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Next generation sequencing to determine a genetic cause of familial intracranial aneurysms Hitchcock, Emma Catherine 2017

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NEXT GENERATION SEQUENCING TO DETERMINE A GENETIC CAUSE OF FAMILIAL INTRACRANIAL ANEURYSMS  by Emma Catherine Hitchcock  B.Sc., The University of British Columbia, 2014  A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF  MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Medical Genetics)  THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver)  April 2017  © Emma Catherine Hitchcock, 2017  ii Abstract Intracranial aneurysms (IA), a common disease that occurs when cerebral arteries weaken and expand, can lead to subarachnoid hemorrhage upon rupture. The prevalence of IA is estimated to be around 3% and is known to increase with age. A small subset of the patient population has a familial form IA, where two or more first- to third- degree relatives have IA. At this time, one gene, THSD1, has been associated with familial IA (FIA). Here we present the preliminary findings from whole exome sequencing on five families diagnosed with FIA. Each family appears to have Mendelian segregation of disease (autosomal dominant, autosomal recessive, or X-linked) and has had their aneurysms clinically confirmed through brain imaging. Sequencing data from the proband of each family was used to identify family-specific candidate genes and was overlapped between families to identify genes that contain rare, possibly pathogenic variants in three or more families. Four genes -- DST, CRIPAK, DNAH1, and TTN --were found to contain rare variants in four out of the five families. Three top candidate genes were selected based on gene function or previous association to cerebral vascular disease from 38 genes that contain rare variants in three out of the five families.    iii Preface Identifying patient data are not reported. Ethics approval was required for Chapters 2 and 3, and was obtained from the University of British Columbia Children’s and Women’s Research Ethics Board (certificate numbers H09-01228 and H08-00784). Written, informed consent was obtained from all participants.  A version of Chapter 1 and the pedigrees for Families 1, 2, and 3 in Sections 3.2.1, 3.3.1, and 3.4.1, respectively, have previously been published: Hitchcock, E., and Gibson WT. A Review of the Genetics of Intracranial Berry Aneurysms and Implications for Genetic Counseling. Journal of Genetic Counseling 2017, Volume 26, Issue 1, pp 21–31, First Online: 14 October 2016. My review article summarizes previous genetic research on intracranial aneurysms, and on pleiotropic syndromes that confer increased risk for intracranial aneurysms. I researched and wrote the entire manuscript. Dr. W.T. Gibson contributed revisions and intellectually to the manuscript’s content.  Dr. W. T. Gibson and I designed a strategy for family recruitment and DNA analysis, in order to seek genetic causes of familial intracranial aneurysms. Families 1 and 2 were first identified and enrolled by Dr. W.T. Gibson. I enrolled all subsequent families in collaboration with Dr. G. Redekop, Head of Surgery at Vancouver General Hospital, and in collaboration with the Brain Aneurysm Foundation.  I collected DNA samples for this research. Jillian Diamond, a former summer student in the Gibson Laboratory, collected samples from five members of Family 1. I extracted genomic DNA from samples and performed all quality control and validation measures.  Dr. P. Eydoux, director of the Cytogenetic Laboratory at the Women’s and Children’s Health Centre of BC, performed genome-wide microarray on the third generation of Family 1, in  iv order to identify regions of identity-by-descent among the affected sibs that were not shared with the unaffected sibs.  I analyzed the results to select candidate copy number variants, and used quantitative PCR (qPCR) to perform validation of candidate variants.  Drs. S. Jones and Yaoqing Shen, both at the Michael Smith Genome Sciences Centre (GSC) carried out exome or genome sequencing on participant DNA, as well as the bioinformatic alignment of sequencing results. I then analyzed the variants identified by the GSC to create a list of candidate variants. Additionally, I compared candidate variants between families.     v Table of Contents Abstract .......................................................................................................................................... ii Preface ........................................................................................................................................... iii Table of Contents ...........................................................................................................................v List of Tables ................................................................................................................................ ix List of Figures ............................................................................................................................... xi List of Abbreviations .................................................................................................................. xii Acknowledgements ......................................................................................................................xv Chapter 1: Introduction  ...............................................................................................................1 1.1 Overview ......................................................................................................................... 1 1.2 Vascular Structure, Function, and Development ............................................................ 2 1.2.1 Vasculogenesis and Angiogenesis .............................................................................. 4 1.2.2 Blood-Brain Barrier .................................................................................................... 5 1.3 Familial Intracranial Aneurysms..................................................................................... 6 1.3.1 Genetics of IBA and FIA ............................................................................................ 8 1.3.1.1 Previous Research ............................................................................................... 8 1.3.1.1.1 Familial Mapping Studies ............................................................................. 9 1.3.1.1.2 Genome-Wide Association Studies ............................................................... 9 1.3.1.1.3 Whole-Exome Sequencing Studies ............................................................. 13 1.3.1.2 Associated Syndromes ...................................................................................... 15 1.3.1.2.1 Autosomal Dominant Polycystic Kidney Disease ...................................... 15 1.3.1.2.2 Ehlers-Danlos Syndrome............................................................................. 16 1.3.1.2.3 Loeys-Dietz Syndrome ................................................................................ 17  vi 1.3.1.2.4 Marfan Syndrome ........................................................................................ 18 1.3.1.2.5 Neurofibromatosis Type I ........................................................................... 18 1.3.1.2.6 Other Syndromes ......................................................................................... 19 1.3.1.2.7 Concluding Remarks ................................................................................... 20 1.3.1.3 Genetic Counselling .......................................................................................... 21 1.4 Objectives and Hypotheses ........................................................................................... 23 Chapter 2: Methods and Materials ............................................................................................25 2.1 Family and Clinical History .......................................................................................... 25 2.1.1 Data Collection Form ................................................................................................ 25 2.1.2 Family Selection ....................................................................................................... 25 2.2 DNA Collection and Extraction .................................................................................... 26 2.2.1 Quality Control ......................................................................................................... 28 2.3 Microarray..................................................................................................................... 29 2.3.1 Validation of Candidate CNV by qPCR ................................................................... 30 2.4 Next-Generation Sequencing ........................................................................................ 31 2.5 Variant List Annotation ................................................................................................ 31 2.6 Sanger Sequencing ........................................................................................................ 32 2.7 Overall Analysis Strategy ............................................................................................. 33 2.7.1 De Novo Variant Analysis ........................................................................................ 36 Chapter 3: Results........................................................................................................................38 3.1 Study Cohort ................................................................................................................. 38 3.2 Family 1 ........................................................................................................................ 40 3.2.1 Pedigree and Phenotype ............................................................................................ 40  vii 3.2.2 Microarray................................................................................................................. 43 3.2.3 Exome Sequencing.................................................................................................... 49 3.3 Family 2 ........................................................................................................................ 53 3.3.1 Pedigree and Phenotype ............................................................................................ 53 3.3.2 Genome Sequencing ................................................................................................. 56 3.4 Family 3 ........................................................................................................................ 58 3.4.1 Pedigree and Phenotype ............................................................................................ 58 3.4.2 Exome Sequencing.................................................................................................... 61 3.5 Family 4 ........................................................................................................................ 63 3.5.1 Pedigree and Phenotype ............................................................................................ 63 3.5.2 Exome Sequencing.................................................................................................... 66 3.6 Family 5 ........................................................................................................................ 66 3.6.1 Pedigree and Phenotype ............................................................................................ 66 3.6.2 Exome Sequencing.................................................................................................... 69 3.7 Comparative Analysis of Families ................................................................................ 72 3.7.1 Candidate Genes with Rare Variants in Four Families ............................................. 74 3.7.2 Candidate Genes with Rare Variants in Three Families ........................................... 77 Chapter 4: Discussion ..................................................................................................................81 4.1 Summary of Findings .................................................................................................... 81 4.2 Strengths ....................................................................................................................... 83 4.3 Limitations .................................................................................................................... 84 4.4 Future Research Directions ........................................................................................... 85 4.4.1 Cohort Recruitment and Sequencing ........................................................................ 85  viii 4.4.2 Animal Models.......................................................................................................... 85 4.4.2.1 Zebrafish ........................................................................................................... 86 4.4.2.2 Mice .................................................................................................................. 86 4.4.3 Functional Experiments ............................................................................................ 87 4.5 Significance of the Research ......................................................................................... 88 4.5.1 Screening Families .................................................................................................... 88 4.5.2 Screening Unrelated Families and Sporadic Cases ................................................... 89 4.5.3 Treatment .................................................................................................................. 89 Bibliography .................................................................................................................................91 Appendices ..................................................................................................................................117 Appendix A Phenotype Collection Form ................................................................................ 117 Appendix B Primer sequences used in qPCR validation of the CNV disrupting DMBT1. .... 120 Appendix C Primer sequences used in PCR validation of candidate variants in Family 1. ... 121 Appendix D Primer sequences used in PCR validation of candidate variants in Family 2. ... 122 Appendix E Primer sequences used in PCR validation of candidate THSD1 variant ............ 123 Appendix F Primer sequences used in PCR validation of candidate PKD1 variant ............... 124 Appendix G Sanger sequencing traces of THSD1 variant in Family 5................................... 125 Appendix H Sanger sequencing traces of PKD1 variant in Family 5..................................... 127    ix List of Tables Table 1.1 Loci associated with familial intracranial aneurysms by linkage analysis. .................. 11 Table 1.2 Loci associated with intracranial berry aneurysms through genome-wide association studies. .......................................................................................................................................... 12 Table 1.3 Prevalence of intracranial aneurysms in selected syndromes ....................................... 21 Table 2.1 Literature search terms.................................................................................................. 32 Table 3.1 Demographics of Cohort ............................................................................................... 39 Table 3.2 Demographics of Affecteds .......................................................................................... 39 Table 3.3 Phenotypes of the third generation in Family 1 ............................................................ 42 Table 3.4 Top candidate variants from Family 1 .......................................................................... 52 Table 3.5 Phenotype of Family 2 .................................................................................................. 55 Table 3.6 Candidate variant in CCM2 in Family 2 ....................................................................... 57 Table 3.7 Phenotype of Family 3 .................................................................................................. 60 Table 3.8 De novo variants in II-2 in Family 3 ............................................................................. 62 Table 3.9 Compound heterozygous variants in II-2 in Family 3 .................................................. 62 Table 3.10 Phenotype of Family 4 ................................................................................................ 65 Table 3.11 Phenotype of Family 5 ................................................................................................ 68 Table 3.12 Candidate variants in Family 5 ................................................................................... 71 Table 3.13 Phenotype of affected individuals sequenced from Families 1 - 5 ............................. 73 Table 3.14 Variants in DST ........................................................................................................... 75 Table 3.15 Variants in TTN ........................................................................................................... 75 Table 3.16 Variants in DNAH1 ..................................................................................................... 75 Table 3.17 Variants in CRIPAK .................................................................................................... 76  x Table 3.18 Variants in ASTN2 ...................................................................................................... 80 Table 3.19 Variants in ITGB4 ....................................................................................................... 80 Table 3.20 Variants in HSPG2 ...................................................................................................... 80 Table 4.1 Summary of Candidate Genes in Families 1 - 5 ........................................................... 82   xi List of Figures Figure 1.1 Intracranial berry aneurysm ........................................................................................... 2 Figure 1.2 Cross section of middle cerebral artery ......................................................................... 4 Figure 2.1 Outline of analysis of FIA families ............................................................................. 35 Figure 2.2 Disease penetrance versus allele frequency ................................................................ 36 Figure 3.1 Pedigree of Family 1  .................................................................................................. 41 Figure 3.2 Candidate microdeletion in DMBT1 in Family 1 ........................................................ 45 Figure 3.3 Candidate microdeletion in DMBT1 in affected siblings of Family 1 ........................ 46 Figure 3.4 Region of DMBT1 microdeletion common between affected siblings ....................... 47 Figure 3.5 Relative gDNA in region 5' of DMBT1 between unaffected and affected family members ........................................................................................................................................ 48 Figure 3.6 Relative gDNA in region of microdeletion between unaffected and affected family members ........................................................................................................................................ 48 Figure 3.7 Pedigree of Family 2  .................................................................................................. 54 Figure 3.8 Pedigree of Family 3  .................................................................................................. 59 Figure 3.9 Pedigree of Family 4 ................................................................................................... 64 Figure 3.10 Pedigree of Family 5 ................................................................................................. 67   xii List of Abbreviations AAA Abdominal aortic aneurysms Acom Anterior communicating artery ADPKD Autosomal dominant polycystic kidney disease AVM Arteriovenous malformation BBB Blood brain barrier CADD Combined annotation dependent depletion CCM Cerebral cavernous malformation ChAS Chromosome Analysis Suite CNP C-type natriuretic peptide CNV Copy number variant CTA Computerized tomographic angiography Cx Connexin DGV Database of Genomic Variants DLL4 Delta-like-4 ligand DNA deoxyribonucleic acid ECM Extracellular matrix EDS Ehlers-Danlos syndrome EPC Endothelial precursor cells ExAC Exome Aggregation Consortium FATHMM Functional Analysis Through Hidden Markov Models FIA Familial intracranial aneurysms FMD Fibromuscular dysplasia  xiii FORGE Finding of Rare Disease Genes in Canada FTAAD Familial thoracic aortic aneurysms and dissections  GSC Genome Sciences Centre GTEx Genotype-Tissue Expression GWAS Genome wide association study HHT Hereditary hemorrhagic telangiectasia HUVEC Human umbilical vein endothelial cells IBA Intracranial berry aneurysm(s) ICA internal carotid artery JAM junctional adhesion molecule Indel Insertion/deletion LDS Loeys-Dietz syndrome MAF Minor allele frequency MCA Middle cerebral artery MMP Matrix metalloproteinases MRA Magnetic resonance angiography MRI Magnetic resonance imaging mRNA Messenger RNA NF1 Neurofibromatosis type I NHLBI National Heart, Lung, and Blood Institute NO Nitric oxide OMIM Online Mendelian Inheritance in Man Pcom Posterior communicating artery  xiv PCR Polymerase chain reaction PDGF Platelet-derived growth factor PET Paired-end tag PGI2 Prostaglandin I2 Polyphen Polymorphism phenotyping qPCR Quantitative PCR RNA Ribonucleic acid ROH Regions of homozygosity SAH Subarachnoid hemorrhage  SIFT Sorting Intolerant From Tolerant siRNA Small interfering RNA SNP Single nucleotide polymorphism SNV Single nucleotide variant TGF-β Transforming growth factor beta TJ Tight junction UBC University of British Columbia USCS University of California, Santa Cruz VEGF Vascular endothelial growth factor VSMC Vascular smooth muscle cell WES Whole exome sequencing WGS Whole genome sequencing   xv Acknowledgements  I would like to thank my supervisor, Dr. William Gibson, for his continuing support and encouragement throughout my graduate studies, as well as for his mentorship and investment in me as a geneticist. I would also like to acknowledge my committee members, Drs. Steven Jones and Jan Friedman, for their practical and extremely helpful advice on my research.  Thank you to my lab, Ana Cohen, Katey Townsend, and CK Wong, for their patience and kindness, and constant willingness to teach, discuss, and laugh that made it easy to come to lab each day.  I cannot express how grateful I am to my family for their unwavering love and support. Thank you Mom, Dad, Will, Sue and Ian. I would like to say a special thank you to Grams for listening to me talk about my research over many cups of tea and cookies.  Finally, thank you to the Brain Aneurysm Foundation (www.bafound.org), not only for granting my research the Cynthia Lynn Sherwin Chair of Research, but also for being willing collaborators who are truly invested in seeing this project succeed.   1 Chapter 1: Introduction A 1.1 Overview Intracranial berry aneurysms (IBA) develop in the walls of cerebral arteries, where the endothelial layer has weakened and formed a sac-like abnormality. IBA are also referred to as saccular aneurysms and differ from other intracranial aneurysms in shape, forming an out-pocketing off of a cerebral artery, reminiscent of a berry on a vine (Figure 1.1). Fusiform aneurysms involve dilatation of the entire vessel wall for some component of its length, and in the cerebral circulation they are much rarer than berry aneurysms.1 IBA can vary in size, location, and shape, with some aneurysms being multi-lobed. IBA greater than 2.5 cm in diameter are considered “giant aneurysms.” IBA predominantly form along the internal carotid artery or the other major arteries of the circle of Willis in the anterior circulation, often at branching points or other areas under high hemodynamic stress.2,3 It is estimated that 3% of the general population have at least one IBA,4,5 a prevalence that increases to 3.6-6.5% in people over 30 years of age.6 Aneurysmal rupture accounts for a significant proportion (80-85%) of subarachnoid hemorrhage (SAH), a type of hemorrhagic stroke.7 SAH is fatal in 35-50% of patients with IBA, and leads to permanent brain damage in 25-50% of survivors.8-11 From a genetic epidemiology perspective, IBA are considered to be a common, complex condition with multiple risk factors including advanced age, ancestry, sex (women affected more often than men), smoking, longstanding hypertension, and family history.12-15 A meta-analysis examining 33 studies on aneurysmal SAH found that the mean age of hemorrhage was 62 years, and that                                                  A A version of this chapter has been published as: Hitchcock, E., and Gibson WT. A Review of the Genetics of Intracranial Berry Aneurysms and Implications for Genetic Counseling. Journal of Genetic Counseling 2017, Volume 26, Issue 1, pp 21–31, First Online: 14 October 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium.   2 63% of patients who experience rupture were women.16 However, population-wide screening is not currently recommended, as most cerebral aneurysms are asymptomatic and will never rupture.11  The introduction of this thesis will discuss the structure of cerebral vasculature, familial intracranial aneurysms (FIA), as well as the genetics of both IBA and FIA, including associated syndromes.  Figure 1.1 Intracranial berry aneurysm  Figure of an intracranial berry aneurysm, also called a cerebral aneurysm, on cerebral arterial tissue. (Adapted from Columbia University Medical Centre accessed at: http://www.columbianeurosurgery.org/conditions/cerebral-aneurysm/)17  1.2 Vascular Structure, Function, and Development Arteries are comprised of three layers of tissue: closest to circulating blood is a layer of squamous endothelial cells with a basal membrane and the elastic lamina called the intima;  3 second is media, which consists of vascular smooth muscle cells (VSMC) as well as some collagen and elastin fibrils; this is covered by the adventitia, consisting of diffuse connective tissues (Figure 1.2).18,19 Case reports and reviews have documented aneurysms at most major arteries throughout the body.20,21 Defects in a variety of connective tissue genes lead to vascular fragility and aneurysm formation in the aorta (see Section 1.3.1.2), but the pathogenesis of aneurysms in the brain has not been solved at the molecular level. Nevertheless, defects in the endothelial and smooth muscle linings of arterial walls are a known cause of IBA at the cellular level. Several molecular mechanisms have been proposed, including loss of tight junction proteins, infiltration of macrophages leading to loss of vascular smooth muscle tissue, and remodeling due to hemodynamic stress.22-24 Since 1980, when Furchgott and Zawadzki demonstrated that arterial smooth muscle requires the presence of endothelial cells to relax when stimulated by acetylcholine,25 multiple papers have shown signaling occurs between endothelium and VSMC to control functions of the vasculature. Endothelial cells have the ability to regulate vasodilation and vasoconstriction, VSMC growth, angiogenesis, and inflammation,26 such that numerous types of dysfunction within these cells could lead to aneurysm formation.    4  Extracellular Matrix     Adventitia  Media      Intima Figure 1.2 Cross section of middle cerebral artery  Cross-section of the middle cerebral artery showing the intima, media, adventitia, and extracellular matrix. The bar represents 50 um. Adapted from Walmsley et al. (1983). Stroke 14;5 781-790  1.2.1 Vasculogenesis and Angiogenesis Vasculogenesis describes the process of forming rudimentary blood vessels during embryogenesis, whereas angiogenesis describes the expansion and repair of vasculature both pre- and postnatally. Endothelial precursor cells (EPC) are critical for both vasculogenesis and angiogenesis. Embryonic EPCs stem from the periphery of blood islands, and respond to vascular endothelial growth factor (VEGF) by migration, proliferation, and differentiation into endothelial cells. Exposure to platelet-derived growth factor (PDGF) also induces their  5 development into VSMC.27 Angiogenic sprouting of vascular endothelial cells is regulated by Notch receptors and their Delta-like-4 ligand (DLL4) though lateral inhibition by neighbouring endothelial cells.28-30 The growth of the sprouting vasculature is guided by a gradient of VEGFA.31,32 Endothelial cells can promote VSMC growth through growth factors and signaling molecules, such as nitric oxide (NO) and Prostaglandin I2 (PGI2),33-35 and can also suppresses VSMC growth through signaling of C-type natriuretic peptide (CNP), 36 which is initiated by sheer stress. Matrix metalloproteinases (MMP) can contribute positively to angiogenesis by degrading collagen and other structural proteins between endothelial cells, thereby facilitating sprouting and release of pro-ECM factors.37-39 This process enables organization of endothelial cells on the scaffold of the extracellular matrix (ECM), which provide the necessary support for the sprouting blood vessels. Jagged-1 signaling from endothelial cells received by Notch receptors on VSMC promotes adhesion between the endothelium and VSMC and leads to maturation of vasculature.40   1.2.2 Blood-Brain Barrier Cerebral vasculature differs from other blood vessels by the presence of the blood-brain barrier (BBB), which restricts the transport of certain molecules from circulation into the cerebral tissue. Junctional complexes, including tight junctions (TJ), adherens junctions, and gap junctions, form an interdependent network of proteins that restrict the permeability around the cells that comprise the BBB. Reese and Karnovsky first documented the BBB in 1967 when they identified rows of “belt-like” TJ between endothelial cells that blocked the transport of peroxidase, and a scarcity of transport vesicles within the endothelial cells.41 While the BBB has most frequently been studied at the level of capillaries, a recent paper by Hanske and colleges  6 (2015) used electron microscopy and fluorescent staining to determine that the most common TJ proteins associated with the BBB are distributed evenly along all types of cerebral blood vessels, including along arteries.42 Claudin-5, claudin-3, zonula occludens-1 (ZO-1), occludin, and junctional adhesion molecules (JAM) are critical to the integrity of tight junctions.43-47 Similarly, the cadherin family of proteins make up an important part of the adherens junctions. These transmembrane proteins primarily form adhesions between cells, and between cells and scaffolding proteins. The most commonly expressed cadherin in vascular endothelial cells is VE-cadherin, with N- and E-cadherins found in much lower abundance.48,49 On cerebral endothelial cells, gap junctions are composed of the connexin (Cx) family of proteins, specifically Cx37, Cx40, and Cx43.50-52 Notch signaling is also important in BBB function; Notch3-/- mice show a disruption of the BBB that is characterized by “patchy” VSMC on blood vessels in the central nervous system and blood vessel leakage.53  1.3 Familial Intracranial Aneurysms Familial intracranial aneurysms (FIA), a hereditary subtype of IBA, is suspected when two or more affected first- to third- degree relatives are present in a family.54 Differences in study populations and methodology have contributed to variability in the reported prevalence of FIA. For example, the rate of detection of intracranial aneurysms when screening first-degree relatives with at least two affected family members has been reported to be 9.2-9.8% in patients older than 30 years, which is approximately 2-3 times higher than the risk within the general population.11,55 A more recent study screened for aneurysms among asymptomatic first-degree relatives of families with two affected first-degree relatives or three affected second- to third- degree relatives, and found detection rates as high as 20.6% among patients older than 30  7 years.56 Individuals with FIA seem to have a more severe phenotype: they are more likely to develop more than one brain aneurysm,4,7 and have 17 times greater risk of rupture compared to those with sporadic IBA.56 Furthermore, aneurysms that do rupture tend to rupture at a younger age and at a smaller aneurysmal diameter among patients with FIA.56-60 Along with the increased risk for aneurysm formation and rupture, patients with FIA appear to have a poorer outcome after rupture.61,62  Families with FIA do not seem to experience anticipation in subsequent generations, so the underlying genetic cause (if present) is more likely attributable to single nucleotide variants (SNVs) or copy number variants (CNVs) than expansion of a trinucleotide repeat. Anticipation might also appear to be present in FIA families because of ascertainment bias; as the family history grows, each subsequent affected generation is more likely to be brought to the attention of a health care provider and diagnosed via imaging at an earlier age.63 Generally, screening with magnetic resonance angiography (MRA) or computerized tomographic angiography (CTA) is recommended for individuals with two or more first-degree relatives diagnosed with intracranial aneurysms.11,14,64-66 In the absence of prospective longitudinal studies, expert consensus appears to be that relatives at sufficient risk to merit screening should begin such screening 10 years prior to the earliest age-at-diagnosis in their pedigree.  After diagnosis of IBA or FIA, patients either remain under observation, receiving periodic brain imaging to assess the size of their intracranial aneurysm(s), or receive invasive treatment. The two primary means of treating IBA are surgical clipping, which requires a craniotomy, or endovascular coiling, which requires the insertion of a microcatheter in the femoral artery.67 Surgical clipping removes circulation to the aneurysms, whereas endovascular coiling within the aneurysm helps to stabilize the vascular tissue. Endovascular coiling has lower  8 risk of mortality and long-term morbidity when treating ruptured or unruptured IBA, but a slightly higher risk of aneurysm recurrence or re-bleeding compared to surgical clipping.66-71  1.3.1 Genetics of IBA and FIA 1.3.1.1 Previous Research Previous genetic research on IBA and FIA has consisted of familial mapping studies, genome-wide association studies (GWAS), and whole-exome sequencing (WES) studies. The first gene-disease association for FIA was made by Santiago-Sim et al. in 2016.72 From a cohort of over 100 families with intracranial aneurysms (saccular, fusiform, or both), a causative gene was found in a single extended pedigree. WES of two affected first-cousins from this pedigree produced 53 variants that were shared between the cousins. A truncating variant (p.R450X) in THSD1 was found to segregate with disease in their five-generation family, being present in all affected members, obligate carriers, and also in three members whose disease status is unknown. The variant was not found in the 11 clinically unaffected family members. The researchers also validated their findings in a cohort of 507 cases of sporadic intracranial aneurysms against a control cohort consisting of individuals on the ExAC database and 305 locally-collected individuals. Rare THSD1 variants were found in 8 of the 507 sporadic cases, which are enriched compared to controls.  A knock-in fluorescence reporter of the mouse orthologue Thsd1 in mouse brain co-localized with endothelial cell markers. Knock-out mouse models and knock-down morpholino zebrafish models of THSD1 led to intracranial hemorrhage in the animals. In vitro knock-down of THSD1 in human umbilical venous endothelial cell (HUVEC) lines with small interfering RNA (siRNA) showed that THSD1 interacts with a key member of focal adhesion complexes,  9 talin, and that HUVEC adhesion to collegen I in the basement membrane was reduced significantly. Co-transcription of siRNA-resistant wildtype THSD1 mRNA rescued the impaired adhesion phenotype in HUVECs. However co-transcription of siRNA resistant THSD1 mRNA containing patient-derived THSD1 mutations did not rescue the cellular phenotype.72   1.3.1.1.1 Familial Mapping Studies Familial mapping studies have been done in large pedigrees that appear to have a single causal mutation transmitted as a Mendelian trait for intracranial aneurysm development. Mapping follows the hypothesis that such a variant will be found in a chromosomal region that has been inherited by all affected family members. Markers of known genomic location, such as single nucleotide polymorphisms (SNPs), are used to derive haplotypes that can in turn be used to identify loci that co-segregate with FIA. Investigations of families and affected sibling-pairs have suggested numerous loci associated with FIA (Table 1.1). From these studies the loci with the strongest association are 7q11, 19q13, and Xp22.73-87 A recent meta-analysis of five familial mapping studies revealed an additional two loci in linkage disequilibrium with FIA, 3q27.3-3qter and 17p12-q21.33.88 A SNP association study aimed at replicating loci previously flagged by linkage analysis confirmed the association at 14q23 (found by Ozturk et al., 2006) in a cohort of 266 affected and 288 unaffected Japanese individuals.89 The number of loci identified though linkage analysis indicates there is genetic heterogeneity in FIA.  1.3.1.1.2 Genome-Wide Association Studies  Genome-Wide Association Studies (GWAS) interrogate the genome for statistically significant associations between SNPs and disease at a population level. Several loci have been  10 associated with sporadic IBA by GWAS, primarily using large discovery and replication cohorts from the Dutch, Finnish, and Japanese populations (Table 1.2).90-98 The most frequently replicated locus is 9p21.3, which contains the long non-coding RNA, CDKN2B-AS1, and is adjacent to the cyclin-dependent kinase inhibitor genes, CDKN2A and CDKN2B. The same linkage block in 9p21.3 associated with IBA has also been associated with other vascular diseases, including coronary artery disease, myocardial infarction, and abdominal aortic aneurysms: this suggests that there may be a single locus that predisposes to all of these conditions via a common pathology.99,100 Alg et al. (2013) conducted a meta-analysis of 61 GWAS studies that replicated the association between three loci (9p21.3, 8q11, and 4q31.23) and IBA.101 In contrast to the postulated high-penetrance Mendelian loci in FIA, loci discerned through GWAS each have a relatively small effect size on the risk of developing IBA. For example, SNPs at the most strongly associated locus, 9p21.3, have reported odds ratios between 1.29-1.34 in the major GWAS studies.91,93,97  11 Table 1.1 Loci associated with familial intracranial aneurysms by linkage analysis. Associated Loci LOD Score Study Population(s) OMIM Locus Name OMIM Number Studied in >1 Population Study Cohort                  [affected (unaffected)]  References 1p36.13-p34.3 4.2 - North American, Dutch ANIB3 609122 Yes 12(8) from 1 family               7(10) from 1 family Nahed et al. (2005)      Ruigrok et al. (2008) 2p13 3.55 Dutch - - No 7(9) from 1 familya Roos et al. (2004) 4q32.2 2.5 2.6 FIA Study - - Yes 192 familiesb,c                               333 familiesb,c Foroud et al (2008)       Foroud et al (2009) 5p15.2-p14.3 3.57 French-Canadian ANIB4 610213 No 9(3) from 1 family Verlaan et al. (2006) 5q22-31 2.24 Japanese - - No 104 ASP from 85 families Onda et al. (2001) 7q11.2 3.22 3.22 Japanese, North American ANIB1 105800 Yes 104 ASP from 85 families  39(0) from 13 families Onda et al. (2001)      Farnham et al. (2004) 8p22 3.61 South Korean ANIB11 614252 No 9(22) from 5 families Kim et al. (2011) 11q24-q25 4.3 Colombian, North American ANIB7 612161 Yes 2 familiesb Ozturk et al. (2006) 12p12.3 3.1 FIA Study - - Yes 333 families Foroud et al. (2009) 13q14.12-q21.1 4.56 French-Canadian - - No 10(25) from 1 family Santiago-Sim et al. (2009) 14q22 2.31 Japanese - - No 104 ASP from 85 families Onda et al. (2001) 14q23 3.0 Colombian, North American ANIB8 612162 Yes 2 familiesb Ozturk et al. (2006) 17cen 3.0 Japanese - - No 93(27) from 29 families Yamada et al. (2004) 19q13 2.58 2.58 2.6 2.15 Finnish, Japanese ANIB2 608542 Yes 48 ASP from 22 families         222 ARP from 121 families   93(27) from 29 families       41(0) from 9 families Olson et al. (2002)                van der Voet et al. (2004)   Yamada et al. (2004)   Mineharu et al. (2007) Xp22 2.16 2.08 4.54 North American, Japanese, Dutch ANIB5 330870 Yes 48 ASP from 22 families   93(27) from 29 families       7(10) from 1 family Olson et al. (2002)       Yamada et al. (2004)    Ruigrok et al. (2008) Study cohort data corresponds with the reference in each horizontal row. ASP: affected sib-pair; ARP: affected relative pair                                                                                                                                                    a. Family is consanguineous. b. The number of affected and unaffected individuals included in the linkage analysis was not available. c. A total of 1155 affected and 1895 unaffected family members were genotyped in Foroud et al. (2008) and Foroud et al. (2009). Families were enrolled at recruitment sites located in North America, New Zealand, and Australia  12 Table 1.2 Loci associated with intracranial berry aneurysms through genome-wide association studies. Associated Loci O.R. (95% C.I) p-value Study Population(s) OMIM Locus Name OMIM Number Replicated in >1 Population Size(s) of Study Cohort References 2q33.1 1.22 (1.13-1.32) 5.8 x 10-7 Dutch, Finnish, Japanese ANIB9 612586 Yes 2,196 cases; 8,085 controls Bilguvar et al. (2008) 4q31.22 1.25 (1.16-1.34) 9.58 x 10-9 Japanese - - No 2,431 cases; 12,696 controls Low et al. (2012) 4q31.23 1.22 (1.14-1.31) 1.1 x 10-5 Dutch, Finnish, Japanese - - Yes 5,891 cases; 14,181 controls Yasuno et al (2011) 5q31.3 1.92 (1.53-2.40) 3.17 x 10-8 Finnish, Dutch - - Yes 2,335 cases; 9,565 controls Kurki et al. (2014) 8q11.12 –12.1  1.36 (1.24-1.49) 1.17 (1.10-1.25) 1.86 (1.40-2.47) 1.25 (1.11-1.40) 1.4 x 10-10 9.0 x 10-7 9.2 x 10-5 < 0.001 Dutch, Finnish Japanese ANIB10 612587 Yes 2,196 cases; 8,085 controls 5,891 cases; 14,181 controls 406 cases; 392 controls      1,483 cases; 1,683 controls  Bilguvar et al. (2008) Yasuno et al. (2010)     Deka et al. (2010)       Foroud et al. (2012) 9p21.3 1.29 (1.19-1.40) 1.32 (1.19-1.45) 1.24 (1.01-1.52) 1.36 (1.22-1.52) 1.34 (1.23-1.45) 1.21 (1.13-1.30) 1.41 (1.05-1.89) 1.4 x 10-10 1.5 x 10-22 0.017 < 0.001 4.07 x 10-12 1.55 x 10-7 Dutch, Finnish, Japanese, Portuguese ANIB6 611892 Yes 2,196 cases; 8,085 controls 5,891 cases; 14,181 controls           406 cases; 392 controls       1,483 cases; 1,683 controls 4,133 cases; 7,869 controls 2,431 cases; 12,696 controls 200 cases; 499 controls Bilguvar et al. (2008)    Yasuno et al. (2010)          Deka et al. (2010)          Foroud et al. (2012)      Foroud et al. (2014)            Low et al. (2012)        Abrantes et al. (2015) 10q24.32 1.29 (1.19-1.40) 1.2 x10-9 Dutch, Finnish, Japanese - - Yes 5,891 cases; 14,181 controls Yasuno et al. (2010) 12q22 1.16 (1.10-1.23) 1.2 x 10-5 Dutch, Finnish Japanese - - Yes 5,891 cases; 14,181 controls Yasuno et al. (2011) 13q13.1 1.20 (1.13-1.28) 2.5 x 10-9 Dutch, Finnish Japanese - - Yes 5,891 cases; 14,181 controls Yasuno et al. (2010) 18q11.2 1.22 (1.15-1.28) 1.1 x 10-12 Dutch, Finnish, Japanese - - Yes 5,891 cases; 14,181 controls Yasuno et al. (2010) 20p12.1  1.20 (1.11-1.28) 1.5 x 10-5 Dutch, Finnish, Japanese - - Yes 5,891 cases; 14,181 controls Yasuno et al. (2011)  The size of each study cohort corresponds with the reference in the same horizontal row. Yasuno et al. (2010) and Yasuno et al. (2011) analyzed the same discovery and replication cohorts, which were expanded on from the cohort studied in Bilguvar et al. (2008). 13 1.3.1.1.3 Whole-Exome Sequencing Studies Unlike GWAS, but similar to linkage analysis, whole-exome sequencing (WES) aims to identify rare variants that have a large effect size and impart a high risk of developing intracranial aneurysms. Recently, three WES studies of multiplex families diagnosed with FIA have revealed new candidate genes in the development of intracranial aneurysms. All three studies excluded individuals who were diagnosed with a syndromic form of IBA.  The Familial Intracranial Aneurysm (FIA) Study, a separate initiative from those who discovered THSD1-related FIA, published two exome sequencing studies on seven multiplex families of European-American ancestry. These families were selected for having high numbers of affected individuals, and for having pedigrees consistent with either autosomal dominant or autosomal recessive inheritance. Initially, WES was carried out on 50 affected and unaffected individuals from these families, and analysis identified 96 candidate genes (Foroud for the FIA Study Investigators, 2013).  In their second publication the FIA Study researchers analyzed WES data from 36 affected and 9 unaffected family members.102 Unaffected family members were only included if they were above 45 years of age and had received a negative screen by MRA – it is of course possible that some of the family members who were scored as unaffected may yet develop an IBA in their lifetime. For this analysis, Farlow et al. (2015) employed six biological filters on their WES data to generate a list of 68 candidate variants in 68 genes. These filters examined the variant type (non-synonymous SNVs or exonic and splice site indels), variants with a minor allele frequency (MAF) of <0.01, the segregation within families, and the predicted effect on protein (via combined annotation dependent depletion (CADD) score ≥10, and predicted damaging by Polyphen2 or SIFT). Five variants, found in GSTCD, DUSP16, LMBR1L, HAL and  14 TSC2, segregated fully with disease in one family and were present in the affected individuals of a second FIA family. None of the variants found in this study overlapped with any GWAS flagged loci (Farlow et al., 2015). This is presumably because rare, highly-penetrant pathogenic variants that result in a Mendelian inheritance pattern in a multiplex family tend not to spread through to the general population (unless some sort of balancing selection occurs).    Yan et al. (2013) had broader inclusion criteria and sequenced families with three or more affected first- to third- degree relatives.103 They sequenced 42 affected people from 12 families of Japanese ancestry. After filtering for their presence in all affected family members, minor allele frequency (MAF) <0.05, and a predicted damaging effect to the protein (Polyphen2 and SIFT), WES analysis resulted in 78 candidate variants. Two variants, p.Y193F in GPR63 and p.R142H in C10orf122 (TEX36), segregated with affected individuals in more than one family. While both of these protein changes are predicted to be deleterious, relatively little is known about the gene function, and there was not sufficient evidence to classify either mutation as pathogenic. Yan et al. (2015) then selected ten variants from nine genes, based on functions that were plausibly associated to the pathogenesis of intracranial aneurysms, for Sanger sequencing and replication in two additional Japanese cohorts. The first replication cohort consisted of probands from 24 independent FIA families, and the second replication cohort included 426 individuals diagnosed with sporadic IBA. A variant in ADAMTS15 was significantly associated with the familial cases in the first replication cohort, while variants in THBD, IL11RA, PAFAH2, and ZNF222 had a slightly increased MAF among the sporadic IBA cases in the second replication cohort compared to the Japanese population. None of these variants had sufficient evidence for the authors to determine them as causative for FIA.   15 For rare diseases with characteristic phenotypes, a gene-disease association is established when rare variants are present in the same gene in three independent families. For more common diseases such as IBA, issues such as non-penetrance and phenocopies make additional evidence (such as functional studies) highly desirable, in order to lower the false discovery rate. Whereas none of the candidate genes yet flagged through the three WES studies mentioned above have sufficient genetic evidence to prove a causal association, the recent publication of THSD1 is an important milestone in the field, as it included multiple lines of functional inquiry and effectively “sets the bar” for acceptance this type of gene-disease association when a potentially causal variant is segregating in a single extended pedigree (at least until other pedigrees are identified with different functional variants in the same gene).  1.3.1.2 Associated Syndromes There are several Mendelian syndromes that confer susceptibility to IBA. These syndromes are predominately connective tissue disorders that lead to decreased integrity of the extracellular matrix of vascular tissue, but also include conditions such as autosomal dominant polycystic kidney disease (ADPKD) and Neurofibromatosis Type I (NF1).   1.3.1.2.1 Autosomal Dominant Polycystic Kidney Disease Apart from family history, diagnosis of autosomal dominant polycystic kidney disease (ADPKD) imparts the highest risk for developing IBA (Table 1.3). Between 4% and 17% of patients with ADPKD will develop IBA, with an equal risk distribution between sexes.104-108As seen with non-syndromic IBA, the prevalence of IBA increases with age in these syndromes.106,108 The combined risk for aneurysmal formation in patients diagnosed with  16 ADPKD and a family history of IBA or SAH increases to approximately 22-25%.105,107 Screening for IBA in ADPKD is recommended in patients above 30 years of age or in patients with a family history of IBA.108 Hypertension, found commonly in ADPKD patients, is not considered to be an obligatory risk factor for aneurysm formation in this context. Individuals with ADPKD who have well-controlled hypertension, or blood pressure within the normal range, have still been seen to develop intracranial aneurysms.106,108-110  Pathogenic variants in the PKD1 and PKD2 genes are causative for ADPKD and account for 85% and 15% of diagnoses, respectively.111 Patients with pathogenic variants in PKD1 or PKD2 appear to have an equivalent risk of IBA.112 PKD1 and PKD2 mutations cause defects in the mechanosensory cilia found on renal and vascular endothelium, which leads to cyst and aneurysm formation, respectively.113-116 Patients with tuberous sclerosis complex can also have a concurrent diagnosis of ADPKD when their disease is caused by a contiguous gene deletion affecting TSC2 and PKD1 at chromosome 16p13.3. These patients not only have more severe kidney disease, but are also at risk for intracranial aneurysms.117-119  1.3.1.2.2 Ehlers-Danlos Syndrome Ehlers-Danlos syndrome (EDS) is an autosomal dominant connective tissue disorder. In classical EDS, the majority of patients have pathogenic variants in COL5A1 or COL5A2, while in vascular EDS, previously referred to as EDS Type IV, variants in COL3A1 are responsible for disease.120 Vascular EDS patients have a high risk of mortality, due to vascular fragility that often leads to hemorrhage.120 Intracranial aneurysms have been reported in both classical and non-classical forms of EDS, but relatively speaking it is patients with the vascular subtype of EDS who are at the highest risk for IBA formation.121-128 Kim et al. (2016) found intracranial  17 aneurysms in 12 individuals, seven of whom had vascular EDS, three of whom had classical EDS, and one who had the hypermobility form, from a chart review of 99 EDS patients (mean age 41.7 years) who underwent brain imaging.128 There is currently no consensus on the clinical utility of screening for intracranial aneurysms among otherwise asymptomatic vascular EDS patients. Results of a positive test on such screening may not be easily actionable, because of the high risks associated with surgical intervention. If screening is desired, a non-invasive approach (such as MRA) should be strongly considered in these patients, in order to avoid further weakening of the vasculature.125,129 Certain tertiary care centers with specialized expertise have reported low rates of complications from endovascular procedures in EDS,130,131 such that treatment may be safe for EDS patients receiving care at experienced centers.    1.3.1.2.3 Loeys-Dietz Syndrome Loeys-Dietz syndrome (LDS) is a connective tissue disorder characterized by severe vascular defects, primarily arterial aneurysms, that can hemorrhage or dissect very early in life.132,133 Autosomal dominant mutations in TGF-β pathway genes, most frequently TGFBR1 and TGFBR2, cause LDS. Although LDS is not commonly listed as having an association with IBA, a number of patient cases have reported IBA as a feature.132-137 Cerebrovascular bleeding is the third leading cause of death in LDS patients, and intracranial aneurysms have been seen at a frequency ranging between 10-28%.128,134,137 Although further studies are needed to assess the clinical utility of screening LDS patients specifically for intracranial aneurysms, surveillance of each part of the vascular tree is currently recommended every two years.138      18 1.3.1.2.4 Marfan Syndrome Marfan syndrome is an autosomal dominant connective tissue disorder caused by pathogenic variants in FBN1. It is characterized by skeletal, ocular, and cardiovascular anomalies with wide phenotypic variability. Aortic aneurysm, dissection, and root enlargement are the most commonly reported vascular defects.139,140 IBA have been associated with Marfan syndrome through multiple case reports.141-147 Conway et al. (1999) did not find evidence for an association between intracranial aneurysms and Marfan syndrome upon autopsy of 25 patients.148 Only one patient autopsied was found to have an intracranial aneurysm, a number that would agree with the general population frequency. However, a recent retrospective chart review of 59 Marfan syndrome patients estimated that 14% have one or more intracranial aneurysms.128 Specific screening for intracranial aneurysms is not routinely recommended in Marfan syndrome patients, although it could be considered in family members of affected individuals who have had a diagnosed IBA.  1.3.1.2.5 Neurofibromatosis Type I Neurofibromatosis Type I (NF1) is an autosomal dominant condition caused by pathogenic variants in NF1. The primary characteristics of NF1 are café-au-lait spots, iris Lisch nodules, and benign neurofibromas.149 Vascular abnormalities are also a recognized characteristic of NF1, and patients under 29 years of age have an increased prevalence of intracranial aneurysms relative to the general population risk.150 Though Conway and coauthors (2001) did not detect any intracranial aneurysms in their autopsy study of 25 NF1 patients between 3 and 69 years of age,149 intracranial aneurysms have been documented as a cerebrovascular feature of NF1 by other investigators.151,152 Retrospective reviews of NF1 patient  19 data have reported the prevalence of intracranial aneurysms to be between 9-11%, and the youngest NF1 patient reported to have an intracranial aneurysm was 1 year of age. However, routine screening for intracranial aneurysms is not currently recommended for NF1 patients.153-159 Moyamoya angiopathy, which is also associated with NF1,160 appears to have a pathogenesis that is distinct from that of intracranial berry aneurysms; it is not clear whether the occasional association of intracranial aneurysms with moyamoya161,162 reflects a common pathophysiology at the molecular level, or whether it reflects pathology at one vascular site that perturbs downstream hemodynamics.  1.3.1.2.6 Other Syndromes Multiple Endocrine Neoplasia Type I,163 Pseudoxanthoma Elasticum,164-166 and Hereditary Hemorrhagic Telangiectasia (HHT)167 are often mentioned as being associated with IBA. While all have had individual patient case reports which document the presence of intracranial aneurysms, these data are not as robust as are the data for the syndromes listed above and in Table 1.3. Specific recommendations for IBA screening in these disorders must await larger cohort studies, although in the case of HHT, the currently recommended screening protocols to detect cerebral arteriovenous malformations (AVM) would be expected to detect IBA as well.168 Most frequently in HHT patients intracranial aneurysms form along arteries leading into AVM.167  Patients with fibromuscular dysplasia (FMD) are also believed to be at risk for aneurysms in the brain and elsewhere, so current recommendations are that all FMD patients have cross-sectional imaging from head to pelvis with a sensitive method like CTA or MRA.169 Though  20 autosomal dominant inheritance has been suggested for fibromuscular dysplasia, definitive genetic candidates have yet to emerge.170   1.3.1.2.7 Concluding Remarks Among the syndromes discussed above that confer increased risk of IBA, ADPKD has the strongest association. Published estimates of IBA prevalence in Marfan syndrome, NF1, EDS, and LDS are likely biased toward reporting a higher percentage of affected patients. In the studies discussed, patients found to be at risk for vascular complications received brain imaging, whereas patients lacking these risk factors were not screened and were not included in the prevalence calculation. Additionally, many of these studies also included fusiform aneurysms when documenting the presence of intracranial aneurysms.    21  Table 1.3 Prevalence of intracranial aneurysms in selected syndromes Relative Prevalence Syndrome OMIM Number(s) Associated Genes Prevalence of patients with IBA Frequent Autosomal Dominant Polycystic Kidney Disease 173900 613095 PKD1, PKD2 4-17% Infrequent Vascular Ehlers-Danlos Syndrome  130050  COL3A1   12%a  Loeys-Dietz Syndrome 609192 610168 TGFBR1, TFGBR2, SMAD3b  11-28%a  Marfan Syndrome 154700 FBN1    14%a  Neurofibromatosis Type I 162200 NF1   9-11%a Rare c  Pseudoxanthoma Elasticum 264800 ABCC6 -  Hereditary Hemorrhagic Telangiectasia  187300 ENG ~10%d  Multiple Endocrine Neoplasia Type I 131100 MEN1 - a. Prevalence estimates may be influenced by selection bias and the inclusion of both fusiform and berry aneurysms.  b. Pathogenic variants in TGFB2 and TGFB3 also account for < 5% of LDS cases. c. Individual case reports only. d. As the prevalence of IBA in HHT patients is unknown, the prevalence of arteriovenous malformations, which can also lead to cerebral hemorrhage, has been given.  These two methodological limitations have prevented an accurate measurement of IBA prevalence in the syndromes listed, which may or may not be significantly higher than the background population risk. LDS prevalence measurements may not be as affected by ascertainment bias, if patients are receiving screening every two years as recommended. As more data are collected on the natural history of LDS, this syndrome may move to a higher risk category for IBA.   1.3.1.3 Genetic Counselling Certified genetic counsellors are familiar with family trees that suggest Mendelian inheritance that follows autosomal dominant, autosomal recessive or X-linked patterns of inheritance. Even if a DNA-level diagnosis is not available in those situations, counsellors will  22 be able to estimate recurrence risks and suggest appropriate follow-up. Where feasible, risk for apparently-unaffected family members may be refined by imaging studies in living parents or grandparents and other relatives (sibs, aunts and uncles, etc.).  Unusual situations may arise that demand consideration of screening protocols that have not been validated by prospective studies. For example, pediatric IBA is extremely rare, with cases often only being described as case reports. A retrospective study found only 2% of patients diagnosed with intracranial aneurysms were children, and many of those aneurysms were either fusiform or associated with an underlying syndromic diagnosis.164 Family 3 in this study has a child under age 15 who suffered a subarachnoid haemorrhage attributed to a berry aneurysm of the cerebral circulation. Although this child is not known to have another affected first-degree relative, when a child develops a disease that is rare in children but common among elderly adults, an underlying high-penetrance risk allele may well be a major contributing risk factor. Challenging situations such as these may demand a multidisciplinary approach that includes engagement of the genetic counsellor with other medical and surgical practitioners involved in the family’s care. Counsellors may also need to provide an opinion to insurance providers as to the utility of screening in one family member for the purposes of estimating risk in other family members. In the examples given above, screening of clinically-unaffected sibs may be worthwhile, but screening of clinically-unaffected parents may also provide useful information. Where one or more aneurysms are detected in a parent, the unaffected sibs would definitely be considered to be at risk and to merit screening under current guidelines. As there is not yet a genetic test, or a conclusive familial recurrence rate, genetic counsellors will need to estimate patient risk for developing non-syndromic IBA on a case-by-case basis, through analyzing inheritance within a pedigree. Counsellors should also investigate  23 the possibility of an associated syndrome by taking a targeted family history; if warranted by specific findings, they could then refer the patient to a medical geneticist or other suitable specialist. The heterogeneity of findings on IBA within Marfan syndrome, NF1, EDS, and LDS does not give clear direction to genetic counsellors. However, genetic counsellors should be aware that patients with these syndromes could be at increased risk for IBA development, and may want to recommend screening for patients who present with additional risk factors such as a specific history of IBA in their family members.  1.4 Objectives and Hypotheses My objective was to identify one or more disease-causing genes for intracranial berry aneurysms. While several loci and candidate genes have been identified, only a single conclusive gene-disease association has been made for non-syndromic families. Further next-generation sequencing studies were needed to identify causative genes in families with intracranial aneurysms as the only clinical finding. Patients with FIA are at increased risk for aneurysm formation and rupture compared to the general population, and screening of all first-degree relatives using MRA or CTA is currently recommended. Definitive identification of a single-gene cause of FIA in a particular family or group of families would allow genetic confirmation of which family members are at risk. Family members who did not inherit the pathogenic variant would not need to undergo regular screening, and could obtain peace of mind regarding aneurysm formation later in life.  I have hypothesized that major Mendelian genes for intracranial aneurysms exist. A recent example of this is the pathogenic mutation in THSD1 was reported to account for a small proportion (~1%) of nonsyndromic brain aneurysm families.   24 My hypotheses are that: 1. In multiplex families with FIA segregating in a Mendelian manner (autosomal dominant, autosome recessive, or X-linked) there will be a single pathogenic variant per family that leads to the formation of intracranial aneurysms. 2. Among multiple independent families diagnosed with FIA, different rare pathogenic variants will be found to affect the same gene in a subset of these families.  25 Chapter 2: Methods and Materials 2.1  Family and Clinical History After informed consent, a detailed family history was taken from each study participant and/or family through an in-person interview, or via an over-the-phone interview for individuals who do not live locally. Additionally, a clinical history was taken from each participant to gather information on the screening and treatment of their intracranial aneurysms. Participants were also offered the option of signing a release of information form permitting access to their medical records regarding the care of their aneurysms. This provided further resolution of the oral clinical history given by the patient and allowed for collection of more granular data such as size and location of IBA.  2.1.1 Data Collection Form A data collection form was created for this study to ensure a standardized set of information was collected from each participant (Appendix A). This form included collection of basic demographic information, such as age and ethnicity, clinical information such as age of diagnosis, number of aneurysms and type of surgical intervention, as well as research information, such as ADPKD status. The data collection form was updated in October 2016 to include questions about smoking, hypertension, and connective tissue disorders.   2.1.2 Family Selection Participants were required to fulfill a minimum of one of the following three criteria in order to be enrolled in this study: 1. Had ≥1 family member also diagnosed with intracranial aneurysms.  26 2. Were diagnosed with ≥2 intracranial aneurysms. 3. Were <40 years of age when diagnosed with intracranial aneurysms. Individuals fulfilling criterion 1 were prioritized for sequencing above those fulfilling criteria 2 or 3, as family history is a stronger predictor of genetic risk factors for disease than are age of onset or disease severity. Individuals with a concurrent diagnosis of a disease or syndrome known to confer a genetic predisposition to IBA/FIA (such as ADPKD) were excluded from this study.   2.2 DNA Collection and Extraction  DNA samples were obtained from study participants using the Oragene DNA OG-500 collection kit by DNA Genotek (Kanata, Ontario) to collect a saliva sample. As the majority of study participants reside outside of Vancouver, British Columbia, collection kits with detailed instructions were mailed to each study participant. Participants then provided saliva samples following Oragene DNA protocol, and mailed samples back using the return envelope provided. The collection kits include a preservative that permits the transportation of the saliva without DNA degradation or the need for refrigeration.  Two methods were utilized to extract DNA from the Oragene kits. For Family 1, DNA was extracted manually according to the DNA Genotek prepIT-L2P laboratory protocol for manual purification of DNA. To ensure samples were free of RNA contamination, a subsequent RNase treatment was performed. First, DNA samples were diluted with elution buffer to a total volume of 500 uL, and 0.5 uL of RNase was added so that the final RNase concentration was 10 ug/mL. The DNA/RNase solution was incubated at 37 ˚C for 30 minutes. Next, 50 µL of 3M sodium acetate (pH 5.2) and 1 mL of 100% ethanol were added to each sample to precipitate the  27 DNA. Samples were then incubated overnight (18.5 hours total) at -20 ˚C to allow for complete precipitation of the DNA. After incubation, samples were centrifuged at 14,000 rpm for 10 minutes at 4 ˚C. The supernatant from each sample was removed, and then 200 µL of ice cold 70% ethanol was added to each sample. Samples were centrifuged at 14,000 rpm for 10 minutes at 4 ˚C for a second time, and the supernatant and all remaining 70% ethanol was pipetted out. The lids of the Eppendorf tubes containing the samples were left open for 5.5 hours to evaporate any residual ethanol. Lastly, DNA was re-suspended in 100 µL of elution buffer (a pH neutral nucleic acid solvent), for a final volume of 100 µL per sample.  For all subsequent families after Family 1, and for one member of Family 1 who required DNA to be re-collected due to poor quality, the Maxwell RSC Blood DNA AS1400 extraction kit from Promega (Madison, Wisconsin) was used following the blood/saliva RSC DNA protocol. The Maxwell extraction kit is an automated process that extracts DNA from blood or saliva samples through the use of magnetic beads. Saliva was heated for one hour at 50 ˚C in a water bath before the extraction process. With clean gloves, extraction kit cartridges and 0.5 mL elution tubes were placed into the tray. Then 50 µL of elution buffer was added to each of the 0.5 mL elution tubes. For each study participant, DNA was extracted from two 300 µL aliquots of saliva sample. First, 300 µL from the collected saliva sample was pipetted into the first well of each extraction cartridge. After the automated DNA extraction process was complete, the Maxwell processor deposited the genomic DNA into the 50 µL of elution buffer in a 0.5 mL PCR tube. Residual magnetic beads were also deposited into the PCR tube; these were concentrated by centrifuging the DNA samples at 10,000 G for two minutes. Duplicate samples were then combined by pipetting 40 µL of each one into a single sterile 1.5 mL Eppendorf tube, taking care to exclude the magnetic beads. This resulted in 80 µL total of extracted DNA from  28 each study participant. Concentrations varied from 8 – 230 ng/µL, depending on the initial quality of the saliva sample. None of the samples extracted using this automated process required RNase treatment.  2.2.1 Quality Control Assessment of DNA quality was achieved using three different measures: agarose gel, NanoDrop 2000 spectrometer, and Quantus fluorometer. All DNA samples were quantified using the NanoDrop 2000 and by visualizing the DNA on a gel. Additionally the Quantus fluorometer was used to measure DNA concentration in samples extracted using the Maxwell RSC Blood DNA AS1400 extraction kit. An agarose gel was made at 1% concentration using 40 mL of 1x TBE buffer, 0.4 g of agarose, and 4 µL of 10,000x CyberSafe DNA gel stain. DNA samples were prepared on parafilm, combining 1 µL of 6x DNA loading dye with a combination of 5 µL sample and elution buffer so that absolute amount of DNA added was ~200 ng, and the final volume was 6 µL. Next, 5 µL of 1 kb ladder was added to the first well of the agarose gel, with samples in neighbouring wells. The agarose gel was run for 30 minutes at 100 V before DNA within the gel was visualized using a UV transilluminator. NanoDrop-based quality assurance was conducted using the following protocol. The NanoDrop (Thermo Fisher Scientific, Waltham, MA) was set to measure nucleic acid quality. First, 1 µL of elution buffer (from the DNA Genotek or Promega kits, depending on prior extraction method) was placed on the NanoDrop and measured as the blank, setting the background wavelengths that would be present in the DNA samples. Between each  29 measurement, the NanoDrop was cleaned with a Kimtech wipe. Next, 1 µL of patient sample was placed on the Nanodrop and measured to determine DNA concentration and purity.  To measure DNA concentration 1 µL of sample was added to 199 µL of Quantus fluorometer dye in a 0.5 mL Eppendorf tube, vortexed briefly, and incubated in a dark drawer for 5 minutes. After incubation, each 0.5 mL Eppendorf tube containing the sample was placed in the Quantus fluorometer and the nucleic acid concentration was measured. Human cancer cell K562 genomic DNA was used as the standard for Quantus measurements.  2.3 Microarray Aliquots of participants’ samples from Family 1 were sent to the Cytogenetics Laboratory at Children’s and Women’s Health Centre of BC for whole-genome SNP microarray on the CytoScan HD Array from Affymetrix (Santa Clara, California). Microarray data were analyzed on Affymetrix Chromosome Analysis Suite (ChAS) software to identify candidate genomic regions of interest. In collaboration with Dr. Patrice Eydoux, regions of homozygosity (ROH) and copy number variants (CNVs) shared between affected and unaffected siblings were eliminated as potential candidate regions. Thresholds for detection of candidate pathogenic CNVs in affected subjects were set to require a minimum of 20 CNV markers for deletions and 30 CNV markers for duplications. The clinical thresholds for minimum length (200kb for deletions and 400kb for duplications) were not used for calling CNVs, as we reasoned that pathogenic CNVs would likely be smaller than these thresholds and did not want to limit our scope of discovery. These thresholds were chosen after consulting with Dr. Patrice Eydoux, Director of the Cytogenetics laboratory at Children’s and Women’s Health Centre of British Columbia.   30  2.3.1 Validation of Candidate CNV by qPCR Candidate CNVs were validated with quantitative polymerase chain reaction (qPCR). Four sets of primers, two sets within the deleted region and two sets in the undisrupted region (approximately 2 Kb in length) 5’ of the microdeletion, were designed to carry out the qPCR. Primers were design using Primer BLAST on NCBI (http://www.ncbi.nlm.nih.gov/tools/primer-blast/), with an amplicon size between 105 – 115 bp (an optimal length for qPCR), and melting temp below 62°C (Appendix B). To check for self-complementarity of primer pairs, OligoCalc (http://biotools.nubic.northwestern.edu/OligoCalc.html) algorithm was used to scan for hair-pin formation and self-annealing. Primer sequences were inputed into in silico PCR by the UCSC algorithm (https://genome.ucsc.edu/cgi-bin/hgPcr), to ensure specificity by determining the location(s) and number of predicted PCR products. G6PD was used as a gene control to check for amplification of DNA from each sample. The qPCR reaction was optimized for these primers in two steps:  First, the optimal amount of gDNA to be added to each reaction was determined. Stock DNA was diluted eight times by multiples of 10 from its initial concentration of 38.7 mg/µL, and run following Promega’s GoTaq qPCR Master Mix protocol using primers already known to work, in this case the G6PD primers. Based on the CT value (26 for 100x dilution) it was determined that 5 ng of gDNA per reaction would be appropriate. Second, each designed primer pair was confirmed to produce an amplified product using 5 ng of test DNA per reaction.  Patient DNA samples were then diluted to a final concentration of 1.25 ng/µL and following the GoTaq qPCR Master Mix protocol by Promega. Each qPCR reaction contained 10 µL GoTaq qPCR Master Mix (2x), 1 µL 5M forward primer, 1 µL 5M reverse primer, 0.2 µL  31 CXR reference dye, 4 µL of patient DNA and 3.8 µL ddH2O for an overall volume of 20 µL per reaction.   2.4 Next-Generation Sequencing  Whole-exome sequencing for Family 1 was carried out by Perkin Elmer Inc. with the SureSelect V4 (51 Mb) All Exon Kit (Agilent) for targeted exome selection and sequenced on an Illumina HiSeq 2000 to 50x mean coverage. Variant calling, filtering, and annotation were carried out using VarSeq software by Golden Helix. WES for Families 3, 4 and 5, was carried out using Agilent Human SureSelect kit for multiplex exome capture and Illumina HiSeq 2500 with four samples per 125 base paired-end tag (PET) to 30X mean coverage lane by the Michael Smith Genome Sciences Centre (GSC) in Vancouver, British Columbia under the supervision of Dr. Steven Jones. Whole-genome sequencing for Family 2 was carried out using an Illumina HiSeq 2500 with two lanes of 125 base PET to 30X mean coverage, also by the GSC under the supervision of Dr. Jones. Read alignment and variant calling, filtering and annotation were done via the GSC in-house pipeline.   2.5 Variant List Annotation  For Family 1, VarSeq used five algorithms (Polyphen 2, MutationTaster, MutationAssessor, FATHMM and SIFT) to predict the effect of each variant on the cognate protein. The GSC pipeline annotated variants using two protein prediction algorithms, Polyphen 2 and SIFT. Both VarSeq and the GSC annotated variants with known Online Mendelian Inheritance in Man (OMIM; https://www.omim.org/) associations to disease.   32 Additionally, all candidate variant lists were annotated manually using the Gene Ontology Consortium (http://geneontology.org), National Centre for Biotechnology Information Gene database (https://www.ncbi.nlm.nih.gov/gene), International Mouse Phenotyping Consortium (http://www.mousephenotype.org), Genotype-Tissue Expression (GTEx) Portal (http://www.gtexportal.org/home/), and through a literature search of the gene name with a defined set of search terms (Table 2.1). Table 2.1 Literature search terms BROAD NARROW RELATED  • Angiogenesis • Artery • Blood vessel • Brain • Cerebral • Endothelium/ Endothelial • Smooth muscle • Vascular/Vasculature  • Aneurysm • Intracranial berry aneurysm (IBA) • Saccular aneurysm • Subarachnoid haemorrhage (SAH) • Stroke   • Abdominal aortic aneurysm (AAA) • Inflammation • Thoracic aortic aneurysm (TAA)   2.6 Sanger Sequencing Sanger sequencing was used to validate or reject candidate variants identified through exome sequencing. Primers were designed for PCR amplification of participant DNA prior to Sanger sequencing using the same tools as were used to design primers for qPCR on CNVs. In Family 1 primers were designed for one candidate variant in each of 6 genes (RYR1, BSN, VAT1, HSPB6, ARHGAP33, and FRY) and two candidate variants in one gene (SLC7A9). Primer sequences are shown in Appendix C. All additional primers for Sanger validation were designed following the same methods as in Family 1. Primers for validation of one candidate variant in CCM2 in Family 2 are shown in Appendix D. Primers for validation and segregation analysis of rare variants in THSD1 and PKD1 in Family 5 are shown in Appendix E and Appendix F, respectively.  33 Primer pairs were tested and optimized using test DNA at six annealing temperatures (52°C, 55°C, 57°C, 59°C, 61°C, and 63°C). Before Sanger sequencing, each DNA sample was amplified using GoTaq Master Mix (2x concentration) by Promega following the associated protocol on the Veriti 96 Well Thermal Cycler by Applied Biosystems. The settings for the Thermal Cycler were as follows: 2 minutes at 94°C; 45 seconds at 94°C; 45 seconds at optimal primer annealing temperature, followed by 1 minute at 72°C, repeated a total of 35 times; 10 minutes at 72°C; hold at 4°C until the Thermal Cycler run stopped. Each reaction contained 10 µL GoTaq Master Mix, 1 µL Primer pair (with each forward and reverse primer at 5 µM concentration), 1 µL 100% DMSO, 3 µl ddH20, and 5 µl of sample DNA (at a concentration of 8 ng/µL). Amplified DNA was then sequenced using the ABI Prism 3130xl Genetic Analyzer, and ABI BigDye v3.1 Terminator chemistry. Sequenced reads were analyzed using Sequence Scanner 2 by Applied Biosystems to identify variants, and CLC Sequence Viewer 7 by Qiagen to align sequenced reads to the reference genome.   2.7 Overall Analysis Strategy Most rare disease phenotypes that have been solved to date are caused by rare coding variants in the exome that are predicted to be protein-damaging.171 Thus, this study used next generation sequencing to identify rare coding variants in families with FIA. A minimum of one affected member from each FIA family received sequencing. Variants in the exome of each sequenced individual were filtered to meet quality thresholds (Read Depth and Genotype Quality > 20) and to have a minor allele frequency (MAF) <0.01. MAF for each variant was initially determined using the National Heart, Lung, and Blood Institute (NHLBI) database, and then confirmed against broader population data found in the Exome Aggregation Consortium (ExAC)  34 database. Variants were also filtered by zygosity to match the hypothesized inheritance pattern in the family (e.g. for families that appear to have dominant inheritance, heterozygous variants were retained) (Figure 2.1). Through this filtering, both the very rare variants that cause Mendelian disease (MAF <0.001) as well as variants that have an intermediate penetrance (MAF between 0.001 and 0.01) were identified (Figure 2.2). We used a less stringent MAF, because of what we know about the genetics of other common, complex diseases. Diseases that rarely present as a Mendelian disorders, and more commonly present as sporadic disease, typically feature very rare and highly-penetrant alleles in multiplex families, as well as an enrichment for rare but less-penetrant alleles in apparently sporadic late-onset cases. An example of a disease that exhibits this type of allelic architecture is coronary artery disease; both rare loss-of-function variants and uncommon variants in ANGPTL4 significantly lower triglyceride levels, and are protective against this common, complex disease in the individuals and families who carry them.172,173  The list of rare, potentially damaging candidate variants identified in each affected family member was then overlapped to identify candidate genes that contained rare variants in three or more families. Upon the recent discovery of the role of THSD1 in intracranial aneurysm formation, sequencing data were used to seek rare variants in this specific gene in all families in our cohort. All 5 exons of THSD1 had mean 30x coverage from the exome or genome sequencing.   Among large multiplex families, such as Family 1, whole-genome SNP microarray was used to find genomic regions shared among affected family members that were not shared by unaffected family members. Due to the variability in family size, only families for which we had large numbers of both affected and unaffected members received microarray for haplotype mapping. The genomic coordinates of the candidate regions shared by affected family members  35 were then used to filter the rare variants found via WES even further (Figure 2.1). In families that received microarray, CNVs were also identified and investigated as the potential cause of IBA formation.   Figure 2.1 Outline of analysis of FIA families  CNV: Copy number variant; MAF: Minor allele frequency; SNP: single nucleotide polymorphism      36    Figure 2.2 Disease penetrance versus allele frequency            This graph shows the genetic architecture of common, complex disease. Both rare and common disease variants contribute to disease risk for conditions such as IBA.174  2.7.1 De Novo Variant Analysis In families such as Family 3, wherein the parents appear to be unaffected, the presence of severe and/or early onset of disease in the proband is suggestive of a de novo mutation leading to aneurysm formation. Since de novo variants would be considered top candidates for pathogenic mutations causing IBA formation in families with this structure (followed by compound heterozygous and homozygous variants), trio-based exome sequencing can be a useful strategy to find these variants. However, without diagnostic brain imaging in the parents, it is not possible to rule out conclusively that one of them may be harbouring an unruptured IBA. Furthermore, it is impossible to be truly certain that a parent is unaffected, since he or she might develop an IBA later on in life. Lastly, a parent may carry the risk allele and be non-penetrant. Thus, in families  37 with pediatric-onset IBA, rare variants in genes that overlap with candidates from other FIA families should also be considered, even when these variant(s) are inherited from unaffected parents.  38 Chapter 3: Results 3.1 Study Cohort The families presented in this thesis are the first to be sequenced and analyzed in an ongoing research study on the genetics of familial intracranial aneurysms. The size of the entire cohort is 49 affected and 28 unaffected individuals from 18 families, and 5 isolated affected cases, for a total of 82 individuals (Table 3.1 and Table 3.2). At the time of writing, DNA from 17 affected and 2 unaffected individuals from this cohort has undergone next-generation sequencing. Sections 3.2, 3.3, 3.4, 3.5, and 3.6, describe genome or exome sequencing results specific to each family. Section 3.7 describes the results from the analysis done by overlapping the genes containing rare variants between all of the families.      39 n 82No. of singletons 5No. of familes 18       by ethnicity (%)African 1 (5.6)    European 14 (77.8)         First Nations 3 (16.7)Age, mean* 49.4 Range 12-78No. Women, (%) 56 (68.3)No. Affected (%) 49 (59.8)No. DNA samples collected (%) 34 (41.5)No. Families with ≥1 affected sequenced 9 (50.0)No. Affected sequenced (%) 9 (11.0)No. Unaffected sequenced (%) 2 (2.4)No. Rare variants 2147Demographics of Cohort*This refers to the mean age at diagnosis or screening. *This refers to the mean age at diagnosis or screening. n 49No. Women (%) 36 (73.5)Age, mean* 47.9Range 12-78No. Ruptured 16 (32.7)Demographics of Affecteds          Table 3.1 Demographics of Cohort                                                     Table 3.2 Demographics of Affecteds           40 3.2 Family 1 3.2.1 Pedigree and Phenotype The first family has a history of IBA spanning three generations and is of European ancestry. Family 1 contains three affected siblings and four clinically unaffected siblings in the third generation, all of whom have had clinical brain imaging (Figure 3.1). Family members III-2, III-4, and III-5 were all screen-positive by age 60 years, and have since had surgical intervention (either by clipping or coiling) (Table 3.3).  The proband, III-2, was diagnosed by CT scan at 59 years of age with a single aneurysm on her anterior communicating artery. She chose not to pursue treatment at that time, but subsequently had two coiling procedures done at the age of 63. The first coiling procedure was done on an emergent basis because of aneurysmal hemorrhaging, and a second was done 6 months later in the same location because her aneurysm had increased in size to 4 mm in diameter. III-2 smokes approximately half a pack of cigarettes per day and has controlled hypertension, both of which are additional risk factors for aneurysm formation and rupture.  III-4 has been diagnosed with four IBA: bilateral lesions on the middle carotid artery (MCA), one on the left internal carotid artery (ICA), and the last on the posterior communicating (Pcom) artery. At age 54 she had the bilateral MCA aneurysms clipped surgically and the left ICA treated with endovascular coiling. The Pcom aneurysm was 3 mm in size when last scanned and remains untreated.  III-5 had two aneurysms treated through surgical clipping at the age of 53.  III-1, III-3, III-6, and III-7 have all been screened using MRI, MRA, or CT and do not show any indications of intracranial aneurysms by ages 72, 66, 57, and 55, respectively. I-1 and II-1 both died from SAH at age 56 years and 66 years, respectively.  41   Figure 3.1 Pedigree of Family 1 B   “P” indicates the proband; “dx.” denotes the age at diagnosis; “d.” denotes the age at death                                                      B A version of this figure has been published as: Hitchcock, E., and Gibson WT. A Review of the Genetics of Intracranial Berry Aneurysms and Implications for Genetic Counseling. Journal of Genetic Counseling 2017, Volume 26, Issue 1, pp 21–31, First Online: 14 October 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, with attribution. I II III 1 2 1 2 3 4 1 2 3 4 5 6 7 P d. 66y d. 57y 72y 61y dx. 53y 62y dx. 54y 66y 68y dx. 59y 55y 57y  42  Table 3.3 Phenotypes of the third generation in Family 1 Family Member III-1 III-2 III-3 III-4 III-5 III-6 III-7 Affected (Y/N) N Y N Y Y N N Sex (M/F) M F F F M F M Age (years) 72 68 66 62 61 57 55 At diagnosis or screening 64 59 60 54 53 50 48 Number of IBA - 1 - 4 2 - - Location and size of IBA -    Acom (5 mm) -    L. ICA (6 mm)    unknown - -            recurred (4mm)      L. MCA (7.4 mm)                  R. MCA (6.4 mm)                  R. Pcom (3 mm)       Symptomatic (Y/N) - Y - N N - -      Headache   Severe headache and nausea at time of SAH                Dizziness    N                Other   N           SAH (Y/N) - Y - N N - -      Age (years), Location   63, Acom            Treatment (Y/N) - Y - Y Y  - -      Age (years), Location         53, unknown          Surgical clipping   -      53, bilateral MCA            Endovascular coiling   Y      54, Pcom            Other   -           Hypertension (Y/N) Y N - N Y - post-treatment, controlled by medication - - Smoking (Y/N) N Y - - - - - Additional Phenotype(s) - - - - - - - Affected family members are indicated by bold text. Information was not collected, or not applicable, for fields marked by a dash. Acom: Anterior communicating artery; IBA: Intracranial berry aneurysm; L. ICA: Left interior carotid artery; L. MCA: Left middle communicating artery; R. MCA: Right middle communicating artery; R. Pcom: Right posterior communicating artery; SAH: Subarachnoid hemorrhage  43  3.2.2 Microarray A single candidate CNV, a microdeletion, was identified using ChAS. This CNV was found to be common only between the three affected siblings and absent from the DNA of the four unaffected siblings. This copy number loss disrupted one gene, deleted in malignant brain tumors 1 (DMBT1), on chromosome 10 and deleted a minimum of 12 exons at the 5’end of the gene (Figure 3.2). The length of this microdeletion varied between affected siblings, and is almost three times as long in III-2. The chromosomal section of the microdeletion that is absent in all three siblings is approximately 12.7 kb in length from chr:124,343,937-124,356,641 (Figure 3.4). Its presence in the three siblings with brain aneurysms and absence in the four siblings without brain aneurysm was confirmed by qPCR of genomic DNA (Figure 3.5 and Figure 3.6).  DMBT1 is expressed by endothelial cells and secreted into the extracellular matrix, and is also found to bind with known components of angiogenic pathways, including VEGF. In DMBT1 knock-out mouse models vascular repair after hind limb ischemia was impaired compared to wild-type mice.175 Although this microdeletion was found to segregate with disease, it was ultimately discarded as a candidate due to the apparent size discrepancy between affected siblings and the highly polymorphic nature of the region in which the CNV was found. DMBT1 also transcribes salivary agglutinin protein (SAG). This protein is thought to interact with oral bacteria and certain isoforms are associated with a decrease in dental carries. DMBT1 is known to have two highly polymorphic regions within the gene, which are characterized by both copy number gain and copy number loss formed through non-allelic homologous recombination. These CNVs have a 5% de novo mutation rate per gamete and change the number of tandem scavenger-receptor cysteine-rich domains (SRCR) within the protein.176 The first highly variable  44 region consisting of many tandem repeat sequencing and involves SRCR 2-6, overlaps with the region that contains all three microdeletions in the affected siblings from Family 1. Although these tandem repeats account for the varying lengths of the microdeletions, the presence of CNVs at this region within DMBT1 do not appear to be a rare occurrence. Both deletions and duplications have been reported in the Database of Genomic Variants (DGV; Build GRCh37: Feb. 2009, hg19) (http://dgv.tcag.ca/dgv/app/home) numerous times, further indicating that these CNVs are common changes within the general population. Despite the suggestive evidence from animal studies, we considered the combined evidence from the literature and DGV to be stronger predictors of lack of pathogenicity, and discarded this variant as a candidate.     45    Figure 3.2 Candidate microdeletion in DMBT1 in Family 1   A microdeletion in DMBT1 found in affected siblings III-2, III-4, and III-5 shown in red on Chromosome Analysis Suite. The boxes and lines in pink show the exons transcribed in three different transcripts of DMBT1. The coloured lines (different for each sibling) and dots along each line display the log2 ratio for each CNV probe. Dots that lie on the line represent a normal copy number of two, while dots that lie approximately 0.45 units below the line indicate a single copy number loss, as is seen in the deleted regions. The dark green and light green boxes denote the location CNV markers and SNP markers along this genomic region, respectively.   46 Figure 3.3 Candidate microdeletion in DMBT1 in affected siblings of Family 1                  A microdeletion within DMBT1 found in affected siblings III-2, III-4, and III-5 shown in red on Chromosome Analysis Suite. The full length of the CNV in III-2 has been truncated in this figure in order to show the log2 ratios. The coloured lines (different for each sibling) and dots along each line display the log2 ratio for each CNV probe. Dots that lie on the line represent a normal copy number of two, while dots that lie approximately 0.45 units below the line indicate a single copy number loss, as is seen in the deleted regions. The dark green boxes denote the location CNV markers along this genomic region.  III-2 III-4 III-5  47 Figure 3.4 Region of DMBT1 microdeletion common between affected siblings    Exome sequencing coverage from affected brother III-5 shown on Genome Browse software by Golden Helix. The red bars mark the chromosomal region between chr10:124,343,937 - 124,356,641, approximately 12.7kb in length, which is deleted in all three affected siblings.   48 Family 1 Family 2 Figure 3.5 Relative gDNA in region 5' of DMBT1 between unaffected and affected family members              Figure 3.6 Relative gDNA in region of microdeletion between unaffected and affected family members             Family 1 Family 2  49  3.2.3 Exome Sequencing WES of III-5, filtered following the methods in Chapter 2, produced 1,042 rare heterozygous variants. Further filtering using the coordinates of genomic regions shared by affected siblings resulted in 76 variants in 68 genes. Detailed annotation and literature search of all 68 genes resulted in six variants in NOTCH4, CFB, PIK3C2G, HLA-DRB1, and DDR1 being selected as top candidates (Table 3.4). Eight additional variants in seven genes (RYR1, BSN, VAT1, HSPB6, ARHGAP33, SLC7A9 and FRY) were not confirmed upon Sanger sequencing and were eliminated as candidates. NOTCH4 encodes a protein belonging to the evolutionarily conserved NOTCH family of membrane bound receptors, which are known to be important in early embryogenesis for vascular development. The Notch genes are expressed in many tissues types, however Notch4 is thought to be expressed only in vascular endothelium and arteries.177,178 In mouse models, endothelium-specific expression of constitutively activated Notch4 during embryogenesis resulted in embryonic lethality due to abnormal vasculature around 10 days postcoitum. Blood vessels failed to form in the brain and around the periphery blood vessels either did not form or were dilated, indicating a loss of structural integrity.179 Notch4-deficient mice (through homozygous knock-out) develop normally into adulthood. However, mice with a double homozygous knock-out of Notch1 and Notch4 show a more severe phenotype of abnormal angiogenic remodeling and morphogenesis than do mice with a single knock-out of Notch1. This finding indicates that although Notch4 is not essential for vascular development during embryogenesis, it does have a role in vascular maintenance in adult mice.180 Mice with constitutively active Notch4, induced by tetracycline at birth, developed arteriovenous  50 malformations (AVM) by 3 weeks and died of cerebral hemorrhage by 5 weeks of age. Abnormal connections between arteries and veins were seen in these mice, as were enlarged and tangled blood vessels, all of which are hallmarks of AVM in humans.181  In Family 1 a six base pair insertion in NOTCH4, was predicted to result in two leucine amino acids being added between residues 16 and 17. The two leucine amino acids are inserted into a string of 11 leucine residues near the 5’ end of the protein. It is unclear whether or not this variant leads to disease.  CFB encodes complement factor B, a component of the alternative complement pathway, which has been associated with aneurysm formation in mouse models of abdominal aortic aneurysms.182,183 CFB is also expressed in the endothelium of kidney cysts, but not in other types of kidney disease.184  Phosphatidylinositol-4-Phosphate 3-Kinase Catalytic Subunit Type 2 Gamma (PIK3C2G) remains largely unstudied and its function is not known. PIK3C2A, a protein in the same family, is critical for clathrin-coated vesicle endocytosis-related angiogenesis and the normal formation of vasculature. However, PIK3C2A is structurally distinct from PIK3C2G and other PIK2C2 family members and is limited in its expression to smooth muscle and vascular endothelium. Thus, PIK3C2G is thought to have a different expression profile and function compared to its better-studied family members.185,186 As a HLA Class II beta chain molecule, HLA-DRB1 has been associated with a number of auto-inflammatory conditions such as multiple sclerosis and rheumatoid arthritis. In a cohort of 37 abdominal aortic aneurysm (AAA) patients compared to 90 controls, HLA-DRB1 alleles *0404 and *15 have a higher frequency in AAA patients compared to controls: 14% versus 3% and 47% versus 27%, respectively.187 In Marfan syndrome patients, increased HLA-DRB1  51 expression is associated with aortic root dilation compared to patients with low aortic root dilation.188 DDRI encodes a discoidin domain receptor (DDR), a type of tyrosine kinase. DDRs are autophosphorylated upon binding to Type 1 and Type VIII Collagen. Ddr1 mRNA and protein expression is increased in rat aorta after balloon-catheter injury. Cultured smooth muscle cells from mouse aortas were used for an attachment assay that compared wild type cells with those bearing targeted deletion of Ddr1. The smooth muscle cells containing the Ddr1 deletion had reduced adherence to collagen and reduced proliferation on the collagen matrix. Mice with the targeted deletion in Ddr1 also showed reduced intimal growth of the carotid arteries in response to wire-induced injury.189 Another experiment on smooth muscle cells from mouse aorta with knock-out of Ddr1 showed impaired attachment to and migration toward Type I Collagen. Transfection of these cells with Ddr1b cDNA lacking the catalytic domain partially rescued the phenotype, restoring attachment but not migration of the smooth muscle cells.190  Although each of the genes discussed above have a role in vasculature, none are a compelling candidate and will require further functional work to name them as causative within this family.    52   Table 3.4 Top candidate variants from Family 1 Chr:Pos Ref/Alt Allele Identifier MAF Gene Names Protein Change OMIM Disease Association CADD Score 6:31917898 C/A - 0.000008493 CFB p.P996T Complement factor B deficiency 29.8 12:18719887 C/T rs146312199 0.003642 PIK3C2G p.P1262S - 28.8 6:32549582 G/T rs200516145 - HLA-DRB1 p.T135N Autoimmune susceptibility  23.4 19:35842992 G/A rs146654047 0.003077 FFAR1 p.G180S - 17.84 6:32549583 T/C rs17433947 - HLA-DRB1 p.T135A Autoimmune susceptibility  10.07 6:30862440 A/G rs55787895 0.009611 DDR1 p.N502S - 0.166 6:32191659 -/AGCAGC - - NOTCH4 p.L16_L17insLL - 0.005 6:24456812 G/T - - GLPD1 p.F354L - 0.003 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, MAF: minor allele frequency (for European ancestry), OMIM: Online Mendelian Inheritance in Man, Ref: reference.      53 3.3 Family 2 3.3.1 Pedigree and Phenotype Family 2 has a history FIA spanning two generations with onset 15 to 20 years earlier than the mean age-of-onset in the general population with sporadic aneurysms (Figure 3.7 and Table 3.5). Family 2 is of Canadian First Nations ancestry and has three affected individuals. Affected family members I-2 and II-3 died by SAH, both at age 36 years; additional clinical and phenotypic information is unavailable. There have also been four deaths from SAH in extended family members on the paternal side (I-1) of the family (not shown in pedigree). There is no known consanguinity in this family. The proband, II-1, was first diagnosed with FIA, upon rupture of an IBA on the left middle MCA at age 40 years, for which he was subsequently treated with surgical clipping. The proband has since been diagnosed two additional IBA. The second IBA is located on the left Pcom, which was treated with endovascular coiling at 47 years of age after SAH. The third IBA, located on the right MCA, is currently stable and being monitored. There is also an abnormality on the anterior communicating (Acom) artery, which may turn out to be a fourth IBA. The two sons of the proband, III-1 and III-2, appear unaffected, but are not yet at the age to require screening, meaning their true affected status is currently unknown.  54    Figure 3.7 Pedigree of Family 2 C   “P” indicates the proband; “dx.” denotes the age at diagnosis; “d.” denotes the age at death                                                      C A version of this figure has been published as: Hitchcock, E., and Gibson WT. A Review of the Genetics of Intracranial Berry Aneurysms and Implications for Genetic Counseling. Journal of Genetic Counseling 2017, Volume 26, Issue 1, pp 21–31, First Online: 14 October 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, with attribution. III               1 2 2 1 I II 3 4 5 6 7 2 1 3 4 5 P d. 36y d. 36y 55y dx. 40y  55   Table 3.5 Phenotype of Family 2 Family Member I-2 II-1 II-3 Affected (Y/N) Y Y Y Sex (M/F) F M F Age (years) - 55 - At diagnosis or screening 36 40 36 Number of IBA 1 3 1 Location and size of IBA unknown L. MCA unknown     R. MCA       L. Pcom   Symptomatic (Y/N) - N -      Headache            Dizziness             Other       SAH (Y/N) Y Y Y      Age (years), Location 36, unknown 40, L. MCA  36, unknown     47, L. Pcom   Treatment (Y/N)  - Y -      Age (years), Location            Surgical clipping   40, L. MCA         Endovascular coiling   47, L. Pcom        Other   -   Hypertension (Y/N) - N - Smoking (Y/N) - - - Additional Phenotype(s) - Long-QT Syndrome - Affected family members are indicated by bold text. Information was not collected, or not applicable, for fields marked by a dash. Acom: Anterior communicating artery; IBA: Intracranial berry aneurysm; L. MCA: Left middle communicating artery;  R. MCA: Right middle communicating artery; L. Pcom: Left posterior communicating artery; SAH: Subarachnoid hemorrhage    56 3.3.2 Genome Sequencing Previous to this study, II-1 tested negative for pathogenic variants in TGFBR1 and TGFBR2 at University of Washington.WGS, filtered following the methods in Chapter 2:, produced 1,106 rare heterozygous variants in the exome. Analysis of unique variants in known OMIM disease-causing genes produced one candidate variant in cerebral cavernous malformations 2 (CCM2), shown in Table 3.6. Heterozygous mutations in CCM2 lead to cerebral cavernous malformations (CCM), which are characterized by chronic headaches, seizures, and subarachnoid hemorrhage. While missense variants have been reported in CCM2 to cause CCM, most often the pathogenic mutations are multi-exon deletions or truncating mutations.191,192 CCM2 is part of a scaffolding protein complex that maintains endothelial cell-cell binding and vascular integrity.193,194  Homozygous knock-out and morpholino knock-down of the zebrafish CCM2 orthologue valentine, leads to embryonic lethality and causes enlargement of the heart chambers.195 In mice, constitutive deletion of Ccm2 results in a very similar phenotype to that of the zebrafish, with lethality by embryonic day 10.5 due to a grossly enlarged heart and cardiac failure. Endothelial-specific knock-out of Ccm2 in mice is usually embryonic lethal, and also leads to an enlarged heart and dilated major blood vessels.196 We hypothesize that if the p.Q11R variant in CCM2 in this family is pathogenic for FIA, the mechanism of aneurysm formation would be through a weakening of endothelial cell-cell adhesion allowing the blood vessel wall to expand over time.  57   Table 3.6 Candidate variant in CCM2 in Family 2 Chr:Pos Ref/Alt Allele Zygosity MAF Gene Names Protein Change OMIM Disease Association CADD Score 7:45067335 A/G het 0.000008242 CCM2 p.Q11R Cerebral Cavernous Malformations 11.53 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, het: heterozygous, MAF: minor allele frequency (for global ancestries), OMIM: Online Mendelian Inheritance in Man, Ref: reference.        58  3.4 Family 3 3.4.1 Pedigree and Phenotype Family 3 presents a single pediatric case of IBA and SAH in a 12-year-old boy (Figure 3.8 and Table 3.7). This family is of European ancestry and does not have a family history of intracranial aneurysms. The proband, II-2, was diagnosed with IBA upon hemorrhage of a 4 mm aneurysm that had formed off the anterior communicating artery (Acom). The proband did not experience any symptoms before SAH and is an otherwise healthy, athletic child with no known risk factors. Upon rupture of the Acom aneurysm the proband experienced severe head pain and was taken to his local hospital where he was screened with a CT scan that showed the ruptured aneurysm with a small daughter lobule also present. He was subsequently treated with surgical clipping. None of the other family members have been screened to date (on the advice of their neurosurgeon), so their affected status is not known.   59    Figure 3.8 Pedigree of Family 3 D  “P” indicates the proband; “dx.” denotes the age at diagnosis; “d.” denotes the age at death                                                      D  A version of this figure has been published as: Hitchcock, E., and Gibson WT. A Review of the Genetics of Intracranial Berry Aneurysms and Implications for Genetic Counseling. Journal of Genetic Counseling 2017, Volume 26, Issue 1, pp 21–31, First Online: 14 October 2016. This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, with attribution. I II 1 2 1 2 3 P 49y 45y 14y 12y dx. 12y 10y  60 Table 3.7 Phenotype of Family 3 Family Member I-1 I-2 II-1 II-2 II-3 Affected (Y/N) N N N Y N Sex (M/F) M F F M F Age (years) 49 45 14 12 10 At diagnosis or screening - - - 12 - Number of IBA - - - 1 - Location and size of IBA -   -   Acom (4 mm) - Symptomatic (Y/N) - - - - -      Headache                Dizziness                 Other           SAH (Y/N) - - - Y N      Age (years), Location       12, Acom   Treatment (Y/N)    - - - Y -      Age (years), Location                Surgical clipping         Acom (4 mm)        Endovascular coiling                Other           Hypertension (Y/N) - N N N N Smoking (Y/N) - - N N N Additional Phenotype(s) N N N N N Affected family members are indicated by bold text. Information was not collected, or not applicable, for fields marked by a dash. Acom: Anterior communicating artery; IBA: Intracranial berry aneurysm; SAH: Subarachnoid hemorrhage   61 3.4.2 Exome Sequencing WES of II-2, filtered following the methods in Chapter 2:, produced 770 rare heterozygous or homozygous variants. Trio analysis of sequencing data from the proband and his two parents identified 2 de novo variants in CA5A and C2orf16 (Table 3.8). Compound heterozygous variants were found in 5 genes in the proband: VPS18, AHCTF1, FAM198B, RPF2, and ARFGEF1 (Table 3.9). There were no candidate homozygous variants.   Homozygous variants in carbonic anhydrase 5A (CA5A) that disrupt enzyme function lead to an autosomal recessive form of hyperammonemia caused by carbonic anhydrase deficiency. Patients with these pathogenic mutations have an early-onset metabolic phenotype.193 Information on the function of C2orf16 is not yet available from the scientific literature. VPS18, AHCTF1, FAM198B, RPF2, and ARFGEF1 have not been associated with intracranial aneurysms previously, and do not appear to have functions related to the vasculature.  At this time there is no evidence to support the variants discussed above as being causative for the IBA in II-2. However, as research discovers more information on each genes function, one or more of these variants may become a compelling candidate.    62  Table 3.8 De novo variants in II-2 in Family 3 Chr:Pos Ref/Alt Allele Identifier MAF Gene Names Protein Change OMIM Disease Association CADD Score 16:87935534 G/A - 0 CA5A p.P201L Hyperammonemia due to carbonic anhydrase VA deficiency 24.7 2:27804355 G/A rs199903910 0.00001499 C2orf16 p.R1639H - 13.22 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, MAF: minor allele frequency (for European ancestry), OMIM: Online Mendelian Inheritance in Man, Ref: reference.   Table 3.9 Compound heterozygous variants in II-2 in Family 3 Chr:Pos Ref/Alt Allele Identifier MAF Gene Names Protein Change OMIM Disease Association CADD Score 1:247013595 T/C rs149899496 0.0007215 AHCTF1 K1914E - 10.92 1:247065904 C/A - 0 AHCTF1 S347I - 24.7 4:159091752 C/A - 0 FAM198B R259L - 12.73 4:159092106 C/T rs147697286 0.01126 FAM198B G141E - 14.83 6:111345454 A/G - 0 RPF2 D189G - 28.9 6:111345474 C/T - 0 RPF2 H196Y - 23.8 8:68165850 T/C - 0 ARFGEF1 N845S - 14.92 8:68204202 C/A rs61753695 0.006731 ARFGEF1 D266Y - 23.3 15:41191665 C/T - 0.00003057 VPS18 R217C - 28.3 15:41195357 C/T rs189855795 0.008217 VPS18 R914W - 24.8 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, MAF: minor allele frequency (for European ancestry), OMIM: Online Mendelian Inheritance in Man, Ref: reference.      63 3.5 Family 4 3.5.1 Pedigree and Phenotype Family 4 has one affected family member (II-6) with a clinical history of IBA (Figure 3.9). II-6 was diagnosed with three IBA, consisting of a giant aneurysm (2.5 cm in size) of the internal carotid artery (ICA), and bilateral aneurysms on the middle cerebral artery (MCA). She was brought to her local emergency department upon blood leaking from her ICA aneurysm, and immediately received surgical clipping for two of her three IBA. The third IBA was also clipped two years later (Table 3.10). Initially it was thought that the hemorrhagic stroke experienced by the proband’s sister, II-2, was caused by an IBA, but upon further investigation was found to be caused by a spontaneous posterior fossa hematoma (that showed no signs of vascular involvement).  64    Figure 3.9 Pedigree of Family 4            “P” indicates the proband; “dx.” denotes the age at diagnosis; “d.” denotes the age at death                 65 Table 3.10 Phenotype of Family 4 Family Member II-1 II-2 II-3 II-4 II-5 II-6 II-7 II-8 II-9 II-10 II-11 Affected (Y/N) N N N N N Y N N N N N Sex (M/F) F F F M M F F F F F M Age (years) - 79 - 75 73 71 69 - 64 62 59    At diagnosis or screening - - - - - 68         - Number of IBA - - - - - 3 - - - - 2 Location and size of IBA - - - - - L. MCA (4 mm) - - - - -             R. MCA (3 mm)                       L. ICA (2.5 cm)           Symptomatic (Y/N) - - - - - Y - - - - -      Headache                            Dizziness            Y                Other                       SAH (Y/N) - - - - - Y - - - - -      Age (years), Location           68, L. ICA           Treatment (Y/N)    - - - - - Y - - - - -      Age (years), Location                            Surgical clipping           70, R. MCA                       68, L. MCA                       68, L. ICA                Endovascular coiling                            Other                       Hypertension (Y/N) - - - - - - - - - - - Smoking (Y/N) - - - - - N - - - - - Additional Phenotype(s) Stomach cancer Posterior fossa hematoma Stomach cancer N N N St. Vitus' Dance Stomach cancer N N N Affected family members are indicated by bold text. Information was not collected, or not applicable, for fields marked by a dash. IBA: Intracranial berry aneurysm; L. ICA: Left interior carotid artery; L. MCA: Left middle communicating artery; R. MCA: Right middle communicating artery; SAH: Subarachnoid hemorrhage    66 3.5.2 Exome Sequencing WES of II-6, filtered following the methods in Chapter 2, produced 900 rare heterozygous or homozygous variants. Family-specific candidate genes were not identified in Family 4.  3.6 Family 5 3.6.1 Pedigree and Phenotype Family 5 has a history of FIA spanning two generations and is of European ancestry. Family 5 has four affected and two unaffected members, all of who have been screened clinically with MRI or CT scans (Figure 3.10). The proband (II-5), was diagnosed by MRI at 35 years of age after being referred because of his family history. At the time of his diagnosis, the proband’s older sister (II-1) and older brother (II-2) had already experienced SAH from a ruptured IBA. II-1 was diagnosed with two IBA, both of which have subsequently ruptured and were treated surgically (information on specific intervention was not collected). II-2 also has two IBA, one on the middle cerebral artery (MCA) and one on the posterior communicating artery (Pcom). His initial diagnosis was made after the MCA aneurysm ruptured. Both aneurysms were treated with endovascular coiling; however the Pcom aneurysm recurred and required surgical clipping when it ruptured three years after its initial coiling. Since the diagnosis of three of her children, I-2 received screening and was found to have a small IBA 3 mm in size.  All family members, excluding II-3, have hypertension, which is being controlled by medication. Affected brothers II-2 and II-5 both have a history of smoking, although II-5 has subsequently ceased. II-2 and II-5 developed recurrent seizures since the surgical treatment for their IBA.  67 I II 1 2 1 2 3 4 5 P 82y dx. 76y 60y dx. 41y 41y dx. 35y 53y 57y 59y dx. 53y   Figure 3.10 Pedigree of Family 5              “P” indicates the proband; “dx.” denotes the age at diagnosis          68 Table 3.11 Phenotype of Family 5 Family Member I-2 II-1 II-2 II-3 II-4 II-5 Affected (Y/N) Y Y Y N N Y Sex (M/F) F F M F M M Age (years) 82 60 59 62 53 41 At diagnosis or screening 76 41 53 - - 35 Number of IBA 1 2 2 - - 1 Location and size of IBA 3mm unknown R. Pcom - - R. MCA (6 mm)     1.2 mm R. MCA       Symptomatic (Y/N) N Y N - - N      Headache   Y - Severe headache at time of SAH              Dizziness                   Other             SAH (Y/N) N Y Y - - N      Age (years), Location  41 53, R. MCA       56 56, R. Pcom    Treatment (Y/N)    N  Y - - Y      Age (years), Location                  Surgical clipping    41 56, R. Pcom     36, R. MCA      56            (recurred)            Endovascular coiling    - 53, R. MCA             53, R. Pcom            Other             Hypertension (Y/N) Y - controlled by medication Y - controlled by medication Y - controlled by medication N Y - controlled by medication Y - controlled by medication Smoking (Y/N) N Y - - - Y Additional Phenotype(s) Epilepsy - - - - Epilepsy Affected family members are indicated by bold text. Information was not collected, or not applicable, for fields marked by a dash. IBA: Intracranial berry aneurysm; R. MCA: Right middle communicating artery; R. Pcom: Right posterior communicating artery; SAH: Subarachnoid hemorrhage    69 3.6.2 Exome Sequencing WES of the proband, II-5, filtered following the methods in Chapter 2, produced 770 rare heterozygous variants. The proband screened positive for a rare variant, c.2056C>T (MAF = 0.0 in people of European ancestry), in thrombospondin type 1 domain containing protein 1 (THSD1) (Table 3.12). This variant is predicted to lead to the protein change p.R686W in the canonical transcript, and p.R633W in the alternate transcript. Sanger sequencing confirmed the variant in the proband, but it was not found to segregate with disease in the remaining family members (Appendix G). Interestingly, the affected mother (I-2) was not found to carry the p.R686W mutation in blood, suggesting that the variant was transmitted on the paternal allele. The affected sister (II-1) and both unaffected siblings (II-3 and II-4) also carried p.R686W.  While lack of segregation eliminates p.R686W as the single mutation leading to Family 5’s Mendelian presentation of FIA, the possibility that it could be a significant risk allele for aneurysm formation cannot be eliminated.  Notably, II-5 was also found to have a rare, non-synonymous variant in polycystin 1 (PKD1), predicted to cause the amino acid change p.C508F (Table 3.12 Candidate variants in Family 5). Although it is unlikely that a pathogenic variant in PKD1 would lead to late onset aneurysm formation with no clinical kidney phenotype, p.C508F was tested for segregation within Family 5. It was not found to cosegregate with FIA (Appendix H). Although loss of function variants are relatively rare in relation to the size of PKD1, ~97% of the missense variants in PKD1 on ExAC have a MAF less than 0.01. To our knowledge there is no functional relationship between PKD1 and THSD1. Neither the PKD1 variant nor the THSD1 variant has enough genetic evidence to be considered the single genetic cause of IBA in Family 5. At time of writing exome sequencing on  70 DNA from I-2, II-1, and II-2 are being completed. A candidate list of genes for this family will be made once data from these exomes are available.    71  Table 3.12 Candidate variants in Family 5 Chr:Pos Ref/Alt Allele Zygosity MAF Gene Names Protein Change OMIM Disease Association CADD Score 16:2158482 C/A het 0 PKD1 p.C508F Autosomal Dominant Polycystic Kidney Disease 26.5 13:52952049 G/A het 0 THSD1 p.R686W Intracranial Aneurysms 15.3 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, het: heterozygous, MAF: minor allele frequency (for European ancestry), OMIM: Online Mendelian Inheritance in Man, Ref: reference.            72 3.7 Comparative Analysis of Families Following the analysis strategy outlined in Chapter 2, rare, potentially pathogenic variants identified through next-generation sequencing in one affected family member from each of Families 1- 5 were overlapped. The affected individuals being compared range in age from 12 years to 68 years at diagnosis, and their aneurysms vary in size and location (Table 3.13). Genes that had rare variants in three or more families were selected for manual annotation and literature search. A total of 38 variants affecting four genes were found to overlap across any four out of five families. None of these four genes present as strong candidates. When we lowered the threshold to variants that overlapped across any three out of our five families, 116 variants overlapped in 32 genes. Of these 32 candidates, three genes, ASTN2, HSPG2, and ITGB4 all have been annotated to have a disease association and/or a function relevant to the development or maintenance of vasculature. Thus, these were selected as the top candidates from this list of 32 genes.       73 Table 3.13 Phenotype of affected individuals sequenced from Families 1 - 5 Family 1 2 3 4 5 Family Member III-5 II-1 II-2 II-6 II-5 Affected (Y/N) Y Y Y Y Y Sex (M/F) M M M F M Age (years) 61 55 12 71 41 At diagnosis or screening 53 40 12 68 35 Number of IBA 2 3 4 3 1 Location and size of IBA    unknown L. MCA   Acom (4 mm) L. MCA (4 mm) R. MCA (6 mm)     R. MCA   R. MCA (3 mm)       L. Pcom   L. ICA (2.5 cm)   Symptomatic (Y/N) N N N Y N      Headache               Dizziness        Y        Other           SAH (Y/N) N Y Y Y N      Age (years), Location   40, L. MCA  12, Acom 68, L. ICA       47, L. Pcom       Treatment (Y/N)    Y  Y Y Y Y      Age (years), Location 53, unknown     70, R. MCA 36, R. MCA      Surgical clipping   40, L. MCA    Acom (4 mm) 68, L. MCA        Endovascular coiling   47, L. Pcom   68, L. ICA       Other           Hypertension (Y/N) Y - post-treatment, controlled by medication N N - Y - controlled by medication Smoking (Y/N) - - N N Y Additional Phenotype(s) - Long-QT Syndrome N N Epilepsy Information was not collected for fields marked by a dash. Acom: Anterior communicating artery; IBA: Intracranial berry aneurysm; L. ICA: Left interior carotid artery; L. MCA: Left middle communicating artery;  R. MCA: Right middle communicating artery; R. Pcom: Right posterior communicating artery; SAH: Subarachnoid hemorrhage   74 3.7.1 Candidate Genes with Rare Variants in Four Families  In four out of the five families presented in this thesis, 38 variants overlapped in four genes: DST, TTN, DNAH1, and CRIPAK. As only a limited number of genes fell into this analysis category, and all have been included in this thesis despite being relatively poor candidates functionally. Dystonin (DST) contains rare variants in Families 2, 3, 4 and 5 (Table 3.14). DST codes for the protein, bullous pemphigoid antigen 1 (BPAG1), a component of the cytoskeleton in epithelial cells. Homozygous mutations in DST cause epidermolysis bullosa simplex, a condition characterized by skin blistering.197    Titin (TTN) contains rare variants in Families 1, 2, 4, and 5 (Table 3.15). Titin is a sarcomere protein found in cardiac, skeletal, and smooth muscle. In humans it is associated with myopathies, cardiomyopathies, and muscular dystrophies.170,198-200 TTN is an extremely large gene containing 363 exons.201 Due to its size the mutational target space of TTN is huge and is statistically more likely than other genes to contain a rare variant.   Dynein Axonemal Heavy Chain 1 (DNAH1) contains rare variants in Families 1, 2, 4, and 5 (Table 3.16). DNAH1 is a ciliary protein that is critical for the function of sperm flagellum. Homozygous mutations in DNAH1 lead to impaired sperm motility and male infertility.202  Cysteine rich PAK1 inhibitor (CRIPAK) contains rare variants in Families 2, 3, 4, and 5 (Table 3.17). CRIPAK is expressed in many tissue types, where it negatively regulates PAK1. Knock-down of CRIPAK by small interfering RNA in a breast cancer cell line led to increased cytoskeletal remodeling though the increased activity of PAK1.203 CRIPAK has not been implicated in any disease at this time.    75 Table 3.14 Variants in DST Family Chr:Pos Ref/Alt MAF Zygosity Protein Change CADD Score 2 6:56481627 T/C 0.00004989 het p.R20565H 14.57 3 6:56485496 C/G 0.005227 het p.E1112D 18.15   6:56569113 T/C 0.002996 het p.I248V 18.54 4 6:56485243 G/A 0.00008246 het p.R1197C 20.8 5 6:56481130 C/T 0.001898 het p.A2379T 11.21 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, MAF: minor allele frequency.  Table 3.15 Variants in TTN Family Chr:Pos Ref/Alt MAF Zygosity Protein Change CADD Score 1 2:179449204 T/C 0.0004544 het p.I12819V 14.67   2:179542447 C/A 0 het p.V10154F 21.3   2:179658136 C/A 0 het p.E511* 37 2 2:179419672 C/T 0.00004989 het p.R20565H 23.4 4 2:179544347 T/C 0.000008845 het K9971E 20.2   2:179410271 G/T 0.00000828 het R29288S 23.2 5 2:179612315 T/C 0.0009906 het p.M252V 11.87 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, MAF: minor allele frequency. Table 3.16 Variants in DNAH1 Family Chr:Pos Ref/Alt MAF Zygosity Protein Change CADD Score 1 3:52392645 C/A 0 het p.F1386L 18.99 2 3:52397098 A/T 0.002393 het p.S1728C 25.6   3:52379582 C/T 0.0002741 het p.R506W 33   3:52396410 C/T 0.00675 het p.R1663C 34 4 3:52398865 G/T 0.00002499 het p.R1783L 26.7   3:52356727 C/T 0.0002329 het p.P90L 32 5 3:52378570 A/G 0.0015 het p.K451E 20.4 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, het: heterozygous; MAF: minor allele frequency.    76 Table 3.17 Variants in CRIPAK Family Chr:Pos Ref/Alt MAF Zygosity Protein Change CADD Score 2 4:1388867 A/C 0.007825 het p.I190L 0.063 3 4:1388786 G/C 0.00003212 het p.R146P 0.001   4:1388976 C/T 0.001073 het p.A226V 0.611 4 4:1388886 A/G - het E196G 11.06   4:1388769 G/A 0.0001821 het R157H 16.76 5 4:1388852 T/C 0.00004991 het W185R 0.437 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, het: heterozygous; MAF: minor allele frequency.   77 3.7.2 Candidate Genes with Rare Variants in Three Families  In three out of the five families 116 variants overlapped in 32 genes. These candidates were further filtered down by gene function or previous association to FIA to three top candidate genes, ASTN2, HSPG2, and ITGB4. Astrotactin 2 (ASTN2) contains rare variants in Families 1, 2, and 4 (Table 3.18). Polymorphisms in ASTN2 have been associated with risk for a number of conditions, including attention deficit hyperactivity disorder (ADHD) and Alzheimer’s disease.204,205 Functionally, ASTN2 is thought have a role in glial-guided neuronal migration by forming a complex with and regulating ASTN1, a known ligand in this process. A heterozygous variant in ASTN2 that causes the protein change p.T1083I (MAF = 0.024 in Japanese populations) was previously found to segregate fully in one consanguineous Japanese family, and partially with three additional Japanese families affected by FIA.103 Family 2 carries this same mutation. However, this variant appears to be a polymorphism in the Japanese population, and may be present in Family 2 due to ancestral founder effects. Genome data on First Nations individuals at a population level would be needed to calculate the true MAF of p.T1083I in Family 2, in which a CCM2 variant was also identified.   Integrin beta 4 (ITGB4) contains rare variants in Families 1, 4, and 5 (Table 3.19). Integrins are transmembrane proteins that maintain cell-cell, or cell-cytoskeleton, adhesion, as well as propagate signals received from inside or outside the cell. Beta 4 (β4) is known to adhere the basement membrane to the cytoskeleton in endothelial cells of adult vasculature. During angiogenesis β4 is negatively regulated. However, an overexpression of β4 is able to initiate migration of nearby β4-negative endothelial cells during angiogenesis.206,207 Knock-out of ITGB4 in mice leads to death shortly after birth due to epithelial defects.208 Induction of cerebral  78 aneurysm by surgically increasing hemodynamic stress in rats led to the upregulation of 15 genes, including Itgb4, over a three month period of time.209 Heparan sulfate proteoglycan 2 (HSPG2) contains rare variants in Families 1, 2, and 4 (Table 3.20). HSPG2 has been implicated in FIA through familial mapping studies and a previous candidate gene association study. Linkage analysis of a large Dutch pedigree and large European pedigree both mapped an FIA susceptibility locus to the chromosomal region 1p36.13-p34.3. Analysis of 44 candidate genes in 328 Dutch individuals with intracranial aneurysms associated SNPs found in HSPG2. This was replicated in another Dutch cohort of 310 individuals.210 HPSG2 encodes the protein perlecan, which is an extracellular matrix component in many mesenchymal tissue types, including vascular tissue.211,212  Hspg2 whole gene knock-out mice are usually embryonic lethal due to cartilage and/or cranial abnormalities (e.g. exencephaly) or die shortly after birth from respiratory failure.213 Gustafsson et al. found that about 40% of embryonic mice with Hspg2 knock-out had dilated microvasculature that had hemorrhaged in the brain and skin by embryonic day 12.5.214 Perlecan has both heperan sulfate and glycosaminoglycan side chains. In vitro the glycosaminoglycan side chain inhibited VSMC binding to the perlecan core, while the heparan sulfate side chains were able to bind FGF1 and FGF2 and propagate FGF2 signaling. In endothelial cells, adhesion to perlecan was not affected by the presence of glycosaminoglycan side chain, and the heparan sulfate side chains bound and promoted signalling of both FGF1 and FGF2.215 Mice with deficiency of the heparin sulfate side chain (homozygous deletion of exon 3 in Hspg2) survived through embryonic development and appeared healthy. However, upon skin puncture, 6-week-old mice showed delayed wound healing. The basement membrane of the vasculature was not affected, but FGF-2 mediated angiogenesis was impaired.216 Zebrafish with perlecan knock- 79 down via translation-blocking morpholinos displayed decreased extension of vessel sprouts from the dorsal aorta into the tail and trunk. In humans, homozygous or compound heterozygous mutations in HSPG2 cause Schwartz-Jampel syndrome, an autosomal recessive condition characterized by osteochondrodysplasia, myotonia, and dysmorphic facial features.217  HSPG2 and ITGB4 are interesting candidate genes based on gene function and animal models, while ASTN2 has not yet been associated with vascular development or function. Based on both gene function and previous association to FIA, HSPG2 has the strongest evidence for causality supporting it – however further work is required before it can my labeled as causative. The specific mutations seen in our family will need to be tested with an animal model (such as CRISPR/Cas9 knock-in in a zebrafish model) to determine their in vivo effect.   80  Table 3.18 Variants in ASTN2 Family Chr:Pos Ref/Alt MAF Zygosity Protein Change CADD Score 1 9:119495803 C/A 0.0 het Exon 12 +1 26.8 2 9:119249734 G/A 0.002238 het p.T1083I 24.8 4 9:120177201 C/A 0.0 het p.A6S 23 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, het: heterozygous, MAF:  minor allele frequency.   Table 3.19 Variants in ITGB4 Family Chr:Pos Ref/Alt MAF Zygosity Protein Change CADD Score 1 17:73736078 G/A 0.00006211 het p.R791H 33 4 17:73733712 G/T 0.006933 het p.C736F 29.7 5 17:73728022 G/A 0.001166 het p.G365S 3.574 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, het: heterozygous, MAF:  minor allele frequency.   Table 3.20 Variants in HSPG2 Family Chr:Pos Ref/Alt MAF Zygosity Protein Change CADD Score 1 1:22178643 C/T 0.0005131 het p.G2270R 33 2 1:22222455 G/T 0.001927 het p.D34E 8.884 4 1:22186149 T/C 0.000008351 het p.S1735G 21.2 Alt: Alternate, CADD: combined annotation dependent depletion; Chr:Pos: chromosome:position, het: heterozygous, MAF:  minor allele frequency.    81 Chapter 4: Discussion 4.1 Summary of Findings The thesis describes our initial findings from an ongoing research project. In Chapter 3: we presented the results of our genetic investigations into the underlying cause of FIA in five families, using various combinations of next-generation sequencing, whole-genome SNP microarray, and Sanger sequencing techniques. We presented data on both family-specific candidate genes and candidate genes selected through overlap of sequence variants between families. Our findings are summarized in Table 4.1.  At this time, our study was not able to find sufficient evidence to associate a specific gene as the single cause of FIA in any one family or in a subset of families. The lack of conclusive associations within our cohort, as well as the lack of conclusive phenotypic associations from previous familial exome sequencing studies, coupled with the most recent finding that the first gene associated with FIA, THSD1, is estimated to account for approximately 1% of all intracranial aneurysm cases, indicates that familial intracranial aneurysms is a genetically heterogeneous condition.  Comparison with the genetic architecture of other known aneurysm phenotypes can be can provide parallel information. Pathogenic mutations in ACTA2 account for 15% of cases of familial thoracic and aortic aneurysms/dissections (FTAAD).218 Theoretically, if coding mutations in a specific gene accounted for a similar proportion of FIA cases, then studies like the FIA Study (with over 300 families), should have identified such a gene. Thus, it is likely that mutations in many different genes can lead to FIA, and that each gene accounts for only a small percentage of cases.   82 Notably, the rare variants presented in our study have varying CADD scores. CADD is an algorithm for SNVs and indels that combines multiple annotation tools to compare simulated variants to “fixed” or real variants at every base in the genome. Some of the algorithms combined in CADD include genomic annotation from the UCSC Genome Browser, conservation scores from GERP, and predicted effect on protein function by SIFT and Polyphen. The CADD scores reported in this thesis are scaled in comparison to all other possible SNVs in the genome. Variants with a CADD score higher than 10 are within the top 10% of variants unlikely to be seen in the human genome, whereas variants with a CADD score greater than 20 are in the top 1% of variants unlikely to be seen in humans. Most known pathogenic variants annotated to disease have a scaled CADD score between 30 and 40.219 For this reason, candidate variants in our study with a CADD score greater than 20 have been ranked more highly as potentially pathogenic, compared to variants with lower CADD scores. Moving forward, candidate genes that have rare variants with scaled CADD scores greater than 20 in multiple families will be prioritized for animal studies over candidate genes with variants that have lower CADD scores.  Table 4.1 Summary of Candidate Genes in Families 1 - 5   At the cellular level, we hypothesize that intracranial berry aneurysms form through “two-hit kinetics.” This process requires two pathogenic mutations to arise in the same gene (or pathway of genes) within the same cell in order for disease to manifest. My idea is based on the two-hit hypothesis of cancer initiation first put forward by Knudson in 1971.220 Since that time Family 1 2 3 4 5Family Specfic Candidate GenesNOTCH4, CFB,    PIK3C2G, HLA-DRB1, DDR1 CCM2CA5A, C2orf16, VPS18, AHCTF1, FAM198B, RPF2, ARFGEF1  - THSD1, PKD1Overlap Analysis Candidate GenesTTN, DNAH1, ASTN2,       ITGB4, HSPG2TTN, DNAH1, CRIPAK, DST,  ASTN2, HSPG2DST, CRIPAKTTN, DNAH1, CRIPAK, DST, ASTN2, ITGB4, HSPG2TTN, DNAH1, CRIPAK, DST, ITGB4 83 numerous other diseases have been found to have a two hit-mechanism, including the renal cyst and intracranial aneurysm formation in patients with ADPKD.221,222 At a population level, individuals would acquire these “hits” throughout their lifetime; phenotypically, their IBA would appear sporadic, developing only from cells with two “hits.” Since the majority of FIA pedigrees show a dominant inheritance of disease, I suggest that affected FIA family members inherit the first “hit” as a Mendelian allele and acquire the second “hit” as a somatic mutation during their lifetime. As is seen in familial cancer syndromes, such as familial retinoblastoma,223,224 the predisposing inherited “hit” significantly increases the chances of obtaining two “hits,” leading to high penetrance in these families, acting recessively at the cellular level while appearing dominant at the phenotypic level. This model also explains why familial cases would present at a younger age and with more severe disease compared to patients with sporadic IBA (as discussed in Section 1.3).  4.2 Strengths Our inclusion of cases with only non-syndromic FIA or IBA has enriched our cohort for patients more likely to have a strong genetic contribution to their aneurysm formation. The exome sequencing, and exome sequencing plus microarray, strategies outlined in Chapter 2: are well-validated methods for identifying genetic associations with disease, and have been used by large consortia such as FORGE Canada.171 We identified strong family-specific candidate variants as well as strong candidate genes from our overlap analysis. Though intuitively appealing, it is difficult to disentangle our own assessment of candidacy from the intrinsic “narrative potential of the human genome,” whereby a plausible argument can be made for the involvement of almost any gene in any process, particularly one as complex as vasculogenesis.  84 Nevertheless, the single successful study to date used an approach similar to ours in a much larger group of patients, demonstrating proof-of-principle to our overall approach.  4.3 Limitations A significant limitation to this research is the number and size of families enrolled in our cohort. Linkage mapping in Family 1 produced numerous candidate chromosomal regions, which could have been reduced in number if clinical information and a DNA sample were available on an affected member distantly related to the nuclear family. Our linkage analysis also depended on the assumption that family members who were not diagnosed by brain imaging are truly unaffected, and that they will not develop an intracranial aneurysm later in life. The two youngest unaffected individuals were screened at 48 years and 50 years old, both earlier than the youngest diagnosis of FIA in their family, raising the possibility that the assumptions on which our mapping data are based may be inaccurate.  Using Sanger sequencing to test for variant segregation within a family also relies on family members being diagnosed correctly as affected or unaffected. This problem has been noted in studies of familial forms of other common, complex and late-onset diseases such as Parkinson’s disease. When genes or variants have an age-dependent penetrance, they may be discarded from the analysis prematurely due to phenotypic misclassification.225  Our research also had some intrinsic technical limitations, because exome sequencing is unable to detect large CNVs, epigenetic variation, or non-coding variation such as deep intronic variants that might be important in disease.226 Notably, the most up-to-date build of the human genome (GRCh38.p7) recognizes 20,441 coding genes and  22,219 noncoding genes, suggesting  85 that the “mutational target space” of RNA-only genes may exceed that of protein-coding genes, at least with respect to the number of targets.227,228  4.4 Future Research Directions 4.4.1 Cohort Recruitment and Sequencing  Based on my finding that FIA is likely extremely heterogeneous, further enrollment of additional FIA families will be critical to identify the gene(s) that are pathogenic for FIA and IBA when mutated with a disease-causing variant. Next-generation sequencing of the proband from each new family to compare with the sequencing data of probands from the other families in the cohort should continue. This strategy allows for the most cost-effective accumulation of genetic information on FIA; coupled with Sanger sequencing, it would still allow for variant segregation to be tested within families. In families containing more distant affected relatives separated by multiple meioses, exome sequencing with rare variant comparisons between distantly-related affected relatives can be a powerful method to filter the number of shared candidate variants.    4.4.2 Animal Models In addition to preliminary functional work in human and yeast cell lines, evidence from one (or more) animal models is generally considered essential to assess the impact of candidate variants in vivo. Though worms (C. elegans) and flies (D. melanogaster) offer powerful methods of screening for genetic function, the fact that their circulatory systems are not easily comparable to that of humans renders them less valuable in the context of this phenotype. However, the circulatory systems of fish and rodents share significant similarities to human circulatory  86 systems, such that these two model organisms are used frequently for functional validation of genes implicated in vascular biology.  4.4.2.1 Zebrafish Zebrafish are often used to study cardiovascular and cerebrovascular conditions. Zebrafish embryos are transparent during development, so the embryonic vasculature can be viewed both easily and directly.229 Zebrafish models of aortic aneurysm genes have clearly displayed hemorrhage of malformed blood vessels.230,231 As well, 82% of human disease genes have a zebrafish orthologue, indicating that we are likely to be able to interrogate our candidate genes using this model.232 Using morpholino oligonucleotides (MO) specific to the transcript of the fish orthologue, we could knock-down the function of our candidate gene through complementary binding of the MO to the transcript. This knock-down experiment allows us to model the effects of a non-functional gene. To validate whether the transcripts containing the variants found in our FIA families are sufficient to carry out the function, we could proceed to rescue experiments. In such an experiment, co-injection of the wild-type transcript should restore a normal phenotype to the MO-bearing zebrafish, whereas transcripts containing a damaging variant would not rescue the fish phenotype.223   4.4.2.2 Mice Intracranial aneurysms do not develop in mice naturally, and must be induced surgically or by a combination treatment of elastase and induced hypertension.209,233 Despite this, knock-out of many of the candidate genes discussed in Chapter 3 does disrupt vascular function in mice. It is possible that because mice do not develop intracranial aneurysms without intervention, even  87 knock-out of true aneurysm-causing genes in mice might not recapitulate the human phenotype exactly (as was seen with THSD1, where the mice developed spontaneous SAH but did not have detectable aneurysms). Additionally, many candidate genes cause embryonic lethality in mice when knocked-out constitutively, so mouse validation may require studies of embryonic vasculature, or of an endothelial-specific knock-out model. As intracranial aneurysms are usually a late-onset condition, an inducible knock-out model that removed the candidate gene after development might allow visualization of this vascular phenotype without causing embryonic lethality. This could be accomplished with a tamoxifen-dependent Cre-loxp system.225    4.4.3 Functional Experiments Candidate genes that meet our threshold for sufficient genetic evidence for association with intracranial aneurysms may have little, or no, supporting functional evidence at the time they are found (as was the case with THSD1). In such a situation, it would be practical to proceed with screening of a human vascular cell line (such as a human umbilical venous endothelial cells, HUVECs) for expression of the candidate transcript (and possibly for absence of the mutant transcript) prior to animal modeling. Co-immunoprecipitation assays could then be used to identify binding partners of the candidate protein, if none were already known. To test the effect of the variants seen in the families in our cohort, a relatively simple assay, such as the yeast-two hybrid assay could be used to test protein-protein binding. A benefit of using this assay is that cDNA of human wildtype and mutant transcripts and of the known binding partners can be cloned easily into yeast, allowing protein interactions to be modeled. These experiments would help characterize the role of the candidate protein in vasculature.    88 4.5 Significance of the Research Knowing the frequency and relative penetrance of variants causing or contributing to the formation of IBA in families is important for understanding the pathophysiology of this disease. While the recent discovery of THSD1 provides some insight into these questions, more gene discoveries will be necessary to describe the genetic architecture of FIA. Solving the genetic cause of aneurysms in rare families like these will identify key proteins that are necessary for healthy brain arteries in the general population. Such knowledge will also improve patient screening methods, and aid in the development of novel therapeutics.   4.5.1 Screening Families A successful outcome of this project would be identifying a genetic cause for FIA. This information could benefit families both clinically and psychologically. As screening of families is not recommended until at least two members are confirmed to have intracranial aneurysms and most IBA are asymptomatic, diagnosis of FIA often begins with two or more family members experiencing SAH. This traumatic experience is often accompanied by worry and stress that remaining family members have inherited the predisposing risk factor (pers. comm. from study families). As has been seen when ending the “diagnostic odyssey” of patients with rare genetic diseases, diagnosing families genetically as well as clinically may lessen the stress of having a familial disease.234  Many affected participants in this study have one or more children who are at increased risk for FIA. As mentioned in the Introduction (Section 1.3), relatives of people affected by SAH are more likely to develop an FIA, more likely to rupture, and more likely to have a poor outcome, when compared to sporadic cases of IBA. Therefore, at-risk relatives from families  89 who carry pathogenic variants in FIA-associated genes could receive genetic testing to determine whether or not they are predisposed genetically to intracranial aneurysm formation. For families in whom the onset of FIA is in adulthood, genetic testing could be done at the age of majority, at the discretion of the family member undergoing testing. Family members positive for the pathogenic rare variant could then seek early screening, and family members negative for the pathogenic rare variant would no longer need to worry about having a genetic predisposition for IBA. Family members who were already diagnosed would have a confirmed genetic diagnosis, and would be able to discuss with their physician the option of early intervention to have their aneurysms treated with clipping or endovascular coiling at a smaller size than would otherwise be recommended, potentially reducing morbidity and mortality.   4.5.2 Screening Unrelated Families and Sporadic Cases With a specific gene in hand, other at-risk individuals and families could be tested to discover if their aneurysms were caused by variants in the same gene. Eligible groups would include other families with FIA, people who have more than one IBA, people who have only one other affected family member, and children and adolescents who have early onset-IBA. All of these situations would translate findings from this project usefully outside of the original discovery cohort.   4.5.3 Treatment A long-term outcome of this project would be the development of a new treatment for FIA/IBA. There are no pharmaceuticals specifically being used to prevent IBA. Having a proven causative gene would unlock new ways to investigate the pathogenesis of IBA, enabling  90 development of new therapies by pharmaceutical companies. Notably, many pharmaceutical targets have been chosen via rare versions of common disease that highlight key components of disease pathogenesis.235-237 Examples include statins that target LDLR (for heart disease and stroke),238  and sulfonylureas that target KCNJ11/ABCC8 (for diabetes).239 In these cases, the drugs are being prescribed or developed for use in the general population with common disease, not only for use in the subpopulation with rare mutations. Similarly, we expect that therapeutics developed from our future findings would not only aim to treat families with FIA, but also the 3% of the general population diagnosed with IBA.    91 Bibliography 1. Park, S.-H., Yim, M.-B., Lee, C.-Y., Kim, E. & Son, E.-I. 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Nature Genetics 8, 201–211 (2012).   117 Appendices Appendix A Phenotype Collection Form   118    119    120 Appendix B Primer sequences used in qPCR validation of the CNV disrupting DMBT1. Primer Sequence Tm (°C) 5' Region Forward CTGGTTATCTGGTGGCTCTGG 57.4 5' Region Reverse CAAACCAATGTTGCGGCACT 57.4 Deleted Region Forward AGCTGGCAGTAGTGGACAAGA 58.2 Deleted Region Reverse GCCTTCAGTCCACCCTATGTC 57.0 H6PD Forward GGTGGATAGATGCAGAAACAAGGA 56.8 H6PD Reverse TATGAATGTGTAACTGCTGGAGGTCTT 57.7 Tm: Predicted melting temperature.    121 Appendix C Primer sequences used in PCR validation of candidate variants in Family 1. Primer Sequence Tm (°C) RYR1 Forward GTAGTGTCCATGTGGGCAGATTC 57.6 RYR1 Reverse CCAGCCCTAACCCTTGATATTGATA 56.1 BSN Forward CCCACAGCCGGGTACGAC 61.0 BSN Reverse ATCACCCCTGGCTGCCATTA 59.0 VAT1 Forward CTACCCCCTCCCATATTATGCC 56.7 VAT1 Reverse CCCCTGCTTATGGGTGTCTTG 57.9 SLC7A9_1 Forward GTGCTGACACCTGCCTTACC 58.4 SLC7A9_1 Reverse GAGGGCGTCCATCTTCCG 58.2 SLC7A9_2 Forward CAGTGGAAGGGCGTTTGGT 58.2 SLC7A9_2 Reverse CTCCAGGGCTTTGCTGAAAAC 56.8 HSPB6 Forward GGCAATGGAAGTGGTCGAGT 57.6 HSPB6 Reverse AGGAGCAGGATGGAGATCCC 58.5 ARHGAP33 Forward TCATTGCCCTGCCAGAACC 58.1 ARHGAP33 Reverse GATCGTGGTGGGCAGTAGC 58.3 FRY Forward GCCCCCATTACAGGGACTTT 57.4 FRY Reverse TGCTCAAGTTGAGAGCACCTTAG 56.8 Tm: Predicted melting temperature.    122 Appendix D Primer sequences used in PCR validation of candidate variants in Family 2. Primer Sequence Tm (°C) CCM2 Forward CTGGGTGCTGCCTGCTTTTTAAAC 59.3 CCM2 Reverse CTATACTCCCCACCTGGGTGGAA 59.9 Tm: Predicted melting temperature.    123 Appendix E Primer sequences used in PCR validation of candidate THSD1 variant Primer Sequence Tm (°C) THSD1 Forward CCCAAGGTCTGGTTTCCTCAA 63.5 THSD1 Reverse GAGTTTCCATGAAGCCAGGCA 64.7 Tm: Predicted melting temperature.    124 Appendix F Primer sequences used in PCR validation of candidate PKD1 variant Primer Sequence Tm (°C) PKD1 Forward CAGGTACACATGCTCCACTGTT  PKD1 Reverse GCTGCCAACCACACCTATG      125 I II 1 2 1 2 3 4 5 P (-) p.R686W (+)  p.R686W (+)  p.R686W (+)  p.R686W (+)  p.R686W (-) p.R686W Appendix G Sanger sequencing traces of THSD1 variant in Family 5           I-2: THDS1 (+)      I-2: THSD1 (-)         II-1: THSD1 (+)         II-1: THSD1 (-)         126 II-2: THSD1 (+)         II-2: THSD1 (-)       II-3: THSD1 (+)         II-3: THSD1 (-)        II-4: THSD1 (+)         II-4: THSD1 (-)      II-5: THSD1 (+)         II-5: THSD1 (-)         127 I II 1 2 1 2 3 4 5 P (-) p.C508F  (+) p.C508F  (+) p.C508F  (+) p.C508F  (-) p.C508F  (-) p.C508F  Appendix H Sanger sequencing traces of PKD1 variant in Family 5           I-2: PKD1 (+)      I-2: PKD1 (-)    (Not Available)    II-1: PKD1 (+)         II-1: PKD1 (-)          128 II-2: PKD1 (+)         II-2: PKD1 (-)       II-3: PKD1 (+)         II-3: PKD1 (-)        II-4: PKD1 (+)         II-4: PKD1 (-)      II-5: PKD1 (+)         II-5: PKD1 (-)  

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