Interactions between genetic predisposition to obesity, insulin resistance and type 2 diabetes risk, and food or beverage intake for incident type 2 diabetes: European Prospective Investigation into Cancer and Nutrition (EPIC) InterAct case–cohort study

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Authors: Sherly X. Li, Fumiaki Imamura, Stephen J. Sharp, Matthias B. Schulze, Ju-Sheng Zheng, Pilar Amiano, Ardanaz Eva, Manuela M. Bergmann, Maria-Dolores Chirlaque, Guy Fagherazzi, Paul W. Franks, Sara Grioni
+20 more Daniel B. Ibsen, Paula Gabriela Jakszyn, Ingegerd Johansson, Verena A. Katzke, Nasser Laouali, Francesca R. Mancini, Kim Overvad, Domenico Palli, Salvatore Panico, Daniel Redondo‐Sánchez, Fulvio Ricceri, Olov Rolandsson, Bernard Srour, Anne Tjønneland, Tammy Y. N. Tong, Yvonne T. van der Schouw, Elio Riboli, Claudia Langenberg, Nita G Forouhi, Nick J Wareham
Cited by: 1
References: 37

Abstract

BACKGROUND: Limited evidence exists for effect modification of genetic characteristics on the associations of food consumption and incident type 2 diabetes (T2D). OBJECTIVES: We aimed to investigate whether the food-T2D association would vary by genetic susceptibility to metabolic traits. METHODS: We analyzed data from 9542 incident T2D cases and a subcohort of 12,477 participants nested within the 340,234-participant cohort recruited in 1991-1998 and followed up for 10.9 y on average in 8 European countries. Polygenic risk scores (PRSs) for higher body mass index, insulin resistance, and T2D were constructed. Fifteen dietary variables potentially associated with T2D, obtained with cohort-specific self-reported dietary assessment, were examined: fruits, green leafy vegetables, root vegetables, wholegrains, rice, legumes, nuts and seeds, fermented dairy, red meat, processed meat, fish, eggs and egg products, sugar-sweetened beverages, coffee, and tea. A cross-product term between each PRS and each food/beverage was evaluated by genotyping chip and country with Prentice-weighted Cox regression for incident T2D, and stratum-specific estimates were meta analyzed, followed by Benjamini-Yekutieli multiple-testing correction. RESULTS: Accounting for multiple tests of 3 PRSs × 15 dietary items, no evidence of statistical interaction was evident on either a multiplicative or additive scale, with exp(β for a multiplicative interaction) (95% confidence interval) ranging from 0.84 (0.64, 1.10) (root vegetables and PRS for T2D) to 1.45 (0.78-2.76) (fish and PRS for T2D). CONCLUSIONS: Genetic susceptibility to high-risk metabolic traits did not modify the diet-T2D associations in European populations. Acknowledging the limitations of current PRS-based methods to detect gene-diet interactions, research should continue into the potential for precision nutrition and tailored food-based dietary guidance for T2D prevention.

Fields of Study & Subjects

Nutrition Genetics and Disease Genetic Associations and Epidemiology Nutritional Studies and Diet

Publication details

Journal / source
American Journal of Clinical Nutrition
Publisher
Elsevier BV
Volume
123
Issue
3
Pages
101198–101198
Publication date
17 January 2026
Language
EN