Systematic variant-to-gene mapping highlights TGFB2 and VEGFA as adipokine-coding genes with non-obese, insulin-resistance-like characteristics and distinct disease risks
Chen‐Yang SuiD, Masashi HasebeiD, Adriaan van der GraafiD, Yefeng Yang, Hsuan Megan TsaoiD, Leighton Smith, Guillaume Butler‐LaporteiD, Sirui ZhouiD, Wenmin ZhangiD, Tianyuan LuiD, Satoshi YoshijiiD
Abstract
Adipokines are key metabolic hormones that modulate cardiometabolic risk through multiple distinct biological pathways. To delineate these pathways, we systematically mapped adipokineassociated variants to putative effector genes (V2G) across{square}1,669 human traits in three ancestries from the Million Veteran Program. Grouping the variants by their associations with insulinresistance-related traits yielded six discrete variant clusters, including a "Lipodystrophy" cluster characterised by lower bodymass index but higher waisttohip ratio, fasting glucose, and insulin levels. V2G mapping implicated TGFB2 and VEGFA as candidate effector genes in the Lipodystrophy cluster. VEGFA also appeared in a distinct "Thyroid-adiposity" cluster that was strongly associated with increased insulin resistance and decreased thyroid function. The Thyroid-adiposity cluster comprised variants that are thyroid eQTLs, unlike those in the Lipodystrophy cluster. These findings indicate that VEGFA may influence insulin resistance via two separate mechanisms: abnormal adiposity and altered thyroid function. Although both clusters increased coronary artery disease risk, only the Lipodystrophy cluster increased type{square}2 diabetes risk. Our results highlight mechanistically distinct routes by which adipokines modulate insulin resistance and cardiometabolic disease.
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