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Diabetes, Cardiovascular Risks, and Lipoproteins / Adipokines, Inflammation, and Metabolic Diseases · Journal article
International Journal of Molecular Sciences · September 9, 2026
Encouraging direction, but not yet definitive.
This multivariate genome-wide association study identified 79 genetic variants associated with metabolic syndrome in Korean populations, substantially more than conventional univariate analysis (which detected 2 variants). All findings replicated in independent validation cohorts, but functional mechanisms and clinical impact remain to be established.
Multivariate genome-wide association study with discovery and validation cohorts. Korean adults from the Korean Genome and Epidemiology Study with and without metabolic syndrome.. n = 67,245. Korea (Ansan and Ansung studies, CAVAS, HEXA cohorts).
Multivariate analyses identified 79 significant single-nucleotide polymorphisms compared to 2 APOA5 variants detected by logistic regression All 79 variants were replicated in the HEXA cohort Functional annotation prioritized 27 high-risk variants mapping to 12 genes
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This discovery of pleiotropic genetic loci may inform understanding of metabolic syndrome biology and potentially support development of biomarkers for early detection; however, clinical utility requires functional validation and demonstration that these variants improve prediction or guide intervention.
A well-designed multivariate genome-wide association study with discovery and validation cohorts identifying 79 susceptibility loci for metabolic syndrome; findings are replicable but represent discovery in a specific population without functional or clinical validation.
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Quoted from the source exactly as published.
This discovery of pleiotropic genetic loci may inform understanding of metabolic syndrome biology and potentially support development of biomarkers for early detection; however, clinical utility requires functional validation and demonstration that these variants improve prediction or guide intervention.
Graded across the dimensions that decide whether you should act, each from what the source actually supports. There is no single score, and where a dimension was not assessed it says so.
Metabolic syndrome (MetS), characterized by a cluster of interrelated metabolic abnormalities including central obesity, elevated blood pressure, dysglycemia, hypertriglyceridemia, and reduced high-density lipoprotein cholesterol (HDL-C), substantially increases type 2 diabetes and cardiovascular disease risk. Conventional genome-wide association studies (GWASs) analyze individual traits or a dichotomized MetS status, only partially capturing its heritability and potentially overlooking variants with shared (pleiotropic) effects across correlated traits. Here, we performed a multiple-trait GWAS using data from the Korean Genome and Epidemiology Study. Using the Korea Biobank Array (K-Chip), we analyzed a discovery cohort from the Ansan and Ansung studies (1490 cases and 3856 controls) and validated the findings in CAVAS (3620 cases and 4461 controls) and HEXA (15,257 cases and 41,807 controls) cohorts. We jointly modeled six MetS-related traits using the complementary multivariate frameworks Multiple Phenotype Association Tests and Genome-wide Efficient Mixed Model Association, alongside a baseline logistic regression. Whereas logistic regression detected 2 APOA5 variants (rs662799 and rs2075291), the multivariate analyses identified 79 significant single-nucleotide polymorphisms; all were replicated in the HEXA cohort. Functional annotation prioritized 27 high-risk variants mapping to 12 genes, whereas pathway analysis (DAVID) implicated eight Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathways related to lipid metabolism. Our findings demonstrate that multivariate analysis substantially improves the identification of pleiotropic susceptibility loci for MetS in the Korean population and indicates candidate genes for early detection and management.
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