Integrative Transcriptomic and Genetic Analysis Prioritizes IRF1 as a Candidate Regulatory Gene Associated with Ulcerative Colitis

Abstract

Background Ulcerative colitis (UC) is a chronic inflammatory bowel disease with a complex and incompletely understood pathogenesis. This study aimed to prioritize candidate genes associated with UC and characterize their potential genetic and immune-related molecular context using an integrative transcriptomic and genetic framework. Methods Bulk transcriptomic analysis was first performed using the discovery cohort GSE87466. After duplicated gene symbols were collapsed by mean expression, differential expression analysis and weighted gene co-expression network analysis (WGCNA) were conducted to identify UC-related candidate genes. Candidate genes for downstream analyses were defined by the overlap between differentially expressed genes and genes within selected WGCNA core modules. An expression quantitative trait locus-based summary-data-based Mendelian randomization (SMR) framework integrating UC genome-wide association study data with blood-derived eQTL data was subsequently applied to prioritize putative gene–disease associations. Functional enrichment analysis, CIBERSORT-based immune infiltration analysis, single-gene gene set enrichment analysis, and single-cell RNA sequencing analyses were performed to characterize the biological context of the prioritized genes. Three independent transcriptomic cohorts were used for external validation, and a small DSS-induced colitis mouse experiment was used for exploratory experimental assessment. Results eQTL-based SMR analysis identified IRF1 and JAK2 as candidate genes associated with UC susceptibility. IRF1 was prioritized for downstream characterization based on convergent evidence from transcriptomic, immune, single-cell, and experimental analyses. IRF1 expression was associated with multiple CIBERSORT-inferred immune-cell proportions, including positive correlations with M1 macrophages, neutrophils, activated dendritic cells, and T follicular helper cells, and negative correlations with M2 macrophages and activated natural killer cells. Higher IRF1 expression was associated with interferon, NF-κB, and IL-6/JAK/STAT3 signaling pathways. Single-cell analysis showed IRF1 expression across myeloid cells, fibroblasts, endothelial cells, and epithelial cells. DSS-treated mice showed descriptively higher colonic IRF1 protein expression, providing preliminary experimental support consistent with human transcriptomic findings. Conclusion IRF1 was prioritized as a candidate gene associated with UC and was linked to interferon-related inflammatory pathways and altered immune-cell profiles. These findings provide an integrated framework for further investigation of the potential role of IRF1 in UC. Given the use of blood-derived eQTL data and preliminary animal evidence, the findings should be considered hypothesis-generating and require further functional validation.