{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,9,29]],"date-time":"2026-09-29T11:13:57Z","timestamp":1790680437330,"version":"4.1.0"},"reference-count":38,"publisher":"Oxford University Press (OUP)","issue":"18","license":[{"start":{"date-parts":[[2021,4,16]],"date-time":"2021-04-16T00:00:00Z","timestamp":1618531200000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/academic.oup.com\/journals\/pages\/open_access\/funder_policies\/chorus\/standard_publication_model"}],"funder":[{"DOI":"10.13039\/100000062","name":"NIDDK","doi-asserted-by":"publisher","award":["2T32DK007028\u201346"],"award-info":[{"award-number":["2T32DK007028\u201346"]}],"id":[{"id":"10.13039\/100000062","id-type":"DOI","asserted-by":"publisher"}]},{"DOI":"10.13039\/100000002","name":"NIH","doi-asserted-by":"publisher","award":["R01HL145025"],"award-info":[{"award-number":["R01HL145025"]}],"id":[{"id":"10.13039\/100000002","id-type":"DOI","asserted-by":"publisher"}]},{"name":"American Diabetes Association Fellowship","award":["1\u201319-PDF-028"],"award-info":[{"award-number":["1\u201319-PDF-028"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2021,8,28]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Diet is a significant modifiable risk factor for type 2 diabetes (T2D), and its effect on disease risk is under partial genetic control. Identification of specific gene\u2013diet interactions (GDIs) influencing risk biomarkers such as glycated hemoglobin (HbA1c) is a critical step towards precision nutrition for T2D prevention, but progress has been slow due to limitations in sample size and accuracy of dietary exposure measurement. We leveraged the large UK Biobank (UKB) cohort and a diverse group of dietary exposures, including 30 individual dietary traits and 8 empirical dietary patterns, to conduct genome-wide interaction studies in ~340\u2009000 European-ancestry participants to identify novel GDIs influencing HbA1c. We identified five variant-dietary trait pairs reaching genome-wide significance (P\u2009&amp;lt;\u20095\u2009\u00d7\u200910\u22128): two involved dietary patterns (meat pattern with rs147678157 and a fruit &amp; vegetable-based pattern with rs3010439) and three involved individual dietary traits (bread consumption with rs62218803, dried fruit consumption with rs140270534 and milk type [dairy vs. other] with 4:131148078_TAGAA_T). These were affected minimally by adjustment for geographical and lifestyle-related confounders, and four of the five variants lacked genetic main effects that would have allowed their detection in a traditional genome-wide association study for HbA1c. Notably, multiple loci near transient receptor potential subfamily M genes (TRPM2 and TRPM3) interacted with carbohydrate-containing food groups. These interactions were further characterized using non-European UKB subsets and alternative measures of glycaemia (fasting glucose and follow-up HbA1c measurements). Our results highlight GDIs influencing HbA1c for future investigation, while reinforcing known challenges in detecting and replicating GDIs.<\/jats:p>","DOI":"10.1093\/hmg\/ddab109","type":"journal-article","created":{"date-parts":[[2021,4,14]],"date-time":"2021-04-14T20:36:49Z","timestamp":1618432609000},"page":"1773-1783","source":"Crossref","is-referenced-by-count":28,"title":["Genome-wide gene\u2013diet interaction analysis in the UK Biobank identifies novel effects on hemoglobin A1c"],"prefix":"10.1093","volume":"30","author":[{"given":"Kenneth E","family":"Westerman","sequence":"first","affiliation":[{"name":"Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA"},{"name":"Department of Medicine, Harvard Medical School, Boston, MA 02115, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jenkai","family":"Miao","sequence":"additional","affiliation":[{"name":"Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children\u2019s Hospital, Boston, MA 02115, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Daniel I","family":"Chasman","sequence":"additional","affiliation":[{"name":"Division of Preventive Medicine, Brigham and Women\u2019s Hospital, Boston, MA 02115, USA"},{"name":"Division of Genetics, Brigham and Women\u2019s Hospital, Boston, MA 02115, USA"},{"name":"Medical and Population Genetics Program, Broad Institute, Cambridge, MA 02142, USA"},{"name":"Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA 02115, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Jose C","family":"Florez","sequence":"additional","affiliation":[{"name":"Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA"},{"name":"Department of Medicine, Harvard Medical School, Boston, MA 02115, USA"},{"name":"Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Han","family":"Chen","sequence":"additional","affiliation":[{"name":"Human Genetics Center, Department of Epidemiology, Human Genetics and Environmental Sciences, School of Public Health, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA"},{"name":"Center for Precision Health, School of Public Health and School of Biomedical Informatics, The University of Texas Health Science Center at Houston, Houston, TX 77030, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Alisa K","family":"Manning","sequence":"additional","affiliation":[{"name":"Clinical and Translational Epidemiology Unit, Mongan Institute, Massachusetts General Hospital, Boston, MA 02114, USA"},{"name":"Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA"},{"name":"Department of Medicine, Harvard Medical School, Boston, MA 02115, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]},{"given":"Joanne B","family":"Cole","sequence":"additional","affiliation":[{"name":"Programs in Metabolism and Medical & Population Genetics, Broad Institute of Harvard and MIT, Cambridge, MA 02142, USA"},{"name":"Division of Endocrinology and Center for Basic and Translational Obesity Research, Boston Children\u2019s Hospital, Boston, MA 02115, USA"},{"name":"Diabetes Unit and Center for Genomic Medicine, Massachusetts General Hospital, Boston, MA 02114, USA"}],"role":[{"vocabulary":"crossref","role":"author"}]}],"member":"286","published-online":{"date-parts":[[2021,4,16]]},"reference":[{"key":"2021090214222418700_ref1","doi-asserted-by":"crossref","first-page":"1079","DOI":"10.1016\/j.cell.2015.11.001","article-title":"Personalized nutrition by prediction of Glycemic responses","volume":"163","author":"Zeevi","year":"2015","journal-title":"Cell"},{"key":"2021090214222418700_ref2","doi-asserted-by":"crossref","first-page":"399","DOI":"10.1534\/genetics.117.300536","article-title":"Improving metabolic health through precision dietetics in mice","volume":"208","author":"Barrington","year":"2018","journal-title":"Genetics"},{"key":"2021090214222418700_ref3","doi-asserted-by":"crossref","first-page":"e77442","DOI":"10.1371\/journal.pone.0077442","article-title":"Genome-wide contribution of genotype by environment interaction to variation of diabetes-related traits","volume":"8","author":"Zheng","year":"2013","journal-title":"PLoS One"},{"key":"2021090214222418700_ref4","doi-asserted-by":"crossref","first-page":"35","DOI":"10.1016\/j.gde.2018.02.001","article-title":"Gene-lifestyle interplay in type 2 diabetes","volume":"50","author":"Franks","year":"2018","journal-title":"Curr. 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Public Heal."},{"key":"2021090214222418700_ref16","first-page":"79\u201396","article-title":"Herbal compounds and toxins modulating TRP channels","volume":"6","author":"Vriens","year":"2008","journal-title":"Curr. Neuropharmacol."},{"key":"2021090214222418700_ref17","doi-asserted-by":"crossref","first-page":"209","DOI":"10.4161\/isl.3.4.16130","article-title":"TRPM2 modulates insulin secretion in pancreatic \u03b2-cells","volume":"3","author":"Uchida","year":"2011","journal-title":"Islets"},{"key":"2021090214222418700_ref18","doi-asserted-by":"crossref","first-page":"1421","DOI":"10.1038\/ncb1801","article-title":"Transient receptor potential M3 channels are ionotropic steroid receptors in pancreatic \u03b2 cells","volume":"10","author":"Wagner","year":"2008","journal-title":"Nat. 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Nutr."},{"key":"2021090214222418700_ref24","doi-asserted-by":"crossref","first-page":"e1001779","DOI":"10.1371\/journal.pmed.1001779","article-title":"UK biobank: an open access resource for identifying the causes of a wide range of complex diseases of middle and old age","volume":"12","author":"Sudlow","year":"2015","journal-title":"PLoS Med."},{"key":"2021090214222418700_ref25","doi-asserted-by":"crossref","first-page":"203","DOI":"10.1038\/s41586-018-0579-z","article-title":"The UK biobank resource with deep phenotyping and genomic data","volume":"562","author":"Bycroft","year":"2018","journal-title":"Nature"},{"key":"2021090214222418700_ref26","volume-title":"R: A Language and Environment for Statistical Computing","author":"R Core Team","year":"2019"},{"key":"2021090214222418700_ref27","doi-asserted-by":"crossref","first-page":"e0162388","DOI":"10.1371\/journal.pone.0162388","article-title":"Algorithms for the capture and adjudication of prevalent and incident diabetes in UK biobank","volume":"11","author":"Eastwood","year":"2016","journal-title":"PLoS One"},{"key":"2021090214222418700_ref28","doi-asserted-by":"crossref","first-page":"1990","DOI":"10.1175\/1520-0442(1999)012<1990:TENOSD>2.0.CO;2","article-title":"The effective number of spatial degrees of freedom of a time-varying field","volume":"12","author":"Bretherton","year":"1999","journal-title":"J. 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Psychiatry"},{"key":"2021090214222418700_ref34","doi-asserted-by":"crossref","first-page":"4851","DOI":"10.1093\/bioinformatics\/btz469","article-title":"PhenoScanner V2: an expanded tool for searching human genotype\u2013phenotype associations","volume":"35","author":"Kamat","year":"2019","journal-title":"Bioinformatics"},{"key":"2021090214222418700_ref35","doi-asserted-by":"crossref","first-page":"3207","DOI":"10.1093\/bioinformatics\/btw373","article-title":"PhenoScanner: a database of human genotype\u2013phenotype associations","volume":"32","author":"Staley","year":"2016","journal-title":"Bioinformatics"},{"key":"2021090214222418700_ref36","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1038\/ng.3721","article-title":"Disease variants alter transcription factor levels and methylation of their binding sites","volume":"49","author":"Bonder","year":"2017","journal-title":"Nat. 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