@article{bd26029c0f4944a3b42bc6849bd82cc2,
title = "Using genetic variation to disentangle the complex relationship between food intake and health outcomes",
abstract = "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.",
keywords = "Causality, Eating, Genetic Variation, Humans, Outcome Assessment, Health Care, Risk Factors",
author = "Nicola Pirastu and Ciara McDonnell and Grzeszkowiak, \{Eryk Jan\} and Ninon Mounier and Fumiaki Imamura and Jordi Merino and Day, \{Felix R\} and Jie Zheng and Nele Taba and \{Pina Concas\}, Maria and Linda Repetto and Katherine Kentistou and Antonietta Robino and T{\~o}nu Esko and Joshi, \{Peter K\} and Krista Fischer and Ong, \{Ken K.\} and Gaunt, \{Tom R\} and Zoltan Kutalik and Perry, \{John R. B.\} and Wilson, \{James F\}",
note = "Funding Information: J.F.W. acknowledges support from the MRC Human Genetics Unit quinquennial programme grant “QTL in Health and Disease” (MC\_UU\_00007/10). EGCUT was funded by Estonian Research Council Grant IUT20-60, PRG1291 (T.E.), PUT1665 (K.F.), PRG1197 (K.F.), the European Union through the European Regional Development Fund grant no. 2014-2020.4.01.15-0012 GENTRANSMED (T.E.) and 2014-2020.4.2.2 (N.T.) and 2014-2020.4.2.2(T.E.), and Estonian and European Research Roadmap grant no.2014-2020.4.01.16-0125(T.E.). The EPIC-Norfolk study (DOI 10.22025/2019.10.105.00004) has received funding from the Medical Research Council MR/N003284/1, MCPC\_13048, MC-UU\_12015/1, and MC\_UU\_00006/1 (J.P., K.O). The Fenland study (DOI: 10.1186/ ISRCTN72077169) was funded by the Medical Research Council and the Wellcome Trust Ref: 074548.(J.P., K.O., F.I. and F.R.D). J.P., K.O., F.I. and F.R.D were funded by the UK Medical Research Council Epidemiology Unit core grant MC\_UU\_00006/2 and MC\_UU\_00006/3. T.R.G. receives funding from the UK Medical Research Council (MC\_UU\_00011/4). Z.K. received funding from the Swiss National Science Foundation (31003A\_169929). J.M. was partially supported by American Diabetes Association grant \#7-21-JDFM-005 and by the National Institutes of Health grant P30 DK040561. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. This research has been conducted using the UK Biobank Resource under Application Number 19655. We would like to thank Professor George Davey Smith for the precious feedback, Erin MacDonald-Dunlop, and Pascale Lubbe for help with statistical analyses and Dr. Nana Matoba for providing the results from the smoking GWAS. We are grateful to all the participants who have been part of the EPIC-Norfolk study, the Fenland study and to the many members of the study teams at the University of Cambridge who have enabled this research. Publisher Copyright: {\textcopyright} 2022 Pirastu et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.",
year = "2022",
month = jun,
doi = "10.1371/journal.pgen.1010162",
language = "English",
volume = "18",
journal = "PLoS Genetics",
issn = "1553-7390",
publisher = "Public Library of Science",
number = "6",
}