Causal Associations of Adiposity and Body Fat Distribution With Coronary Heart Disease, Stroke Subtypes, and Type 2 Diabetes Mellitus: A Mendelian Randomization Analysis
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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 is a major risk factor for type 2 diabetes, dyslipidemia, cardiometabolic disease, cancer, and death.
“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 measuredMR is being widely applied to quantitative traits with the aim of discovering modifiable risk factors for disease that are causal and amenable to therapeutic modification.
“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]
HDL cholesterol MRs do not provide evidence of causation, once unbalanced horizontal pleiotropy is taken into account.
“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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Cites
Measuring inconsistency in meta-analyses
Higgins, J. P. T., Thompson, S. G., Deeks, J. J., & Altman, D. G. (2003) · BMJ · doi:10.1136/bmj.327.7414.557 · Cited by 63,139 · see citing works
Ng, M., Fleming, T., Robinson, M., Thomson, B., Graetz, N., Margono, C., Mullany, E. C., Biryukov, S., Abbafati, C., Abera, S. F., et al. (2014) · The Lancet · doi:10.1016/s0140-6736(14)60460-8 · Cited by 11,952 · see citing works
Bowden, J., Davey Smith, G., & Burgess, S. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv080 · Cited by 9,816 · see citing works
Bowden, J., Davey Smith, G., Haycock, P. C., & Burgess, S. (2016) · Genetic Epidemiology · doi:10.1002/gepi.21965 · Cited by 8,922 · see citing works
The metabolic phenotype in obesity: Fat mass, body fat distribution, and adipose tissue function
Goossens, G. H. (2017) · Obesity Facts · doi:10.1159/000471488 · Cited by 8,481 · see citing works
Prospective Studies Collaboration (2009) · The Lancet · doi:10.1016/s0140-6736(09)60318-4 · Cited by 4,807 · see citing works
Genetic studies of body mass index yield new insights for obesity biology
Study, T. L. C., Locke, A. E., The ADIPOGen Consortium, The AGEN-BMI Working Group, The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The, G. L. G. C., The, I. C. B. P., The MAGIC Investigators, The MuTHER Consortium, et al. (2015) · Nature · doi:10.1038/nature14177 · Cited by 4,534 · see citing works
Self-citationWiller (2013) · doi:10.1038/ng.2797 · Cited by 2,983 · see citing works
Self-citationYusuf, S., Hawken, S., Ôunpuu, S., Bautista, L., Franzosi, M. G., Commerford, P., Lang, C. C., Rumboldt, Z., Onen, C. L., Lisheng, L., et al. (2005) · The Lancet · doi:10.1016/s0140-6736(05)67663-5 · Cited by 2,903 · cited 1× · see citing works
“We conducted 3 tests for the causal estimation of each adiposity measure on cardiometabolic outcomes: (1) inverse variance–weighted (IVW) method, (2) MR-Egger, and (3) weighted median.”
O'Donnell, M. J., Chin, S. L., Rangarajan, S., Xavier, D., Liu, L., Zhang, H., Rao-Melacini, P., Zhang, X., Pais, P., Agapay, S., et al. (2016) · The Lancet · doi:10.1016/s0140-6736(16)30506-2 · Cited by 2,296 · see citing works
General and abdominal adiposity and risk of death in Europe
Pischon, T., Boeing, H., Hoffmann, K., Bergmann, M., Schulze, M. B., Overvad, K., van der Schouw, Y. T., Spencer, E., Moons, K. G. M., Tjønneland, A., et al. (2008) · New England Journal of Medicine · doi:10.1056/nejmoa0801891 · Cited by 2,155 · see citing works
the DIAbetes Genetics Replication And Meta-analysis (DIAGRAM) Consortium, Morris, A. P., Voight, B. F., Teslovich, T. M., Ferreira, T., Segrè, A. V., Steinthorsdottir, V., Strawbridge, R. J., Khan, H., Grallert, H., et al. (2012) · Nature Genetics · doi:10.1038/ng.2383 · Cited by 1,912 · see citing works
Calculating statistical power in Mendelian randomization studies.
Brion, M.-J. A., Shakhbazov, K., & Visscher, P. M. (2013) · International Journal of Epidemiology · doi:10.1093/ije/dyt179 · Cited by 1,751 · see citing works
Large-scale association analysis identifies new risk loci for coronary artery disease
The CARDIoGRAMplusC4D Consortium, Deloukas, P., DIAGRAM Consortium, CARDIOGENICS Consortium, MuTHER Consortium, Wellcome Trust Case Control Consortium, Kanoni, S., Willenborg, C., Farrall, M., Assimes, T. L., et al. (2013) · Nature Genetics · doi:10.1038/ng.2480 · Cited by 1,614 · see citing works
New genetic loci link adipose and insulin biology to body fat distribution
The ADIPOGen Consortium, Shungin, D., The CARDIOGRAMplusC4D Consortium, The CKDGen Consortium, The GEFOS Consortium, The GENIE Consortium, The, G. L. G. C., The, I. C. B. P., The International Endogene Consortium, Study, T. L. C., et al. (2015) · Nature · doi:10.1038/nature14132 · Cited by 1,580 · see citing works
Self-citationBody Fat Distribution and Risk of Cardiovascular Disease: An Update
Després, J.-P. (2012) · Circulation · doi:10.1161/circulationaha.111.067264 · Cited by 1,481 · see citing works
The Emerging Risk Factors Collaboration (2011) · The Lancet · doi:10.1016/s0140-6736(11)60105-0 · Cited by 1,216 · see citing works
Burgess, S., Dudbridge, F., & Thompson, S. G. (2016) · Statistics in Medicine · doi:10.1002/sim.6835 · Cited by 1,153 · see citing works
Self-citationVazquez, G., Duval, S., Jacobs, D. R., & Silventoinen, K. (2007) · Epidemiologic Reviews · doi:10.1093/epirev/mxm008 · Cited by 976 · cited 1× · see citing works
“We conducted 3 tests for the causal estimation of each adiposity measure on cardiometabolic outcomes: (1) inverse variance–weighted (IVW) method, (2) MR-Egger, and (3) weighted median.”
Aune, D., Sen, A., Prasad, M., Norat, T., Janszky, I., Tonstad, S., Romundstad, P., & Vatten, L. J. (2016) · BMJ · doi:10.1136/bmj.i2156 · Cited by 955 · see citing works
The Comprehensive R Archive Network
Hornik, K. (2012) · Wiley Interdisciplinary Reviews Computational Statistics · doi:10.1002/wics.1212 · Cited by 753 · see citing works
Burgess, S., Daniel, R. M., Butterworth, A. S., Thompson, S. G., & the EPIC-InterAct Consortium (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyu176 · Cited by 543 · see citing works
Traylor, M., Farrall, M., Holliday, E. G., Sudlow, C. L. M., Hopewell, J. C., Cheng, Y., Fornage, M., Ikram, M. A., Malik, R., Bevan, S., et al. (2012) · The Lancet Neurology · doi:10.1016/s1474-4422(12)70234-x · Cited by 475 · see citing works
Self-citationVoight, B. F., Kang, H. M., Ding, J., Palmer, C. D., Sidore, C., Chines, P. S., Burtt, N. P., Fuchsberger, C., Li, Y., Erdmann, J., et al. (2012) · PLoS Genetics · doi:10.1371/journal.pgen.1002793 · Cited by 464 · see citing works
Self-citationEmdin, C. A., Khera, A. V., Natarajan, P., Klarin, D., Zekavat, S. M., Hsiao, A. J., & Kathiresan, S. (2017) · JAMA · doi:10.1001/jama.2016.21042 · Cited by 378 · see citing works
Causal Mediation Analysis with Multiple Mediators
Daniel, R., Stavola, B. L. D., Cousens, S. N., & Vansteelandt, S. (2014) · Biometrics · doi:10.1111/biom.12248 · Cited by 319 · see citing works
Adjusting for Heritable Covariates Can Bias Effect Estimates in Genome-Wide Association Studies
Aschard, H., Vilhjálmsson, B. J., Joshi, A. D., Price, A. L., & Kraft, P. (2015) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2014.12.021 · Cited by 287 · see citing works
Würtz, P., Wang, Q., Kangas, A. J., Richmond, R. C., Skarp, J., Tiainen, M., Tynkkynen, T., Soininen, P., Havulinna, A. S., Kaakinen, M., et al. (2014) · PLoS Medicine · doi:10.1371/journal.pmed.1001765 · Cited by 280 · see citing works
Self-citationNordestgaard, B. G., Palmer, T., Benn, M., Zacho, J., Tybjærg‐Hansen, A., Smith, G. D., & Timpson, N. J. (2012) · PLoS Medicine · doi:10.1371/journal.pmed.1001212 · Cited by 280 · see citing works
Self-citationHolmes, M. V., Lange, L. A., Palmer, T., Lanktree, M. B., North, K. E., Almoguera, B., Buxbaum, S., Chandrupatla, H. R., Elbers, C. C., Guo, Y., et al. (2014) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2013.12.014 · Cited by 216 · see citing works
Self-citationThe Role of Adiposity in Cardiometabolic Traits: A Mendelian Randomization Analysis
Fall, T., Hägg, S., Mägi, R., Ploner, A., Fischer, K., Horikoshi, M., Sarin, A.-P., Thorleifsson, G., Ladenvall, C., Kals, M., et al. (2013) · PLoS Medicine · doi:10.1371/journal.pmed.1001474 · Cited by 203 · see citing works
Self-citationChange in Body Mass Index Associated With Lowest Mortality in Denmark, 1976-2013
Afzal, S., Tybjærg‐Hansen, A., Jensen, G. B., & Nordestgaard, B. G. (2016) · JAMA · doi:10.1001/jama.2016.4666 · Cited by 153 · see citing works
Reverse Causality and Confounding and the Associations of Overweight and Obesity with Mortality
Lawlor, D. A., Hart, C., Hole, D. J., & Smith, G. D. (2006) · Obesity · doi:10.1038/oby.2006.269 · Cited by 148 · see citing works
Self-citationAdiposity as a cause of cardiovascular disease: a Mendelian randomization study
Hägg, S., Fall, T., Ploner, A., Mägi, R., Fischer, K., Draisma, H. H. M., Kals, M., de Vries, P. S., Dehghan, A., Willems, S. M., et al. (2015) · International Journal of Epidemiology · doi:10.1093/ije/dyv094 · Cited by 142 · see citing works
Apfeltyp erhöht Diabetes- und KHK-Risiko
(2017) · DMW - Deutsche Medizinische Wochenschrift · doi:10.1055/s-0043-103789 · Cited by 142 · see citing works
Plasma urate concentration and risk of coronary heart disease: a Mendelian randomisation analysis.
White, J., Sofat, R., Hemani, G., Shah, T., Engmann, J., Dale, C., Shah, S., Kruger, F. A., Giambartolomei, C., Swerdlow, D. I., et al. (2016) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(15)00386-1 · Cited by 132 · see citing works
Self-citationLawlor, D. A., Harbord, R. M., Timpson, N. J., Lowe, G. D. O., Rumley, A., Gaunt, T. R., Baker, I. A., YARNELL, J. W. G., Mika Kivimaki, B., Meena Kumari, B., et al. (2008) · PLoS ONE · doi:10.1371/journal.pone.0003011 · Cited by 104 · see citing works
Self-citationAge- and Sex-Specific Causal Effects of Adiposity on Cardiovascular Risk Factors
Fall, T., Hägg, S., Ploner, A., Mägi, R., Fischer, K., Draisma, H. H. M., Sarin, A., Benyamin, B., Ladenvall, C., Åkerlund, M., et al. (2015) · Diabetes · doi:10.2337/db14-0988 · Cited by 73 · see citing works
Silverwood, R. J., Holmes, M. V., Dale, C. E., Lawlor, D. A., Whittaker, J. C., Smith, G. D., Leon, D. A., Palmer, T., Keating, B. J., Zuccolo, L., et al. (2014) · International Journal of Epidemiology · doi:10.1093/ije/dyu187 · Cited by 66 · see citing works
Self-citationCanoy, D., Cairns, B. J., Balkwill, A., Wright, F. L., Green, J., REEVES, G. K., Beral, V., & Collaborators, F. T. M. W. S. (2013) · European Journal of Preventive Cardiology · doi:10.1177/2047487313492631 · Cited by 44 · see citing works
Trichopoulou, A., Gnardellis, C., Lagiou, A., Benetou, V., Naska, A., & Trichopoulos, D. (2001) · American Journal of Clinical Nutrition · doi:10.1093/ajcn/74.5.574 · Cited by 36 · see citing works
Truong, Q. A., Ptaszek, L. M., Charipar, E. M., Taylor, C. M., Fontes, J. D., Kriegel, M. F., Irlbeck, T., Toepker, M. H., Schlett, C. L., Bamberg, F., et al. (2010) · Journal of Hypertension · doi:10.1097/hjh.0b013e32833b49cb · Cited by 28 · see citing works
Body-mass index, abdominal adiposity, and cardiovascular risk
Yusuf, S., & Anand, S. S. (2011) · The Lancet · doi:10.1016/s0140-6736(11)61120-3 · Cited by 26 · see citing works
HPTN 052 and the future of HIV treatment and prevention
Cates, W. (2011) · The Lancet · doi:10.1016/s0140-6736(11)61116-1 · Cited by 16 · see citing works
Dale, C. E., Nüesch, E., Prieto‐Merino, D., Choi, M., Amuzu, A., Ebrahim, S. B. J., Casas, J. P., & Smith, G. D. (2015) · PLoS ONE · doi:10.1371/journal.pone.0115446 · Cited by 4 · see citing works
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Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians
Davies, N. M., Holmes, M. V., & Davey Smith, G. (2018) · BMJ · doi:10.1136/bmj.k601 · Cited by 4,404 · see citing works
Self-citationMendelian randomization for cardiovascular diseases: Principles and applications
Larsson, S. C., Butterworth, A. S., & Burgess, S. (2023) · European Heart Journal · doi:10.1093/eurheartj/ehad736 · Cited by 735 · see citing works
“48 In a recent meta-analysis of MR studies, genetically predicted higher BMI was associated with an increased risk of all 14 studied CVDs. 46 56 Mendelian randomization studies have provided evidence that higher fasting insulin, fasting glucose, or glycated haemoglobin levels are causally…”
Mendelian randomization in cardiometabolic disease: challenges in evaluating causality
Holmes, M. V., Ala-Korpela, M., & Smith, G. D. (2017) · Nature Reviews Cardiology · doi:10.1038/nrcardio.2017.78 · Cited by 679 · see citing works
Self-citationCauses, consequences, and treatment of metabolically unhealthy fat distribution
Stefan, N. (2020) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(20)30110-8 · Cited by 548 · see citing works
The role of adipose tissue in cardiovascular health and disease
Oikonomou, E. K., & Antoniades, C. A. (2018) · Nature Reviews Cardiology · doi:10.1038/s41569-018-0097-6 · Cited by 509 · see citing works
Lifestyle, cardiometabolic disease, and multimorbidity in a prospective Chinese study
Han, Y., Hu, Y., Yu, C., Guo, Y., Pei, P., Yang, L., Chen, Y., Du, H., Sun, D., Pang, Y., et al. (2021) · European Heart Journal · doi:10.1093/eurheartj/ehab413 · Cited by 480 · see citing works
Larsson, S. C., Bäck, M., Rees, J. M. B., Mason, A. M., & Burgess, S. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehz388 · Cited by 436 · see citing works
“Genetically predicted BMI was shown to be strongly associated with arterial hypertension as well as systolic and diastolic blood pressure in a previous MR study.(4) A strong positive association between BMI and arterial hypertension was also observed in the present MR study.”
BackgroundObesity and loss of disease-free years owing to major non-communicable diseases: a multicohort study
Nyberg, S. T., Batty, G. D., Pentti, J., Virtanen, M., Alfredsson, L. S., Fransson, E. I., Goldberg, M., Heikkilä, K., Jokela, M. M., Knutsson, A., et al. (2018) · The Lancet Public Health · doi:10.1016/s2468-2667(18)30139-7 · Cited by 393 · see citing works
Association Between Obesity and Cardiovascular Outcomes
Riaz, H., Khan, M. S., Siddiqi, T. J., Usman, M., Shah, N. P., Goyal, A., Khan, S. S., Mookadam, F., Krasuski, R. A., & Ahmed, H. M. (2018) · JAMA Network Open · doi:10.1001/jamanetworkopen.2018.3788 · Cited by 359 · see citing works
Obesity phenotypes and their paradoxical association with cardiovascular diseases
Vecchié, A., Dallegri, F., Carbone, F., Bonaventura, A., Liberale, L., Portincasa, P., Frühbeck, G., & Montecucco, F. (2017) · European Journal of Internal Medicine · doi:10.1016/j.ejim.2017.10.020 · Cited by 332 · see citing works
Diagnosis of obesity and use of obesity biomarkers in science and clinical medicine
Nimptsch, K., Konigorski, S., & Pischon, T. (2018) · Metabolism · doi:10.1016/j.metabol.2018.12.006 · Cited by 317 · see citing works
Lotta, L. A., Wittemans, L. B. L., Zuber, V., Stewart, I. D., Sharp, S. J., Luan, J., Day, F. R., Li, C., Bowker, N., Cai, L., et al. (2018) · JAMA · doi:10.1001/jama.2018.19329 · Cited by 229 · see citing works
“Stage 1 included data from participants of European ancestry in the UK Biobank study and summary statistics from previously published GWAS of the Genetic Investigation of Anthropometric Traits (GIANT) Consortium.16 In stage 2, general, hip-, and waist-specific polygenic scores for higher WHR were derived using 202 gen…”
BackgroundMethodInfluentialBiomarkers for type 2 diabetes
Laakso, M. (2019) · Molecular Metabolism · doi:10.1016/j.molmet.2019.06.016 · Cited by 225 · see citing works
Causal relationships between obesity and the leading causes of death in women and men
Censin, J. C., Peters, S. A. E., Bovijn, J., Ferreira, T. C., Pulit, S. L., Mägi, R., Mahajan, A., Holmes, M. V., & Lindgren, C. M. (2019) · PLoS Genetics · doi:10.1371/journal.pgen.1008405 · Cited by 204 · see citing works
Self-citationZhao, Q., Chen, Y., Wang, J., & Small, D. S. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyz142 · Cited by 188 · see citing works
Stroke genetics: discovery, biology, and clinical applications
Dichgans, M., Pulit, S. L., & Rosand, J. M. (2019) · The Lancet Neurology · doi:10.1016/s1474-4422(19)30043-2 · Cited by 184 · see citing works
Holmes, M. V., Richardson, T. G., Ference, B. A., Davies, N. M., & Davey Smith, G. (2021) · Nature Reviews Cardiology · doi:10.1038/s41569-020-00493-1 · Cited by 184 · see citing works
Self-citationWang, Q., Holmes, M. V., Smith, G. D., & Ala‐Korpela, M. (2017) · Diabetes Care · doi:10.2337/dc17-1642 · Cited by 184 · see citing works
Self-citationGenomics and phenomics of body mass index reveals a complex disease network
Huang, J., Huffman, J. E., Huang, Y., Do Valle, Í., Assimes, T. L., Raghavan, S., Voight, B. F., Liu, C., Barabási, A.-L., Huang, R. D. L., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-35553-2 · Cited by 170 · see citing works
Associations of Body Mass and Fat Indexes With Cardiometabolic Traits
Bell, J. A., Carslake, D., O’Keeffe, L. M., Frysz, M., Howe, L. D., Hamer, M., Wade, K. H., Timpson, N. J., & Smith, G. D. (2018) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2018.09.066 · Cited by 166 · see citing works
Vasan, S. K., Osmond, C., Canoy, D., Christodoulides, C., Neville, M. J., Gravio, C. D., Fall, C. H. D., & Karpe, F. (2017) · International Journal of Obesity · doi:10.1038/ijo.2017.289 · Cited by 164 · see citing works
Farmer, R. E., Mathur, R., Schmidt, A. F., Bhaskaran, K., Fatemifar, G., Eastwood, S. V., Finan, C., Denaxas, S., Smeeth, L., & Chaturvedi, N. (2019) · Journal of the American Heart Association · doi:10.1161/jaha.118.011638 · Cited by 144 · see citing works
Self-citationMendelian Randomization Study of Obesity and Cerebrovascular Disease
Marini, S., Merino, J., Montgomery, B. E., Malik, R., Sudlow, C. L. M., Dichgans, M., Florez, J. C., Rosand, J. M., Gill, D., & Anderson, C. D. (2020) · Annals of Neurology · doi:10.1002/ana.25686 · Cited by 152 · see citing works
Biological and functional multimorbidity—from mechanisms to management
Langenberg, C., Hingorani, A. D., & Whitty, C. W. M. (2023) · Nature Medicine · doi:10.1038/s41591-023-02420-6 · Cited by 152 · see citing works
Self-citationGenomic insights into the causes of type 2 diabetes
Langenberg, C., & Lotta, L. A. (2018) · The Lancet · doi:10.1016/s0140-6736(18)31132-2 · Cited by 142 · see citing works
Posttraumatic Stress Disorder and Cardiovascular Disease
O’Donnell, C. J., Longacre, L. S., Cohen, B. E., Fayad, Z. A., Gillespie, C. F., Liberzon, I., Pathak, G. A., Polimanti, R. A., Risbrough, V. B., Ursano, R. J., et al. (2021) · JAMA Cardiology · doi:10.1001/jamacardio.2021.2530 · Cited by 142 · see citing works
Loos, R. J. F. (2018) · Current Opinion in Genetics & Development · doi:10.1016/j.gde.2018.02.009 · Cited by 127 · see citing works
Transforming obesity: The advancement of multi-receptor drugs
Kusminski, C. M., Perez-Tilve, D., Müller, T. D., DiMarchi, R. D., Tschöp, M. H., & Scherer, P. E. (2024) · Cell · doi:10.1016/j.cell.2024.06.003 · Cited by 126 · see citing works
Hartwig, F. P., Tilling, K. M., Smith, G. D., Lawlor, D. A., & Borges, M. C. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyaa266 · Cited by 116 · see citing works
Self-citationGenetics Insights in the Relationship Between Type 2 Diabetes and Coronary Heart Disease
Goodarzi, M. O., & Rotter, J. I. (2020) · Circulation Research · doi:10.1161/circresaha.119.316065 · Cited by 117 · see citing works
Bovijn, J., Krebs, K., Chen, C.-Y., Boxall, R., Censin, J. C., Ferreira, T., Pulit, S. L., Glastonbury, C. A., Laber, S., Millwood, I. Y., et al. (2020) · Science Translational Medicine · doi:10.1126/scitranslmed.aay6570 · Cited by 119 · see citing works
Self-citationGeng, T., Smith, C. E., Li, C., & Huang, T. (2018) · Diabetes Care · doi:10.2337/dc17-2141 · Cited by 121 · see citing works
“Recently, MR analyses have demonstrated that both adult general and central obesity have causal effects on CAD, type 2 diabetes, and cardiometabolic traits in midlife (10,11).”
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Lumish, H. S., O'Reilly, M. E., & Reilly, M. P. (2019) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.119.313154 · Cited by 118 · see citing works
Associations of General and Central Adiposity With Incident Diabetes in Chinese Men and Women
Bragg, F., Tang, K., Yu, C., Iona, A., Du, H., Holmes, M. V., Bian, Z., Kartsonaki, C., Chen, Y., Yang, L., et al. (2018) · Diabetes Care · doi:10.2337/dc17-1852 · Cited by 106 · see citing works
“Adiposity is an established causal risk factor for type 2 diabetes (6,7).”
BackgroundSelf-citationB Lymphocytes and Adipose Tissue Inflammation
Srikakulapu, P., & McNamara, C. A. (2020) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.119.312467 · Cited by 106 · see citing works
Genetics of coronary artery disease in the post‐GWAS era
Chen, Z., & Schunkert, H. (2021) · Journal of Internal Medicine · doi:10.1111/joim.13362 · Cited by 106 · see citing works
On the utilization of polygenic risk scores for therapeutic targeting
Gibson, G. C. (2019) · PLoS Genetics · doi:10.1371/journal.pgen.1008060 · Cited by 101 · see citing works
“…a polygenic risk score genetic instrument explaining ~2% of BMI indicate that a one standard deviation unit increase (~ 5 kg/m 2 ) causally doubles the risk of type 2 diabetes [34], and similar results are seen in the DIAGRAM study [35] for WHR with an independent PRS explaining ~1% of the trait.”
Genetics of common cerebral small vessel disease
Bordes, C., Sargurupremraj, M., Mishra, A., & Debette, S. (2022) · Nature Reviews Neurology · doi:10.1038/s41582-021-00592-8 · Cited by 101 · see citing works
Adipose group 1 innate lymphoid cells promote adipose tissue fibrosis and diabetes in obesity
Wang, H., Shen, L., Sun, X., Liu, F., Feng, W., Jiang, C., Chu, X., Ye, X., Jiang, C., Wang, Y., et al. (2019) · Nature Communications · doi:10.1038/s41467-019-11270-1 · Cited by 98 · see citing works
Liu, X., Bragg, F., Yang, L., Kartsonaki, C., Guo, Y., Du, H., Bian, Z., Chen, Y., Yu, C., Lv, J., et al. (2018) · The Lancet Public Health · doi:10.1016/s2468-2667(18)30026-4 · Cited by 94 · see citing works
Periodontitis and metabolic diseases (diabetes and obesity): Tackling multimorbidity
Marruganti, C., Suvan, J. E., & D’Aiuto, F. (2023) · Periodontology 2000 · doi:10.1111/prd.12536 · Cited by 96 · see citing works
Effects of Type II Diabetes Mellitus on Tendon Homeostasis and Healing
Nichols, A. E. C., Oh, I. C., & Loiselle, A. E. (2019) · Journal of Orthopaedic Research® · doi:10.1002/jor.24388 · Cited by 89 · see citing works
“Increased adiposity (abdominal fat in particular) is thought to be one of the major underlying causes of T2DM through its contribution to aberrant endocrine function and elevated secretion of pro‐inflammatory cytokines.(5) T2DM is characterized by systemic metabolic dysfunction including dyslipidemia and elevated plas…”
BackgroundBMI and Mortality in UK Biobank: Revised Estimates Using Mendelian Randomization
Wade, K. H., Carslake, D., Sattar, N. A., Smith, G. D., & Timpson, N. J. (2018) · Obesity · doi:10.1002/oby.22313 · Cited by 84 · see citing works
Self-citationGenetics of Type 2 Diabetes: Past, Present, and Future
Laakso, M., & Silva, L. F. (2022) · Nutrients · doi:10.3390/nu14153201 · Cited by 89 · see citing works
“MR studies have confirmed that obesity [85] and the waist/hip ratio [86] are causal for the risk of T2D.”
BackgroundAssessing the Causal Role of Body Mass Index on Cardiovascular Health in Young Adults
Wade, K. H., Chiesa, S. T., Hughes, A. D., Chaturvedi, N., Charakida, M., Rapala, A., Muthurangu, V., Khan, T. A., Finer, N., Sattar, N. A., et al. (2018) · Circulation · doi:10.1161/circulationaha.117.033278 · Cited by 83 · see citing works
Self-citationMallah, M. A., Ali, M., Liu, Y., He, X., Wang, W., Feng, F., & Zhang, Q. (2021) · Frontiers in Public Health · doi:10.3389/fpubh.2021.763706 · Cited by 79 · see citing works
Golubnitschaja, O., Polívka, J., Potužník, P., Pešta, M., Štětkářová, I., Mazuráková, A., Lacková, L., Kubatka, P., Kropp, M., Thumann, G., et al. (2024) · The EPMA Journal · doi:10.1007/s13167-024-00356-6 · Cited by 73 · see citing works
Goudswaard, L. J., Bell, J. A., Hughes, D. A., Corbin, L. J., Walter, K., Smith, G. D., Soranzo, N., Danesh, J., Angelantonio, E. D., Ouwehand, W. H., et al. (2021) · International Journal of Obesity · doi:10.1038/s41366-021-00896-1 · Cited by 72 · see citing works
Childhood Obesity and Risk of Stroke: A Mendelian Randomisation Analysis
Zou, X., Wang, S., Wang, L., Xiao, L., Yao, T., Zeng, Y., & Zhang, L. (2021) · Frontiers in Genetics · doi:10.3389/fgene.2021.727475 · Cited by 65 · see citing works
“Current MR studies (Dale et al., 2017; Larsson et al., 2020), which focused on adult obesity and stroke, showed that adult obesity was not associated with stroke, suggesting that childhood and adult obesity may influence stroke in different pathways.”
BackgroundCirculating vitamin E levels and Alzheimer's disease: a Mendelian randomization study
Liu, G., Zhao, Y., Jin, S., Hu, Y., Wang, T., Tian, R., Han, Z., Xu, D., & Jiang, Q. (2018) · Neurobiology of Aging · doi:10.1016/j.neurobiolaging.2018.08.008 · Cited by 62 · see citing works
Richardson, T. G., Wang, Q., Sanderson, E. C. M., Mahajan, A., McCarthy, M. I., Frayling, T. M., Ala‐Korpela, M., Sniderman, A. D., Smith, G. D., & Holmes, M. V. (2021) · The Lancet Healthy Longevity · doi:10.1016/s2666-7568(21)00086-6 · Cited by 61 · see citing works
Self-citationBoth lean and fat body mass associate with blood pressure
Korhonen, P. E., Mikkola, T. M., Kautiainen, H., & Eriksson, J. G. (2021) · European Journal of Internal Medicine · doi:10.1016/j.ejim.2021.04.025 · Cited by 59 · see citing works
Surowiec, I., Noordam, R., Bennett, K., Beekman, M., Slagboom, P. E., Lundstedt, T., & van Heemst, D. (2019) · Metabolomics · doi:10.1007/s11306-019-1484-7 · Cited by 59 · see citing works
Self-citationMallah, M. A., Li, C., Mallah, M. A., Naveed, M., Liu, Y., Noreen, S., He, X., Wang, W., Feng, F., & Zhang, Q. (2022) · Environmental Research · doi:10.1016/j.envres.2022.112775 · Cited by 58 · see citing works
Rare loss of function variants in the hepatokine gene INHBE protect from abdominal obesity
Deaton, A. M., Dubey, A., Ward, L. D., Dornbos, P., Flannick, J. A., Yee, E., Ticau, S., Noetzli, L. J., Parker, M. M., Hoffing, R. A., et al. (2022) · Nature Communications · doi:10.1038/s41467-022-31757-8 · Cited by 58 · see citing works
Lane, M. M., Travica, N., Gamage, E., Marshall, S., Trakman, G., Young, C., Teasdale, S. B., Dissanayaka, T. D., Dawson, S. L., Orr, R., et al. (2024) · Annual Review of Nutrition · doi:10.1146/annurev-nutr-062322-020650 · Cited by 55 · see citing works
Polygenic prediction of body mass index and obesity through the life course and across ancestries
Smit, R. A. J., Wade, K. H., Hui, Q., Arias, J. D., Yin, X., Christiansen, M. R., Yengo, L., Preuss, M. H., Nakabuye, M., Rocheleau, G., et al. (2025) · Nature Medicine · doi:10.1038/s41591-025-03827-z · Cited by 54 · see citing works
Self-citationBrouwers, M. C. G. J., Simons, N., Stehouwer, C. D. A., Koek, G. H., Schaper, N. C., & Isaacs, A. J. (2019) · Hepatology Communications · doi:10.1002/hep4.1319 · Cited by 53 · see citing works
Yin, W., Hou, J., Xu, T., Cheng, J., Li, P., Lin, W., Zhang, Y., Wang, X., Hu, C., Huang, C., et al. (2017) · The Science of The Total Environment · doi:10.1016/j.scitotenv.2017.10.238 · Cited by 52 · see citing works
Wang, L., Qiao, Y., Zhang, H., Zhang, Y., Hua, J., Jin, S., & Liu, G. (2019) · Journal of Alzheimer s Disease · doi:10.3233/jad-190713 · Cited by 51 · see citing works
“cept test to assess the presence of potential pleiotropy 174 [28], and Mendelian randomization pleiotropy resid175 ual sum and outlier (MR-PRESSO) test to identify 176 the horizontal pleiotropic outliers [29].”
BackgroundGuan, B., Wang, A., & Xu, H. (2023) · Cardiovascular Diabetology · doi:10.1186/s12933-023-01927-z · Cited by 50 · see citing works
“CMD is of particular interest because of the widespread epidemics of T2D, NAFLD, obesity, and CKD, which are associated with a significant increase in the CVDs prevalence in the context of genetic predisposition [26–28].”
BackgroundTynkkynen, T., Wang, Q., Ekholm, J., Anufrieva, O., Ohukainen, P., Vepsäläinen, J., Männikkö, M., Keinanen-Kiukaanniemi, S. M., Holmes, M. V., Goodwin, M., et al. (2018) · International Journal of Epidemiology · doi:10.1093/ije/dyy287 · Cited by 48 · see citing works
Self-citationBell, J. A., Richardson, T. G., Wang, Q., Sanderson, E. C. M., Palmer, T., Walker, V. M., O’Keeffe, L. M., Timpson, N. J., Cichońska, A., Julkunen, H., et al. (2022) · The Lancet Regional Health - Europe · doi:10.1016/j.lanepe.2022.100457 · Cited by 47 · see citing works
Self-citationAdipocyte Fatty Acid-Binding Protein, Cardiovascular Diseases and Mortality
Lee, C., Lui, D. T. W., & Lam, K. S. L. (2021) · Frontiers in Immunology · doi:10.3389/fimmu.2021.589206 · Cited by 47 · see citing works
Adipocyte GPX4 protects against inflammation, hepatic insulin resistance and metabolic dysregulation
Schwärzler, J., Mayr, L., Radlinger, B., Grabherr, F., Philipp, M., Texler, B., Grander, C., Ritsch, A., Hunjadi, M., Enrich, B., et al. (2022) · International Journal of Obesity · doi:10.1038/s41366-022-01064-9 · Cited by 46 · see citing works
“These diseases afflict substantial morbidity and mortality to individuals, which is strongly conferred by cardiovascular complications [1, 2].”
BackgroundHealthy lifestyle and life expectancy free of major chronic diseases at age 40 in China
The China Kadoorie Biobank Collaborative Group, Sun, Q., Hu, Y., Yu, C., Guo, Y., Pei, P., Yang, L., Chen, Y., Du, H., Sun, D., et al. (2023) · Nature Human Behaviour · doi:10.1038/s41562-023-01624-7 · Cited by 46 · see citing works
“Fourth, the conclusion of this study was based on the premise that lifestyle factors have a causal association with the disease of interest, which, however, could not be inferred from the present study but supported by evidence from other Mendelian randomization studies 24–26 .”
Parkinson’s disease and Alzheimer’s disease: a Mendelian randomization study
Han, Z., Tian, R., Ren, P., Zhou, W., Wang, P., Luo, M., Jin, S., & Jiang, Q. (2018) · BMC Medical Genetics · doi:10.1186/s12881-018-0721-7 · Cited by 46 · see citing works
“MR-Egger could also provide a statistical test the presence of potential pleiotropy, and account for this potential pleiotropy [31].”
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 · see citing works
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 44 · see citing works
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 · see citing works
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 · see citing works
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 · see citing works
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 43 · see citing works
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 · see citing works
“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 · see citing works
Xu, H., Jin, C., & Guan, Q.-B. (2020) · Frontiers in Genetics · doi:10.3389/fgene.2020.00603 · Cited by 43 · see citing works
Yuan, S., Merino, J., & Larsson, S. C. (2023) · Diabetologia · doi:10.1007/s00125-023-05879-7 · Cited by 41 · see citing works
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 40 · see citing works
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 39 · see citing works
Multivariable MR Can Mitigate Bias in Two‐Sample MR Using Covariable‐Adjusted Summary Associations
Gilbody, J., Borges, M. C., Smith, G. D., & Sanderson, E. C. M. (2025) · Genetic Epidemiology · doi:10.1002/gepi.22606 · Cited by 37 · see citing works
Blood-brain barrier pathology in cerebral small vessel disease
Jia, R., Guardia, G. S., & Kiliaan, A. J. (2023) · Neural Regeneration Research · doi:10.4103/1673-5374.385864 · Cited by 38 · see citing works
“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 35 · see citing works
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 35 · see citing works
The “Common Soil Hypothesis” Revisited—Risk Factors for Type 2 Diabetes and Cardiovascular Disease
Silva, L. F., Vangipurapu, J., & Laakso, M. (2021) · Metabolites · doi:10.3390/metabo11100691 · Cited by 36 · see citing works
“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 · see citing works
Self-citationVerkouter, I., Noordam, R., le Cessie, S., van Dam, R. M., Lamb, H. J., Rosendaal, F. R., van Heemst, D., & de Mutsert, R. (2019) · Journal of Clinical Medicine · doi:10.3390/jcm8101559 · Cited by 33 · see citing works
Self-citationGao, X., Jia, Z.-M., Zhao, F., An, D., Wang, B., Cheng, E., Chen, Y., Gong, J., Liu, D., Huang, Y., et al. (2020) · Aging · doi:10.18632/aging.102725 · Cited by 33 · see citing works
Huang, S.-Y., Yang, Y., Chen, S., Li, H.-Q., Zhang, X.-Q., Kuo, K., Tan, L., Feng, L., Dong, Q., Zhang, C. M., et al. (2021) · BMC Medicine · doi:10.1186/s12916-021-02030-4 · Cited by 33 · see citing works
Wang, C., Sun, Y., Jiang, D., Wang, C., & Liu, S. (2021) · Journal of the American Heart Association · doi:10.1161/jaha.121.021024 · Cited by 34 · see citing works
Obesity and the Risk of Cryptogenic Ischemic Stroke in Young Adults
Jaakonmäki, N., Zedde, M., Sarkanen, T., Martinez‐Majander, N., TUOHINEN, S. S., Sinisalo, J. P., Ryödi, E., Autere, J. M., Hedman, M., Junttola, U., et al. (2022) · Journal of Stroke and Cerebrovascular Diseases · doi:10.1016/j.jstrokecerebrovasdis.2022.106380 · Cited by 33 · see citing works
Cheng, S., Han, Y., Jiang, L., Lan, Z., Liao, H., & Guo, J. (2023) · BMJ Open · doi:10.1136/bmjopen-2023-072334 · Cited by 31 · see citing works
Sletner, L., Mahon, P. A., Crozier, S., Inskip, H. M., Godfrey, K. M., Chiesa, S. T., Bhowruth, D. J., Charakida, M., Deanfield, J. E., Cooper, C. C., et al. (2018) · Arteriosclerosis Thrombosis and Vascular Biology · doi:10.1161/atvbaha.118.311455 · Cited by 31 · see citing works
Ferguson, L. D., Brown, R., Celis-Morales, C. A., Welsh, P. I., Lyall, D. M., Pell, J. P., McInnes, I. B., Siebert, S., & Sattar, N. A. (2019) · Lara D. Veeken · doi:10.1093/rheumatology/kez192 · Cited by 30 · see citing works
Self-citationNoordam, R., Läll, K., Smit, R. A. J., Laisk, T., Metspalu, A., Esko, T., Milani, L. A., Loos, R. J. F., Mägi, R., van Dijk, K. W., et al. (2021) · Diabetes · doi:10.2337/db20-0602 · Cited by 30 · see citing works
Self-citationThe diverse roles of macrophages in metabolic inflammation and its resolution
Guha-Ray, A., Odum, O., Wiseman, D., & Weinstock, A. (2023) · Frontiers in Cell and Developmental Biology · doi:10.3389/fcell.2023.1147434 · Cited by 29 · see citing works
“The increase in the prevalence of type 2 diabetes is not surprising, since obesity is one of its major causes (Dale et al., 2017).”
BackgroundBos, M. M., Noordam, R., van den Berg, R., de Mutsert, R., Rosendaal, F. R., Blauw, G. J., Rensen, P. C. N., Biermasz, N. R., & van Heemst, D. (2018) · Journal of Sleep Research · doi:10.1111/jsr.12776 · Cited by 28 · see citing works
“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”
BackgroundSelf-citationMendelian randomization studies on atherosclerotic cardiovascular disease: evidence and limitations
Hu, Q., Hao, P., Liu, Q., Dong, M., Gong, Y., Zhang, C., & Zhang, Y. (2019) · Science China Life Sciences · doi:10.1007/s11427-019-9537-4 · Cited by 30 · see citing works
Stroke in the patient with diabetes (part 1) – Epidemiology, etiology, therapy and prognosis
Bell, D. S. H., & Gonçalves, E. (2020) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2020.108193 · Cited by 29 · see citing works
Dam, V., Onland‐Moret, N. C., Burgess, S., Chirlaque, M., Peters, S. A. E., Schuit, E., Tikk, K., Weiderpass, E., Oliver‐Williams, C., Wood, A., et al. (2022) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgac171 · Cited by 28 · see citing works
“When unbalanced horizontal pleiotropy is absent, results of all methods are expected to be consistent (27).”
Goudswaard, L. J., Corbin, L. J., Burley, K., Mumford, A. D., Akbari, P., Soranzo, N., Butterworth, A. S., Watkins, N. A., Pournaras, D. J., Harris, J. M., et al. (2022) · Platelets · doi:10.1080/09537104.2021.2003317 · Cited by 28 · see citing works
- 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
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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