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

ABSTRACT: 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.

SUBMITTER: Cole JB

PROVIDER: S-EPMC7081342 | biostudies-literature | 2020 Mar

REPOSITORIES: biostudies-literature

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

Cole Joanne B JB Florez Jose C JC Hirschhorn Joel N JN

Nature communications 20200319 1

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 ...[more]

PMID: 32193382

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Project description:Background and aimsExcess energy intake can lead to metabolic dysfunction-associated steatotic liver disease (MASLD), but the relationship between dietary carbohydrate intake and liver fat content remains unclear. This study aimed to examine the associations between types and sources of dietary carbohydrates and liver fat content.MethodsUK Biobank participants with no pre-existing diabetes, liver disease or cardiovascular disease reported dietary intake of types and sources of carbohydrates (total carbohydrates, free sugars, non-free sugars, starch from whole grains, starch from refined grains, and fibre) on at least two 24-h dietary assessments. In cross-sectional analyses, (n = 22,973), odds ratios (OR) of high liver fat content (defined as a score of ≥ 36 in the hepatic steatosis index) by quintiles of carbohydrate intakes were estimated using multivariable logistic regression models. In prospective analyses, a second sample (n = 9268) had liver proton density fat fraction (PDFF) measured by magnetic resonance imaging (2014-2020). Multivariable linear regression models estimated geometric means of PDFF (%) by quintiles of carbohydrate intakes. Models were adjusted for demographic and lifestyle confounders, including total energy intake.ResultsIn the cross-sectional analyses, 6894 cases of high liver fat content were identified. Inverse associations between intakes of fibre (OR of highest vs. lowest quintile 0.46 [95% CI: 0.41-0.52]), non-free sugars (0.63 [0.57-0.70]) and starch from whole grains (0.52 [0.47-0.57]) with liver fat were observed. There were positive associations between starch from refined grains and liver fat (1.33 [1.21-1.46]), but no association with free sugars (p=0.61). In prospective analyses, inverse associations with PDFF (%) were observed for intakes of fibre (- 0.48 geometric mean difference between highest and lowest quintile of intake [- 0.60 to - 0.35]), non-free sugars (- 0.37 [- 0.49 to - 0.25]) and starch from whole grains (- 0.31 [- 0.42 to - 0.19]). Free sugars, but not starch from refined grains, were positively associated with PDFF (0.17 [0.05 to 0.28]).ConclusionThis study suggests that different carbohydrate types and sources have varying associations with liver fat, which may be important for MASLD prevention. Non-free sugars, fibre, and starch from whole grains could be protective, while associations with free sugars and starch from refined grains are less clear.

Dataset Information

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

Publications

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

Similar Datasets

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