TY - JOUR

T1 - Using genetic variation to disentangle the complex relationship between food intake and health outcomes

AU - Pirastu, Nicola

AU - McDonnell, C

AU - Grzeszkowiak, Eryk Jan

AU - Mounier, Ninon

AU - Imamura, Fumiaki

AU - Jordi Merino, PhD

AU - Day, Felix

AU - Zheng, Jie

AU - Taba, Nele

AU - concas, maria pina

AU - Repetto, Linda

AU - Kentistou, Katherine

AU - Robino, Antonietta

AU - Esko, Tõnu

AU - Joshi, Peter

AU - Fischer, Krista

AU - Ong, Ken

AU - Gaunt, Tom

AU - Kutalik, Z

AU - Perry, JRB

AU - Wilson, James F

PY - 2022

Y1 - 2022

N2 - Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes.

AB - Diet is considered as one of the most important modifiable factors influencing human health, but efforts to identify foods or dietary patterns associated with health outcomes often suffer from biases, confounding, and reverse causation. Applying Mendelian randomization in this context may provide evidence to strengthen causality in nutrition research. To this end, we first identified 283 genetic markers associated with dietary intake in 445,779 UK Biobank participants. We then converted these associations into direct genetic effects on food exposures by adjusting them for effects mediated via other traits. The SNPs which did not show evidence of mediation were then used for MR, assessing the association between genetically predicted food choices and other risk factors, health outcomes. We show that using all associated SNPs without omitting those which show evidence of mediation, leads to biases in downstream analyses (genetic correlations, causal inference), similar to those present in observational studies. However, MR analyses using SNPs which have only a direct effect on the exposure on food exposures provided unequivocal evidence of causal associations between specific eating patterns and obesity, blood lipid status, and several other risk factors and health outcomes.

U2 - 10.1371/journal.pgen.1010162

DO - 10.1371/journal.pgen.1010162

M3 - Journal article

C2 - 35653391

VL - 18

JO - P L o S Genetics

JF - P L o S Genetics

SN - 1553-7390

IS - 6

M1 - e1010162

ER -