Metabolomic signatures of long-term coffee consumption and risk of type 2 diabetes in women

Dong Hang, Oana A. Zeleznik, Xiaosheng He, Marta Guasch-Ferre, Xia Jiang, Jun Li, Liming Liang, A. Heather Eliassen, Clary B. Clish, Andrew T. Chan, Zhibin Hu, Hongbing Shen, Kathryn M. Wilson, Lorelei A. Mucci, Qi Sun, Frank B. Hu, Walter C. Willett, Edward L. Giovannucci, Mingyang Song*

*Corresponding author af dette arbejde

Publikation: Bidrag til tidsskriftTidsskriftartikelForskningpeer review

32 Citationer (Scopus)

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 5 457 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. Coffeerelated metabolites might help improve prediction of diabetes, but further validation studies are needed.

OriginalsprogEngelsk
TidsskriftDiabetes Care
Vol/bind43
Udgave nummer10
Sider (fra-til)2588-2596
Antal sider9
ISSN0149-5992
DOI
StatusUdgivet - 2020
Udgivet eksterntJa

Bibliografisk note

Funding Information:
Acknowledgments. The authors thank the participants and staff of the NHS and NHSII for their valuable contributions. Funding. This work was supported by the American Cancer Society Mentored Research Scholar Grant (MRSG-17-220-01-NEC [to M.S.]), by U.S. National Institutes of Health grants (UM1 CA186107 to M.J. Stampfer; R01 CA49449 to S.E. Hankinson; U01 CA176726 and R01 CA050385 to W.C.W. and A.H.E.; P01 CA087969 and R01 CA163451 to S.S. Tworoger; R01 AR057327 to E.W. Karlson; R01 NS045893 and R01 NS089619 to A. Ascherio; P01 CA087969 to R.M. Tamimi; K24 DK098311, R01 CA137178, R01 CA202704, and R01 CA176726 to A.T.C.; K99 CA215314 and R00 CA215314 to M.S.; and R01 DK112940 to F.B.H.), by the Department of Defense (W81XWH-12-1-0561), and by grants from National Natural Science Foundation of China (81973127 to D.H.) and Natural Science Foundation of Jiangsu Province (BK20190083 to D.H.). A.T.C. is a Stuart and Suzanne Steele MGH Research Scholar.

Funding Information:
This work was supported by the American Cancer Society Mentored Research Scholar Grant (MRSG-17-220-01-NEC [to M.S.]), by U.S. National Institutes of Health grants (UM1 CA186107 to M.J. Stampfer; R01 CA49449to S.E. Hankinson; U01 CA176726 and R01 CA050385 to W.C.W. and A.H.E.; P01 CA087969 and R01 CA163451 to S.S. Tworoger; R01 AR057327 to E.W. Karlson; R01 NS045893 and R01 NS089619 to A. Ascherio; P01 CA087969 to R.M. Tamimi; K24 DK098311, R01 CA137178, R01 CA202704, and R01 CA176726 to A.T.C.; K99 CA215314 and R00 CA215314 to M.S.; and R01 DK112940 to F.B.H.), by the Department of Defense (W81XWH-12-1-0561), and by grants from National Natural Science Foundation of China (81973127 to D.H.) and Natural Science Foundation of Jiangsu Province (BK20190083 to D.H.). A.T.C. is a Stuart and SuzanneSteeleMGHResearchScholar. Grants to individuals who are not authors of this work contributed to the establishment of cohorts but not directly to the current analysis. The authors assume full responsibility for analyses and interpretation of these data.

Publisher Copyright:
© 2020 by the American Diabetes Association.

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