Genomic analysis of diet composition finds novel loci and associations with health and lifestyle
S. Fleur W. Meddens, et al.
Molecular Psychiatry (2020)
Abstract
We conducted genome-wide association studies (GWAS) of relative intake from the macronutrients fat, protein, carbohydrates, and sugar in over 235,000 individuals of European ancestries. We identified 21 unique, approximately independent lead SNPs. Fourteen lead SNPs are uniquely associated with one macronutrient at genome-wide significance (P < 5 × 10−8), while five of the 21 lead SNPs reach suggestive significance (P < 1 × 10−5) for at least one other macronutrient. While the phenotypes are genetically correlated, each phenotype carries a partially unique genetic architecture. 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). In contrast, relative carbohydrate and sugar intake have negative genetic correlations with waist circumference, waist-hip ratio, and neighborhood deprivation (|rg| ≈ 0.1–0.3) and positive genetic correlations with physical activity (rg ≈ 0.1 and 0.2). Relative fat intake has no consistent pattern of genetic correlations with poor health but has a negative genetic correlation with educational attainment (rg ≈−0.1). Although our analyses do not allow us to draw causal conclusions, we find no evidence of negative health consequences associated with relative carbohydrate, sugar, or fat intake. However, our results are consistent with the hypothesis that relative protein intake plays a role in the etiology of metabolic dysfunction.
Scientific Clearing House 
is there a simple way of explaining what this study found?
e.g. one took 225,000 blood or DNA samples from different people and looked at certain SNPs. then one looked at what intake of nutrients people took in (protein, fat, carbodydrates, etc.) and also their behavioral and health profiles (health, weight, education, etc.)
One is trying to correlate genetic traits (SNPs) with behavioral outcomes (or phenotypes).
Diet is usually thought of as an environmental trait unless you follow R Plomin of UK and say ‘genes choose their environment (which may even include your zip code and schoo, as well as income).
They apparently find protein is positively correlated with negative health outcomes (eg diabetes). I know of or have known a few people who have or had type 2 diabetes and many eat or ate alot of protein (sometimes pork, other times alot of things like lentils with quite a bit of oil in combination with nuts and sweets.) Most of them do or did some physical activity, but not alot—most of them spent half their days are driving a car or in front of a computer; one did physical labor maintaining the physical plant of a local university (he also drank alot).
Anecdotally i would say too much protein may be associated with diabetes (as well as high blood pressure) unless you are an extreme athlete or physical worker. USA has a sort of fetish for protein (along with sweets, junk food like french fries, chips, etc.) .
I sort of question whether the 21 or 14 independent or lead SNPs which seemed to correlate with pheotypes would be the only ones, and also whether diet choices can be attributed to genetic rather than environmental causes.
An April 15 2020 article by Morris, Davies, et al in Science Advances (from AAAS) ‘population phenomena inflate genetic associations of complex traits’ seems to be on this topic.
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@ishi I think you basically have it
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