T2, respectively. T1 and T2 are calculated by extrapolating past half-width-maxima to determine 20% contraction. Resting time is calculated by taking the difference between two peaks at 0% contraction. 3.3.13 Bulk RNA-seq and Analysis of Differential Expression and Splicing RNA of iPSC-CMs were extracted using the RNAspin Mini RNA Isolation Kit (Cytiva), and RNA of EHTs were extracted using the Total RNA Purification Kit (Norgen Biotek). Total RNA integrity was assessed with the TapeStation 4200 (Agilent Technologies) and quantified with the Qubit RNA HS assay (Thermo Fisher Scientific). 200ng of total RNA was used as input for ribosomal RNA depletion using the MGIEasy rRNA Depletion kit (MGI). Strand-specific libraries were prepared using the MGIEasy RNA Directional Library Prep kit (MGI). Library quality and size were checked with the TapeStation 4200 D1000 Assay (Agilent Technologies) then quantified using the Qubit dsDNA HS Assay (Thermo Fisher Scientific). Libraries were 60 sequenced on a MGI DNB-G50 sequencer to generate approximately 40 million 100-bp paired-end reads per library. Fastq files were aligned to the reference transcriptome with STAR v2.6.0a, quantified with HTSEQ v0.11.2 and normalized/differential expression was calculated with DESEQ2 v1.16.1. Log-fold change estimates of gene expression were shrunk using a generalized linear model, and the Wald test was applied to assess differential expression. Multiple testing correction was performed using the Benjamini-Hochberg method. Genes with an absolute fold change >1.5 and an adjusted P-value <0.05 were considered significantly differentially expressed. Over-representation analysis was performed using Metascape v3.5 with default settings for human samples and a background gene list containing 23,058 genes. Differential splicing was assessed using the AS-Quant pipeline with a canonical 2x2 chi-square test.151 Splicing events with false discover rate (FDR)-adjusted P-values <0.05 and absolute ratio differences >0.1 were determined to be significantly differentially spliced. A ratio difference <-0.1 indicates a splicing event in WT/WT samples, while a ratio difference >0.1 indicates a splicing event in WT/TTNtv samples. Allele balance was determined by counting the number of transcripts with the wild-type allele or TTNtv allele in fastq files or by determining the ratio of HISAT2-aligned reads to the position of the TTNtv relative to adjacent bases. An allele balance value equal to zero indicates all reads mapped to the position of the variant contain the wild-type allele with the TTNtv allele being absent, while a value equal to 0.5 indicates a 1:1 ratio of the wild-type and TTNtv alleles. Titin isoform usage was determined using IsoformSwitchAnalyzeR.152 61 3.3.14 Statistical Analysis Statistical analyses were performed using R v4.2.1 (www.r-project.org). For two group comparisons, data were analyzed using Welchâs t-test assuming unequal variances or the Mann-Whitney U test. Multiple testing correction was performed using the Benjamini-Hochberg procedure. Sample matching for EHT contractility analysis was performed using the coarsened exact matching method from the MatchIt R package to match WT/WT and WT/TTNtv EHTs by spontaneous beat rate. Matching was performed separately for the atrial and ventricular EHTs. Matched samples were analyzed through univariate linear regression and by incorporating matching probability weights. Data plots are displayed in mean ± SEM unless otherwise specified, and P-values <0.05 were determined to be statistically significant. 3.4 Results 3.4.1 Atrial Fibrillation Patient iPSC Reprogramming and CRISPR/Cas9 Genome Editing The proband was diagnosed with early-onset âloneâ atrial fibrillation at 18 years old in the absence of known clinical risk factors. Clinical characteristics of the patient at the time of recruitment are described in Table B.5. Notably, the patient did not exhibit signs of cardiomyopathy on cardiac MRI. We performed whole exome sequencing and identified a heterozygous titin truncating variant (TTNtv) in this patient. The TTNtv is a four base pair deletion (NM_001267550.2; c.63624_63627delCAGC) in exon 305 of the inferred-complete titin meta transcript. Exon 305 lies in the titin A-band and has a percentage spliced-in score of 100%.43 The American College of Medical Genetics and Genomics classification guidelines153 62 denote this variant to be likely pathogenic as it leads to a frameshift and early translation termination at the A-band region of titin (Figure 3.1A). Figure 3.1 Patient iPSC reprogramming and CRISPR/Cas9 gene editing. A, Diagram of titin truncating variant location. B, Schematic of CRISPR/Cas9 gene editing approach to revert the mutation to wild-type through a 4-bp insertion. C, Sequence chromatograms of parental iPSCs and CRISPR-edited clones. D, Representative immunofluorescent images showing iPSCs expressing pluripotency markers TRA-1-60 (yellow), 63 NANOG (purple), and nuclei (cyan). Scale bars = 50 µm. TTNtv indicates titin truncating variant; WT, wild-type. To study the effects of the patientâs TTNtv in an in vitro model, we reprogrammed peripheral blood mononuclear cells into iPSCs. We used CRISPR/Cas9-mediated homology-directed repair to correct the heterozygous titin truncating variant (WT/TTNtv) to wild-type (WT/WT), producing a pair of isogenic iPSC lines that differ only by the presence or absence of the titin variant (Figure 3.1B and 3.1C). The genome-edited iPSCs expressed the pluripotency markers TRA-1-60 and NANOG (Figure 3.1D). 3.4.2 Assessing TTNtv using Cell Type-Specific iPSC-CM Models We used previously described differentiation techniques89,91,114,115,144 to generate atrial and ventricular iPSC-CMs to study chamber-specific effects of the TTNtv (Figure 3.2A). 64 Figure 3.2 Differentiation of patient iPSCs to atrial and ventricular iPSC-CMs. A, iPSC-CM differentiation process. Assessment of cardiac differentiation efficiency via expression of B, pan-cardiac marker cTnT and, C, MLC2v in atrial and ventricular iPSC-CMs (n = 5-6 differentiation batches). Data are presented as mean ± SEM; t-test. D, Representative action potential (black) and calcium transient (orange) averaged traces in atrial and ventricular iPSC-CMs. E, Characterization of iPSC-CM spontaneous beat rate, rate-corrected APDs at 80% and 30% repolarization (n = 8-13 differentiation batches). Mann-Whitney U test. cTnT indicates cardiac Troponin T; MLC2v, ventricular paralog of myosin light chain 2; *P<0.05; **P<0.01; ***P<0.001; ****P<0.0001. 65 The iPSC-CMs expressed high levels of the pan-cardiac marker cardiac troponin T (Figure 3.2B) and expression of the ventricular paralog of myosin light chain was significantly higher in the ventricular iPSC-CMs (Figure 3.2C). The iPSC-CMs expressed comparable levels of the pan-cardiac gene TNNT2 while TTN expression was significantly higher in ventricular iPSC-CMs (P=0.046; Figure 3.3). 66 Figure 3.3 Atrial and ventricular iPSC-CM mRNA expression. A, RT-qPCR analysis of cardiac gene expression in atrial and ventricular iPSC-CMs (n = 4-5 differentiation batches per genotype). Data are presented as median Â± IQR; whiskers represent 1.5Ãinterquartile range; paired t-test with Benjamini-Hochberg correction. B, Heatmap showing expression of cell type-specific markers in atrial and ventricular iPSC-CMs from bulk RNA- 67 sequencing (n = 3 per cell type; n = 3 per genotype). Colours represent z-scores of normalized gene counts. TTNtv indicates titin truncating variant; WT, wild-type. *P < 0.05; **P < 0.01; ***P < 0.001; ****P < 0.0001. The iPSC-CMs also showed marked differences in the expression of known atrial and ventricular genes.113,114 Atrial-specific markers such as the T-box transcription factor 5 gene (TBX5), atrial natriuretic peptide gene (NPPA), and potassium channel genes (KCNJ3 and KCNA5) were expressed at significantly greater levels in atrial iPSC-CMs compared to ventricular iPSC-CMs. Ventricular-specific markers such as the Iroquois Homeobox 4 gene (IRX4) and myosin light chain 2 gene (MYL2) were expressed at significantly lower levels in atrial iPSC-CMs compared to ventricular iPSC-CMs. To assess electrophysiological differences, we optically mapped voltage and calcium transients in spontaneously beating iPSC-CMs. The iPSC-CMs exhibited distinct electrophysiological phenotypes with atrial iPSC-CMs having more triangular action potential shapes, faster beat rates, and shorter rate-corrected action potential durations (APDs) (Figure 3.2D and 3.2E). These results indicate that the differentiation protocols employed efficiently directed the iPSCs into atrial and ventricular cardiac lineages. 3.4.3 TTNtv Increases Susceptibility to Pacing-Induced Arrhythmia in Atrial and Ventricular iPSC-CMs We did not observe significant differences in baseline electrophysiological characteristics including beat rate, rate-corrected APDs (Figure 3.2E), calcium transient durations (Figure 3.4A and 3.4B), or upstroke velocities (Appendix Figure B.1A) between WT/TTNtv and WT/WT iPSC-CMs. 68 Figure 3.4 TTNtv increases the susceptibility of iPSC-CMs to pacing-induced arrhythmia. Comparisons of A, rate-corrected calcium transient durations at 80% and B, 30% repolarization (n = 6-9 differentiation batches) in WT/TTNtv iPSC-CMs versus isogenic WT/WT. Data are presented as mean ± SEM; Mann-Whitney U test. Response of C, atrial (n = 7 differentiation batches) and D, ventricular iPSC-CMs (n = 9-10 differentiation batches) to electrical pacing for 20 seconds/cycle length. Fisher exact test. Representative traces of ventricular E, WT/WT iPSC-CMs paced at 300ms showing normal electrophysiology without alternans or, F, WT/TTNtv iPSC-CMs paced at 300ms showing voltage and calcium transient alternans. TTNtv indicates titin truncating variant; WT, wild-type. 69 APDs were also comparable in WT/TTNtv versus WT/WT iPSC-CMs under pacing (Appendix Figure B.1B and B.1C). We then applied electrical stimulation at increasing frequencies from a cycle length near the spontaneous beat rate to 200ms in atrial iPSC-CMs or 300ms in ventricular iPSC-CMs. We observed a significantly greater prevalence of arrhythmogenic phenotypes, such as voltage and/or calcium alternans, in atrial WT/TTNtv iPSC-CMs compared to isogenic WT/WT iPSC-CMs (85.7% versus 14.3%; P=0.03; Figure 3.4C). Similarly, a greater prevalence of arrhythmogenic phenotypes was observed in ventricular WT/TTNtv iPSC-CMs compared to isogenic controls (90.0% versus 33.3%; P=0.02; Figures 3.4D and Appendix Figure B.1D). The most common arrhythmogenic phenotype observed was the appearance of voltage and/or calcium alternans at cycle lengths of 200ms or 300ms in atrial WT/TTNtv iPSC-CMs and between 300ms to 800ms in ventricular WT/TTNtv iPSC-CMs (Figures 3.4E and 3.4F). 3.4.4 TTNtv Impairs Sarcomere Structures in Atrial and Ventricular iPSC-CMs Titin mediates sarcomere formation in cardiomyocytes, and previous studies have shown TTNtv can lead to sarcomere disarray or insufficiency in ventricular iPSC-CM models of TTNtv DCM and a zebrafish model of TTNtv AF.31,35,84 We hypothesized that the TTNtv associated with AF may cause sarcomere defects, indicating an underlying myopathy, which contribute to arrhythmogenesis in atrial iPSC-CMs. We quantified the organization of sarcomere structures and observed significantly less organized sarcomere structures in atrial WT/TTNtv iPSC-CMs compared to CRISPR-corrected iPSC-CMs (mean ± SEM, 66.3 ± 6.8% versus 88.0 ± 2.9%; P=0.04; Figures 3.5A and 3.5B). 70 Figure 3.5 TTNtv iPSC-CMs exhibited disorganized sarcomere structures. A, Confocal images of atrial iPSC-CMs stained for sarcomere proteins α-actinin and titin. B, Quantification of sarcomere organization in atrial iPSC-CMs using α-actinin striation patterns (n = 4-5 differentiation batches, 4-6 images each). C, Confocal images of ventricular iPSC-CMs stained for α-actinin and titin. D, Quantification of sarcomere organization in ventricular iPSC-CMs using α-actinin striation patterns (n = 5 differentiation batches, 4-7 images each). Scale bars 71 = 10 µm. Data are presented as median Â± IQR; whiskers represent 1.5Ãinterquartile range. TTNtv indicates titin truncating variant; WT, wild-type; *P<0.05; **P<0.01; t-test. Ventricular WT/TTNtv iPSC-CMs also displayed less organized sarcomere structures compared to isogenic controls (62.0 ± 3.9% versus 82.9 ± 2.9%; P=0.003; Figures 3.5C and 3.5D). To determine if the TTNtv led to reduced titin protein expression and subsequently sarcomere disorganization, we assessed titin expression using SDS-agarose gel electrophoresis and Western blot (Figure 3.6). 72 Figure 3.6 iPSC-CM gel electrophoresis and Western blot. A, SDS-agarose gels of atrial (left) and ventricular (right) iPSC-CMs stained with Coomassie blue for protein normalization and immunoblots probed for anti-titin N-terminus (n = 3). LI-COR Chameleon 800 Pre-stained Protein Ladder was used to identify myosin heavy chain by size. B, Relative expression of titin protein in atrial (left) and ventricular (right) iPSC-CMs normalized to myosin heavy chain expression (0.22MDa). t-test. TTNtv indicates titin truncating variant; WT, wild-type; *P < 0.05; **P < 0.01. 73 Titin expression was significantly reduced in WT/TTNtv iPSC-CMs compared to isogenic controls. Truncated titin was not detected on the Coomassie-stained SDS-agarose gels nor Western blots of either cell types. Taken together, the TTNtv leads to sarcomere disarray in both atrial and ventricular cell types, and genetic correction of the TTNtv can restore sarcomere structures to levels comparable to isogenic controls. 3.4.5 TTNtv Impairs Contractile Force Generation in Atrial EHTs We next examined the consequences of TTNtv and sarcomere disorganization on the contractility of atrial and ventricular iPSC-CMs. We generated engineered heart tissue (EHT) constructs (Figures 3.7A, 3.7B, and Appendix Figure B.2A) and measured force parameters based on the displacement of polydimethylsiloxane posts during contraction (Appendix Figure B.2B). 74 Figure 3.7 Atrial TTNtv EHTs displayed reduced contractile force compared to isogenic WT EHTs. A, Diagram of EHT setup. B, Whole-mount immunostaining of ventricular WT/WT EHTs for sarcomere α-actinin (yellow), titin M-line (purple), and nuclei (cyan). Scale bars = 10 μm. Spontaneous maximum contractile force in C, atrial EHTs (n = 8-17 EHTs) and D, ventricular EHTs (n = 10-17 EHTs). t-test. Data are presented as median±IQR; whiskers represent 1.5Ãinterquartile range. EHT indicates engineered heart tissue; PDMS, polydimethylsiloxane; TTNtv, titin truncating variant; WT, wild-type; *P<0.05; **P<0.01. In spontaneously beating atrial EHTs, WT/TTNtv EHTs exhibited significantly weaker maximal contractile force compared to WT/WT EHTs (0.013 ± 0.003mN versus 0.027 ± 0.004mN; P<0.01; Figure 3.7C), shorter contraction time T1 (P<0.05; Appendix Figure B.2C), and shorter relaxation time T2 (P<0.05). No significant differences were observed in contraction and 75 relaxation velocities (Appendix Figure B.2D). In ventricular EHTs, no significant differences in any parameters were observed (Figures 3.7D, Appendix Figures B.2E, and B.2F). To control for the effects of differing spontaneous beat rates on contractility (Appendix Figure B.2G), we performed a sensitivity analysis on a subset of EHTs matched by beat rates. In rate-matched atrial EHTs, the contractile force of WT/TTNtv EHTs remained significantly weaker compared to wild-type (P<0.001; Appendix Table B.6). Contraction (P<0.01) and relaxation velocities (P<0.05) were also significantly slower in WT/TTNtv compared to WT/WT EHTs. In rate-matched ventricular EHTs, contractility was not significantly different between genotypes. Contractile forces were also reduced in atrial WT/TTNtv EHTs paced at fixed beating rates whereas ventricular WT/TTNtv EHTs generated comparable forces to isogenic controls (Appendix Figure B.3). 3.4.6 Whole Transcriptome Sequencing Reveals Differential Splicing of Cardiac-Specific Genes as Well as Upregulation of Genes Involved in Cell Adhesion and Extracellular Matrix in TTNtv EHTs To understand how the TTNtv influences global gene expression, we performed whole transcriptome sequencing of the EHTs (Figure 3.8A). 76 Figure 3.8 Whole transcriptome differential gene expression of atrial and ventricular EHTs. A, Principal component analysis of engineered heart tissues (n = 3 per cell type; n = 3 per genotype). B, Overlapping significantly upregulated and downregulated genes in atrial and ventricular WT/TTNtv EHTs relative to atrial and ventricular WT/WT EHTs, respectively. C, Differentially expressed genes in atrial WT/TTNtv EHTs relative to isogenic WT/WT controls (blue dots: adjusted P-value <0.05 and |fold change >1.5|). D, Differentially expressed genes in 77 ventricular WT/TTNtv EHTs relative to isogenic WT/WT controls (green dots: adjusted P-value <0.05 and |fold change >1.5|). E, Expression of extracellular matrix and fibrosis markers in EHTs. Colours represent fold change relative to WT/WT EHTs. EHT indicates engineered heart tissue; TTNtv, titin truncating variant; Vent., ventricular; WT, wild-type; *P<0.05. The TTNtv did not alter allele balance, as indicated by a ratio near 0.4-0.5 for the heterozygous WT/TTNtv samples (Appendix Figures B.4A and B.4B), and TTN transcript isoform usage was not significantly different between WT/TTNtv and WT/WT genotypes (Appendix Figures B.4C and B.4D), similar to existing data from patients with TTNtv-associated DCM.80,81 While TTN splicing was not significantly different between genotypes, we detected splicing events in other transcripts associated with the contractile apparatus, cytoskeletal genes, and adhesion or extracellular matrix genes (Appendix Figures B.5, B.6, Appendix Tables B.7, and B.8). Next, we performed differential expression analysis to identify genes perturbed by the presence of the WT/TTNtv (Figure 3.8B). The TTNtv led to a significant downregulation of 13 genes in the atrial WT/TTNtv EHTs compared to the isogenic WT/WT EHTs (Figure 3.8C and Appendix Table B.9), including KLHL40 a gene associated with skeletal myopathies.154 Significantly downregulated genes were not detected in the ventricular samples (Figure 3.8D). A number of genes were significantly upregulated in the WT/TTNtv samples for both cell types compared to their respective isogenic WT/WT controls (atrial: 80 genes; ventricular: 35 genes; overlap: 28 genes; Figures 3.8B-8D, Appendix Tables B.10, and B.11). We performed over-representation analysis of the significantly upregulated genes to identify potential processes implicated. A significant enrichment of genes involved in cell-to-cell adhesion (GO:0007156, - 78 log(q-value)=2.83; GO:0098742, -log(q-value)=1.61) as well as antiviral response (hsa05168, -log(q-value)=5.49) were identified to be upregulated in atrial EHTs. Expression of cell adhesion and extracellular matrix-associated genes were also significantly upregulated, suggesting remodelling of cell-cell interactions that could have an impact on electrophysiology and contractile function. Although not statistically significant, several extracellular matrix and fibrosis-associated genes were expressed at higher levels in WT/TTNtv EHT samples compared to isogenic controls (Figure 3.8E). Other significantly upregulated genes previously linked to cardiac disorders and tissue remodelling included sodium channel subunits (SCN3B and SCN9A),155,156 IRAK4,157 and LAMP3.158 Together, these findings suggest an effect of the TTNtv on splicing and gene expression which may impact atrial electrophysiology and contractile function. 3.5 Discussion Titin truncating variants (TTNtv) are found in approximately 0.6% of the general population, and genetic association studies have linked pathogenic mutations to cardiomyopathies and arrhythmias.35,37â39 TTNtv have also been linked to an increased propensity for AF in patients with and without AF risk factors.35,38 Existing studies have focused on the effects of TTNtv in ventricular tissue.81,84,85 Thus, the mechanisms by which TTNtv contribute to atrial arrhythmias, particularly in the absence of ventricular disease or cardiomyopathy, remain unclear. We employed human iPSC-CMs, EHTs, and CRISPR/Cas9 genome editing to investigate the role of TTNtv in AF pathogenesis in a patient without ventricular dysfunction. 79 We found that WT/TTNtv iPSC-CMs exhibit comparable electrophysiology to isogenic controls at baseline. This absence of APD prolongation in WT/TTNtv iPSC-CMs, in contrast to observations in models of TTNtv DCM,82,85 agrees with the patientâs clinical presentation of normal QT-interval durations. WT/TTNtv iPSC-CMs were significantly more susceptible to developing arrhythmogenic phenotypes upon rapid pacing. The development of AF in individuals harboring an arrhythmia-associated genetic variant may depend on the presence of additional triggers,159,160 and we have previously demonstrated an additive effect between modifiable factors, such as hypertension, and titin variant status on the risk of incident AF in Chapter 2.161 Interestingly, both the atrial and ventricular iPSC-CMs displayed a greater prevalence of in vitro arrhythmogenic phenotypes with rapid pacing, suggesting similarities in susceptibility to pacing-induced arrhythmia between atrial and ventricular TTNtv iPSC-CMs compared to their respective isogenic wild-type controls. TTNtv have been significantly associated with both atrial and ventricular arrhythmias at a population level,39 and our findings here provide in vitro evidence supporting the possibility of common mechanisms of atrial and ventricular arrhythmogenesis in TTNtv carriers. In line with titinâs known function as a critical sarcomeric structural protein,31 we found that the TTNtv led to sarcomere disorganization and reduced titin protein expression. Truncated titin was not detectable, indicating the TTNtv may contribute to functional defects through haploinsufficiency rather than a dominant-negative effect. We also observed decreased force generation by atrial WT/TTNtv EHTs, suggesting the possibility of a propensity towards an atrial-specific myopathy. As the proband was in permanent AF for many years, accurate assessments of patient atrial function could not be performed. Despite decreased titin protein 80 expression, contractility was not impaired in ventricular WT/TTNtv EHTs in contrast to existing data from patient-specific models of DCM.81,84 This may be due to differing effects of the TTNtv on the expression of titin in atrial versus ventricular iPSC-CMs that were not distinguishable using SDS-agarose gel electrophoresis and Western blot. It is also possible that the TTNtv alters the expression of non-titin sarcomere proteins if sarcomere integrity is compromised due to the decrease in titin expression. Atrial and ventricular cardiomyocytes have inherent differences in sarcomere structure, composition, and kinetics, which can impact contractility at a tissue levels. For instance, atrial cells exhibit lower myofibril densities,105 which could cause atrial EHTs to be more prone to contractility defects when sarcomeric protein expression is reduced or perturbed compared to ventricular EHTs. A number of cell type-specific sarcomere protein isoforms are also differentially expressed in healthy atrial and ventricular cardiomyocytes,110 including the atrial and ventricular paralogs of myosin light chains 1 and 2,106 elevated atrial expression of α-myosin heavy chain instead of β-myosin heavy chain,107 and the atrial expression of both myosin binding proteins C and H-like instead of mainly myosin binding protein C in the ventricles.108 Differential effects of the TTNtv on expression of non-titin proteins that are involved in the maintenance of sarcomere integrity and contractility as well as cell type-specific cardiac proteins in atrial and ventricular iPSC-CMs could contribute to the observed differences in contractility phenotypes. Further analyses of protein expression using more sensitive, accurate, and comprehensive techniques such as mass spectrometry are needed to compare the protein expression profiles of atrial and ventricular TTNtv iPSC-CMs to their respective isogenic controls and improve our understanding of the factors leading to the observed atrial-specific contractile defect. While we cannot rule out the presence of subclinical structural alterations in the ventricles, the absence of contractility defects in the ventricular EHTs aligns with the 81 patientâs cardiac MRI results which showed normal biventricular size and function. The TTNtv in this case demonstrated cell type-specific effects which correlate with observed clinical phenotypes and raises the possibility that unique variants in TTNtv may have varying chamber-specific pathophysiologic consequences. A previous study on TTNtv and AF detected increased fibrosis in the atria of zebrafish hearts with TTNtv.35 Furthermore, DCM patients with titin mutations exhibited increased left atrial volume and worse left atrial strain.53 We hypothesized that TTNtv may lead to atrial fibrosis or structural remodelling which can cause myopathic tissue alterations associated with the initiation and maintenance of AF.162 In addition to differential splicing of sarcomere and extracellular matrix genes, we identified an upregulation of genes associated with cell adhesion, extracellular matrix, and inflammation, which have been linked to AF, and provide evidence that TTNtv is involved in adverse tissue remodelling which may contribute to arrhythmogenesis.163,164 Re-expression of collagens in iPSC-CMs was previously reported to occur when cultured in fibrotic matrix conditions.165 Thus, the elevated expression of extracellular matrix and fibrosis-associated genes in WT/TTNtv EHTs may be in response to fibrotic conditions and potentially drive further fibrosis through extracellular matrix remodelling. Genes encoding sodium channel subunits were also upregulated which could contribute to arrhythmogenesis by increasing heterogeneity of tissue refractoriness or enhancing late sodium current. Taken together, these findings suggest multiple and potentially patient-specific pathways and factors contributing to an increased propensity to AF. This may include both electrophysiologic derangements, as observed, and an atrial-specific myopathy which would serve as a substrate for AF. 82 This study has several limitations that should be considered. Compared to human adult hearts, iPSC-CMs exhibit immature electrophysiological, structural, metabolic, and transcriptional properties that more closely resemble fetal cardiomyocytes.166 To overcome this challenge, we used iPSC-CMs after prolonged culture periods, assessed sarcomere defects in iPSC-CMs maintained on maturity-promoting micropatterned surfaces, and generated EHT constructs to compare contractility and gene expression. Further studies employing maturation techniques or other cardiac cell types, such as fibroblasts or endothelial cells, can improve our ability to recapitulate AF in vitro. While we have demonstrated that the TTNtv investigated can lead to the development of in vitro phenotypic and functional abnormalities associated with atrial myopathy, a precursor and driver of AF pathogenesis, the underlying mechanisms require further investigation. It also remains unclear if this specific mutation alone is sufficient to cause AF if present in other individuals. Despite multiple studies35,38,39,167 demonstrating strong associations between other reported TTNtv and AF, including early-onset AF and lone AF, the underlying mechanisms of arrhythmogenesis may be distinct to each patient or each titin truncating variant and warrants further investigation. Given the varying disease phenotypes and penetrance of titin mutations in the general population, our findings do not preclude the possibility of additional factors contributing to the onset of AF in other patients with a TTNtv. More studies of this TTNtv in other genetic contexts and of other TTNtv associated with lone AF are needed to broaden the applicability of these findings. In summary, we evaluated the effects of a heterozygous TTNtv implicated in AF in atrial and ventricular patient-derived iPSC-CMs. We observed an increase in arrhythmogenicity and sarcomere disarray in atrial and ventricular TTNtv iPSC-CMs compared to isogenic controls. 83 Using atrial and ventricular EHT constructs, we showed that the TTNtv impairs contractility in atrial EHTs but not ventricular EHTs, and that the TTNtv leads to transcriptional changes which may contribute to altered cell-cell interactions and extracellular matrix composition. Our findings suggest a link between TTNtv and both structural and electrophysiological abnormalities in atrial tissue that could be relevant to the pathogenesis of AF. These findings deepen our understanding of the effects of TTNtv on atrial and ventricular tissues and their relationship to atrial and ventricular myopathies and arrhythmias. 84 Chapter 4: TTNtv-Associated Ventricular Fibrillation Leads to Abnormal Electrophysiology and β-Adrenergic Response in Patient-Specific Ventricular iPSC-CMs 4.1 Chapter Summary Background: Ventricular fibrillation (VF) is a life-threatening arrhythmia that can lead to sudden cardiac death. While population-level studies have linked protein truncating variants in titin to increased risk of cardiomyopathies and myopathy-induced VF, the functional consequences of titin truncating variants (TTNtv) in cardiomyocytes and their contributions to arrhythmias that arise in the absence of structural heart disease are unclear. Our objective was to investigate the cellular effects of a titin variant identified in a VF patient without clinically diagnosed cardiomyopathies. Methods: We identified a patient who experienced unexplained VF and is a carrier of a likely pathogenic heterozygous TTNtv. We generated patient-specific induced pluripotent stem cells (iPSCs), used CRISPR/Cas9 genome editing to correct the variant to wild-type, and generated atrial-like and ventricular-like iPSC-derived cardiomyocytes (iPSC-CMs) to examine the effects of the TTNtv on cellular electrophysiology and contractility. Results: We found that TTNtv decreases calcium transient durations in ventricular iPSC-CMs but not atrial iPSC-CMs compared to their respective CRISPR/Cas9-corrected wild-type controls. In ventricular iPSC-CMs treated with isoproterenol, TTNtv led to shorter action potential durations and calcium transient durations compared to isogenic controls. 85 Conclusion: Ventricular iPSC-CMs with a TTNtv exhibited impaired electrophysiology under baseline conditions and after treatment with isoproterenol, demonstrating a cell type-specific effect of the variant that recapitulates the patientâs clinical phenotype. These findings provide insights to the role of TTNtv in arrhythmogenesis in the absence of cardiomyopathies and further our understanding of ventricular arrhythmias. 4.2 Introduction Ventricular fibrillation (VF) is a life-threatening arrhythmia that can lead to sudden cardiac death. Titin is a key sarcomere protein that is identified in up to ~25% of familial dilated cardiomyopathy (DCM) cases, and recent studies have identified an association between titin truncating variants (TTNtv) and increased risk of atrial and ventricular fibrillation in cardiomyopathy patients.36,37,168 While this may occur in part due to cardiomyopathy-related tissue fibrosis,169,170 the association to ventricular arrhythmia remains significant after adjustment for a DCM diagnosis,39 suggesting that TTNtv may have arrhythmogenic potential independent of typical myopathic pathophysiology. We identified a heterozygous TTNtv in a VF patient with no evidence of cardiomyopathy. This presented us with a unique opportunity to examine the cellular mechanisms by which TTNtv can lead to ventricular arrhythmia in the absence of structural heart disease. Using atrial and ventricular patient-specific induced pluripotent stem cell-derived cardiomyocyte (iPSC-CM) models, CRISPR/Cas9 genome editing, and optical mapping, we show that TTNtv impacts the action potential and calcium transient durations in ventricular iPSC-CMs and provide evidence to 86 support altered electrophysiological properties as a possible contributor to ventricular arrhythmogenesis in TTNtv carriers. 4.3 Methods 4.3.1 Study Approval This study was approved by the University of British Columbia Childrenâs and Womenâs Research Ethics Board (H18-01465). All participants provided written informed consent. 4.3.2 Patient Sequencing and Titin Variant Identification Patient recruitment was completed through the BC Inherited Arrhythmia Program in Vancouver, Canada. Variant identification was performed by Blueprint Genetics Laboratories using the Comprehensive Cardiology Panel Plus (version 3; June 26, 2017). Mutation carrier status was further confirmed through targeted Sanger genotyping (Azenta/GENEWIZ). 4.3.3 iPSC Reprogramming and Characterization Reprogramming of iPSCs was performed by the BC Childrenâs Hospital Research Institute Tissue and Disease Modeling Core, as previously described in Chapter 3. Briefly, patient blood samples were collected, and peripheral blood mononuclear cells were isolated from the samples for reprogramming to iPSCs using the CytoTune-iPS 2.0 Sendai Reprogramming Kit (Thermo Fisher Scientific). iPSC clones were screened using the hPSC Genetic Analysis Kit (Stemcell Technologies) to identify clones without genetic abnormalities, and iPSC pluripotency was assessed using flow cytometry to identify clones with >90% TRA-1-60 expression. Pluripotency of iPSC colonies was also assessed by immunofluorescent staining of TRA-1-60 and NANOG 87 and confocal microscopy. iPSCs were fixed with 4% paraformaldehyde and permeabilized with 0.2% Triton X-100 in DPBS without Mg2+/Ca2+. The samples were then blocked overnight in 5% goat serum, 0.2% Triton X-100 in DPBS without Mg2+/Ca2+ at 4°C. Following blocking, samples were stained with mouse anti-TRA-1-60 (Abcam; catalog ab16288; RRID:AB_778563) and rabbit anti-NANOG (Abcam; catalog ab21624; RRID:AB_446437) primary antibodies then incubated in goat anti-mouse AF488 (Abcam; catalog ab150113; RRID:AB_2576208) and goat anti-rabbit AF647 (Thermo Fisher Scientific; catalog A-21245; RRID:AB_2535813) secondary antibodies. Z-stack images and maximum intensity projections were acquired using a Zeiss LSM880 Confocal Microscope at 20X and Zen 2.3 SP1 FP1 v14.0.9.201. iPSCs were maintained in mTeSR1 media (Stemcell Technologies) on hESC-qualified Matrigel (Corning) or Geltrex (Thermo Fisher Scientific). 4.3.4 CRISPR/Cas9 Genome Editing CRISPR/Cas9 homology-directed repair was performed as previously described in Chapter 3 with minor modifications to correct the heterozygous WT/TTNtv to WT/WT in iPSCs. Briefly, We used CRISPOR v4.97145 and the CRISPR/Cas9 gRNA Design Checker (Integrated DNA Technologies) to design a custom gRNA sequence targeting the WT/TTNtv and perform off-target prediction. The gRNA and DNA donor template were ordered from Integrated DNA technologies (Appendix Table C.1). Ribonucleoprotein complexes containing the Cas9 nuclease and gRNA duplex (dual-tracrRNA:crRNA) as well as the DNA donor template were delivered into the iPSCs using a Nucleofector 2b Device and the Human Stem Cell Nucleofector Kit 1 (Lonza) according to manufacturerâs instructions. To improve the editing efficiency, iPSCs were seeded into plating media containing Alt-R HDR Enhancer V2 (Integrated DNA Technologies) 88 after nucleofection (Appendix Table C.2). iPSCs were replated as single cells at low cell densities and individual clones were manually isolated by picking. Genomic DNA were extracted using QuickExtract DNA Extraction Solution (Epicentre) and PCR was used to amplify the target site. The genotype of each clone was determined through Sanger sequencing (Azenta/Genewiz) of the purified PCR products. Evaluation of predicted off-target editing sites (Appendix Table C.3) was performed through PCR amplification and Sanger sequencing (Azenta/Genewiz). PCR primer sequences are listed in Appendix Table C.4. WT/TTNtv iPSCs that underwent the CRISPR/Cas9 editing process but retained the mutation were used as the isogenic control. Two clones per genotype were used in the experiments described in this study. 4.3.5 iPSC-CM Differentiation iPSCs were differentiated to atrial- and ventricular-like iPSC-CMs through temporal modulation of the WNT signalling pathway,89,91,144 as previously described in Chapter 3. Briefly, iPSCs were seeded as single cells on Matrigel-coated plates and maintained for 4 days with daily mTeSR media changes until >90% confluency. iPSCs were treated with the WNT activator CHIR99021 (Stemcell Technologies) in RPMI 1640 with B27 supplement minus insulin (Thermo Fisher Scientific) for 24 hrs followed by the WNT inhibitor IWP-2 (R&D Systems) for 48 hrs. A media change was performed every 2 days, and the media was switched to RPMI 1640 with B27 from day 7 to day 10. On day 10, iPSC-CMs underwent metabolic selection using media without glucose that is supplemented with sodium L-lactate (Sigma-Aldrich) for 4-6 days. Following metabolic selection, iPSC-CMs were cultured in RPMI 1640 with B27 supplement for maintenance and subsequent experiments. Atrial-like iPSC-CMs were differentiated by supplementing the media with 0.75 μM all-trans retinoic acid (Sigma-Aldrich) for 48 hrs during 89 day 3 to day 5 of differentiation.114,115 Experiments were conducted using iPSC-CMs >30 days in culture. 4.3.6 Flow Cytometry Sample preparation and staining was performed as previously described in Chapter 3. Briefly, iPSC-CMs were harvested as single cells using a dissociation solution containing 0.5U/ml Liberase TH (Sigma-Aldrich), 50 U/ml DNaseI (Sigma-Aldrich), and TrypLE (Thermo Fisher Scientific). Cells were fixed with 2% paraformaldehyde and permeabilized with 0.5% Saponin, 2% FBS in DPBS without Mg2+/Ca2+. iPSC-CMs were stained with BV421-conjugated anti-cTnT antibody (BD Biosciences; catalog 565618; RRID:AB_2739306) and rabbit anti-MLC2v antibody (Abcam; catalog ab79935; RRID:AB_1952220) then stained with an AF647-conjugated goat anti-rabbit secondary antibody (Thermo Fisher Scientific; catalog A-21245; RRID:AB_2535813). iPSCs were stained in parallel as a negative cell type control and for gating. Stained samples were ran on a Gallios Flow Cytometer (Beckman Coulter) and analyzed using the Kaluza Analysis Software v2.1 (Beckman Coulter). The gating strategy is illustrated in Appendix Figure C.1. 4.3.7 Optical Mapping of Voltage and Calcium Transients iPSC-CMs were co-stained with FluoVolt (Thermo Fisher Scientific) and Calbryte 630 AM (AAT Bioquest) in DMEM/F12 supplemented with 0.02% pluronic F-127 (Thermo Fisher Scientific) and 1.25 μM probenecid (AAT Bioquest). After staining, iPSC-CMs were placed in a stage-top incubator (Okolab) set to 37°C and imaged in DMEM/F12 with B27 supplement and 1 mM probenecid. Voltage and calcium recordings were acquired at 10X, 200 frames per second 90 using a Nikon Ti2-E microscope equipped with a pco.edge 4.2Q High QE sCMOS camera. Electrical pacing was applied using a custom-built stimulator (biphase 5ms pulse) and carbon Pacing Electrodes (DiNABIOS). For the dynamic pacing experiments, iPSC-CMs were subjected to an initial pacing frequency near its spontaneous beat rate. The pacing frequency was then increased stepwise by increments of 100 ms per recording until a cycle length of 300 ms for atrial samples, 200 ms for ventricular samples, or if an arrhythmogenic event was observed, whichever came first. Arrhythmogenic events were defined as a composite of alternans, early-after or delayed-after depolarizations, missing/extra beats, or irregular rhythms in either the action potential or the calcium transient recording. Isoproterenol was reconstituted in DMEM/F12. iPSC-CMs were incubated in imaging media with 0.1 μM or 1 μM of isoproterenol or DMEM/F12 (vehicle control) at 37°C, 5% CO2. Recordings were acquired before drug treatment, 20 minutes post-treatment, and 20 minutes post-washout. Data were analyzed using a custom-built Python analysis script. Electrophysiological parameters assessed included beat rate, action potential durations (80% repolarization to 30% repolarization), and calcium transient durations (80% repolarization to 30% repolarization). Beat rate-correction was calculated using Bazettâs method: ðð´ðð· àµ ð´ðð·à¶§ 60ðµððð¡ ððð¡ð 91 4.3.8 Contractility Analysis using MUSCLEMOTION iPSC-CMs were imaged in DMEM/F12 with B27 supplement and 1 mM probenecid. Cells were kept at 37°C using a stage-top incubator (Okolab). Recordings of iPSC-CMs were acquired using a Nikon Ti2-E microscope equipped with a pco.edge 4.2Q High QE sCMOS camera at 20X, 100 frames per second. Video recordings were converted to .avi format and analyzed in ImageJ using the MUSCLEMOTION macro.171 4.3.9 Statistical Analysis Statistical analyses were performed using R v4.2.1 (www.r-project.org). For two group comparisons, data were analyzed using Welchâs t-test assuming unequal variances or the Mann-Whitney U test. Multiple testing correction was performed using the Bejamini-Hochberg method. Survival analyses were performed using the R package âSurvivalâ version 3.3-1. Data plots are displayed in mean ± SEM unless otherwise specified. P-values <0.05 were determined to be statistically significant. 4.4 Results 4.4.1 Ventricular Fibrillation Patient iPSC Reprogramming and Genome Editing The proband experienced sudden cardiac arrest while she was running at 13 years of age. She was found to be in VF and was successfully resuscitated. The clinical characteristics of the patient at the time of study recruitment are described in Appendix Table C.5. Due to the patientâs young age, the absence of known clinical risk factors, and the absence of cardiomyopathy upon imaging, the patient underwent genetic testing for variants in 165 genes associated with arrhythmias, cardiomyopathies, or sudden cardiac arrest using the Comprehensive Cardiology 92 Panel from Blueprint Genetics Laboratories. Genetic testing identified a heterozygous TTNtv (p.Ser21134Trpfs*25; RefSeq accession number: NP_001254479.2) in this patient that is predicted to be likely pathogenic. The variant is in an exon with a percentage spliced-in score of 100%43 in the A-band region of titin. This variant has been previously reported in a male individual with early-onset atrial fibrillation,172 who is the father of the proband, and was examined in Chapter 3. We generated patient iPSCs by reprogramming peripheral mononuclear blood cells to investigate the effects of the patientâs TTNtv in vitro (Figure 4.1A). 93 Figure 4.1 Ventricular fibrillation patient iPSC reprogramming and CRISPR/Cas9 gene editing. A, Diagram of study workflow (created with BioRender.com). B, Sanger sequencing results of parental iPSCs and CRISPR-edited WT/WT iPSCs confirming variant correction to wild-type. C, Representative immunofluorescent images showing iPSCs expressing pluripotency markers 94 NANOG (purple), TRA-1-60 (yellow), and nuclei (cyan). Scale bars = 50 µm. TTNtv indicates titin truncating variant; WT, wild-type. Using CRISPR/Cas9-mediated homology-directed repair, we corrected the heterozygous titin truncating variant (WT/TTNtv) to wild-type (WT/WT) to generate a pair of isogenic patient iPSC lines differing only by the presence or absence of the titin variant (Figure 4.1B). The isogenic iPSCs expressed the pluripotency markers NANOG and TRA-1-60, indicating the potential to be differentiated to multiple cell types including iPSC-CMs (Figure 4.1C). 4.4.2 Modelling the TTNtv in Atrial and Ventricular iPSC-CMs We generated atrial and ventricular iPSC-CMs using previously described differentiation methods89,91,115,144 to examine the effects of the TTNtv across different cardiac cell types (Figure 4.2A). 95 Figure 4.2 Differentiation of ventricular fibrillation patient iPSCs to atrial and ventricular iPSC-CMs. 96 A, Atrial and ventricular iPSC-CM differentiation process. Retinoic acid is supplemented to the differentiation media on day 3-5 for atrial differentiation. B, Assessment of pan-cardiac marker cTnT expression in atrial and ventricular iPSC-CMs using flow cytometry (n = 4-7 differentiation batches). t-test. C, Assessment of MLC2v expression in atrial and ventricular iPSC-CMs using flow cytometry (n = 4-7 differentiation batches). t-test. D, Representative action potential (black) and calcium transient (orange) averaged traces in atrial and ventricular iPSC-CMs. E, Characterization of spontaneous beat rate, rate-corrected action potential durations at 80% and 30% repolarization, triangulation index, and rate-corrected calcium transient duration at 80% repolarization in WT/TTNtv iPSC-CMs (n = 6-7 differentiation batches). F, Characterization of spontaneous beat rate, rate-corrected action potential durations at 80% and 30% repolarization, triangulation index, and rate-corrected calcium transient duration at 80% repolarization in WT/WT iPSC-CMs (n = 4-8 differentiation batches). Data are presented as mean ± SEM; Mann-Whitney U test. cTnT indicates cardiac Troponin T; MLC2v, ventricular paralog of myosin light chain 2; TTNtv, titin truncating variant; WT, wild-type; *P<0.05; **P<0.01; ***P<0.001; ****P<0.0001. The iPSC-CMs expressed the pan-cardiac marker cardiac troponin T (Figure 4.2B). Expression of the ventricular paralog of myosin light chain was significantly higher in the ventricular iPSC-CMs compared to atrial iPSC-CMs, reflecting cell type-specific marker expression (Figure 4.2C). We used an optical mapping approach to measure the action potential and calcium transient properties of spontaneously beating atrial and ventricular iPSC-CMs. The atrial iPSC-CMs exhibited action potential and calcium transients that are more triangular (Figure 4.2D) and showed faster beat rates, shorter action potential durations (APDs), and shorter calcium transient 97 durations (CaTDs; Figure 4.2E and Appendix Figure C.2A). These distinct electrophysiological phenotypes of atrial and ventricular cells were also observed in the WT/TTNtv iPSC-CMs (Figure 4.2F and Appendix Figure C.2A), indicating effective directed differentiation of the isogenic iPSCs to atrial and ventricular cardiac lineages. 4.4.3 TTNtv Does Not Impair Contractility in iPSC-CMs Titin is a critical protein in sarcomere formation, and TTNtv have been demonstrated to weaken the contractile force of iPSC-derived engineered heart tissue models of DCM.81,84 To assess the effects of the TTNtv on contractility in atrial and ventricular iPSC-CMs, we acquired phase-contrast video recordings of spontaneously beating iPSC-CMs and used MUSCLEMOTION171 to measure force parameters based on changes in pixel intensities between image frames during contraction. In spontaneously beating iPSC-CMs, no significant differences in contraction amplitudes were detected between WT/TTNtv iPSC-CMs compared to WT/WT iPSC-CMs for either cell type (Figure 4.3A). 98 Figure 4.3 Contraction amplitude analysis of iPSC-CM monolayers. A, Contraction amplitude of spontaneously beating atrial iPSC-CMs and ventricular iPSC-CMs (n = 6-9 differentiation batches). B, Contraction amplitude of atrial iPSC-CMs paced at 120 beats-per-minute and 75 beats-per-minute (n = 2-3 differentiation batches). C, Contraction amplitude of ventricular iPSC-CMs paced at 60 beats-per-minute (n = 8-10 differentiation batches). Data are presented as mean ± SEM; Mann-Whitney U test. TTNtv indicates titin truncating variant; WT, wild-type; *P<0.05. To control for the effects of variable spontaneous beat rates on contractile force, we repeated the analysis with iPSC-CMs paced at fixed frequencies. Atrial iPSC-CMs were paced at 75 beats-per-minute and 120 beats-per-minute while ventricular iPSC-CMs were paced at 60 beats-per-minute. While the contraction amplitude of the atrial WT/TTNtv iPSC-CMs appear to be visually 99 smaller compared to WT/WT iPSC-CMs, we were underpowered to detect significant differences in contraction amplitudes between atrial WT/TTNtv iPSC-CMs and atrial WT/WT iPSC-CMs under pacing (Figure 4.3B). In paced ventricular iPSC-CMs, no significant differences in contractile amplitude were observed in ventricular WT/TTNtv iPSC-CMs compared to WT/WT iPSC-CMs (Figure 4.3C). 4.4.4 TTNtv Impairs Calcium Transient Properties in Ventricular iPSC-CMs We next assessed the electrophysiological effects of the titin variant in atrial and ventricular iPSC-CMs. Under spontaneous conditions, we did not observe significant differences in any measured baseline electrophysiological parameters, including beat rate, rate-corrected APDs, and triangulation index, between WT/TTNtv and WT/WT iPSC-CMs of either cell type (Figure 4.4A and 4.4B). 100 Figure 4.4 Ventricular TTNtv iPSC-CMs exhibit shorter calcium transient durations. A, Spontaneous beat rate, rate-corrected action potential durations at 80% repolarization and 30% repolarization, and triangulation index in atrial iPSC-CMs (n = 4-6 differentiation batches). B, Spontaneous beat rate, rate-corrected action potential durations at 80% repolarization and 101 30% repolarization, and triangulation index in ventricular iPSC-CMs (n = 7-8 differentiation batches). C, Calcium transient durations at 80% repolarization and 30% repolarization in ventricular iPSC-CMs paced at 60 beats-per-minute (n = 7 differentiation batches). D, Action potential durations at 80% repolarization and 30% repolarization in ventricular iPSC-CMs paced at 60 beats-per-minute (n = 7 differentiation batches). E, Calcium transient durations at 80% repolarization and 30% repolarization in atrial iPSC-CMs paced at 120 beats-per-minute (n = 3-5 differentiation batches). F, Action potential durations at 80% repolarization and 30% repolarization in atrial iPSC-CMs paced at 120 beats-per-minute (n = 3-4 differentiation batches). Data are presented as mean ± SEM; Mann-Whitney U test. TTNtv indicates titin truncating variant; WT, wild-type; *P<0.05. The rate-corrected CaTDs were also comparable in spontaneously beating WT/TTNtv and WT/WT iPSC-CMs (Appendix Figure C.2B and C.2C). We then applied external electrical stimulation to assess electrophysiology under fixed pacing frequencies of 120 beats-per-minute for atrial iPSC-CMs and 60 beats-per-minute for ventricular iPSC-CMs. The CaTDs of paced ventricular WT/TTNtv iPSC-CMs were significantly different compared to WT/WT iPSC-CMs, suggesting an effect of the TTNtv on calcium handling (Figure 4.4C and Appendix Table C.6). The APDs of paced ventricular iPSC-CMs were not significantly different between WT/TTNtv and WT/WT genotypes (Figure 4.4D). Similarly, no significant differences were detected in the CaTDs (Figure 4.4E) nor the APDs (Figure 4.4F) between atrial WT/TTNtv and WT/WT iPSC-CMs. 102 4.4.5 TTNtv and the Risk of Pacing-Induced Arrhythmogenic Events in iPSC-CMs To further examine the effects of the TTNtv on the electrophysiological properties of atrial and ventricular iPSC-CMs, we electrically stimulated the cells using a dynamic pacing protocol to mimic increases in the heart rate that occurs during exercise. iPSC-CMs were initially paced at a frequency close to its spontaneous beat rate then subjected to stepwise increases in the pacing frequency up to 300 beats-per-minute for atrial cells or 200 beats-per-minute for ventricular cells. We observed arrhythmogenic events in the form of alternans and early-after depolarizations in atrial iPSC-CMs, with no differences in arrhythmogenic event-free survival regardless of titin variant genotype (Figure 4.5A). 103 Figure 4.5 Analysis of susceptibility to pacing-induced arrhythmia in atrial and ventricular iPSC-CMs. A, Arrhythmogenic event-free survival probability of atrial iPSC-CMs subjected to external pacing (n = 4-8 differentiation batches). Log-rank test. B, Arrhythmogenic event-free survival probability of ventricular iPSC-CMs subjected to external pacing (n = 4-5 differentiation batches). Log-rank test. C, Representative action potential and calcium transient traces of iPSC-CMs paced at 200 beats-per-minute showing normal electrophysiology without alternans (left) or voltage and calcium transient alternans (right). TTNtv indicates titin truncating variant; WT, wild-type. 104 Ventricular iPSC-CMs also exhibited arrhythmogenic events in the form of voltage or calcium transient alternans and missed beats when subjected to dynamic pacing (Figure 4.5B). The TTNtv appears to worsen arrhythmogenic event-free survival in ventricular WT/TTNtv iPSC-CMs compared to WT/WT iPSC-CMs. However, a statistically significant difference in event-free survival was not detected (P=0.078). Examples of normal action potential and calcium transient traces as well as alternans are shown in Figure 4.5C. 4.4.6 TTNtv Impairs Response to Isoproterenol Treatment in Ventricular iPSC-CMs TTNtv have been shown to downregulate β-adrenergic signalling genes in a ventricular iPSC-CM model of DCM.82 Since the VF patient experienced cardiac arrest during exercise, we hypothesized that the TTNtv may influence electrophysiological and contractile response to β-adrenergic receptor agonists which are released during exercise. We treated the atrial and ventricular iPSC-CMs with increasing doses of isoproterenol (vehicle control, 0.1 μM, 1 μM) and acquired voltage, calcium transient, and contractility recordings before drug treatment, 20 minutes post-treatment, and 20 minutes after drug washout. In spontaneously beating ventricular iPSC-CMs, no significant differences were observed in the beat rate of the WT/TTNtv iPSC-CMs compared to WT/WT iPSC-CMs (Appendix Figure C.3A). Contraction amplitudes were also comparable between WT/TTNtv and WT/WT iPSC-CMs treated with isoproterenol (Appendix Figure C.4). We observed a significant difference in APDs in ventricular iPSC-CMs treated with 1 μM isoproterenol (Figure 4.6A) as well as APDs at 30% repolarization in ventricular iPSC-CMs 105 treated with 0.1 μM isoproterenol after 20 minutes (Appendix Figure C.3B). Durations were significantly shorter in ventricular WT/TTNtv iPSC-CMs than the isogenic wild-type controls. Figure 4.6 Ventricular TTNtv iPSC-CMs show altered electrophysiological response to isoproterenol. 106 A, Action potential durations at 80% repolarization in ventricular iPSC-CMs treated with vehicle control, 0.1 μM isoproterenol, or 1 μM isoproterenol (n = 3-5 differentiation batches). B, Calcium transient durations at 80% repolarization in ventricular iPSC-CMs treated with vehicle control, 0.1 μM isoproterenol, or 1 μM isoproterenol in ventricular iPSC-CMs (n = 4-5 differentiation batches). iPSC-CMs were paced at 60 beats-per-minute. C, Rate-corrected action potential duration at 80% repolarization in atrial iPSC-CMs treated with vehicle control, 0.1 μM, or 1 μM isoproterenol (n = 1-3 differentiation batches). D, Rate-corrected calcium transient duration at 80% repolarization in atrial iPSC-CMs treated with vehicle control, 0.1 μM, or 1 μM isoproterenol (n = 1-3 differentiation batches). Mann-Whitney U test. TTNtv indicates titin truncating variant; WT, wild-type; *P<0.05. The ventricular WT/TTNtv iPSC-CMs also exhibited significantly shorter calcium transient durations at 80% repolarization through to 30% repolarization following treatment with 1 μM isoproterenol (Figure 4.6B). In atrial iPSC-CMs, no significant differences in the APDs (Figure 4.6C) and calcium transient durations (Figure 4.6D) were observed in WT/TTNtv iPSC-CMs compared to WT/WT iPSC-CMs. These findings suggest a ventricular-specific effect of the TTNtv on the electrophysiological response to β-adrenergic stimulation, leading to shorter action potential and calcium transient durations which may be pro-arrhythmic. 4.5 Discussion TTNtv are attributed to ~25% of familial DCM34 and have been associated with atrial and ventricular arrhythmias in cardiomyopathy patients.37,168,173 Recent genetic studies have also linked TTNtv to atrial and ventricular arrhythmias such as atrial fibrillation, atrial flutter, non- 107 sustained ventricular tachycardia, and cardiac dysrhythmia independent of a cardiomyopathy diagnosis.35,39,161 However, existing studies on the effects of TTNtv at the cellular or tissue level have primarily focused on TTNtv in ventricular models of DCM, and the underlying mechanisms by which TTNtv contribute to ventricular arrhythmias in the absence of structural disease remains unclear. In this study, we used human atrial and ventricular iPSC-CMs, CRISPR/Cas9 genome editing, and optical mapping to investigate the role of TTNtv in the pathogenesis of VF in a young patient without cardiomyopathy. TTNtv have been reported to weaken contractility in iPSC-derived DCM models. In contrast to existing literature,84,85 we showed that contractility is not impacted in TTNtv iPSC-CMs under baseline conditions nor upon pacing compared to isogenic controls. While contractile forces appear to be visually weaker in paced atrial TTNtv iPSC-CMs compared to WT iPSC-CMs, these results were not statistically significant. We had previously demonstrated an atrial-specific decrease in contractility caused by this TTNtv using an engineered heart tissue model of atrial fibrillation (Chapter 3). We hypothesized that this may be due to cell type-specific effects of the TTNtv and differential expression of contractile proteins in atrial and ventricular tissue.110 It is possible that the analysis here lacked sufficient power to detect a significant effect of the TTNtv on contractility and further studies using engineered heart tissue constructs are needed to determine this. In the presence of isoproterenol, changes in contractility were also not significantly different in TTNtv iPSC-CMs compared to isogenic controls. While these data do not agree with findings from TTNtv-induced DCM models that showed decreased contractility and weakened responses to isoproterenol they agree with isoproterenol experiments conducted using iPSC-derived engineered heart tissues of the atrial fibrillation patient with the same TTNtv 108 (Appendix Figure C.5). Furthermore, they reflect the patientâs clinical phenotype where cardiomyopathy was not detected through imaging and suggest subclinical ventricular myopathic remodelling may not be a contributing factor to arrhythmia in this patient. We found that ventricular TTNtv iPSC-CMs exhibit shorter calcium transient durations compared to WT iPSC-CMs. In contrast to ventricular models of TTNtv-induced DCM,82,85 APDs were not prolonged in ventricular TTNtv iPSC-CMs and were comparable to isogenic controls. The differences in the electrophysiological properties between iPSC-CM models of TTNtv-induced DCM compared to VF suggest that the mechanisms of arrhythmogenesis may be different between arrhythmias that precede or follow DCM. Atrial TTNtv iPSC-CMs also showed comparable beat rates and electrophysiology to isogenic controls. This finding agrees with our analysis of the effects of the TTNtv on APDs in an atrial fibrillation patient iPSC-CM model described in Chapter 3. Since the patient experienced sudden cardiac arrest and VF while exercising, we hypothesized that rapid heart rates or β-adrenergic signalling that occurs during exercise may be involved in arrhythmogenesis. We attempted to replicate these conditions by pacing the cells at fast frequencies and by treating the cells with the β-adrenergic agonist isoproterenol. Upon dynamic pacing, we observed a visual but not statistically significant difference in the arrhythmogenic event-free survival of ventricular TTNtv iPSC-CMs compared to WT iPSC-CMs. The atrial WT iPSC-CMs also exhibited pacing-induced arrhythmia, suggesting that the atrial cells of this patient may be sensitive to pacing regardless of the presence or absence of the TTNtv. Previous studies of TTNtv-associated DCM have reported impaired calcium handling during β-adrenergic stimulation and downregulation of β-adrenergic signalling genes.82,85 We found that iPSC-CMs treated with isoproterenol showed an expected 109 dose-dependent increase in beat rate and decrease in APDs and CaTDs in ventricular WT/TTNtv and WT/WT iPSC-CMs. Interestingly, the APDs and CaTDs were significantly shorter in ventricular WT/TTNtv compared to WT/WT iPSC-CMs after isoproterenol treatment, indicating a ventricular-specific effect of the TTNtv on action potential and calcium transient shortening in the presence of β-adrenergic stimulation. The APDs measured through optical mapping of ventricular cells reflect the QT interval on electrocardiograms. These results suggest β-adrenergic response may be impaired in the presence of TTNtv, and β-adrenergic stimulation may lead to greater QT shortening and shorter refractory periods in TTNtv carriers which may be arrhythmogenic by promoting re-entry rhythms. Further analyses on the effects of TTNtv on restitution properties and refractory periods are needed to compare the electrophysiological differences of atrial and ventricular TTNtv iPSC-CMs to WT/WT controls. Furthermore, studies testing the effects of TTNtv on iPSC-CM electrophysiology in the presence of beta-blocker treatment and rapid pacing or isoproterenol may help elucidate the efficacy of beta-blockade in preventing TTNtv-related arrhythmia. The TTNtv exerted cell type-specific effects on the electrophysiological properties of the iPSC-CMs which may have contributed to the patientâs ventricular disease phenotype. This study has several important limitations. The use of iPSC-CM monolayers as an in vitro model to investigate the TTNtv presents advantages over immortal cell lines or small animal models with differing relevancies to human health. However, iPSC-CMs are limited in their maturity which impacts the expression levels of various cardiac markers, including electrophysiological, contractile, and metabolic genes and proteins, that may play a role in VF arrhythmogenesis. Further studies employing more advanced in vitro models such as engineered 110 heart tissues and maturation techniques will improve our ability to study TTNtv and its contributions to VF. To assess contractility between TTNtv and WT iPSC-CM monolayers, we utilized MUSCLEMOTION, an imaging-based contractility analysis tool that has been validated against other methods such as optical flow analysis and post displacement. Despite its utility in measuring monolayer contractility and ease-of-use, MUSCLEMOTION may lack the sensitivity to detect small differences in the contractile response of WT/TTNtv and WT/WT iPSC-CMs to the concentrations of isoproterenol tested.171 Alternative force measurement methods such as post displacement measurements of atrial and ventricular engineered heart tissues under baseline conditions or during isoproterenol treatment can provide more accurate assessments of contractility and other parameters of interest such as contraction/relaxation velocities. Experiments testing more physiologically relevant β-adrenergic receptor agonists such as epinephrine (β1 and β2 adrenergic receptor agonist), norepinephrine (selective agonist of β1 adrenergic receptor over β2),174 and downstream factors are needed to understand how the TTNtv leads to altered cardiac electrophysiology. Here, we have demonstrated that the TTNtv of this VF patient leads to ventricular-specific electrophysiological abnormalities. However, the underlying mechanisms by which this TTNtv is contributing to alterations in action potential and calcium transient durations remain unknown and require further study. TTNtv have been associated with different myopathic and arrhythmic disease phenotypes with varying degrees of penetrance.35,38,39,173 The applicability of these findings may be limited to this patient and her specific genetic background or environmental context. More studies on other TTNtv associated with VF in the absence of cardiomyopathy are needed. 111 In summary, we investigated the effects of a heterozygous TTNtv identified in a VF patient using patient-specific atrial and ventricular iPSC-CMs. We observed shorter CaTDs in ventricular TTNtv iPSC-CMs compared to WT/WT iPSC-CMs. Under the application of electrical pacing, we found a trend towards poorer arrhythmogenic event-free survival in ventricular TTNtv iPSC-CMs paced at fast rates compared to isogenic controls. Furthermore, we showed that the TTNtv alters electrophysiological response in ventricular TTNtv iPSC-CMs treated with isoproterenol, resulting in shorter action potential and calcium transient durations compared to controls. Our findings suggest a link between TTNtv and electrophysiological abnormalities in ventricular cells that occur in the presence or absence of external stress which could contribute to the onset of VF. These findings broaden our knowledge of the functional abnormalities in atrial and ventricular iPSC-CM models of TTNtv in vitro and improve our understanding of the effects of TTNtv on atrial and ventricular cell types and ventricular arrhythmias. 112 Chapter 5: Conclusion 5.1 Summary AF and life-threatening ventricular arrhythmias can occur in individuals without known risk factors or a previous history of structural cardiomyopathies. In these patients, genetics is thought to be a potential contributor to disease. TTNtv, a well-established cause of DCM, has been linked to the development of atrial and ventricular arrhythmias, including early-onset AF and lone AF. The central objectives of this work were to assess the association between loss-of-function titin variants and increased risk of AF compared to modifiable risk factors and to examine the cellular effects of TTNtv identified in AF and VF patients without DCM. This work investigated several questions on TTNtv-associated arrhythmias that are of growing interest to clinicians and researchers in the cardiac field: are loss-of-function titin variants associated with increased risk of AF in patients without a clinical diagnosis of DCM or heart failure, and do AF patients with these variants experience worse clinical outcomes? Do titin variants add to the risk of AF in individuals with modifiable risk factors? Do TTNtv identified in arrhythmia patients cause the same functional perturbations in vitro as TTNtv linked to DCM? Do TTNtv affect the atria and ventricles differently? To address these questions, this dissertation utilized large-scale biobank data to investigate loss-of-function titin variants and AF at a population level as well as patient-specific iPSC-CM models to study a TTNtv identified in early-onset atrial and ventricular fibrillation without cardiomyopathy in vitro. The findings of this work are summarized here. Chapter 2 investigated whether loss-of-function titin variants increase the risk of AF, whether this risk is further increased by the presence of modifiable risk factors, and whether it leads to 113 worse outcomes in AF patients, using participant data from UK Biobank. We hypothesized that loss-of-function titin variants will lead to an increased risk of AF in the general population as well as in participants without DCM or heart failure, titin and modifiable risk factors will both increase AF incidence, and that AF patients with titin variants will experience worse clinical outcomes. We found significant associations between titin variant status and increased risk of AF. Among participants with a loss-of-function titin variant, having a modifiable risk factor such as hypertension further increases the risk of AF in an additive manner. Furthermore, we showed that AF patients with titin variants are more likely to experience incident DCM but not heart failure, composite cardiovascular events, stroke, or death. These data suggest that genetic testing for titin may improve AF risk stratification and inform on clinical management strategies, and individuals with titin variants may benefit from early preventative strategies targeting modifiable risk factors. Chapter 3 investigated the effects of a TTNtv identified in an early-onset AF patient without structural heart defects using patient-specific atrial and ventricular iPSC-CM and EHT models. We hypothesized that the TTNtv will lead to atrial-specific sarcomere disorganization, reduced contractility, titin haploinsufficiency and truncated titin expression, and abnormal electrophysiology similar to what is observed in TTNtv-associated DCM models. We found that the TTNtv resulted in sarcomere disarray, decreased titin protein expression, undetectable levels of truncated titin, and increased susceptibility to pacing induced arrhythmia in both atrial and ventricular iPSC-CMs. Atrial TTNtv EHTs displayed weakened contractility while ventricular EHTs were unaffected, indicating a cell-type specific effect of TTNtv on contractility. Furthermore, we demonstrated transcriptional changes that were more apparent in atrial EHTs 114 that indicate the possibility of adverse substrate remodelling. The results of this study suggest TTNtv lead to atrial structural and electrophysiological abnormalities that could contribute to the pathogenesis of AF. The finding that the TTNtv increases pacing-induced susceptibility to arrhythmogenic phenotypes suggests commonalities in the mechanism of atrial and ventricular arrhythmogenesis in TTNtv carriers. The reduction in full-length titin indicates a role of titin haploinsufficiency in disease. Since both atrial and ventricular cells exhibited disorganized sarcomere and reduced titin expression but only atrial EHTs showed reduced contractility, it is possible that the atrial cells were more affected by the TTNtv due to cell-type specific sarcomere protein expression. Chapter 4 expanded on our investigation of the TTNtv in Chapter 3 by examining the same variant in a patient with unexplained VF using atrial and ventricular iPSC-CMs. Here, we hypothesized that the TTNtv will lead to ventricular-specific contractile and electrophysiological defects as well as attenuated responses to β-adrenergic stimulation based on findings from TTNtv-associated DCM studies. In contrast to TTNtv-associated DCM studies which showed decreased contractile force and action potential prolongation, contractile defects and action potential prolongation were not observed, suggesting unique effects of TTNtv on contractility and electrophysiology in different cardiac diseases and the possibility of different pathophysiology of arrhythmias that occur in the presence or absence of structural disease. Importantly, we observed significantly shorter calcium transients at baseline as well as action potential and calcium transient shortening under β-adrenergic stimulation in ventricular TTNtv iPSC-CMs compared to wild-type. TTNtv did not alter the electrophysiology of atrial iPSC-CMs compared to controls. These data suggest that 1) TTNtv can lead to cell type-specific 115 electrophysiological defects at baseline and alter β-adrenergic response in ventricular cells, and 2) patients with the same TTNtv may present with different clinical phenotypes that correlate with different functional abnormalities observed in patient-specific iPSC-CM models. 5.2 Limitations and Future Directions There are several limitations and future directions of this work that should be considered. To assess the association between titin and risk of AF, we used genetic, clinical, and demographic data from UK Biobank. Due to the âhealthy volunteer biasâ,138 disease prevalences are lower in UK Biobank and we were unable to examine the effects of TTNtv in the presence of other clinical risk factors of AF such as hyperthyroidism or valvular heart disease due to the limited number of participants with these diseases. Furthermore, we were underpowered to examine interaction effects between titin variants and modifiable risk factors. Lastly, the majority of participants in UK Biobank are of white British/European ancestry which may limit the generalizability of these findings. Future studies validating these findings in a larger and more diverse population cohort are needed. To assess the cellular effects of TTNtv in arrhythmia, we utilized patient-specific iPSC-CMs and EHT constructs. hPSC-CM differentiation protocols typically generate a mixture of cell types. Furthermore, iPSC-CMs exhibit fetal-like electrophysiological and contractile properties compared to human adult cardiac tissue. We improved the purity and maturity of the iPSC-CMs by subjecting the cells to metabolic selection and long-term maintenance and by generating EHT constructs. While EHTs are more mature than iPSC-CMs, they still display less mature electrophysiological and structural properties compared to human adult cardiac tissue,120,121 116 including prolonged APDs, increased sensitivity to the development of early-after depolarizations, and less developed t-tubules. Other maturation methods that could be implemented include glucose-depletion with fatty acid supplementation,175 thyroid and glucocorticoid hormone supplementation,176 mechanical stress,177 or co-culture of cardiomyocytes with other cardiac cell types.178 Studies incorporating additional maturation strategies are needed to examine TTNtv in more physiologically relevant models and broaden the applicability of the study findings. TTNtv have been demonstrated to increase myocardial fibrosis in the hearts of DCM patients as well as atrial fibrosis in a zebrafish model. We used bulk RNA-seq to assess transcriptional changes in extracellular matrix factors such as collagens. However, the effects of TTNtv on extracellular matrix expression at the protein level remains unclear and further studies are needed to examine its fibrotic effects. Methods such as immunostaining, Western blotting, or mass spectrometry can be employed to analyze protein expression. In addition, co-culturing cardiomyocytes with cardiac fibroblasts in EHT constructs can enable the analysis of fibroblast activation in the presence of TTNtv. We were unable to examine a number of key properties of titin that may be impacted by the TTNtv due to limitations of the EHT model. The EHTs are attached to two flexible posts that allow us to measure auxotonic contractile properties. We were unable to stretch the tissue beyond the distance between the two posts to analyze passive tension or modify sarcomere lengths to measure length-dependent active force generation. Further studies using more appropriate models or techniques that permit controlled tissue lengthening or adjustable 117 preload179 are needed to comprehensively assess the contractile and mechanosensing effects of TTNtv. This dissertation focused on characterizing the structural and functional abnormalities in atrial and ventricular cardiomyocytes with a TTNtv that was identified in an AF patient and a VF patient. TTNtv demonstrate incomplete penetrance for arrhythmias and cardiomyopathies and can lead to a variety of clinical phenotypes ranging from the cardiac to skeletal disorders. The TTNtv investigated here is associated with different clinical diagnoses and led to different cellular phenotypes in patient-specific models, suggesting that mechanisms underlying arrhythmogenesis may be distinct in each patient for each variant. More studies of different TTNtv in different genetic contexts will improve our understanding of the role of TTNtv in arrhythmogenesis. Importantly, additional studies investigating the mechanistic link between TTNtv to these phenotypes are needed to develop novel therapeutic strategies for TTNtv-related arrhythmias. 5.3 Conclusions TTNtv have been associated with increased risk of arrhythmias. However, key questions remain regarding titinâs role in the pathophysiology of arrhythmias without cardiomyopathy. This work examined the interplay between titin, modifiable risk factors, and increased risk of AF using the UK Biobank study. We showed that loss-of-function titin variants increase the risk of AF beyond pre-existing modifiable risk factors in an additive manner and increase the risk of DCM following AF onset. These findings raise the possibility that titin-associated AF may increase healthcare costs and utilization due to worse patient outcomes compared to non-titin related AF 118 cases. Furthermore, these findings support the implementation of early genetic screening programs to identify titin variant carriers prior to the development of other risk factors and the onset of AF. While titin variant status is a non-modifiable risk factor known modifiable clinical and behavioral factors can be targeted in variant carriers to reduce overall AF risk. This work identified and investigated a single TTNtv implicated in AF and VF using patient-specific atrial and ventricular iPSC-CM models. The TTNtv led to distinct phenotypic and functional defects such as sarcomere disorganization, reduced contractility, increased susceptibility to pacing-induced arrhythmias, and transcriptional evidence of substrate remodelling in the atrial cells of the AF patient as well as calcium transient and action potential shortening under β-adrenergic stimulation in the ventricular cells of the VF patient (Figure 5.1). Figure 5.1 Effects of the TTNtv in iPSC-CM models of atrial and ventricular fibrillation. 119 Phenotypic and functional defects observed in patient-specific iPSC-CM models of atrial fibrillation (Chapter 3) and ventricular fibrillation (Chapter 4). AF indicates atrial fibrillation; EP, electrophysiology; ECM, extracellular matrix; VF, ventricular fibrillation. There are key implications of these findings regarding the pathogenesis of TTNtv-associated arrhythmias. Most studies to date have focused on TTNtv-associated DCM and ventricular tissue, but it is likely that different mechanisms contribute to the pathogenesis of arrhythmias that occur in the absence of cardiomyopathy, especially AF due to cell type differences between atrial and ventricular cardiomyocytes. Thus, existing data from TTNtv-associated DCM studies may not be applicable to TTNtv-associated arrhythmias. The results of this work showed the phenotypic defects caused by an arrhythmia-associated TTNtv differs from that of DCM and differs between TTNtv-associated AF and VF models. In contrast to the DCM studies, action potential prolongation was not observed in either the AF or VF models, suggesting that it is not a contributor to arrhythmogenesis in TTNtv-associated AF and VF that present without cardiomyopathy. Instead, cell-type specific decreases in atrial contractility in the AF model and ventricular calcium transient shortening in the VF model suggest the TTNtv may lead to structural alterations, conduction abnormalities, and reduced refractoriness which can promote re-entry and contribute to arrhythmogenesis of AF or VF. Despite being a sarcomere protein, the effects of the TTNtv extended beyond contractile dysfunction and impacted the electrophysiological properties of atrial and ventricular cardiomyocytes. This adds to our current understanding of the role of titin in the heart and raises the possibility that other structural proteins may contribute to the pathogenesis of AF. Broadening the repertoire of genes that are 120 sequenced when performing genetic screening in lone AF patients could lead to the identification of unreported structural genes and variants associated with AF. The TTNtv exhibited similar effects on some parameters in atrial and ventricular cardiomyocytes, such as sarcomere disorganization and susceptibility to pacing-induced arrhythmias, indicating a baseline level of pathology in both cell types. However, the observed cell type-specific abnormalities indicate the TTNtv can have chamber-specific effects that contribute to the pathogenesis of different arrhythmias in different individuals. This work advances our knowledge of titin in atrial cardiomyocytes and demonstrates the need for examining TTNtv using both atrial and ventricular in vitro models. This work showed the same TTNtv can be associated with different clinical and cellular phenotypes which suggests that other arrhythmogenic factors may exist and impact the type of arrhythmia or cardiac disease that is first presented in a TTNtv carrier. Accurate risk stratification of TTNtv carriers is challenging due to incomplete disease penetrance and the wide range of cardiac diseases linked to TTNtv. This work adds to our understanding of the variable disease phenotypes associated with a TTNtv in A-band titin that underlies the pathogenesis of atrial and ventricular arrhythmias. In summary, this work highlights the advantages of implementing genetic testing for patient risk stratification and preventative risk factor management, demonstrates the utility of patient-specific atrial and ventricular iPSC-CM and EHT models for investigating the cellular effects of pathogenic variants associated with arrhythmia, and provides evidence of arrhythmogenic phenotypes that may contribute to the pathogenesis of AF or VF in TTNtv carriers. 121 References 1. Wang K, McClure J, Tu A. Titin: major myofibrillar components of striated muscle. Proc Natl Acad Sci U S A. 1979;76(8):3698-3702. doi:10.1073/pnas.76.8.3698 2. Bang ML, Centner T, Fornoff F, et al. The complete gene sequence of titin, expression of an unusual â700-kDa titin isoform, and its interaction with obscurin identify a novel Z-line to I-band linking system. Circ Res. 2001;89(11):1065-1072. doi:10.1161/hh2301.100981 3. Loescher CM, Hobbach AJ, Linke WA. Titin (TTN): from molecule to modifications, mechanics, and medical significance. Cardiovasc Res. 2022;118(14):2903-2918. doi:10.1093/cvr/cvab328 4. Makarenko I, Opitz CA, Leake MC, et al. Passive stiffness changes caused by upregulation of compliant titin isoforms in human dilated cardiomyopathy hearts. Circ Res. 2004;95(7):708-716. doi:10.1161/01.RES.0000143901.37063.2f 5. Tamborrini D, Wang Z, Wagner T, et al. Structure of the native myosin filament in the relaxed cardiac sarcomere. Nature. 2023;623(7988):863-871. doi:10.1038/s41586-023-06690-5 6. Lahmers S, Wu Y, Call DR, Labeit S, Granzier H. Developmental Control of Titin Isoform Expression and Passive Stiffness in Fetal and Neonatal Myocardium. Circ Res. 2004;94(4):505-513. doi:10.1161/01.RES.0000115522.52554.86 7. Warren CM, Krzesinski PR, Campbell KS, Moss RL, Greaser ML. Titin isoform changes in rat myocardium during development. Mech Dev. 2004;121(11):1301-1312. doi:10.1016/j.mod.2004.07.003 122 8. Zou J, Tran D, Baalbaki M, et al. An internal promoter underlies the difference in disease severity between N- and C-terminal truncation mutations of Titin in zebrafish. Elife. 2015;4:e09406. doi:10.7554/eLife.09406 9. Trombitás K, Redkar A, Centner T, Wu Y, Labeit S, Granzier H. Extensibility of isoforms of cardiac titin: variation in contour length of molecular subsegments provides a basis for cellular passive stiffness diversity. Biophys J. 2000;79(6):3226-3234. doi:10.1016/S0006-3495(00)76555-6 10. Granzier HL, Hutchinson KR, Tonino P, et al. Deleting titinâs I-band/A-band junction reveals critical roles for titin in biomechanical sensing and cardiac function. Proc Natl Acad Sci U S A. 2014;111(40):14589-14594. doi:10.1073/pnas.1411493111 11. Bogomolovas J, Gasch A, Simkovic F, Rigden DJ, Labeit S, Mayans O. Titin kinase is an inactive pseudokinase scaffold that supports MuRF1 recruitment to the sarcomeric M-line. Open Biol. 2014;4(5):140041. doi:10.1098/rsob.140041 12. Cazorla O, Freiburg A, Helmes M, et al. Differential Expression of Cardiac Titin Isoforms and Modulation of Cellular Stiffness. Circ Res. 2000;86(1):59-67. doi:10.1161/01.RES.86.1.59 13. Nagueh SF, Shah G, Wu Y, et al. Altered titin expression, myocardial stiffness, and left ventricular function in patients with dilated cardiomyopathy. Circulation. 2004;110(2):155-162. doi:10.1161/01.CIR.0000135591.37759.AF 14. Krüger M, Kötter S, Grützner A, et al. Protein kinase G modulates human myocardial passive stiffness by phosphorylation of the titin springs. Circ Res. 2009;104(1):87-94. doi:10.1161/CIRCRESAHA.108.184408 123 15. Fukuda N, Wu Y, Nair P, Granzier HL. Phosphorylation of titin modulates passive stiffness of cardiac muscle in a titin isoform-dependent manner. J Gen Physiol. 2005;125(3):257-271. doi:10.1085/jgp.200409177 16. Herwig M, Kolijn D, Lódi M, et al. Modulation of Titin-Based Stiffness in Hypertrophic Cardiomyopathy via Protein Kinase D. Front Physiol. 2020;11:240. doi:10.3389/fphys.2020.00240 17. Hamdani N, Krysiak J, Kreusser MM, et al. Crucial role for Ca2(+)/calmodulin-dependent protein kinase-II in regulating diastolic stress of normal and failing hearts via titin phosphorylation. Circ Res. 2013;112(4):664-674. doi:10.1161/CIRCRESAHA.111.300105 18. Hidalgo C, Hudson B, Bogomolovas J, et al. PKC Phosphorylation of Titinâs PEVK Element. Circ Res. 2009;105(7):631-638. doi:10.1161/CIRCRESAHA.109.198465 19. Grützner A, Garcia-Manyes S, Kötter S, Badilla CL, Fernandez JM, Linke WA. Modulation of titin-based stiffness by disulfide bonding in the cardiac titin N2-B unique sequence. Biophys J. 2009;97(3):825-834. doi:10.1016/j.bpj.2009.05.037 20. Alegre-Cebollada J, Kosuri P, Giganti D, et al. S-glutathionylation of cryptic cysteines enhances titin elasticity by blocking protein folding. Cell. 2014;156(6):1235-1246. doi:10.1016/j.cell.2014.01.056 21. Lin YH, Major JL, Liebner T, et al. HDAC6 modulates myofibril stiffness and diastolic function of the heart. J Clin Invest. 2022;132(10):e148333. doi:10.1172/JCI148333 22. Brunello E, Fusi L. Regulating Striated Muscle Contraction: Through Thick and Thin. Annu Rev Physiol. 2024;86:255-275. doi:10.1146/annurev-physiol-042222-022728 124 23. Ma W, Henze M, Anderson RL, et al. The Super-Relaxed State and Length Dependent Activation in Porcine Myocardium. Circ Res. 2021;129(6):617-630. doi:10.1161/CIRCRESAHA.120.318647 24. Hessel AL, Ma W, Mazara N, et al. Titin force in muscle cells alters lattice order, thick and thin filament protein formation. Proc Natl Acad Sci U S A. 2022;119(48):e2209441119. doi:10.1073/pnas.2209441119 25. Granzier HL, Labeit S. Discovery of Titin and Its Role in Heart Function and Disease. Circ Res. 2025;136(1):135-157. doi:10.1161/CIRCRESAHA.124.323051 26. Sun Y, Liu X, Huang W, Le S, Yan J. Structural domain in the Titin N2B-us region binds to FHL2 in a force-activation dependent manner. Nat Commun. 2024;15(1):4496. doi:10.1038/s41467-024-48828-7 27. Strom J, Bull M, Gohlke J, et al. Titinâs cardiac-specific N2B element is critical to mechanotransduction during volume overload of the heart. J Mol Cell Cardiol. 2024;191:40-49. doi:10.1016/j.yjmcc.2024.04.006 28. Ojima K, Kawabata Y, Nakao H, et al. Dynamic distribution of muscle-specific calpain in mice has a key role in physical-stress adaptation and is impaired in muscular dystrophy. J Clin Invest. 2010;120(8):2672-2683. doi:10.1172/JCI40658 29. Miller MK, Bang ML, Witt CC, et al. The muscle ankyrin repeat proteins: CARP, ankrd2/Arpp and DARP as a family of titin filament-based stress response molecules. J Mol Biol. 2003;333(5):951-964. doi:10.1016/j.jmb.2003.09.012 30. Witt CC, Ono Y, Puschmann E, et al. Induction and myofibrillar targeting of CARP, and suppression of the Nkx2.5 pathway in the MDM mouse with impaired titin-based signaling. J Mol Biol. 2004;336(1):145-154. doi:10.1016/j.jmb.2003.12.021 125 31. Chopra A, Kutys ML, Zhang K, et al. Force Generation via β-Cardiac Myosin, Titin, and α-Actinin Drives Cardiac Sarcomere Assembly from Cell-Matrix Adhesions. Dev Cell. 2018;44(1):87-96.e5. doi:10.1016/j.devcel.2017.12.012 32. Zaunbrecher RJ, Abel AN, Beussman K, et al. Cronos titin is expressed in human cardiomyocytes and necessary for normal sarcomere function. Circulation. 2019;140(20):1647-1660. doi:10.1161/CIRCULATIONAHA.119.039521 33. Tonino P, Kiss B, Strom J, et al. The giant protein titin regulates the length of the striated muscle thick filament. Nat Commun. 2017;8(1):1041. doi:10.1038/s41467-017-01144-9 34. Herman DS, Lam L, Taylor MRG, et al. Truncations of Titin Causing Dilated Cardiomyopathy. N Engl J Med. 2012;366(7):619-628. doi:10.1056/NEJMoa1110186 35. Ahlberg G, Refsgaard L, Lundegaard PR, et al. Rare truncating variants in the sarcomeric protein titin associate with familial and early-onset atrial fibrillation. Nat Commun. 2018;9(1):4316. doi:10.1038/s41467-018-06618-y 36. Verdonschot JAJ, Hazebroek MR, Derks KWJ, et al. Titin cardiomyopathy leads to altered mitochondrial energetics, increased fibrosis and long-term life-threatening arrhythmias. Eur Heart J. 2018;39(10):864-873. doi:10.1093/eurheartj/ehx808 37. Corden B, Jarman J, Whiffin N, et al. Association of Titin-Truncating Genetic Variants With Life-threatening Cardiac Arrhythmias in Patients With Dilated Cardiomyopathy and Implanted Defibrillators. JAMA Netw Open. 2019;2(6):e196520. doi:10.1001/jamanetworkopen.2019.6520 38. Choi SH, Weng L chen, Roselli C, et al. Association Between Titin Loss-of-Function Variants and Early-Onset Atrial Fibrillation. JAMA. 2018;320(22):2354. doi:10.1001/jama.2018.18179 126 39. Haggerty CM, Damrauer SM, Levin MG, et al. Genomics-First Evaluation of Heart Disease Associated With Titin-Truncating Variants. Circulation. 2019;140(1):42-54. doi:10.1161/CIRCULATIONAHA.119.039573 40. Peled Y, Gramlich M, Yoskovitz G, et al. Titin Mutation in Familial Restrictive Cardiomyopathy. Int J Cardiol. 2014;171(1):24-30. doi:10.1016/j.ijcard.2013.11.037 41. Domínguez F, Lalaguna L, Martínez-Martín I, et al. Titin Missense Variants as a Cause of Familial Dilated Cardiomyopathy. Circulation. 2023;147(22):1711-1713. doi:10.1161/CIRCULATIONAHA.122.062833 42. Golbus JR, Puckelwartz MJ, Fahrenbach JP, Dellefave-Castillo LM, Wolfgeher D, McNally EM. Population-Based Variation in Cardiomyopathy Genes. Circ Cardiovasc Genet. 2012;5(4):391-399. doi:10.1161/CIRCGENETICS.112.962928 43. Roberts AM, Ware JS, Herman DS, et al. Integrated allelic, transcriptional, and phenomic dissection of the cardiac effects of titin truncations in health and disease. Sci Transl Med. 2015;7(270):270ra6-270ra6. doi:10.1126/scitranslmed.3010134 44. Pirruccello JP, Bick A, Chaffin M, et al. Titin Truncating Variants in Adults Without Known Congestive Heart Failure. J Am Coll Cardiol. 2020;75(10):1239-1241. doi:10.1016/j.jacc.2020.01.013 45. Akinrinade O, Koskenvuo JW, Alastalo TP. Prevalence of Titin Truncating Variants in General Population. PLoS One. 2015;10(12):e0145284. doi:10.1371/journal.pone.0145284 46. Shetty NS, Pampana A, Patel N, Li P, Arora G, Arora P. High-proportion spliced-in titin truncating variants in African and European ancestry in the All of Us Research Program. Nat Cardiovasc Res. 2024;3(2):140-144. doi:10.1038/s44161-023-00417-5 127 47. Miller DT, Lee K, Chung WK, et al. ACMG SF v3.0 list for reporting of secondary findings in clinical exome and genome sequencing: a policy statement of the American College of Medical Genetics and Genomics (ACMG). Genet Med. 2021;23(8):1381-1390. doi:10.1038/s41436-021-01172-3 48. Miller DT, Lee K, Abul-Husn NS, et al. ACMG SF v3.2 list for reporting of secondary findings in clinical exome and genome sequencing: A policy statement of the American College of Medical Genetics and Genomics (ACMG). Genet Med. 2023;25(8):100866. doi:10.1016/j.gim.2023.100866 49. Walsh R, Thomson KL, Ware JS, et al. Reassessment of Mendelian gene pathogenicity using 7,855 cardiomyopathy cases and 60,706 reference samples. Genet Med. 2017;19(2):192-203. doi:10.1038/gim.2016.90 50. Shah RA, Asatryan B, Sharaf Dabbagh G, et al. Frequency, Penetrance, and Variable Expressivity of Dilated Cardiomyopathy-Associated Putative Pathogenic Gene Variants in UK Biobank Participants. Circulation. 2022;146(2):110-124. doi:10.1161/CIRCULATIONAHA.121.058143 51. McGurk KA, Zhang X, Theotokis P, et al. The penetrance of rare variants in cardiomyopathy-associated genes: A cross-sectional approach to estimating penetrance for secondary findings. Am J Hum Genet. 2023;110(9):1482-1495. doi:10.1016/j.ajhg.2023.08.003 52. Anderson JL, Christensen GB, Escobar H, et al. Discovery of TITIN Gene Truncating Variant Mutations and 5-Year Outcomes in Patients With Nonischemic Dilated Cardiomyopathy. Am J Cardiol. 2020;137:97-102. doi:10.1016/j.amjcard.2020.09.026 128 53. Henkens MTHM, Raafs AG, Vanloon T, et al. Left Atrial Function in Patients with Titin Cardiomyopathy. J Card Fail. 2024;30(1):51-60. doi:10.1016/j.cardfail.2023.05.013 54. Roth GA, Mensah GA, Johnson CO, et al. Global Burden of Cardiovascular Diseases and Risk Factors, 1990-2019: Update From the GBD 2019 Study. J Am Coll Cardiol. 2020;76(25):2982-3021. doi:10.1016/j.jacc.2020.11.010 55. Thrall G, Lane D, Carroll D, Lip GYH. Quality of Life in Patients with Atrial Fibrillation: A Systematic Review. Am J Med. 2006;119(5):448.e1-448.e19. doi:10.1016/j.amjmed.2005.10.057 56. Marini C, De Santis F, Sacco S, et al. Contribution of Atrial Fibrillation to Incidence and Outcome of Ischemic Stroke: Results From a Population-Based Study. Stroke. 2005;36(6):1115-1119. doi:10.1161/01.STR.0000166053.83476.4a 57. Stewart S, Hart CL, Hole DJ, McMurray JJV. A population-based study of the long-term risks associated with atrial fibrillation: 20-year follow-up of the Renfrew/Paisley study. Am J Med. 2002;113(5):359-364. doi:10.1016/S0002-9343(02)01236-6 58. Kazi DS, Elkind MS V, Deutsch A, et al. Forecasting the Economic Burden of Cardiovascular Disease and Stroke in the United States Through 2050: A Presidential Advisory From the American Heart Association. Circulation. 2024;150(4):e89-e101. doi:10.1161/CIR.0000000000001258 59. Nattel S, Heijman J, Zhou L, Dobrev D. Molecular Basis of Atrial Fibrillation Pathophysiology and Therapy: A Translational Perspective. Circ Res. 2020;127(1):51-72. doi:10.1161/CIRCRESAHA.120.316363 60. Gemel J, Levy AE, Simon AR, et al. Connexin40 abnormalities and atrial fibrillation in the human heart. J Mol Cell Cardiol. 2014;76:159-168. doi:10.1016/j.yjmcc.2014.08.021 129 61. Andrade JG, Aguilar M, Atzema C, et al. The 2020 Canadian Cardiovascular Society/Canadian Heart Rhythm Society Comprehensive Guidelines for the Management of Atrial Fibrillation. Can J Cardiol. 2020;36(12):1847-1948. doi:10.1016/j.cjca.2020.09.001 62. Benjamin EJ, Levy D, Vaziri SM, DâAgostino RB, Belanger AJ, Wolf PA. Independent risk factors for atrial fibrillation in a population-based cohort: The Framingham Heart Study. JAMA. 1994;271(11):840-844. doi:10.1001/jama.1994.03510350050036 63. Khera AV, Chaffin M, Aragam KG, et al. Genome-wide polygenic scores for common diseases identify individuals with risk equivalent to monogenic mutations. Nat Genet. 2018;50(9):1219-1224. doi:10.1038/s41588-018-0183-z 64. Alonso A, Krijthe BP, Aspelund T, et al. Simple risk model predicts incidence of atrial fibrillation in a racially and geographically diverse population: the CHARGE-AF consortium. J Am Heart Assoc. 2013;2(2):e000102. doi:10.1161/JAHA.112.000102 65. Chen YH, Xu SJ, Bendahhou S, et al. KCNQ1 gain-of-function mutation in familial atrial fibrillation. Science (1979). 2003;299(5604):251-254. doi:10.1126/science.1077771 66. Hodgson-Zingman DM, Karst ML, Zingman L V, et al. Atrial natriuretic peptide frameshift mutation in familial atrial fibrillation. N Engl J Med. 2008;359(2):158-165. doi:10.1056/NEJMoa0706300 67. Orr N, Arnaout R, Gula LJ, et al. A mutation in the atrial-specific myosin light chain gene (MYL4) causes familial atrial fibrillation. Nat Commun. 2016;7:11303. doi:10.1038/ncomms11303 130 68. Gudbjartsson DF, Holm H, Sulem P, et al. A frameshift deletion in the sarcomere gene MYL4 causes early-onset familial atrial fibrillation. Eur Heart J. 2017;38(1):27-34. doi:10.1093/eurheartj/ehw379 69. Narayan SM, Wang PJ, Daubert JP. New Concepts in Sudden Cardiac Arrest to Address an Intractable Epidemic: JACC State-of-the-Art Review. J Am Coll Cardiol. 2019;73(1):70-88. doi:10.1016/j.jacc.2018.09.083 70. Wu J, Nadarajah R, Nakao YM, et al. Temporal trends and patterns in atrial fibrillation incidence: A population-based study of 3.4 million individuals. Lancet Reg Health Eur. 2022;17:100386. doi:10.1016/j.lanepe.2022.100386 71. Rea TD, Eisenberg MS, Sinibaldi G, White RD. Incidence of EMS-treated out-of-hospital cardiac arrest in the United States. Resuscitation. 2004;63(1):17-24. doi:10.1016/j.resuscitation.2004.03.025 72. Atwood C, Eisenberg MS, Herlitz J, Rea TD. Incidence of EMS-treated out-of-hospital cardiac arrest in Europe. Resuscitation. 2005;67(1):75-80. doi:10.1016/j.resuscitation.2005.03.021 73. Al-Khatib SM, Stevenson WG, Ackerman MJ, et al. 2017 AHA/ACC/HRS Guideline for Management of Patients With Ventricular Arrhythmias and the Prevention of Sudden Cardiac Death: A Report of the American College of Cardiology/American Heart Association Task Force on Clinical Practice Guidelines and the Heart Rhythm Society. Circulation. 2018;138(13):e272-e391. doi:10.1161/CIR.0000000000000549 74. Verheul LM, van der Ree MH, Groeneveld SA, et al. The genetic basis of apparently idiopathic ventricular fibrillation: a retrospective overview. Europace. 2023;25(11):euad336. doi:10.1093/europace/euad336 131 75. Bergeman AT, Hoeksema WF, van der Ree MH, et al. Outcomes in Dutch DPP6 risk haplotype for familial idiopathic ventricular fibrillation: a focused update. Neth Heart J. 2023;31(7-8):309-314. doi:10.1007/s12471-023-01792-1 76. Low SK, Takahashi A, Ebana Y, et al. Identification of six new genetic loci associated with atrial fibrillation in the Japanese population. Nat Genet. 2017;49(6):953-958. doi:10.1038/ng.3842 77. Christophersen IE, Rienstra M, Roselli C, et al. Large-scale analyses of common and rare variants identify 12 new loci associated with atrial fibrillation. Nat Genet. 2017;49(6):946-952. doi:10.1038/ng.3843 78. Nielsen JB, Fritsche LG, Zhou W, et al. Genome-wide Study of Atrial Fibrillation Identifies Seven Risk Loci and Highlights Biological Pathways and Regulatory Elements Involved in Cardiac Development. Am J Hum Genet. 2018;102(1):103-115. doi:10.1016/j.ajhg.2017.12.003 79. Vikhorev PG, Smoktunowicz N, Munster AB, et al. Abnormal contractility in human heart myofibrils from patients with dilated cardiomyopathy due to mutations in TTN and contractile protein genes. Sci Rep. 2017;7(1):14829. doi:10.1038/s41598-017-13675-8 80. McAfee Q, Chen CY, Yang Y, et al. Truncated titin proteins in dilated cardiomyopathy. Sci Transl Med. 2021;13(618):eabd7287. doi:10.1126/scitranslmed.abd7287 81. Fomin A, Gärtner A, Cyganek L, et al. Truncated titin proteins and titin haploinsufficiency are targets for functional recovery in human cardiomyopathy due to TTN mutations. Sci Transl Med. 2021;13(618):eabd3079. doi:10.1126/scitranslmed.abd3079 132 82. Huang G, Bisaria A, Wakefield DL, et al. Titin-truncating variants in hiPSC cardiomyocytes induce pathogenic proteinopathy and sarcomere defects with preserved core contractile machinery. Stem Cell Reports. 2023;18(1):220-236. doi:10.1016/j.stemcr.2022.11.008 83. Kellermayer D, Tordai H, Kiss B, et al. Truncated titin is structurally integrated into the human dilated cardiomyopathic sarcomere. J Clin Invest. 2024;134(2):e169753. doi:10.1172/JCI169753 84. Hinson JT, Chopra A, Nafissi N, et al. Titin mutations in iPS cells define sarcomere insufficiency as a cause of dilated cardiomyopathy. Science (1979). 2015;349(6251):982-986. doi:10.1126/science.aaa5458 85. Schick R, Mekies LN, Shemer Y, et al. Functional abnormalities in induced Pluripotent Stem Cell-derived cardiomyocytes generated from titin-mutated patients with dilated cardiomyopathy. Aalto-Setala K, ed. PLoS One. 2018;13(10):e0205719. doi:10.1371/journal.pone.0205719 86. Antzelevitch C, Burashnikov A. Overview of Basic Mechanisms of Cardiac Arrhythmia. Card Electrophysiol Clin. 2011;3(1):23-45. doi:10.1016/j.ccep.2010.10.012 87. Thomson JA, Itskovitz-Eldor J, Shapiro SS, et al. Embryonic stem cell lines derived from human blastocysts. Science (1979). 1998;282(5391):1145-1147. doi:10.1126/science.282.5391.1145 88. Takahashi K, Tanabe K, Ohnuki M, et al. Induction of Pluripotent Stem Cells from Adult Human Fibroblasts by Defined Factors. Cell. 2007;131(5):861-872. doi:10.1016/j.cell.2007.11.019 133 89. Lian X, Zhang J, Azarin SM, et al. Directed cardiomyocyte differentiation from human pluripotent stem cells by modulating Wnt/β-catenin signaling under fully defined conditions. Nat Protoc. 2013;8(1):162-175. doi:10.1038/nprot.2012.150 90. Burridge PW, Matsa E, Shukla P, et al. Chemically defned generation of human cardiomyocytes. Nat Methods. 2014;11(8):855-860. doi:10.1038/nMeth.2999 91. Halloin C, Schwanke K, Löbel W, et al. Continuous WNT Control Enables Advanced hPSC Cardiac Processing and Prognostic Surface Marker Identification in Chemically Defined Suspension Culture. Stem Cell Reports. 2019;13(2):366-379. doi:10.1016/j.stemcr.2019.06.004 92. Garg P, Garg V, Shrestha R, Sanguinetti MC, Kamp TJ, Wu JC. Human induced pluripotent stem cell-derived cardiomyocytes as models for cardiac channelopathies: A primer for non-electrophysiologists. Circ Res. 2018;123(2):224-243. doi:10.1161/CIRCRESAHA.118.311209 93. Blackwell DJ, Schmeckpeper J, Knollmann BC. Animal Models to Study Cardiac Arrhythmias. Circ Res. 2022;130(12):1926-1964. doi:10.1161/CIRCRESAHA.122.320258 94. Bistola V, Nikolopoulou M, Derventzi A, et al. Long-term primary cultures of human adult atrial cardiac myocytes: Cell viability, structural properties and BNP secretion in vitro. Int J Cardiol. 2008;131(1):113-122. doi:10.1016/j.ijcard.2007.10.058 95. Guo G ran, Chen L, Rao M, Chen K, Song J ping, Hu S shou. A modified method for isolation of human cardiomyocytes to model cardiac diseases. J Transl Med. 2018;16(1):288. doi:10.1186/s12967-018-1649-6 134 96. Bergmann O, Bhardwaj RD, Bernard S, et al. Evidence for Cardiomyocyte Renewal in Humans. Science (1979). 2009;324(5923):98-102. doi:10.1126/science.1164680 97. Laksman Z, Wauchop M, Lin E, et al. Modeling Atrial Fibrillation using Human Embryonic Stem Cell-Derived Atrial Tissue. Sci Rep. 2017;7(1):5268. doi:10.1038/s41598-017-05652-y 98. Moretti A, Bellin M, Welling A, et al. Patient-specific induced pluripotent stem-cell models for long-QT syndrome. N Engl J Med. 2010;363(15):1397-1409. doi:10.1056/NEJMoa0908679 99. Itzhaki I, Maizels L, Huber I, et al. Modelling the long QT syndrome with induced pluripotent stem cells. Nature. 2011;471(7337):225-230. doi:10.1038/nature09747 100. Lahti AL, Kujala VJ, Chapman H, et al. Model for long QT syndrome type 2 using human iPS cells demonstrates arrhythmogenic characteristics in cell culture. Dis Model Mech. 2012;5(2):220-230. doi:10.1242/dmm.008409 101. Liang P, Sallam K, Wu H, et al. Patient-Specific and Genome-Edited Induced Pluripotent Stem CellâDerived Cardiomyocytes Elucidate Single-Cell Phenotype of Brugada Syndrome. J Am Coll Cardiol. 2016;68(19):2086-2096. doi:10.1016/j.jacc.2016.07.779 102. Sun N, Yazawa M, Liu J, et al. Patient-Specific Induced Pluripotent Stem Cells as a Model for Familial Dilated Cardiomyopathy. Sci Transl Med. 2012;4(130):130ra47. doi:10.1126/scitranslmed.3003552 103. Tse HF, Ho JCY, Choi SW, et al. Patient-specific induced-pluripotent stem cells-derived cardiomyocytes recapitulate the pathogenic phenotypes of dilated cardiomyopathy due to a novel DES mutation identified by whole exome sequencing. Hum Mol Genet. 2013;22(7):1395-1403. doi:10.1093/hmg/dds556 135 104. Richards MA, Clarke JD, Saravanan P, et al. Transverse tubules are a common feature in large mammalian atrial myocytes including human. Am J Physiol Heart Circ Physiol. 2011;301(5):H1996-2005. doi:10.1152/ajpheart.00284.2011 105. Narolska NA, van Loon RB, Boontje NM, et al. Myocardial contraction is 5-fold more economical in ventricular than in atrial human tissue. Cardiovasc Res. 2005;65(1):221-229. doi:10.1016/j.cardiores.2004.09.029 106. Bayne EF, Rossler KJ, Gregorich ZR, et al. Top-down proteomics of myosin light chain isoforms define chamber-specific expression in the human heart. J Mol Cell Cardiol. 2023;181:89-97. doi:10.1016/j.yjmcc.2023.06.003 107. Miyata S, Minobe W, Bristow MR, Leinwand LA. Myosin Heavy Chain Isoform Expression in the Failing and Nonfailing Human Heart. Circ Res. 2000;86(4):386-390. doi:10.1161/01.RES.86.4.386 108. Barefield DY, Tonino P, Woulfe KC, et al. Myosin-binding protein H-like regulates myosin-binding protein distribution and function in atrial cardiomyocytes. Proc Natl Acad Sci U S A. 2023;120(51):e2314920120. doi:10.1073/pnas.2314920120 109. Piroddi N, Belus A, Scellini B, et al. Tension generation and relaxation in single myofibrils from human atrial and ventricular myocardium. Pflugers Arch. 2007;454(1):63-73. doi:10.1007/s00424-006-0181-3 110. Burnham H V, Cizauskas HE, Barefield DY. Fine tuning contractility: atrial sarcomere function in health and disease. Am J Physiol Heart Circ Physiol. 2024;326(3):H568-H583. doi:10.1152/ajpheart.00252.2023 136 111. Prajapati C, Ojala M, Lappi H, Aalto-Setälä K, Pekkanen-Mattila M. Electrophysiological evaluation of human induced pluripotent stem cell-derived cardiomyocytes obtained by different methods. Stem Cell Res. 2021;51:102176. doi:10.1016/j.scr.2021.102176 112. Devalla HD, Schwach V, Ford JW, et al. Atrial-like cardiomyocytes from human pluripotent stem cells are a robust preclinical model for assessing atrial-selective pharmacology. EMBO Mol Med. 2015;7(4):394-410. doi:10.15252/emmm.201404757 113. Lee JH, Protze SI, Laksman Z, Backx PH, Keller GM. Human Pluripotent Stem Cell-Derived Atrial and Ventricular Cardiomyocytes Develop from Distinct Mesoderm Populations. Cell Stem Cell. 2017;21(2):179-194.e4. doi:10.1016/j.stem.2017.07.003 114. Cyganek L, Tiburcy M, Sekeres K, et al. Deep phenotyping of human induced pluripotent stem cellâderived atrial and ventricular cardiomyocytes. JCI Insight. 2018;3(12):1-17. doi:10.1172/jci.insight.99941 115. Gunawan MG, Sangha SS, Shafaattalab S, et al. Drug screening platform using human induced pluripotent stem cell-derived atrial cardiomyocytes and optical mapping. Stem Cells Transl Med. 2021;10(1):68-82. doi:10.1002/sctm.19-0440 116. Niederreither K, Vermot J, Messaddeq N, Schuhbaur B, Chambon P, Dollé P. Embryonic retinoic acid synthesis is essential for heart morphogenesis in the mouse. Development. 2001;128(7):1019-1031. doi:10.1242/dev.128.7.1019 117. Seibertz F, Rubio T, Springer R, et al. Atrial fibrillation-Associated electrical remodelling in human induced pluripotent stem cell-derived atrial cardiomyocytes: A novel pathway for antiarrhythmic therapy development. Cardiovasc Res. 2023;119(16):2623-2637. doi:10.1093/cvr/cvad143 137 118. Giacomelli E, Sala L, Oostwaard DW van, Bellin M. Cardiac microtissues from human pluripotent stem cells recapitulate the phenotype of long-QT syndrome. Biochem Biophys Res Commun. 2021;572:118-124. doi:10.1016/j.bbrc.2021.07.068 119. Schaaf S, Shibamiya A, Mewe M, et al. Human engineered heart tissue as a versatile tool in basic research and preclinical toxicology. PLoS One. 2011;6(10):e26397. doi:10.1371/journal.pone.0026397 120. Mannhardt I, Breckwoldt K, Letuffe-Brenière D, et al. Human Engineered Heart Tissue: Analysis of Contractile Force. Stem Cell Reports. 2016;7(1):29-42. doi:10.1016/j.stemcr.2016.04.011 121. Lemoine MD, Krause T, Koivumäki JT, et al. Human Induced Pluripotent Stem Cell-Derived Engineered Heart Tissue as a Sensitive Test System for QT Prolongation and Arrhythmic Triggers. Circ Arrhythm Electrophysiol. 2018;11(7):e006035. doi:10.1161/CIRCEP.117.006035 122. Windt LM, Wiendels M, DostaniÄ M, et al. Miniaturized engineered heart tissues from hiPSC-derived triple cell type co-cultures to study human cardiac function. Biochem Biophys Res Commun. 2023;681:200-211. doi:10.1016/j.bbrc.2023.09.034 123. Chugh SS, Havmoeller R, Narayanan K, et al. Worldwide Epidemiology of Atrial Fibrillation: A Global Burden of Disease 2010 Study. Circulation. 2014;129(8):837-847. doi:10.1161/CIRCULATIONAHA.113.005119 124. OâReilly DJ, Hopkins RB, Healey JS, et al. The burden of atrial fibrillation on the hospital sector in Canada. Can J Cardiol. 2013;29(2):229-235. doi:10.1016/j.cjca.2012.03.023 125. Roselli C, Chaffin MD, Weng LC, et al. Multi-ethnic genome-wide association study for atrial fibrillation. Nat Genet. 2018;50(9):1225-1233. doi:10.1038/s41588-018-0133-9 138 126. Nielsen JB, Thorolfsdottir RB, Fritsche LG, et al. Biobank-driven genomic discovery yields new insight into atrial fibrillation biology. Nat Genet. 2018;50(9):1234-1239. doi:10.1038/s41588-018-0171-3 127. Weng LC, Preis SR, Hulme OL, et al. Genetic Predisposition, Clinical Risk Factor Burden, and Lifetime Risk of Atrial Fibrillation. Circulation. 2018;137(10):1027-1038. doi:10.1161/CIRCULATIONAHA.117.031431 128. Bycroft C, Freeman C, Petkova D, et al. The UK Biobank resource with deep phenotyping and genomic data. Nature. 2018;562(7726):203-209. doi:10.1038/s41586-018-0579-z 129. Van Hout CV, Tachmazidou I, Backman JD, et al. Exome sequencing and characterization of 49,960 individuals in the UK Biobank. Nature. 2020;586(7831):749-756. doi:10.1038/s41586-020-2853-0 130. Cingolani P, Platts A, Wang LL, et al. A program for annotating and predicting the effects of single nucleotide polymorphisms, SnpEff. Fly (Austin). 2012;6(2):80-92. doi:10.4161/fly.19695 131. Liu X, Jian X, Boerwinkle E. dbNSFP: A lightweight database of human nonsynonymous SNPs and their functional predictions. Hum Mutat. 2011;32(8):894-899. doi:10.1002/humu.21517 132. Liu X, Wu C, Li C, Boerwinkle E. dbNSFP v3.0: A One-Stop Database of Functional Predictions and Annotations for Human Nonsynonymous and Splice-Site SNVs. Hum Mutat. 2016;37(3):235-241. doi:10.1002/humu.22932 133. Landrum MJ, Lee JM, Riley GR, et al. ClinVar: public archive of relationships among sequence variation and human phenotype. Nucleic Acids Res. 2014;42:D980-D985. doi:10.1093/nar/gkt1113 139 134. Cingolani P, Patel VM, Coon M, et al. Using Drosophila melanogaster as a Model for Genotoxic Chemical Mutational Studies with a New Program, SnpSift. Front Genet. 2012;3:1-9. doi:10.3389/fgene.2012.00035 135. Chang CC, Chow CC, Tellier LCAM, Vattikuti S, Purcell SM, Lee JJ. Second-generation PLINK: rising to the challenge of larger and richer datasets. Gigascience. 2015;4(1):7. doi:10.1186/s13742-015-0047-8 136. van den Ham HA, Klungel OH, Singer DE, Leufkens HGM, van Staa TP. Comparative Performance of ATRIA, CHADS2, and CHA2DS2-VASc Risk Scores Predicting Stroke in Patients With Atrial Fibrillation. J Am Coll Cardiol. 2015;66(17):1851-1859. doi:10.1016/j.jacc.2015.08.033 137. Aspberg S, Chang Y, Atterman A, Bottai M, Go AS, Singer DE. Comparison of the ATRIA, CHADS2, and CHA2DS2-VASc stroke risk scores in predicting ischaemic stroke in a large Swedish cohort of patients with atrial fibrillation. Eur Heart J. 2016;37(42):3203-3210. doi:10.1093/eurheartj/ehw077 138. Fry A, Littlejohns TJ, Sudlow C, et al. Comparison of Sociodemographic and Health-Related Characteristics of UK Biobank Participants With Those of the General Population. Am J Epidemiol. 2017;186(9):1026-1034. doi:10.1093/aje/kwx246 139. Chung MK, Eckhardt LL, Chen LY, et al. Lifestyle and Risk Factor Modification for Reduction of Atrial Fibrillation: A Scientific Statement From the American Heart Association. Circulation. 2020;141:e750-e772. doi:10.1161/cir.0000000000000748 140. Gami AS, Hodge DO, Herges RM, et al. Obstructive Sleep Apnea, Obesity, and the Risk of Incident Atrial Fibrillation. J Am Coll Cardiol. 2007;49(5):565-571. doi:10.1016/j.jacc.2006.08.060 140 141. Nalliah CJ, Sanders P, Kottkamp H, Kalman JM. The role of obesity in atrial fibrillation. Eur Heart J. 2016;37(20):1565-1572. doi:10.1093/eurheartj/ehv486 142. Chamberlain AM, Agarwal SK, Folsom AR, et al. Smoking and incidence of atrial fibrillation: Results from the Atherosclerosis Risk in Communities (ARIC) Study. Heart Rhythm. 2011;8(8):1160-1166. doi:10.1016/j.hrthm.2011.03.038 143. Lazarte J, Laksman ZW, Wang J, et al. Enrichment of loss-of-function and copy number variants in ventricular cardiomyopathy genes in âloneâ atrial fibrillation. Europace. 2021;23(6):844-850. doi:10.1093/europace/euaa421 144. Christidi E, Huang H, Shafaattalab S, et al. Variation in RARG increases susceptibility to doxorubicin-induced cardiotoxicity in patient specific induced pluripotent stem cell-derived cardiomyocytes. Sci Rep. 2020;10(1):10363. doi:10.1038/s41598-020-65979-x 145. Concordet JP, Haeussler M. CRISPOR: Intuitive guide selection for CRISPR/Cas9 genome editing experiments and screens. Nucleic Acids Res. 2018;46(W1):W242-W245. doi:10.1093/nar/gky354 146. Carson D, Hnilova M, Yang X, et al. Nanotopography-Induced Structural Anisotropy and Sarcomere Development in Human Cardiomyocytes Derived from Induced Pluripotent Stem Cells. ACS Appl Mater Interfaces. 2016;8(34):21923-21932. doi:10.1021/acsami.5b11671 147. Salick MR, Napiwocki BN, Kruepke RA, Knight GT, Ashton RS, Crone WC. The scanning gradient Fourier transform (SGFT) method for assessing sarcomere organization and alignment. J Appl Phys. 2020;127(19):194701. doi:10.1063/1.5129347 141 148. Warren CM, Krzesinski PR, Greaser ML. Vertical agarose gel electrophoresis and electroblotting of high-molecular-weight proteins. Electrophoresis. 2003;24(11):1695-1702. doi:10.1002/elps.200305392 149. Greaser ML, Warren CM. Electrophoretic Separation of Very Large Molecular Weight Proteins in SDS Agarose. Methods Mol Biol. 2019;1855:203-210. doi:10.1007/978-1-4939-8793-1_18 150. Buikema JW, Lee S, Goodyer WR, et al. Wnt Activation and Reduced Cell-Cell Contact Synergistically Induce Massive Expansion of Functional Human iPSC-Derived Cardiomyocytes. Cell Stem Cell. 2020;27(1):50-63.e5. doi:10.1016/j.stem.2020.06.001 151. Fahmi NA, Nassereddeen H, Chang J, et al. AS-Quant: Detection and Visualization of Alternative Splicing Events with RNA-seq Data. Int J Mol Sci. 2021;22(9):4468. doi:10.3390/ijms22094468 152. Vitting-Seerup K, Sandelin A. IsoformSwitchAnalyzeR: analysis of changes in genome-wide patterns of alternative splicing and its functional consequences. Bioinformatics. 2019;35(21):4469-4471. doi:10.1093/bioinformatics/btz247 153. Richards S, Aziz N, Bale S, et al. Standards and guidelines for the interpretation of sequence variants: a joint consensus recommendation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. Genet Med. 2015;17(5):405-424. doi:10.1038/gim.2015.30 154. Garg A, OâRourke J, Long C, et al. KLHL40 deficiency destabilizes thin filament proteins and promotes nemaline myopathy. J Clin Invest. 2014;124(8):3529-3539. doi:10.1172/JCI74994 142 155. Olesen MS, Jespersen T, Nielsen JB, et al. Mutations in sodium channel β-subunit SCN3B are associated with early-onset lone atrial fibrillation. Cardiovasc Res. 2011;89(4):786-793. doi:10.1093/cvr/cvq348 156. Barajas-Martinez H, Smith M, Hu D, et al. Susceptibility to Ventricular Arrhythmias Resulting from Mutations in FKBP1B, PXDNL, and SCN9A Evaluated in hiPSC Cardiomyocytes. Stem Cells Int. 2020;2020:1-16. doi:10.1155/2020/8842398 157. Maekawa Y, Mizue N, Chan A, et al. Survival and cardiac remodeling after myocardial infarction are critically dependent on the host innate immune interleukin-1 receptor-associated kinase-4 signaling: A regulator of bone marrow-derived dendritic cells. Circulation. 2009;120(14):1401-1414. doi:10.1161/CIRCULATIONAHA.109.865956 158. Jiang DS, Yi X, Huo B, et al. The potential role of lysosome-associated membrane protein 3 (LAMP3) on cardiac remodelling. Am J Transl Res. 2016;8(1):37-48. http://www.ncbi.nlm.nih.gov/pubmed/27069538 159. Otway R, Vandenberg JI, Guo G, et al. Stretch-Sensitive KCNQ1 Mutation. A Link Between Genetic and Environmental Factors in the Pathogenesis of Atrial Fibrillation? J Am Coll Cardiol. 2007;49(5):578-586. doi:10.1016/j.jacc.2006.09.044 160. Ritchie MD, Rowan S, Kucera G, et al. Chromosome 4q25 variants are genetic modifiers of rare ion channel mutations associated with familial atrial fibrillation. J Am Coll Cardiol. 2012;60(13):1173-1181. doi:10.1016/j.jacc.2012.04.030 161. Huang K, Trinder M, Roston TM, Laksman ZW, Brunham LR. The Interplay Between Titin, Polygenic Risk, and Modifiable Cardiovascular Risk Factors in Atrial Fibrillation. Can J Cardiol. 2021;37(6):848-856. doi:10.1016/j.cjca.2020.12.024 143 162. Rivner H, Mitrani RD, Goldberger JJ. Atrial Myopathy Underlying Atrial Fibrillation. Arrhythm Electrophysiol Rev. 2020;9(2):61-70. doi:10.15420/aer.2020.13 163. Boldt A, Wetzel U, Lauschke J, et al. Fibrosis in left atrial tissue of patients with atrial fibrillation with and without underlying mitral valve disease. Heart. 2004;90(4):400-405. doi:10.1136/hrt.2003.015347 164. Packer M. Characterization, Pathogenesis, and Clinical Implications of Inflammation-Related Atrial Myopathy as an Important Cause of Atrial Fibrillation. J Am Heart Assoc. 2020;9(7):e015343. doi:10.1161/JAHA.119.015343 165. Heras-Bautista CO, Mikhael N, Lam J, et al. Cardiomyocytes facing fibrotic conditions re-express extracellular matrix transcripts. Acta Biomater. 2019;89:180-192. doi:10.1016/j.actbio.2019.03.017 166. Guo Y, Pu WT. Cardiomyocyte Maturation: New Phase in Development. Circ Res. 2020;126(8):1086-1106. doi:10.1161/CIRCRESAHA.119.315862 167. Vad OB, Monfort LM, Paludan-Müller C, et al. Rare and Common Genetic Variation Underlying Atrial Fibrillation Risk. JAMA Cardiol. 2024;9(8):732. doi:10.1001/jamacardio.2024.1528 168. Tayal U, Newsome S, Buchan R, et al. Truncating Variants in Titin Independently Predict Early Arrhythmias in Patients With Dilated Cardiomyopathy. J Am Coll Cardiol. 2017;69(19):2466-2468. doi:10.1016/j.jacc.2017.03.530 169. Gulati A, Jabbour A, Ismail TF, et al. Association of fibrosis with mortality and sudden cardiac death in patients with nonischemic dilated cardiomyopathy. JAMA. 2013;309(9):896-908. doi:10.1001/jama.2013.1363 144 170. Di Marco A, Anguera I, Schmitt M, et al. Late Gadolinium Enhancement and the Risk for Ventricular Arrhythmias or Sudden Death in Dilated Cardiomyopathy: Systematic Review and Meta-Analysis. JACC Heart Fail. 2017;5(1):28-38. doi:10.1016/j.jchf.2016.09.017 171. Sala L, van Meer BJ, Tertoolen LGJ, et al. MUSCLEMOTION: A Versatile Open Software Tool to Quantify Cardiomyocyte and Cardiac Muscle Contraction In Vitro and In Vivo. Circ Res. 2018;122(3):e5-e16. doi:10.1161/CIRCRESAHA.117.312067 172. Chalazan B, Freeth E, Mohajeri A, et al. Genetic testing in monogenic early-onset atrial fibrillation. Eur J Hum Genet. 2023;31(7):769-775. doi:10.1038/s41431-023-01383-z 173. Akhtar MM, Lorenzini M, Cicerchia M, et al. Clinical Phenotypes and Prognosis of Dilated Cardiomyopathy Caused by Truncating Variants in the TTN Gene. Circ Heart Fail. 2020;13(10):e006832. doi:10.1161/CIRCHEARTFAILURE.119.006832 174. Xu X, Kaindl J, Clark MJ, et al. Binding pathway determines norepinephrine selectivity for the human β1AR over β2AR. Cell Res. 2021;31(5):569-579. doi:10.1038/s41422-020-00424-2 175. Feyen DAM, McKeithan WL, Bruyneel AAN, et al. Metabolic Maturation Media Improve Physiological Function of Human iPSC-Derived Cardiomyocytes. Cell Rep. 2020;32(3):107925. doi:10.1016/j.celrep.2020.107925 176. Parikh SS, Blackwell DJ, Gomez-Hurtado N, et al. Thyroid and Glucocorticoid Hormones Promote Functional T-Tubule Development in Human-Induced Pluripotent Stem Cell-Derived Cardiomyocytes. Circ Res. 2017;121(12):1323-1330. doi:10.1161/CIRCRESAHA.117.311920 145 177. Abilez OJ, Tzatzalos E, Yang H, et al. Passive Stretch Induces Structural and Functional Maturation of Engineered Heart Muscle as Predicted by Computational Modeling. Stem Cells. 2018;36(2):265-277. doi:10.1002/stem.2732 178. Dunn KK, Reichardt IM, Simmons AD, et al. Coculture of Endothelial Cells with Human Pluripotent Stem Cell-Derived Cardiac Progenitors Reveals a Differentiation Stage-Specific Enhancement of Cardiomyocyte Maturation. Biotechnol J. 2019;14(8):e1800725. doi:10.1002/biot.201800725 179. Bliley JM, Vermeer MCSC, Duffy RM, et al. Dynamic loading of human engineered heart tissue enhances contractile function and drives a desmosome-linked disease phenotype. Sci Transl Med. 2021;13(603):eabd1817. doi:10.1126/scitranslmed.abd1817 146 Appendices Appendix A A.1 Supplemental Tables Table A.1 Disease and procedure definitions. Name of disease or procedure ICD-10, OPCS-4, self-reported non-cancer illness or operation codes used Atrial fibrillation ICD-10 I48.0 Paroxysmal atrial fibrillation I48.1 Persistent atrial fibrillation I48.2 Chronic atrial fibrillation I48.3 Typical atrial flutter I48.4 Atypical atrial flutter I48.9 Atrial fibrillation and atrial flutter, unspecified Non-cancer illness, self-reported (Data-Field 20002) 1471 Atrial fibrillation 1483 Atrial flutter 12-lead electrocardiogram, at rest automated diagnoses (Data-Field 12653) 147 Atrial fibrillation Atrial flutter Angina ICD-10 I20.0 Unstable angina I20.1 Angina pectoris with documented spasm I20.8 Other forms of angina pectoris I20.9 Angina pectoris, unspecified Non-cancer illness, self-reported (Data-Field 20002) 1074 Angina Atherosclerotic heart disease ICD-10 I25 Chronic ischaemic heart disease- I25.0 Atherosclerotic cardiovascular disease, so described I25.1 Atherosclerotic heart disease I70.0 Atherosclerosis of aorta I70.00 Atherosclerosis of aorta (without gangrene) I70.01 Atherosclerosis of aorta (with gangrene) I70.2 Atherosclerosis of arteries of the extremities I70.20 Atherosclerosis of arteries of extremities (without gangrene) I70.21 Atherosclerosis of arteries of extremities (with gangrene) I70.8 Atherosclerosis of other arteries I70.80 Atherosclerosis of other arteries (without gangrene) 148 I70.9 Generalised and unspecified atherosclerosis I70.90 Generalized and unspecified atherosclerosis (without gangrene) I70.91 Generalized and unspecified atherosclerosis (with gangrene) Diabetes ICD-10 E10.0 Insulin-dependent diabetes mellitus with coma E10.1 Insulin-dependent diabetes mellitus with ketoacidosis E10.2 Insulin-dependent diabetes mellitus with renal complications E10.3 Insulin-dependent diabetes mellitus with ophthalmic complications E10.4 Insulin-dependent diabetes mellitus with neurological complications E10.5 Insulin-dependent diabetes mellitus with peripheral circulatory complications E10.6 Insulin-dependent diabetes mellitus with other specified complications E10.7 Insulin-dependent diabetes mellitus with multiple complications E10.8 Insulin-dependent diabetes mellitus with unspecified complications E10.9 Insulin-dependent diabetes mellitus without complications E11.0 Non-insulin-dependent diabetes mellitus with coma 149 E11.1 Non-insulin-dependent diabetes mellitus with ketoacidosis E11.2 Non-insulin-dependent diabetes mellitus with renal complications E11.3 Non-insulin-dependent diabetes mellitus with ophthalmic complications E11.4 Non-insulin-dependent diabetes mellitus with neurological complications E11.5 Non-insulin-dependent diabetes mellitus with peripheral circulatory complications E11.6 Non-insulin-dependent diabetes mellitus with other specified complications E11.7 Non-insulin-dependent diabetes mellitus with multiple complications E11.8 Non-insulin-dependent diabetes mellitus with unspecified complications E11.9 Non-insulin-dependent diabetes mellitus without complications E12.1 Malnutrition-related diabetes mellitus with ketoacidosis E12.8 Malnutrition-related diabetes mellitus with unspecified complications E12.9 Malnutrition-related diabetes mellitus without complications E13.1 Other specified diabetes mellitus with ketoacidosis E13.2 Other specified diabetes mellitus with renal complications 150 E13.3 Other specified diabetes mellitus with ophthalmic complications E13.4 Other specified diabetes mellitus with neurological complications E13.5 Other specified diabetes mellitus with peripheral circulatory complications E13.6 Other specified diabetes mellitus with other specified complications E13.7 Other specified diabetes mellitus with multiple complications E13.8 Other specified diabetes mellitus with unspecified complications E13.9 Other specified diabetes mellitus without complications E14.0 Unspecified diabetes mellitus with coma E14.1 Unspecified diabetes mellitus with ketoacidosis E14.2 Unspecified diabetes mellitus with renal complications E14.3 Unspecified diabetes mellitus with ophthalmic complications E14.4 Unspecified diabetes mellitus with neurological complications E14.5 Unspecified diabetes mellitus with peripheral circulatory complications E14.6 Unspecified diabetes mellitus with other specified complications E14.7 Unspecified diabetes mellitus with multiple complications 151 E14.8 Unspecified diabetes mellitus with unspecified complications E14.9 Unspecified diabetes mellitus without complications Non-cancer illness, self-reported (Data-Field 20002) 1220 Diabetes 1222 Type 1 diabetes 1223 Type 2 diabetes Dilated cardiomyopathy ICD-10 I42.0 Dilated cardiomyopathy Non-cancer illness, self-reported (Data-Field 20002) 1079 Cardiomyopathy Heart failure ICD-10 I50.0 Congestive heart failure I50.1 left ventricular failure I50.9 heart failure, unspecified Non-cancer illness, self-reported (Data-Field 20002) 1076 heart failure/pulmonary odema Hypertension ICD-10 I10 Essential (primary) hypertension I11.0 Hypertensive heart disease with (congestive) heart failure 152 I11.9 Hypertensive heart disease without (congestive) heart failure I12.0 Hypertensive renal disease with renal failure I12.9 Hypertensive renal disease without renal failure I13.0 Hypertensive heart and renal disease with (congestive) heart failure I13.1 Hypertensive heart and renal disease with renal failure I13.2 Hypertensive heart and renal disease with both (congestive) heart failure and renal failure I13.9 Hypertensive heart and renal disease, unspecified I15.0 Renovascular hypertension I15.1 Hypertension secondary to other renal disorders I15.2 Hypertension secondary to endocrine disorders I15.8 Other secondary hypertension I15.9 Secondary hypertension, unspecified Non-cancer illness, self-reported (Data-Field 20002) 1065 Hypertension 1072 Essential hypertension Myocardial infarction ICD-10 I21.0 Acute transmural myocardial infarction of anterior wall I21.1 Acute transmural myocardial infarction of inferior wall I21.2 Acute transmural myocardial infarction of other sites 153 I21.3 Acute transmural myocardial infarction of unspecified site I21.4 Acute subendocardial myocardial infarction I21.9 Acute myocardial infarction, unspecified I22.0 Subsequent myocardial infarction of anterior wall I22.1 Subsequent myocardial infarction of inferior wall I22.8 Subsequent myocardial infarction of other sites I22.9 Subsequent myocardial infarction of unspecified site I23.0 Haemopericardium as current complication following acute myocardial infarction I23.1 Atrial septal defect as current complication following acute myocardial infarction I23.2 Ventricular septal defect as current complication following acute myocardial infarction I23.3 Rupture of cardiac wall without haemopericardium as current complication following acute myocardial infarction I23.5 Rupture of papillary muscle as current complication following acute myocardial infarction I23.6 Thrombosis of atrium, auricular appendage and ventricle as current complications following acute myocardial infarction I23.8 Other current complications following acute myocardial infarction I24.1 Dresslerâs syndrome 154 Non-cancer illness, self-reported (Data-Field 20002) 1075 Heart attack/myocardial infarction Peripheral vascular disease ICD-10 I71.0 Dissection of aorta [any part] I71.1 Thoracic aortic aneurysm, ruptured I71.2 Thoracic aortic aneurysm, without mention of rupture I71.3 Abdominal aortic aneurysm, ruptured I71.4 Abdominal aortic aneurysm, without mention of rupture I71.5 Thoracoabdominal aortic aneurysm, ruptured I71.6 Thoracoabdominal aortic aneurysm, without mention of rupture I71.8 Aortic aneurysm of unspecified site, ruptured I71.9 Aortic aneurysm of unspecified site, without mention of rupture I73.8 Other specified peripheral vascular diseases I73.9 Peripheral vascular disease, unspecified I79.2 Peripheral angiopathy in diseases classified elsewhere I79.8 Other disorders of arteries, arterioles and capillaries in diseases classified elsewhere Non-cancer illness, self-reported (Data-Field 20002) 1067 Peripheral vascular disease 1492 Aortic aneurysm 155 1591 Aortic aneurysm rupture Revascularization procedure OPCS-4 K40.1 Saphenous vein graft replacement of one coronary artery K40.2 Saphenous vein graft replacement of two coronary arteries K40.3 Saphenous vein graft replacement of three coronary arteries K40.4 Saphenous vein graft replacement of four or more coronary arteries K40.8 Other specified saphenous vein graft replacement of coronary artery K40.9 Unspecified saphenous vein graft replacement of coronary artery K41.1 Autograft replacement of one coronary artery (not elsewhere classified) K41.2 Autograft replacement of two coronary arteries (not elsewhere classified) K41.3 Autograft replacement of three coronary arteries (not elsewhere classified) K41.4 Autograft replacement of four or more coronary arteries (not elsewhere classified) K41.8 Other specified other autograft replacement of coronary artery K41.9 Unspecified other autograft replacement of coronary artery K42.1 Allograft replacement of one coronary artery 156 K42.2 Allograft replacement of two coronary arteries K42.3 Allograft replacement of three coronary arteries K42.4 Allograft replacement of four or more coronary arteries K42.8 Other specified allograft replacement of coronary artery K42.9 Unspecified allograft replacement of coronary artery K43.1 Prosthetic replacement of one coronary artery K43.2 Prosthetic replacement of two coronary arteries K43.3 Prosthetic replacement of three coronary arteries K43.4 Prosthetic replacement of four or more coronary arteries K43.8 Other specified prosthetic replacement of coronary artery K43.9 Unspecified prosthetic replacement of coronary artery K44.1 Replacement of coronary arteries using multiple methods K44.2 Revision of replacement of coronary artery K44.8 Other specified other replacement of coronary artery K44.9 Unspecified other replacement of coronary artery K45.1 Double anastomosis of mammary arteries to coronary arteries K45.2 Double anastomosis of thoracic arteries to coronary arteries (not elsewhere classified) K45.3 Anastomosis of mammary artery to left anterior descending coronary artery K45.4 Anastomosis of mammary artery to coronary artery (not elsewhere classified) 157 K45.5 Anastomosis of thoracic artery to coronary artery (not elsewhere classified) K45.6 Revision of connection of thoracic artery to coronary artery K45.8 Other specified connection of thoracic artery to coronary artery K45.9 Unspecified connection of thoracic artery to coronary artery K46.1 Double implantation of mammary arteries into heart K46.2 Double implantation of thoracic arteries into heart (not elsewhere classified) K46.3 Implantation of mammary artery into heart (not elsewhere classified) K46.4 Implantation of thoracic artery into heart (not elsewhere classified) K46.5 Revision of implantation of thoracic artery into heart K46.8 Other specified other bypass of coronary artery K46.9 Unspecified other bypass of coronary artery K49.1 Percutaneous transluminal balloon angioplasty of one coronary artery K49.2 Percutaneous transluminal balloon angioplasty of multiple coronary arteries K49.3 Percutaneous transluminal balloon angioplasty of bypass graft of coronary artery 158 K49.4 Percutaneous transluminal cutting balloon angioplasty of coronary artery K49.8 Other specified transluminal balloon angioplasty of coronary artery K49.9 Unspecified transluminal balloon angioplasty of coronary artery K50.1 Percutaneous transluminal laser coronary angioplasty K50.2 Percutaneous transluminal coronary thrombolysis using streptokinase K50.3 Percutaneous transluminal injection of therapeutic substance into coronary artery (not elsewhere classified) K50.4 Percutaneous transluminal atherectomy of coronary artery K50.8 Other specified other therapeutic transluminal operations on coronary artery K50.9 Unspecified other therapeutic transluminal operations on coronary artery K55.3 Open removal of cardiac thrombus K75.1 Percutaneous transluminal balloon angioplasty and insertion of 1-2 drug-eluting stents into coronary artery K75.2 Percutaneous transluminal balloon angioplasty and insertion of 3 or more drug-eluting stents into coronary artery 159 K75.3 Percutaneous transluminal balloon angioplasty and insertion of 1-2 stents into coronary artery K75.4 Percutaneous transluminal balloon angioplasty and insertion of 3 or more stents into coronary artery (not elsewhere classified) K75.8 Other specified percutaneous transluminal balloon angioplasty and insertion of stent into coronary artery K75.9 Unspecified percutaneous transluminal balloon angioplasty and insertion of stent into coronary artery K76.1 Percutaneous transluminal balloon dilation of cardiac conduit K76.8 Other specified transluminal operations on cardiac conduit K76.9 Unspecified transluminal operations on cardiac conduit L29.1 Replacement of carotid artery using graft L29.2 Intracranial bypass to carotid artery (not elsewhere classified) L29.3 Bypass to carotid artery (not elsewhere classified) L29.4 Endarterectomy of carotid artery and patch repair of carotid artery L29.5 Endarterectomy of carotid artery (not elsewhere classified) L29.6 High-flow interposition extracranial to intracranial bypass from external carotid artery to middle cerebral artery L29.7 Bypass of carotid artery by anastomosis of superficial temporal artery to middle cerebral artery L29.8 Other specified reconstruction of carotid artery 160 L29.9 Unspecified reconstruction of carotid artery L30.3 Open embolectomy of carotid artery L31.1 Percutaneous transluminal angioplasty of carotid artery L31.3 Endovascular repair of carotid artery L31.4 Percutaneous transluminal insertion of stent into carotid artery L31.8 Other specified transluminal operations on carotid artery L31.9 Unspecified transluminal operations on carotid artery Operation code (Data-Field 20004) 1070 Coronary angioplasty (percutaneous transluminal coronary angioplasty) +/- stent 1095 Coronary artery bypass grafts 1105 Carotid artery surgery/endarterectomy 1109 Carotid artery angioplasty +/- stent 1523 Triple heart bypass Stroke/transient ischemic attack ICD-10 G45.0 Vertebro-basilar artery syndrome G45.1 Carotid artery syndrome (hemispheric) G45.3 Amaurosis fugax G45.4 Transient global amnesia G45.8 Other transient cerebral ischaemic attacks and related syndromes 161 G45.9 Transient cerebral ischaemic attack, unspecified I60.0 Subarachnoid haemorrhage from carotid siphon and bifurcation I60.1 Subarachnoid haemorrhage from middle cerebral artery I60.2 Subarachnoid haemorrhage from anterior communicating artery I60.3 Subarachnoid haemorrhage from posterior communicating artery I60.4 Subarachnoid haemorrhage from basilar artery I60.5 Subarachnoid haemorrhage from vertebral artery I60.6 Subarachnoid haemorrhage from other intracranial arteries I60.7 Subarachnoid haemorrhage from intracranial artery, unspecified I60.8 Other subarachnoid haemorrhage I60.9 Subarachnoid haemorrhage, unspecified I61.0 Intracerebral haemorrhage in hemisphere, subcortical I61.1 Intracerebral haemorrhage in hemisphere, cortical I61.2 Intracerebral haemorrhage in hemisphere, unspecified I61.3 Intracerebral haemorrhage in brain stem I61.4 Intracerebral haemorrhage in cerebellum I61.5 Intracerebral haemorrhage, intraventricular I61.6 Intracerebral haemorrhage, multiple localised I61.8 Other intracerebral haemorrhage I61.9 Intracerebral haemorrhage, unspecified I63.0 Cerebral infarction due to thrombosis of precerebral arteries 162 I63.1 Cerebral infarction due to embolism of precerebral arteries I63.2 Cerebral infarction due to unspecified occlusion or stenosis of precerebral arteries I63.3 Cerebral infarction due to thrombosis of cerebral arteries I63.4 Cerebral infarction due to embolism of cerebral arteries I63.5 Cerebral infarction due to unspecified occlusion or stenosis of cerebral arteries I63.6 Cerebral infarction due to cerebral venous thrombosis, nonpyogenic I63.8 Other cerebral infarction I63.9 Cerebral infarction, unspecified I64 Stroke, not specified as haemorrhage or infarction Non-cancer illness, self-reported (Data-Field 20002) 1081 Stroke 1082 Transient ischaemic attack 1583 Ischaemic stroke Thrombosis ICD-10 I74.0 Embolism and thrombosis of abdominal aorta I74.1 Embolism and thrombosis of other and unspecified parts of aorta I74.2 Embolism and thrombosis of arteries of the upper extremities 163 ICD-10 indicates International Statistical Classification of Disease and Related Health Problems 10th revision; OPCS-4, Office of Population Censuses and Surveys Classification of Interventions and Procedures 4th revision. I74.3 Embolism and thrombosis of arteries of the lower extremities I74.4 Embolism and thrombosis of arteries of extremities, unspecified I74.5 Embolism and thrombosis of iliac artery I74.8 Embolism and thrombosis of other arteries I74.9 Embolism and thrombosis of unspecified artery Non-cancer illness, self-reported (Data-Field 20002) 1068 Venous thromboembolic disease 1088 Arterial embolism 1093 Pulmonary embolism +/- deep venous thrombosis 1094 Deep venous thrombosis 164 Table A.2 Quality control measures for genetic data. Type of data Sample and variant QC measures Whole exome sequencing data Sample and variant QC were performed as previously described.129 Briefly, samples with mismatched genetic and reported sex, high rates of heterozygosity or contamination (D-stat > 0.4), low coverage (< 85% targeted bases with 20X coverage), duplicated samples, and variants discordant with genotyping chip were excluded. SNV genotypes with DP < 7 were relabeled as no-call and only SNVs with AB â¥ 0.15 for at least one heterozygous variant genotype or at least one homozygous variant genotype were included. INDELs were filtered by DP < 10 and AB â¥ 0.20. Additional filtering performed in this study: ï· Excluded variants in titin exons with percent-splice-in values < 90 ï· Excluded variants with MAF â¥ 0.05 ï· Excluded participants withdrawn from the UK Biobank study ï· Excluded participants with mismatched genetic and reported sex 165 Genotyped and imputed data Sample and variant QC were performed as previously described.128 Additional filtering performed in this study: ï· Excluded variants flagged as outliers for heterozygosity or missing rate (Data-Field 22027) ï· Included only participants of White British ancestry (Data-Field 22006) ï· Excluded participants missing > 10% genotypes ï· Excluded variants deviating from Hardy-Weinberg equilibrium (P-value < 1x10-15) and genotyping rate < 90% ï· For imputed variants, only included variants with information scores > 0.80 ï· Excluded participants withdrawn from the UK Biobank study ï· Excluded participants with mismatched genetic and reported sex 166 Table A.3 TTNv identified in UK Biobank participants. Chr:Pos Ref/Alt rsID Variant category ClinVar Significance UKB freq. Carriers in UKB gnomAD freq. 2:178528273 C/T rs112188483 Splice donor variant & intron variant Pathogenic/Likely pathogenic 4.01E-05 2 2.09E-05 2:178528307 G/A Stop gained 2.00E-05 1 2:178528756 C/CT Frameshift variant 2.00E-05 1 2:178528797 G/A rs565675340 Stop gained 2.00E-05 1 1.40E-05 2:178529121 CT/C rs869312069 Frameshift variant Likely pathogenic 2.00E-05 1 2:178529127 G/A Stop gained 2.00E-05 1 2:178529958 A/T rs878854373 Splice donor variant & intron variant 2.00E-05 1 2:178530467 TG/T Frameshift variant 2.00E-05 1 2:178530499 T/TAA rs1394131775 Frameshift variant 2.00E-05 1 6.98E-06 2:178530809 GT/G rs752787097 Frameshift variant Uncertain significance 2.00E-05 1 6.99E-06 167 2:178531423 AAC/A rs770878165 Frameshift variant Likely pathogenic 2.00E-05 1 2:178531668 G/A rs991187915 Stop gained 4.01E-05 2 6.98E-06 2:178531788 G/A rs1202115268 Stop gained 4.01E-05 2 6.98E-06 2:178531887 TG/T rs758264406 Frameshift variant 0.00018 9 2:178531890 AAAAGATATCAAATCTTGCAGACCTCT/A rs779685038 Frameshift variant 0.00018 9 2:178531925 GA/G Frameshift variant 2.00E-05 1 2:178532669 C/CCCCAA rs769385648 Frameshift variant 4.01E-05 2 6.98E-05 2:178532670 GGT/G rs778443775 Frameshift variant 4.01E-05 2 6.98E-05 2:178532844 G/A rs967542291 Stop gained 2.00E-05 1 6.98E-06 2:178532971 A/C Stop gained 2.00E-05 1 2:178533652 G/GTTGA Frameshift variant 2.00E-05 1 2:178534089 G/A Stop gained 2.00E-05 1 2:178534344 G/GGT rs751329439 Frameshift variant 4.01E-05 2 2:178534619 C/T rs869312068 Stop gained Likely pathogenic 2.00E-05 1 168 2:178535516 T/TA rs869312122 Frameshift variant Likely pathogenic 2.00E-05 1 2:178536180 GA/G Frameshift variant 2.00E-05 1 2:178536937 C/T Splice donor variant & intron variant 2.00E-05 1 2:178539559 G/A rs869312085 Stop gained Likely pathogenic 2.00E-05 1 2:178539764 CCT/C rs397517776 Frameshift variant Pathogenic/Likely pathogenic 2.00E-05 1 2.10E-05 2:178540194 G/A rs879097896 Stop gained 2.00E-05 1 2:178540303 C/T Stop gained 2.00E-05 1 2:178542492 C/A Stop gained 2.00E-05 1 2:178543508 T/TA Frameshift variant 2.00E-05 1 2:178544116 C/T Splice acceptor variant & intron variant 2.00E-05 1 2:178544241 G/C Stop gained 2.00E-05 1 2:178544455 CTG/C rs1060500544 Frameshift variant Likely pathogenic 2.00E-05 1 169 2:178545817 TACTG/T rs769407533 Frameshift variant & splice donor variant & splice region variant & intron variant Likely pathogenic 4.01E-05 2 2:178547518 CTTTAA/C rs769488730 Frameshift variant Pathogenic 2.00E-05 1 2:178547521 TA/T Frameshift variant 2.00E-05 1 2:178547890 TG/T Frameshift variant 2.00E-05 1 2:178547907 CTGAT/C Frameshift variant 2.00E-05 1 2:178547979 TC/T Frameshift variant 2.00E-05 1 2:178548147 C/T Stop gained 2.00E-05 1 2:178548966 TGTAGATCA/T Frameshift variant Likely pathogenic 2.00E-05 1 2:178549337 G/GCTTTT rs756367933 Frameshift variant Conflicting interpretations of pathogenicity 4.01E-05 2 1.40E-05 2:178551807 CTTTCT/C Frameshift variant 2.00E-05 1 170 2:178552221 T/A Stop gained 2.00E-05 1 2:178552236 G/GAA Frameshift variant 2.00E-05 1 2:178552237 GGT/G Frameshift variant 2.00E-05 1 2:178553913 C/A Splice donor variant & intron variant 2.00E-05 1 2:178555034 A/AT Frameshift variant & stop gained 2.00E-05 1 2:178557324 TA/T Frameshift variant 2.00E-05 1 2:178557511 G/A rs794729299 Stop gained Pathogenic 2.00E-05 1 2:178557545 TC/T rs869312028 Frameshift variant Conflicting interpretations of pathogenicity 2.00E-05 1 2:178557998 GC/G rs794729356 Frameshift variant Pathogenic 2.00E-05 1 2:178559309 A/T rs397517735 Splice donor variant & intron variant Pathogenic/Likely pathogenic 2.00E-05 1 4.89E-05 2:178559385 TAATA/T Frameshift variant 2.00E-05 1 171 2:178560364 G/A Stop gained Likely pathogenic 2.00E-05 1 2:178560865 G/A rs769664554 Stop gained 6.01E-05 3 2:178561762 CACTT/C Frameshift variant 2.00E-05 1 2:178562528 TC/T rs727505014 Frameshift variant Likely pathogenic 2.00E-05 1 2:178562697 GC/G Frameshift variant 2.00E-05 1 2:178565497 G/A rs79926414 Stop gained Uncertain significance 2.00E-05 1 2:178565651 C/T Stop gained 2.00E-05 1 2:178566149 GT/G Frameshift variant 2.00E-05 1 2:178566162 T/TA Frameshift variant 2.00E-05 1 2:178566237 TC/T Frameshift variant 2.00E-05 1 2:178566634 TG/T Frameshift variant 2.00E-05 1 2:178566838 G/A rs774411587 Stop gained Likely pathogenic 2.00E-05 1 2:178568033 GTTTC/G rs869312117 Frameshift variant Likely pathogenic 2.00E-05 1 2:178570804 G/A rs794729382 Stop gained Pathogenic/Likely pathogenic 2.00E-05 1 172 2:178570882 G/A rs794729286 Stop gained Pathogenic 2.00E-05 1 2:178571261 CT/C Frameshift variant 2.00E-05 1 2:178572193 G/A Stop gained 2.00E-05 1 2:178573085 A/C Stop gained 2.00E-05 1 2:178573323 AT/A Frameshift variant 2.00E-05 1 2:178573742 C/CAA Frameshift variant 2.00E-05 1 2:178573908 T/TC Frameshift variant 2.00E-05 1 2:178575970 G/A rs781540455 Stop gained Pathogenic/Likely pathogenic 4.01E-05 2 6.99E-06 2:178576285 C/A Stop gained 2.00E-05 1 2:178578608 T/TAA rs536078303 Splice donor variant & intron variant 2.00E-05 1 2:178579702 G/A rs574660186 Stop gained Pathogenic/Likely pathogenic 6.01E-05 3 3.50E-05 173 2:178579850 T/G rs753948675 Splice acceptor variant & intron variant 8.02E-05 4 6.99E-06 2:178579938 C/T rs758279518 Splice donor variant & intron variant Likely pathogenic 4.01E-05 2 2:178580481 CAT/C Frameshift variant 2.00E-05 1 2:178584726 G/A Stop gained Likely pathogenic 2.00E-05 1 2:178585227 T/TC Frameshift variant 2.00E-05 1 2:178585291 G/A rs768345594 Stop gained Likely pathogenic 2.00E-05 1 2:178586802 GC/G Frameshift variant 2.00E-05 1 2:178587116 A/G Splice donor variant & intron variant 2.00E-05 1 2:178588700 G/A rs368452607 Stop gained Pathogenic/Likely pathogenic 2.00E-05 1 2:178589076 AACAGTAC/A Frameshift variant 2.00E-05 1 2:178589370 GTC/G Frameshift variant 2.00E-05 1 174 2:178590170 G/A rs794729278 Stop gained 6.01E-05 3 2:178590260 T/A Stop gained 4.01E-05 2 2:178590974 T/A Stop gained 2.00E-05 1 2:178592916 CAG/C rs752948913 Frameshift variant Likely pathogenic 2.00E-05 1 2:178593172 C/A Splice donor variant & intron variant 2.00E-05 1 2:178593959 AC/A Splice donor variant & intron variant 2.00E-05 1 2:178598977 A/AT rs397517626 Frameshift variant Likely pathogenic 4.01E-05 2 6.98E-06 2:178599030 T/TA Frameshift variant 2.00E-05 1 2:178599145 C/T rs397517624 Splice donor variant & intron variant Likely pathogenic 2.00E-05 1 2:178601739 G/A rs1440093502 Stop gained 2.00E-05 1 2:178601788 C/T rs748369265 Splice acceptor variant & intron variant Likely pathogenic 2.00E-05 1 1.40E-05 175 2:178604215 C/CT Frameshift variant 4.01E-05 2 2:178605064 TC/T rs794729325 Frameshift variant Pathogenic/Likely pathogenic 2.00E-05 1 2:178605263 G/A Stop gained 2.00E-05 1 2:178607810 TTG/T rs1329057139 Frameshift variant 2.00E-05 1 6.99E-06 2:178608700 T/TTCAA rs794729323 Frameshift variant & stop gained Pathogenic 2.00E-05 1 2:178609289 G/A rs926741242 Stop gained Likely pathogenic 2.00E-05 1 6.99E-06 2:178609756 G/A rs748956593 Stop gained 2.00E-05 1 2:178610090 G/A rs906494713 Stop gained & splice region variant 2.00E-05 1 2:178610180 C/A Stop gained 2.00E-05 1 2:178611446 ACT/A Frameshift variant 2.00E-05 1 2:178611606 GC/G Frameshift variant 2.00E-05 1 2:178613158 TA/T rs727504851 Splice donor variant & intron variant Pathogenic 8.02E-05 4 2.80E-05 176 2:178613938 C/T rs869312070 Splice acceptor variant & intron variant Pathogenic/Likely pathogenic 4.01E-05 2 2:178614177 TC/T Frameshift variant 2.00E-05 1 2:178614465 C/G Splice donor variant & intron variant 2.00E-05 1 2:178614871 CCT/C Frameshift variant 2.00E-05 1 2:178614930 G/GCATAC Frameshift variant 2.00E-05 1 2:178616728 C/G rs779498825 Splice donor variant & intron variant 2.00E-05 1 2:178616887 T/TTATC Frameshift variant & stop gained 2.00E-05 1 2:178617839 G/A rs762271078 Stop gained 2.00E-05 1 2:178617857 G/A rs751746401 Stop gained Pathogenic/Likely pathogenic 2.00E-05 1 7.00E-06 2:178618468 A/AGTTAC Frameshift variant 2.00E-05 1 177 2:178619714 G/A rs764654357 Stop gained 2.00E-05 1 2:178620285 G/T rs368200299 Stop gained Likely pathogenic 4.01E-05 2 2:178621101 C/T rs1395648308 Splice donor variant & intron variant 2.00E-05 1 2:178621150 C/CGTAA Frameshift variant 4.01E-05 2 2:178621473 A/C Splice donor variant & intron variant 2.00E-05 1 2:178621474 C/A Splice donor variant & intron variant 4.01E-05 2 2:178621709 TG/T Frameshift variant 2.00E-05 1 2:178622669 C/A Splice donor variant & intron variant Uncertain significance 2.00E-05 1 2:178622684 G/A rs727505350 Stop gained Conflicting interpretations of pathogenicity 2.00E-05 1 7.01E-06 2:178629360 AG/A rs397517576 Frameshift variant Likely pathogenic 2.00E-05 1 178 2:178630250 G/A rs140743001 Stop gained Conflicting interpretations of pathogenicity 2.00E-05 1 1.40E-05 2:178632700 T/A Stop gained 2.00E-05 1 2:178633279 CAA/C Frameshift variant 2.00E-05 1 2:178633491 T/A Stop gained 2.00E-05 1 2:178633667 GGA/G Frameshift variant 2.00E-05 1 2:178633670 TC/T Frameshift variant 2.00E-05 1 2:178634613 AAAGTC/A Frameshift variant 2.00E-05 1 2:178635441 TC/T Frameshift variant & splice region variant 2.00E-05 1 2:178636098 G/A rs869312043 Stop gained Conflicting interpretations of pathogenicity 2.00E-05 1 2:178636450 AAC/A Frameshift variant 2.00E-05 1 179 2:178642236 C/T rs368219776 Splice donor variant & intron variant Uncertain significance 0.00012 6 4.20E-05 2:178740151 CT/C Frameshift variant 2.00E-05 1 2:178740754 G/GT Frameshift variant 2.00E-05 1 2:178740827 CA/C rs727503658 Frameshift variant Conflicting interpretations of pathogenicity 2.00E-05 1 2:178741104 CTT/C Frameshift variant 2.00E-05 1 2:178741304 G/A Stop gained 2.00E-05 1 2:178741575 AT/A rs397517826 Frameshift variant Uncertain significance 2.00E-05 1 2:178741797 AT/A Frameshift variant 2.00E-05 1 2:178758982 A/G rs371596417 Splice donor variant & intron variant Conflicting interpretations of pathogenicity 0.00016 8 180 2:178764788 G/A rs869312093 Stop gained Uncertain significance 2.00E-05 1 2:178767782 G/A rs146572907 Stop gained Uncertain significance 2.00E-05 1 6.99E-06 2:178769746 TG/T Frameshift variant 2.00E-05 1 2:178773207 A/AT Frameshift variant Uncertain significance 2.00E-05 1 2:178773558 G/A Stop gained Uncertain significance 2.00E-05 1 2:178774206 C/T rs763909866 Splice donor variant & intron variant 2.00E-05 1 2:178774375 CTTCTATATTTTCT/C Frameshift variant 2.00E-05 1 2:178774920 C/A Splice donor variant & intron variant 2.00E-05 1 2:178776073 G/A Stop gained 2.00E-05 1 181 2:178776378 GTA/G Frameshift variant 2.00E-05 1 2:178776745 T/A Stop gained 2.00E-05 1 2:178777004 AG/A Frameshift variant 4.01E-05 2 2:178777148 C/A Splice donor variant & intron variant 2.00E-05 1 2:178777234 CTTTCA/C rs756433029 Frameshift variant Conflicting interpretations of pathogenicity 0.00010 5 1.40E-05 2:178779019 GA/G Frameshift variant 2.00E-05 1 2:178782240 A/AT Frameshift variant 2.00E-05 1 2:178782872 G/A rs397517547 Stop gained Likely pathogenic 2.00E-05 1 2:178784175 G/C Stop gained 2.00E-05 1 2:178786030 G/A Stop gained 2.00E-05 1 2:178786129 T/A Stop gained Likely pathogenic 2.00E-05 1 2:178794436 G/GA Frameshift variant 4.01E-05 2 6.98E-06 2:178794437 T/TG Frameshift variant 4.01E-05 2 6.98E-06 182 2:178800416 T/C rs1207248463 Protein protein contact 2.00E-05 1 2:178800417 C/T rs141444282 Structural interaction variant Benign/Likely benign 8.02E-05 4 6.98E-05 2:178800418 G/A rs754029303 Structural interaction variant 2.00E-05 1 6.98E-06 2:178800421 G/C Protein protein contact 2.00E-05 1 2:178800434 C/T rs370941860 Protein protein contact 2.00E-05 1 2.09E-05 2:178800479 A/G rs1226873128 Structural interaction variant 2.00E-05 1 6.98E-06 2:178800480 T/G rs769469805 Structural interaction variant 2.00E-05 1 2:178800491 T/C Structural interaction variant 2.00E-05 1 183 2:178800509 C/T rs1471570172 Structural interaction variant 2.00E-05 1 2:178800563 G/A rs752970602 Structural interaction variant Uncertain significance 0.00038 19 4.89E-05 2:178800574 A/ACCACAGGTGTAGGGATT Frameshift variant 4.01E-05 2 2:178800579 A/G Structural interaction variant 4.01E-05 2 2:178800595 G/T Structural interaction variant 2.00E-05 1 2:178800599 C/T rs749010768 Structural interaction variant 4.01E-05 2 2:178800631 C/G rs569775318 Protein protein contact 2.00E-05 1 6.98E-06 2:178800635 C/G rs564777385 Structural interaction variant 2.00E-05 1 184 2:178800635 C/T rs564777385 Structural interaction variant 4.01E-05 2 2.09E-05 2:178800643 C/T Protein protein contact 2.00E-05 1 2:178800648 C/T Structural interaction variant Likely benign 4.01E-05 2 2:178800653 G/A rs150954246 Stop gained Uncertain significance 2.00E-05 1 6.98E-06 2:178800677 T/C rs138945705 Protein protein contact 2.00E-05 1 6.98E-06 2:178802144 C/T rs185921345 Structural interaction variant Benign/Likely benign 0.00014 7 0.0020 2:178802145 G/A rs878881293 Structural interaction variant 2.00E-05 1 2:178802203 C/T rs727503709 Protein protein contact Uncertain significance 2.00E-05 1 185 2:178802215 G/GGGACGATCCCCC rs1250285598 Structural interaction variant 8.02E-05 4 2:178802216 CTTTAGT/C rs1472439594 Structural interaction variant 8.02E-05 4 2:178802225 C/T rs772248060 Structural interaction variant Uncertain significance 2.00E-05 1 4.89E-05 2:178802229 G/A rs201089861 Structural interaction variant Conflicting interpretations of pathogenicity 0.00012 6 0.00012 2:178802231 G/A rs876658046 Structural interaction variant Uncertain significance 2.00E-05 1 6.98E-06 2:178802235 C/T rs764223195 Structural interaction variant Likely benign 2.00E-05 1 6.98E-06 2:178802236 G/A rs372755739 Structural interaction variant Likely benign 0.00014 7 4.19E-05 186 2:178802244 A/G rs1057520389 Structural interaction variant Likely benign 4.01E-05 2 6.98E-06 2:178802246 C/T rs764892312 Structural interaction variant Uncertain significance 2.00E-05 1 1.40E-05 2:178802247 G/A rs528853682 Structural interaction variant Conflicting interpretations of pathogenicity 6.01E-05 3 8.38E-05 2:178802307 A/T Structural interaction variant 2.00E-05 1 2:178804554 C/T rs767153909 Structural interaction variant Uncertain significance 2.00E-05 1 2:178804562 A/G Structural interaction variant 4.01E-05 2 2:178804570 A/C Structural interaction variant 2.00E-05 1 187 2:178804572 G/A rs536235994 Structural interaction variant 2.00E-05 1 6.98E-06 2:178804572 G/T rs536235994 Structural interaction variant 4.01E-05 2 1.40E-05 2:178804577 G/A rs143623862 Structural interaction variant Likely benign 2.00E-05 1 6.98E-05 2:178804580 A/G rs755356877 Structural interaction variant 2.00E-05 1 2:178804597 C/T rs756212082 Protein protein contact 8.02E-05 4 2.09E-05 2:178804598 A/G rs371454228 Structural interaction variant 2.00E-05 1 6.98E-06 2:178804600 C/T rs201857541 Structural interaction variant Conflicting interpretations of pathogenicity 6.01E-05 3 0.00010 188 2:178804601 G/A rs925948430 Protein protein contact Likely benign 6.01E-05 3 6.98E-06 2:178804616 C/T rs760305568 Structural interaction variant Likely benign 8.02E-05 4 2.79E-05 2:178804617 G/A rs146123323 Structural interaction variant Uncertain significance 2.00E-05 1 2.79E-05 2:178804623 G/A rs761344572 Protein protein contact 2.00E-05 1 6.98E-06 2:178804638 G/A Structural interaction variant 2.00E-05 1 2:178804639 T/G Structural interaction variant 4.01E-05 2 Only TTNv in exons with PSI â¥ 90 are shown included in this table. gnomAD allele frequencies were obtained from the v3 dataset. Chr:Pos indicates chromosome:position (hg38); freq., frequency; Ref/Alt, reference/alternative; TTNv, titin variant; UKB, UK Biobank. 189 Table A.4 Participant characteristics, without or with AF. Values include events during follow-up and are presented as n (%) or mean ± SD. AF indicates atrial fibrillation; TTNv, titin variant. Characteristic Without AF (n = 46808) With AF (n = 3073) P value Female sex 26105 (55.8%) 1105 (36.0%) <0.001 Age at recruitment 56.2 ± 8.00 62.0 ± 6.03 <0.001 TTNv 286 (0.6%) 51 (1.7%) <0.001 Angina 2720 (5.8%) 673 (21.9%) <0.001 Diabetes mellitus 3630 (7.8%) 593 (19.3%) <0.001 Dilated cardiomyopathy 53 (0.1%) 70 (2.3%) <0.001 Heart failure 570 (1.2%) 644 (21.0%) <0.001 Hypertension 15543 (33.2%) 2137 (69.5%) <0.001 Myocardial infarction 1401 (3.0%) 392 (12.8%) <0.001 Stroke 1418 (3.0%) 402 (13.1%) <0.001 Thrombosis event 1197 (2.6%) 184 (6.0%) <0.001 Revascularization procedure 1752 (3.7%) 477 (15.5%) <0.001 Peripheral vascular disease 480 (1.0%) 222 (7.2%) <0.001 190 Table A.5 Participant characteristics, AF without or with TTNv. Values include events during follow-up and are presented as n (%) or mean ± SD. AF indicates atrial fibrillation; TTNv, titin variant. Characteristic AF without TTNv (n = 3022) AF with TTNv (n = 51) P value Female sex 1085 (35.9%) 20 (39.2%) 0.66 Age at recruitment 62.0 ± 6.02 61.7 ± 6.39 0.16 Angina 659 (21.8%) 14 (27.5%) 0.31 Diabetes mellitus 581 (19.2%) 12 (23.5%) 0.47 Dilated cardiomyopathy 59 (2.0%) 11 (21.6%) <0.001 Heart failure 627 (20.7%) 17 (33.3%) 0.036 Hypertension 2109 (69.8%) 28 (54.9%) 0.031 Myocardial infarction 386 (12.8%) 6 (11.8%) 1 Stroke 396 (13.1%) 6 (11.8%) 1 Thrombosis event 180 (6.0%) 4 (7.8%) 0.55 Revascularization procedure 472 (15.6%) 5 (9.8%) 0.33 Peripheral vascular disease 221 (7.3%) 1 (2.0%) 0.18 191 Table A.6 Adjusted hazard ratio (aHR) and 95% confidence interval (CI) for TTNv carriers versus non-carriers and disease risk since enrolment. TTNv LOF TTNv Disease aHR 95% CI P-value aHR 95% CI P-value AF 2.10 1.49â2.95 2.31E-05 2.56 1.75â3.74 1.34E-06 AF with DCM excluded 1.96 1.33â2.89 0.00064 2.49 1.60â3.86 5.19E-05 AF with related individuals excluded 2.12 1.41â3.20 0.00030 2.78 1.79â4.32 5.57E-06 HF 1.20 0.72â2.01 0.49 1.14 0.64â2.04 0.65 DCM 7.84 3.54â17.37 3.79E-07 9.16 4.12â20.38 5.71E-08 Composite cardiovascular event 1.18 0.84â1.66 0.34 1.20 0.81â1.77 0.36 AF indicates atrial fibrillation; DCM, dilated cardiomyopathy; HF, heart failure; LOF, loss-of-function; TTNv, titin variant. 192 Table A.7 Stroke rates of AF patients without or with TTNv, grouped by CHA2DS2-VASc score < 2 and â¥ 2. AF without TTNv (n = 3022) AF with TTNv (n = 51) CHA2DS2-VASc score category No. of patients No. of stroke events Follow-up time (person-years) Stroke rate per 100 person-years No. of patients No. of stroke events Follow-up time (person-years) Stroke rate per 100 person-years Score < 2 1479 97 14654.90 0.66 25 1 242.18 0.41 Score â¥ 2 1543 159 14376.04 1.11 26 4 246.10 1.63 AF indicates atrial fibrillation; TTNv, titin variant. 193 Table A.8 Risk of DCM or HF after AF following initial AF diagnosis. TTNv LOF TTNv Disease after AF aHR 95% CI P-value aHR 95% CI P-value DCM after AF 11.39 5.10â25.45 3.04E-09 12.00 5.36â26.85 1.47E-09 6 months blanking 16.32 5.02â53.13 3.51E-06 16.81 5.18â54.58 2.66E-06 12 months blanking 13.23 3.48â50.35 0.00015 13.63 3.59â51.80 0.00013 HF after AF 1.38 0.77â2.46 0.28 1.43 0.78â2.61 0.25 6 months blanking 1.33 0.59â3.03 0.49 1.25 0.51â3.07 0.62 12 months blanking 1.30 0.53â3.20 0.56 1.46 0.60â3.59 0.41 AF indicates atrial fibrillation; DCM, dilated cardiomyopathy; HF, heart failure; LOF, loss-of-function; TTNv, titin variant. 194 Table A.9 Multivariate Cox regression analysis for the association between TTNv and modifiable risk factors and AF since enrolment. Variables aHR 95% CI P-value TTNv 2.10 1.49â2.95 2.31E-05 Hypertension 2.33 2.11â2.57 < 2E-16 Diabetes 1.19 1.07â1.34 0.0020 Obesity 1.27 1.16â1.40 1.65E-07 Current smoking 1.14 0.99â1.31 0.073 DCM 1.74 1.28â2.37 0.00040 HF 6.92 6.18â7.76 < 2E-16 Other co-variates included in the model: sex, age at enrolment, 1st 4 principal components of ancestry. AF indicates atrial fibrillation; DCM, dilated cardiomyopathy; HF, heart failure; TTNv, titin variant. Table A.10 Adjusted hazard ratio (aHR) and 95% confidence interval (CI) for AF stratified by risk factor level and PRS group since enrolment. Risk factor level PRS group aHR 95% CI P-value No modifiable risk factor Low 1 -- -- Low Low 2.19 2.11â2.28 < 2E-16 Intermediate Low 3.40 3.26â3.55 < 2E-16 High Low 5.03 4.78â5.30 < 2E-16 Low High 4.89 4.53â5.29 < 2E-16 195 Intermediate High 6.77 6.17â7.44 < 2E-16 High High 9.72 8.47â11.14 < 2E-16 No modifiable risk factor High 2.50 2.26â2.76 < 2E-16 Participants without hypertension, diabetes, obesity, or current smoking and within the low PRS group were used as the reference. Other co-variates included in the model: sex, age at enrolment, 1st 4 principal components of ancestry. AF indicates atrial fibrillation; PRS, polygenic risk score. Table A.11 Power analysis results. Interaction No. of TTNv carriers with risk factor Power No. of subjects required TTNv * hypertension 117 0.29 199415 TTNv * diabetes 38 0.15 452689 TTNv * obesity 98 0.27 218970 TTNv * current smoking 27 0.12 612847 Power analyses were performed using the R package âpowerSurvEpiâ version 0.1.0 with θ = 2.10 and α = 0.05. TTNv indicates titin variant. A.2 Supplemental Figures 196 Figure A.1 Locations of identified TTNv along the titin protein. Only TTNv with PSI â¥ 90 are shown for AF and non-AF participants. AF indicates atrial fibrillation; TTNv, titin variant. 197 Figure A.2 Cumulative incidence of DCM, HF, and composite events after an AF diagnosis. 198 Incidence of A, DCM, B, HF, and C, composite cardiovascular disease events defined as HF, stroke, or death in previously disease-free AF patients. The x-axis shows time to event in years where time zero is the earliest AF diagnosis. AF indicates atrial fibrillation; CCE, composite cardiovascular disease event; DCM, dilated cardiomyopathy; HF, heart failure; TTNv, titin variant. Figure A.3 Cumulative incidence of AF stratified by PRS group. Incidence of AF in high PRS versus low PRS groups. The x-axis shows time to event in years where birth is time zero. AF indicates atrial fibrillation; PRS, polygenic risk score. 199 Figure A.4 Risk of AF stratified by modifiable risk factor level and PRS group since enrolment. Adjusted hazard ratios for AF. Vertical lines represent the 95% confidence intervals. Participants were grouped by the number of modifiable risk factors present into High (3 or 4 risk factors), Intermediate (2 risk factors), Low (1 risk factor), or None (zero risk factors). Participants with zero modifiable risk factors and low PRS were used as the reference group. AF indicates, atrial fibrillation; aHR, adjusted hazard ratio; CI, confidence interval; PRS, polygenic risk score. 200 Appendix B B.1 Supplemental Tables Table B.1 Custom CRISPR/Cas9 oligonucleotide sequences. Oligonucleotide Sequence IDT Alt-R® CRISPR-Cas9 crRNA GCAAGGAATTCACTGTTACTTGG IDT Ultramer® DNA Oligo homology directed repair template GGTTTGATAGCTTCCTTTAGCTCTGCAGGGCGCCCAATACCAACTTGGTTTTGGGCACACACCCTGAACTCATATTCCTGGTTTTCATCCAAGCTGGTAACAGTGAATTCCTTGCGTACAAGCTGTG Table B.2 CRISPR/Cas9 on-target editing efficiencies. Cell line Genotype Clones screened Efficiency AF patient iPSCs WT/TTNtv ï WT/WT 80 6.3% (5/80) AF indicates atrial fibrillation; TTNtv, titin truncating variant; WT, wild-type. 201 Table B.3 CRISPR/Cas9 predicted off-target sites. Atrial fibrillation patient iPSCs: WT/TTNtv ï WT/WT Gene Sequence Mismatch Locus CFD Score SLC16A3 TCCACGAAGTCACTGTTACT GGG 4 chr17: 80192408-80192430:- 0.2085 KLHL2 KLHL2P1 GCCAAGGATTCACTGTCACT GGG GCCAAGGATTCACTGTCACT GGG 4 4 chr4: 166141149-166141171:- chr4: 120255546-120255568:- 0.1851 0.1851 LEKR1 GCCAGGAATTCACTGTAACT GAG 2 chr3: 156763593-156763615:+ 0.0593 ELOF1 ACAAGGAAGCCACTGTTCCT GGG 4 chr19: 11666196-11666218:+ 0.0566 LZTS3 GCAAAGAATTCACTGCCACC AGG 4 chr20: 3149060-3149082:+ 0.0371 Chr indicates chromosome; CFD, cutting frequency determination; TTNtv, titin truncating variant; WT, wild-type. 202 Table B.4 Primer sequences. Assay Gene/Target Sequence (5â-3â) PCR: genotyping by Sanger sequencing Titin truncating variant TACAGAATCTCCTCCCAGACCA GCTCTCACTATGACCAGTTTCC SLC16A3 TACCAGTATGAGCGGGACCT CCCCTTTCCTTGGGTTCCTC KLHL2 KLHL2P1 GAACTTGGACACCAGGGAGG ATAGAGGAGCCCCACACCAT LEKR1 CCACCACTTTCCCAACCTCA ATCTGCTTGTAGTGGCGCAA ELOF1 AGAGGAGACTTGTGGGGCT CCGCAGTTCCTCAAAAGCAC LZTS3 ACTGACGGAGCCTCTCTCAG TCCCTGCCTGGTTTATGCAG RT-qPCR: iPSC-CM characterization TNNT2 TTCACCAAAGATCTGCTCCT TACTGGTGTGGAGTGGGTG TTN All GTAAAAAGAGCTGCCCCAGTGA GCTAGGTGGCCCAGTGCTACT IRX4 TTCCGTTCTGAAGCGTGGTC TGAAGCAGGCAATTATTGGTGT MYL2 ACAGGGATGGCTTCATTGAC CCGCTCCCTTAAGTTTCTCC 203 TBX5 CTTGTGATGTTTTCAGAGCC TTCTCTCTAAAAGCAAGCGT NPPA ACAGGATTGGAGCCCAGAG GGAGCCTCTTGCAGTCTGTC KCNJ3 CTGCTCAAAGGATGACTTGT CATGGAACTGGGAGTAATCA KCNA5 CGAGGATGAGGGCTTCATTA CTGAACTCAGGCAGGGTCTC GAPDH CAAGAGCACAAGAGGAAGAGAG CTACATGGCAACTGTGAGGAG PCR indicates polymerase chain reaction; RT-qPCR, reverse transcription quantitative polymerase chain reaction. Table B.5 Participant characteristics at recruitment. Participant Titin genotype Sex Ethnicity Age Presentation Early-onset atrial fibrillation (age 18) Heterozygous titin truncating variant. c.63624_63627delCAGC (NM_001267550.2) p.Ser21134Trpfs*25 (NP_001254479.2) Male Asian 56 Paroxysmal atrial fibrillation managed by Sotalol. Hypertension. Dyslipidemia. History of IgA nephropathy and mitral valve prolapse. Reduced renal function. 204 Normal biventricular size, function, and geometry. Table B.6 Univariate linear regression of contractility measurements by genotype in beat rate-matched engineered heart tissues. Cell Type Variable Effect Estimate SEM P-value Ventricular Average Contraction Amplitude (mN) 0.006942 0.005607 0.215706 Beats-per-minute 1.319934 20.87343 0.949579 Contraction Velocity (mN/s) 0.020781 0.109776 0.849854 Relaxation Velocity (mN/s) 0.015698 0.106628 0.882953 Resting Time (s) 0.029957 0.054726 0.584099 Average Peak Widths (s) -0.03802 0.06746 0.573025 Contraction Time T1 (s) -0.03839 0.071697 0.592358 Relaxation Time T2 (s) 0.00688 0.028481 0.809121 Atrial Average Contraction Amplitude (mN) -0.01959 0.005727 0.000623 Beats-per-minute -8.22618 20.00616 0.680939 Contraction Velocity (mN/s) -0.2429 0.082576 0.003266 Relaxation Velocity (mN/s) -0.09508 0.045055 0.034831 Resting Time (s) 0.009221 0.047221 0.845182 Average Peak Widths (s) -0.00387 0.019933 0.846214 Contraction Time T1 (s) 0.018951 0.01399 0.175538 Relaxation Time T2 (s) 0.003816 0.033008 0.907958 205 Table B.7 Significantly differentially spliced genes in atrial WT/TTNtv and isogenic WT/WT engineered heart tissues. Gene Name Exon Start Exon End Ratio difference Adjusted P-value Splicing event type COL16A1 31702120 31702227 -0.303061928 0.011207 Spliced Exon TPM1 63061197 63061273 -0.170830725 4.49E-14 Spliced Exon SIPA1L2 232533489 232533583 -0.119322096 0.032502 Spliced Exon SIPA1L2 232574173 232574222 -0.11464023 0.021224 Spliced Exon FHL2 105396646 105396697 -0.100184577 4.32E-06 Spliced Exon AC109583.1 46811105 46811873 -0.202607315 1.07E-22 Spliced Exon MAP4 47909037 47912421 0.129839162 0.016973 Spliced Exon RBM24 17290848 17290893 0.107057492 0.005013 Spliced Exon LAMA2 129475389 129475401 0.147056086 0.026181 Spliced Exon ACTB 5529018 5529059 0.120249052 1.08E-16 Spliced Exon ATP5F1C 7806973 7807010 -0.220128247 4.18E-06 Spliced Exon POSTN 37574571 37574652 0.297028903 0.005883 Spliced Exon ACTN1 68878988 68879069 -0.206702849 0.001749 Spliced Exon 206 ACTG1 81511762 81511803 0.231863818 3.25E-58 Spliced Exon TMEM259 1010990 1011095 0.125036128 0.013237 Spliced Exon EMC10 50481860 50481947 0.127787939 6.10E-12 Spliced Exon GNAS 58889525 58889549 -0.209209106 2.39E-16 Spliced Exon TNRC6B 40281118 40281289 0.388665087 0.003459 Spliced Exon AC109583.1 46811105 46811873 -0.202607315 5.16E-23 Retained Intron TPM1 63061197 63061273 -0.170830725 3.81E-14 Mutually Exclusive Exon ERBB4 211657753 211657828 -0.270791406 0.010619 Mutually Exclusive Exon RBM24 17290848 17290893 0.107057492 0.005059 Mutually Exclusive Exon ACTN1 68878988 68879069 -0.206702849 0.001695 Mutually Exclusive Exon TMEM259 1010990 1011095 0.125036128 0.011756 Mutually Exclusive Exon MIB2 1624964 1624989 -0.241959315 0.04038 Alternative 3' Splice Site TPM1 63043468 63043704 -0.149459796 2.10E-13 Alternative 3' Splice Site TPM1 63061197 63061711 -0.145303259 2.38E-10 Alternative 3' Splice Site PDLIM5 94575615 94575941 -0.151059192 0.000354 Alternative 3' Splice Site 207 PDE4DIP 148992254 148993483 0.216695568 0.010971 Alternative 3' Splice Site MYL7 44140428 44140517 -0.109655235 1.17E-116 Alternative 3' Splice Site KCP 128891088 128891096 -0.617695153 0.008604 Alternative 3' Splice Site B4GALNT3 545139 545367 0.202645055 0.000134 Alternative 3' Splice Site ENO2 6915435 6915819 -0.107052514 1.65E-05 Alternative 3' Splice Site ENO2 6915435 6915816 -0.107585547 1.62E-05 Alternative 3' Splice Site KRT8 52949579 52949585 -0.101549952 0.047282 Alternative 3' Splice Site SERF2 43798868 43798942 0.246993566 0.0286 Alternative 3' Splice Site HCFC1R1 3023531 3023968 0.256674858 1.93E-05 Alternative 3' Splice Site ACTG1 81511627 81511803 0.18912013 1.64E-36 Alternative 3' Splice Site TPM1 63060940 63061273 -0.144331992 3.26E-10 Alternative 5' Splice Site MYL3 46861296 46861684 -0.114943173 2.55E-25 Alternative 5' Splice Site CRYAB 111913596 111913897 0.277299771 6.40E-16 Alternative 5' Splice Site ATP2A2 110346322 110347791 -0.102499935 4.02E-18 Alternative 5' Splice Site YPEL3 30096614 30096915 0.314238159 0.000203 Alternative 5' Splice Site 208 ZFP36 39406929 39407109 -0.212587558 0.003216 Alternative 5' Splice Site GNAS 58889214 58889353 -0.194003668 1.37E-14 Alternative 5' Splice Site GNAS 58889333 58889353 -0.177813552 3.85E-14 Alternative 5' Splice Site GNAS 58889354 58889549 -0.202198528 6.40E-16 Alternative 5' Splice Site GNAS 58889214 58889549 -0.200449243 1.00E-15 Alternative 5' Splice Site GNAS 58889407 58889549 -0.20552399 9.81E-17 Alternative 5' Splice Site GNAS 58889333 58889549 -0.200125858 8.41E-16 Alternative 5' Splice Site GNAS 58889354 58889406 -0.185899016 9.04E-13 Alternative 5' Splice Site GNAS 58889214 58889406 -0.192896132 3.04E-14 Alternative 5' Splice Site GNAS 58889333 58889406 -0.185746182 2.99E-13 Alternative 5' Splice Site GNAS 58889214 58889332 -0.19616702 1.26E-14 Alternative 5' Splice Site TTNtv indicates titin truncating variant; WT, wild-type. Table B.8 Significantly differentially spliced genes in ventricular WT/TTNtv and isogenic WT/WT engineered heart tissues. Gene Name Exon Start Exon End Ratio difference Adjusted P-value Splicing event type ADCY5 123296979 123297054 0.13876064 2.04E-07 Spliced Exon 209 RPS24 78040200 78040225 0.152983148 0.003475 Spliced Exon RPS24 78037964 78037982 0.201641219 3.13E-05 Spliced Exon RPS24 78040203 78040225 0.145676338 0.002271 Spliced Exon RPS24 78037964 78037993 0.216746383 0.001785 Spliced Exon NACA 56715870 56716110 0.22077717 0.002591 Spliced Exon WARS1 100375282 100375406 -0.314919305 0.042279 Spliced Exon WARS1 100375282 100375403 -0.313966667 0.042279 Spliced Exon ACTG1 81511762 81511803 0.166542068 4.30E-11 Spliced Exon TPM4 16095263 16095357 0.309618907 0.003455 Spliced Exon GNAS 58889525 58889549 -0.151298113 1.72E-08 Spliced Exon EIF4G2 10808704 10808940 0.134168855 0.000783 Retained Intron RPS24 78037964 78037982 0.201641219 4.30E-05 Mutually Exclusive Exon RPS24 78037964 78037993 0.216746383 0.001358 Mutually Exclusive Exon NACA 56715870 56716110 0.22077717 0.001882 Mutually Exclusive Exon WARS1 100375282 100375406 -0.314919305 0.027557 Mutually Exclusive Exon 210 WARS1 100375282 100375350 -0.291749779 0.043183 Mutually Exclusive Exon WARS1 100375282 100375403 -0.313966667 0.027557 Mutually Exclusive Exon TNNT2 201367804 201367806 0.104067197 6.03E-14 Alternative 3' Splice Site MAP4 47852939 47853039 -0.158068226 0.012278 Alternative 3' Splice Site VDAC1 133993016 133993018 -0.127367196 0.00014 Alternative 3' Splice Site WARS1 100375351 100375406 -0.340871859 0.03057 Alternative 3' Splice Site WARS1 100375351 100375403 -0.340314706 0.03057 Alternative 3' Splice Site CTDNEP1 7251413 7251601 0.203556757 4.04E-07 Alternative 3' Splice Site ACTG1 81511627 81511803 0.12124877 0.000142 Alternative 3' Splice Site HSPB1 76303845 76303888 0.109949247 5.50E-29 Alternative 5' Splice Site HSPB1 76303845 76303882 0.10864134 4.37E-31 Alternative 5' Splice Site CRYAB 111910632 111910852 -0.107059692 0.001672 Alternative 5' Splice Site CRYAB 111910632 111910830 -0.111446648 0.001015 Alternative 5' Splice Site CRYAB 111910669 111910852 -0.105345815 0.002644 Alternative 5' Splice Site GNAS 58889214 58889353 -0.219466034 9.08E-19 Alternative 5' Splice Site 211 GNAS 58889333 58889353 -0.229812597 2.02E-19 Alternative 5' Splice Site GNAS 58889354 58889549 -0.164079373 2.12E-10 Alternative 5' Splice Site GNAS 58889214 58889549 -0.18843914 5.73E-14 Alternative 5' Splice Site GNAS 58889407 58889549 -0.171590295 3.70E-11 Alternative 5' Splice Site GNAS 58889333 58889549 -0.172845968 2.02E-11 Alternative 5' Splice Site GNAS 58889354 58889406 -0.140911576 5.71E-08 Alternative 5' Splice Site GNAS 58889214 58889406 -0.201006346 5.23E-16 Alternative 5' Splice Site GNAS 58889333 58889406 -0.175522242 9.36E-12 Alternative 5' Splice Site GNAS 58889214 58889332 -0.21646305 1.05E-18 Alternative 5' Splice Site TTNtv indicates titin truncating variant; WT, wild-type. Table B.9 Significantly downregulated genes in atrial WT/TTNtv relative to isogenic WT/WT engineered heart tissues. Gene stable ID Gene name Gene description log2 Fold Change Adjusted P-value ENSG00000119411 BSPRY B-box and SPRY domain containing -3.47367 0.019887 ENSG00000137434 C6orf52 chromosome 6 open reading frame 52 -3.30707 0.00138 ENSG00000138669 PRKG2 protein kinase cGMP-dependent 2 -3.26698 0.009476 212 ENSG00000143171 RXRG retinoid X receptor gamma -2.38815 0.00376 ENSG00000157119 KLHL40 kelch like family member 40 -4.27097 0.009476 ENSG00000178403 NEUROG2 neurogenin 2 -5.04081 0.040403 ENSG00000184470 TXNRD2 thioredoxin reductase 2 -8.04512 0.01302 ENSG00000188321 ZNF559 zinc finger protein 559 -7.552 0.000155 ENSG00000188393 CLEC2A C-type lectin domain family 2 member A -5.71134 1.23E-05 ENSG00000206532 RP11-553A10.1 -4.28411 2.93E-05 ENSG00000217330 SSXP10 SSX family pseudogene 10 -7.3713 0.000252 ENSG00000250616 YPEL3-DT YPEL3 divergent transcript -3.53372 0.002404 ENSG00000260088 DDX59-AS1 DDX59 antisense RNA 1 -4.77757 0.000888 TTNtv indicates titin truncating variant; WT, wild-type. Table B.10 Significantly upregulated genes in atrial WT/TTNtv relative to isogenic WT/WT engineered heart tissues. Gene stable ID Gene name Gene description log2FoldChange Adjusted P-value ENSG00000053747 LAMA3 laminin subunit alpha 3 4.73246535 0.007761752 ENSG00000075407 ZNF37A zinc finger protein 37A 6.961820548 2.33E-10 213 ENSG00000077943 ITGA8 integrin subunit alpha 8 4.123297475 0.009475613 ENSG00000078081 LAMP3 lysosomal associated membrane protein 3 6.587032331 0.013303784 ENSG00000087116 ADAMTS2 ADAM metallopeptidase with thrombospondin type 1 motif 2 4.700112636 0.00192069 ENSG00000102802 MEDAG mesenteric estrogen dependent adipogenesis 5.466979678 0.006310348 ENSG00000106278 PTPRZ1 protein tyrosine phosphatase receptor type Z1 5.089726357 0.004878801 ENSG00000106483 SFRP4 secreted frizzled related protein 4 6.699140575 0.008100616 ENSG00000108846 ABCC3 ATP binding cassette subfamily C member 3 3.674480799 0.02443468 ENSG00000109193 SULT1E1 sulfotransferase family 1E member 1 6.905738139 0.009475613 ENSG00000112562 SMOC2 SPARC related modular calcium binding 2 5.485283399 0.021048328 ENSG00000113209 PCDHB5 protocadherin beta 5 3.089478251 0.007953563 ENSG00000113248 PCDHB15 protocadherin beta 15 3.747232345 1.80E-10 ENSG00000121297 TSHZ3 teashirt zinc finger homeobox 3 2.888817169 0.01751481 ENSG00000125618 PAX8 paired box 8 7.141347937 0.001355237 ENSG00000129317 PUS7L pseudouridine synthase 7 like 8.925461098 1.09E-06 214 ENSG00000130600 H19 H19 imprinted maternally expressed transcript 7.264879772 0.03254399 ENSG00000134240 HMGCS2 3-hydroxy-3-methylglutaryl-CoA synthase 2 17.11923388 0.034676146 ENSG00000136010 ALDH1L2 aldehyde dehydrogenase 1 family member L2 4.465388416 0.000137723 ENSG00000140538 NTRK3 neurotrophic receptor tyrosine kinase 3 4.558324091 0.008206936 ENSG00000145908 ZNF300 zinc finger protein 300 6.10519421 2.59E-07 ENSG00000149451 ADAM33 ADAM metallopeptidase domain 33 4.667785584 0.000371649 ENSG00000154277 UCHL1 ubiquitin C-terminal hydrolase L1 5.080177949 0.000251852 ENSG00000156265 MAP3K7CL MAP3K7 C-terminal like 5.50514234 0.001181619 ENSG00000157554 ERG ETS transcription factor ERG 6.687241778 0.012952016 ENSG00000159403 C1R complement C1r 3.192951937 0.017026672 ENSG00000163661 PTX3 pentraxin 3 3.972852419 0.008100616 ENSG00000164161 HHIP hedgehog interacting protein 3.96440239 0.01988705 ENSG00000164220 F2RL2 coagulation factor II thrombin receptor like 2 3.83713954 0.034445456 ENSG00000165300 SLITRK5 SLIT and NTRK like family member 5 3.840579396 0.007137213 ENSG00000166257 SCN3B sodium voltage-gated channel beta subunit 3 3.579458424 0.034445456 215 ENSG00000167637 ZNF283 zinc finger protein 283 9.593265443 8.76E-09 ENSG00000169432 SCN9A sodium voltage-gated channel alpha subunit 9 3.380581054 0.000616209 ENSG00000170477 KRT4 keratin 4 5.592746472 0.02443468 ENSG00000171291 ZNF439 zinc finger protein 439 5.503237958 6.21E-14 ENSG00000171466 ZNF562 zinc finger protein 562 8.846749211 5.22E-17 ENSG00000174080 CTSF cathepsin F 5.722741884 0.007953563 ENSG00000176971 FIBIN fin bud initiation factor homolog 4.252020748 0.005431214 ENSG00000177932 ZNF354C zinc finger protein 354C 3.85601352 0.030869795 ENSG00000178187 ZNF454 zinc finger protein 454 4.465514068 0.005243655 ENSG00000179542 SLITRK4 SLIT and NTRK like family member 4 2.884967354 0.022471867 ENSG00000180543 TSPYL5 TSPY like 5 12.67580153 2.12E-16 ENSG00000181291 TMEM132E transmembrane protein 132E 4.324064453 0.002848939 ENSG00000183715 OPCML opioid binding protein/cell adhesion molecule like 2.548859592 0.038679978 ENSG00000185070 FLRT2 fibronectin leucine rich transmembrane protein 2 3.224744513 0.015020896 ENSG00000185215 TNFAIP2 TNF alpha induced protein 2 4.060394089 0.02932957 216 ENSG00000185869 ZNF829 zinc finger protein 829 9.512833358 2.33E-08 ENSG00000186446 ZNF501 zinc finger protein 501 5.16042094 2.00E-07 ENSG00000187955 COL14A1 collagen type XIV alpha 1 chain 3.711935178 1.46E-05 ENSG00000187957 DNER delta/notch like EGF repeat containing 4.419727036 0.029458148 ENSG00000189129 PLAC9 placenta associated 9 4.650679649 0.04997267 ENSG00000189223 PAX8-AS1 PAX8 antisense RNA 1 8.844898287 1.65E-19 ENSG00000196268 ZNF493 zinc finger protein 493 4.32394697 0.000222539 ENSG00000196867 ZFP28 ZFP28 zinc finger protein 8.3601092 3.62E-08 ENSG00000197608 ZNF841 zinc finger protein 841 6.717254931 0.00583753 ENSG00000197928 ZNF677 zinc finger protein 677 11.58725394 7.03E-13 ENSG00000198001 IRAK4 interleukin 1 receptor associated kinase 4 8.054837003 1.52E-05 ENSG00000198121 LPAR1 lysophosphatidic acid receptor 1 3.525742039 0.001355237 ENSG00000198768 APCDD1L APC down-regulated 1 like 7.477195725 0.008579337 ENSG00000204969 PCDHA2 protocadherin alpha 2 6.280341079 0.021734506 ENSG00000205038 PKHD1L1 PKHD1 like 1 8.223526111 0.022373684 217 ENSG00000205403 CFI complement factor I 3.446871213 0.02443468 ENSG00000215146 zinc finger protein pseudogene 8.131461525 7.54E-05 ENSG00000224597 SVIL-AS1 SVIL antisense RNA 1 6.634598033 0.010415631 ENSG00000227124 ZNF717 zinc finger protein 717 8.089604774 7.48E-09 ENSG00000234773 zinc finger protein pseudogene 2.536211107 0.042637422 ENSG00000245680 ZNF585B zinc finger protein 585B 2.694229782 0.005666615 ENSG00000247516 MIR4458HG MIR4458 host gene 7.986597856 3.46E-05 ENSG00000250120 PCDHA10 protocadherin alpha 10 2.954184065 1.66E-05 ENSG00000253731 PCDHGA6 protocadherin gamma subfamily A, 6 3.620141284 0.031414742 ENSG00000253767 PCDHGA8 protocadherin gamma subfamily A, 8 2.803143838 0.003298428 ENSG00000253953 PCDHGB4 protocadherin gamma subfamily B, 4 2.543059282 3.46E-05 ENSG00000254221 PCDHGB1 protocadherin gamma subfamily B, 1 3.963078142 0.022373684 ENSG00000255366 novel lncRNA 7.478968041 0.004854819 ENSG00000263711 LINC02864 long intergenic non-protein coding RNA 2864 9.750600837 1.18E-08 ENSG00000267254 ZNF790-AS1 ZNF790 antisense RNA 1 5.158361744 0.03254399 218 ENSG00000267454 ZNF582-DT ZNF582 divergent transcript 4.496082871 0.036655923 ENSG00000278318 ZNF229 zinc finger protein 229 8.066497713 3.67E-12 ENSG00000278897 6.914451586 0.000251852 ENSG00000281406 BLACAT1 BLACAT1 overlapping LEMD1 locus 6.811191735 0.012952016 TTNtv indicates titin truncating variant; WT, wild-type. Table B.11 Significantly upregulated genes in ventricular WT/TTNtv relative to isogenic WT/WT engineered heart tissues. Gene stable ID Gene name Gene description log2FoldChange Adj. P-value ENSG00000075407 ZNF37A zinc finger protein 37A 7.553598887 6.21E-08 ENSG00000110446 SLC15A3 solute carrier family 15 member 3 4.677662572 0.037842 ENSG00000113248 PCDHB15 protocadherin beta 15 3.483071755 6.27E-09 ENSG00000119917 IFIT3 interferon induced protein with tetratricopeptide repeats 3 4.585193712 0.000108 ENSG00000120322 PCDHB8 protocadherin beta 8 2.750884908 0.014655 ENSG00000125618 PAX8 paired box 8 5.273166136 0.03645 ENSG00000129317 PUS7L pseudouridine synthase 7 like 7.172293317 3.08E-07 ENSG00000130600 H19 H19 imprinted maternally expressed transcript 8.113800368 0.0118 219 ENSG00000134321 RSAD2 radical S-adenosyl methionine domain containing 2 4.487811019 0.007546 ENSG00000136010 ALDH1L2 aldehyde dehydrogenase 1 family member L2 3.910717703 0.006694 ENSG00000145908 ZNF300 zinc finger protein 300 6.077428648 3.41E-06 ENSG00000148053 NTRK2 neurotrophic receptor tyrosine kinase 2 2.422081661 0.005305 ENSG00000167637 ZNF283 zinc finger protein 283 6.113981747 4.87E-06 ENSG00000171291 ZNF439 zinc finger protein 439 5.498734294 2.07E-11 ENSG00000171466 ZNF562 zinc finger protein 562 7.501896608 9.13E-14 ENSG00000174080 CTSF cathepsin F 6.363698718 0.049949 ENSG00000177932 ZNF354C zinc finger protein 354C 4.662710977 0.004087 ENSG00000180543 TSPYL5 TSPY like 5 8.426718801 1.45E-24 ENSG00000185869 ZNF829 zinc finger protein 829 6.801090794 4.45E-05 ENSG00000186446 ZNF501 zinc finger protein 501 5.519309359 3.41E-06 ENSG00000188313 PLSCR1 phospholipid scramblase 1 3.172239557 0.016319 ENSG00000189223 PAX8-AS1 PAX8 antisense RNA 1 9.367161469 9.13E-14 ENSG00000196268 ZNF493 zinc finger protein 493 4.514693814 0.000164 220 ENSG00000196867 ZFP28 ZFP28 zinc finger protein 7.655048369 8.78E-09 ENSG00000197928 ZNF677 zinc finger protein 677 7.863501949 5.55E-12 ENSG00000198001 IRAK4 interleukin 1 receptor associated kinase 4 8.56279668 2.20E-06 ENSG00000215146 zinc finger protein pseudogene 6.836732629 0.000444 ENSG00000227124 ZNF717 zinc finger protein 717 5.727448646 4.06E-06 ENSG00000247516 MIR4458HG MIR4458 host gene 6.189238115 0.010693 ENSG00000253953 PCDHGB4 protocadherin gamma subfamily B, 4 2.537513048 6.33E-05 ENSG00000254221 PCDHGB1 protocadherin gamma subfamily B, 1 5.616136067 0.008617 ENSG00000263711 LINC02864 long intergenic non-protein coding RNA 2864 8.478985464 1.31E-06 ENSG00000272674 PCDHB16 protocadherin beta 16 2.423355024 0.014768 ENSG00000278318 ZNF229 zinc finger protein 229 6.571400241 6.59E-10 ENSG00000278897 5.761487035 0.003287 Adj indicates adjusted; TTNtv, titin truncating variant; WT, wild-type. 221 B.2 Supplemental Figures Figure B.1 iPSC-CM electrophysiology characteristics. A, Maximal upstroke velocity of spontaneously beating atrial and ventricular iPSC-CMs (n = 3 differentiation batches per genotype). Action potential duration at 80% repolarization and 30% repolarization in, B, atrial iPSC-CMs paced at 100 beats-per-minute and, C, ventricular iPSC-CMs paced at 60 beats-per-minute. D, Representative trace of a missed beat in the calcium recording of ventricular WT/TTNtv iPSC-CMs. iPSC-CMs were co-stained with FluoVolt and Calbryte 630 AM. Voltage and calcium recordings were sequentially acquired at a pacing cycle length of 600ms (100 beats-per-minute). Mann-Whitney U test. TTNtv indicates titin truncating variant; Vel., velocity; WT, wild-type. 222 Figure B.2 Atrial and ventricular EHT characterization. A, Heatmap showing expression of cell type-specific markers in atrial and ventricular EHT samples (n = 3 per cell type; n = 3 per genotype). Colours represent z-scores of normalized gene counts. B, Diagram of contractility variables measured. C, Contraction (T1) and relaxation (T2) times of atrial EHTs (n = 8-17 EHTs). D, Contraction and relaxation velocities of atrial EHTs (n 223 = 8-17 EHTs). E, Contraction and relaxation velocities of ventricular EHTs (n = 10-17 EHTs). F, Contraction (T1) and relaxation (T2) times of ventricular EHTs (n = 10-17 EHTs). G, Spontaneous beat rates of atrial and ventricular EHTs (n = 8-17 EHTs). Data are presented as median Â± IQR; whiskers represent 1.5Ãinterquartile range. t-test. EHT indicates engineered heart tissue; TTNtv, titin truncating variant; WT, wild-type; Vel., velocity; *P < 0.05; **P < 0.01. Figure B.3 Contractile force generation in atrial and ventricular EHTs under paced conditions. A, Maximum contractile force in atrial EHTs paced at 75 beats-per-minute (n = 2-7 EHTs). B, Maximum contractile force in ventricular EHTs paced at 75 beats-per-minute (n = 7-10 EHTs). C, Maximum contractile force in atrial EHTs paced at 200 beats-per-minute (n = 3-12 EHTs). D, Maximum contractile force in ventricular EHTs paced at 200 beats-per-minute (n = 6-14 EHTs). Data are presented as median Â± IQR; whiskers represent 1.5Ãinterquartile range. t-test. EHT indicates engineered heart tissue; TTNtv, titin truncating variant; WT, wild-type. 224 Figure B.4 Allele balance and titin isoform usage in EHTs. A, Allele balance in EHTs assessed by titin truncating variant hit counts. B, Allele balance in EHTs assessed by read alignment and adjacent bases. C, Transcript isoform usage of N2B and N2BA titin isoforms in atrial EHTs. D, Transcript isoform usage of N2B and N2BA titin isoforms in ventricular EHTs. n = 3 EHTs per genotype and cell type. EHT indicates engineered heart tissue; TTNtv, titin truncating variant; WT, wild-type. 225 226 Figure B.5 Differential splicing analysis of atrial EHTs. Volcano plots of genes with A, skipped exons, B, mutually excluded exons, C, retained introns, D, alternative 5â splice sites, and E, alternative 3â splice sites in atrial WT/TTNtv and WT/WT EHTs (ratio difference < 0 indicates a splicing event in WT/WT EHTs; ratio difference > 0 indicates an event in WT/TTNtv EHTs). Events with an FDR-adjusted P-value < 0.05 and absolute ratio difference > 0.1 are considered significant. EHT indicates engineered heart tissue; TTNtv, titin truncating variant; WT, wild-type. 227 228 Figure B.6 Differential splicing analysis of ventricular EHTs. Volcano plots of genes with A, skipped exons, B, mutually excluded exons, C, retained introns, D, alternative 5â splice sites, and E, alternative 3â splice sites in ventricular WT/TTNtv and WT/WT EHTs (ratio difference < 0 indicates a splicing event in WT/WT EHTs; ratio difference > 0 indicates an event in WT/TTNtv EHTs). Events with an FDR-adjusted P-value < 0.05 and absolute ratio difference > 0.1 are considered significant. EHT indicates engineered heart tissue; TTNtv, titin truncating variant; WT, wild-type. 229 Appendix C C.1 Supplemental Tables Table C.1 Custom CRISPR/Cas9 oligonucleotide sequences. Oligonucleotide Sequence IDT Alt-R® CRISPR-Cas9 crRNA GCAAGGAATTCACTGTTACTTGG IDT Ultramer® DNA Oligo homology directed repair template GGTTTGATAGCTTCCTTTAGCTCTGCAGGGCGCCCAATACCAACTTGGTTTTGGGCACACACCCTGAACTCATATTCCTGGTTTTCATCCAAGCTGGTAACAGTGAATTCCTTGCGTACAAGCTGTG Table C.2 CRISPR/Cas9 on-target editing efficiencies. Cell line Genotype Clones screened Efficiency VF patient iPSCs WT/TTNtv ï WT/WT 42 9.5% (4/42) VF indicates ventricular fibrillation; TTNtv, titin truncating variant; WT, wild-type. Table C.3 CRISPR/Cas9 predicted off-target sites. Atrial fibrillation patient iPSCs: WT/TTNtv ï WT/WT Gene Sequence Mismatch Locus CFD Score 230 SLC16A3 TCCACGAAGTCACTGTTACT GGG 4 chr17: 80192408-80192430:- 0.2085 KLHL2 KLHL2P1 GCCAAGGATTCACTGTCACT GGG GCCAAGGATTCACTGTCACT GGG 4 4 chr4: 166141149-166141171:- chr4: 120255546-120255568:- 0.1851 0.1851 LEKR1 GCCAGGAATTCACTGTAACT GAG 2 chr3: 156763593-156763615:+ 0.0593 ELOF1 ACAAGGAAGCCACTGTTCCT GGG 4 chr19: 11666196-11666218:+ 0.0566 LZTS3 GCAAAGAATTCACTGCCACC AGG 4 chr20: 3149060-3149082:+ 0.0371 Chr indicates chromosome; CFD, cutting frequency determination; TTNtv, titin truncating variant; WT, wild-type. Table C.4 PCR genotyping primer sequences. Gene/Target Sequence (5â-3â) Titin truncating variant TACAGAATCTCCTCCCAGACCA GCTCTCACTATGACCAGTTTCC SLC16A3 TACCAGTATGAGCGGGACCT CCCCTTTCCTTGGGTTCCTC KLHL2 GAACTTGGACACCAGGGAGG 231 KLHL2P1 ATAGAGGAGCCCCACACCAT LEKR1 CCACCACTTTCCCAACCTCA ATCTGCTTGTAGTGGCGCAA ELOF1 AGAGGAGACTTGTGGGGCT CCGCAGTTCCTCAAAAGCAC LZTS3 ACTGACGGAGCCTCTCTCAG TCCCTGCCTGGTTTATGCAG Table C.5 Participant characteristics at recruitment. Participant Titin genotype Sex Ethnicity Age Presentation Ventricular fibrillation patient (age 13) Heterozygous titin truncating variant. c.63624_63627delCAGC (NM_001267550.2) p.Ser21134Trpfs*25 (NP_001254479.2) Female Asian 13 Unexplained sudden cardiac arrest during exercise. Ventricular fibrillation. No imaging evidence of dilated cardiomyopathy. Table C.6 Comparison of calcium transient durations in ventricular iPSC-CMs paced at 60 beats-per-minute. Variable Comparison group 1 Comparison group 2 P-value 232 CaTD80 WT/TTNtv WT/WT 0.026224 CaTD70 WT/TTNtv WT/WT 0.037879 CaTD60 WT/TTNtv WT/WT 0.037879 CaTD50 WT/TTNtv WT/WT 0.011072 CaTD40 WT/TTNtv WT/WT 0.004079 CaTD30 WT/TTNtv WT/WT 0.017483 CaTD indicates calcium transient duration; TTNtv, titin truncating variant; WT, wild-type. 233 C.2 Supplemental Figures Figure C.1 iPSC-CM flow cytometry gating strategy. Gating strategy implemented to analyze the expression of cTnT and MLC2v in atrial and ventricular iPSC-CMs. iPSCs co-stained with cTnT and MLC2v were used as the negative cell type control for gating. cTnT indicates cardiac troponin T; FS, forward scatter; MLC2v, ventricular paralog of myosin light chain 2; SS, side scatter. 234 Figure C.2 Spontaneously beating iPSC-CM electrophysiology characteristics. A, Characterization of rate-corrected calcium transient duration at 30% repolarization between atrial and ventricular iPSC-CMs. (n = 4-8 differentiation batches). B, Characterization of rate-corrected calcium transient durations at 80% and 30% repolarization and calcium transient triangulation index between atrial WT/TTNtv and WT/WT iPSC-CMs. (n = 4-6 differentiation batches). C, Characterization of rate-corrected calcium transient durations at 80% and 30% repolarization and calcium transient triangulation index between ventricular WT/TTNtv and 235 WT/WT iPSC-CMs. (n = 7-8 differentiation batches). Mann-Whitney U test. TTNtv indicates titin truncating variant; WT, wild-type; *P < 0.05. Figure C.3 Electrophysiological response to isoproterenol in iPSC-CMs A, Beat rate in spontaneously beating ventricular iPSC-CMs treated with vehicle control, 0.1 μM, or 1 μM isoproterenol (n = 2-4 differentiation batches). B, Action potential duration at 30% repolarization in ventricular iPSC-CMs paced at 60 beats-per-minute treated with vehicle control, 0.1 μM, or 1 μM isoproterenol (n = 3-5 differentiation batches). Mann-Whitney U test. ISO indicates isoproterenol; TTNtv, titin truncating variant; WT, wild-type; *P < 0.05. 236 Figure C.4 Contraction analysis in iPSC-CMs treated with isoproterenol. A, Contraction amplitude analysis in ventricular iPSC-CMs paced at 60 beats-per-minute treated with vehicle control, 0.1 μM, or 1 μM isoproterenol (n = 3-5 differentiation batches). B, Contraction amplitude analysis in spontaneously beating ventricular iPSC-CMs treated with vehicle control, 0.1 μM, or 1 μM isoproterenol (n = 2-5 differentiation batches). C, Contraction amplitude analysis in spontaneously beating atrial iPSC-CMs treated with vehicle control, 0.1 μM, or 1 μM isoproterenol (n = 1-3 differentiation batches). Mann-Whitney U test. ISO indicates isoproterenol; TTNtv, titin truncating variant; WT, wild-type; *P < 0.05. 237 Figure C.5 Atrial fibrillation patient iPSC-derived TTNtv EHTs display comparable contractile force generation in response to isoproterenol stimulation as WT EHTs. A, Maximum contractile force in atrial EHTs treated with increasing doses of isoproterenol (n=2-7 EHTs). B, Maximum contractile force in ventricular EHTs treated with increasing doses of isoproterenol (n=9-10 EHTs). EHTs were paced at 75 beats-per-minute. t-test. Data are presented as median Â± IQR; whiskers represent 1.5Ãinterquartile range. EHT indicates engineered heart tissue; TTNtv, titin truncating variant; WT, wild-type.
Thesis/Dissertation
eng
Experimental Medicine
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Brunham, Liam
Laksman, Zachary
Connecting the clinic to the bench : modelling the functional effects of a titin variant associated with atrial and ventricular arrhythmias
Text