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Multi-trait genome-wide association meta-analysis of dietary intake identifies new loci and genetic and functional links with metabolic traits

By Jordi Merino, Hassan S. Dashti, Chloé Sarnowski, Jacqueline M Lane, Miriam S. Udler, Petar V Todorov, Yanwei Song, Heming Wang, Jaegil Kim, Chandler Tucker, John Campbell, Toshiko Tanaka, Audrey Y Chu, Linus Tsai, Tune H Pers, Daniel I Chasman, Josée Dupuis, Martin K. Rutter, Jose C Florez, Richa Saxena

Posted 01 May 2019
bioRxiv DOI: 10.1101/623728

Dietary intake, a major contributor to the global obesity epidemic, is a complex phenotype partially affected by innate physiological processes. However, previous genome-wide association studies (GWAS) have only implicated a few loci in variability of dietary composition. 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 b1-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.

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