Dietary fatty acids modulate associations between genetic variants and circulating fatty acids in plasma and erythrocyte membranes: Meta‐analysis of nine studies in the CHARGE consortium
Open accessAbstract
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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Evidence for interactions between diet and these genes is uncommon.
“Large investigations pooling multiple cohorts have observed main (population) effects of either dietary influences or genes on major cardiometabolic risk factors, but evidence for interactions between diet and these genes is uncommon and, more relevantly, magnitudes of such potential interactions are often small.78-83”
From Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review (2016) · cites this paper as [83]
Magnitudes of such potential gene-diet interactions are often small.
“Large investigations pooling multiple cohorts have observed main (population) effects of either dietary influences or genes on major cardiometabolic risk factors, but evidence for interactions between diet and these genes is uncommon and, more relevantly, magnitudes of such potential interactions are often small.78-83”
From Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review (2016) · cites this paper as [83]
Large investigations pooling multiple cohorts have observed main (population) effects of either dietary influences or genes on major cardiometabolic risk factors.
“Large investigations pooling multiple cohorts have observed main (population) effects of either dietary influences or genes on major cardiometabolic risk factors, but evidence for interactions between diet and these genes is uncommon and, more relevantly, magnitudes of such potential interactions are often small.78-83”
From Dietary and Policy Priorities for Cardiovascular Disease, Diabetes, and Obesity: A Comprehensive Review (2016) · cites this paper as [83]
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- Authors
- Smith, C. E., Follis, J. L., Nettleton, J. A., Foy, M., Wu, J. H. Y., Ma, Y., Tanaka, T., Manichakul, A. W., Wu, H., Chu, A. Y., Steffen, L. M., Fornage, M., Mozaffarian, D., Kabagambe, E. K., Ferruci, L., Chen, Y. I., Rich, S. S., Djoussé, L., Ridker, P. M., Tang, W., McKnight, B., Tsai, M. Y., Bandinelli, S., Rotter, J. I., Hu, F. B., Chasman, D. I., Psaty, B. M., Arnett, D. K., King, I. B., Sun, Q., Wang, L., Lumley, T., Chiuve, S. E., Siscovick, D. S., Ordovás, J. M., & Lemaitre, R. N.
- Affiliations
- Tufts University (US)
- University of St. Thomas - Texas (US)
- The University of Texas Health Science Center at Houston (US)
- The University of Sydney (AU)
- National Institute on Aging (US)
- University of Virginia (US)
- Harvard University (US)
- Brigham and Women's Hospital (US)
- University of Minnesota (US)
- Vanderbilt University (US)
- Translational Gerontology Branch National Institute on Aging Baltimore MD USA
- The Lundquist Institute (US)
- University of Washington (US)
- Azienda Sanitaria di Firenze (IT)
- Group Health Cooperative (US)
- University of Alabama at Birmingham (US)
- University of New Mexico (US)
- University of Auckland (NZ)
- Cardiovascular Health Research Unit Department of Medicine Group Health Research Institute Group Health Cooperative Seattle WA USA
- Corresponding author
- Smith, Caren E.
- ORCID
- Smith, Caren E.
- Wu, Jason H.Y.
- Ma, Yiyi
- Tanaka, Toshiko
- Wu, Hongyu
- Chu, Audrey Y.
- Steffen, Lyn M.
- Fornage, Myriam
- Mozaffarian, Dariush
- Kabagambe, Edmond K.
- Chen, Yii‐Der Ida
- Rich, Stephen S.
- Djoussé, Luc
- Ridker, Paul M.
- Tang, Weihong
- Tsai, Michael Y.
- Bandinelli, Stefania
- Rotter, Jerome I.
- Hu, Frank B.
- Chasman, Daniel I.
- Psaty, Bruce M.
- Arnett, Donna K.
- King, Irena B.
- Sun, Qi
- Wang, Lu
- Lumley, Thomas
- Chiuve, Stephanie E.
- Siscovick, David S.
- Ordovás, José M.
- Venue
- Molecular Nutrition & Food Research
- Publisher
- Wiley
- Published
- 2015-03-16
- Volume
- 59
- Issue
- 7
- Pages
- 1373-1383
- ISSN
- 1613-4125 (ISSN-L)
- 1613-4133
- PMC
- PMC4491005
- OpenAlex
- W1996071127
- Cited by
- 46
- References
- 26
- Citations by year
- 2026: 1 · 2025: 1 · 2024: 2 · 2023: 1 · 2022: 3 · 2021: 5 · 2020: 3 · 2019: 3 · 2018: 10 · 2017: 4 · 2016: 9 · 2015: 4
- FWCI
- 8.55
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Molecular Nutrition & Food Research (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- eScholarship (California Digital Library) (submittedVersion)
- Funders
- National Institutes of Health (n01hc95164-17-0-1, n01hc085082-026, n01hc085081-021, n01hc085079-024, n01hc085083-027, n01hc95165-34-0-1, n01hc085080-026, n01hc95161-24-0-1, n01hc095169-003, UL1TR000124, n01hc95166-21-0-1, n01hc085086-022, n01hc95162-31-0-1, n01hc95168-27-0-1, n01hc95160-18-0-1, n01hc095167-000, n01hc95163-22-0-1, n01hc55222-0-0-0, n02hl64278-6-0-0, 5r01hl043851-10, n01hc95159-40-0-1, UL1TR000170, 5r01hl084099-04)
- National Institute on Aging (R56AG023629, AG023629, R01AG023629)
- National Heart, Lung, and Blood Institute (HHSN268201 100012C, HL60712, R01HL080467, HHSN268201100007I, HHSN268201300028C, N01 HC085086, HHSN268201100007C, R01HL060712, N01 HC-95159, N01-HC-95160, N01-HC095169, HHSN2682 01100008C, HL54776, N01 HC-95168, HH-SN-268201100006C, HHSN268201100011C, HHS-N2-68201300029C, HHSN2682011-00005I, HHSN268201300027C, N01 HC95167, HL-105756, N01 HC085079, (N01-HC-95163, R01‐HL043851, N01 HC085083, HL-087652, R01-HL-084099, HL099355, HHSN2682011-00009I, N01 HC-95161, N01 HC95165, N01HC95164, N01 HC085080, R01HL087652, HHSN268201100005C, HHSN268200900041C, HHSN 268200800007C, N02 HL064278, HHSN268201100005G, HHSN268201100010C, R01HL035464, N01-HC-095159, U01HL072524, HL078885, HHSN268201300026C, HHS-N2-68201300025C, R00HL097068, HHSN268201100011I, R01HL087641, HHSN268201200036C, R01HL059367, R01HL054776, HHSN26820 1100009C, N01HC085082, RC1HL099355, R01HL105756, U01HL080295, HL080467, HL085710, N01 HC055222, R00HL098459, HHSN2682011-00008I, N01‐HC‐95166, K08HL112845, R01HL091357, N01 HC085081, R01HL085710, R01HL078885, HL080295, R01HL080295, N01 HC-95162, R00HL095649, R01HL086694, R01HL034594, N01 HC95169)
- National Human Genome Research Institute (U01HG004402, U01HG004446, U01HG004729, U01HG004424)
- National Cancer Institute (CA055075, P01CA087969, CA 047988, UM1CA182913, P01CA055075, R01CA047988, UM1CA167552)
- National Institute of Diabetes and Digestive and Kidney Diseases (DK063491, P30DK063491)
- National Center for Research Resources (UL1RR024156, UL1RR025005, RR024156)
- National Center for Advancing Translational Sciences
- National Institute on Minority Health and Health Disparities (R01MD009164)
- Topics
- Health Sciences › Nursing › Nutrition and Dietetics › Fatty Acid Research and Health
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Nutrition, Genetics, and Disease
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Keywords
- dietary fatty acids, gene-diet interaction, omega-3 fatty acids, circulating fatty acids, erythrocyte membrane, plasma lipids, FADS1, alpha-linolenic acid, docosahexaenoic acid, docosapentaenoic acid, eicosapentaenoic acid, linoleic acid, genetic variants, fatty acid desaturase, fatty acid elongation, cardiovascular risk
- MeSH terms
- Fatty Acid Elongases, Delta-5 Fatty Acid Desaturase, Acetyltransferases, Acyltransferases, Carboxy-Lyases, Diet, Docosahexaenoic Acids, Erythrocyte Membrane, Fatty Acids, Female, Humans, Male, Middle Aged, Eicosapentaenoic Acid, Fatty Acids, Omega-3, Polymorphism, Single Nucleotide, Fatty Acid Desaturases, Adaptor Proteins, Signal Transducing
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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