Achkar, Jean–Paul

Abstract Inflammatory bowel diseases (IBD), principally Crohn’s disease (CD) and ulcerative colitis (UC), are common chronic disorders involving inflammation and often progressive tissue damage. Genome-wide association studies have mapped many risk signals, but the causal variants, effector genes and relevant cellular contexts remain difficult to resolve, limiting mechanistic interpretation and therapeutic translation. Here we performed a multi-ancestry GWAS meta-analysis of 125,992 individuals with IBD and more than 1.2 million controls, identifying 619 independent association signals (374 novel) at 420 IBD regions that account for 77–80% of SNP-based heritability. Fine-mapping resolved 81 high-confidence variants, 41 not previously reported. Although most signals were shared between CD and UC, 39% showed IBD subtype specificity, with UC signals showing stronger enrichment in functional annotations from intestinal epithelial, secretory and enteroendocrine cells, and CD showing stronger genetic correlations with circulating inflammatory biomarkers, including C-reactive protein and glycoprotein acetylation. Latent causal modelling supported a causal effect of decreased high-density lipoprotein on CD risk. By integrating bulk and single-cell eQTL and pQTL resources using colocalisation and Mendelian randomisation, together with coding-variant evidence from exome sequencing, we prioritised 664 candidate effector genes across 341 signals, including 390 newly implicated IBD genes, revealing new biological mechanisms and candidate therapeutic targets supported by human genetics.

INTRODUCTION: Patients with ulcerative colitis (UC) who are likely to have primary sclerosing cholangitis (PSC) should be identified because PSC can influence UC clinical behavior and outcomes.The aim of this study was to establish a model incorporating clinical and genetic risk predictors that identifies patients with UC at risk of developing PSC. METHODS: We conducted a retrospective case-control study. Inflammatory bowel disease cohorts from multiple institutions were used as discovery and replicate datasets. Quality control criteria, including minor allele frequency, call rates, Hardy-Weinberg equilibrium, cryptic relatedness, and population stratification (through principal components), were used. Discriminative accuracy was evaluated with area under the receiver operating characteristic curve. RESULTS: Fifty-seven of 581 patients (9.8%) with UC had PSC. Multivariate analysis showed that patients with UC-PSC had more extensive disease (odds ratio [OR], 5.42; P = 1.57E-04), younger diagnosis age (younger than 20 years; OR, 2.22; P = 0.02), and less smoking (OR, 0.42; P = 0.02) than those with UC. After linkage disequilibrium pruning and multivariate analyses, 3 SNPs (rs3131621 at 6p21.33; rs9275596 and rs11244 at 6p21.32) at the HLA region were found associated with a 2- to 3-fold increased risk of PSC. Our model demonstrated good discriminatory power (area under the receiver operating characteristic curve, 88%). DISCUSSION: Three variants in HLA (6p21.3) region significantly distinguished patients with UC-PSC from patients with UC alone. Once further validated in an independent large cohort, our model could be used to identify patients with UC at risk of PSC, and it could also help guide disease management.