ESPEYB25 15. Editors' Choice Genetics (9 abstracts)
15.7. Multivariate genomic analysis of 5 million people elucidates the genetic architecture of shared components of the metabolic syndrome
Park S , Kim S , Kim B , Kim DS , Kim J , Ahn Y , Kim H , Song M , Shim I , Jung SH , Cho C , Lim S , Hong S , Jo H , Fahed AC , Natarajan P , Ellinor PT , Torkamani A , Park WY , Yu TY , Myung W & Won HH
Nat Genet 2024; 56:2380-2391. PMID: 39349817 doi: 10.1038/s41588-024-01933-1
In Brief: The authors perform a large multivariate genome-wide association analysis (GWAS) of components of the metabolic syndrome (MetS) in nearly 5 million individuals. They identify 1,307 independent genetic signals, which are primarily expressed in brain tissues. They analyse transcriptomic data, perform phenome-wide association and Mendelian randomization analyses to highlight associations of MetS with diverse non-cardiometabolic diseases.
Comment: Multivariate (GWAS) is a powerful statistical approach, which leverages information from multiple related traits. It is a particularly relevant approach to study conditions such as Mets, where the definition relies on contributions from different but related traits (i.e. measures of central obesity, dyslipidemia, hypertension and impaired glucose tolerance). By doing this, the authors report by far the largest GWAS for MetS to date. As well as the expected genetic relevance of MetS to obesity, diabetes and cardiovascular disease, unexpected links were identified with renal (e.g. renal failure and urinary tract infection), respiratory (e.g. pneumonia) and mental disorders (e.g. tobacco use and anxiety disorders).
The study provides a rich ‘treasure trove’ of statistical genetics results, which will hopefully inform future experimental work to understand the mechanisms that lead to MetS, particular those underlying their (surprising) enrichment for gene expression in the brain.
Volume 22
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ESPE Yearbook of Paediatric Endocrinology
ISSN 1662-4009 (Online)
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