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Causal Associations of Adiposity and Body Fat Distribution With Coronary Heart Disease, Stroke Subtypes, and Type 2 Diabetes Mellitus: A Mendelian Randomization Analysis
Open accessAbstract
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/m 2 ; 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.
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“Obesity, characterized by excessive body fat, constitutes a major risk factor for the development of type 2 diabetes (T2D), dyslipidemia, cardiometabolic disease1, cancer2, and overall mortality3.”
From Transforming obesity: The advancement of multi-receptor drugs (2024) · cites this paper as [1]
Experimental — accuracy not yet measuredIn the citing paper
“With increasing availability of large-scale phenotyping (and genotyping), MR is being widely applied to quantitative traits (e.g. markers or adiposity, such as body mass index 13-16 ; blood lipids such as HDL-cholesterol 17-19 ; inflammation-related proteins such as interleukin-6 receptor 20,21 12 ) with the aim of discovering modifiable risk factors for disease that are causal and amenable to the”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [17]
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“HDL cholesterol 17,19 MRs do not provide evidence of causation, once unbalanced horizontal pleiotropy is taken into account”
From Integrating genomics with biomarkers and therapeutic targets to invigorate cardiovascular drug development (2021) · cites this paper as [17]
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BackgroundActivin E–ACVR1C cross talk controls energy storage via suppression of adipose lipolysis in mice
Adam, R. C., Pryce, D. S., Lee, J. S., Zhao, Y., Mintah, I. J., Min, S., Halasz, G., Mastaitis, J., Atwal, G. S., Aykul, S., et al. (2023) · Proceedings of the National Academy of Sciences · doi:10.1073/pnas.2309967120 · Cited by 44
Impact of Serum Calcium Levels on Alzheimer’s Disease: A Mendelian Randomization Study
He, Y., Zhang, H., Wang, T., Han, Z., Ni, Q., Wang, K., Wang, L., Zhang, Y., Hu, Y., Jin, S., et al. (2020) · Journal of Alzheimer s Disease · doi:10.3233/jad-191249 · Cited by 45
Big Data Features, Applications, and Analytics in Cardiology—A Systematic Literature Review
Nazir, S., Nawaz, M., Adnan, A., Shahzad, S., & Asadi, S. (2019) · IEEE Access · doi:10.1109/access.2019.2941898 · Cited by 45
Kapoor, N., Lotfaliany, M., Sathish, T., Thankappan, K. R., Thomas, N., Furler, J., Oldenburg, B. F., & Tapp, R. J. (2020) · Journal of Nutritional Science · doi:10.1017/jns.2020.8 · Cited by 44
Emdin, C. A., Khera, A. V., Aragam, K. G., Haas, M. E., Chaffin, M. D., Klarin, D. M., Natarajan, P., Bick, A. G., Zekavat, S. M., Nomura, A., et al. (2018) · Diabetes · doi:10.2337/db18-0857 · Cited by 42
Michaëlsson, K., Baron, J. A., Byberg, L., Höijer, J., Larsson, S. C., Svennblad, B., Melhus, H., Wolk, A., & Lemming, E. W. (2020) · PLoS Medicine · doi:10.1371/journal.pmed.1003331 · Cited by 45
Achilles Tendon Rupture and Dysmetabolic Diseases: A Multicentric, Epidemiologic Study
Oliva, F., Marsilio, E., Asparago, G., Via, A. G., Biz, C., Padulo, J., Spoliti, M., Foti, C., Oliva, G., Mannarini, S., et al. (2022) · Journal of Clinical Medicine · doi:10.3390/jcm11133698 · Cited by 42
“Increased abdominal adiposity, chronic inflammation status, and endocrine system disfunction are also three of the main features of diabetes mellitus [41].”
BackgroundJoint impact of polygenic risk score and lifestyles on early- and late-onset cardiovascular diseases
The China Kadoorie Biobank Collaborative Group, Sun, D., Ding, Y., Yu, C., Sun, D., Pang, Y., Pei, P., Yang, L., Millwood, I. Y., Walters, R. G., et al. (2024) · Nature Human Behaviour · doi:10.1038/s41562-024-01923-7 · Cited by 43
Xu, H., Jin, C., & Guan, Q.-B. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00603 · Cited by 43
Yuan, S., Merino, J., & Larsson, S. C. (2023) · Diabetologia · doi:10.1007/s00125-023-05879-7 · Cited by 42
Johansen, M. Ø., Nielsen, S. F., Afzal, S., Vedel‐Krogh, S., Smith, G. D., & Nordestgaard, B. G. (2020) · Clinical Chemistry · doi:10.1093/clinchem/hvaa290 · Cited by 42
Wang, T., Zhang, R., Ma, X., Wang, S., He, Z., Huang, Y., Xu, B., Li, Y., Zhang, H., Jiang, F., et al. (2018) · Obesity · doi:10.1002/oby.22167 · Cited by 43
Multivariable MR Can Mitigate Bias in Two‐Sample MR Using Covariable‐Adjusted Summary Associations
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Blood-brain barrier pathology in cerebral small vessel disease
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“In fact, the risk of ischemic stroke was found to have increased by 30% per each standard deviation increase in abdominal obesity (Dale et al., 2017).”
Bell, J. A., Bull, C. J., Gunter, M. J., Carslake, D., Mahajan, A., Smith, G. D., Timpson, N. J., & Vincent, E. E. (2020) · Diabetes Care · doi:10.2337/dc19-2348 · Cited by 32
Katsoulis, M., Stavola, B. L. D., Diaz‐Ordaz, K., Gomes, M., Lai, A. G., Λάγιου, Π., Wannamethee, S. G., Tsilidis, K. K., Lumbers, R. T., Denaxas, S., et al. (2021) · Epidemiology · doi:10.1097/ede.0000000000001393 · Cited by 36
The “Common Soil Hypothesis” Revisited—Risk Factors for Type 2 Diabetes and Cardiovascular Disease
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“These observations agree with previously published population-based studies showing that waist-to-hip ratio is an independent risk factor for T2D [72].”
ResultChristen, T., Trompet, S., Rensen, P. C. N., van Dijk, K. W., Lamb, H. J., Jukema, J. W., Rosendaal, F. R., le Cessie, S., & de Mutsert, R. (2019) · Nutrition Metabolism and Cardiovascular Diseases · doi:10.1016/j.numecd.2019.03.010 · Cited by 35
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Obesity and the Risk of Cryptogenic Ischemic Stroke in Young Adults
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“The increase in the prevalence of type 2 diabetes is not surprising, since obesity is one of its major causes (Dale et al., 2017).”
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“We hypothesized that these discrepant findings could be explained by differences in the considered confounding factors, which includes the adjustment for the confounding factors, BMI and sleep apnea (Dale et al., 2017; Javaheri et al., Shortest (0–5”
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Stroke in the patient with diabetes (part 1) – Epidemiology, etiology, therapy and prognosis
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“When unbalanced horizontal pleiotropy is absent, results of all methods are expected to be consistent (27).”
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Metadata
- Authors
- Dale, C. E., Fatemifar, G., Palmer, T. M., White, J., Prieto-Merino, D., Zabaneh, D., Engmann, J. E. L., Shah, T., Wong, A., Warren, H. R., McLachlan, S., Trompet, S., Moldovan, M., Morris, R. W., Sofat, R., Kumari, M., Hyppönen, E., Jefferis, B. J., Gaunt, T. R., Ben-Shlomo, Y., Zhou, A., Gentry-Maharaj, A., Ryan, A., Mutsert, R. D., Noordam, R., Caulfield, M. J., Jukema, J. W., Worrall, B. B., Munroe, P. B., Menon, U., Power, C., Kuh, D., Lawlor, D. A., Humphries, S. E., Mook-Kanamori, D. O., Sattar, N., Kivimaki, M., Price, J. F., Davey Smith, G., Dudbridge, F., Hingorani, A. D., Holmes, M. V., & Casas, J. P.
- Affiliations
- Farr Institute (GB)
- 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,...
- ORCID
- Dale, Caroline E.
- Fatemifar, Ghazaleh
- Palmer, Tom M.
- White, Jon
- Zabaneh, Delilah
- Engmann, Jorgen E.L.
- Shah, Tina
- Wong, Andrew
- Warren, Helen R.
- McLachlan, Stela
- Trompet, Stella
- Moldovan, Max
- Morris, Richard W.
- Sofat, Reecha
- Hyppönen, Elina
- Jefferis, Barbara J.
- Gaunt, Tom R.
- Zhou, Ang
- Ryan, Andy
- Mutsert, Renée de
- Noordam, Raymond
- Caulfield, Mark J.
- Jukema, J. Wouter
- Worrall, Bradford B.
- Munroe, Patricia B.
- Menon, Usha
- Power, Chris
- Kuh, Diana
- Lawlor, Debbie A.
- Humphries, Steve E.
- Sattar, Naveed
- Dudbridge, Frank
- Hingorani, Aroon D.
- Holmes, Michael V.
- Casas, Juan P.
- Venue
- Circulation
- Published
- 2017-06-13
- Volume
- 135
- Issue
- 24
- Pages
- 2373-2388
- ISSN
- 0009-7322 (ISSN-L)
- 1524-4539
- PMC
- PMC5515354
- OpenAlex
- W2626288726
- Cited by
- 345
- References
- 45
- Citations by year
- 2026: 14 · 2025: 25 · 2024: 34 · 2023: 42 · 2022: 48 · 2021: 41 · 2020: 39 · 2019: 45 · 2018: 46 · 2017: 11
- FWCI
- 25.53
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Circulation (publishedVersion)
- PubMed (publishedVersion)
- Edinburgh Research Explorer (University of Edinburgh) (publishedVersion, other-oa)
- Bristol Research (University of Bristol) (publishedVersion, other-oa)
- Lancaster EPrints (Lancaster University) (acceptedVersion)
- Europe PMC (PubMed Central) (acceptedVersion)
- PubMed Central (acceptedVersion)
- ENLIGHTEN (Jurnal Bimbingan dan Konseling Islam) (acceptedVersion)
- Open Access at Essex (University of Essex) (acceptedVersion)
- LSHTM Research Online (London School of Hygiene and Tropical Medicine) (acceptedVersion)
- Leicester Research Archive (University of Leicester) (submittedVersion, other-oa)
- Data Archiving and Networked Services (DANS) (submittedVersion)
- Leiden Repository (Leiden University) (submittedVersion)
- Adelaide Research & Scholarship (AR&S) (University of Adelaide) (submittedVersion)
- UCL Discovery (University College London) (submittedVersion)
- Figshare (submittedVersion)
- Research Portal (King's College London) (submittedVersion)
- Queen Mary Research Online (Queen Mary University of London) (submittedVersion)
- Explore Bristol Research (submittedVersion, other-oa)
- Funders
- Pfizer (RG/10/12/28456, K013351, ET2DS)
- National Institute for Health and Care Research (NF-SI-0515-10091, MC_UU_12013/1, NF-SI-0512-10113)
- British Heart Foundation (RG/08/008/25291, K013351, RG/10/12/28456, RG008/08, PG/13/66/30442, SP/13/6/30554)
- Imperial College London
- University College London
- European Commission (602757)
- Universiteit Leiden
- ZonMw (91614023)
- NordForsk (K013351)
- Leids Universitair Medisch Centrum
- Medical Research Council (MR/K013351/1, MR/K006584/1, RG/10/12/28456, K013351, MC_UU_12013, MR/N01104X/1, MC_UU_12013/1‐9, MCUU12013/1, MR/N01104X/2, ET2DS)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Cardiovascular Disease and Adiposity
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Keywords
- adiposity, abdominal obesity, waist-to-hip ratio, body mass index, coronary artery disease, ischemic stroke, type 2 diabetes, cardiometabolic disease, left ventricular hypertrophy, carotid intima-media thickness, circulating lipids, interleukin-6, glycemic traits
- MeSH terms
- Coronary Disease, Diabetes Mellitus, Type 2, Humans, Longitudinal Studies, Prospective Studies, Stroke, Polymorphism, Single Nucleotide, Adiposity, Body Fat Distribution, Mendelian Randomization Analysis, Observational Studies as Topic
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