Genomic analysis of diet composition finds novel loci and associations with health and lifestyle
S Fleur W Meddens,
Ronald de Vlaming,
Casper AP Burik,
Richard Karlsson Linnér,
Cornelius A. Rietveld,
Mark Alan Fontana,
Peter J van der Most,
Kaitlin H Wade,
Emma L Anderson,
Kim VE Braun,
Pauline M Emmett,
Juan R Gonzalez,
Jessica C Kiefte-de Jong,
Josje D Schoufour,
Frank JA van Rooij,
Bruce HR Wolffenbuttel,
23andMe Research Team, EPIC-InterAct Consortium, Lifelines Cohort Study,
George Davey Smith,
Oscar H Franco,
Nita G Forouhi,
M. Arfan Ikram,
Andre G Uitterlinden,
Jana V van Vliet-Ostaptchouk,
Nick J Wareham,
K. Paige Harden,
James J Lee,
Daniel J Benjamin,
Carson C. Chow,
Philipp D Koellinger
Posted 02 Aug 2018
bioRxiv DOI: 10.1101/383406 (published DOI: 10.1038/s41380-020-0697-5)
Posted 02 Aug 2018
We conducted genome-wide association study (GWAS) meta-analyses of relative caloric intake from fat, protein, carbohydrates and sugar in over 235,000 individuals. We identified 21 approximately independent lead SNPs. Relative protein intake exhibits the strongest relationships with poor health, including positive genetic associations with obesity, type 2 diabetes, and heart disease (rg ≈ 0.15-0.5). Relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood poverty (|rg| ≈ 0.1-0.3). Overall, our results show that the relative intake of each macronutrient has a distinct genetic architecture and pattern of genetic correlations suggestive of health implications beyond caloric content.
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