Weihua Guan1, Brian T Steffen2, Rozenn N Lemaitre3, Jason H Y Wu4,5, Toshiko Tanaka6, Ani Manichaikul7, Millennia Foy8, Luigi Ferrucci6, Myriam Fornage8,9, Dariush Mozafarrian10, Michael Y Tsai2, Lyn M Steffen11, Stephen S Rich7, Lu Wang4, Jennifer A Nettleton9, Weihong Tang11, Xiangjun Gu8, Stafania Bandinelli12, Irena B King13, Barbara McKnight3, Bruce M Psaty14,15, David Siscovick14, Luc Djousse16, Yii-Der Ida Chen17. 1. Division of Biostatistics, School of Public Health, University of Minnesota, Minneapolis, MN. 2. Laboratory Medicine & Pathology, University of Minnesota, Minneapolis, MN. 3. Cardiovascular Health Research Unit, Department of Medicine, University of Washington, Seattle, WA. 4. Department of Epidemiology and Nutrition, Harvard School of Public Health, Boston, MA. 5. School of Medicine and Pharmacology, University of Western Australia, Perth, Australia. 6. Translational Gerontology Branch, National Institute on Aging, National Institutes of Health, Baltimore, MD. 7. Center for Public Health Genomics, Division of Biostatistics and Epidemiology, University of Virginia, Charlottesville, VA. 8. Institute of Molecular Medicine, University of Texas Health Sciences Center in Houston, Houston, TX. 9. Department of Epidemiology, University of Texas Health Sciences Center in Houston, Houston, TX. 10. Division of Cardiovascular Medicine, Brigham and Women's Hospital and Harvard Medical School; Department of Epidemiology, Harvard School of Public Health, Boston, MA. 11. Division of Epidemiology and Community Health, School of Public Health, University of Minnesota, Minneapolis, MN. 12. Geriatric Rehabilitation Unit, Azienda Sanitaria Firenze (ASF), Florence, Italy. 13. Department of Internal Medicine, University of New Mexico, Albuquerque, New Mexico. 14. Cardiovascular Health Research Unit, Departments of Medicine, Epidemiology and Health Services, University of Washington, Seattle, WA. 15. Group Health Research Institute, Group Health Cooperative, Seattle, WA. 16. Department of Medicine, Brigham and Women's Hospital, Harvard Medical School & Boston VA Healthcare System, Boston, MA. 17. Cedars-Sinai Medical Center, Los Angeles, CA.
Abstract
BACKGROUND: Omega6 (n6) polyunsaturated fatty acids (PUFAs) and their metabolites are involved in cell signaling, inflammation, clot formation, and other crucial biological processes. Genetic components, such as variants of fatty acid desaturase (FADS) genes, determine the composition of n6 PUFAs. METHODS AND RESULTS: To elucidate undiscovered biological pathways that may influence n6 PUFA composition, we conducted genome-wide association studies and meta-analyses of associations of common genetic variants with 6 plasma n6 PUFAs in 8631 white adults (55% women) across 5 prospective studies. Plasma phospholipid or total plasma fatty acids were analyzed by similar gas chromatography techniques. The n6 fatty acids linoleic acid (LA), γ-linolenic acid (GLA), dihomo-GLA, arachidonic acid, and adrenic acid were expressed as percentage of total fatty acids. We performed linear regression with robust SEs to test for single-nucleotide polymorphism-fatty acid associations, with pooling using inverse-variance-weighted meta-analysis. Novel regions were identified on chromosome 10 associated with LA (rs10740118; P=8.1×10(-9); near NRBF2), on chromosome 16 with LA, GLA, dihomo-GLA, and arachidonic acid (rs16966952; P=1.2×10(-15), 5.0×10(-11), 7.6×10(-65), and 2.4×10(-10), respectively; NTAN1), and on chromosome 6 with adrenic acid after adjustment for arachidonic acid (rs3134950; P=2.1×10(-10); AGPAT1). We confirmed previous findings of the FADS cluster on chromosome 11 with LA and arachidonic acid, and further observed novel genome-wide significant association of this cluster with GLA, dihomo-GLA, and adrenic acid (P=2.3×10(-72), 2.6×10(-151), and 6.3×10(-140), respectively). CONCLUSIONS: Our findings suggest that along with the FADS gene cluster, additional genes may influence n6 PUFA composition.
BACKGROUND:Omega6 (n6) polyunsaturated fatty acids (PUFAs) and their metabolites are involved in cell signaling, inflammation, clot formation, and other crucial biological processes. Genetic components, such as variants of fatty acid desaturase (FADS) genes, determine the composition of n6PUFAs. METHODS AND RESULTS: To elucidate undiscovered biological pathways that may influence n6PUFA composition, we conducted genome-wide association studies and meta-analyses of associations of common genetic variants with 6 plasma n6PUFAs in 8631 white adults (55% women) across 5 prospective studies. Plasma phospholipid or total plasma fatty acids were analyzed by similar gas chromatography techniques. The n6 fatty acidslinoleic acid (LA), γ-linolenic acid (GLA), dihomo-GLA, arachidonic acid, and adrenic acid were expressed as percentage of total fatty acids. We performed linear regression with robust SEs to test for single-nucleotide polymorphism-fatty acid associations, with pooling using inverse-variance-weighted meta-analysis. Novel regions were identified on chromosome 10 associated with LA (rs10740118; P=8.1×10(-9); near NRBF2), on chromosome 16 with LA, GLA, dihomo-GLA, and arachidonic acid (rs16966952; P=1.2×10(-15), 5.0×10(-11), 7.6×10(-65), and 2.4×10(-10), respectively; NTAN1), and on chromosome 6 with adrenic acid after adjustment for arachidonic acid (rs3134950; P=2.1×10(-10); AGPAT1). We confirmed previous findings of the FADS cluster on chromosome 11 with LA and arachidonic acid, and further observed novel genome-wide significant association of this cluster with GLA, dihomo-GLA, and adrenic acid (P=2.3×10(-72), 2.6×10(-151), and 6.3×10(-140), respectively). CONCLUSIONS: Our findings suggest that along with the FADS gene cluster, additional genes may influence n6PUFA composition.
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