RT Journal Article
SR Electronic
T1 Multi-trait genome-wide association meta-analysis of dietary intake identifies new loci and genetic and functional links with metabolic traits
JF bioRxiv
FD Cold Spring Harbor Laboratory
SP 623728
DO 10.1101/623728
A1 Jordi Merino
A1 Hassan S. Dashti
A1 Chloé Sarnowski
A1 Jacqueline M. Lane
A1 Miriam S. Udler
A1 Petar V. Todorov
A1 Yanwei Song
A1 Heming Wang
A1 Jaegil Kim
A1 Chandler Tucker
A1 John Campbell
A1 Toshiko Tanaka
A1 Audrey Y. Chu
A1 Linus Tsai
A1 Tune H. Pers
A1 Daniel I. Chasman
A1 Josée Dupuis
A1 Martin K. Rutter
A1 Jose C. Florez
A1 Richa Saxena
YR 2019
UL http://biorxiv.org/content/early/2019/05/01/623728.abstract
AB 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 β1-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.