Frontiers in immunology · 2026
Multi-dimensional evidence establishing the causal association between metabolic syndrome and gout and the molecular mechanisms of comorbidity.
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Li Jianbin, Zhang Jiamin, Li Suiran, Yao Xiaoge, Li Renhe, Liu Wei
Аннотация
OBJECTIVE: To systematically evaluate the causal association between metabolic syndrome (MetS) and its components with gout through integrated multi-dimensional methods, and reveal the genetic basis and transcriptomic characteristics of comorbidity.
METHODS: A three-phase research design was employed: (1) Real-world clinical cohort (n=8,853) was analyzed using propensity score matching (PSM), restricted cubic spline (RCS), and latent class trajectory modeling; (2) Two-sample Mendelian randomization (MR) and linkage disequilibrium score regression (LDSC) were applied for causal inference and genetic correlation assessment; (3) Transcriptomic data (GSE160170, GSE98895) were integrated for molecular mechanism analysis, with single-cell RNA sequencing data (GSE217561) used for hub gene cell-type specificity validation.
RESULTS: After PSM, MetS remained an independent risk factor for gout (OR = 1.456, 95%CI: 1.212-1.750, P<0.001), with hypertension (OR = 2.984) and hyperlipidemia (OR = 2.719) showing strongest associations. RCS analysis revealed significant non-linear relationships between metabolic indicators and gout risk. Trajectory analysis identified three triglyceride dynamic patterns, with the progressive elevation type showing significantly increased gout risk (HR = 1.92, P<0.001). MR analysis confirmed causal associations for MetS (OR = 1.171, P<0.001), hypertension (OR = 5.426, P = 0.002), triglycerides (OR = 1.325, P<0.001), and waist circumference (OR = 1.523, P<0.001), while HDL-C showed protective effect (OR = 0.887, P = 0.049); fasting blood glucose showed no significant causal association. LDSC revealed significant genetic correlation (rg=0.321, P = 4.24×10-15). Gene-level MR identified common risk genes including SNX11 and PGAP3, enriched in ABC transporters and immune regulatory pathways. Transcriptomic analysis identified core hub genes including JUN and FOS, enriched in Th17 cell differentiation and Toll-like receptor signaling pathways. Single-cell validation confirmed hub genes exhibited highest expression in monocytes and dendritic cells, with JUN, FOS, and IFNGR1 significantly upregulated in gout patients (P<0.0001), while TAP2 showed no expression change, supporting its pathogenic role through functional defects rather than transcriptional alterations.
CONCLUSION: This study systematically established the causal association between MetS and gout through multi-dimensional evidence chains, revealing the molecular mechanism of comorbidity centered on antigen presentation-immune response and proposing a TAP2-UPR-Th17 pathological axis. These findings provide evidence-based support for early risk stratification and precision prevention of gout based on metabolic phenotypes.
METHODS: A three-phase research design was employed: (1) Real-world clinical cohort (n=8,853) was analyzed using propensity score matching (PSM), restricted cubic spline (RCS), and latent class trajectory modeling; (2) Two-sample Mendelian randomization (MR) and linkage disequilibrium score regression (LDSC) were applied for causal inference and genetic correlation assessment; (3) Transcriptomic data (GSE160170, GSE98895) were integrated for molecular mechanism analysis, with single-cell RNA sequencing data (GSE217561) used for hub gene cell-type specificity validation.
RESULTS: After PSM, MetS remained an independent risk factor for gout (OR = 1.456, 95%CI: 1.212-1.750, P<0.001), with hypertension (OR = 2.984) and hyperlipidemia (OR = 2.719) showing strongest associations. RCS analysis revealed significant non-linear relationships between metabolic indicators and gout risk. Trajectory analysis identified three triglyceride dynamic patterns, with the progressive elevation type showing significantly increased gout risk (HR = 1.92, P<0.001). MR analysis confirmed causal associations for MetS (OR = 1.171, P<0.001), hypertension (OR = 5.426, P = 0.002), triglycerides (OR = 1.325, P<0.001), and waist circumference (OR = 1.523, P<0.001), while HDL-C showed protective effect (OR = 0.887, P = 0.049); fasting blood glucose showed no significant causal association. LDSC revealed significant genetic correlation (rg=0.321, P = 4.24×10-15). Gene-level MR identified common risk genes including SNX11 and PGAP3, enriched in ABC transporters and immune regulatory pathways. Transcriptomic analysis identified core hub genes including JUN and FOS, enriched in Th17 cell differentiation and Toll-like receptor signaling pathways. Single-cell validation confirmed hub genes exhibited highest expression in monocytes and dendritic cells, with JUN, FOS, and IFNGR1 significantly upregulated in gout patients (P<0.0001), while TAP2 showed no expression change, supporting its pathogenic role through functional defects rather than transcriptional alterations.
CONCLUSION: This study systematically established the causal association between MetS and gout through multi-dimensional evidence chains, revealing the molecular mechanism of comorbidity centered on antigen presentation-immune response and proposing a TAP2-UPR-Th17 pathological axis. These findings provide evidence-based support for early risk stratification and precision prevention of gout based on metabolic phenotypes.