BACKGROUND: Gout is a systemic metabolic disease with rising prevalence and complex etiology, yet its molecular mechanisms remain incompletely defined. Multi-omics Mendelian randomization (MR) enables causal prioritization of genes implicated in gout. Because the gut microbiota (GM) can modulate urate metabolism and inflammation, integrating microbiome analyses may help nominate potential therapeutic candidates. This study aimed to nominate candidate targets for gout by integrating multi-omics MR, clinical validation, GM analysis, and in-silico druggability assessment.
METHODS: We performed multi-omics MR (pQTL/eQTL/mQTL) to prioritize genes with putative causal effects on gout risk. Candidate gene expression patterns were examined in a public single-cell RNA sequencing dataset to determine their distribution across immune cell subtypes and functional context. Associations between identified candidate genes and GM composition were evaluated using the MiBioGen database. Potential therapeutic interactions were predicted through the Comparative Toxicogenomics Database (CTD). Expression of candidate genes was validated in peripheral blood samples from 51 gout patients and 50 healthy controls by quantitative real-time polymerase chain reaction (qRT-PCR). Finally, molecular docking and molecular dynamics (MD) simulations were conducted to explore binding poses and stability between prioritized proteins and predicted drugs.
RESULTS: MR analysis identified four gout-associated genes (BAIAP2, CD248, GCHFR, and ABHD14B). Among them, BAIAP2, CD248, and GCHFR showed significant causal relationships with specific gut microbial taxa in MiBioGen, whereas ABHD14B showed no GM associations. CTD-based drug prediction further highlighted three compounds-benzbromarone, calcitriol, and cyclosporine-potentially targeting these genes. In an independent cohort (51 gout vs. 50 controls), qRT-PCR confirmed GCHFR dysregulation consistent with MR estimates, and molecular docking plus MD simulations supported stable binding of benzbromarone to GCHFR, providing mechanistic plausibility.
CONCLUSIONS: This integrative framework convergently prioritizes GCHFR as a candidate for therapeutic investigation in gout and identifies CD248, BAIAP2, and ABHD14B as additional gout-related candidates. These results generate testable hypotheses for GCHFR-focused mechanistic and therapeutic studies, as well as further functional studies of the other genes.
