NEW YORK – A team from South Korea and the US has used multivariate analyses on genetic data for millions of individuals to elucidate the genetic architecture of metabolic syndrome, a set of interconnected traits and conditions that have been implicated in type 2 diabetes and heart disease risk.
"Collectively, our results provided new insights into the complex genetic structure of [metabolic syndrome]," co-senior and co-corresponding authors Hong-Hee Won of Sungkyunkwan University School of Medicine and Woojae Myung of Seoul National University Bundang Hospital and their colleagues wrote in a paper published in Nature Genetics on Monday.
For their study, the researchers brought together summary statistic data from previous genome-wide association studies on seven metabolic syndrome-related traits: body mass index, waist circumference, central obesity, fasting glucose levels, type 2 diabetes diagnoses, hypertension, and dyslipidemia.
With genetic data for 151,188 to nearly 1.3 million individuals of European ancestry per trait — more than 4.9 million individuals altogether — the team used a form of multivariate GWAS known as genomic structural equation modeling (genomic SEM) to tease out genetic relationships between the metabolic syndrome contributors.
From a set of 1,650 suspicious SNPs, the investigators narrowed in on 1,307 variants with significant ties to metabolic syndrome, including some SNPs that had not been linked to individual metabolic syndrome-related traits or measurements in the past.
The team flagged more than 400 corresponding genes with the help of mapping, expression quantitative trait locus, and chromatin interaction studies, while transcriptomic analyses using gene expression data from brain, blood, fat, muscle, and other tissue types highlighted 11 metabolic syndrome-associated genes.
Among other results, they found metabolic syndrome-linked SNPs to be associated with gene expression changes, particularly in brain tissue. In addition, phenome-wide association analyses on data for hundreds of thousands of UK Biobank participants offered a look at other disorders associated with the SNPs, including circulatory, respiratory, digestive, kidney, and mental health conditions.
"Most health outcomes with a causal relationship to MetS are related to the circulatory system," the authors reported. "However, the association between digestive, respiratory, and genitourinary system disorders and mental disorders was notable."
Finally, the team came up with a metabolic syndrome polygenic risk score (PRS), dubbed MetS PRS, that distinguished participants of European ancestry who were more likely to develop metabolic syndrome. MetS also showed promise for finding individuals of East Asian ancestry at risk of metabolic syndrome and related conditions in the "Korean Genome and Epidemiology Study" (KoGES) cohorts.
Together, the authors explained, their findings "emphasize the utility of the MetS PRS in identifying individuals at high [cardiovascular disease] risk and in implementing proactive lifestyle adjustments and clinical interventions."