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Circulation. 2017 Jun 13;135(24):2373-2388. doi: 10.1161/CIRCULATIONAHA.116.026560. Epub 2017 May 12.

Causal Associations of Adiposity and Body Fat Distribution With Coronary Heart Disease, Stroke Subtypes, and Type 2 Diabetes Mellitus: A Mendelian Randomization Analysis.

Author information

1
From Farr Institute of Health Informatics Research, UCL Institute of Health Informatics, University College London, United Kingdom (C.E.D., G.F., D.P.-M., A.D.H., J.P.C.); Department of Mathematics and Statistics, Lancaster University, United Kingdom (T.M.P.); UCLGenetics Institute, University College London, United Kingdom (J.W.); Applied Statistical Methods in Medical Research Group, Universidad Catolica de San Antonio de Murcia, Spain (D.P.-M.); Social Genetic & Developmental Psychiatry, King's College London, United Kingdom (D.Z.); Institute of Cardiovascular Science, University College London, United Kingdom (J.E.L.E., T.S., A.D.H., S.E.H.); MRC Unit for Lifelong Health & Ageing at UCL, London, United Kingdom (A.W., D.K.); Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (H.R.W., M.J.C., P.B.M.); NIHR Barts Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (H.R.W., M.J.C., P.B.M.); Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, United Kingdom (S.M., J.F.P.); Department of Cardiology, Leiden University Medical Center, The Netherlands (S.T., W.J.); South Australian Health and Medical Research Institute, Adelaide (M.M., E.H.); EMBL Australia, Adelaide (M.M.); School of Social and Community Medicine, University of Bristol, United Kingdom (R.W.M., T.R.G., Y.B.-S., D.A.L., G.D.S.); Centre for Clinical Pharmacology, University College London, United Kingdom (R.S.); Institute for Social and Economic Research, University of Essex, Colchester, United Kingdom (M.K.); Centre for Population Health Research, School of Health Sciences and Sansom Institute, University of South Australia, Adelaide (E.H., A.Z.); Population, Policy & Practice, UCL Great Ormond Street Institute of Child Health, London, United Kingdom (E.H., C.P.); Department of Primary Care & Population Health, University College London, Royal Free Campus, United Kingdom (B.J.J.); MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom (T.R.G., D.A.L., G.D.S.); Department of Women's Cancer, Institute for Women's Health, UCL, London, United Kingdom (A.G.-M., A.R., U.M.); Department of Clinical Epidemiology, Leiden University Medical Center, The Netherlands (R.d.M., D.O.M.-K.); Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center, The Netherlands (R.N., S.T.); Interuniversity Cardiology Institute Netherlands, Utrecht (W.J.); Departments of Neurology and Public Health Sciences, University of Virginia, Charlottesville (B.B.W.); Department of Public Health and Primary Care, Leiden University Medical Center, The Netherlands (D.O.M.-K.); BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, United Kingdom (N.S.); Department of Epidemiology and Public Health, University College London, United Kingdom (M.K.); Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, United Kingdom (F.D.); Department of Health Sciences, University of Leicester, United Kingdom (F.D.); Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, United Kingdom (M.V.H.); Medical Research Council Population Health Research Unit at the University of Oxford, United Kingdom (M.V.H.); and National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals, United Kingdom (M.V.H.). jp.casas@ucl.ac.uk c.dale@ucl.ac.uk.
2
From Farr Institute of Health Informatics Research, UCL Institute of Health Informatics, University College London, United Kingdom (C.E.D., G.F., D.P.-M., A.D.H., J.P.C.); Department of Mathematics and Statistics, Lancaster University, United Kingdom (T.M.P.); UCLGenetics Institute, University College London, United Kingdom (J.W.); Applied Statistical Methods in Medical Research Group, Universidad Catolica de San Antonio de Murcia, Spain (D.P.-M.); Social Genetic & Developmental Psychiatry, King's College London, United Kingdom (D.Z.); Institute of Cardiovascular Science, University College London, United Kingdom (J.E.L.E., T.S., A.D.H., S.E.H.); MRC Unit for Lifelong Health & Ageing at UCL, London, United Kingdom (A.W., D.K.); Clinical Pharmacology, William Harvey Research Institute, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (H.R.W., M.J.C., P.B.M.); NIHR Barts Cardiovascular Biomedical Research Unit, Barts and The London School of Medicine and Dentistry, Queen Mary University of London, United Kingdom (H.R.W., M.J.C., P.B.M.); Usher Institute of Population Health Sciences and Informatics, University of Edinburgh, United Kingdom (S.M., J.F.P.); Department of Cardiology, Leiden University Medical Center, The Netherlands (S.T., W.J.); South Australian Health and Medical Research Institute, Adelaide (M.M., E.H.); EMBL Australia, Adelaide (M.M.); School of Social and Community Medicine, University of Bristol, United Kingdom (R.W.M., T.R.G., Y.B.-S., D.A.L., G.D.S.); Centre for Clinical Pharmacology, University College London, United Kingdom (R.S.); Institute for Social and Economic Research, University of Essex, Colchester, United Kingdom (M.K.); Centre for Population Health Research, School of Health Sciences and Sansom Institute, University of South Australia, Adelaide (E.H., A.Z.); Population, Policy & Practice, UCL Great Ormond Street Institute of Child Health, London, United Kingdom (E.H., C.P.); Department of Primary Care & Population Health, University College London, Royal Free Campus, United Kingdom (B.J.J.); MRC Integrative Epidemiology Unit, University of Bristol, United Kingdom (T.R.G., D.A.L., G.D.S.); Department of Women's Cancer, Institute for Women's Health, UCL, London, United Kingdom (A.G.-M., A.R., U.M.); Department of Clinical Epidemiology, Leiden University Medical Center, The Netherlands (R.d.M., D.O.M.-K.); Department of Internal Medicine, Section Gerontology and Geriatrics, Leiden University Medical Center, The Netherlands (R.N., S.T.); Interuniversity Cardiology Institute Netherlands, Utrecht (W.J.); Departments of Neurology and Public Health Sciences, University of Virginia, Charlottesville (B.B.W.); Department of Public Health and Primary Care, Leiden University Medical Center, The Netherlands (D.O.M.-K.); BHF Glasgow Cardiovascular Research Centre, Faculty of Medicine, United Kingdom (N.S.); Department of Epidemiology and Public Health, University College London, United Kingdom (M.K.); Department of Non-communicable Disease Epidemiology, London School of Hygiene and Tropical Medicine, United Kingdom (F.D.); Department of Health Sciences, University of Leicester, United Kingdom (F.D.); Clinical Trial Service Unit & Epidemiological Studies Unit, Nuffield Department of Population Health, Big Data Institute Building, University of Oxford, United Kingdom (M.V.H.); Medical Research Council Population Health Research Unit at the University of Oxford, United Kingdom (M.V.H.); and National Institute for Health Research Oxford Biomedical Research Centre, Oxford University Hospitals, United Kingdom (M.V.H.).

Abstract

BACKGROUND:

The implications of different adiposity measures on cardiovascular disease etiology remain unclear. In this article, we quantify and contrast causal associations of central adiposity (waist-to-hip ratio adjusted for body mass index [WHRadjBMI]) and general adiposity (body mass index [BMI]) with cardiometabolic disease.

METHODS:

Ninety-seven independent single-nucleotide polymorphisms for BMI and 49 single-nucleotide polymorphisms for WHRadjBMI were used to conduct Mendelian randomization analyses in 14 prospective studies supplemented with coronary heart disease (CHD) data from CARDIoGRAMplusC4D (Coronary Artery Disease Genome-wide Replication and Meta-analysis [CARDIoGRAM] plus The Coronary Artery Disease [C4D] Genetics; combined total 66 842 cases), stroke from METASTROKE (12 389 ischemic stroke cases), type 2 diabetes mellitus from DIAGRAM (Diabetes Genetics Replication and Meta-analysis; 34 840 cases), and lipids from GLGC (Global Lipids Genetic Consortium; 213 500 participants) consortia. Primary outcomes were CHD, type 2 diabetes mellitus, and major stroke subtypes; secondary analyses included 18 cardiometabolic traits.

RESULTS:

Each one standard deviation (SD) higher WHRadjBMI (1 SD≈0.08 U) associated with a 48% excess risk of CHD (odds ratio [OR] for CHD, 1.48; 95% confidence interval [CI], 1.28-1.71), similar to findings for BMI (1 SD≈4.6 kg/m2; OR for CHD, 1.36; 95% CI, 1.22-1.52). Only WHRadjBMI increased risk of ischemic stroke (OR, 1.32; 95% CI, 1.03-1.70). For type 2 diabetes mellitus, both measures had large effects: OR, 1.82 (95% CI, 1.38-2.42) and OR, 1.98 (95% CI, 1.41-2.78) per 1 SD higher WHRadjBMI and BMI, respectively. Both WHRadjBMI and BMI were associated with higher left ventricular hypertrophy, glycemic traits, interleukin 6, and circulating lipids. WHRadjBMI was also associated with higher carotid intima-media thickness (39%; 95% CI, 9%-77% per 1 SD).

CONCLUSIONS:

Both general and central adiposity have causal effects on CHD and type 2 diabetes mellitus. Central adiposity may have a stronger effect on stroke risk. Future estimates of the burden of adiposity on health should include measures of central and general adiposity.

KEYWORDS:

Mendelian randomization analysis; adiposity; body fat distribution; body mass index; coronary artery disease; stroke; waist-hip ratio

PMID:
28500271
PMCID:
PMC5515354
DOI:
10.1161/CIRCULATIONAHA.116.026560
[Indexed for MEDLINE]
Free PMC Article

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