Science, Faculty of
Microbiology and Immunology, Department of
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UBCV
Mann, Simranpreet Kaur
Master of Science - MSc
University of British Columbia
Chronic primary systemic vasculitis (PSV) describes a group of rare and potentially life-threatening disorders characterized by the inflammation and necrosis of blood vessels in one or more vital organs. In children, PSV typically affects small blood vessels, with anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) being the most common form. Compared to adult-onset AAV, AAV in children is more likely to be severe at outset and present with multi-organ involvement. Furthermore, more than 80% of children exhibit kidney involvement at initial presentation, and approximately one-third develop permanent kidney damage within the first year. Due to the rarity of childhood-onset AAV, most knowledge of the disease is obtained by studying adult-onset AAV. In adults with AAV, certain autoantibodies and urine proteins have been identified as biomarkers of risk for severe disease, kidney involvement, and relapse, and are now used to guide treatment decisions. The intent of this thesis is to assess the utility of these adult-derived tools in childhood-onset vasculitis. Using the single largest repository of retrospective data and biosamples from children with vasculitis stored at the University of British Columbia and the BC Childrenâs Hospital Research Institute, this thesis reports, as primary findings, a higher likelihood of presenting with kidney involvement for children who are seropositive for ANCA directed towards myeloperoxidase (MPO) compared to those with ANCA towards proteinase-3 (PR3) and those without ANCA against either autoantigen, while neither ANCA seropositivity nor specificity were informative of the risk of relapse. Additionally, none of the three urine proteins (usCD163, usCD25, uMCP-1) identified as markers of kidney disease activity in adult-onset AAV exhibited a similar utility in the pediatric population. The findings from this thesis research identify potential differences in the utility of adult-derived biomarkers between childhood- and adult-onset AAV, and, in doing so, emphasize the importance of validating these tools in children prior to their use in clinical care for this population. Furthermore, these findings highlight a need to identify novel, pediatric-specific biomarkers for the detection and monitoring of overall and kidney-specific disease in children with AAV.
EVALUATING THE UTILITY OF ADULT-DEFINED BIOMARKERS IN CHILDHOOD-ONSET CHRONIC PRIMARY SYSTEMIC VASCULITIS by Simranpreet Kaur Mann B.Sc., Integrated Sciences, University of British Columbia, 2022 A THESIS SUBMITTED IN PARTIAL FULFILLMENT OF THE REQUIREMENTS FOR THE DEGREE OF MASTER OF SCIENCE in THE FACULTY OF GRADUATE AND POSTDOCTORAL STUDIES (Microbiology and Immunology) THE UNIVERSITY OF BRITISH COLUMBIA (Vancouver) July 2024 © Simranpreet Kaur Mann, 2024 ii The following individuals certify that they have read, and recommend to the Faculty of Graduate and Postdoctoral Studies for acceptance, the thesis entitled: Evaluating the utility of adult-defined biomarkers in childhood-onset chronic primary systemic vasculitis submitted by Simranpreet Kaur Mann in partial fulfilment of the requirements for the degree of Master of Science in Microbiology and Immunology Examining Committee: Dr. Kelly Brown, Associate Professor, Dept. of Pediatrics, Division of Rheumatology, UBC Supervisor Dr. Donald Sin, Professor, Faculty of Medicine, Division of Respiratory Medicine, UBC Supervisory Committee Member Dr. Maria Tokuyama, Assistant Professor, Dept. of Microbiology and Immunology, UBC Additional Examiner Additional Supervisory Committee Members: Dr. Stuart Turvey, Professor, Faculty of Medicine, Dept. of Pediatrics, UBC Supervisory Committee Member iii Abstract Chronic primary systemic vasculitis (PSV) describes a group of rare and potentially life-threatening disorders characterized by the inflammation and necrosis of blood vessels in one or more vital organs. In children, PSV typically affects small blood vessels, with anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) being the most common form. Compared to adult-onset AAV, AAV in children is more likely to be severe at outset and present with multi-organ involvement. Furthermore, more than 80% of children exhibit kidney involvement at initial presentation, and approximately one-third develop permanent kidney damage within the first year. Due to the rarity of childhood-onset AAV, most knowledge of the disease is obtained by studying adult-onset AAV. In adults with AAV, certain autoantibodies and urine proteins have been identified as biomarkers of risk for severe disease, kidney involvement, and relapse, and are now used to guide treatment decisions. The intent of this thesis is to assess the utility of these adult-derived tools in childhood-onset vasculitis. Using the single largest repository of retrospective data and biosamples from children with vasculitis stored at the University of British Columbia and the BC Childrenâs Hospital Research Institute, this thesis reports, as primary findings, a higher likelihood of presenting with kidney involvement for children who are seropositive for ANCA directed towards myeloperoxidase (MPO) compared to those with ANCA towards proteinase-3 (PR3) and those without ANCA against either autoantigen, while neither ANCA seropositivity nor specificity were informative of the risk of relapse. Additionally, none of the three urine proteins (usCD163, usCD25, uMCP-1) identified as markers of kidney disease activity in adult-onset AAV exhibited a similar utility in the pediatric population. iv The findings from this thesis research identify potential differences in the utility of adult-derived biomarkers between childhood- and adult-onset AAV, and, in doing so, emphasize the importance of validating these tools in children prior to their use in clinical care for this population. Furthermore, these findings highlight a need to identify novel, pediatric-specific biomarkers for the detection and monitoring of overall and kidney-specific disease in children with AAV. v Lay Summary Vasculitis refers to a group of rare diseases that cause damage to blood vessels in major organs of the body, usually the kidneys in children, and can be fatal. Although newer treatments have been lifesaving, giving these drugs at higher doses or over a long time should be reserved for patients at a higher risk of having generally persistent disease and/or particularly severe disease in the kidneys. This study evaluated if markers like antibodies (known as ANCA) and certain urine proteins (called usCD163, usCD25, uMCP-1) that are used to guide care for adults with vasculitis are also helpful for children with vasculitis. The results showed that these markers were not particularly useful for assessing vasculitis in children. Thus, it is clear that tools used for adults need to be studied in children before being used for their care. New markers that are specific for vasculitis in children are also needed. vi Preface This thesis contains both published and unpublished data, described below. The research presented in this thesis was performed at the BC Childrenâs Hospital Research Institute, an affiliated campus of the University of British Columbia, under the supervision of Drs. Kelly L. Brown and Kimberly A. Morishita. The clinical data and biological (urine) samples used for this research were collected through an international initiative on childhood-onset vasculitis led by investigators at UBC and BC Childrenâs Hospital (co-lead principal investigators: Dr. D.A. Cabral, Dr. K.L. Brown and Dr. K.A. Morishita). Clinical data from the time of diagnosis (collected from 2007 onwards) was entered by participating sites into A Registry of Childhood Vasculitis (ARChiVe), hosted on the Research Electronic Data Capture (REDCap) platform. ARChiVe was modified in 2012, through the Pediatric Vasculitis Initiative (PedVas), to also include clinical data from follow-up visits, as well as biological samples. Entered data was reviewed and locked by Dr. D. Cabral, Dr. K. Morishita, Dr. A. Rivera, and Dr. E. Bosman prior to its use in the analyses described in this thesis. Samples from participating study sites were received at BCCH, processed, and stored at the BCCH Biobank and/or in Dr. Brownâs laboratory. Clinical data and biological samples were collected from children and adolescents with chronic primary systemic vasculitis, as well as otherwise healthy adults, in accordance with protocols approved by the Childrenâs and Womenâs Research Ethics Board of the University of British Columbia (H12-00894) and the respective ethical committees or IRBs at the national and international sites participating in ARChiVe/PedVas. vii Chapter 3: The results presented in Chapter 3 have been published as part of a research article (Sections 3.3 - 3.4): S.K. Mann, J.N. Bone, E.S. Bosman, D.A. Cabral, K.A. Morishita, K.L. Brown. Predictive utility of ANCA positivity and antigen specificity in the assessment of kidney disease in paediatric-onset small vessel vasculitis, RMD Open, 2024 Jun;10(2):e004315. An online version of this manuscript can be accessed using the following link: https://doi.org/10.1136/rmdopen-2024-004315 I was responsible for 80% of the work for this manuscript, including extracting (from the ARChiVe/PedVas database) and analyzing data, as well as preparing figures and tables. Dr. E.S. Bosman provided advice and assistance with regards to the ARChiVe/PedVas database in REDCap. J.N. Bone provided support for statistical analyses. Drs. D.A. Cabral, K.A. Morishita, and K.L. Brown oversaw all aspects of the study, and all authors were involved in the conceptualisation of the project. I wrote the manuscript and incorporated feedback from all contributing authors and in response to peer-review. Chapter 4: A subset of the results presented in Chapter 4 (Sections 4.3.1 â 4.3.2, Section 4.4) have been published as part of the research article containing Chapter 3 data (Mann et al RMD Open, 2024). The remaining results from this chapter have been published as an abstract (Mann SK, Vasquez-Rios C, Cabral DA, Morishita KA, Brown KL (2024). Pilot study of urine biomarkers for assessing kidney disease in pediatric-onset anti-neutrophil cytoplasmic antibody-associated vasculitis. Canadian Rheumatology Association (CRA) - Arthritis Health Professions Association (AHPA) Annual Scientific Meeting. Feb 28 â Mar 2, 2024. Winnipeg, Canada. Abstract #82 The viii Journal of Rheumatology 2024, ahead of print) and were presented at the Canadian Rheumatology Association annual scientific conference (2024, Winnipeg, MB). A manuscript is in preparation and will be submitted for publication. With regards to this, I was responsible for literature review, designing and performing all experiments, analyzing data, and preparing figures and tables. Mrs. S. Hughes (Brown Lab technician) provided assistance with urine protein measures (ELISA). Dr. K. L. Brown oversaw all aspects of this study, including experiment design, data analysis, and the interpretation of results. ix Table of Contents Abstract ......................................................................................................................................... iii Lay Summary ................................................................................................................................ v Preface ........................................................................................................................................... vi Table of Contents .......................................................................................................................... ix List of Tables ............................................................................................................................... xiv List of Figures ............................................................................................................................. xvi List of Abbreviations ................................................................................................................. xvii Acknowledgements ..................................................................................................................... xix Dedication ................................................................................................................................... xxi Chapter 1: Introduction ................................................................................................................ 1 1.1 Chronic primary systemic vasculitis (PSV) .......................................................................... 1 1.2 Childhood-onset ANCA-associated vasculitis (AAV) .......................................................... 3 1.2.1 Anti-neutrophil cytoplasmic antibodies (ANCA) .......................................................... 3 1.2.1.1 ANCA positivity and antigen specificity in AAV .................................................... 4 1.2.1.2 Development of ANCA ........................................................................................... 5 1.2.1.3 Detection of ANCA ................................................................................................. 6 1.2.2 Subtypes of AAV ............................................................................................................ 6 1.2.2.1 Clinical classification criteria for AAV subtypes .................................................... 7 1.2.2.2 Clinical features of AAV ......................................................................................... 8 1.2.2.3 Current treatments of AAV .................................................................................... 10 x 1.2.3 AAV onset and disease course ...................................................................................... 11 1.2.3.1 Measures of disease activity and damage ............................................................. 11 1.2.3.2 Key differences between childhood- and adult-onset AAV .................................. 12 1.3 Biomarkers .......................................................................................................................... 13 1.3.1 Biomarkers of overall disease outcomes ...................................................................... 13 1.3.2 Biomarkers of kidney-specific disease outcomes ........................................................ 14 1.3.2.1 Histopathologic classification ............................................................................... 14 1.3.2.2 Urine soluble proteins ........................................................................................... 15 1.3.2.2.1 Urine soluble (us)CD163 ............................................................................... 15 1.3.2.2.2 Urine soluble (us)CD25 ................................................................................. 16 1.3.2.2.3 Urine (u)MCP-1 ............................................................................................. 17 1.4 Rationale .............................................................................................................................. 18 Chapter 2: Materials and Methods ............................................................................................ 19 2.1 Study Participants ................................................................................................................ 19 2.1.1 Small vessel vasculitis (SVV) cohort for the evaluation of ANCA ............................. 19 2.1.2 Renal and non-renal SVV cohorts for the evaluation of urine proteins ....................... 20 2.1.3 Large vessel vasculitis (LVV) cohort for the evaluation of urine proteins .................. 22 2.1.4 Healthy (adult) control cohort ...................................................................................... 22 2.2 Quantification of overall disease activity, damage, and outcome ....................................... 22 2.2.1 Overall disease activity ................................................................................................ 22 2.2.2 Overall disease damage ................................................................................................ 22 2.2.3 Overall disease outcomes ............................................................................................. 23 2.3 Kidney-specific disease activity, damage, function, and outcome ...................................... 23 xi 2.3.1 Kidney disease activity and damage ............................................................................ 23 2.3.2 Kidney function ............................................................................................................ 24 2.3.3 Kidney disease outcomes ............................................................................................. 25 2.4 Urine collection and total urine protein isolation ................................................................ 25 2.5 Quantification of total protein in urine ................................................................................ 26 2.6 Quantification of usCD163 ................................................................................................. 27 2.7 Quantification of usCD25 ................................................................................................... 27 2.8 Quantification of uMCP-1 ................................................................................................... 28 2.9 Statistical Analysis .............................................................................................................. 28 Chapter 3: The utility of ANCA seropositivity and antigen specificity in the assessment of overall disease activity and outcome in childhood-onset small vessel vasculitis ................... 35 3.1 Rationale and introduction .................................................................................................. 35 3.2 Study cohort ........................................................................................................................ 36 3.3 Results ................................................................................................................................. 38 3.3.1 ANCA seropositivity is associated with higher overall disease activity at diagnosis. . 38 3.3.2 Disease states within 2-years of diagnosis do not differ by ANCA seropositivity or specificity ............................................................................................................................... 40 3.3.3 MPO-ANCA seropositivity is associated with a higher prevalence of kidney involvement and a lower prevalence of ENT involvement than PR3-ANCA seropositivity .. 46 3.4 Discussion ........................................................................................................................... 53 Chapter 4: The utility of ANCA and urine proteins (usCD163, uMCP-1, and usCD25) in identifying active disease in the kidneys in childhood-onset small vessel vasculitis .............. 56 4.1 Rationale and introduction .................................................................................................. 56 xii 4.2 Study cohorts ....................................................................................................................... 57 4.3 Results ................................................................................................................................. 61 4.3.1 MPO-ANCA seropositivity is more often associated with kidney insufficiency at diagnosis compared to PR3-ANCA seropositivity ................................................................. 61 4.3.2 MPO-ANCA seropositivity is associated with a more favourable kidney disease trajectory than PR3-ANCA seropositivity in individuals with severely reduced kidney function or kidney failure at diagnosis .................................................................................. 65 4.3.3 usCD163 and usCD25, but not uMCP-1, are detected in urine from children with small vessel vasculitis in the kidneys ..................................................................................... 69 4.3.4 Elevated usCD163 and usCD25 in an overlapping subset of patients with relatively high total protein concentration ............................................................................................ 75 4.3.5 usCD163 and usCD25 concentrations do not correlate with kidney disease activity at diagnosis or trajectory over 1 year ....................................................................................... 79 4.4 Discussion ........................................................................................................................... 83 Chapter 5: Conclusion and future directions ........................................................................... 86 5.1 Summary ............................................................................................................................. 86 5.2 Clinical significance ............................................................................................................ 87 5.3 Study limitations and future directions ............................................................................... 88 5.4 Conclusion ........................................................................................................................... 91 References .................................................................................................................................... 93 Appendices ................................................................................................................................. 103 Appendix A: Clinical scoring tools for disease activity (pVAS) and damage (pVDI) ............ 103 xiii A.1 Organ systems and clinical features considered by the pVAS ..................................... 103 A.2 Organ systems and clinical features considered by the pVDI ...................................... 106 xiv List of Tables Table 1.1 An overview of the classification criteria for AAV subtypes and their limitations ......... 8 Table 1.2 Histopathologic classification schema .......................................................................... 15 Table 2.1 Kidney function defined by eGFR and KDIGO stage .................................................. 25 Table 2.2 Summary of the statistical approach and primary comparisons of interest ................... 30 Table 3.1 Demographic and clinical characteristics of the SVV cohort ....................................... 37 Table 3.2 Differences in overall disease activity (total pVAS) at diagnosis between childhood-onset SVV stratified by ANCA status ........................................................................................... 39 Table 3.3 Definitions of disease states used to assess overall outcomes in SVV ......................... 40 Table 3.4 Overall outcomes between 1- and 2-years post-diagnosis in childhood-onset SVV stratified by ANCA status .............................................................................................................. 43 Table 3.5 Treatment for remission-induction in childhood-onset SVV stratified by ANCA status ....................................................................................................................................................... 46 Table 3.6 Treatment for remission-maintenance (1-year) in childhood-onset SVV stratified by ANCA status .................................................................................................................................. 46 Table 3.7 Organ involvement and clinical characteristics associated with ANCA type in childhood-onset SVV at diagnosis ................................................................................................ 49 Table 4.1 Demographic and clinical characteristics of childhood-onset vasculitis patients with and without kidney involvement for the analysis of urine protein biomarkers ............................. 60 Table 4.2 Predicted probabilities of KDIGO stages at diagnosis for childhood-onset small vessel vasculitis stratified by ANCA specificity ...................................................................................... 65 Table 4.3 Kidney function over the first 12 months in PR3-ANCA and MPO-ANCA positive childhood-onset SVV .................................................................................................................... 69 xv Table 4.4 Concentration in urine of usCD163, usCD25, and total protein ................................... 71 Table 4.5 Assay features for measurement of usCD163, usCD25, and uMCP-1 concentrations . 74 Table 4.6 Clinical characteristics of children with SVV with kidney involvement stratified by absolute usCD163 and usCD25 concentrations relative to detection thresholds .......................... 78 xvi List of Figures Figure 1.1 Childhood-onset PSV study group designations and ANCA status ............................... 3 Figure 2.1 Inclusion and exclusion criteria for the SVV cohort ................................................... 21 Figure 2.2 Inclusion and exclusion criteria for the renal and non-renal SVV cohorts .................. 21 Figure 3.1 Overall disease activity (total pVAS) at diagnosis in childhood-onset SVV stratified by ANCA status ............................................................................................................................. 39 Figure 3.2 Time of diagnosis organ involvement associated with ANCA positivity and specificity ....................................................................................................................................................... 48 Figure 4.1 Kidney disease at diagnosis in childhood-onset SVV stratified by ANCA status ....... 64 Figure 4.2 Kidney disease trajectory from diagnosis to 1-year post-diagnosis in childhood-onset SVV stratified by KDIGO stage at diagnosis and ANCA specificity ........................................... 68 Figure 4.3 usCD163 and usCD25 concentrations in childhood-onset SVV with kidney involvement ................................................................................................................................... 77 Figure 4.4 Comparison of usCD163 and usCD25 concentrations with kidney disease activity in childhood-onset SVV with kidney involvement ........................................................................... 81 Figure 4.5 Comparison of usCD163 and usCD25 concentrations with kidney function at diagnosis in childhood-onset SVV with kidney involvement ....................................................... 82 Figure 4.6 Comparison of usCD163 and usCD25 concentrations with kidney function at 1-year post-diagnosis in childhood-onset SVV with kidney involvement ............................................... 83 xvii List of Abbreviations AAV ANCA-associated vasculitis ACR American College of Rheumatology ANCA anti-neutrophil cytoplasmic antibodies ANCA-GN ANCA-associated glomerulonephritis ARChiVe A Registry of Childhood Vasculitis BCA bicinchoninic acid BSA bovine serum albumin BVAS Birmingham vasculitis activity score c-ANCA cytoplasmic ANCA CCR2 C-C chemokine receptor 2 CHCC Chapel Hill Consensus Conference eGFR estimated glomerular filtration rate EGPA eosinophilic granulomatosis with polyangiitis ELISA enzyme-linked immunosorbent assay EMA European Medicines Agency ENT ear, nose, and throat EULAR European Alliance of Associations for Rheumatology GPA granulomatosis with polyangiitis HLA human leukocyte antigen KDIGO Kidney Disease Improving Global Outcomes LAMP-2 lysosome associated membrane protein-2 LLOD lower limit of detection xviii LVV large vessel vasculitis MPA microscopic polyangiitis MPO myeloperoxidase MVV medium vessel vasculitis NETs neutrophil extracellular traps p-ANCA perinuclear ANCA PAN polyarteritis nodosa PedVas Pediatric Vasculitis Initiative PR3 proteinase-3 PReS Pediatric Rheumatology European Society PRINTO Pediatric Rheumatology International Trials Organisation PSV primary systemic vasculitis pVAS pediatric vasculitis activity score pVDI pediatric vasculitis damage index RAVE Rituximab in ANCA-Associated Vasculitis SVV small vessel vasculitis TA Takayasuâs arteritis uMCP-1 urinary monocyte chemoattractant protein-1 usCD163 urine soluble CD163 usCD25 urine soluble CD25 VDI vasculitis damage index xix Acknowledgements To my supervisors, Dr. Kelly Brown and Dr. Kimberly Morishita, I cannot thank you enough for this wonderful opportunity. These past two years have been the most enriching learning experience of my life, and I owe it all to you. Thank you for your unwavering support and encouragement, and for fostering a supportive environment that allowed me the freedom to be curious. I am incredibly fortunate to have had the privilege of learning from not just one, but two, exceptional mentors. To my supervisory committee, Dr. Stuart Turvey and Dr. Donald Sin, your continuous support and insightful feedback have been invaluable to my research. To past and present members of the Brown Lab, thank you for your friendship. A heartfelt thank you to Stephanie Hughes for always brightening the lab with her cheerful spirit, and to Kirandeep Toor and Sarah Bowers, for being two of the kindest people I have ever had the pleasure of knowing. I will forever cherish our coffee runs. To the BC Childrenâs Hospital (BCCH) and the BC Childrenâs Hospital Research Institute (BCCHR), thank you for providing funding support for my project through the BC Childrenâs Hospital Graduate (Masterâs) Studentship. My sincerest thanks to Veronica Chow and Vi Nguyen from the BCCH Biobank for diligently managing the pediatric patient samples used in my research, and to Jeffrey Bone from the BCCH Biostatistics Core for his invaluable statistical support. To the BCCH Division of Rheumatology, Dr. David Cabral and Dr. Else Bosman, I am very grateful for your ongoing support, thoughtful feedback and continuous encouragement. xx To the University of British Columbia (UBC), thank you for your ongoing financial support. A special thank you to the UBC Department of Microbiology and Immunology, especially Darlene Birkenhead and Jiaojiao Lu, for their continuous support and guidance throughout my degree. To the Canadian Institutes for Health Research, thank you for providing funding for the Pediatric Vasculitis Initiative and for awarding me the Canada Graduate (Masterâs) Scholarship. To all study participants and their families, thank you for contributing to my research, which truly would not have been possible without you. To my friend, Aathavan Sriharan, thank you for letting me park next to your house for the past two years. Your generosity and kindness are greatly appreciated. To my friend, Gunraas Sachdeva, thank you for listening to my worries over Krispy Kreme donuts. You are an incredibly kind and genuine person with a remarkable sense of humor, and I am very lucky to have you as a friend. To my mom, Kuldip Mann, words cannot express how deeply grateful I am for all that you do, from bringing me food on days I was engrossed in thesis writing to working two jobs to raise Karn and me all on your own. I am continuously inspired by your strength and determination. To my partner, Prabhjot Nagra, thank you for always being by my side, whether at UBC or at Breka, until sunrise, through every moment of writing this thesis. Thank you for believing in me so fervently, even when I doubted myself, and for your unwavering love and support. I am incredibly blessed to have you in my life. Finally, to my dog, Rhea, who may not be able to read this but will definitely be getting some extra treats. Thank you for making me instantly forget all my worries the second I walk through the door each evening. You are forever my best friend. xxi Dedication For my mom. I hope to always make you proud. 1 Chapter 1: Introduction In adults with anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV), certain autoantibodies and urine proteins have been identified as predictive biomarkers of risk for severe disease, kidney involvement, and relapse. In the adult clinical setting, these biomarkers are now used to select treatment at diagnosis and, over the disease course, to inform decisions about when to start and stop treatment. Due to the rarity of childhood-onset AAV, it has been difficult to study the utility of such biomarkers in the pediatric population. In children, AAV is often severe and affects the kidneys in the majority of cases. When major organs like the kidneys are involved, aggressive treatment strategies are used. The risks of such treatments must be weighed differently in children who have developing immune systems and long lives ahead of them. There is an important need to identify biomarkers that can aid in predicting outcome and tailoring treatment in children. The intent of this thesis is to assess the utility of these adult-derived tools using the single largest repository of retrospective data and biosamples from children with vasculitis that is housed at the University of British Columbia and the BC Childrenâs Hospital Research Institute. In the context of this thesis, the âutilityâ of a biomarker refers to its capacity to provide insights into the disease state and its progression, thus having potential to guide treatment and improve health outcomes. 1.1 Chronic primary systemic vasculitis (PSV) Vasculitis describes a heterogenous group of rare disorders that are characterized by the inflammation of blood vessels 1,2. Inflammation may cause blood vessel walls to thicken and restrict blood flow, leading to ischemia and necrosis of the surrounding tissue. Although inflammation of blood vessels is common to all vasculitides, the predominant size (small, 2 medium, large) of affected blood vessels and their location in single organs (e.g., kidneys, lungs) or multiple organs simultaneously results in a wide range of clinical manifestations, from skin rash to multi-organ failure and even death. Vasculitis can develop as a primary disorder without an apparent cause, or secondary to an underlying condition (e.g., infections, autoimmune diseases, malignancies). Some forms of vasculitis can be acute and short-lived, while others are chronic and recurring. Any form of vasculitis that is chronic, primary, and in blood vessels external to the central nervous system is aptly called a chronic primary systemic vasculitis (PSV). This group of vasculitides is less common than acute forms of vasculitis, but due to their chronic and remitting-relapsing nature, have a disproportionately high burden on patients, their families, and the health care system. In children, PSV most frequently affects small-sized blood vessels such as the arterioles, capillaries, venules, and, in some cases, small arteries or veins. Under this umbrella of small vessel vasculitides (SVV), anti-neutrophil cytoplasmic antibody (ANCA)-associated vasculitis (AAV) is the most common and will be the focus of this thesis research (Figure 1.1). 3 Figure 1.1 Childhood-onset PSV study group designations and ANCA status A flow chart providing an overview of the different subtypes comprising chronic primary systemic vasculitis (PSV) and the associated autoantibody (ANCA) status, specifically seropositivity and specificity for myeloperoxidase (MPO) and/or proteinase-3 (PR3). 1.2 Childhood-onset ANCA-associated vasculitis (AAV) Childhood-onset AAV predominantly affects the small blood vessels. Despite being the most common form of PSV in children, childhood-onset AAV is still extremely rare, with an annual incidence of approximately 0.22 per million children reported in a French cohort 3. 1.2.1 Anti-neutrophil cytoplasmic antibodies (ANCA) The presence of circulating autoantibodies, known as anti-neutrophil cytoplasmic antibodies (ANCA), is a defining feature of AAV, as reflected in the name. ANCA are reactive against multiple antigens in the cytoplasmic (c-ANCA) and perinuclear (p-ANCA) region in neutrophils 4 and, to a lesser extent, in monocytes. They were incidentally detected in 1982 in a patient with crescentic glomerulonephritis, and, three years later, their association with the AAV subtype granulomatosis with polyangiitis (GPA) was observed. 1.2.1.1 ANCA positivity and antigen specificity in AAV In AAV, ANCA are typically directed to one of two endogenous proteins, myeloperoxidase (MPO) or proteinase-3 (PR3), although some AAV patients may be seropositive for ANCA against both MPO and PR3. In addition, ~11% of pediatric patients who meet diagnostic criteria for AAV do not have detectable levels of ANCA against either MPO or PR3 (i.e., ANCA-negative AAV) 4. MPO is a cationic (pI > 10) peroxidase with an estimated molecular weight of 150 kDa 5,6. It is primarily stored in azurophilic (primary) granules of neutrophils and in the lysosomes of monocytes, where its main physiological function is to promote the microbicidal activity of these cells by catalyzing the generation of reactive oxygen intermediates 5,7. Since MPO is not constitutively expressed on the surface of these cells, the exact mechanism by which ANCA target MPO is unclear, with one theory suggesting that cellular activation by inflammatory stimuli can lead to the translocation of MPO to the cell surface 8. Alternatively, MPO may be expelled along with DNA/histones in extracellular traps released by neutrophils (NETs), where it contributes to the NET-mediated killing of extracellular microbes 5. Proteinase-3 (PR3) 9 is a serine protease with an estimated molecular weight of approximately 29-30 kDa 10,11. Similar to MPO, PR3 is found in azurophil granules of neutrophils and, to a 5 lesser extent, in lysosomes within certain subsets of monocytes, where it contributes to the degradation of phagocytosed microbes 12. Additionally, PR3 has been detected on the surface of neutrophils. A higher percentage of cells expressing membrane-bound PR3 was observed in adults with GPA compared to healthy controls and was correlated with a higher risk of relapse 13,14. Additionally, like MPO, PR3 is also secreted in association with NETs, where it facilitates the degradation of extracellular matrix proteins at sites of inflammation 15. 1.2.1.2 Development of ANCA The exact mechanisms underlying the development of ANCA against MPO and PR3 are poorly understood. While it is plausible that ANCA are naturally occurring in individuals with AAV 16, several theories have been postulated for the development of ANCA (reviewed in 17). According to the molecular mimicry model, ANCA are initially generated in response to a microbial antigen, but homology with self-antigens leads to cross-reactivity. In support of this theory, the human lysosome associated membrane protein-2 (LAMP-2/CD107b) epitope shares 100% sequence homology with FimH, a bacterial adhesin, and rats immunized with FimH were shown to develop antibodies against LAMP-2, as well as pauci-immune glomerulonephritis 18. The complementary peptide model posits that the initial immune response is directed against peptides with complementary structures to autoantigens, leading to the production of antibodies against these peptides. The subsequent generation of anti-idiotype antibodies, however, is responsible for directly targeting the autoantigens. Notwithstanding the possibility that these antibodies may form in response to the antisense transcript of autoantigens, sequence homologies have been observed between complementary PR3 and pathogens previously linked to GPA such as Entamoeba histolytica, and Staphylococcus aureus 19â22. Lastly, genetic predisposition may also 6 contribute to the development of ANCA. In support of this, previous studies have identified certain human leukocyte antigen HLA-DQ and HLA-DP alleles as being associated with antigen specificity for MPO-ANCA and PR3-ANCA, respectively, in individuals with AAV 23. 1.2.1.3 Detection of ANCA Serological testing for ANCA is widely used in clinical practice to aid in the diagnosis of AAV. Historically, indirect immunofluorescence was the âgold standardâ for detecting ANCA in patient sera 24. Using ethanol-fixed neutrophils, this method identifies the presence of cytoplasmic (c-) and perinuclear (p-) ANCA via distinct fluorescence staining patterns corresponding to their respective names. While the majority of c-ANCA and p-ANCA in AAV patients are directed, respectively, against PR3 and MPO, other antigens in the cytoplasmic and perinuclear regions may also be targeted, resulting in a similar staining pattern. Thus, antigen-specific immunoassays (typically enzyme-linked immunosorbent assays, ELISAs) have become the preferred method for determining ANCA seropositivity and specificity for MPO or PR3 25â27. 1.2.2 Subtypes of AAV Clinically, AAV is comprised of three subtypes: granulomatosis with polyangiitis (GPA), microscopic polyangiitis (MPA), and eosinophilic granulomatosis with polyangiitis (EGPA). In children, they are characterized by a similar age at onset of approximately 11 to 14 years and female predominance 3,28â30. Due to the rarity of AAV, it is difficult to estimate the incidence and prevalence of these conditions, especially in pediatric populations. Nevertheless, GPA and MPA are widely recognized as the most common subtypes (reviewed in 31), yet distinguishing among them can be challenging due to overlapping clinical features. 7 1.2.2.1 Clinical classification criteria for AAV subtypes In 1990, the American College of Rheumatology (ACR) proposed the first classification criteria for adult-onset GPA and EGPA (1990 ACR criteria) 32,33. Since then, several criteria have been developed and periodically revised to facilitate the classification of GPA, MPA, and EGPA, including the 1994 international Chapel Hill Consensus Conference (CHCC) definitions 34, the 2007 European Medicines Agency (EMA) classification algorithm 35, and, more recently, the 2022 ACR and European Alliance of Associations for Rheumatology (EULAR) classification criteria (Table 1.1) 36â38. Given the rarity of childhood-onset AAV, however, these criteria were derived from adult data. Consequently, their application to pediatric populations results in substantial difficulties, with differing classifications depending on the criteria being applied, and many individuals remaining unclassified. For example, approximately one-third of children diagnosed with GPA based on expert assessment do not meet the 1990 ACR criteria for GPA 39. In 2006, the Pediatric Rheumatology European Society (PReS) modified the 1990 ACR criteria to propose the first classification criteria for GPA in children, which was later endorsed and validated by EULAR and the Pediatric Rheumatology International Trials Organisation (PRINTO) (EULAR/PRINTO/PReS criteria for GPA) 40. While these criteria demonstrated higher sensitivity for classifying GPA in children compared to the 1990 ACR criteria for GPA, it was limited by the lack of specific classification guidelines for MPA. As a result, the classification of AAV in children remains a challenge with no clear âgold standardâ. 8 Table 1.1 An overview of the classification criteria for AAV subtypes and their limitations Classification Criteria Description Limitations 1990 ACR criteria Classification criteria used to identify patients with GPA and EGPA based on a core set of 4 or 6 differentiating clinical features â¢ Derived from adult data with less utility in the classification of childhood-onset AAV 39 â¢ No criteria for the classification of MPA 1994 CHCC definitions Standardized nomenclature and definitions for common forms of PSV, including GPA, MPA, and EGPA â¢ Derived from adult data with less utility in childhood-onset AAV 2007 EMA classification algorithm A four-step algorithm, integrating the 1990 ACR criteria and 1994 CHCC definitions, for the classification of GPA, MPA, EGPA, and polyarteritis nodosa (PAN) â¢ Derived from adult data with less utility in the classification of childhood-onset AAV 39 â¢ Classification of MPA is based on exclusion of EGPA and GPA 2008 EULAR/PRINTO/PReS criteria for GPA Classification criteria, adapted from the 1990 ACR criteria, used to identify childhood-onset GPA based on the presence of 6 clinical, histopathological, radiological, and laboratory findings â¢ No criteria for the classification of MPA 2022 ACR/EULAR classification criteria Classification criteria for GPA, MPA, and EGPA which allocates weighted points to clinical, histopathological, radiological, and laboratory findings, with patients meeting cut-off values classified accordingly â¢ Derived from adult data, and performance has not yet been tested in childhood-onset AAV 1.2.2.2 Clinical features of AAV Formerly known as Wegenerâs granulomatosis, GPA is characterized by granulomatous, necrotizing inflammation of small blood vessels and the clinical triad of upper respiratory tract involvement, lower respiratory tract involvement, and kidney disease. In children with GPA, upper airway disease, involving the ears, nose, and throat, usually manifests as recurrent nasal symptoms (e.g., nasal bloody discharge/crusting/obstruction/ulcer) and chronic or recurrent sinusitis, while lower airway, or pulmonary, disease is characterized by chronic cough, alveolar hemorrhage and massive hemoptysis 28. Although upper respiratory tract involvement is rare in 9 children with MPA, lower respiratory tract involvement is common and presents with similar clinical features as in GPA 28. Likewise, EGPA also involves the inflammation of small blood vessels in the respiratory tract, often accompanied by the development of granulomas 29,30. However, EGPA is distinct from the other AAV subtypes in that it is characterized by, initially, asthma and allergic rhinitis or nasal polyposis, followed by peripheral blood eosinophilia and the infiltration of eosinophils into tissues for the majority of pediatric patients. Kidney involvement is one of the most common clinical manifestations of AAV, contributing substantially to morbidity and mortality associated with the disease. It is observed in a majority (>80%) of children with GPA and MPA, and, while less common, has also been noted in those with EGPA 3,28â30. Kidney involvement is typically characterized by hypertension, edema, proteinuria, impaired creatinine clearance, microscopic hematuria, and red blood cell casts 28. Pauci-immune necrotizing glomerulonephritis is a severe manifestation of AAV which often progresses to chronic or end-stage kidney disease and, in some cases, kidney failure. A previous study of pediatric AAV by our group demonstrated that 7% of children had end-stage kidney disease at initial presentation, and 16% were in kidney failure requiring dialysis 28. Similarly, in a separate cohort of childhood-onset AAV patients, two-thirds of children presented with acute kidney injury, and 14% needed dialysis 3. In addition to the high prevalence and severity of kidney disease at initial presentation, approximately one-third of children with AAV go on to develop permanent kidney damage within one year of diagnosis 4. Therefore, the presence of kidney disease is a major driver of treatment decisions. 10 1.2.2.3 Current treatments of AAV There is currently no cure for AAV. Thus, treatment is focused on reducing inflammation, managing clinical symptoms, and minimizing the accumulation of permanent damage from both the disease and treatment-associated toxicity. If left untreated, the prognosis for AAV is poor with a mortality rate of up to 80% and a mean survival time of 5 months; therefore, timely and appropriate treatment is crucial 41. Treatment of AAV is typically divided into two phases: remission-induction for 3 to 6 months, followed by remission-maintenance for a minimum of 18 months. Cyclophosphamide has been considered standard practice for remission-induction since the early 1970s 42. Despite its efficacy, however, the prolonged use of cyclophosphamide is associated with both short- and long-term toxicity risks including infections, infertility and malignancy 43,44. While cyclophosphamide remains central to the treatment of organ- and/or life-threatening AAV, rituximab, an anti-CD20 monoclonal antibody, has recently emerged as a favourable alternative for individuals who are intolerant to cyclophosphamide, or for whom side effects such as infertility are particular concerning, such as younger patients. Findings from the Rituximab in ANCA-Associated Vasculitis (RAVE) trial identified cyclophosphamide and rituximab as being equally effective for remission-induction in organ- and/or life-threatening adult-onset AAV, while rituximab was shown to be superior for those with relapsing disease 45. Based on these findings in adults, the 2022 EULAR guidelines recommend remission-induction with high-dose glucocorticoids in combination with either cyclophosphamide or rituximab for severe cases of GPA and MPA, especially for patients with relapsing disease, followed by rituximab for remission-maintenance, with azathioprine and methotrexate considered suitable alternatives 27. Given the rarity of childhood-onset AAV, however, randomized controlled trials to 11 assess the efficacy and toxicity of these drugs in pediatric populations are challenging. As a result, treatment protocols for childhood-onset AAV are largely informed by adult studies. 1.2.3 AAV onset and disease course Until recently, most children with AAV died within a year of diagnosis due to organ (often kidney or lung) failure or infection. Although modern treatments, described in Section 1.2.2.3, have dramatically improved survival and reduced morbidity for pediatric and adult patients with AAV, it remains a chronic, remitting and relapsing disease. In children, this leads to the continuous, over decades, accrual of damage from both the disease itself and treatment toxicity. Maximizing treatment efficacy while minimizing toxicity requires frequent monitoring of global and organ-specific disease activity and damage. 1.2.3.1 Measures of disease activity and damage Presently, the gold standard for differentiating between disease activity and irreversible damage in an individual organ is via histopathological examination of a biopsy. However, biopsies have inherent risks/errors such as bleeding and infection 46, and invasive serial biopsies are not always practical. Additionally, it is not feasible to track the extent of disease activity across several concurrently affected organs via biopsies. To this end, clinical scoring tools such as the Birmingham Vasculitis Activity Score (BVAS) 47 and the Vasculitis Damage Index (VDI) 48 were developed and subsequently modified for use in pediatric populations. The Pediatric Vasculitis Activity Score (pVAS) is a validated and standardized clinical scoring tool adapted from the BVAS with pediatric-specific modifications (e.g., incorporating age-specific references for blood pressure range) for the weighted assessment of disease activity in children with vasculitis 49. The 12 Pediatric Vasculitis Damage Index (pVDI) 49 is a clinical tool for assessing damage in children with vasculitis, adapted from the VDI with the addition of items such as absence from school. While the pVAS and pVDI allow for the systematic assessment of disease activity and damage, respectively, across organs, both tools have limitations. For instance, the pVAS lacks sensitivity to gauge persistent mild activity; therefore, stopping treatment on this basis could trigger a flare 50,51. Furthermore, the pVDI only considers organ insults as damage, and not active disease, if they persist unchanged for more than 3 months. However, for some vital organs, notably the kidneys, a 3-month interval for distinguishing between disease activity and damage may be too long for critical treatment decisions. Therefore, a better approach to assess disease activity and damage is urgently needed. 1.2.3.2 Key differences between childhood- and adult-onset AAV Although the origins of vasculitis are likely similar in children and adults, there are important differences in childhood- and adult-onset AAV. The median age at onset for childhood-onset AAV is 14 years (IQR: 11 to 16), in contrast to 53 years (IQR: 41 â 63) for adults. While childhood-onset AAV is characterized by a female predominance 3,52,53, adult-onset AAV is slightly more common in males 54,55. Furthermore, there are differences in the clinical presentation of childhood- and adult-onset AAV. For instance, myalgias and peripheral neuropathy are more common in adult-onset AAV, while children are more often febrile and more likely to develop nasal cartilage damage and ischemic abdominal pain 56. Compared to adults, children also have a higher overall burden of the disease; childhood-onset AAV is more likely to be severe at outset and more likely to present with (moderate-to-severe) multi-organ involvement 28,56,57. Lastly, the lifetime burden of the disease and drug-induced side-effects is 13 also higher for children who experience a longer disease course and are, therefore, exposed to treatments for a longer duration, which can negatively impact their growth and development, as well as increase the risk of toxic side effects such as infertility and malignancy. 1.3 Biomarkers According to the National Institutes of Health, âbiomarkers are characteristics that can be objectively measured and used as an indicator of normal biological processes, disease processes, or pharmacologic responses to therapyâ 58. Prognostic biomarkers for overall and kidney-specific disease in AAV are needed to optimize treatment strategies and minimize the cumulative exposure to, and the risk of, toxicities associated with treatments. To this end, subclinical markers of the disease may provide more meaningful insight than classification criteria which are largely based on clinical phenotypes. Given the rarity of childhood-onset AAV, however, advances in this area are derived solely from studies in adult-onset AAV. 1.3.1 Biomarkers of overall disease outcomes Although the exact mechanisms of AAV etiopathogenesis remain unknown, prior studies have provided evidence of a genetic component, with several genetic polymorphisms being linked to an increased risk of developing AAV. In a genome-wide association study, Lyons et al. demonstrated that ANCA specificity, rather than clinical phenotype, exhibit the strongest association with these genetic risk factors, indicating that ANCA can provide valuable clinical insights into the development and progression of AAV 23. In support of this, some studies, investigating the prognostic value of ANCA, have demonstrated a significant association between increased ANCA titers and likelihood of a relapse 59â61. In a cohort of 502 adults with 14 AAV, Lionaki et al. found ANCA specificity to be predictive of relapse, with the risk of relapse in PR3-ANCA seropositive patients being almost double that in MPO-ANCA seropositive patients 62. Similarly, in a study of 92 adults with AAV, Bantis et al. also described a higher rate of relapse for PR3-ANCA seropositive patients compared to MPO-ANCA seropositive patients 63. In addition to this, Bantis et al. identified differences in clinical presentation among these subgroups, where extra renal manifestations, including involvement of the upper and lower respiratory systems, were more frequent in PR3-ANCA seropositive patients, while MPO-ANCA seropositive disease often presented with reduced kidney function 63. Taken together, these studies provide support for the prognostic role of ANCA in adult-onset AAV. 1.3.2 Biomarkers of kidney-specific disease outcomes Considering that the majority (>80%) of childhood-onset AAV cases present with kidney disease at outset and approximately one-third develop permanent kidney damage within a year, it is crucial to identify reliable biomarkers to predict kidney disease progression. To date, histopathological classification (Berdenâs classification) and urine proteins, most notably urine soluble (us)CD163, usCD25, and urinary monocyte chemoattractant protein-1 (uMCP-1), have been identified as promising biomarkers for kidney disease in adult-onset AAV. 1.3.2.1 Histopathologic classification In 2010, Berden et al. proposed a classification system categorizing biopsies as focal, crescentic, sclerotic or mixed on the basis of glomerular morphology as observed via light microscopy (Table 1.2) 64. The focal category represents the mildest form of glomerulonephritis, in which the majority of glomeruli have not yet been affected by the disease. Conversely, the sclerotic 15 category is defined by widespread glomerular sclerosis (i.e., scarring). In a cohort of 100 adults with ANCA-associated glomerulonephritis (ANCA-GN), Berden et al. reported an increasing risk of end-stage kidney disease at 1- and 5-year follow-up as the classification category moves from focal to sclerotic at diagnosis, reflecting higher renal impairment. Since then, other studies have validated the prognostic value of Berdenâs classification for renal survival in larger cohorts of 121 65, 250 66, and 251 67 adults with ANCA-GN. The utility of the Berden classification system was preliminarily assessed by Noone et al. 68. The results provided support for the prognostic utility of the focal and sclerotic categories at diagnosis; however, due to a small sample size, the other categories (mixed and crescentic) had to be combined and could not be analyzed as individual groups. Table 1.2 Histopathologic classification schema Adapted from Berden et al. (2010) 64. Class Inclusion Criteria Focal Â³ 50% normal glomeruli Crescentic Â³ 50% glomeruli with cellular crescents Mixed < 50% normal, < 50 % crescentic, < 50% globally sclerotic glomeruli Sclerotic Â³ 50% globally sclerotic glomeruli 1.3.2.2 Urine soluble proteins 1.3.2.2.1 Urine soluble (us)CD163 Macrophages are the most abundant inflammatory cells present in glomerular crescents in the kidneys of adults with AAV 69. M2 macrophages expressing CD163, a glycosylated plasma membrane protein are present in regions of initial glomerular injury 69. Membrane-bound CD163 is cleaved into its soluble (s) form (sCD163) via ectodomain shedding in response to pro-inflammatory stimuli 70. Soluble CD163, in turn, is considered a macrophage activation marker, 16 and prior studies have demonstrated its utility as a biomarker in diseases characterized by excessive macrophage activation and proliferation such as hemophagocytic syndrome, celiac disease, and Gaucherâs disease, suggesting its potential utility in renal vasculitis 71â73. Previously, in a cohort of adults with AAV, OâReilly et al. demonstrated higher expression of CD163 mRNA in glomerular and tubulointerstitial regions of the kidney in adults with AAV relative to healthy controls 74. The elevated expression of CD163 in the kidneys of these patients was confirmed via immunohistochemistry. Additionally, OâReilly et al. measured elevated urine soluble (us)CD163 concentrations in adults with active renal vasculitis, defined by the vasculitis activity score (BVAS), compared to those with active extra renal vasculitis, and those in remission. Similarly, other studies demonstrated, in independent cohorts, elevated usCD163 concentrations in adults with renal vasculitis 75â77. OâReilly et al. identified an optimal cut-off value of 0.3 ng/mmol of creatinine for distinguishing active disease in the kidneys. 1.3.2.2.2 Urine soluble (us)CD25 In addition to macrophages, there is substantial evidence suggesting a central role of T cells in the pathogenesis of AAV, although the exact mechanisms of involvement are unclear 78. Soluble (s)CD25 is a transmembrane glycoprotein that is shed, into serum and other bodily fluids (e.g., urine), via proteolytic cleavage following T cell activation 79. As a result, sCD25 has been explored as a surrogate marker of T cell activation in various autoimmune diseases 80â82. In support of this, a previous study, in a cohort of adults with AAV, by Dekkema et al. reported correlations between urine soluble (us)CD25 and urinary CD4+ T cell counts in adults with active renal vasculitis 77. usCD25 concentrations were also elevated in these patients compared to those with active extra renal vasculitis, those in remission, and healthy controls. Based on these data, 17 Dekkema et al. calculated an optimal cut-off value of 125 ng/mmol of creatinine for identifying patients with active disease in the kidneys. 1.3.2.2.3 Urine (u)MCP-1 The central role of MCP-1 in the inflammatory response has been well established. MCP-1 is known to recruit inflammatory cells such as monocytes and macrophages to the site of infection or injury by binding cell surface C-C chemokine receptor 2 (CCR2) 83. The infiltration of monocytes and macrophages into the glomeruli is associated with worsening kidney disease in individuals with AAV 84. Since glomerulonephritis in individuals with AAV typically involves macrophage infiltration, uMCP-1 is considered a promising biomarker for active kidney disease in these patients. In support of this, in a cohort of adults with AAV, Tam et al. identified elevated uMCP-1 concentrations in patients with active renal vasculitis compared to those with active extra renal vasculitis, inactive vasculitis, and healthy adults 85. Additionally, longitudinal analyses showed a reduction in uMCP-1 concentrations in 10 patients with improvements in renal function over four months. In one patient, rising uMCP-1 concentrations were correlated with a subsequent worsening of renal function, and this patient eventually required dialysis. Lastly, in a separate cohort of adults with AAV, Moran et al. identified an optimal cut-off of 10.0 pg/mmol of creatinine for distinguishing patients with active renal vasculitis from those with active extra renal vasculitis and those in remission 76. These findings highlight the utility of uMCP-1 with regards to active kidney disease in adults. 18 1.4 Rationale Given the differences in childhood- and adult-onset AAV, it is necessary to validate adult-derived biomarkers in pediatric populations prior to their adoption into clinical practice for these patients. However, studies investigating the utility of these markers in childhood-onset AAV have been limited, in large part because the pediatric disease rarity has precluded studies. To this end, a time-of-diagnosis registry, called A Registry of Childhood Vasculitis (ARChiVe), was established in 2007 at the BC Childrenâs Hospital (Division of Rheumatology) and, in 2012, was expanded under the Pediatric Vasculitis Initiative (PedVas) to include longitudinal clinical data and paired biosamples. Altogether, ARChiVe/PedVas has collected clinical data from more than 600 children with PSV, with corresponding biological samples, including urine, from over 250 of these patients. Although biomarker studies in adult-onset vasculitis are focused on patients with AAV (GPA, MPA, and/or EGPA), this thesis research will include patients in the ARChiVe/PedVas registry with a diagnosis of SVV, the majority of whom (86%) meet criteria for AAV. With this approach, I ensure the inclusion of ANCA-negative cases of SVV, which are more common in children than in adults, and up to 30% of children with SVV who are otherwise unclassifiable using adult-derived classification criteria for AAV. My thesis will evaluate, in this select cohort of children with small vessel vasculitis, the utility of adult-derived biomarkers, namely ANCA and urine proteins (usCD163, usCD25, and uMCP-1), for informing overall and kidney-specific disease at the time of diagnosis, as well as later in the disease course. 19 Chapter 2: Materials and Methods 2.1 Study Participants Study participants were selected from A Registry of Childhood Vasculitis (ARChiVe), which was established as a pilot time-of-diagnosis repository in 2007 86 and modified through the Pediatric Vasculitis Initiative (PedVas; 2013) for the longitudinal collection of biological samples and follow-up clinical data from children and adolescents, referred to simply as âchildrenâ hereafter, with PSV 4,86. Clinical data includes demographics, diagnosis, clinical features, laboratory results with organ-specific function tests, medications, disease activity and damage scores, and ANCA status (seropositivity and specificity for MPO and/or PR3). The study protocol was approved by the Childrenâs and Womenâs Research Ethics Board of the University of British Columbia (H12-00894) and the respective ethical committees or IRBs at the ~40 sites participating in ARChiVe/PedVas. Written informed consent and assent/consent, respectively, was obtained from parents/guardians and from pediatric patients. Information regarding the demographics and clinical characteristics of participants, separated by study cohort, is provided in Tables 3.1 and 4.1. Study cohorts include: 2.1.1 Small vessel vasculitis (SVV) cohort for the evaluation of ANCA Figure 2.1 and Table 3.1. Eligible participants included children less than eighteen years of age at the time of diagnosis by the treating physician of a PSV affecting small-sized blood vessels (SVV), inclusive of the AAV subtypes GPA and MPA, as well as ANCA-positive pauci-immune glomerulonephritis, and unclassified primary (small vessel) vasculitis. Children with EGPA (n = 20) were excluded as it is exceedingly rare in childhood (representing only 4% of SVV patients 20 in the ARChiVe/PedVas registry), and although the ANCA-positive EGPA patients may share some phenotypic features of GPA or MPA patients, ANCA-negative EGPA patients, which are the majority, have a distinct clinical presentation and are usually treated differently. ANCA seropositivity and specificity for MPO and/or PR3 was determined by the participating sites and recorded in the registry. Individuals with missing data for ANCA status (n = 43) or those with specificity for both MPO and PR3 (n = 10) were excluded from this cohort. Clinical data for ANCA-negative cases were scrutinized for evidence consistent with primary small vessel vasculitis that, for the majority (31/41 cases; 76%), came from histopathologic analysis of a biopsy. Given the importance of controlling for age at diagnosis and biological sex as potential confounding variables (see Section 2.9), individuals with missing data for either variable (n = 23) were also excluded. In total, 406 children and adolescents were included in this cohort, 236 of whom were PR3-ANCA seropositive, 129 were MPO-ANCA seropositive, and 41 were seronegative for ANCA against either antigen. 2.1.2 Renal and non-renal SVV cohorts for the evaluation of urine proteins Figure 2.2 and Table 4.1. Children with a time-of-diagnosis urine sample (n = 103) who were diagnosed with SVV, inclusive of AAV but not EGPA (n = 20), as outlined in Section 2.1.1, were eligible for inclusion in one of two cohorts for the analysis of urine proteins. Patients with missing clinical data for kidney disease activity (renal pVAS, n = 21) at diagnosis were excluded. The remaining (n = 62) individuals were divided into two cohorts, labelled renal and non-renal SVV, based on kidney disease activity at diagnosis, as described in Chapter 4.2. 21 Figure 2.1 Inclusion and exclusion criteria for the SVV cohort A flow chart outlining the inclusion and exclusion criteria used to select 406 children and adolescents with SVV for the evaluation of ANCA as a disease biomarker (results presented in Chapter 3 and Chapter 4). Figure 2.2 Inclusion and exclusion criteria for the renal and non-renal SVV cohorts A flow chart outlining the inclusion and exclusion criteria used to select 62 children and adolescents in the renal (n = 52) and non-renal (n = 10) SVV cohorts with available urine samples for the evaluation of urine proteins as a biomarker of renal disease (results presented in Chapter 4). 22 2.1.3 Large vessel vasculitis (LVV) cohort for the evaluation of urine proteins Table 4.1. Eligible participants included children less than eighteen years of age at the time of diagnosis, who were diagnosed with Takayasuâs arteritis (TA, n = 87), a form of vasculitis affecting large blood vessels, by the treating physician. Urine samples, collected at the time of diagnosis, were available for a total of 11 individuals. 2.1.4 Healthy (adult) control cohort This cohort included healthy adults (n = 20) who provided written consent to the PedVas study and contributed a one-time urine sample. 2.2 Quantification of overall disease activity, damage, and outcome 2.2.1 Overall disease activity Disease activity was quantified using the pediatric Vasculitis Activity Score (pVAS) (Table A.1) 47,49. The pVAS ranges from 0 to 63 and identifies active disease in nine organ systems based on the absence and presence of new/worse or persistent clinical features, where a higher score reflects higher disease activity. The total and organ-specific scores for participants are calculated for each clinic visit (diagnosis and routine follow-up) based on data entered in the ARChiVe/PedVas registry by participating sites. 2.2.2 Overall disease damage The pediatric Vasculitis Damage Index (pVDI) was used to identify damage 87 (Table A.2). The pVDI ranges from 0 to 76 and records damage in individual organ systems when abnormal 23 features/functions persist for â¥ 3 months 48,87. As damage is considered permanent, scored items are carried forward to subsequent visits. 2.2.3 Overall disease outcomes Overall outcome measures as previously described 4 at 1-year post-diagnosis and summarized in Table 3.3 included: (i) achievement of inactive overall disease, measured by total pVAS < 1 (ii) improving disease defined by a â¥ 50% and â¥ 70% reduction in total pVAS from diagnosis (iii) the presence of damage, as measured by pVDI â¥ 1 (iv) the occurrence of relapse (minor or major) between 1- and 2-years post-diagnosis as reported by the physician or by an increase in the total pVAS from 0 to â¥ 2, or 1 to â¥ 4, during this time interval. Relapse was solely defined as a recurrence of disease activity after achievement of inactive disease; a change or escalation of treatment was not required to meet the definition of relapse. 2.3 Kidney-specific disease activity, damage, function, and outcome 2.3.1 Kidney disease activity and damage The renal (kidney) system is one of nine organ systems included in the calculation of the total pVAS 49. Disease activity in the kidneys was quantified by the renal pVAS, which is the renal subcomponent score of the total pVAS. The renal pVAS ranges from 0 to 12 and considers the following variables in the assessment of kidney disease activity at a given timepoint: hypertension, defined by systolic blood pressure above the 95th percentile according to age and 24 height; proteinuria, defined by urinary protein excretion greater than 300 mg per 24 hours or greater than 20 mg/mmol creatinine; kidney dysfunction, indicated by an estimated glomerular filtration rate (eGFR) below 80 ml/min/1.73m2; and a rise in serum creatinine or fall in creatinine clearance of more than 10% or 25%, respectively. A renal pVAS of 0 indicates inactive kidney disease. Permanent damage in the kidneys was quantified by the renal pVDI, which is the renal subcomponent score of the total pVDI 87. The renal pVDI ranges from 0 to 4 and considers the following variables in assessing kidney damage at a given timepoint: hypertension and proteinuria, as defined previously; reduced kidney function identified by an eGFR below 60 ml/min/1.73m2; and end-stage kidney disease indicated by an eGFR below 15 ml/min/1.73m2. A renal pVDI of 0 indicates no kidney damage. 2.3.2 Kidney function Kidney function was assessed by the eGFR (mL/min/1.73m2). In accordance with the Kidney Disease Improving Global Outcomes (KDIGO) guidelines for children, the Schwartz formula [(0.41)(height in cm)/(serum creatinine in mg/dL)] was used to calculate eGFR based on clinical registry data entered by participating sites (i.e., height and serum creatinine) 88. Kidney function was further categorized (based on eGFR) according to KDIGO guidelines, where Stage 1 (eGFR â¥ 90) corresponded to normal kidney function, Stage 2 (60 < eGFR < 89) indicated mildly reduced kidney function, Stage 3 (30 < eGFR < 59) indicated moderately decreased kidney function, Stage 4 (15 < eGFR < 29) indicated severely reduced kidney function, and Stage 5 (eGFR < 15) was indicative of kidney failure (Table 2.1) 89. 25 2.3.3 Kidney disease outcomes Kidney-specific outcome measures at 1-year post-diagnosis included: (i) active disease in the kidneys, as quantified by the renal pVAS (ii) kidney (dys)function, measured using the eGFR and classified according to KDIGO guidelines Table 2.1 Kidney function defined by eGFR and KDIGO stage KDIGO Stage eGFR (ml/min/1.73m2) Description of kidney function 1 â¥ 90 Normal kidney function 2 60-89 Mildly reduced kidney function 3 30-59 Moderately reduced kidney function 4 15-29 Severely reduced kidney function 5 <15 Kidney failure 2.4 Urine collection and total urine protein isolation Urine (5 â 15 mL) from study participants (Chapter 4 and Figure 2.2) was collected by participating sites into urine collection and preservation tubes (Norgen Biotek, Thorold, ON, CA; #18120) that allow room temperature preservation of urine proteins. Upon receipt, native urine samples were stored at room temperature at BC Childrenâs Hospital Research Institute (Brown Lab) until use. Urine proteins were isolated from 1 - 5 mL of native urine samples (per study participant) using the ProteoSpin Urine Protein Concentration Midi Kits (Norgen Biotek, Thorold, ON, CA; #52300) according to the manufacturerâs instructions. In brief, each urine sample was diluted with binding buffer until a pH of ~3.5 was confirmed using pH strips (VWR Chemicals, Radnor, 26 PA, USA; #BDH353309.606). Purification columns were washed twice with wash solution (1 mL) and centrifuged at 1,000 x g for 3 minutes. The pH-adjusted sample was transferred to the activated column and centrifuged at 1,000 x g for 5 minutes, and if needed, an additional 3 minutes at 1,000 x g and 3 minutes at 2,000 x g to allow the entire sample to pass through the column. The column was washed twice with wash solution (1 mL) and centrifuged at 1,000 x g for 3 minutes, then for 5 minutes. Protein neutralizer (18.6 µL â 93 µL, depending on initial sample volume) was added to a fresh 15 mL elution tube, after which the column was transferred to the tube. Urine proteins were eluted by adding elution buffer (100 µL â 500 µL, depending on initial sample volume) containing 10 mM Na3PO4 (pH 12.5) and centrifuged at 1,000 x g for 2 minutes, twice. Aliquots were transferred to sterile microcentrifuge tubes (Diamed Lab Supplies, Mississauga, ON, CA; #SPE155-N) and 10 µL of (100x) Halt protease inhibitor cocktail (ThermoFisher Scientific, Waltham, MA, USA; #87786) was added per 1 mL of sample. Aliquots were stored at -80°C until further use. 2.5 Quantification of total protein in urine The Pierce Bicinchoninic Acid (BCA) kit (Thermofisher, MA, USA; #23227) was used for the quantification of total protein in purified urine protein samples (see Section 2.4) according to the manufacturerâs instructions. In brief, duplicates (25 µL) of bovine serum albumin (BSA) standards (BSA diluted in ddH2O to 2,000 µg/mL â 0 µg/mL) and samples were transferred to a 96-well microtiter plate and mixed with 200 µL/well of working reagent containing equal parts BCA reagent A and B. All reagents were mixed thoroughly by shaking for 30 seconds on a rocking shaker at 80 rpm. Following incubation at 37°C for 30 minutes, the optical density of standards and samples was measured at 562 nm. A four-parameter sigmoidal standard curve was 27 used to quantify total protein concentration in the isolated urine protein samples (GraphPad Software, San Diego, CA). 2.6 Quantification of usCD163 Urine soluble (us)CD163 concentration (pg/mL) in purified urine protein samples was quantified using a Human CD163 DuoSet ELISA Kit (R&D Systems, Minneapolis, MN, USA; #DY1607-05) according to the manufacturerâs instructions. Samples were diluted 5-fold or 10-fold (Table 4.3) in PBS containing 1% BSA (pH 7.2 â 7.4). All samples and standards were assayed in duplicate in a 96-well microplate. Using the optical density (450 nm â 540 nm), a four-parameter sigmoidal standard curve was generated to determine the concentration of usCD163 for each sample. The lower limit of detection (LLOD, 87.0 pg/mL) was identified as the lowest concentration of usCD163 measured in the linear range of the assay (Table 4.4). For all analyses, concentrations below the LLOD, were imputed with half of the LLOD (43.5 pg/mL) prior to multiplication by the appropriate dilution factor (5). 2.7 Quantification of usCD25 The concentration of urine soluble (us)CD25 (pg/mL) in purified urine protein samples was quantified using a Human IL-2RA/CD25 ELISA Kit (Thermofisher, MA, USA; #EHIL2RAX5) as per the manufacturerâs instructions. Samples were diluted 2-, 5- or 10-fold (Table 4.3) in (1x) Assay Diluent B. All samples and standards were assayed in duplicate in a 96-well microplate. As described previously (see Section 2.6), the optical density (450 nm â 540 nm) was used to generate a four-parameter sigmoidal standard curve to determine the concentration of usCD25 in each sample. The experimental LLOD was 2.4 pg/mL, below which, usCD25 concentration was 28 imputed with half of the LLOD (1.2 pg/mL) prior to multiplication by the appropriate dilution factor (2, 5, or 10) (Table 4.4). 2.8 Quantification of uMCP-1 Urine (u)MCP-1 concentration (pg/mL) in purified urine protein samples was quantified using a Human CCL2/MCP-1 Quantikine ELISA Kit (R&D Systems, Minneapolis, MN, USA; #SCP00), according to the manufacturerâs instructions with a slight modification. Instead of 200 µL, as recommended by the manufacturer, 100 µL of standards and samples, diluted 5- or 10-fold in Calibrator Diluent RD5L (Table 4.3), were added to their respective wells in a 96-well microplate. In line with this, the volumes used of all reagents were also decreased to half of the amount suggested in the protocol (i.e., 100 µL of Human MCP-1 Conjugate, 100 µL of Substrate Solution, and 25 µL of Stop Solution added to each well). As described previously (see Section 2.6), the optical density (450 nm â 540 nm) was used to generate a four-parameter sigmoidal standard curve to determine the concentration of uMCP-1 in each sample. The LLOD was 4.0 pg/mL, and, where below the LLOD, uMCP-1 concentration was imputed with half of the LLOD (2.0 pg/mL) prior to multiplication by the appropriate dilution factor (5 or 10). 2.9 Statistical Analysis Analyses were performed using R (R Foundation for Statistical Computing, version 4.2.2, Vienna, Austria) and visualized using GraphPad Prism version 9.3.1 for MacOS (GraphPad Software, San Diego, CA). Data were presented as median Â± interquartile range (IQR) or mean ± 29 standard deviation (SD) for continuous variables and counts and percentages for categorical variables. Statistical models and tests used for various analyses and the corresponding baseline variables are provided in Table 2.2. All models were adjusted for potential confounding variables. These included biological sex assigned at birth, age at diagnosis (see Section 3.2), and, where appropriate, baseline disease activity and kidney function. Results are interpreted based on the size and direction of effect, and the uncertainty (confidence interval) rather than null hypothesis significance testing 90. In summary, (i) linear regression models were fit to investigate the association between ANCA status (the independent factor) and quantitative measures of overall (total pVAS) and kidney-specific (renal pVAS, eGFR) disease as dependent factors. Similarly, linear regression models were used to investigate the association between urine protein (usCD163 and usCD25) concentration and kidney-specific (renal pVAS, eGFR) disease. (ii) multivariable logistic regression models were also fit to evaluate associations between ANCA status and categorical measures of overall and organ-specific disease collected as part of the pVAS assessment, as well as overall disease outcome measures (inactive disease, improvement, damage, relapse). For these models, the adjusted odds ratios, 95% confidence interval (CI), and p-values were reported. The inverse odds ratio was calculated and reported where appropriate to improve clarity of comparisons. 30 (iii) Using eGFR, participants stratified by ANCA specificity were compared for KDIGO stage at diagnosis using an ordinal logistic regression model. Results from this model were presented as predicted probabilities of outcome level. (iv) To evaluate longitudinal changes between groups, linear mixed effects models (with random intercept for patients) for kidney function at diagnosis, 6-months post-diagnosis, and 12-months post-diagnosis were fit. These models were stratified by kidney function at diagnosis. Results were summarized as time-specific mean differences between groups (of ANCA positivity and specificity). Table 2.2 Summary of the statistical approach and primary comparisons of interest Tables/Figures Cohort/sample size Outcome Statistical analysis CHAPTER 3: The utility of ANCA seropositivity and antigen specificity in the assessment of overall disease activity and outcome in childhood-onset small vessel vasculitis. Shaded rows indicate primary comparisons of interest. Section 3.2 n = 406 â¢ ANCA-negative, n = 41 â¢ ANCA-positive, n = 365 o MPO-ANCA, n = 129 o PR3-ANCA, n = 236 Biological sex Logistic regression model was used to compare differences in sex distribution. Section 3.2 n = 406 â¢ ANCA-negative, n = 41 â¢ ANCA-positive, n = 365 o MPO-ANCA, n = 129 o PR3-ANCA, n = 236 Age at the time of diagnosis Shapiro-Wilk test was used to assess normality, followed by Kruskal-Wallis and Dunnâs multiple comparisons tests to evaluate differences in age at the time of diagnosis. Figure 3.1 Table 3.2 Dx, n = 398 â¢ ANCA-negative, n = 40 â¢ ANCA-positive, n = 358 o MPO-ANCA, n = 126 o PR3-ANCA, n = 232 Overall disease activity at the time of diagnosis defined by activity score (pVAS) Linear regression model adjusted for baseline variables (age at the time of diagnosis and biological sex) was used to measure mean differences in disease activity. Table 3.4 A 1yr follow up clinical data for n = 220 â¢ ANCA-negative, n = 17 â¢ ANCA-positive, n = 203 o MPO-ANCA, n = 74 Inactive disease at 1-year post-diagnosis defined by activity score (pVAS â¤ 1) Logistic regression models adjusted for baseline variables (age and total pVAS at the time of diagnosis, as well as 31 o PR3-ANCA, n = 129 biological sex) were used to compare differences in the proportion of children achieving inactive disease, improving, or accruing damage at 1-year post-diagnosis, or experiencing a relapse between 1- and 2-years post-diagnosis. Table 3.4 B Table 3.4 C 1yr follow up clinical data for n = 215 â¢ ANCA-negative, n = 16 â¢ ANCA-positive, n = 199 o MPO-ANCA, n = 72 o PR3-ANCA, n = 127 Improvement at 1-year post-diagnosis defined by reduction in the activity score (pVAS) from the time of diagnosis Table 3.4 D 1yr follow up clinical data for n = 203 â¢ ANCA-negative, n = 15 â¢ ANCA-positive, n = 188 o MPO-ANCA, n = 67 o PR3-ANCA, n = 121 Damage at 1-year post-diagnosis defined by damage index (pVDI â¥ 1) Table 3.4 E 1yr follow up clinical data for n = 150 â¢ ANCA-negative, n = 14 â¢ ANCA-positive, n = 136 o MPO-ANCA, n = 51 o PR3-ANCA, n = 85 Relapse between 1- and 2-years post-diagnosis defined by the change in the activity score (pVAS) alongside relapses noted by the treating physician Table 3.5 Dx, n = 384 â¢ ANCA-negative, n = 40 â¢ ANCA-positive, n = 344 o MPO-ANCA, n = 121 o PR3-ANCA, n = 223 Treatment for remission-induction using one or more of the following medications: cyclophosphamide, rituximab, azathioprine, methotrexate Logistic regression models were used to compare differences in the proportion of children being treated with a given medication for remission-induction and remission-maintenance. Table 3.6 1yr follow up clinical data for n = 223 â¢ ANCA-negative, n = 15 â¢ ANCA-positive, n = 208 o MPO-ANCA, n = 79 o PR3-ANCA, n = 129 Treatment for remission-maintenance using one or more of the following medications: cyclophosphamide, rituximab, azathioprine, methotrexate Figure 3.2 Table 3.7 Dx, n = 398 â¢ ANCA-negative, n = 40 â¢ ANCA-positive, n = 358 o MPO-ANCA, n = 126 o PR3-ANCA, n = 232 Organ involvement and the presence/absence of clinical characteristics at the time of diagnosis as recorded in the activity score (pVAS) assessment form by the treating physician Logistic regression models adjusted for baseline variables (age at the time of diagnosis and biological sex) were used to assess differences in the organ system(s) involved and clinical characteristics present at diagnosis. 32 CHAPTER 4: The utility of ANCA and urine proteins (usCD163, usCD25, uMCP-1) in identifying active disease in the kidneys in childhood-onset small vessel vasculitis. Shaded rows indicate primary comparisons of interest. Figure 4.1 A Dx, n = 401 â¢ ANCA-negative, n = 43 â¢ ANCA-positive, n = 358 o MPO-ANCA, n = 126 o PR3-ANCA, n = 232 Kidney disease activity at the time of diagnosis defined by the renal subcomponent of the activity score (renal pVAS) Linear regression models adjusted for baseline variables (age at the time of diagnosis and biological sex) were used to measure mean differences in kidney disease activity and function at diagnosis. Figure 4.1 B Figure 4.1 C Dx, n = 123 â¢ MPO-ANCA, n = 39 â¢ PR3-ANCA, n = 84 Dx, n = 82 (with biopsy-proven glomerulonephritis) â¢ MPO-ANCA, n = 37 â¢ PR3-ANCA, n = 45 Kidney function at the time of diagnosis defined by the estimated glomerular filtration rate (eGFR) Figure 4.1 D Table 4.2 Dx, n = 123 â¢ MPO-ANCA, n = 39 â¢ PR3-ANCA, n = 84 Kidney function at the time of diagnosis categorized (based on eGFR) according to KDIGO guidelines Ordinal logistic regression model adjusted for baseline variables (age at the time of diagnosis and biological sex) were used to compare the probability of being assigned to specific KDIGO stages at diagnosis. Figure 4.2 Table 4.3 Dx, n = 123 â¢ KDIGO stages 1-2 o MPO-ANCA, n = 13 o PR3-ANCA, n = 61 â¢ KDIGO stage 3 o MPO-ANCA, n = 4 o PR3-ANCA, n = 12 â¢ KDIGO stages 4-5 o MPO-ANCA, n = 22 o PR3-ANCA, n = 11 6-months follow-up, n = 103 â¢ KDIGO stages 1-2 o MPO-ANCA, n = 13 o PR3-ANCA, n = 49 â¢ KDIGO stage 3 o MPO-ANCA, n = 3 o PR3-ANCA, n = 11 â¢ KDIGO stages 4-5 o MPO-ANCA, n = 17 o PR3-ANCA, n = 10 12-months follow-up, n = 95 Change in kidney function (eGFR) from diagnosis to 6- and 12-months follow-up Linear mixed effects model, adjusted for baseline variables (eGFR and age at the time of diagnosis, alongside biological sex), were used to compare changes in eGFR from diagnosis to follow-up at 6- and 12-months post-diagnosis. 33 â¢ KDIGO stages 1-2 o MPO-ANCA, n = 12 o PR3-ANCA, n = 47 â¢ KDIGO stage 3 o MPO-ANCA, n = 4 o PR3-ANCA, n = 9 â¢ KDIGO stages 4-5 o MPO-ANCA, n = 16 o PR3-ANCA, n = 7 Figure 4.3 â¢ Renal SVV, n = 52 â¢ Non-Renal SVV, n = 10 â¢ LVV, n = 11 â¢ Healthy adults, n = 20 Absolute and normalized (to total urine protein) concentration of usCD163 and usCD25 Kruskal-Wallis tests, followed by Dunnâs multiple comparison tests, and Mann-Whitney U tests were used to compare absolute and normalized, respectively, concentrations of usCD163 and usCD25. Figure 4.4 A Figure 4.4 B â¢ Renal SVV with detected usCD163 and available data for renal pVAS at Dx, n = 25 â¢ Renal SVV with detected usCD25 and available data for renal pVAS at Dx, n = 29 Normalized concentration of usCD163 or usCD25 and kidney disease activity (renal pVAS) at the time of diagnosis Linear regression models adjusted for baseline variables (age at diagnosis and biological sex) were used to evaluate the association between normalized urine protein concentrations and kidney disease activity at diagnosis. Figure 4.4 C Figure 4.4 D â¢ Renal SVV with detected usCD163 and available data for renal pVAS at both Dx and 1-year post-diagnosis, n = 20 â¢ Renal SVV with detected usCD25 and available data for renal pVAS at both Dx and 1-year post-diagnosis, n = 19 Normalized concentration of usCD163 or usCD25 and improvement in kidney disease activity (decrease in renal pVAS) from diagnosis to 1-year post-diagnosis Linear regression models adjusted for baseline variables (age at diagnosis and biological sex) were used to evaluate the association between normalized urine protein concentrations and the improvement in kidney disease activity from diagnosis to 1-year post-diagnosis. Figure 4.5 â¢ Renal SVV with detected usCD163 and available data for eGFR at Dx, n = 14 o Normal to mildly reduced kidney function, n = 7 o Moderately to severely reduced kidney function, n = 7 â¢ Renal SVV with detected usCD25 and available data for eGFR at Dx, n = 17 Normalized concentration of usCD163 or usCD25 and kidney function at the time of diagnosis defined by eGFR and categorized (based on eGFR) according to KDIGO guidelines Linear regression models adjusted for baseline variables (age at diagnosis and biological sex) were used to evaluate the association between normalized urine protein concentrations and kidney function at diagnosis. 34 o Normal to mildly reduced kidney function, n = 9 o Moderately to severely reduced kidney function, n = 8 Figure 4.6 â¢ Renal SVV with detected usCD163 and available data for eGFR at 1-year post-diagnosis, n = 16 â¢ Renal SVV with detected usCD25 and available data for eGFR at 1-year post-diagnosis, n = 15 Normalized concentration of usCD163 or usCD25 and kidney function at 1-year post-diagnosis defined by eGFR Linear regression models adjusted for baseline variables (age at diagnosis and biological sex) were used to evaluate the association between normalized urine protein concentrations and kidney function at 1-year post-diagnosis. 35 Chapter 3: The utility of ANCA seropositivity and antigen specificity in the assessment of overall disease activity and outcome in childhood-onset small vessel vasculitis 3.1 Rationale and introduction Due to the rarity of AAV in childhood, most knowledge of the disease is derived from the study of adult-onset AAV. Studies in adults have demonstrated that the presence and specificity of circulating autoantibodies (ANCA towards MPO or PR3) can be used as biomarkers to predict disease severity, outcomes, and risk for relapse 62,91. PR3-ANCA seropositivity is associated with multi-organ involvement, frequently the lungs 62,92,93, and a higher rate of relapse 62 that is more responsive to treatment with rituximab rather than cyclophosphamide 27,94. In contrast, MPO-ANCA seropositive AAV in adults typically presents with disease limited to the kidneys, which is more severe at presentation; for these individuals, cyclophosphamide may be preferred for remission-induction instead of rituximab 95. The primary outcomes of interest were organ involvement, specifically kidney involvement, at the time of diagnosis, and the likelihood of having a relapse between 1- and 2-years post-diagnosis. In addition to this, the secondary outcomes of interest included overall disease activity at diagnosis, as well as overall disease outcomes such as the achievement of inactive disease, exhibiting improvements in the disease, and accruing permanent damage at 1-year post-diagnosis. I hypothesized that the utility of ANCA seropositivity and specificity (for MPO or PR3) as biomarkers for assessing overall disease activity and outcomes in childhood-onset SVV, inclusive of AAV, will mirror their use in adults; namely, children with ANCA against PR3 will have the highest overall disease activity at diagnosis, characterized by the involvement of 36 multiple organ systems, and worse outcomes at 1- to 2-years post diagnosis. Children with ANCA against MPO, on the other hand, will be more likely to present with kidney-limited disease. 3.2 Study cohort The study cohort consisted of (n = 406) children enrolled in the ARChiVe/PedVas study with a diagnosis of chronic primary SVV (see Section 2.1.1) and complete clinical data for ANCA status (seropositivity and specificity), age at diagnosis, and biological sex. In this cohort, ANCA status, as recorded in the ARChiVe/PedVas registry, was measured by participating study sites commonly with an ELISA (for 392/406 cases) or by indirect immunofluorescence (for 14/406 cases). Detailed characteristics of this cohort can be found in Table 3.1. Briefly, 58% (n = 236) of children were PR3-ANCA seropositive, 32% (n = 129) of children were MPO-ANCA seropositive and 10% (n = 41) were seronegative for ANCA against either autoantigen. The majority of children were Caucasian (53%, 214/406) and female (68%, 278/406), reflecting known sex-specific variations in the incidence of childhood-onset SVV 3,4,96. There was a significant association between biological sex and ANCA status (p < 0.001), with MPO-ANCA seropositive children 2.53 (95% CI: 1.55 to 4.25) times more likely to be female compared to PR3-ANCA seropositive children. The median age at diagnosis was 14.0 years (IQR: 11.0 â 16.0) across the entire cohort. Notably, MPO-ANCA seropositive children were also significantly younger at diagnosis compared to children with PR3-ANCA (p < 0.001). 37 Table 3.1 Demographic and clinical characteristics of the SVV cohort ANCA Status All (n = 406) ANCA-negative (n = 41) MPO-ANCA (n = 129) PR3-ANCA (n = 236) Age at diagnosis, median (IQR) years 14.0 (11.0 â 16.0) 14.0 (12.0 â 16.0) 12.0 (9.0 â 15.0) 15.0 (13.0 â 16.0) Sex, Female 278 (68.5) 31 (75.6) 103 (79.8) 144 (61.0) Ethnicity Native American/First Nations 9 (2.2) 1 (2.4) 6 (4.7) 2 (0.8) Asian 12 (3.0) 1 (2.4) 5 (3.9) 6 (2.5) Black 9 (2.2) 2 (4.9) 4 (3.1) 3 (1.3) Caucasian/White 214 (52.7) 19 (46.3) 55 (42.6) 140 (59.3) East Indian/South Asian 27 (6.7) 0 (0.0) 5 (3.9) 22 (9.3) Hispanic/Latino 24 (5.9) 2 (4.9) 16 (12.4) 6 (2.5) Middle Eastern 5 (1.2) 2 (4.9) 1 (0.8) 2 (0.8) Other/Mixed 43 (10.6) 7 (17.1) 15 (11.6) 21 (8.9) Unknown 63 (15.5) 7 (17.1) 22 (17.1) 34 (14.4) SVV Subtype Granulomatosis with Polyangiitis (GPA; formerly Wegener's Granulomatosis) 251 (61.8) 7 (17.1) 33 (25.6) 211 (89.4) Limited GPA 31 (7.6) 7 (17.1) 9 (7.0) 15 (6.4) Microscopic polyangiitis (MPA) 56 (13.8) 1 (2.4) 52 (40.3) 3 (1.3) MPA with isolated renal involvement 10 (2.5) 1 (2.4) 8 (6.2) 1 (0.4) ANCA positive pauci-immune glomerulonephritis 22 (5.4) 0 (0.0) 17 (13.2) 5 (2.1) Unclassified primary vasculitis 36 (8.9) 25 (61.0) 10 (7.8) 1 (0.4) *Unless indicated otherwise, values refer to the absolute number (%) of patients in the given category. IQR: Interquartile Range 38 Previous research shows that age at diagnosis and biological sex are associated with differences in disease presentation and outcomes in individuals with SVV 97,98. Given the differences in demographics between MPO-ANCA and PR3-ANCA seropositive children in this cohort, it was important to consider both of the aforementioned variables as potential confounders in my analyses. Therefore, multivariable linear and logistic regression models, adjusted for age at diagnosis and biological sex, were fit to investigate the association between ANCA status, and continuous and categorical measures of overall disease, respectively, in childhood-onset SVV. For detailed information regarding the statistical tests and models used, as well as the baseline variables considered for each, please refer to Table 2.2. 3.3 Results 3.3.1 ANCA seropositivity is associated with higher overall disease activity at diagnosis. A score of overall disease activity (total pVAS) at diagnosis was available from n = 398 children, including those who were ANCA seronegative, n = 40; MPO-ANCA seropositive, n = 126; and PR3-ANCA seropositive, n = 232. Across the entire cohort, the median total pVAS was 18.0 (IQR: 12.0 â 22.0). Children with ANCA seropositivity had a significantly higher mean pVAS compared to seronegative patients (mean difference: 6.67, 95% CI: 4.17 to 9.16, p < 0.001). Among the ANCA seropositive patients, however, no significant differences in disease activity were observed between MPO-ANCA and PR3-ANCA seropositive cases (mean difference: 1.15, 95% CI: -0.59 to 2.89, p = 0.195) (Figure 3.1 and Table 3.2). 39 Figure 3.1 Overall disease activity (total pVAS) at diagnosis in childhood-onset SVV stratified by ANCA status A linear regression model adjusted for age at the time of diagnosis and biological sex was used to compare overall disease activity, quantified by the total pVAS (y-axis), at diagnosis in n = 398 children with SVV (x-axis) stratified according to the absence (ANCA -, n = 40) or presence (ANCA +, n = 358) of ANCA as well as specificity of ANCA towards MPO (MPO-ANCA, n = 126) and PR3 (PR3-ANCA, n = 232). Data are presented as boxplots showing the median (solid line) and interquartile range (IQR). See Table 3.2 for mean differences. Table 3.2 Differences in overall disease activity (total pVAS) at diagnosis between childhood-onset SVV stratified by ANCA status Mean Total pVAS ± SD Mean Difference (95% CI) P-value ANCA-Positive vs. ANCA-Negative 18.3 ± 7.7 vs. 11.7 ± 7.5 6.67 (4.17, 9.16) <0.001 MPO-ANCA vs. ANCA-Negative 17.2 ± 6.4 vs. 11.7 ± 7.5 5.91 (3.17, 8.65) <0.001 PR3-ANCA vs. ANCA-Negative 19.0 ± 8.2 vs. 11.7 ± 7.5 7.06 (4.50, 9.62) <0.001 PR3-ANCA vs. MPO-ANCA 19.0 ± 8.2 vs. 17.2 ± 6.4 1.15 (-0.59, 2.89) 0.195 40 3.3.2 Disease states within 2-years of diagnosis do not differ by ANCA seropositivity or specificity Given that ANCA seropositive children exhibited higher disease activity at the time of diagnosis, I questioned if these individuals may also experience different overall outcomes such as sustained disease activity and/or greater accrual of damage within the first 1 to 2 years of diagnosis. The overall outcomes of interest that could be assessed using the available data included the achievement of inactive disease, exhibiting improvements in the disease, and the presence of damage at 1-year post-diagnosis, as well as the occurrence of relapses between 1- and 2-years post-diagnosis. Definitions of overall outcome measures are provided in Table 3.3. Table 3.3 Definitions of disease states used to assess overall outcomes in SVV Disease State Definition Inactive Disease No disease activity (pVAS â¤ 1) Improvement Decrease in pVAS (relative to diagnosis) of at least 50% or 70% by 1-year post-diagnosis Damage Quantified by pVDI, where pVDI â¥ 1 indicates damage Relapse An increase in total pVAS from 0 to â¥ 2 or 1 to â¥ 4 from 1- to 2-years post-diagnosis, alongside relapses noted by the treating physician during this time interval Of the 406 children in the cohort, 220 children with 1- to 2-year follow up data were available for analysis, representing 54% of the cohort. In sum, there were no significant differences in any of the outcome measures between children stratified by their ANCA status. Data are provided in Table 3.4 and described herein in brief. 41 Within the cohort, 68% (150/220) of children had inactive disease, defined by the total pVAS â¤ 1, at 1-year post-diagnosis. When stratifying children by ANCA status, 67% (136/203) of children who were seropositive for ANCA against either MPO or PR3, and 82% (14/17) of children who were seronegative for ANCA against both autoantigens had achieved inactive disease by 1-year post-diagnosis. There was no significant difference between children seropositive or seronegative for ANCA in the likelihood of achieving inactive disease (ANCA-positive vs. ANCA-negative, adjusted odds ratio [AOR]: 0.47, 95% CI: 0.10 to 0.59, p = 0.26) (Table 3.4 A). Similarly, within the ANCA seropositive subgroup, 66% (85/129) of PR3-ANCA seropositive and 69% (51/74) of MPO-ANCA seropositive children had achieved inactive disease at 1-year post-diagnosis with no significant difference in the likelihood of doing so (PR3-ANCA vs. MPO-ANCA, AOR: 0.93, 95% CI: 0.48 to 1.78, p = 0.75). Improvement, defined as per EULAR guidelines as a 50% or greater reduction in overall disease activity (i.e., total pVAS) from diagnosis to 1-year post-diagnosis, was observed in a majority (96%, 206/215) of children. Even when divided by ANCA seropositivity and specificity, more than 93% of children in each subgroup exhibited at least a 50% improvement in the disease. When applying a more stringent definition of improvement requiring a reduction of at least 70% in the total pVAS from diagnosis to 1-year post-diagnosis, 87% (187/215) of children exhibited improvements. Regardless of the threshold for improvement, the likelihood of improving (â¥ 50% and â¥ 70% decline in disease activity) was similar for children stratified by ANCA seropositivity and specificity (Table 3.4 B and C). 42 Among the participants studied, 58% (117/203) of children had indications of permanent damage by 1-year post-diagnosis. The proportion of children with damage at this time was higher for children who were seropositive for either MPO-ANCA (58%, 39/67) or PR3-ANCA (60%, 72/121) compared to those who were seronegative for ANCA against both autoantigens (40%, 6/15). However, the adjusted odds ratios had wide confidence intervals, suggesting uncertainty in these conclusions (e.g., MPO-ANCA vs. ANCA-negative, AOR: 2.27, 95% CI; 0.70 to 7.84, p = 0.18) (Table 3.4 D). Across the entire cohort, a total of 16 children experienced a relapse between 1- to 2-years after diagnosis. The vast majority (n = 15/16) of these children were ANCA seropositive with relapses noted in 12% (6/51) of MPO-ANCA seropositive cases and 11% (9/85) of PR3-ANCA seropositive cases. Thus, the likelihood of having a relapse 1- to 2-years after diagnosis did not differ significantly among children stratified by ANCA specificity (Table 3.4 E). 43 Table 3.4 Overall outcomes between 1- and 2-years post-diagnosis in childhood-onset SVV stratified by ANCA status Overall outcomes1 % (n) Adjusted OR (95% CI) P-value Adjusted OR (95% CI) P-value (A) Inactive Disease at 1-year All participants 68.2 (150/220) ANCA-negative 82.4 (14/17) Reference - 2.06 (0.57, 9.85) 0.67 ANCA-positive 67.0 (136/203) 0.47 (0.10, 1.59) 0.26 - - MPO-ANCA 68.9 (51/74) 0.49 (0.10, 1.75) 0.31 Reference - PR3-ANCA 65.9 (85/129) 0.745 (0.10, 1.60) 0.26 0.93 (0.48, 1.78) 0.75 (B) Improvement (â¥ 50%) at 1-year All participants 95.8 (206/215) ANCA-negative 93.8 (15/16) Reference - 1.66 (0.17, 39.73) 0.69 ANCA-positive 96.0 (191/199) 0.59 (0.03, 4.84) 0.67 - - MPO-ANCA 94.4 (68/72) 0.60 (0.03, 5.81) 0.69 Reference - PR3-ANCA 96.9 (123/127) 0.58 (0.02, 5.72) 0.67 0.96 (0.20, 4.43) 0.95 (C) Improvement (â¥ 70%) at 1-year All participants 87.0 (187/215) ANCA-negative 93.8 (15/16) Reference - 3.89 (0.61, 77.24) 0.23 ANCA-positive 86.4 (172/199) 0.25 (0.01, 1.45) 0.20 - - MPO-ANCA 84.7 (61/72) 0.26 (0.01, 1.64) 0.23 Reference - PR3-ANCA 87.4 (111/127) 0.24 (0.01, 1.48) 0.20 0.92 (0.37, 2.21) 0.85 44 (D) Damage at 1-year All participants 57.6 (117/203) ANCA-negative 40.0 (6/15) Reference - 0.44 (0.13, 1.43) 0.18 ANCA-positive 59.0 (111/188) 2.01 (0.66, 6.49) 0.22 - - MPO-ANCA 58.2 (39/67) 2.27 (0.70, 7.84) 0.18 Reference - PR3-ANCA 59.5 (72/121) 1.86 (0.59, 6.16) 0.29 0.82 (0.42, 1.58) 0.55 (E) Relapse between 1 and 2 years All participants 10.7 (16/150) ANCA-negative 7.1 (1/14) Reference - 0.71 (0.03, 5.22) 0.77 ANCA-positive 11.0 (15/136) 1.52 (0.24, 30.00) 0.71 - - MPO-ANCA 11.8 (6/51) 1.41 (0.19, 29.03) 0.77 Reference - PR3-ANCA 10.6 (9/85) 1.64 (0.23, 33.44) 0.67 1.16 (0.36, 3.96) 0.80 âReferenceâ indicates the reference group to which the odds ratios are being compared. Abbreviations: OR: odds ratio, CI: confidence interval. 1Outcomes defined in Table 3.3 45 Since disease outcomes reflect treatment responsiveness, I questioned if there was an association between ANCA specificity and treatment using cyclophosphamide, rituximab, azathioprine, and methotrexate. In this cohort, cyclophosphamide was the most commonly administered medication for remission-induction regardless of ANCA status, with approximately 64% of the cohort, or 243 children, receiving this treatment. When evaluating the association between ANCA specificity and treatment, the odds of receiving cyclophosphamide (AOR: 1.20, 95% CI: 0.75 to 1.92, p = 0.434), rituximab (AOR: 0.79, 95% CI: 0.47 to 1.34, p = 0.374), azathioprine (AOR: 1.27, 95% CI: 0.35 to 6.00, p = 0.729), and methotrexate (AOR: 1.68, 95% CI: 0.84 to 3.60, p = 0.162) for remission-induction were similar for children who were seropositive for MPO-ANCA compared to those who were seropositive for PR3-ANCA (Table 3.5). With respect to treatment for remission-maintenance, azathioprine was the most commonly administered medication for both MPO-ANCA (33%, 26/79) and PR3-ANCA seropositive (44%, 57/129) children, whereas methotrexate was used slightly more than azathioprine for ANCA seronegative patients (33%, 5/15). When evaluating the association between ANCA status and treatment for remission-maintenance, the odds of receiving cyclophosphamide, rituximab, or azathioprine were similar across groups, but the odds of receiving methotrexate (AOR: 2.57, 95% CI: 1.16 to 6.34, p = 0.027) were slightly higher for children who were seropositive for PR3-ANCA (Table 3.6). These findings, combined with the similarities in disease outcomes between MPO-ANCA and PR3-ANCA seropositive children, suggest that methotrexate is not more or less effective for remission-maintenance compared to the other medications studied. 46 Table 3.5 Treatment for remission-induction in childhood-onset SVV stratified by ANCA status ANCA Status PR3-ANCA vs. MPO-ANCA All (n = 384) ANCA-negative (n = 40) MPO-ANCA (n = 121) PR3-ANCA (n = 223) Adjusted OR (95% CI) P-value Cyclophosphamide 243 (63.3) 12 (30.0) 78 (64.5) 153 (68.6) 1.20 (0.75, 1.92) 0.434 Rituximab 78 (20.3) 2 (5.0) 30 (24.8) 46 (20.6) 0.79 (0.47, 1.34) 0.374 Azathioprine 11 (2.9) 1 (2.5) 3 (2.5) 7 (3.1) 1.27 (0.35, 6.00) 0.729 Methotrexate 51 (13.3) 8 (20.0) 11 (9.1) 32 (14.3) 1.68 (0.84, 3.60) 0.162 Data are presented as the absolute number (%) of individuals in a given category. Abbreviations: OR: odds ratio, CI: confidence interval Table 3.6 Treatment for remission-maintenance (1-year) in childhood-onset SVV stratified by ANCA status ANCA Status PR3-ANCA vs. MPO-ANCA All (n = 223) ANCA-negative (n = 15) MPO-ANCA (n = 79) PR3-ANCA (n = 129) Adjusted OR (95% CI) P-value Cyclophosphamide 51 (22.9) 3 (20.0) 21 (26.6) 27 (20.9) 0.73 (0.38, 1.42) 0.349 Rituximab 54 (24.2) 3 (20.0) 24 (30.4) 27 (20.9) 0.61 (0.32, 1.15) 0.126 Azathioprine 87 (39.0) 4 (26.7) 26 (32.9) 57 (44.2) 1.61 (0.91, 2.92) 0.108 Methotrexate 42 (18.8) 5 (33.3) 8 (10.1) 29 (22.5) 2.57 (1.16, 6.34) 0.027 Data are presented as the absolute number (%) of individuals in a given category. Abbreviations: OR: odds ratio, CI: confidence interval 3.3.3 MPO-ANCA seropositivity is associated with a higher prevalence of kidney involvement and a lower prevalence of ENT involvement than PR3-ANCA seropositivity Although overall disease activity at onset and 1- to 2-year outcomes were similar between children seropositive for MPO-ANCA versus PR3-ANCA, I sought to assess the potential phenotypic differences in organ involvement related to ANCA antigen positivity and specificity (Figure 3.2 and Table 3.7). Information regarding the organ system(s) involved at the time of 47 diagnosis, and the presence or absence of associated clinical characteristics, were recorded categorically by the treating physician using the pVAS assessment form. Kidney involvement was noted in a majority of children with MPO-ANCA (88%, 111/126) and PR3-ANCA (77%, 179/232), as well as half of the children with ANCA-negative vasculitis (50%, 20/40) (Figure 3.2 and Table 3.7). Compared to ANCA-negative vasculitis cases, the adjusted odds of children having kidney involvement were 7.8 (95% CI: 3.4 â 18.5, p < 0.001) and 3.3 (95% CI: 1.6 â 6.6, p < 0.001) times higher in those with MPO-ANCA and PR3-ANCA, respectively. Additionally, the adjusted odds of kidney involvement were 2.4 (95% CI: 1.3 â 4.7, p = 0.008) times higher in children who were seropositive for MPO-ANCA versus PR3-ANCA. This was attributable to certain clinical manifestations, specifically hypertension, proteinuria, and hematuria/presence of red blood cell casts. Conversely, the odds of ear, nose, and throat (ENT) involvement were highest in PR3-ANCA seropositive children (PR3-ANCA vs. ANCA-negative, AOR: 5.6, 95% CI: 2.7 â 12.0, p < 0.001; PR3-ANCA vs. MPO-ANCA, AOR: 5.6, 95% CI: 3.3 â 9.1, p < 0.001), characterized by significantly higher adjusted odds of bloody nasal discharge/crusts/ulcers/granuloma, paranasal sinus involvement, and conductive hearing loss (Figure 3.2 and Table 3.7). PR3-ANCA positive children also had 2.6 (95% CI: 1.5 â 4.3, p < 0.001) times the adjusted odds of mucous membranes/ocular involvement, which was predominantly characterized by the presence of mouth ulcers/granulomata, compared to MPO-ANCA seropositive cases. 48 Figure 3.2 Time of diagnosis organ involvement associated with ANCA positivity and specificity A logistic regression model adjusted for age at the time of diagnosis and biological sex was used to evaluate differences in organ involvement (y-axis; organ system) at diagnosis between children stratified by ANCA status (ANCA negative, n = 40; MPO-ANCA, n = 126; PR3-ANCA, n = 232). (A) PR3-ANCA seropositivity and (B) MPO-ANCA seropositivity are compared to ANCA seronegative cases. (C) MPO-ANCA seropositive and PR3-ANCA seropositive cases are compared. Data are presented as forest plots with the odds ratio (x-axis, logarithmic scale) and 95% CI. 49 Table 3.7 Organ involvement and clinical characteristics associated with ANCA type in childhood-onset SVV at diagnosis Logistic Regression Model % (n) PR3-ANCA vs ANCA-Negative MPO-ANCA vs ANCA-Negative MPO-ANCA vs PR3-ANCA ANCA-Negative (n = 40) MPO-ANCA (n = 126) PR3-ANCA (n = 232) Adjusted OR (95% CI) P-value Adjusted OR (95% CI) P-value Adjusted OR (95% CI) P-value Constitutional involvement 47.5 (19) 62.7 (79) 76.7 (178) 3.77 (1.88, 7.62) <0.001 1.82 (0.88, 3.79) 0.109 0.48 (0.29, 0.80) 0.004 Myalgia 12.5 (5) 15.9 (20) 16.8 (39) 1.41 (0.56, 4.33) 0.475 1.47 (0.54, 4.73) 0.475 1.04 (0.55, 1.92) 0.893 Arthralgia or arthritis 42.5 (17) 38.1 (48) 60.8 (141) 2.22 (1.12, 4.47) 0.023 0.88 (0.42, 1.84) 0.722 0.39 (0.24, 0.63) <0.001 Fever â¥ 38°C 27.5 (11) 23.0 (29) 32.8 (76) 1.28 (0.62, 2.82) 0.522 0.68 (0.30, 1.60) 0.366 0.53 (0.31, 0.90) 0.021 Weight loss â¥ 5% of weight 15.0 (6) 29.4 (37) 43.1 (100) 4.19 (1.80, 11.48) 0.002 2.70 (1.09, 7.68) 0.043 0.64 (0.39, 1.04) 0.075 Cutaneous involvement 37.5 (15) 31.0 (39) 46.1 (107) 1.46 (0.74, 2.99) 0.281 0.77 (0.37, 1.67) 0.506 0.53 (0.32, 0.85) 0.009 Polymorphous exanthema 2.5 (1) 4.8 (6) 9.5 (22) 4.10 (0.82, 74.62) 0.174 1.82 (0.29, 35.24) 0.587 0.44 (0.15, 1.12) 0.104 Livedo 0.0 (0) 3.2 (4) 2.6 (6) - - - - 0.89 (0.21, 3.31) 0.858 Panniculitis 7.5 (3) 3.2 (4) 0.4 (1) 0.06 (2.80e-03, 0.47) 0.015 0.46 (0.09, 2.50) 0.337 8.00 (1.12, 160.57) 0.069 Purpura 22.5 (9) 13.5 (17) 32.8 (76) 1.69 (0.79, 3.95) 0.194 0.54 (0.22, 1.40) 0.189 0.32 (0.17, 0.58) <0.001 Skin nodules 7.5 (3) 4.0 (5) 8.6 (20) 1.16 (0.37, 5.16) 0.816 0.62 (0.14, 3.15) 0.524 0.53 (0.17, 1.39) 0.228 Infarct (nail edge lesion, splinter hemorrhage) 2.5 (1) 1.6 (2) 5.2 (12) 2.14 (0.39, 39.77) 0.476 0.80 (0.07, 17.73) 0.861 0.38 (0.06, 1.46) 0.214 Ulcer (full-thickness necrosis) 0.0 (0) 0.8 (1) 3.4 (8) - - - - 0.21 (0.01, 1.21) 0.147 Gangrene (extensive necrosis) 0.0 (0) 0.0 (0) 1.3 (3) - - - - - - Other skin vasculitis 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Mucous membranes/ocular involvement 27.5 (11) 20.6 (26) 39.2 (91) 1.69 (0.82, 3.71) 0.165 0.67 (0.30, 1.57) 0.337 0.39 (0.23, 0.66) <0.001 Mouth ulcers/granulomata 0.0 (0) 4.0 (5) 18.5 (43) - - - - 0.18 (0.06, 0.45) <0.001 50 Genital ulcers 0.0 (0) 0.8 (1) 0.4 (1) - - - - 1.51 (0.06, 40.10) 0.777 Adnexal inflammation 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Significant proptosis 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Red eye (epi)scleritis 5.0 (2) 3.2 (4) 10.8 (25) 2.02 (0.56, 12.97) 0.356 0.75 (0.14, 5.60) 0.745 0.37 (0.10, 1.02) 0.079 Red eye conjunctivitis/blepharitis/keratitis 7.5 (3) 6.3 (8) 12.5 (29) 1.61 (0.53, 7.02) 0.453 0.83 (0.22, 4.02) 0.800 0.52 (0.21, 1.18) 0.134 Uveitis 5.0 (2) 0.0 (0) 3.9 (9) 0.67 (0.16, 4.57) 0.623 - - - - Blurred vision 15.0 (6) 4.8 (6) 3.0 (7) 0.18 (0.06, 0.61) 0.004 0.30 (0.09, 1.05) 0.056 1.65 (0.50, 5.29) 0.394 Sudden visual loss 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Retinal vasculitis/retinal vessel thrombosis/retinal exudates/hemorrhages 0.0 (0) 0.0 (0) 0.4 (1) - - - - - - ENT involvement 30.0 (12) 27.8 (35) 70.3 (163) 5.55 (2.71, 12.01) <0.001 1.00 (0.46, 2.28) 0.991 0.18 (0.11, 0.30) <0.001 Bloody nasal discharge/crusts/ulcers/granuloma 12.5 (5) 15.9 (20) 54.3 (126) 8.29 (3.40, 24.88) <0.001 1.45 (0.54, 4.65) 0.490 0.18 (0.10, 0.30) <0.001 Paranasal sinus involvement 10.0 (4) 15.1 (19) 37.9 (88) 5.88 (2.24, 20.28) 0.001 1.80 (0.62, 6.56) 0.319 0.31 (0.17, 0.54) <0.001 Subglottic stenosis/hoarseness/stridor 12.5 (5) 4.8 (6) 8.6 (20) 0.69 (0.25, 2.19) 0.483 0.41 (0.11, 1.52) 0.165 0.60 (0.21, 1.49) 0.298 Conductive hearing loss 0.0 (0) 1.6 (2) 12.1 (28) - - - - 0.13 (0.02, 0.46) 0.007 Sensorineural hearing loss 2.5 (1) 1.6 (2) 3.0 (7) 1.13 (0.19, 21.65) 0.912 0.82 (0.08, 17.97) 0.870 0.72 (0.10, 3.19) 0.695 Chest involvement 30.0 (12) 43.7 (55) 49.6 (115) 2.20 (1.08, 4.70) 0.034 1.95 (0.92, 4.36) 0.090 0.89 (0.56, 1.41) 0.616 Wheeze or expiratory dyspnea 7.5 (3) 7.9 (10) 7.8 (18) 0.97 (0.31, 4.33) 0.968 1.18 (0.33, 5.53) 0.811 1.21 (0.50, 2.79) 0.658 Endobronchial/endotracheal involvement 5.0 (2) 0.8 (1) 3.0 (7) 0.65 (0.15, 4.48) 0.596 0.17 (0.01, 1.81) 0.150 0.26 (0.01, 1.53) 0.212 Nodules or cavities 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - 51 Pleural effusion/pleurisy 7.5 (3) 10.3 (13) 9.9 (23) 1.35 (0.44, 5.93) 0.641 1.67 (0.50, 7.67) 0.445 1.24 (0.57, 2.60) 0.574 Infiltrate 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Massive hemoptysis/alveolar hemorrhage 15.0 (6) 28.6 (36) 34.9 (81) 2.83 (1.21, 7.77) 0.026 2.39 (0.97, 6.84) 0.076 0.85 (0.51, 1.39) 0.513 Respiratory failure 12.5 (5) 5.6 (7) 12.1 (28) 0.88 (0.34, 2.73) 0.799 0.46 (0.14, 1.66) 0.215 0.53 (0.20, 1.23) 0.159 Cardiovascular involvement 12.5 (5) 0.8 (1) 3.4 (8) 0.25 (0.08, 0.89) 0.024 0.04 (1.90e-03, 0.27) 0.005 0.15 (0.01, 0.93) 0.088 Loss of pulses 2.5 (1) 0.0 (0) 0.9 (2) 0.29 (0.03, 6.44) 0.323 - - - - Bruits over accessible arteries 0.0 (0) 0.0 (0) 0.9 (2) - - - - - - Blood pressure discrepancy 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Caudication of extremities 5.0 (2) 0.0 (0) 0.9 (2) 0.17 (0.02, 1.50) 0.087 - - - - Ischaemic cardiac pain 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Cardiomyopathy 5.0 (2) 0.0 (0) 0.0 (0) - - - - - - Congestive cardiac failure 2.5 (1) 0.0 (0) 0.0 (0) - - - - - - Valvular heart disease 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Pericarditis 5.0 (2) 0.8 (1) 1.3 (3) 0.27 (0.04, 2.13) 0.164 0.12 (0.01, 1.37) 0.098 0.44 (0.02, 3.82) 0.496 Abdominal involvement 22.5 (9) 31.7 (40) 25.0 (58) 1.04 (0.48, 2.47) 0.919 1.65 (0.73, 4.03) 0.250 1.58 (0.94, 2.64) 0.083 Abdominal pain 15.0 (6) 29.4 (37) 22.0 (51) 1.48 (0.62, 4.11) 0.408 2.44 (0.99, 6.98) 0.069 1.65 (0.97, 2.81) 0.063 Peritonitis 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Blood in stools or bloody diarrhea 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Bowel ischaemia 2.5 (1) 0.0 (0) 2.2 (5) 1.02 (0.15, 2.00) 0.988 - - - - Kidney involvement 50.0 (20) 88.1 (111) 77.2 (179) 3.27 (1.63, 6.58) <0.001 7.82 (3.42, 18.49) <0.001 2.39 (1.28, 4.72) 0.008 Hypertension >95th centile (for height) 17.5 (7) 33.3 (42) 19.4 (45) 1.04 (0.45, 2.71) 0.937 2.41 (1.02, 6.45) 0.058 2.33 (1.37, 3.99) 0.002 Proteinuria >0.3g/24h, >20mg/mmol creatinine 30.0 (12) 84.1 (106) 63.4 (147) 3.92 (1.92, 8.42) <0.001 11.93 (5.29, 28.50) <0.001 3.04 (1.75, 5.49) <0.001 Haematuria â¥ 2+ or 5 rbc/hpf or red blood cell casts 27.5 (11) 79.4 (100) 69.4 (161) 5.72 (2.77, 12.60) <0.001 10.69 (4.78, 25.51) <0.001 1.87 (1.10, 3.26) 0.024 52 eGFR 50-80ml/min/1.73m2 10.0 (4) 3.2 (4) 5.2 (12) 0.48 (0.15, 1.79) 0.224 0.33 (0.07, 1.48) 0.134 0.69 (0.18, 2.13) 0.545 eGFR 15-49ml/min/1.73m2 5.0 (2) 19.8 (25) 8.2 (19) 1.62 (0.44, 10.49) 0.526 4.95 (1.36, 31.91) 0.036 3.05 (1.55, 6.11) 0.001 eGFR <15ml/min/1.73m2 2.5 (1) 15.9 (20) 6.0 (14) 2.54 (0.49, 46.82) 0.374 7.27 (1.42, 133.14) 0.058 2.86 (1.34, 6.23) 0.007 Rise in creatinine >10% or creatinine clearance (eGFR) fall >25% 0.0 (0) 0.8 (1) 0.4 (1) - - - - 1.06 (0.04, 29.32) 0.967 Nervous system involvement 22.5 (9) 20.6 (26) 15.9 (37) 0.64 (0.29, 1.53) 0.288 0.99 (0.42, 2.46) 0.978 1.55 (0.85, 2.78) 0.145 Headache 17.5 (7) 13.5 (17) 9.1 (21) 0.46 (0.19, 1.25) 0.106 0.76 (0.30, 2.14) 0.585 1.65 (0.80, 3.38) 0.172 Meningitis/encephalitis 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Organic confusion/cognitive dysfunction 2.5 (1) 1.6 (2) 0.4 (1) 0.13 (0.01, 3.54) 0.165 0.42 (0.03, 10.58) 0.527 3.10 (0.19, 80.69) 0.422 Seizures (not hypertensive) 2.5 (1) 4.8 (6) 2.2 (5) 0.83 (0.13, 16.22) 0.868 1.89 (0.30, 36.79) 0.566 2.28 (0.62, 8.62) 0.210 Stroke 2.5 (1) 0.0 (0) 0.0 (0) - - - - - - Cord lesion 0.0 (0) 0.0 (0) 0.0 (0) - - - - - - Cranial nerve palsy 0.0 (0) 2.4 (3) 4.3 (10) - - - - 0.61 (0.13, 2.12) 0.472 Sensory peripheral neuropathy 2.5 (1) 1.6 (2) 1.3 (3) 0.50 (0.06, 10.84) 0.572 0.94 (0.08, 21.59) 0.964 1.87 (0.23, 12.15) 0.509 Motor mononeuritis multiplex 0.0 (0) 0.8 (1) 0.9 (2) - - - - 0.98 (0.04, 10.62) 0.990 (-) indicates unreliable statistical results due to an insufficient sample size in one or both of the groups being compared. 53 3.4 Discussion Untreated AAV can be organ- and life-threatening and, although modern treatments (namely glucocorticoids in combination with either cyclophosphamide or rituximab) have dramatically lowered mortality rates, the prolonged use of these immunosuppressive agents in high doses is associated with both short- and long-term toxicity risks 43,44. As a result, AAV remains a chronic, remitting, and relapsing disease, with continuous accumulation of damage from treatment toxicity and the disease itself. In adult-onset AAV, ANCA positivity and specificity facilitate treatment decision-making by predicting disease prognosis. Therefore, I evaluated associations between ANCA status, disease activity at diagnosis, and one-to-two-year outcomes in 406 children with SVV, inclusive of ANCA-positive and ANCA-negative cases of AAV. In the study cohort, I assessed differences in overall disease activity at diagnosis and outcomes later in the disease course between children stratified by ANCA positivity. I observed similar disease activity at diagnosis in children seropositive for MPO-ANCA and PR3-ANCA that was significantly higher than disease activity at the onset of ANCA-negative vasculitis. These findings are consistent with a previous study in a cohort of 84 adults with pauci-immune glomerulonephritis that demonstrated elevated disease activity in ANCA-positive versus ANCA-negative individuals 99. Similarly, in 105 pediatric AAV patients 4, improving disease and achievement of disease inactivity occurred, although not without damage, for the majority of individuals within one year of diagnosis. Further, I demonstrated that ANCA positivity and specificity may not have differential effects on these outcomes (i.e., improvement, achievement of inactive disease, and damage). Similarly, and in contrast to a higher risk of relapsing disease in adult-onset PR3-ANCA seropositive vasculitis 62, neither ANCA positivity nor specificity was 54 predictive of relapse, at least not in this cohort of children with SVV. Interestingly, the incidence of relapse was lower among children with SVV compared to adults 62,100,101. Although disease activity at diagnosis was similar between children in the cohort with either PR3- or MPO-ANCA, I sought to assess whether disease activity was comprised of differences in organ system involvement and the presence of particular clinical characteristics at presentation. I noted differences in clinical manifestations that are consistent with observations in adults 102. Namely, multi-organ involvement comprising both renal and extra renal organ systems is seen more frequently in children with PR3-ANCA, while individuals with MPO-ANCA typically present with kidney-limited disease. In comparing my data to previous reports on adult-onset SVV, specifically the RAVE trial describing baseline clinical manifestations in adults, the mucous membranes/ocular and ENT systems are more frequently involved in PR3- versus MPO-ANCA seropositive disease, in both pediatric- and adult-onset cases 94. Focusing on the frequency of pulmonary involvement, no differences were observed between PR3- and MPO-ANCA seropositive adults in the RAVE trial cohort 94 or in my pediatric SVV cohort. In contrast, cutaneous involvement, shown in my data to be more frequent in pediatric PR3-ANCA seropositive cases, does not exhibit similar differences in adults stratified by ANCA specificity 94,102. Although historically, the prevalence of kidney involvement did not differ in adults stratified by ANCA specificity, more recent studies describe significant differences 94,103,104 that are aligned with my findings in this pediatric SVV cohort of more frequent kidney involvement at diagnosis in individuals with MPO-ANCA relative to PR3-ANCA seropositivity. Both MPO- and PR3- 55 ANCA seropositive cases also exhibited higher frequencies of kidney involvement than ANCA-negative vasculitis. Thus, unlike other organ systems, the frequency of kidney disease among pediatric small vessel vasculitis patients varied depending on ANCA positivity and specificity; specifically, kidney involvement was increasingly frequent from ANCA-negative, to PR3-ANCA-positive, to MPO-ANCA-positive cases. In summary, findings presented in this chapter affirm, for the first time in childhood-onset vasculitis, associations described in adult-onset AAV between MPO-ANCA seropositivity and a higher prevalence of kidney-limited disease compared to individuals with PR3-ANCA seropositivity, despite similarly high disease activity at diagnosis. While my data do not recapitulate findings in adult-onset AAV demonstrating that PR3-ANCA seropositivity is predictive of relapsing disease, it is noteworthy that a lower proportion of the cohort had a relapse within the time interval studied compared to what has been previously reported for adult-onset AAV 100,101. 56 Chapter 4: The utility of ANCA and urine proteins (usCD163, uMCP-1, and usCD25) in identifying active disease in the kidneys in childhood-onset small vessel vasculitis 4.1 Rationale and introduction The majority (>80%) of children with AAV present with kidney disease at diagnosis 3,4,96. Even with aggressive treatment, by 1-year post-diagnosis, 70% of affected children have abnormal kidney function and 35% have permanent kidney damage leading to increased morbidity and mortality 4. The presence of kidney disease in childhood-onset AAV is a major driver of treatment decisions. Studies investigating the utility of putative biomarkers for kidney disease activity and function, as well as kidney-specific disease outcomes, in childhood-onset AAV are desperately needed, yet lacking, largely due to disease rarity. In adult-onset AAV, autoantibodies towards proteinase-3 (PR3-ANCA) and myeloperoxidase (MPO-ANCA) have been identified as prognostic biomarkers of kidney disease. The presence of MPO-ANCA has been associated with kidney-limited disease that is frequently more severe at presentation and more likely to progress to kidney failure than PR3-ANCA seropositive AAV 62,92. In accordance with this, I demonstrated (see Section 3.3.3) higher odds of kidney involvement in children with SVV (inclusive of AAV) and MPO-ANCA compared to those with PR3-ANCA and those without ANCA (i.e., ANCA-negative vasculitis). Additionally, it has been shown that elevated concentrations of urine (u) soluble (s) proteins (usCD163 74â77, usCD25 77, and uMCP-1 76,85) are associated with active disease in the kidneys in adult-onset AAV and may reflect the activation and glomerular infiltration of macrophages and T-cells. 57 The primary outcome of interest was kidney disease activity at diagnosis. In addition to this, the secondary outcomes of interest included kidney function at diagnosis, kidney disease activity at 1-year post-diagnosis, as well as kidney function at 1-year post-diagnosis. I hypothesized that the utility of adult-derived biomarkers (i.e., ANCA and select urine proteins) for assessing kidney disease in pediatric patients will mirror their use in adults; namely, children with ANCA against MPO and elevated concentrations of usCD163, usCD25, and/or uMCP-1 will have the highest kidney disease activity (as measured by renal pVAS, see Chapter 2) and the worst kidney function (as measured by eGFR and categorized according to KDIGO guidelines 89, see Chapter 2 and Table 2.1) at diagnosis and 1 year later. 4.2 Study cohorts (i) Evaluation of ANCA: The association between kidney disease and ANCA seropositivity and specificity was evaluated in a subset of children with SVV (inclusive of AAV, ANCA-positive glomerulonephritis and unclassified primary small vessel vasculitis), as described in Section 3.2 (Table 3.1), and with available clinical data for renal pVAS and/or eGFR. As described in Chapter 2, ANCA seropositivity/specificity was measured by participating centres using ELISA or indirect immunofluorescence. Further details regarding the inclusion/exclusion of individuals in this sub-cohort are provided in Figure 2.1. (ii) Evaluation of urine proteins: The association between kidney disease and urine protein (usCD163, usCD25, and uMCP-1) concentrations was evaluated in a subset of children (n = 52) with SVV and moderate-to-high kidney disease activity at diagnosis. The concentration of urine proteins in this Renal SVV Cohort was measured against n = 41 individuals among three 58 comparator cohorts: children with SVV without kidney involvement (Non-Renal SVV Cohort), children with large vessel vasculitis (LVV) with kidney involvement but not glomerulonephritis (LVV Cohort), and healthy adults (Healthy Adult Cohort). As described in Chapter 2, usCD163, usCD25, and uMCP-1 were measured in urine collected at the time of diagnosis by ELISA. Renal SVV Cohort (n = 52; Table 4.1): Within this cohort, the median renal pVAS at diagnosis was 12.0 (IQR: 10.0 â 12.0), with a majority (81%, n = 42/52) of children having a score at or near the maximum (renal pVAS = 10 â 12). The median age at diagnosis was 14.0 (IQR: 13.0 â 16.0). The majority of children were Caucasian (62%, n = 32/52) and female (62%, n = 32/52), and although there was some overlap between these two categories, it should be noted that not all Caucasian children were female. Non-Renal SVV Cohort (n = 10; Table 4.1): In the non-renal SVV cohort, the median renal pVAS at diagnosis was 0.0 (0.0 â 0.0), corresponding to the absence of clinical signs of kidney disease (i.e., proteinuria, hematuria, eGFR â¤ 80 mL/min/1.73m2, and a rise in serum creatinine or fall in creatinine clearance of more than 10% or 25%, respectively). As a result, the non-renal SVV cohort functioned as a disease-specific comparator, allowing me to assess changes in urine protein concentrations due to SVV alone, and, in doing so, identify if changes in urine concentration are specific for moderate-to-high kidney disease activity in SVV. Like the renal SVV cohort, the majority of children in this cohort were also Caucasian (50%, n = 5/10) and female (70%, n = 7/10) with a median age at diagnosis of 14.0 (13.0 â 15.0). Further details regarding the inclusion and exclusion of individuals in both the renal and non-renal SVV cohorts are provided in Figure 2.2. 59 LVV Cohort (n = 11; Table 4.1): In the LVV cohort, the median age at diagnosis was 13.0 (9.0 â 15.0) and, as with the renal and non-renal SVV cohorts, a substantial proportion of children were Caucasian (45%, n = 5/11) and female (64%, n = 7/11). The median renal pVAS at diagnosis was 4.0 (4.0 â 9.0). All children in this cohort were diagnosed with Takayasuâs arteritis (TA), a form of vasculitis predominantly affecting the aorta and its major (large vessel) branches. The renal arteries leading to the kidneys are affected in a subset of patients in this cohort (indicated by a renal pVAS > 4) 105. In contrast to SVV in the kidneys, TA-associated involvement of the renal artery rarely leads to damage to the glomeruli or interstitial tubules, with the predominant clinical manifestation of TA being renovascular hypertension. Therefore, the LVV cohort served to test the specificity of urine protein concentration to glomerulonephritis, which is a hallmark of kidney disease in SVV. Healthy Adult Cohort (n = 20): Urine from healthy adults was an important comparator to establish a baseline for urine protein concentrations in the absence of disease. The majority of adults in this cohort, for whom data regarding biological sex were available, were female (64%, n = 7/11). The association between kidney disease and adult-derived biomarkers, specifically ANCA seropositivity and specificity and urine protein concentrations, was evaluated in the aforementioned cohorts using linear and logistic regression models, in addition to linear mixed effects models. As mentioned previously (see Section 3.2), these models were selected for their ability to control for potential confounding variables (e.g., age at diagnosis, biological sex, etc.). Detailed information regarding the statistical analyses employed can be found in Table 2.2. 60 Table 4.1 Demographic and clinical characteristics of childhood-onset vasculitis patients with and without kidney involvement for the analysis of urine protein biomarkers Comparator Groups Renal SVV (n = 52) Non-Renal SVV (n = 10) LVV (n = 11) Age at diagnosis, median (IQR) years 14.0 (13.0 â 16.0) 14.0 (13.0 â 15.0) 13.0 (9.0 â 15.0) Sex, Female 32 (61.5) 7 (70.0) 7 (63.6) Ethnicity Native American/First Nations 4 (7.7) 0 (0.0) 1 (9.1) Asian 1 (1.9) 0 (0.0) 2 (18.2) Black 2 (3.8) 1 (10.0) 0 (0.0) Caucasian/White 32 (61.5) 5 (50.0) 5 (45.0) East Indian/South Asian 8 (15.4) 0 (0.0) 0 (0.0) Middle Eastern 1 (1.9) 0 (0.0) 0 (0.0) Other/Mixed 1 (1.9) 3 (30.0) 2 (18.2) Unknown 3 (5.8) 1 (10.0) 1 (9.1) Subtype Classification Granulomatosis with Polyangiitis 34 (65.4) 4 (40.0) - Limited GPA 0 (0.0) 3 (30.0) - Microscopic polyangiitis (MPA) 10 (19.2) 0 (0.0) - MPA with isolated renal involvement 1 (1.9) 0 (0.0) - ANCA positive pauci-immune glomerulonephritis 5 (9.6) 0 (0.0) - Unclassified primary vasculitis 2 (3.8) 3 (30.0) - Takayasu arteritis - - 11 (100.0) Renal pVAS at diagnosis, median (IQR) 12.0 (10.0 â 12.0) 0.0 (0.0 â 0.0) 4.0 (4.0 â 9.0) ANCA status1 ANCA-negative 4 (8.0) 3 (33.3) 7 (100.0) MPO-ANCA 16 (32.0) 1 (11.1) 0 (0.0) PR3-ANCA 30 (60.0) 5 (55.6) 0 (0.0) *Unless indicated otherwise, values refer to the absolute number (%) of patients in the given category. IQR: Interquartile Range 1Data from ANCA (towards MPO and PR3) testing performed by participating study sites was available for n = 50/52, n = 9/10, and n = 7/11 individuals in the renal SVV, non-renal SVV and LVV cohorts, respectively. 61 4.3 Results 4.3.1 MPO-ANCA seropositivity is more often associated with kidney insufficiency at diagnosis compared to PR3-ANCA seropositivity Given the reported associations between kidney disease activity and ANCA status in adult-onset AAV 62,92, I investigated whether a similar association existed in childhood-onset small vessel vasculitis. To do this, I compared children with SVV stratified by ANCA status (seropositivity and specificity) for both kidney disease activity and kidney function at the time of diagnosis. A score of kidney disease activity (renal pVAS) at diagnosis was available from a total of n = 401 children, including those who were ANCA seronegative (n = 43) and those who were seropositive for either MPO-ANCA (n = 126) or PR3-ANCA (n = 232). The median renal pVAS of children with MPO-ANCA was 12.0 (IQR: 10.0 â 12.0) compared to 10.0 (4.0 â 10.5) in children with PR3-ANCA and 2.0 (0.0 â 6.5) for children with ANCA-negative vasculitis. At the time of diagnosis, children who were seropositive for either MPO-ANCA or PR3-ANCA had a significantly higher mean renal pVAS compared to those who were ANCA seronegative (MPO-ANCA vs. ANCA-negative, mean ± SD: 9.6 ± 3.9 vs. 3.9 ± 4.5, mean difference: 5.71, 95% CI: 4.13 to 7.29, p < 0.001; PR3-ANCA vs. ANCA-negative, mean ± SD: 7.5 ± 4.6 vs. 3.9 ± 4.5, mean difference: 3.45, 95% CI: 1.98 to 4.93, p < 0.001) (Figure 4.1 A). Furthermore, the mean renal pVAS of MPO-ANCA seropositive children was significantly higher than that of children with PR3-ANCA (MPO-ANCA vs. PR3-ANCA, mean ± SD: 9.6 ± 3.9 vs. 7.5 ± 4.6, mean difference: 2.26, 95% CI: 1.26 to 3.26, p < 0.001) (Figure 4.1 A). 62 Kidney function was assessed at diagnosis in ANCA seropositive children with available eGFR data (n = 123) and specifically in children (n = 82) with biopsy-confirmed glomerulonephritis, the hallmark of kidney disease in AAV. Kidney function (eGFR) was infrequently measured in ANCA-negative cases (only 4/41 individuals), likely due to a low suspicion of kidney involvement, thus, this subgroup was statistically underpowered and not included in analyses of kidney function. Children (n = 39) who were seropositive for MPO-ANCA had a lower mean eGFR, and, therefore, worse kidney function, at diagnosis compared to (n = 84) PR3-ANCA seropositive cases (MPO-ANCA vs. PR3-ANCA, mean ± SD: 48.9 ± 47.8 vs. 87.4 ± 43.6, mean difference: -42.70, 95% CI: -60.15 to -25.26, p < 0.001) (Figure 4.1 B). Consistent with this, among children with biopsy-confirmed glomerulonephritis, those with MPO-ANCA (n = 37) had a lower mean eGFR at diagnosis compared to children (n = 45) with PR3-ANCA (MPO-ANCA vs. PR3-ANCA, mean ± SD: 51.1 ± 48.1 vs. 70.2 ± 44.8, mean difference: -27.6, 95% CI: -48.8 to -6.5, p = 0.001) (Figure 4.1 C). In clinical practice, kidney function is often classified into one of five stages of severity as per KDIGO guidelines (see Section 2.3.2, Table 2.1) 89 where eGFR across a defined range indicate a similar extent of kidney (dys)function. I, therefore, considered whether a comparison of kidney function based on KDIGO category would reduce the deviation observed when comparing mean eGFR and, in doing so, more accurately assess potential differences in kidney disease at onset for patients stratified by ANCA specificity. A subset of 123 children, 39 and 84 of whom were seropositive for MPO-ANCA and PR3-ANCA, respectively, were compared for the likelihood of being assigned to specific KDIGO stages at diagnosis. In accordance with significantly lower eGFR in MPO-ANCA seropositive children, the adjusted odds of being in a higher KDIGO stage 63 (i.e., having worse kidney function) at diagnosis were 6.04 (95% CI: 2.77 to 13.57, p < 0.001) times higher compared to children seropositive for PR3-ANCA. Specifically, MPO-ANCA seropositive children exhibited a higher probability of being in kidney failure (KDIGO stage 5) at diagnosis than PR3-ANCA seropositive children (0.36 [95% CI: 0.23 to 0.52] vs. 0.09 [95% CI: 0.05 to 0.15]). Conversely, the probability of having normal kidney function (KDIGO stage 1) was higher for PR3-ANCA seropositive children compared to those who were seropositive for MPO-ANCA (0.57 [95% CI: 0.47 to 0.68] vs. 0.18 [95% CI: 0.10 to 0.31]) (Figure 4.1 D and Table 4.2). 64 Figure 4.1 Kidney disease at diagnosis in childhood-onset SVV stratified by ANCA status A linear regression model was used to compare (A) kidney disease activity, as measured by the renal pVAS (y-axis; median) (x-axis: ANCA-negative, n = 43; MPO-ANCA, n = 126; PR3-ANCA, n = 232), and (B) kidney function, as measured by the eGFR (y-axis; median) (x-axis: MPO-ANCA, n = 39; PR3-ANCA, n = 84), at the time of diagnosis in a cohort of children with small vessel vasculitis, as well as (C) kidney function in a subset of individuals in this cohort with biopsy-proven glomerulonephritis (x-axis: MPO-ANCA, n = 37; PR3-ANCA, n = 45). (D) An ordinal logistic regression model was used to compare the predicted probability (y-axis) of having (x-axis) normal kidney function (KDIGO stage 1, eGFR â¥ 90), mildly reduced kidney function (KDIGO stage 2, 60 â¤ eGFR â¤ 89), moderately reduced kidney function (KDIGO stage 3, 30 â¤ eGFR â¤ 59), severely reduced kidney function (KDIGO stage 4, 15 â¤ eGFR â¤ 29), and kidney failure (KDIGO stage 5, < 15) at diagnosis between children with small vessel vasculitis seropositive for MPO-ANCA (grey, n = 39) and PR3-ANCA (black, n = 84). All models were adjusted for age at diagnosis and biological sex as baseline variables. 1 2 3 4 50.00.20.40.60.8KDIGO StagePredicted Probability MPO-ANCAPR3-ANCAAMPO-ANCA PR3-ANCA0100200ANCA StatuseGFR (mL/min/1.73 m2 )P < 0.001ANCA - MPO-ANCA PR3-ANCA051015ANCA StatusRenal pVASP < 0.001 P < 0.001P < 0.001BDMPO-ANCA PR3-ANCA0100200ANCA StatuseGFR (mL/min/1.73 m2 )C 65 Table 4.2 Predicted probabilities of KDIGO stages at diagnosis for childhood-onset small vessel vasculitis stratified by ANCA specificity ANCA Status MPO-ANCA (n = 39) PR3-ANCA (n = 84) KDIGO Stage Predicted Probability 95% CI Predicted Probability 95% CI 1 0.18 0.10 â 0.31 0.57 0.47 â 0.68 2 0.12 0.07 â 0.19 0.15 0.09 â 0.22 3 0.17 0.10 â 0.27 0.12 0.07 â 0.19 4 0.17 0.10 â 0.28 0.07 0.04 â 0.13 5 0.36 0.23 â 0.52 0.09 0.05 â 0.15 4.3.2 MPO-ANCA seropositivity is associated with a more favourable kidney disease trajectory than PR3-ANCA seropositivity in individuals with severely reduced kidney function or kidney failure at diagnosis The evaluation of kidney disease described in Section 3.3.3 suggested key differences in kidney involvement at diagnosis between children seropositive for MPO-ANCA versus PR3-ANCA. These findings, in conjunction with previous reports of worse kidney outcomes in MPO-ANCA seropositive adults compared to those with PR3-ANCA 92,106â108, led me to investigate whether ANCA specificity is also associated with differences in kidney outcomes in the pediatric population, as determined by changes in kidney function (eGFR/KDIGO) within one year of diagnosis. To determine if kidney disease trajectories differed between MPO-ANCA and PR3-ANCA seropositive children who were matched for kidney function (KDIGO category) at diagnosis, children with normal to mildly reduced kidney function (KDIGO stages 1-2), moderately reduced kidney function (KDIGO stage 3), and severely reduced kidney function to kidney failure (KDIGO stages 4-5) at diagnosis were compared for changes in eGFR from diagnosis to 66 follow-up at 6- and 12-months post-diagnosis. There were 74, 16, and 33 children with KDIGO stages 1-2, 3, and 4-5, respectively. In children with normal to mildly reduced kidney function (KDIGO stage 1-2) at the time of diagnosis, there was a decline (worsening) in mean eGFR in PR3-ANCA-positive individuals at 6- and 12-months post-diagnosis (6-months vs. diagnosis, mean ± SD: 95.6 ± 27.6 vs. 109.9 ± 25.3, mean difference: -14.97, 95% CI: -22.10 to -7.82, p < 0.001; 12-months vs. diagnosis, mean ± SD = 91.7 ± 27.6 vs. 109.9 ± 25.3, mean difference: -19.20, 95% CI: -26.40 to -11.90, p < 0.001). In contrast, no such pattern was noted for MPO-ANCA seropositive cases (Figure 4.2 A and Table 4.3). In those with indications of moderately reduced kidney function (KDIGO stage 3), both PR3-ANCA and MPO-ANCA seropositivity exhibited an increase (improvement) in eGFR at 12 months (PR3-ANCA: 12-months vs. diagnosis, 68.7 ± 35.9 vs. 42.1 ± 7.6, mean difference: 26.20, 95% CI: 10.18 to 42.20, p = 0.001) (MPO-ANCA: 12-months vs. diagnosis, 74.8 ± 32.3 vs. 44.3 ± 11.7, mean difference: 30.50, 95% CI: 5.47 to 55.60, p = 0.017) (Figure 4.2 B and Table 4.3). Finally, for participants experiencing severely reduced kidney function or kidney failure (KDIGO stage 4-5) at diagnosis, I observed an increase in the eGFR of MPO-ANCA seropositive individuals from the time of diagnosis to 6- and 12-months post-diagnosis (6-months vs. diagnosis, 38.2 ± 32.4 vs. 13.0 ± 7.1, mean difference: 23.50, 95% CI: 12.57 to 34.40, p < 0.001; 12-months vs. diagnosis, 44.6 ± 39.4 vs. 13.0 ± 7.1, mean difference: 28.76, 95% CI : 17.60 to 39.90, p < 0.001) (Figure 4.2 C and Table 4.3). Similarly, an increase in the mean eGFR was noted for PR3-ANCA seropositive individuals from the time of diagnosis to 6- and 12-months post-diagnosis (6-months vs. diagnosis, 25.0 ± 19.2 vs. 11.8 ± 7.1, mean difference: 12.30, 95% CI: -2.27 to 26.80, p = 0.098; 12-months vs. diagnosis, 20.5 ± 19.3 vs. 67 11.8 ± 7.1, mean difference: 5.76, 95% CI : -10.70 to 22.20, p = 0.493). However, the results were less certain with confidence intervals also suggesting moderate decreases in eGFR from the time of diagnosis to 6- and 12-months post-diagnosis. Based on the mean eGFR in MPO-ANCA seropositive individuals at each time point, an accompanying shift to KDIGO stage 3 (moderately reduced kidney function) was observed. In contrast, there were no significant differences between eGFR at diagnosis, 6-months post-diagnosis, and 12-months post-diagnosis in PR3-ANCA seropositive participants who had severely reduced kidney function or kidney failure (KDIGO stages 4-5) at diagnosis. In a subgroup analysis of 23 children (16 MPO-ANCA positive and 7 PR3-ANCA positive) with severely reduced kidney function or kidney failure (KDIGO stages 4-5) at diagnosis and available paired data (eGFR) at 12-months post-diagnosis, I found that 56% (9/16) of MPO-ANCA seropositive participants showed improvement in kidney function at 1-year. Of these individuals, 31% improved to KDIGO stage 3, and 25% improved to KDIGO stages 1-2 (Figure 4.2 D). In contrast, only 28% (2/7) of PR3-ANCA seropositive individuals with severely reduced kidney function or kidney failure (KDIGO stages 4-5) at diagnosis achieved KDIGO stage 3 by 12-months post-diagnosis and no PR3-ANCA seropositive individual improved to KDIGO stages 1-2. It is, however, important to note the relatively small sample size of the PR3-ANCA subgroup and interpret the associated results with caution. 68 Figure 4.2 Kidney disease trajectory from diagnosis to 1-year post-diagnosis in childhood-onset SVV stratified by KDIGO stage at diagnosis and ANCA specificity A linear mixed effects model, adjusted for eGFR and age at diagnosis, alongside sex, was used to compare changes in kidney function, quantified using eGFR (y-axis) at the time of diagnosis, 6-months post-diagnosis, and 12-months post-diagnosis (x-axis) between MPO- and PR3-ANCA seropositive pediatric patients with (A) normal-to-mildly reduced kidney function (KDIGO stage 1-2, eGFR â¥ 60), (B) moderately reduced kidney function (KDIGO stage 3, 30 â¤ eGFR < 60), or (C) severely reduced kidney function or kidney failure (KDIGO stage 4-5, eGFR < 30) at the time of diagnosis. (D) eGFR at diagnosis and 1-year post-diagnosis are also shown for a subset of participants with data availability who had severely reduced kidney function or kidney failure at diagnosis. Graphs are shaded to visualize KDIGO stages 1-2 (white), 3 (grey), and 4-5 (dark grey). Numbers in brackets on the x-axis (A-C) are individual patients. Data are presented as violin plots with the median (dotted line) and interquartile range (IQR). 69 Table 4.3 Kidney function over the first 12 months in PR3-ANCA and MPO-ANCA positive childhood-onset SVV 4.3.3 usCD163 and usCD25, but not uMCP-1, are detected in urine from children with small vessel vasculitis in the kidneys Previous studies have reported significantly elevated concentrations of usCD163, usCD25, and uMCP-1 in adult-onset AAV with active disease in the kidneys, as identified by the Birmingham Vasculitis Activity Score (BVAS) 47,74â77,85. To evaluate a potential association in childhood-onset vasculitis, I assessed the utility of these urine proteins as markers for active kidney disease in Mean eGFR ± SD Mean Difference (95 % CI) P-value (A) MPO-ANCA (I) Stage 1-2 6-months vs. diagnosis 105.9 ± 29.1 vs. 111.0 ± 23.5 -5.12 (-19.60, 9.35) 0.488 12-months vs. diagnosis 108.3 ± 25.3 vs. 111.0 ± 23.5 -2.50 (-17.30, 12.30) 0.741 12-months vs. 6-months 108.3 ± 25.3 vs. 105.9 ± 29.1 2.62 (-12.20, 17.43) 0.729 (II) Stage 3 6-months vs. diagnosis 66.1 ± 21.0 vs. 44.3 ± 11.7 26.60 (-1.08, 54.40) 0.060 12-months vs. diagnosis 74.8 ± 32.3 vs. 44.3 ± 11.7 30.50 (5.47, 55.60) 0.017 12-months vs. 6-months 74.8 ± 32.3 vs. 66.1 ± 21.0 3.89 (-23.84, 31.60) 0.784 (III) Stage 4-5 6-months vs. diagnosis 38.2 ± 32.4 vs. 13.0 ± 7.1 23.50 (12.57, 34.40) <0.001 12-months vs. diagnosis 44.6 ± 39.4 vs. 13.0 ± 7.1 28.76 (17.60, 39.90) <0.001 12-months vs. 6-months 44.6 ± 39.4 vs. 38.2 ± 32.4 5.29 (-6.34, 16.90) 0.373 (B) PR3-ANCA (I) Stage 1-2 6-months vs. diagnosis 95.6 ± 27.6 vs. 109.9 ± 25.3 -14.97 (-22.10, -7.82) <0.001 12-months vs. diagnosis 91.7 ± 27.6 vs. 109.9 ± 25.3 -19.20 (-26.40, -11.90) <0.001 12-months vs. 6-months 91.7 ± 27.6 vs. 95.6 ± 27.6 -4.19 (-11.80, 3.45) 0.283 (II) Stage 3 6-months vs. diagnosis 61.2 ± 33.7 vs. 42.1 ± 7.6 20.00 (5.03, 34.90) 0.009 12-months vs. diagnosis 68.7 ± 35.9 vs. 42.1 ± 7.6 26.20 (10.18, 42.20) 0.001 12-months vs. 6-months 68.7 ± 35.9 vs. 61.2 ± 33.7 6.22 (-9.95, 22.40) 0.451 (III) Stage 4-5 6-months vs. diagnosis 25.0 ± 19.2 vs. 11.8 ± 7.1 12.30 (-2.27, 26.80) 0.098 12-months vs. diagnosis 20.5 ± 19.3 vs. 11.8 ± 7.1 5.76 (-10.70, 22.20) 0.493 12-months vs. 6-months 20.5 ± 19.3 vs. 25.0 ± 19.2 -6.49 (-23.13, 10.10) 0.444 70 children with moderate to high levels of vasculitis disease activity in the kidneys as measured by the pVAS, which is a modified version of the BVAS. Proteins isolated from native urine collected at diagnosis were analyzed for usCD163, usCD25, and uMCP-1 using commercially available ELISAs with detection ranges well below concentrations reported for adult-onset AAV cohorts; for further details, see Chapter 2 and Table 4.4. My results indicate that usCD163, usCD25, and uMCP-1 were detected in urine, respectively, from 48% (n = 25/52), 56% (n = 29/52) and 8% (n = 4/52) of children with moderate-to-high kidney disease activity (Table 4.5). Since uMCP-1 concentration was below the lower limit of detection for the majority of samples, it was excluded as a potential biomarker of active kidney disease in pediatric patients and further analyses on uMCP-1 were not performed. 71 Table 4.4 Concentration in urine of usCD163, usCD25, and total protein ID Total protein (µg/mL) usCD163 (pg/mL) usCD25 (pg/mL) Normalized usCD163 (per mg total protein) Normalized usCD25 (per mg total protein) ANCA Renal pVAS Renal SVV Cohort 1 2307.1 434.9 169.9 188.5 73.7 PR3 10 2 484.8 469.1 <12 967.7 12.4 MPO 12 3 970.7 536.4 56.6 552.5 58.3 PR3 10 4 992.3 552.8 177.7 557.1 179.1 PR3 6 5 505.4 637.1 64.2 1260.6 127.0 PR3 12 6 1181.5 706.6 <12 598.1 5.1 MPO 12 7 355.6 945.1 261.5 2657.5 735.2 PR3 10 8 803.4 991.7 71.3 1234.4 88.7 MPO 12 9 1736.7 1232.8* <12 709.8 3.5 PR3 12 10 1056.2 1386.9 304.2 1313.2 288.0 MPO 10 11 1731.4 1579.5 166.0 912.2 95.9 PR3 12 12 3651.5 2056.5 199.8 563.2 54.7 PR3 12 13 899.2 2718.8* 96.0 3023.7 106.8 MPO 12 14 757.0 3091.0 189.0 4083.4 249.6 - 12 15 1797.0 3390.7 2362.7 1886.8 1314.8 PR3 10 16 543.8 4121.3* 192.6 7578.8 354.2 PR3 12 17 1152.7 4297.8 <12** 3728.3 2.1 PR3 12 18 1925.6 4897.8* 169.9 2543.5 88.3 PR3 12 19 1399.5 6534.3 705.5 4669.0 504.1 PR3 10 20 2976.8 6553.8 405.4 2201.6 136.2 PR3 10 21 3982.2 7237.5* 312.3 1817.4 78.4 MPO 12 22 1561.5 8646.3 <12** 5537.3 1.5 PR3 10 23 766.2 9264.5* 90.3 12091.3 117.8 MPO 12 24 1927.8 9679.4 181.5 5021.0 94.2 PR3 4 25 2359.2 11191.5* 38.8 4743.8 16.4 PR3 12 26 1109.4 <435 12.0 196.1 10.8 MPO 12 27 408.8 <435 38.8 532.0 94.9 PR3 6 28 1491.2 <435 56.6 145.9 37.9 MPO 12 29 1092.2 <435 56.6 199.1 51.8 MPO 12 30 1617.3 <435 64.2 134.5 39.7 - 12 31 1051.8 <435 84.2 206.8 80.1 PR3 10 32 2141.7 <435 101.6 101.6 47.4 MPO 12 33 1600.2 <435 101.6 135.9 63.5 PR3 6 34 627.6 <435 117.8 346.6 187.7 PR3 8 35 1086.2 <435 <12** 200.2 2.2 PR3 6 72 36 1300.1 <435 <12 167.3 4.6 Neg 12 37 860.7 <435 <12 252.7 7.0 MPO 12 38 771.6 <435 <12 281.9 7.8 PR3 10 39 673.7 <435 <12 322.8 8.9 MPO 12 40 652.4 <435 <12 333.4 9.2 PR3 12 41 245.0 <435 <12** 887.7 9.8 PR3 10 42 1095.4 <435 <12* 198.5 11.0 PR3 12 43 520.8 <435 <12 417.6 11.5 PR3 6 44 985.6 <435 <12* 220.7 12.2 PR3 12 45 348.9 <435 <12 623.5 17.2 PR3 10 46 501.3 <435 <12* 433.9 23.9 MPO 12 47 243.3 <435 <12 893.8 24.7 MPO 4 48 458.1 <435 <12* 474.7 26.2 MPO 12 49 419.6 <435 <12* 518.4 28.6 Neg 12 50 176.4 <435 <12 1233.2 34.0 Neg 8 51 168.5 <435 <12 1290.5 35.6 PR3 12 52 94.6 <435 <12 2298.0 63.4 Neg 6 Non-Renal SVV Cohort 53 1430.3 10044.9* 227.1 7022.9 158.8 PR3 0 54 2179.6 <435 486.5 99.8 223.2 Neg 4 55 1025.5 <435 493.2 212.1 481.0 PR3 0 56 61.9 <435 <12 3514.7 97.0 Neg 0 57 167.5 <435 <12 1298.7 35.8 MPO 0 58 175.1 <435 <12 1242.3 34.3 Neg 0 59 713.2 <435 <12** 305.0 3.4 - 0 60 422.2 <435 <12 515.1 14.2 PR3 0 61 605.7 <435 <12* 359.1 19.8 PR3 0 62 263.1 <435 <12 826.6 22.8 PR3 0 LVV Cohort 63 491.3 541.4 296.0 1102.0 602.4 - 10 64 1310.9 661.8 276.2 504.9 210.7 Neg 4 65 2498.9 3638.3 175.4** 1455.9 70.2 Neg 10 66 233.8 <435 352.6 930.3 1508.3 - 4 67 948.1 <435 <12 229.4 6.3 Neg 4 68 1427.7 <435 <12 152.3 4.2 Neg 12 69 2329.3 <435 <12 93.4 2.6 - 8 70 531.8 <435 <12 409.0 11.3 Neg 8 71 187.0 <435 <12 1163.0 32.1 Neg 4 72 288.9 <435 <12 752.8 20.8 - 0 73 247.2 <435 <12 880.0 24.3 Neg 0 73 Unless indicated otherwise, the dilution factor for all samples was 1:5. Normalized concentrations for samples with detectable usCD163 and/or usCD25 are provided in bold. * indicates a dilution factor of 1:10. ** indicates a dilution factor of 1:2. 1Neg indicates ANCA seronegativity; â-â indicates that ANCA testing was not done. Healthy Adults Cohort 74 44.5 <435 <12 4887.6 134.8 - - 75 240.9 <435 <12 902.9 24.9 - - 76 4714.1 <435 2429.9 46.1 515.5 - - 77 114.4 <435 <12 1901.7 52.5 - - 78 291.4 <435 <12 746.5 20.6 - - 79 242.9 <435 <12 895.3 24.7 - - 80 144.2 <435 <12 1508.0 41.6 - - 81 342.4 <435 <12 635.2 17.5 - - 82 765.6 <435 <12 284.1 7.8 - - 83 455.0 <435 <12 478.0 13.2 - - 84 110.7 <435 <12 1965.1 54.2 - - 85 163.7 <435 <12 1328.4 36.6 - - 86 183.4 <435 <12 1185.9 32.7 - - 87 405.6 <435 <12 536.2 14.8 - - 88 385.5 <435 <12 564.2 15.6 - - 89 341.9 <435 <12 636.1 17.5 - - 90 180.3 <435 <12 1206.0 33.3 - - 91 619.3 <435 <12 351.2 9.7 - - 92 155.0 <435 <12 1403.7 38.7 - - 93 136.2 <435 <12 1597.3 44.1 - - 74 Table 4.5 Assay features for measurement of usCD163, usCD25, and uMCP-1 concentrations Protein ELISA Kit (Supplier, Catalog #) Reported Assay Range (pg/mL) Lowest detectable concentration (pg/mL) Reported cutoffs for active renal disease in adult-onset AAV Pediatric patients in the renal SVV cohort with concentrations above LDC usCD163 Human CD163 DuoSet ELISA (R&D Systems, DY1607) 156.0 â 10,000 435.0 (i) 1,300 pg/mL1 (ii) 0.3 ng/mmol Cr1 (iii) 72.9 ng/mmol Cr2 (iv) 350 ng/mmol Cr3 (v) 20,000 ng/mmol Cr4 25 (48.1%) usCD25 IL-2RA/CD25 Human ELISA Kit (ThermoFisher, EHIL2RAX5) 16.4 â 4,000 12.0 (i) 125 ng/mmol Cr3 29 (55.8%) uMCP-1 Human CCL2/MCP-1 Quantikine ELISA Kit (R&D Systems, SCP00) 31.2 â 2,000 20.0 (i) 10.0 pg/mmol Cr2 4 (7.7%) 1OâReilly et al. (2016). 2Moran et al. (2020). 3Dekkema et al. (2019). 4Villacorta et al. (2020). Cr: Creatinine. LDC: lowest detectable concentration. 75 Within the comparator cohorts, none of the urine proteins (usCD163, usCD25, uMCP1), with the exception of usCD25 in a single sample, were detected in urine from healthy adults. In the non-renal SVV and LVV cases, usCD163 and usCD25 were detected in 14.3% (3/21) and 33.3% (7/21) of individuals, corresponding to a high total protein concentration in these individuals. Comparison of absolute and normalized (to total urine protein) concentrations revealed no statistically significant difference in the mean concentration of usCD163 in children with renal SVV compared to children with non-renal SVV or LVV (Figure 4.3A and B). usCD163 concentration at diagnosis was, however, significantly higher in children with renal SVV compared to healthy adults (p < 0.001). Similarly, while there was no significant difference in the absolute and normalized mean concentrations of usCD25 in children with renal SVV compared to those with non-renal SVV or LVV, usCD25 concentration was significantly higher when compared to healthy adults (p = 0.006) (Figure 4.3C and D). 4.3.4 Elevated usCD163 and usCD25 in an overlapping subset of patients with relatively high total protein concentration To investigate why usCD163 and usCD25 were detected in some children but not in others, I compared the clinical characteristics of (n = 20) children in the renal SVV cohort who had detectable usCD163 and usCD25 to (n = 18) children in whom neither were detected (Table 4.6). Age at diagnosis and biological sex distribution was similar among the two subgroups. The total protein concentration was significantly higher in urine samples from children with detectable concentrations of both usCD163 and usCD25 compared to urine from children in whom neither protein was detected (p < 0.001). This was not accompanied by significant difference in the prevalence of proteinuria among the two subgroups. Moreover, the median eGFR was lower at 76 diagnosis and at 1-year post-diagnosis for children with detected concentrations of usCD163 and usCD25, although these differences were not statistically significant. 77 Figure 4.3 usCD163 and usCD25 concentrations in childhood-onset SVV with kidney involvement Comparisons of (A, C) absolute (y-axis; pg/mL) and (B, D) normalized, to total protein, concentrations (y-axis; per mg total protein) of (top, A-B) usCD163 and (bottom, C-D) usCD25 in children with SVV with moderate-to-high (renal SVV, n = 52) and low-to-no (non-renal SVV, n = 10) kidney disease activity at diagnosis, children with large vessel vasculitis (LVV, n = 11), and otherwise healthy adults (n = 20). Data were analyzed by (A, C) Kruskal-Wallis tests followed by Dunnâs multiple comparison tests, and (B, D) Mann-Whitney tests. Data are presented as scatter plots showing the mean, where each dot represents a sample collected from a single individual. ns = not significant (p > 0.05), ** p < 0.01, *** p < 0.001. 100100010000100000usCD163 (pg/mL)ns nsnsRenalSVVNon-RenalSVVHealthyAdults(n = 52) (n = 10) (n = 20)LVV(n = 11)nsnsâ±â±â±110100100010000usCD25 (pg/mL)RenalSVVNon-RenalSVVHealthyAdults(n = 52) (n = 10) (n = 20)LVV(n = 11)ns nsnsnsnsâ±â±050001000015000Normalized usCD163 (per mg total protein)RenalSVVNon-RenalSVV(n = 52) (n = 10)ns050010001500Normalized usCD25(per mg total protein)RenalSVVNon-RenalSVV(n = 52) (n = 10)nsA BC D 78 Table 4.6 Clinical characteristics of children with SVV with kidney involvement stratified by absolute usCD163 and usCD25 concentrations relative to detection thresholds usCD163 < 435 pg/mL and usCD25 < 12 pg/mL (n = 18) usCD163 > 435 pg/mL and usCD25 > 12 pg/mL (n = 20) p-value1 Sex, Female 12 (66.7) 10 (50.0) 0.299 ANCA status2 - ANCA-negative 4 (22.2) 0 (0.0) MPO-ANCA 5 (27.8) 5 (26.3) PR3-ANCA 9 (50.0) 14 (73.7) Diagnosis Age (years) 14.0 (11.0 â 16.0) 15.0 (14.0 â 16.0) 0.147 Renal pVAS 12.0 (8.5 â 12.0) 12.0 (10.0 â 12.0) 0.717 eGFR (mL/min/1.73 m2)3 81.0 (50.4 â 110.5) 54.8 (14.2 â 103.4) 0.328 Total protein (µg/mL) 511.0 (271.0 â 838.4) 1227.8 (794.1 â 2022.6) < 0.001 Proteinuria 15 (83.3) 18 (90.0) 0.544 1-year post-diagnosis Renal pVAS4 0.0 (0.0 â 0.0) 0.0 (0.0 â 0.0) 0.662 eGFR (mL/min/1.73 m2)3 83.2 (61.2 â 102.4) 66.7 (10.4 â 84.6) 0.228 Data are presented as absolute number (%) of patients and median (IQR) for categorical and continuous variables, respectively. IQR: Interquartile Range 1Associations between categorical variables were evaluated using chi-square test. For continuous variables, the Shapiro-Wilk normality test was used to check normality, and, if confirmed, the Studentâs t-test was applied. If not, the Mann-Whitney U test was performed. 2Data from ANCA (towards MPO and PR3) testing performed by participating study sites was not available for n = 1 individual with usCD163 and usCD25 concentrations above the detection thresholds. 3Data for eGFR at diagnosis was available for n = 12/20 and n = 11/18 individuals with usCD163 and usCD25 concentrations above and below the detection thresholds, respectively. Data for eGFR at 1-year post-diagnosis was available for n = 13/20 and n = 11/18 individuals with usCD163 and usCD25 concentrations above and below the detection thresholds, respectively. 4Data for renal pVAS at 1-year post-diagnosis was available for n = 16/20 and n = 12/18 individuals with usCD163 and usCD25 concentrations above and below the detection thresholds, respectively. 79 4.3.5 usCD163 and usCD25 concentrations do not correlate with kidney disease activity at diagnosis or trajectory over 1 year To assess whether usCD163 and usCD25 can provide meaningful insights into kidney disease activity, I investigated potential correlations between the normalized concentrations of these proteins and renal pVAS at diagnosis. This analysis focused on children in the renal SVV cohort for whom usCD163 (n = 25) and/or usCD25 (n = 29) was detected in their urine. No significant correlation was observed between renal pVAS at diagnosis and the concentrations of either usCD163 (p = 0.940) or usCD25 (p = 0.257) (Figure 4.4A and B). Similarly, there was no significant correlation between the change in renal pVAS (from time of diagnosis to 1-year post-diagnosis) and the concentrations of either usCD163 (n = 20, p = 0.775) or usCD25 (n = 19, p = 0.128) (Figure 4.4C and D). 4.3.6 usCD163 and usCD25 concentrations do not correlate with kidney function at diagnosis or 1 year later To determine if usCD163 and usCD25 are associated with kidney function rather than active disease, I looked for correlations between normalized concentrations of these proteins and eGFR as a measure of kidney function in a subset of children in the renal SVV cohort for whom usCD163 and/or usCD25 was detected in their urine. No correlation was observed between eGFR at diagnosis and usCD163 (n = 14, p = 0.605) or usCD25 (n = 17, p = 0.367) (Figure 4.5A and B). Consistent with these findings, usCD163 (n = 14, p = 0.605) and usCD25 (n = 17, p = 0.319) concentrations also did not differ between samples collected from children with normal to mildly reduced versus moderately to severely reduced kidney function (Figure 4.5C and D). Since no association was found between usCD163 and usCD25 concentrations and kidney function at diagnosis, I questioned whether this was also the case for kidney function later in the 80 disease course. While the correlation between usCD163 concentration and eGFR at 1-year post-diagnosis in a subset of patients with follow-up data was not statistically significant, the observed trend is approaching significance (n = 16, p = 0.062), suggesting a potential association that may become evident with larger sample sizes (Figure 4.6A). There was no correlation between usCD25 concentration and eGFR at 1-year post-diagnosis (n = 15, p = 0.641) (Figure 4.6B). 81 Figure 4.4 Comparison of usCD163 and usCD25 concentrations with kidney disease activity in childhood-onset SVV with kidney involvement Linear regression models, adjusted for age at diagnosis and biological sex, were used to (A-B) compare kidney disease activity, quantified by the renal pVAS (x-axis), at diagnosis with normalized, to total protein, concentrations (y-axis; per mg total protein) of (A) usCD163 (n = 25) and (B) usCD25 (n = 29) in children with SVV with moderate-to-high kidney disease activity at diagnosis (renal SVV). In the same cohort, (C-D) improvement in kidney disease activity from diagnosis to 1-year post-diagnosis, defined by a decrease in renal pVAS, was compared to normalized concentrations of (C) usCD163 (n = 20) and (D) usCD25 (n = 19). Data are presented as scatter plots, where each dot represents a sample collected from a single individual. 0 5 10 15050001000015000Renal pVAS at DiagnosisNormalized usCD163 (per mg total protein) β (95% CI): 24.7 (-653.9, 703.4)P = 0.9400 5 10 15050001000015000Improvement in Renal pVASNormalized usCD163 (per mg total protein) β (95% CI): 133.8 (-858.6, 1126.2)P = 0.7750 5 10 15050010001500Renal pVAS at DiagnosisNormalized usCD25 (per mg total protein) β (95% CI): -24.7 (-68.8, 19.4)P = 0.2570 5 10 15050010001500Improvement in Renal pVASNormalized usCD25 (per mg total protein)β (95% CI): 37.6 (-12.4, 87.6)P = 0.128A BDC 82 Figure 4.5 Comparison of usCD163 and usCD25 concentrations with kidney function at diagnosis in childhood-onset SVV with kidney involvement Linear regression models, adjusted for age at diagnosis and biological sex, were used to (A-B) compare kidney function, as measured by the eGFR (x-axis; mL/min/1.73m2), at diagnosis with normalized, to total protein, concentrations (y-axis; per mg total protein) of (A) usCD163 (n = 14) and (B) usCD25 (n = 17) in children with SVV with moderate-to-high kidney disease activity at diagnosis (renal SVV). In the same cohort, (C) normalized concentrations of usCD163 and (D) usCD25 were compared between children stratified by KDIGO function, defined by KDIGO category, at diagnosis, where KDIGO stages 1-2 (eGFR â¥ 60) corresponded to normal to mildly reduced kidney function, and KDIGO stages 3-5 (eGFR < 60) indicated moderately to severely reduced kidney function, as well as kidney failure. Data are presented scatter plots with mean. 0 50 100 150 200050001000015000eGFR at Diagnosis (mL/min/1.73m2)Normalized usCD163 (per mg total protein) β (95% CI): -13.4 (-72.0, 45.2)P = 0.605050001000015000Normalized usCD163 (per mg total protein)normal tomildly reducedkidney function(n = 7)moderately toseverely reducedkidney function(n = 7)P = 0.6050 50 100 150 200050010001500eGFR at Diagnosis (mL/min/1.73m2)Normalized usCD25 (per mg total protein) β (95% CI): 1.6 (-2.1, 5.2)P = 0.367050010001500Normalized usCD25 (per mg total protein)normal tomildly reducedkidney function(n = 9)moderately toseverely reducedkidney function(n = 8)P = 0.319A BDC 83 Figure 4.6 Comparison of usCD163 and usCD25 concentrations with kidney function at 1-year post-diagnosis in childhood-onset SVV with kidney involvement Linear regression models, adjusted for age at diagnosis and biological sex, were used to compare kidney function, as measured by the eGFR (x-axis; mL/min/1.73m2), at 1-year post-diagnosis with normalized, to total protein, concentrations (y-axis; per mg total protein) of (A) usCD163 (n = 16) and (B) usCD25 (n = 15) in children with SVV with moderate-to-high kidney disease activity at diagnosis (renal SVV). Data are presented as scatter plots, where each dot represents a sample collected from a single individual. 4.4 Discussion Although previous studies have explored the utility of autoantibodies against myeloperoxidase (MPO-ANCA) and proteinase-3 (PR3-ANCA) 62,92, as well as urine proteins, specifically usCD163 74â77, usCD25 77, and uMCP-1 76,85, as biomarkers of kidney disease in adult-onset AAV, their utility has not been evaluated in pediatric patients. Results in this chapter demonstrate higher kidney disease activity (as indicated by a higher renal pVAS) in children who were seropositive for MPO-ANCA compared to those with PR3-ANCA (Figure 4.1). Additionally, I noted worse kidney function (as indicated by a lower eGFR and a higher probability of meeting criteria for KDIGO stage 5, kidney failure) in children with MPO- 84 ANCA, with the opposite observed in PR3-ANCA seropositive patients. These data are consistent with findings in adult studies 109. It is noteworthy that while patients with MPO-ANCA seropositivity were more likely to have worse kidney disease at outset compared to PR3-ANCA positive patients, they were also more likely to have more pronounced improvements in kidney function; these improvements were more pronounced for individuals presenting with severely reduced kidney function or kidney failure (KDIGO stage 4-5) compared to PR3-ANCA seropositive individuals with similarly poor baseline kidney function (Figure 4.2). These findings are unique to pediatric-onset SVV and have not been previously noted in adult-onset disease. The corollary to this is that PR3-ANCA positive kidney disease may be more refractory in nature compared to MPO-ANCA positive kidney disease of similar severity as evident by less substantive improvements (with respect to patient numbers and absolute change in eGFR) in kidney function between diagnosis and 12-months irrespective of baseline KDIGO stage. These findings should, however, be considered in the context of a relatively small sample size for the PR3-ANCA seropositive subgroup. usCD163, usCD25, uMCP-1 have been identified as promising biomarkers for active renal vasculitis in adult-onset AAV. Several studies demonstrate significantly elevated concentrations of these proteins in adults with active renal vasculitis, defined by the vasculitis activity score (renal BVAS), compared to those with active extra renal vasculitis and healthy individuals 74â77,85. These studies have led to proposed optimum cut-off values for each of these proteins to distinguish active renal and extra renal vasculitis: 125 ng/mmol of creatinine for usCD25 (sensitivity: 70.8 %, specificity 76.5%) 77 and several values for usCD163 ranging from 0.3 to 85 350 ng/mmol of creatinine with varying sensitivities and specificities 74,76,77. Although my findings demonstrate that usCD163 and usCD25 concentrations were significantly elevated in children with moderate-to-high kidney disease activity compared to healthy individuals, mirroring findings in adult-onset AAV, neither usCD163 nor usCD25 concentrations differed significantly between children who had moderate-to-high kidney disease activity at diagnosis (renal pVAS) and those with low-to-no kidney disease activity (Figure 4.3). Within the subgroup of children with kidney disease activity, only total urine protein concentration, not age at onset, biological sex, ANCA status, eGFR, renal pVAS or proteinuria, differed significantly between individuals with and without elevated concentrations of usCD163 and usCD25. Therefore, my findings do not support a role for usCD163, usCD25 and uMCP-1 as indicators of kidney disease activity in childhood-onset SVV. In summary, findings presented in this chapter show, compared to children with PR3-ANCA, those with MPO-ANCA present with higher kidney disease activity and worse kidney function at diagnosis, as reported in adult-onset AAV. In contrast to adult-onset AAV, however, usCD163, usCD25, and uMCP-1 did not exhibit utility as biomarkers of kidney disease activity in childhood-onset AAV. 86 Chapter 5: Conclusion and future directions 5.1 Summary Chronic primary systemic vasculitides (PSV) are a group of complex disorders that, without timely and appropriate treatment, can result in considerable morbidity and mortality. Although advances in treatment have dramatically improved disease outcomes, there is currently no cure for vasculitis; therefore, therapeutic interventions focus on minimizing the accumulation of damage from both the disease and treatment toxicity. The disease can affect both children and adults, but in children, PSV is especially rare. As a result, the clinical management (e.g., classification criteria, treatment regimens) of pediatric-onset vasculitis is largely based on evidence derived from the study of larger cohorts of adults with PSV. This is despite clinical and biological differences in pediatric- and adult-onset disease such as the age at onset, clinical manifestations, comorbidities, and maturity of the immune system that necessitate research in pediatric patients before findings from adults can be integrated into clinical care for this population. The research presented in this thesis aimed to assess, in pediatric patients, the utility of biomarkers, namely ANCA and urine proteins, that have been derived from the study of adult-onset AAV. Results presented in Chapter 3 of this thesis demonstrated that ANCA seropositivity and specificity for MPO or PR3 is associated with the involvement of particular organ systems at diagnosis. Mirroring previous findings in adults, PR3-ANCA seropositivity in childhood-onset AAV was associated with the involvement of multiple organ systems and, commonly, the upper respiratory tract (i.e., ear, nose and throat), while MPO-ANCA seropositive disease was largely limited to the kidneys. In contrast to outcomes reported in adult-onset AAV, children with MPO- 87 ANCA and PR3-ANCA had similar likelihoods of experiencing a relapse between 1 to 2 years after diagnosis. Since more than 80% of children with AAV present with kidney involvement, urine proteins identified as promising biomarkers for detecting and monitoring active kidney disease in adults were evaluated in pediatric patients in Chapter 4 of this thesis. While usCD163 and usCD25 were detected in a subset of children with moderate-to-high kidney disease activity, neither protein correlated with kidney disease activity or kidney function at diagnosis, or one year later, suggesting that the utility of these biomarkers in children does not mirror their use in adults. 5.2 Clinical significance Since the early 1990s, several classification criteria have been proposed to distinguish AAV subtypes on the basis of clinical, histopathological and radiological findings 33,40,104,110,111. However, these criteria have limitations as the same patients can be classified differently depending on the criteria used, while a large proportion remain unclassified, resulting in delayed diagnosis and treatment. Recently, Lyons et al. demonstrated a stronger association between genetic susceptibility to AAV and ANCA specificity compared to the clinically defined phenotypes 23. These findings, in conjunction with clinical evidence supporting the prognostic value of ANCA and the benefits of treating patients stratified by ANCA differently 62, have led to ANCA seropositivity and specificity being increasingly considered for the classification of AAV. Reflecting this shift in perspective, the most recent 2022 ACR/EULAR classification criteria heavily weighs ANCA specificity for MPO and PR3 in the subtype classification of adult AAV patients 36,37. 88 Previously, Lionaki et al. have identified PR3-ANCA seropositivity as a predictor of relapse in adult-onset AAV, with PR3-ANCA seropositive patients being almost twice as likely to relapse than those with MPO-ANCA 62. The findings presented in this thesis do not suggest a similar utility for PR3-ANCA seropositivity in childhood-onset AAV. Almost 40% (147/374) of adults in the cohort described by Lionaki et al. experienced a relapse 62. A similarly high incidence of relapse has also been reported by other studies in adult-onset AAV 100,101. In contrast, a major or minor relapse was observed in only 11% (16/50) of children in my cohort, suggesting a re-evaluation of whether a biomarker for relapse would be clinically useful for children, considering the relatively low frequency of relapses in this population during this time period. While usCD163, usCD25, and uMCP-1 have been identified as promising biomarkers of active kidney disease in adult-onset AAV, these proteins did not exhibit such a utility in childhood-onset AAV. These findings highlight the need to assess adult-derived tools in children prior to adopting them into clinical practice for this population. Moreover, it provides strong evidence to study disease mechanisms and markers of childhood-onset AAV separate from adult-onset AAV. 5.3 Study limitations and future directions Duration of follow-up: Outcome assessment in this study was limited to times of follow-up study visits, namely at 1- and 2-years post-diagnosis. While there was no difference in the likelihood of a relapse occurring within this time frame among MPO- and PR3-ANCA seropositive children with AAV in my cohort, it would be of interest to evaluate relapse rates between two to five years post-diagnosis given the mean time to relapse in adult-onset AAV is 31.3 months 62. With an extended period for follow-up data, it would be possible to assess whether relapse rates are 89 indeed considerably lower in childhood-onset AAV compared to adult-onset AAV, and, secondarily, if ANCA status informs the likelihood of a âlateâ relapse. Cohort size and data availability: Due to the rarity of pediatric-onset AAV, the research presented in this thesis relied on contributions (of data and samples) from investigators at ~ 40 centres worldwide over a period of 10-15 years. Despite this, and the ARChiVE/PedVas cohort being the largest collection of data and samples from children with PSV, some analyses were still underpowered due to small sample sizes and/or data availability. For example, comparisons with the ANCA-negative subgroup were underpowered due to its relatively small size. A sample size of 267 was required to achieve 80% power to detect a 20% difference in outcome rate at a significance level of 0.05; however, only n = 150 children had available data for relapse as a disease outcome, only n = 14 of whom were ANCA-negative and only one of whom experienced a relapse. Further, when the ARChiVe/PedVas registry was first established, kidney function was collected as a categorical field (normal, mildly elevated, and moderately-to-severely elevated). Any participant enrolled during this time would not have had a numerical value for serum creatinine from which eGFR could be calculated. As a result, only a subset of my cohort had data for kidney function available. Comparisons of kidney disease trajectory, measured by the changes in eGFR from diagnosis to 6- and 12-months follow-up, were severely underpowered due to limited sample sizes, and compounded by data availability and the stratification of children by kidney function at diagnosis and other timepoints (i.e., diagnosis, 6-months, or 12-months), in addition to ANCA specificity. 90 Urine collection: Mindful of disease rarity, the ARChiVe/PedVas initiative strategized to reduce barriers to site participation in order to maximize the number of patients. In an initial survey, it was found that most study sites did not have the resources to immediately freeze, store and ship (on dry ice) research samples. Furthermore, the cost of dry ice shipments would be prohibitive. Therefore, sample collection was done in such a way that did not require processing, on-site storage, or special shipping conditions. Sample collection was also aligned with routine clinical care visits. Two advantages of this approach are reduced barriers to participation (therefore, greater patient numbers) and a potentially high translatability of findings as the time and method of study data/sample collection is already aligned with clinical practice. There were downsides, however, in this approach, particularly to the collection and storage of urine samples. According to standard best practices, if 24-hour urine collection is not feasible, first morning void is preferred. For this study, however, the timing of urine collection was dictated by clinic visits or in-patient care, therefore, varied. Furthermore, urine osmolality, which is a measure of total solute concentration in the urine, may be impacted by factors unrelated to overall kidney healthy (e.g., hydration status, electrolyte imbalance). Clinical scoring tools: The scoring of overall and organ-specific disease activity via the pVAS is the best available tool for assessing disease activity in pediatric vasculitis. Despite availability of a comprehensive manual and instructional video to support accurate completion of the pVAS assessment form, it is susceptible to human error. For example, all clinical manifestations should theoretically be considered ânewly presentâ at the time of diagnosis; however, if a manifestation was noted prior to diagnosis and progressively worsened, it may be inaccurately scored as 91 âpersistentâ, leading to, in some instances, a lower overall and organ-specific disease activity score. Cohort bias: Previous studies have reported a geographic difference in the incidence and prevalence of AAV likely influenced by factors such as environmental exposures and genetic susceptibility 112. Although the ARChiVe/PedVas registry contains clinical data for more than 600 children with vasculitis from over 40 study sites in 10 countries, not all countries are represented in this registry, with a bias towards larger centres in North America. Additionally, language and cultural barriers may have hindered the recruitment, enrollment, and retention of racial and ethnic minorities. As a result, the generalizability of these data to non-White populations in geographic regions outside of North America may be limited. Future studies may explore underlying differences in gene expression patterns among ANCA-seropositive children in an effort to identify novel biomarkers of active disease in these patients. Since elevated urine proteins (usCD163, usCD25, uMCP1) were not detected or associated with disease activity in this pediatric SVV cohort, an in-depth comparison of children in whom these proteins were detected is needed. Additionally, unsupervised analyses of these urine samples, for example, via urine metabolomics or proteomics, may reveal novel biomarkers of kidney disease. 5.4 Conclusion Using retrospectively collected data and samples from an international cohort of children with vasculitis, the overarching aim of the research presented in this thesis was to determine the utility of adult-derived biomarkers to inform overall and kidney-specific disease at diagnosis and at 1- 92 to 2-year follow-up in pediatric-onset AAV. In this single largest cohort of children with AAV, ANCA seropositivity and specificity delineated differential clinical presentation at diagnosis; however, it was not predictive of overall disease outcomes within the first two years of diagnosis. Similarly, none of the three urine proteins (usCD163, usCD25, uMCP-1) used in the management of adult-onset AAV proved informative to kidney disease in the pediatric population. 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J Clin Med. 2022;11(9):2573. doi:10.3390/jcm11092573 103 Appendices Appendix A: Clinical scoring tools for disease activity (pVAS) and damage (pVDI) A.1 Organ systems and clinical features considered by the pVAS Adapted from Dolezalova et al. (2013) 49. Disease features are scored only when they are due to active vasculitis, after excluding other causes (e.g. infection, hypertension, etc.). If the feature is due to active disease, it is scored in the boxes. It is essential to apply these principles to each item below. Scores have been weighted according to the severity which each symptom or sign is thought to represent. Tick "Persistent Disease" box if all the abnormalities are due to active (but not new or worse) vasculitis. If any of the abnormalities are due to new/worse disease, DO NOT tick the "Persistent Disease" box. For some features, further information (from specialist opinion or further tests) is required if abnormality is newly present or worse. Remember that in most instances, you will be able to complete the whole record when you see the patient. However, you may need further information before entering some items. Please leave these items blank, until the information is available, and then fill them in. For example, if the patient has new onset of stridor, you would usually ask an ENT colleague to investigate this further to determine whether or not it is due to active Wegenerâs granulomatosis. PVAS persistent PVAS new/ worse 1. General Maximum scores 2 3 Myalgia Diffuse, spontaneous, hard to localize muscle pain or tenderness on muscle palpatıon. Exclude fibromyalgia. 1 1 Arthralgia or arthritis Joint pain in any number of joints or presence of objective signs of active synovitis: intraarticular swelling due to synovial proliferation and/or joint effusion with limited range of movement and/or pain on movement or joint tenderness. Any number of joints. 1 1 Fever â¥ 38.0 0C Documented temperature elevation >38ºC. The value refers to axillary/oral temperature (rectal temperature 0.5 ºC higher). Exclude infections by appropriate cultures, serology and PCR methods. 2 2 Weight Loss â¥ 5% body weight At least 5% loss of body weight (not fluid) having occurred since last assessment or in the 4 weeks not as a consequence of dieting 2 2 2. Cutaneous Maximum scores 3 6 Polymorphous exanthema Non-haemorrhagic, non-necrotising skin eruption of any type or combined types. Exclude allergy/drug reaction/infection 1 1 Livedo Purplish reticular pattern usually irregularly distributed around subcutaneous fat lobules, often more prominent with cooling, common over foot margins. Exclude antiphospholipid syndrome. 1 1 Panniculitis Single or multiple tender deep subcutaneous nodules caused by inflammation of deep subcutaneous tissue with typical histopathology findings if biopsy performed 1 1 Purpura Petechiae (small red spots), palpable purpura, or ecchymoses (large plaques) in skin or oozing (in the absence of trauma) in the mucous membranes. 1 2 Skin nodules Subcutaneous nodules, often along arteries, tender on palpation. 1 1 Infarct Nail edge lesion, splinter haemorrhage or flea bite lesion of small vessel vasculitis 1 1 Ulcer Area of full-thickness skin/subcutaneous tissue ulceration/necrosis 1 4 Gangrene Extensive skin/subcutaneous tissue/underlying structure necrosis, digital phalanx or other peripheral (nose, ear tips) necrosis/gangrene 2 6 Other skin vasculıtıs Vasculıtıs dıfferent from prevıous e.g. subcutaneous swelling/oedema due to capillary leak in small vessel involvement, Raynaud´s phenomenon etc. 1 1 3. Ocular Maximum scores 3 6 Mouth ulcers/granulomata Aphtous stomatitis, ischaemic ulcers and/or granulomatous inflammation in oral cavity. Exclude other causes (SLE, infection) 1 2 Genital ulcers Ulcers localised in the genitalia or perineum, excluding infections. 1 1 Adnexal inflammation Salivary (diffuse, tender swelling unrelated to meals) or lacrimal gland inflammation. Exclude other causes (infection). Specialist opinion preferably required. 2 4 Significant proptosis Protrusion of the eyeball due to significant amounts of inflammatory in the orbit; if unilateral, there should be a difference of 2 mm between one eye and the other. This may be associated with diplopia due to infiltration of extra-ocular muscles. Developing myopia (measured on best visual acuity, see later) can also be a manifestation of proptosis 2 4 Red eye (Epi)scleritis Inflammation of the sclerae (specialist opinion usually required). Can be heralded by photophobia. 1 2 Red eye conjunctivitis Blepharitis Keratitis Inflammation of the conjuctivae (exclude infectious causes and excluding uveitis as cause of red eye, also exclude conjunctivitis sicca which should not be scored as this is not a feature of active vasculitis); (specialist opinion not usually required). Inflammation of eyelids. Exclude other causes (trauma, infection). Usually no specialist opinion is required Inflammation of central or peripheral cornea as evaluated by specialist 1 1 104 Blurred vision Altered measurement of best visual acuity from previous or baseline, requiring specialist opinion for further evaluation. 2 3 Sudden visual loss Sudden loss of vision requiring ophthalmological assessment. 6 Uveitis Inflammation of the uvea (iris, ciliary body, choroid) confirmed by ophthalmologist. 2 6 Retinal vasculitis Retinal vessel sheathing on examination by specialist or confirmed by retinal fluoroscein angiography 2 6 Retinal vessel thrombosis Arterial or venous retinal blood vessel occlusion Retinal exudates Any area of soft retinal exudates (exclude hard exudates) seen on ophthalmoscopic examination. Retinal haemorrhages Any area of retinal haemorrhage seen on ophthalmoscopic examination. 4. ENT Maximum scores 3 6 Bloody nasal discharge/ nasal crusts/ulcers and/or granulomata Bloody, mucopurulent, nasal secretion, light or dark brown crusts frequently obstructing the nose, nasal ulcers and/or granulomatous lesions observed by rhinoscopy 2 4 Paranasal sinus involvement Tenderness or pain over paranasal sinuses usually with pathologic imaging (CT, MR, x- ray, ultrasound) 1 2 Subglottic stenosis Stridor and hoarseness due to inflammation and narrowing of the subglottic area observed by laryngoscopy 3 6 PVAS persistent PVAS new/worse Conductive hearing loss Hearing loss due to middle ear involvement confirmed by otoscopy and/or tuning fork examination and/or audiometry 1 3 Sensorineural hearing loss Hearing loss due to auditory nerve or cochlear damage confirmed by audiometry 2 6 5. Chest Maximum scores 3 6 Wheeze or expiratory dyspnea Clinical signs of bronchial obstruction on examination 1 2 Nodules or cavities New lesions, detected by CXR 3 Pleural effusion/pleurisy Pleural pain and/or friction rub on clinical assessment or new onset of radiologically confirmed pleural effusion. Other causes (e.g. infection, malignancy) should be excluded 2 4 Infiltrate Detected by CXR or CT scan. Other causes (infection) should be excluded 2 4 Endobronchial involvement Endobronchial pseudotumor or ulcerative lesions. Other causes such as infection or malignancy should be excluded. NB: smooth stenotic lesions to be included in VDI; subglottic lesions to be recorded in the ENT section. 2 4 Massive haemoptysis/alveolar haemorrhage Major pulmonary bleeding, with shifting pulmonary infiltrates; other causes of bleeding should be excluded if possible 4 6 Respiratory failure Dyspnoea which is sufficiently severe as to require artificial ventilation 4 6 6. Cardiovascular Maximum scores 3 6 Loss of pulses Loss of pulses in any vessel detected clinically; this may include loss of pulses leading to threatened loss of limb 1 4 Bruits over accessible arteries Audible murmurs on auscultation or palpable bruits/thrills over large arteries and aorta 1 2 Blood pressure discrepancy >10 mm Hg difference in any limb 1 2 Claudication of extremities Focal muscle pain elicited usually by physical activity 1 2 Ischaemic cardiac pain Typical clinical history of cardiac pain leading to myocardial infarction or angina. 2 4 Cardiomyopathy Significant impairment of cardiac function due to poor ventricular wall motion confirmed on echocardiography. 3 6 Congestive cardiac failure Heart failure by history or clinical examination 3 6 Valvular heart disease Significant valve abnormalities in the aortic mitral or pulmonary valves detected clinically or echocardiographically. 2 4 Pericarditis Pericardial pain &/or friction rub on clinical assessment 1 3 7. Abdominal Maximum scores 5 9 Abdominal pain Persistent or recurrent abdominal pain, other than vasculitic causes excluded 2 4 105 Peritonitis Acute abdominal pain with peritonism/peritonitis due to perforation/infarction of small bowel, appendix or gallbladder etc., or acute pancreatitis confirmed by radiology/surgery/elevated amylase 3 9 Blood in stools or bloody diarrhoea Overt or occult blood in stools or bloody diarrhoea of recent onset; inflammatory bowel disease, anal fissure and infectious causes excluded. 2 6 Bowel ischaemia Severe and recurrent abdominal pain often with GI bleeding due to ischaemic necrosis of the gut confirmed by imaging or at surgery, with typical appearances of aneurysms or abnormal vasculature characteristic of mesenteric vasculitis. 3 9 8. Kidney Maximum scores 6 12 Hypertension >95th centile Systolic blood pressure greater than 95th centile by age and height 1 4 Proteinuria >0.3g/24hr or >20mmol/mg Cr Persistent >20 mmol/mg creatinine and/or >0.3 g/24 hours. 2 4 Haematuria â¥5 rbc/hpf or red cell casts 10 or more RBC per hpf ( high power field ), excluding urinary infection and urinary lithiasis (stone) 3 6 GFR 50-80ml/min/1.73 m2 Calculated or measured GFR 50-80mls/min/1.73m2. 2 4 GFR 15-49 ml/min/1.73 m2 Calculated or measured GFR 15-49mls/min/1.73m2. 3 6 GFR <15 mk/min/1.73m2 Calculated or measured GFR <15 mls/min/1.73m2 4 8 Rise in creatinine > 10% or Creatinine clearance (GFR) fall > 25% Significant deterioration in renal function attributable to active vasculitis. Rise in creatinine >10% when compared to previous value or fall in calculated or measured GFR >25% 6 9. Nervous system Maximum scores 6 9 Headache New, unaccustomed & persistent headache 1 1 Meningitis/encephalitis Severe headache with neck stiffness ascribed to inflammatory meningitis after excluding infection/bleeding 1 3 Organic confusion/cognitive dysfunction Impaired orientation, memory or other intellectual function in the absence of metabolic, psychiatric, pharmacological or toxic causes. 1 3 Seizures (not hypertensive) Focal motor, generalised or psychomotoric epileptic paroxysm, due to CNS vasculitis. Exclude idiopathic epilepsy, febrile seizures 3 9 Stroke Cerebrovascular accident resulting in focal neurological signs as paresis, weakness etc. 3 9 Cord lesion Transverse myelitis with lower extremity weakness or sensory loss (usually with a detectable sensory level) with loss of sphincter control (rectal & urinary bladder). 3 9 Cranial nerve palsy Facial nerve palsy, recurrent nerve palsy, oculomotor nerve palsy etc. excluding sensorineural hearing loss and ophthalmic symptoms due to inflammation 3 6 Sensory peripheral neuropathy Sensory neuropathy resulting in glove &/or stocking distribution of sensory loss. Other causes should be excluded (e.g. idiopathic, metabolic, vitamin deficiencies, infectious, toxic, hereditary). 3 6 Motor mononeuritis multiplex Simultaneous neuritis of single or many peripheral nerves, only scored if motor involvement. Other causes should be excluded (diabetes, sarcoidosis, carcinoma, amyloidosis). 3 9 10. OTHER Other feature of active vasculitis (e.g. malaise, pulmonary hypertension, auricular chondritis etc.) - please describe 106 A.2 Organ systems and clinical features considered by the pVDI Adapted from Dolezalova et al. (2014) 87.
Thesis/Dissertation
eng
Microbiology and Immunology
Vancouver : University of British Columbia Library
Attribution-NonCommercial-NoDerivatives 4.0 International
Graduate
Brown, Kelly L.
Evaluating the utility of adult-defined biomarkers in childhood-onset chronic primary systemic vasculitis
Text