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PLoS One. 2017 Dec 13;12(12):e0186456. doi: 10.1371/journal.pone.0186456. eCollection 2017.

Genome-wide association meta-analysis of fish and EPA+DHA consumption in 17 US and European cohorts.

Author information

1
Friedman School of Nutrition Science & Policy, Tufts University, Boston, MA, United States of America.
2
Nutrition and Genomics Laboratory, Jean Mayer US Department of Agriculture Human Nutrition Research Center on Aging, Tufts University, Boston, MA, United States of America.
3
Division of Statistical Genomics, Department of Genetics, Washington University School of Medicine, St. Louis, MO, United States of America.
4
Division of Preventive Medicine, Brigham and Women's Hospital, Boston, MA, United States of America.
5
Division of Epidemiology, Human Genetics and Environmental Sciences, University of Texas Health Science Center at Houston, Houston, TX, United States of America.
6
National Institute for Health and Welfare, Helsinki, Finland.
7
Estonian Genome Center, University of Tartu, Tartu, Estonia.
8
Institute of Behavioural Sciences, University of Helsinki, Helsinki, Finland.
9
Folkhälsan Research Centre, Helsinki, Finland.
10
Sticht Center on Aging, Wake Forest School of Medicine, Winston Salem, NC, United States of America.
11
Department of Nutrition, Harvard School of Public Health, Boston, MA, United States of America.
12
Department of Epidemiology, Erasmus MC, Rotterdam, The Netherlands.
13
Netherlands Genomics Initiative-sponsored Netherlands Consortium for Healthy Aging, Leiden, The Netherlands.
14
Department of Dietetics and Nutrition, Harokopio University, Athens, Greece.
15
William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, London, United Kingdom.
16
Department of Food and Environmental Sciences, University of Helsinki, Finland.
17
Research Centre of Applied and Preventive Cardiovascular Medicine, University of Turku, Turku, Finland.
18
Division of Epidemiology and Community Health, University of Minnesota School of Public Health, Minneapolis, MN, United States of America.
19
Department of Medicine, Epidemiology and Health Services, University of Washington, Seattle, WA, United States of America.
20
Department of Medicine, Harvard Medical School, and Division of Aging Brigham and Women's Hospital, Boston, MA, United States of America.
21
Los Angeles Biomedical Research Institute and Department of Pediatrics, Harbor-UCLA Medical Center, Los Angeles, CA, United States of America.
22
Institute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland.
23
University of Tartu, Estonian Genome Center, Tartu, Estonia.
24
Department of Biostatistics, Boston University School of Public Health, Boston, MA, United States of America.
25
Division of Cardiovascular Medicine, Howard University College of Medicine, Washington DC, United States of America.
26
Nutritional Epidemiology Program, USDA Human Nutrition Research Center on Aging, Tufts University, Boston, MA, United States of America.
27
Department of Chronic Disease Prevention, National Institute for Health and Welfare, Helsinki, Finland.
28
Department of Medical Genetics, University of Helsinki and University Central Hospital, Helsinki, Finland.
29
Department of Biostatistical Sciences, Wake Forest School of Medicine, Winston Salem, NC, United States of America.
30
Laboratory of Neurogenetics, National Institute of Aging, Bethesda, MD, United States of America.
31
Clinical Research Branch, National Institute on Aging, Baltimore, MD, United States of America.
32
Center for Public Health Genomics and Division of Biostatistics and Epidemiology, Department of Public Health Sciences, University of Virginia, Charlottesville, VA, United States of America.
33
Department of Laboratory Medicine and Pathology, University of Minnesota, Minneapolis, MN, United States of America.
34
Leiden University College, The Hague, The Netherlands.
35
Department of Internal Medicine, Erasmus MC, Rotterdam, The Netherlands.
36
Second Department of Cardiology, University General Hospital Attikon, Athens, Greece.
37
Harvard Medical School, Boston MA, United States of America.
38
Department of Clinical Chemistry, Fimlab Laboratories, University of Tampere School of Medicine, Tampere, Finland.
39
Department of Clinical Physiology, University of Tampere and Tampere University Hospital, Tampere, Finland.
40
Department of Medicine, University of Turku and Turku University Hospital, Turku, Finland.
41
Department of Medicine, University of Washington, Seattle, WA, United States of America.
42
NHLBI Framingham Heart Study, Framingham, MA, United States of America.
43
Department of General Practice and Primary health Care, University of Helsinki, Helsinki, Finland.
44
Helsinki University Central Hospital, Unit of General Practice, Helsinki, Finland.
45
Geriatric Rehabilitation Unit, Azienda Sanitaria Firenze, Florence, Italy.
46
New York Academy of Medicine, New York, NY, United States of America.
47
Princess Al-Jawhara Al-Brahim Centre of Excellence in Research of Hereditary Disorder, King Abdulaziz University, Jeddah, Saudi Arabia.
48
Department of Clinical Physiology and Nuclear Medicine, Turku University Hospital, Turku, Finland.

Abstract

BACKGROUND:

Regular fish and omega-3 consumption may have several health benefits and are recommended by major dietary guidelines. Yet, their intakes remain remarkably variable both within and across populations, which could partly owe to genetic influences.

OBJECTIVE:

To identify common genetic variants that influence fish and dietary eicosapentaenoic acid plus docosahexaenoic acid (EPA+DHA) consumption.

DESIGN:

We conducted genome-wide association (GWA) meta-analysis of fish (n = 86,467) and EPA+DHA (n = 62,265) consumption in 17 cohorts of European descent from the CHARGE (Cohorts for Heart and Aging Research in Genomic Epidemiology) Consortium Nutrition Working Group. Results from cohort-specific GWA analyses (additive model) for fish and EPA+DHA consumption were adjusted for age, sex, energy intake, and population stratification, and meta-analyzed separately using fixed-effect meta-analysis with inverse variance weights (METAL software). Additionally, heritability was estimated in 2 cohorts.

RESULTS:

Heritability estimates for fish and EPA+DHA consumption ranged from 0.13-0.24 and 0.12-0.22, respectively. A significant GWA for fish intake was observed for rs9502823 on chromosome 6: each copy of the minor allele (FreqA = 0.015) was associated with 0.029 servings/day (~1 serving/month) lower fish consumption (P = 1.96x10-8). No significant association was observed for EPA+DHA, although rs7206790 in the obesity-associated FTO gene was among top hits (P = 8.18x10-7). Post-hoc calculations demonstrated 95% statistical power to detect a genetic variant associated with effect size of 0.05% for fish and 0.08% for EPA+DHA.

CONCLUSIONS:

These novel findings suggest that non-genetic personal and environmental factors are principal determinants of the remarkable variation in fish consumption, representing modifiable targets for increasing intakes among all individuals. Genes underlying the signal at rs72838923 and mechanisms for the association warrant further investigation.

PMID:
29236708
PMCID:
PMC5728559
DOI:
10.1371/journal.pone.0186456
[Indexed for MEDLINE]
Free PMC Article

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