ArticleClinical, cosmetic and investigational dermatology2026
Causal Effects of Inflammatory Proteins and Metabolites on Skin Soft Tissue Infections: Mendelian Randomization and Mediation Analysis.
Article in Clinical, cosmetic and investigational dermatology, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Introduction: The pathogenesis of skin and soft tissue infections (SSTIs) remains incompletely understood, particularly regarding the causal relationships between circulating inflammatory proteins (CIPs), metabolites, and infection susceptibility. Mendelian randomization (MR) provides an approach to investigate potential causal associations while reducing confounding and reverse causation. Methods: We conducted a bidirectional two-sample MR study integrating proteomic and metabolomic data. Genetic instruments for 91 CIPs were obtained from a proteomic GWAS (14,824 participants), SSTI summary statistics were obtained from the FinnGen consortium (R10 release), and 1400 plasma metabolites were analyzed from the GWAS Catalog. The inverse-variance weighted (IVW) method was used as the primary analysis, with sensitivity analyses performed to evaluate robustness. MR-based mediation analysis was conducted to assess metabolite-mediated pathways. Results: Genetic evidence supported potential causal associations between six CIPs and SSTI risk. Higher genetically predicted IL-12B levels were associated with increased SSTI risk (OR = 1.036, 95% CI: 1.001-1.073, p = 0.044), whereas higher levels of CD40L (OR = 0.954, 95% CI: 0.914-0.996, p = 0.032), CX3CL1 (OR = 0.930, 95% CI: 0.869-0.996, p = 0.038), IL-10 (OR = 0.892, 95% CI: 0.842-0.946, p = 0.0001), IL-13 (OR = 0.935, 95% CI: 0.889-0.985, p = 0.012), and TNF-related activation-induced cytokine (OR = 0.952, 95% CI: 0.916-0.989, p = 0.011) were associated with reduced risk. Reverse MR showed no evidence of SSTI influencing these proteins. Mediation analysis identified an inconsistent mediation pathway involving the threonine-to-pyruvate ratio, which accounted for -7.79% (p = 0.028) of the total IL-10 protective association. Discussion: This study provides genetic evidence supporting potential roles of inflammatory proteins and metabolites in SSTI susceptibility and highlights a counteracting metabolic pathway related to IL-10. The findings expand understanding of host immunometabolic mechanisms underlying SSTI risk. Conclusion: Our findings provide genetic evidence supporting potential causal relationships between CIPs, metabolites, and SSTI susceptibility. Further functional studies are required to validate the identified immunometabolic pathways.
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