Trans Fatty Acid Biomarkers and Incident Type 2 Diabetes: Pooled Analysis of 12 Prospective Cohort Studies in the Fatty Acids and Outcomes Research Consortium (FORCE)

Heidi T M Lai; Fumiaki Imamura; Andres V Ardisson Korat; Rachel A Murphy; Nathan Tintle; Julie K Bassett; Jiaying Chen; Janine Kröger; Kuo-Liong Chien; Mackenzie Senn; Alexis C Wood; Nita G Forouhi; Matthias B Schulze; William S Harris; Ramachandran S Vasan; Frank Hu; Graham G Giles; Allison Hodge; Luc Djousse; Ingeborg A Brouwer; Frank Qian; Qi Sun; Jason H Y Wu; Matti Marklund; Rozenn N Lemaitre; David S Siscovick; Amanda M Fretts; Aladdin H Shadyab; JoAnn E Manson; Barbara V Howard; Jennifer G Robinson; Robert B Wallace; Nick J Wareham; Yii-Der Ida Chen; Jerome I Rotter; Michael Y Tsai; Renata Micha; Dariush Mozaffarian; Fatty Acids and Outcomes Research Consortium (FORCE)

doi:10.2337/dc21-1756

Trans Fatty Acid Biomarkers and Incident Type 2 Diabetes: Pooled Analysis of 12 Prospective Cohort Studies in the Fatty Acids and Outcomes Research Consortium (FORCE)

Diabetes Care. 2022 Apr 1;45(4):854-863. doi: 10.2337/dc21-1756.

Authors

Heidi T M Lai^{1

2}, Fumiaki Imamura³, Andres V Ardisson Korat^{4

5}, Rachel A Murphy⁶, Nathan Tintle^{7

8}, Julie K Bassett⁹, Jiaying Chen¹⁰, Janine Kröger¹¹, Kuo-Liong Chien¹², Mackenzie Senn¹³, Alexis C Wood¹³, Nita G Forouhi³, Matthias B Schulze^{11

14

15}, William S Harris^{8

16}, Ramachandran S Vasan^{17

18}, Frank Hu^{4

5}, Graham G Giles^{9

19

20}, Allison Hodge⁹, Luc Djousse²¹, Ingeborg A Brouwer²², Frank Qian²³, Qi Sun^{4

5}, Jason H Y Wu²⁴, Matti Marklund^{1

24

25}, Rozenn N Lemaitre²⁶, David S Siscovick²⁷, Amanda M Fretts²⁸, Aladdin H Shadyab²⁹, JoAnn E Manson^{30

31}, Barbara V Howard³², Jennifer G Robinson³³, Robert B Wallace³³, Nick J Wareham³, Yii-Der Ida Chen³⁴, Jerome I Rotter³⁴, Michael Y Tsai³⁵, Renata Micha¹, Dariush Mozaffarian¹; Fatty Acids and Outcomes Research Consortium (FORCE)

Affiliations

¹ Friedman School of Nutrition Science and Policy, Tufts University, Boston, MA.
² Department of Primary Care and Public Health, Imperial College London, London, U.K.
³ MRC Epidemiology Unit, University of Cambridge, Cambridge, U.K.
⁴ Department of Nutrition and Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
⁵ Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
⁶ School of Population & Public Health, Faculty of Medicine, The University of British Columbia, Vancouver, British Columbia, Canada.
⁷ Department of Mathematics and Statistics, Dordt University, Sioux Center, IA.
⁸ Fatty Acid Research Institute, Sioux Falls, SD.
⁹ Cancer Epidemiology Division, Cancer Council Victoria, Melbourne, Victoria, Australia.
¹⁰ Division of Aging, Brigham and Women's Hospital, Boston, MA.
¹¹ Department of Molecular Epidemiology, German Institute of Human Nutrition Potsdam-Rehbruecke, Nuthetal, Germany.
¹² Institute of Epidemiology and Preventive Medicine, College of Public Health, National Taiwan University, Taipei City, Republic of China.
¹³ U.S. Department of Agriculture/Agriculture Research Service Children's Nutrition Research Center, Department of Pediatrics, Baylor College of Medicine, Houston, TX.
¹⁴ German Center for Diabetes Research (DZD), Neuherberg, Germany.
¹⁵ Institute of Nutritional Science, University of Potsdam, Nuthetal, Germany.
¹⁶ Department of Internal Medicine, Sanford School of Medicine, University of South Dakota, Sioux Falls, SD.
¹⁷ Boston University School of Medicine, Boston, MA.
¹⁸ The Framingham Heart Study, Framingham, MA.
¹⁹ Centre for Epidemiology and Biostatistics, The University of Melbourne, Parkville, Victoria, Australia.
²⁰ Precision Medicine, School of Clinical Sciences at Monash Health, Monash University, Clayton, Victoria, Australia.
²¹ Divisions of Aging, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA.
²² Department of Health Sciences, Faculty of Science, Vrije Universiteit Amsterdam, Amsterdam Public Health Research Institute, Amsterdam, the Netherlands.
²³ Department of Nutrition, Harvard T.H. Chan School of Public Health, Boston, MA.
²⁴ The George Institute for Global Health, the Faculty of Medicine, University of New South Wales, Sydney, New South Wales, Australia.
²⁵ Department of Public Health and Caring Sciences, Clinical Nutrition and Metabolism, Uppsala University, Uppsala, Sweden.
²⁶ Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA.
²⁷ The New York Academy of Medicine, New York, NY.
²⁸ Cardiovascular Health Research Unit, Department of Epidemiology, University of Washington School of Public Health, Seattle, WA.
²⁹ Family Medicine and Public Health, School of Medicine, University of California, San Diego, La Jolla, CA.
³⁰ Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA.
³¹ Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA.
³² Georgetown University Medical Center, Georgetown University, Hyattsville, MD.
³³ The University of Iowa, Iowa City, IA.
³⁴ The Institute for Translational Genomics and Population Sciences, Department of Pediatrics, The Lundquist Institute for Biomedical Innovation at Harbor-UCLA Medical Center, Torrance, CA.
³⁵ Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN.

Abstract

Objective: Trans fatty acids (TFAs) have harmful biologic effects that could increase the risk of type 2 diabetes (T2D), but evidence remains uncertain. We aimed to investigate the prospective associations of TFA biomarkers and T2D by conducting an individual participant-level pooled analysis.

Research design and methods: We included data from an international consortium of 12 prospective cohorts and nested case-control studies from six nations. TFA biomarkers were measured in blood collected between 1990 and 2008 from 25,126 participants aged ≥18 years without prevalent diabetes. Each cohort conducted de novo harmonized analyses using a prespecified protocol, and findings were pooled using inverse-variance weighted meta-analysis. Heterogeneity was explored by prespecified between-study and within-study characteristics.

Results: During a mean follow-up of 13.5 years, 2,843 cases of incident T2D were identified. In multivariable-adjusted pooled analyses, no significant associations with T2D were identified for trans/trans-18:2, relative risk (RR) 1.09 (95% CI 0.94-1.25); cis/trans-18:2, 0.89 (0.73-1.07); and trans/cis-18:2, 0.87 (0.73-1.03). Trans-16:1n-9, total trans-18:1, and total trans-18:2 were inversely associated with T2D (RR 0.81 [95% CI 0.67-0.99], 0.86 [0.75-0.99], and 0.84 [0.74-0.96], respectively). Findings were not significantly different according to prespecified sources of potential heterogeneity (each P ≥ 0.1).

Conclusions: Circulating individual trans-18:2 TFA biomarkers were not associated with risk of T2D, while trans-16:1n-9, total trans-18:1, and total trans-18:2 were inversely associated. Findings may reflect the influence of mixed TFA sources (industrial vs. natural ruminant), a general decline in TFA exposure due to policy changes during this period, or the relatively limited range of TFA levels.

Publication types

Meta-Analysis
Research Support, N.I.H., Extramural
Research Support, Non-U.S. Gov't

MeSH terms

Adolescent
Adult
Biomarkers
Cohort Studies
Diabetes Mellitus, Type 2* / epidemiology
Fatty Acids
Humans
Outcome Assessment, Health Care
Prospective Studies
Risk Factors
Trans Fatty Acids* / adverse effects

Trans Fatty Acid Biomarkers and Incident Type 2 Diabetes: Pooled Analysis of 12 Prospective Cohort Studies in the Fatty Acids and Outcomes Research Consortium (FORCE)

Authors

Affiliations

Abstract

Publication types

MeSH terms

Substances

Associated data

Grants and funding