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Imamura F, Sharp SJ, Koulman A, Schulze MB, Kröger J, Griffin JL, Huerta JM, Guevara M, Sluijs I, Agudo A, Ardanaz E, Balkau B, Boeing H, Chajes V, Dahm CC, Dow C, Fagherazzi G, Feskens EJM, Franks PW, Gavrila D, Gunter M, Kaaks R, Key TJ, Khaw KT, Kühn T, Melander O, Molina-Portillo E, Nilsson PM, Olsen A, Overvad K, Palli D, Panico S, Rolandsson O, Sieri S, Sacerdote C, Slimani N, Spijkerman AMW, Tjønneland A, Tumino R, van der Schouw YT, Langenberg C, Riboli E, Forouhi NG, Wareham NJ. A combination of plasma phospholipid fatty acids and its association with incidence of type 2 diabetes: The EPIC-InterAct case-cohort study. PLoS Med 2017; 14:e1002409. [PMID: 29020051 PMCID: PMC5636062 DOI: 10.1371/journal.pmed.1002409] [Citation(s) in RCA: 50] [Impact Index Per Article: 7.1] [Reference Citation Analysis] [What about the content of this article? (0)] [Affiliation(s)] [Abstract] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Submit a Manuscript] [Subscribe] [Scholar Register] [Received: 06/12/2017] [Accepted: 09/14/2017] [Indexed: 01/08/2023] Open
Abstract
BACKGROUND Combinations of multiple fatty acids may influence cardiometabolic risk more than single fatty acids. The association of a combination of fatty acids with incident type 2 diabetes (T2D) has not been evaluated. METHODS AND FINDINGS We measured plasma phospholipid fatty acids by gas chromatography in 27,296 adults, including 12,132 incident cases of T2D, over the follow-up period between baseline (1991-1998) and 31 December 2007 in 8 European countries in EPIC-InterAct, a nested case-cohort study. The first principal component derived by principal component analysis of 27 individual fatty acids (mole percentage) was the main exposure (subsequently called the fatty acid pattern score [FA-pattern score]). The FA-pattern score was partly characterised by high concentrations of linoleic acid, stearic acid, odd-chain fatty acids, and very-long-chain saturated fatty acids and low concentrations of γ-linolenic acid, palmitic acid, and long-chain monounsaturated fatty acids, and it explained 16.1% of the overall variability of the 27 fatty acids. Based on country-specific Prentice-weighted Cox regression and random-effects meta-analysis, the FA-pattern score was associated with lower incident T2D. Comparing the top to the bottom fifth of the score, the hazard ratio of incident T2D was 0.23 (95% CI 0.19-0.29) adjusted for potential confounders and 0.37 (95% CI 0.27-0.50) further adjusted for metabolic risk factors. The association changed little after adjustment for individual fatty acids or fatty acid subclasses. In cross-sectional analyses relating the FA-pattern score to metabolic, genetic, and dietary factors, the FA-pattern score was inversely associated with adiposity, triglycerides, liver enzymes, C-reactive protein, a genetic score representing insulin resistance, and dietary intakes of soft drinks and alcohol and was positively associated with high-density-lipoprotein cholesterol and intakes of polyunsaturated fat, dietary fibre, and coffee (p < 0.05 each). Limitations include potential measurement error in the fatty acids and other model covariates and possible residual confounding. CONCLUSIONS A combination of individual fatty acids, characterised by high concentrations of linoleic acid, odd-chain fatty acids, and very long-chain fatty acids, was associated with lower incidence of T2D. The specific fatty acid pattern may be influenced by metabolic, genetic, and dietary factors.
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Affiliation(s)
- Fumiaki Imamura
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Stephen J. Sharp
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Albert Koulman
- National Institute for Health Research Biomedical Research Centres Core Nutritional Biomarker Laboratory, University of Cambridge, Addenbrooke’s Hospital, Cambridge, United Kingdom
- National Institute for Health Research Biomedical Research Centres Core Metabolomics and Lipidomics Laboratory, University of Cambridge, Addenbrooke’s Hospital, Cambridge, United Kingdom
- Medical Research Council Epidemiology Unit Elsie Widdowson Laboratory, Cambridge, United Kingdom
| | - Matthias B. Schulze
- Department of Molecular Epidemiology, German Institute of Human Nutrition, Potsdam, Germany
| | - Janine Kröger
- Department of Molecular Epidemiology, German Institute of Human Nutrition, Potsdam, Germany
| | - Julian L. Griffin
- Medical Research Council Epidemiology Unit Elsie Widdowson Laboratory, Cambridge, United Kingdom
- Department of Biochemistry, University of Cambridge, Cambridge, United Kingdom
| | - José M. Huerta
- Department of Epidemiology, Consejería de Sanidad y Política Social, CIBER de Epidemiología y Salud Pública, Murcia, Spain
- CIBER Epidemiología y Salud Pública, Madrid, Spain
| | - Marcela Guevara
- CIBER Epidemiología y Salud Pública, Madrid, Spain
- Navarre Public Health Institute, Pamplona, Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Ivonne Sluijs
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Antonio Agudo
- Unit of Nutrition, Environment and Cancer, Cancer Epidemiology Research Program, Catalan Institute of Oncology, Barcelona, Spain
| | - Eva Ardanaz
- CIBER Epidemiología y Salud Pública, Madrid, Spain
- Navarre Public Health Institute, Pamplona, Navarra Institute for Health Research (IdiSNA), Pamplona, Spain
| | - Beverley Balkau
- Center for Research in Epidemiology and Population Health, Inserm U1018, Paris-Sud University, University Versailles Saint-Quentin-en-Yvelines, Paris Saclay University, Villejuif, France
| | - Heiner Boeing
- Department of Molecular Epidemiology, German Institute of Human Nutrition, Potsdam, Germany
| | | | - Christina C. Dahm
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Courtney Dow
- Center for Research in Epidemiology and Population Health, Inserm U1018, Paris-Sud University, University Versailles Saint-Quentin-en-Yvelines, Paris Saclay University, Villejuif, France
- Gustave Roussy Institute, Villejuif, France
| | - Guy Fagherazzi
- Center for Research in Epidemiology and Population Health, Inserm U1018, Paris-Sud University, University Versailles Saint-Quentin-en-Yvelines, Paris Saclay University, Villejuif, France
- Gustave Roussy Institute, Villejuif, France
| | - Edith J. M. Feskens
- Department of Agrotechnology and Food Sciences, Wageningen University, Wageningen, Netherlands
| | - Paul W. Franks
- Family Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
- Department of Clinical Sciences, Lund University, Skane University Hospital, Malmo, Sweden
| | - Diana Gavrila
- CIBER Epidemiología y Salud Pública, Madrid, Spain
- Department of Epidemiology, Murcia Regional Health Council, Murcia, Spain
- Murcia BioHealth Research Institute–Hospital Virgen de la Arrixaca, Murcia, Spain
| | - Marc Gunter
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
| | - Rudolf Kaaks
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Timothy J. Key
- Cancer Epidemiology Unit, Nuffield Department of Population Health, University of Oxford, Oxford, United Kingdom
| | - Kay-Tee Khaw
- Department of Public Health and Primary Care, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Tilman Kühn
- Division of Cancer Epidemiology, German Cancer Research Center (DKFZ), Heidelberg, Germany
| | - Olle Melander
- Department of Clinical Sciences, Lund University, Skane University Hospital, Malmo, Sweden
| | - Elena Molina-Portillo
- CIBER Epidemiología y Salud Pública, Madrid, Spain
- Escuela Andaluza de Salud Pública, Instituto de Investigación Biosanitaria ibs.GRANADA, Hospitales Universitarios de Granada/Universidad de Granada, Granada, Spain
| | - Peter M. Nilsson
- Department of Public Health and Primary Care, University of Cambridge School of Clinical Medicine, Cambridge, United Kingdom
| | - Anja Olsen
- Danish Cancer Society Research Center, Copenhagen, Denmark
| | - Kim Overvad
- Section for Epidemiology, Department of Public Health, Aarhus University, Aarhus, Denmark
- Department of Cardiology, Aalborg University Hospital, Aarhus, Denmark
| | - Domenico Palli
- Cancer Risk Factors and Lifestyle Epidemiology Unit, Cancer Research and Prevention Institute, Florence, Italy
| | - Salvatore Panico
- Dipartimento di Medicina Clinica e Chirurgia, Università degli Studi di Federico II University, Naples, Italy
| | - Olov Rolandsson
- Family Medicine, Department of Public Health and Clinical Medicine, Umeå University, Umeå, Sweden
| | - Sabina Sieri
- Epidemiology and Prevention Unit, Fondazione IRCCS Istituto Nazionale dei Tumori, Milan, Italy
| | - Carlotta Sacerdote
- Unit of Cancer Epidemiology, Città della Salute e della Scienza Hospital–University of Turin and Center for Cancer Prevention, Torino, Italy
| | - Nadia Slimani
- International Agency for Research on Cancer, Lyon, France
| | | | | | - Rosario Tumino
- Affiliation Cancer Registry, Department of Prevention, Azienda Sanitaria Provinciale di Ragusa, Ragusa, Italy
| | - Yvonne T. van der Schouw
- Julius Center for Health Sciences and Primary Care, University Medical Center Utrecht, Utrecht University, Utrecht, Netherlands
| | - Claudia Langenberg
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Elio Riboli
- School of Public Health, Imperial College London, London, United Kingdom
| | - Nita G. Forouhi
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
| | - Nick J. Wareham
- Medical Research Council Epidemiology Unit, University of Cambridge, Cambridge, United Kingdom
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