bioRxivGeneticsPreprint
Multi-trait genome-wide association meta-analysis of dietary intake identifies new loci and genetic and functional links with metabolic traits
Jordi MerinoiD, Hassan S. DashtiiD, Chloé SarnowskiiD, Jacqueline M. LaneiD, Miriam S. UdleriD, Petar V. TodoroviD, Yanwei SongiD, Heming WangiD, Jaegil KimiD, Chandler Tucker, John N. CampbelliD, Toshiko TanakaiD, Audrey Y. ChuiD, Linus T.-Y. TsaiiD, Tune H. PersiD, Daniel I. ChasmaniD, Josée DupuisiD, Martin K. RutteriD, José C. FloreziD, Richa SaxenaiD
Abstract
Dietary intake, a major contributor to the global obesity epidemic1-5, is a complex phenotype partially affected by innate physiological processes.6-11 However, previous genome-wide association studies (GWAS) have only implicated a few loci in variability of dietary composition.12-14 Here, we present a multi-trait genome-wide association meta-analysis of inter-individual variation in dietary intake in 283,119 European-ancestry participants from UK Biobank and CHARGE consortium, and identify 96 genome-wide significant loci. Dietary intake signals map to different brain tissues and are enriched for genes expressed in {beta}1-tanycytes and serotonergic and GABAergic neurons. We also find enrichment of biological pathways related to neurogenesis. Integration of cell-line and brain-specific epigenomic annotations identify 15 additional loci. Clustering of genome-wide significant variants yields three main genetic clusters with distinct associations with obesity and type 2 diabetes (T2D). Overall, these results enhance biological understanding of dietary composition, highlight neural mechanisms, and support functional follow-up experiments.
- organism: human
- assay: GWAS summary statistics
- research focus: GWAS / association mapping
- approach: statistical model
- Citations
- 3
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