Comprehensive genomic analysis of dietary habits in UK Biobank identifies hundreds of genetic associations

• Published in: Nature communications Vol. 11; no. 1; p. 1467
• Main Authors: Cole, Joanne B., Florez, Jose C., Hirschhorn, Joel N.
• Format: Journal Article
• Language: English
• Published: London Nature Publishing Group UK 19.03.2020; Nature Publishing Group; Nature Portfolio
• Subjects: 45/43; 631/208/1515; 631/208/205/2138; 692/700/2814; Biobanks; Biological Specimen Banks; Cardiovascular disease; Coronary artery; Coronary artery disease; Diabetes mellitus (non-insulin dependent); Diet; Dietary intake; Eating; Feeding Behavior; Food; Food intake; Genetic analysis; Genetic Association Studies; Genetic Loci; Genetics; Genome-Wide Association Study; Genomic analysis; Genomics; Heart diseases; Heritability; Humanities and Social Sciences; Humans; Inheritance Patterns - genetics; Mendelian Randomization Analysis; multidisciplinary; Phenotyping; Polymorphism, Single Nucleotide - genetics; Principal Component Analysis; Randomization; Receptors, Odorant - metabolism; Risk analysis; Risk Factors; Science; Science (multidisciplinary); Tea; United Kingdom; United Kingdom; United Kingdom > UK
• ISSN: 2041-1723; 2041-1723
• DOI: 10.1038/s41467-020-15193-0

Unhealthful dietary habits are leading risk factors for life-altering diseases and mortality. Large-scale biobanks now enable genetic analysis of traits with modest heritability, such as diet. We perform a genomewide association on 85 single food intake and 85 principal component-derived dietary patterns from food frequency questionnaires in UK Biobank. We identify 814 associated loci, including olfactory receptor associations with fruit and tea intake; 136 associations are only identified using dietary patterns. Mendelian randomization suggests our top healthful dietary pattern driven by wholemeal vs. white bread consumption is causally influenced by factors correlated with education but is not strongly causal for coronary artery disease or type 2 diabetes. Overall, we demonstrate the value in complementary phenotyping approaches to complex dietary datasets, and the utility of genomic analysis to understand the relationships between diet and human health. The choice of food intake is at least partially influenced by genetics, even though the effect sizes appear rather modest. Here, Cole et al. perform GWAS for food intake (85 individual food items and 85 derived dietary patterns) and test potential causal relationships with cardiometabolic traits using Mendelian randomization.