Caren E Smith1, Jack L Follis2, Jennifer A Nettleton3, Millennia Foy4, Jason H Y Wu5, Yiyi Ma1, Toshiko Tanaka6, Ani W Manichakul7,8, Hongyu Wu9, Audrey Y Chu10, Lyn M Steffen11, Myriam Fornage3,4, Dariush Mozaffarian12,13,14, Edmond K Kabagambe15, Luigi Ferruci6, Yii-Der Ida Chen16, Stephen S Rich8, Luc Djoussé17,18, Paul M Ridker10,19, Weihong Tang11, Barbara McKnight20, Michael Y Tsai21, Stefania Bandinelli22, Jerome I Rotter16, Frank B Hu9,23,24,25, Daniel I Chasman10,19, Bruce M Psaty26,27,28, Donna K Arnett29, Irena B King30, Qi Sun9,24,25, Lu Wang10, Thomas Lumley31, Stephanie E Chiuve9, David S Siscovick26,27, José M Ordovás1,32,33, Rozenn N Lemaitre26. 1. Nutrition and Genomics Laboratory, Jean Mayer USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, USA* 2. Department of Mathematics, Computer Science, and Cooperative Engineering, University of St. Thomas, Houston, TX, USA. 3. Division of Epidemiology, Human Genetics, and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX, USA. 4. Institute of Molecular Medicine, University of Texas Health Science Center at Houston, Houston, TX, USA. 5. The George Institute for Global Health, The University of Sydney, Sydney, NSW, Australia. 6. Translational Gerontology Branch, National Institute on Aging, Baltimore, MD, USA. 7. Center for Public Health Genomics, University of Virginia, Charlottesville, VA, USA. 8. Division of Biostatistics and Epidemiology, University of Virginia, Charlottesville, VA, USA. 9. Department of Nutrition, Harvard School of Public Health, Boston, MA, USA. 10. Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, USA. 11. Division of Epidemiology & Community Health, University of Minnesota School of Public Health, Minneapolis, MN, USA. 12. Department of Epidemiology, Harvard School of Public Health, Harvard Medical School, Boston, MA, USA. 13. Department of Nutrition, Harvard School of Public Health, Harvard Medical School, Boston, MA, USA. 14. Department of Medicine, Brigham & Women's Hospital, Harvard Medical School, Boston, MA, USA. 15. Division of Epidemiology, Department of Medicine, Vanderbilt University, Nashville, TN, USA. 16. Institute for Translational Genomics and Population Sciences, Los Angeles Biomedical Research Institute at Harbor, UCLA Medical Center, Torrance, CA, USA. 17. Division of Aging, Brigham and Women's Hospital and Harvard Medical School, Boston, MA, USA. 18. Boston Veterans Affairs Healthcare System, Boston, MA, USA. 19. Harvard Medical School, Boston, MA, USA. 20. Department of Biostatistics, University of Washington, Seattle, WA, USA. 21. Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, USA. 22. Geriatric Rehabilitation Unit, Azienda Sanitaria Firenze, Florence, Italy. 23. Department of Epidemiology, Harvard School of Public Health, Boston, MA, USA. 24. Harvard School of Public Health, Boston, MA, USA. 25. Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital, Harvard Medical School, Boston, MA, USA. 26. Cardiovascular Health Research Unit, Department of Medicine, Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA. 27. Department of Epidemiology, Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA. 28. Department of Health Services, Group Health Research Institute, Group Health Cooperative, Seattle, WA, USA. 29. Department of Epidemiology, Section on Statistical Genetics, and The Office of Energetics, University of Alabama at Birmingham, Birmingham, AL, USA. 30. Department of Internal Medicine, Division of Endocrinology, University of New Mexico, Albuquerque, NM, USA. 31. Department of Statistics, University of Auckland, Auckland, New Zealand. 32. Department of Epidemiology and Population Genetics, Centro Nacional Investigación Cardiovasculares (CNIC), Madrid, Spain. 33. Instituto Madrilenõs de Estudios Avanzados Alimentación, Madrid, Spain.
Abstract
SCOPE: Tissue concentrations of omega-3 fatty acids may reduce cardiovascular disease risk, and genetic variants are associated with circulating fatty acids concentrations. Whether dietary fatty acids interact with genetic variants to modify circulating omega-3 fatty acids is unclear. We evaluated interactions between genetic variants and fatty acid intakes for circulating alpha-linoleic acid, eicosapentaenoic acid, docosahexaenoic acid, and docosapentaenoic acid. METHODS AND RESULTS: We conducted meta-analyses (N = 11 668) evaluating interactions between dietary fatty acids and genetic variants (rs174538 and rs174548 in FADS1 (fatty acid desaturase 1), rs7435 in AGPAT3 (1-acyl-sn-glycerol-3-phosphate), rs4985167 in PDXDC1 (pyridoxal-dependent decarboxylase domain-containing 1), rs780094 in GCKR (glucokinase regulatory protein), and rs3734398 in ELOVL2 (fatty acid elongase 2)). Stratification by measurement compartment (plasma versus erthyrocyte) revealed compartment-specific interactions between FADS1 rs174538 and rs174548 and dietary alpha-linolenic acid and linoleic acid for docosahexaenoic acid and docosapentaenoic acid. CONCLUSION: Our findings reinforce earlier reports that genetically based differences in circulating fatty acids may be partially due to differences in the conversion of fatty acid precursors. Further, fatty acids measurement compartment may modify gene-diet relationships, and considering compartment may improve the detection of gene-fatty acids interactions for circulating fatty acid outcomes.
SCOPE: Tissue concentrations of omega-3 fatty acids may reduce cardiovascular disease risk, and genetic variants are associated with circulating fatty acids concentrations. Whether dietary fatty acids interact with genetic variants to modify circulating omega-3 fatty acids is unclear. We evaluated interactions between genetic variants and fatty acid intakes for circulating alpha-linoleic acid, eicosapentaenoic acid, docosahexaenoic acid, and docosapentaenoic acid. METHODS AND RESULTS: We conducted meta-analyses (N = 11 668) evaluating interactions between dietary fatty acids and genetic variants (rs174538 and rs174548 in FADS1 (fatty acid desaturase 1), rs7435 in AGPAT3 (1-acyl-sn-glycerol-3-phosphate), rs4985167 in PDXDC1 (pyridoxal-dependent decarboxylase domain-containing 1), rs780094 in GCKR (glucokinase regulatory protein), and rs3734398 in ELOVL2 (fatty acid elongase 2)). Stratification by measurement compartment (plasma versus erthyrocyte) revealed compartment-specific interactions between FADS1 rs174538 and rs174548 and dietary alpha-linolenic acid and linoleic acid for docosahexaenoic acid and docosapentaenoic acid. CONCLUSION: Our findings reinforce earlier reports that genetically based differences in circulating fatty acids may be partially due to differences in the conversion of fatty acid precursors. Further, fatty acids measurement compartment may modify gene-diet relationships, and considering compartment may improve the detection of gene-fatty acids interactions for circulating fatty acid outcomes.
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