Genetic evidence strongly supports managing weight and blood pressure in addition to glycemic control in preventing vascular complications in people with type 2 diabetes
Open accessAbstract
OBJECTIVE: To investigate the causal association of type 2 diabetes and its components with risk of vascular complications independent of shared risk factors obesity and hypertension and to identify the main driver of this risk. RESEARCH DESIGN AND METHODS: We conducted Mendelian randomization (MR) using independent genetic variants previously associated with type 2 diabetes, fasting glucose, HbA1c, fasting insulin, BMI, and systolic blood pressure as instrumental variables. We obtained summary-level data for 18 vascular diseases (15 for type 2 diabetes) from FinnGen and publicly available genome-wide association studies as our outcomes. We conducted univariable and multivariable MR, in addition to sensitivity tests to detect and minimize pleiotropic effects. RESULTS: Univariable MR analysis showed that type 2 diabetes was associated with 9 of 15 outcomes; BMI and systolic blood pressure were associated with 13 and 15 of 18 vascular outcomes, respectively; and fasting insulin was associated with 4 and fasting glucose with 2. No robust association was found for HbA1c instruments. With adjustment for correlated traits in the multivariable test, BMI and systolic blood pressure, consistent causal effects were maintained, while five associations with type 2 diabetes (chronic kidney disease, ischemic heart disease, heart failure, subarachnoid hemorrhage, and intracerebral hemorrhage) were attenuated to null. CONCLUSIONS: Our findings add strong evidence to support the importance of BMI and systolic blood pressure in the development of vascular complications in people with type 2 diabetes. Such findings strongly support the need for better weight and blood pressure management in type 2 diabetes, independent of glucose lowering, to limit important complications.
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Additional evidence confirms that obesity is a contributing factor for type 2 diabetes, hypertension, and thrombotic episodes, as well as conditions linked to inflammation such as heart failure with preserved ejection fraction.
“Additional evi dence confirms that obesity is a contributing factor for type 2 diabetes, hypertension, and thrombotic ep isodes, as well as conditions linked to inflammation such as heart failure with preserved ejection frac tion. 2-7”
From Comprehensive Long-Term Changes in Cardiovascular Risk Biomarkers With Tirzepatide (2026) · cites this paper as [3]
The Introduction (page unavailable) identifies excess adiposity as an upstream factor in type 2 diabetes, and the vascular-complications results link higher BMI to several outcomes. The paper also discusses heart failure and pulmonary embolism, but the passages do not establish obesity as a cause of hypertension or thrombotic episodes generally, and they do not address inflammation or heart failure with preserved ejection fraction specifically. (LLM, conf=0.85)
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Cites
The MR-Base platform supports systematic causal inference across the human phenome
Hemani, G., Zheng, J., Elsworth, B., Wade, K. H., Haberland, V., Baird, D., Laurin, C., Burgess, S., Bowden, J., Langdon, R., et al. (2018) · eLife · doi:10.7554/elife.34408 · Cited by 7,959 · see citing works
Global aetiology and epidemiology of type 2 diabetes mellitus and its complications
Zheng, Y., Ley, S. H., & Hu, F. B. (2018) · Nature Reviews Endocrinology · doi:10.1038/nrendo.2017.151 · Cited by 5,697 · see citing works
Sanderson, E., Glymour, M. M., Holmes, M. V., Kang, H., Morrison, J., Munafò, M. R., Palmer, T., Schooling, C. M., Wallace, C., Zhao, Q., et al. (2022) · Nature Reviews Methods Primers · doi:10.1038/s43586-021-00092-5 · Cited by 2,229 · see citing works
Basal insulin and cardiovascular and other outcomes in dysglycemia
The ORIGIN Trial Investigators (2012) · New England Journal of Medicine · doi:10.1056/nejmoa1203858 · Cited by 1,636 · see citing works
Malik, R., Chauhan, G., Traylor, M., Sargurupremraj, M., Okada, Y., Mishra, A., Rutten‐Jacobs, L. C. A., Giese, A., van der Laan, S. W., Grétarsdóttir, S., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0058-3 · Cited by 1,566 · see citing works
Ray, K. K., Seshasai, S. R. K., Wijesuriya, S., Sivakumaran, R., Nethercott, S., Preiss, D., Erqou, S., & Sattar, N. (2009) · The Lancet · doi:10.1016/s0140-6736(09)60697-8 · Cited by 1,383 · see citing works
Self-citationProgram, T. M. V., Evangelou, E., Warren, H. R., Mosen-Ansorena, D., Mifsud, B., Pazoki, R., Gao, H., Ntritsos, G., Dimou, N., Cabrera, C. P., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0205-x · Cited by 1,381 · see citing works
Pulit, S. L., Harlow, C. E., Morris, A. P., Wood, A. R., Glastonbury, C. A., Tyrrell, J., Yengo, L., Ferreira, T. C., Marouli, E., Ji, Y., et al. (2018) · Human Molecular Genetics · doi:10.1093/hmg/ddy327 · Cited by 1,169 · see citing works
Self-citationvan der Harst, P., & Verweij, N. (2018) · Circulation Research · doi:10.1161/circresaha.117.312086 · Cited by 1,141 · see citing works
Sanderson, E., Davey Smith, G., Windmeijer, F., & Bowden, J. (2019) · International Journal of Epidemiology · doi:10.1093/ije/dyy262 · Cited by 1,085 · see citing works
Biobank-driven genomic discovery yields new insight into atrial fibrillation biology
Nielsen, J. B., Thorolfsdottir, R. B., Fritsche, L. G., Zhou, W., Skov, M. W., Graham, S. E., Herron, T. J., McCarthy, S., Schmidt, E. M., Sveinbjornsson, G., et al. (2018) · Nature Genetics · doi:10.1038/s41588-018-0171-3 · Cited by 876 · see citing works
Shah, S. H., Henry, A., Roselli, C., Lin, H., Sveinbjörnsson, G., Fatemifar, G., Hedman, Å. K., Wilk, J. B., Morley, M. P., Chaffin, M. D., et al. (2020) · Nature Communications · doi:10.1038/s41467-019-13690-5 · Cited by 832 · see citing works
The trans-ancestral genomic architecture of glycemic traits
Chen, J., Spracklen, C. N., Marenne, G., Varshney, A., Corbin, L. J., Luan, J., Willems, S. M., Wu, Y., Zhang, X., Horikoshi, M., et al. (2021) · Nature Genetics · doi:10.1038/s41588-021-00852-9 · Cited by 798 · see citing works
Diabetes and hypertension: a position statement by the American Diabetes Association
de Boer, I. H., Bangalore, S., Benetos, A., Davis, A. M., Michos, E. D., Muntner, P., Rossing, P., Zoungas, S., & Bakris, G. (2017) · Diabetes Care · doi:10.2337/dci17-0026 · Cited by 714 · see citing works
Mahajan, A., Spracklen, C. N., Zhang, W., Ng, M. C. Y., Petty, L. E., Kitajima, H., Yu, G. Z., Rüeger, S., Speidel, L., Kim, Y. J., et al. (2022) · Nature Genetics · doi:10.1038/s41588-022-01058-3 · Cited by 704 · see citing works
Self-citationMingrone, G., Panunzi, S., De Gaetano, A., Guidone, C., Iaconelli, A., Capristo, E., Chamseddine, G., Bornstein, S. R., & Rubino, F. (2021) · The Lancet · doi:10.1016/s0140-6736(20)32649-0 · Cited by 577 · see citing works
Zoungas, S., Arima, H., Gerstein, H. C., Holman, R. R., Woodward, M., Reaven, P., Hayward, R. A., Craven, T., Coleman, R. L., & Chalmers, J. (2017) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(17)30104-3 · Cited by 529 · see citing works
Pattaro, C., Teumer, A., Gorski, M., Chu, A. Y., Li, M., Mijatovic, V., Garnaas, M., Tin, A., Sorice, R., Li, Y., et al. (2016) · Nature Communications · doi:10.1038/ncomms10023 · Cited by 514 · 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
Understanding the mechanisms of reversal of type 2 diabetes
Taylor, R., Al-Mrabeh, A., & Sattar, N. (2019) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(19)30076-2 · Cited by 299 · see citing works
Self-citationLitwak, L., Goh, S., Hussein, Z. B., Malek, R., Prusty, V., & Khamseh, M. E. (2013) · Diabetology & Metabolic Syndrome · doi:10.1186/1758-5996-5-57 · Cited by 284 · see citing works
Genome-wide analysis identifies novel susceptibility loci for myocardial infarction
Hartiala, J., Han, Y. Y., Jia, Q., Hilser, J. R., Huang, P., Gukasyan, J., Schwartzman, W. S., Cai, Z., Biswas, S., Trégouët, D., et al. (2020) · European Heart Journal · doi:10.1093/eurheartj/ehaa1040 · Cited by 272 · see citing works
Usual Blood Pressure and Risk of New-Onset Diabetes
Emdin, C. A., Anderson, S. G., Woodward, M., & Rahimi, K. (2015) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2015.07.059 · Cited by 216 · see citing works
Sex-dimorphic genetic effects and novel loci for fasting glucose and insulin variability
Lagou, V., Mägi, R., Hottenga, J., Grallert, H., Perry, J. R. B., Bouatia‐Naji, N., Marullo, L., Rybin, D. V., Jansen, R., Min, J. L., et al. (2021) · Nature Communications · doi:10.1038/s41467-020-19366-9 · Cited by 154 · see citing works
Zheng, J., Zhang, Y., Rasheed, H., Walker, V. M., Sugawara, Y., Li, J., Leng, Y., Elsworth, B., Wootton, R. E., Fang, S., et al. (2021) · International Journal of Epidemiology · doi:10.1093/ije/dyab203 · Cited by 124 · see citing works
Glycated Hemoglobin, Prediabetes, and the Links to Cardiovascular Disease: Data From UK Biobank
Welsh, C. E., Welsh, P. I., Celis-Morales, C. A., Mark, P. B., Mackay, D., Ghouri, N., Ho, F. K. W., Ferguson, L. D., Brown, R., Lewsey, J., et al. (2019) · Diabetes Care · doi:10.2337/dc19-1683 · Cited by 111 · see citing works
Self-citationBlood Pressure and Risk of Cardiovascular Disease in UK Biobank
Wan, E. Y. F., Fung, W. T., Schooling, C. M., Yeung, S. L. A., Kwok, M. K., Yu, E. Y. T., Wang, Y., Chan, E. W., Wong, I. C. K., & Lam, C. L. K. (2021) · Hypertension · doi:10.1161/hypertensionaha.120.16138 · Cited by 97 · see citing works
Beyond Mendelian randomization: how to interpret evidence of shared genetic predictors
Burgess, S., Butterworth, A. S., & Thompson, J. R. (2015) · Journal of Clinical Epidemiology · doi:10.1016/j.jclinepi.2015.08.001 · Cited by 92 · see citing works
Yokoyama, H., Oishi, M., Takamura, H., Yamasaki, K., Shirabe, S., Uchida, D., Sugimoto, H., Kurihara, Y., Araki, S., & Maegawa, H. (2016) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2016-000294 · Cited by 83 · see citing works
Chen, W., Wang, S., Lv, W., & Pan, Y. (2020) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2020-001217 · Cited by 83 · see citing works
Diabetes Mellitus: Is It Protective against Aneurysm? A Narrative Review
Patel, K., Zafar, M. A., Ziganshin, B. A., et al. (2018) · Cardiology · doi:10.1159/000490373 · Cited by 75 · see citing works
Association between younger age when first overweight and increased risk for CKD.
Silverwood, R., Pierce, M., Thomas, C., Hardy, R., Ferro, C., Sattar, N., Whincup, P., Savage, C. O. S., Kuh, D., & Nitsch, D. (2013) · Journal of the American Society of Nephrology · doi:10.1681/asn.2012070675 · Cited by 66 · see citing works
Self-citationGarfield, V., Salzmann, A., Burgess, S., & Chaturvedi, N. (2023) · Diabetes · doi:10.2337/db22-0110 · Cited by 30 · see citing works
Harati, H., Zanetti, D., Rao, A. S., Gustafsson, S., Perez, M. V., Ingelsson, E., & Knowles, J. W. (2019) · Diabetologia · doi:10.1007/s00125-019-4836-y · Cited by 29 · see citing works
Fasting Glucose Variation Predicts Microvascular Risk in ACCORD and VADT
Zhou, J. J., Koška, J., Bahn, G., & Reaven, P. D. (2020) · The Journal of Clinical Endocrinology & Metabolism · doi:10.1210/clinem/dgaa941 · Cited by 24 · see citing works
Huang, M., Laina-Nicaise, L.-D., Zha, L., Tang, T., & Cheng, X. C. (2022) · Frontiers in Endocrinology · doi:10.3389/fendo.2022.840579 · Cited by 24 · see citing works
Liu, B., Mason, A. M., Sun, L., Angelantonio, E. D., Gill, D., & Burgess, S. (2021) · Genes · doi:10.3390/genes12101644 · Cited by 23 · see citing works
Sattar, N., Deanfield, J., & Delles, C. (2024) · Cardiovascular Research · doi:10.1093/cvr/cvac186 · Cited by 20 · see citing works
Self-citationAhmed, A., Sattar, N., & Yaghootkar, H. (2022) · Diabetic Medicine · doi:10.1111/dme.14982 · Cited by 10 · see citing works
Self-citationMACROVASCULAR AND MICROVASCULAR COMPLICATIONS IN TYPE 2 DIABETES MELLITUS
Dobrică, E.-C., Găman, M., Cozma, M.-A., et al. (2019) · Journal of Hypertension · doi:10.1097/01.hjh.0000571816.00025.b3 · Cited by 5 · see citing works
Guo, Y., Gao, J., Liu, Y., Jia, Y., An, X., Zhang, X., & Su, P. (2023) · Frontiers in Endocrinology · doi:10.3389/fendo.2023.1132298 · Cited by 5 · see citing works
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Comprehensive Long-Term Changes in Cardiovascular Risk Biomarkers With Tirzepatide
Sattar, N., Linetzky, B., Ruotolo, G., Verma, S., Sourij, H., Wang, H., Vanderman, K., Wilson, J. M., Griffin, R. M., Stefanski, A., et al. (2026) · JACC · doi:10.1016/j.jacc.2026.04.044 · Cited by 5 · see citing works
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- Authors
- Ahmed, A., Amin, H., Drenos, F., Sattar, N., & Yaghootkar, H.
- Affiliations
- Brunel University of London (GB)
- University of Glasgow (GB)
- University of Lincoln (GB)
- Corresponding author
- Yaghootkar, Hanieh
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2023-08-09
- Volume
- 46
- Issue
- 10
- Pages
- 1783-1791
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- OpenAlex
- W4385690655
- Cited by
- 10
- References
- 41
- Citations by year
- 2026: 2 · 2024: 8
- FWCI
- 1.66
- Type
- journal article
- Language
- en
- Open access
- green
- bura.brunel.ac.uk
- Locations
- Diabetes Care (publishedVersion)
- PubMed (publishedVersion)
- Lincoln Repository (University of Lincoln) (acceptedVersion)
- Brunel University Research Archive (BURA) (Brunel University London) (submittedVersion)
- Figshare (submittedVersion, cc-by)
- Funders
- British Heart Foundation (RE/18/6/34217)
- Diabetes UK (17/0005594)
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Health Sciences › Medicine › Endocrinology, Diabetes and Metabolism › Diabetes, Cardiovascular Risks, and Lipoproteins
- Health Sciences › Medicine › Cardiology and Cardiovascular Medicine › Blood Pressure and Hypertension Studies
- Keywords
- type 2 diabetes, vascular complications, body mass index, systolic blood pressure, weight management, blood pressure control, glycemic control, fasting insulin, fasting blood glucose, HbA1c, chronic kidney disease, ischemic heart disease, heart failure, subarachnoid hemorrhage, intracerebral hemorrhage, causal relationship, pleiotropy
- MeSH terms
- Glycemic Control, Blood Glucose, Blood Pressure, Cardiovascular Diseases, Diabetes Mellitus, Type 2, Glycated Hemoglobin, Humans, Insulin, Risk Factors, Body Mass Index, Polymorphism, Single Nucleotide, Genome-Wide Association Study, Mendelian Randomization Analysis
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