PloS one · 2025
Investigating the common genetic basis between inflammatory bowel disease and metabolic syndrome through genomic structural equation modeling.
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Shen Pan, Xiong Hao, Luo Qing-Hua, Ding Yi-Fan, Ge Wei, Liao Wu, Zhang Lei-Chang
Аннотация
BACKGROUND: Inflammatory bowel disease (IBD) and metabolic syndrome (MetS) exhibit a complex interplay, with clinical evidence indicating an increasing incidence of their co-occurrence. However, current research lacks a systematic framework to model the pleiotropic genetic architecture linking gastrointestinal and liver-metabolic phenotypes, thereby hindering a comprehensive understanding of how multiple genetic risk factors converge to drive IBD-MetS comorbidity.
METHODS: This study employed genomic structural equation modeling (SEM) to integrate genome-wide association study (GWAS) summary datasets for IBD and MetS-related traits (body mass index, triglycerides, non-alcoholic fatty liver disease, hypertension, and type 2 diabetes), creating the multivariate GWAS summary datasets. Post-GWAS analytical approaches were subsequently utilized to assess risky loci, gene functionality, and tissue-specific regulatory networks, aiming to elucidate the pathological connections between chronic low-grade inflammation and the gut-liver-metabolic axis.
RESULTS: Genomic SEM identified a shared latent genetic factor between IBD and MetS (Comparative Fit Index = 0.9864, Standardized Root Mean Square Residual = 0.0602). A total of 522 lead single nucleotide polymorphism (SNP) loci were identified, including 21 novel SNPs specific to the multivariate model that were not detected in univariate GWAS. Fine-mapping with SuSiE and FINEMAP identified 29 high-confidence causal SNPs. Integrating SNP fine-mapping with MAGMA, FUSION, and FOCUS analyses confirmed seven core genes.
CONCLUSION: To the best of our knowledge, this study provides the first comprehensive characterization of the shared genetic architecture of IBD and MetS through a multivariate genetic model. The results deepen the understanding of the genetic mechanisms underlying IBD and MetS and offer potential therapeutic targets and a conceptual framework for developing interventions for cross-system diseases.
METHODS: This study employed genomic structural equation modeling (SEM) to integrate genome-wide association study (GWAS) summary datasets for IBD and MetS-related traits (body mass index, triglycerides, non-alcoholic fatty liver disease, hypertension, and type 2 diabetes), creating the multivariate GWAS summary datasets. Post-GWAS analytical approaches were subsequently utilized to assess risky loci, gene functionality, and tissue-specific regulatory networks, aiming to elucidate the pathological connections between chronic low-grade inflammation and the gut-liver-metabolic axis.
RESULTS: Genomic SEM identified a shared latent genetic factor between IBD and MetS (Comparative Fit Index = 0.9864, Standardized Root Mean Square Residual = 0.0602). A total of 522 lead single nucleotide polymorphism (SNP) loci were identified, including 21 novel SNPs specific to the multivariate model that were not detected in univariate GWAS. Fine-mapping with SuSiE and FINEMAP identified 29 high-confidence causal SNPs. Integrating SNP fine-mapping with MAGMA, FUSION, and FOCUS analyses confirmed seven core genes.
CONCLUSION: To the best of our knowledge, this study provides the first comprehensive characterization of the shared genetic architecture of IBD and MetS through a multivariate genetic model. The results deepen the understanding of the genetic mechanisms underlying IBD and MetS and offer potential therapeutic targets and a conceptual framework for developing interventions for cross-system diseases.