Abstract TH816: Carbohydrate Quality, Pathway-specific Polygenic Risk Scores, and Risk of Type 2 Diabetes among US Men and Women

Z Zhendong Mei (Brigham and Women's Hospital, Boston, Massachusetts, United States) H Hala Alessa (Harvard T.H. Chan School of Public, Boston, Massachusetts, United States) X Xingyan Wang (Helmholtz International Lab for Anti-Infectives, State Key Laboratory of Microbial Technology) S Seyed Mousavi (Harvard T.H. Chan School of Public, Boston, Massachusetts, United States) M Magdalena Sevilla-Gonzalez H Huan Yun (Harvard T.H. Chan School of Public, Boston, Massachusetts, United States) J Jie Hu (School of Biomedical Sciences and Engineering) S Shilpa Bhupathiraju (CHANNING DIV NETWORK MEDICINE, Boston, Massachusetts, United States) Q Qi Sun M Meir Stampfer (CHANNING DIV NETWORK MEDICINE, Boston, Massachusetts, United States) W Walter Willett (Harvard university, Cambridge, Massachusetts, United States) L Liming Liang F Frank Hu (HARVARD SCHOOL OF PUBLIC HEALTH, Boston, Massachusetts, United States) J Jun Li

Abstract

Introduction: Carbohydrate quality is associated with type 2 diabetes (T2D) risk, but whether intakes of specific carbohydrates interact with genetic susceptibility remains unclear. Hypothesis: The associations between lower carbohydrate quality and higher T2D risk may be modified by global and pathway-specific polygenic risk scores (PRS). Methods: We analyzed up to 36 years of longitudinal data from 39,540 participants in the Nurses’ Health Studies and Health Professionals Follow-Up Study, free of diabetes, cardiovascular disease, and cancer at baseline. Diet was assessed every 4 years using validated food frequency questionnaires. We calculated cumulatively averaged alternative Carbohydrate Quality Index (aCQI; based on cereal fiber, whole fruit carbohydrates, glycemic index, sugar from sugar-sweetened beverages [SSB], and whole grain carbohydrates), with a lower score indicating poorer long-term carbohydrate quality. We calculated global and 12 pathway-specific PRS based on 650 genetic variants reflecting distinct T2D mechanisms. Cox regression was used to examine associations between aCQI (and secondarily, its components), PRS, and their interactions with T2D risk. Results: We identified 5,116 incident T2D cases. The global-PRS, and 11 out of 12 pathway-specific PRS (except for bilirubin metabolism) robustly predicted T2D risk. In multivariable analysis, a lower aCQI was associated with higher T2D risk (HR per IQR: 1.20, 95% CI: 1.14-1.26, P <0.001). A significant additive interaction was observed, among participants older than 65 yrs but not younger, between global-PRS and aCQI, with T2D risk (relative excess risk due to interaction =0.21, P int =0.025, Fig. A ). In secondary analysis of aCQI components in those ≥65 yrs, nominally significant interactions were noted between global-PRS with low whole fruit carbohydrates and low whole grain carbohydrates for T2D risk ( P int ≤0.011 ; Fig. A ). Further analysis on pathway-specific PRS suggested potential additive interactions between whole fruit carbohydrates and PRS reflecting proinsulin, hyper insulin, and obesity-mediated insulin resistance pathways, and between sugar from SSB and PRS for obesity-mediated insulin resistance ( P int ≤0.038; Fig. B ). Conclusions: Our data suggest that the association between lower carbohydrate quality and T2D risk may be stronger in older adults with higher genetic risk. Replication studies are needed to examine how specific carbohydrates may interact with genetic risk through specific pathways.

Article Details

Journal Circulation
Volume / Issue Vol. 153, Issue Suppl_1
Published March 24, 2026
ISSN 0009-7322
Publisher Lippincott Williams & Wilkins

Journal Info

Circulation

Lippincott Williams & Wilkins

ISSN: 0009-7322 Health Sciences

Authors (14)

Z

Zhendong Mei

Brigham and Women's Hospital, Boston, Massachusetts, United States

H

Hala Alessa

Harvard T.H. Chan School of Public, Boston, Massachusetts, United States

X

Xingyan Wang

Helmholtz International Lab for Anti-Infectives, State Key Laboratory of Microbial Technology

S

Seyed Mousavi

Harvard T.H. Chan School of Public, Boston, Massachusetts, United States

M

Magdalena Sevilla-Gonzalez

H

Huan Yun

Harvard T.H. Chan School of Public, Boston, Massachusetts, United States

J

Jie Hu

School of Biomedical Sciences and Engineering

S

Shilpa Bhupathiraju

CHANNING DIV NETWORK MEDICINE, Boston, Massachusetts, United States

Q

Qi Sun

M

Meir Stampfer

CHANNING DIV NETWORK MEDICINE, Boston, Massachusetts, United States

W

Walter Willett

Harvard university, Cambridge, Massachusetts, United States

L

Liming Liang

F

Frank Hu

HARVARD SCHOOL OF PUBLIC HEALTH, Boston, Massachusetts, United States

J

Jun Li