TY - JOUR
T1 - Interactions between genetic predisposition to obesity, insulin resistance and type 2 diabetes risk and food or beverage intake for incident type 2 diabetes
T2 - European Prospective Investigation into Cancer (EPIC) InterAct case-cohort study
AU - Li, Sherly X
AU - Imamura, Fumiaki
AU - Sharp, Stephen J
AU - Schulze, Matthias B
AU - Zheng, Ju-Sheng
AU - Amiano, Pilar
AU - Ardanaz, Eva
AU - Bergmann, Manuela M
AU - Chirlaque, Maria-Dolores
AU - Fagherazzi, Guy
AU - Franks, Paul W
AU - Grioni, Sara
AU - Ibsen, Daniel B
AU - Jakszyn, Paula
AU - Johansson, Ingegerd
AU - Katzke, Verena A
AU - Laouali, Nasser
AU - Mancini, Francesca R
AU - Overvad, Kim
AU - Palli, Domenico
AU - Panico, Salvatore
AU - Redondo-Sánchez, Daniel
AU - Ricceri, Fulvio
AU - Rolandsson, Olov
AU - Srour, Bernard
AU - Tjønneland, Anne
AU - Tong, Tammy Y N
AU - van der Schouw, Yvonne T
AU - Riboli, Elio
AU - Langenberg, Claudia
AU - Forouhi, Nita G
AU - Wareham, Nick J
N1 - Publisher Copyright:
Crown Copyright © 2026 Published by Elsevier Inc. on behalf of American Society for Nutrition. This is an open access article under the CC BY license. http://creativecommons.org/licenses/by/4.0/
PY - 2026/3
Y1 - 2026/3
N2 - 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.
AB - 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.
U2 - 10.1016/j.ajcnut.2026.101198
DO - 10.1016/j.ajcnut.2026.101198
M3 - Article
C2 - 41548598
SN - 0002-9165
VL - 123
JO - American Journal of Clinical Nutrition
JF - American Journal of Clinical Nutrition
IS - 3
M1 - 101198
ER -