Investigating the Genetic Architecture of Juvenile Onset Common Complex Diseases

Abstract

Background and aims: Juvenile idiopathic arthritis (JIA) encompasses a group of childhood rheumatic diseases. JIA is contributed to by genetic and environmental risk factors. The majority of genetic studies utilise common variant association analysis methods when investigating the genetics of JIA. Therefore, this project aimed to investigate rare variants in JIA onset. JIA treatment has greatly improved in recent years but some individuals remain unresponsive to multiple treatments. This is refractory disease. This project aimed to investigate the role of genetics in the onset of refractory disease. Individuals with JIA often develop comorbidities, with JIA associated uveitis (JIAU) being the most common comorbidity. JIAU can be severe in onset, therefore this project aimed to further define risk to uveitis in JIA patients and the role of genetics in JIAU clinical risk factors. Methods: For uveitis analysis, patients were genotyped using the Illumina Infinium CoreExome array. The dataset was restricted to the human leukocyte antigen (HLA) region and SNPs were imputed using SNP2HLA. Logistic regression was used for association analysis of bi-allelic markers and an omnibus test was used for multi-allelic markers. Forward stepwise logistic regression and conditional analysis were used to test for additional effects. Univariate and multivariate analysis were used to investigate clinical and genetic risk factors. For rare variant analysis of JIA, samples were genotyped using the Illumina HumanCoreExome and Illumina Infinium CoreExome genotyping arrays. Genotype calling was conducted using GenCall and zCall. Single variant association analysis was conducted using logistic regression and a SKATO test was used to conduct gene-based association analysis. For refractory analysis, whole exome sequencing (WES) was carried out using the Agilent SureSelect Human all ExonV6 kit. Genetic analysis was conducted using VarSeqTM (v2.2.1). Results: Two genetic markers were confirmed for JIAU, at positions 11 of 13 of HLA-DRB1, and two further signals were detected, rs2523765 of HLA-A and HLA-DPB1*0201. Positions 11 and 13 of HLA-DRB1, rs2523765 and HLA-DPB1*0201 were also associated in “polygo” subtypes of JIA. The clinical risk factor ANA status was found to be a good predictor of uveitis outcome. Rare variant analysis revealed association signals at the gene regions of interest PRSS57, ANKRD54, MVK, WISP3, LIL2RA and VIPAS39. Analysis of refractory patients revealed that 13 individuals carried pathogenic variants for other paediatric diseases, 20 individuals carried rare variants from known JIA susceptibility loci and there were an additional 24 variants within genes linked to other diseases or immune related genes of interest to JIA. Conclusions: This PhD has investigated the role of genetic risk factors in JIA, JIAU and refractory JIA and has implications to improve the diagnosis and treatment of JIA. Genetic risk factors for JIAU can be combined with current screening guidelines to define individuals most at risk of uveitis. Rare variant analysis has highlighted the role that rare variants play in JIA onset and requires further analysis. Refractory analysis revealed that individuals with JIA carry rare variants for paediatric diseases and rare immune related variants that requires further analysis.

Date of Award	1 Aug 2023
Original language	English
Awarding Institution	The University of Manchester
Supervisor	Andrew Morris (Supervisor), John Bowes (Supervisor) & Tracy Briggs (Supervisor)