Metabolomic Signatures of Long-term Coffee Consumption and Risk of Type 2 Diabetes in Women

Author:

Hang Dong12,Zeleznik Oana A.3,He Xiaosheng45,Guasch-Ferre Marta23,Jiang Xia6ORCID,Li Jun2,Liang Liming78ORCID,Eliassen A. Heather37ORCID,Clish Clary B.9,Chan Andrew T.349ORCID,Hu Zhibin1,Shen Hongbing1,Wilson Kathryn M.37,Mucci Lorelei A.7,Sun Qi23,Hu Frank B.237ORCID,Willett Walter C.237,Giovannucci Edward L.237,Song Mingyang247ORCID

Affiliation:

1. Department of Epidemiology and Biostatistics, Jiangsu Key Lab of Cancer Biomarkers, Prevention and Treatment, Collaborative Innovation Center for Cancer Personalized Medicine, School of Public Health, Nanjing Medical University, Nanjing, China

2. Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA

3. Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital and Harvard Medical School, Boston, MA

4. Clinical and Translational Epidemiology Unit and Division of Gastroenterology, Massachusetts General Hospital and Harvard Medical School, Boston, MA

5. Department of Colorectal Surgery, The Sixth Affiliated Hospital, Sun Yat-sen University, Guangzhou, China

6. Program in Genetic Epidemiology and Statistical Genetics, Harvard T.H. Chan School of Public Health, Boston, MA

7. Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA

8. Department of Biostatistics, Harvard T.H. Chan School of Public Health, Boston, MA

9. Broad Institute of Massachusetts Institute of Technology and Harvard, Cambridge, MA

Abstract

OBJECTIVE Coffee may protect against multiple chronic diseases, particularly type 2 diabetes, but the mechanisms remain unclear. RESEARCH DESIGN AND METHODS Leveraging dietary and metabolomic data in two large cohorts of women (the Nurses’ Health Study [NHS] and NHSII), we identified and validated plasma metabolites associated with coffee intake in 1,595 women. We then evaluated the prospective association of coffee-related metabolites with diabetes risk and the added predictivity of these metabolites for diabetes in two nested case-control studies (n = 457 case and 1,371 control subjects). RESULTS Of 461 metabolites, 34 were identified and validated to be associated with total coffee intake, including 13 positive associations (primarily trigonelline, polyphenol metabolites, and caffeine metabolites) and 21 inverse associations (primarily triacylglycerols [TAGs] and diacylglycerols [DAGs]). These associations were generally consistent for caffeinated and decaffeinated coffee, except for caffeine and its metabolites that were only associated with caffeinated coffee intake. The three cholesteryl esters positively associated with coffee intake showed inverse associations with diabetes risk, whereas the 12 metabolites negatively associated with coffee (5 DAGs and 7 TAGs) showed positive associations with diabetes. Adding the 15 diabetes-associated metabolites to a classical risk factor–based prediction model increased the C-statistic from 0.79 (95% CI 0.76, 0.83) to 0.83 (95% CI 0.80, 0.86) (P < 0.001). Similar improvement was observed in the validation set. CONCLUSIONS Coffee consumption is associated with widespread metabolic changes, among which lipid metabolites may be critical for the antidiabetes benefit of coffee. Coffee-related metabolites might help improve prediction of diabetes, but further validation studies are needed.

Funder

American Cancer Society

National Institutes of Health

Department of Defense

National Natural Science Foundation of China

Natural Science Foundation of Jiangsu Province

Publisher

American Diabetes Association

Subject

Advanced and Specialized Nursing,Endocrinology, Diabetes and Metabolism,Internal Medicine

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