Integrative multi-omics analyses suggest a candidate microbial metabolite-associated host gene network in ulcerative colitis.

Ulcerative colitis (UC) is associated with gut microbial dysbiosis, but the host molecular alterations potentially linked to microbially derived metabolites remain incompletely understood. We integrated Mendelian randomization (MR), microbial metabolite annotation, computational target prediction, colonic transcriptomics, network analysis, and machine learning. MiBioGen microbiome GWAS data were used as exposures and FinnGen Release 12 ULCERENTER as the outcome. Metabolites linked to MR-prioritized taxa were retrieved from GutMGene, and human targets were predicted using SwissTargetPrediction and SEA. UC-related genes were defined by integrating differential expression analysis and WGCNA and then intersected with predicted metabolite targets. MR prioritized one family and eight genera showing nominal genetically supported associations with UC, but none remained significant after Benjamini-Hochberg FDR correction. Three prioritized genera were linked to 15 microbe-metabolite records, corresponding to 13 unique metabolites; nine were retained for target prediction, yielding 277 unique predicted human targets. Transcriptomic analysis identified 1,530 DEGs and a 312-gene MEgrey60 module, with 273 overlapping genes, producing 1,569 unique UC-related genes. Their intersection with the 277 predicted targets yielded 47 candidate genes. Enrichment analyses highlighted mainly metabolic and lipid-related processes. Random Forest showed the highest mean AUC across the two independent external benchmarking cohorts, and SHAP prioritized EPHX1, HSD17B2, IGFBP5, and MMP10. IBDome analysis showed inflammation-associated expression differences in these genes. This study provides a genomics-informed, hypothesis-generating framework that prioritizes candidate microbe-metabolite-host relationships in UC for future experimental validation.