Moving from GWAS signals to rare functional variation in inflammatory bowel disease through application of GenePy2 as a potential DNA biomarker

ObjectivesWe adopt a weighted variant burden score GenePy2.0 for the UK Biobank phase 2 cohort of inflammatory bowel disease (IBD), to explore potential genomic biomarkers underpinning IBDs known associations. DesignNucleating from IBD GWAS signals, we identified 794 GWAS loci, including target genes/LD-blocks (LDBs) based on linkage-disequilibrium (LD) and functional mapping. We calculated GenePy2.0-a burden score of target regions integrating variants with CADDPhred>15 weighted by deleteriousness and zygosity. Collating with other burden-based test, GenePy-based Mann-Whitney-U tests on cases/controls with varying extreme scores were used. Significance-levels and effect sizes were used for tuning the optimal GenePy thresholds for discriminating patients from controls. Individuals binarized GenePy status (above or below threshold) of candidate regions, was subject to itemset association test via the sparse Apriori algorithm. ResultsA tailored IBD cohort was curated (nCrohns_Disease(CD)=891, nUlcerative_Colitis(UC)=1409, nControls=60118). Analysing 885 unified target regions (794 GWAS loci and 104 monogenic genes with 13 overlaps), the GenePy approach detected statistical significance (permutation p<5.65x10-5) in 35 regions of CD and 25 of UC targets exerting risk and protective effects on the disease. Large effect sizes were observed, e.g. CYLD-AS1 (Mann-Whitney-{square}=0.89[CI:0.78-0.96]) in CD/controls with the top 1% highest scores of the gene. Itemset association learning further highlighted an intriguing signal whereby GenePy status of IL23R and NOD2 were mutually exclusive in CD but always co-occurring in controls. ConclusionGenePy score per IBD patient detected deleterious variation of large effect underpinning known IBD associations and proved itself a promising tool for genomic biomarker discovery. What is already known on this topicInflammatory bowel disease (IBD) is a genetically heterogeneous disease with both common polygenic, and rare monogenic, presentations. Previous studies have identified known genetic variants associated with disease. What this study addsA genomic biomarker tool, tailored for large cohort, GenePy2.0 is developed. Its rank-based test is more powerful than mutation-burden based test in validating known associations and finding new associations of IBD. We identified large risk and protective effects of pathogenic genes/loci in IBD, including expanding previous associations to wider genomic regions. How this study might affect research, practice or policyGenePy2.0 facilitates analysis of diseases with genetic heterogeneity and facilitates personalised genomic analysis on patients. The revealed genetic landscape of IBD captures both risk and protective effects of rare pathogenic variants, alongside more common variation. This, could provide a fresh angle for future targeted therapies in specific groups of patients.