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Integrative Transcriptomic and Genetic Analysis Prioritizes IRF1 as a Candidate Regulatory Gene Associated with
Yanyan Wang1,2, Yuehang Chen1,2, Hailin Wu1,2
1College of Clinical Medicine for Obstetrics & Gynecology and Pediatrics, Fujian Medical University, Fuzhou, Fujian, People's Republic of China.
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.
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