Impact of glucose level on micro- and macrovascular disease in the general population: a Mendelian randomization study
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OBJECTIVE: To evaluate whether high glucose levels in the normoglycemic range and higher have a causal genetic effect on risk of retinopathy, neuropathy, nephropathy, chronic kidney disease (CKD), peripheral arterial disease (PAD), and myocardial infarction (MI; positive control) in the general population. RESEARCH DESIGN AND METHODS: This study applied observational and one-sample Mendelian randomization (MR) analyses to individual-level data from 117,193 Danish individuals, and validation by two-sample MR analyses on summary-level data from 133,010 individuals from the Meta-Analyses of Glucose and Insulin-Related Traits Consortium (MAGIC), 117,165 from the CKDGen Consortium, and 452,264 from the UK Biobank. RESULTS: Observationally, glucose levels in the normoglycemic range and higher were associated with high risks of retinopathy, neuropathy, diabetic nephropathy, PAD, and MI (all P for trend <0.001). In genetic causal analyses, the risk ratio for a 1 mmol/L higher glucose level was 2.01 (95% CI 1.18–3.41) for retinopathy, 2.15 (1.38–3.35) for neuropathy, 1.58 (1.04–2.40) for diabetic nephropathy, 0.97 (0.84–1.12) for estimated glomerular filtration rate (eGFR) <60 mL/min/1.73 m2, 1.19 (0.90–1.58) for PAD, and 1.49 (1.02–2.17) for MI. Summary-level data from the MAGIC, the CKDGen Consortium, and the UK Biobank gave a genetic risk ratio of 4.55 (95% CI 2.26–9.15) for retinopathy, 1.48 (0.83–2.66) for peripheral neuropathy, 0.98 (0.94–1.01) for eGFR <60 mL/min/1.73 m2, and 1.23 (0.57–2.67) for PAD per 1 mmol/L higher glucose level. CONCLUSIONS: Glucose levels in the normoglycemic range and higher were prospectively associated with a high risk of retinopathy, neuropathy, diabetic nephropathy, eGFR <60 mL/min/1.73 m2, PAD, and MI. These associations were confirmed in genetic causal analyses for retinopathy, neuropathy, diabetic nephropathy, and MI, but they could not be confirmed for PAD and seemed to be refuted for eGFR <60 mL/min/1.73 m2.
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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
A New Equation to Estimate Glomerular Filtration Rate
Levey, A. S., Stevens, L. A., Schmid, C. H., Zhang, Y. (., Castro, A. F., Feldman, H. I., Kusek, J. W., Eggers, P., Van Lente, F., Greene, T., et al. (2009) · Annals of Internal Medicine · doi:10.7326/0003-4819-150-9-200905050-00006 · Cited by 25,603 · 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
KDIGO 2024 clinical practice guideline for the evaluation and management of chronic kidney disease
Stevens, P. E., Ahmed, S. B., Carrero, J. J., Foster, B., Francis, A., Hall, R. K., Herrington, W. G., Hill, G., Inker, L. A., Kazancıoğlu, R., et al. (2024) · Kidney International · doi:10.1016/j.kint.2023.10.018 · Cited by 8,530 · see citing works
Canagliflozin and Renal Outcomes in Type 2 Diabetes and Nephropathy
Perkovic, V., Jardine, M. J., Neal, B., Bompoint, S., Heerspink, H. J. L., Charytan, D. M., Edwards, R., Agarwal, R., Bakris, G., Bull, S., et al. (2019) · New England Journal of Medicine · doi:10.1056/nejmoa1811744 · Cited by 6,189 · see citing works
Mendelian Randomization Analysis With Multiple Genetic Variants Using Summarized Data
Burgess, S., Butterworth, A., & Thompson, S. G. (2013) · Genetic Epidemiology · doi:10.1002/gepi.21758 · Cited by 6,050 · see citing works
The Emerging Risk Factors Collaboration (2010) · The Lancet · doi:10.1016/s0140-6736(10)60484-9 · Cited by 5,125 · see citing works
Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology
Lawlor, D. A., Harbord, R. M., Sterne, J. A. C., Timpson, N., & Davey Smith, G. (2008) · Statistics in Medicine · doi:10.1002/sim.3034 · Cited by 4,618 · see citing works
Global Prevalence of Chronic Kidney Disease – A Systematic Review and Meta-Analysis
Hill, N. R., Fatoba, S., Oke, J. L., Hirst, J. A., O’Callaghan, C. A., Lasserson, D. S., & Hobbs, R. F. (2016) · PLoS ONE · doi:10.1371/journal.pone.0158765 · Cited by 4,046 · see citing works
Davies, M. J., D’Alessio, D. A., Fradkin, J., Kernan, W. N., Mathieu, C., Mingrone, G., Rossing, P., Tsapas, A., Wexler, D. J., & Buse, J. B. (2018) · Diabetes Care · doi:10.2337/dci18-0033 · Cited by 3,518 · see citing works
(2012) · Kidney International Supplements · doi:10.1038/kisup.2012.73 · Cited by 3,247 · see citing works
2. Classification and Diagnosis of Diabetes: <i>Standards of Medical Care in Diabetes—2018</i>
American Diabetes Association (2018) · Diabetes Care · doi:10.2337/dc18-s002 · Cited by 3,159 · see citing works
Diabetes Prevention Program Research Group (2009) · The Lancet · doi:10.1016/s0140-6736(09)61457-4 · Cited by 3,020 · see citing works
Instrumental Variables and GMM: Estimation and Testing
Baum, C. F., Schaffer, M. E., & Stillman, S. (2003) · The Stata Journal Promoting communications on statistics and Stata · doi:10.1177/1536867x0300300101 · Cited by 2,632 · see citing works
Lindström, J., Ilanne-Parikka, P., Peltonen, M., Aunola, S., Eriksson, J. G., Hemiö, K., Hämäläinen, H., Härkönen, P., Keinänen-Kiukaanniemi, S., Laakso, M., et al. (2006) · The Lancet · doi:10.1016/s0140-6736(06)69701-8 · Cited by 1,799 · see citing works
Li, G., Zhang, P., Wang, J., Gregg, E. W., Yang, W., Gong, Q., Li, H., Li, H., Jiang, Y., An, Y., et al. (2008) · The Lancet · doi:10.1016/s0140-6736(08)60766-7 · Cited by 1,600 · see citing works
Davies, M. J., D’Alessio, D. A., Fradkin, J., Kernan, W. N., Mathieu, C., Mingrone, G., Rossing, P., Tsapas, A., Wexler, D. J., & Buse, J. B. (2018) · Diabetologia · doi:10.1007/s00125-018-4729-5 · Cited by 1,455 · see citing works
TCF7L2 Polymorphisms and Progression to Diabetes in the Diabetes Prevention Program
Florez, J. C., Jablonski, K. A., Bayley, N., Pollin, T. I., de Bakker, P. I. W., Shuldiner, A. R., Knowler, W. C., Nathan, D. M., & Altshuler, D. (2006) · New England Journal of Medicine · doi:10.1056/nejmoa062418 · Cited by 834 · see citing works
Scott, R. A., Lagou, V., Welch, R., Wheeler, E., Montasser, M. E., Luan, J., Mägi, R., Strawbridge, R. J., Rehnberg, E., Gustafsson, S., et al. (2012) · Nature Genetics · doi:10.1038/ng.2385 · Cited by 817 · see citing works
CKD in diabetes: diabetic kidney disease versus nondiabetic kidney disease
Anders, H., Huber, T. B., Isermann, B., & Schiffer, M. (2018) · Nature Reviews Nephrology · doi:10.1038/s41581-018-0001-y · Cited by 816 · see citing works
Collider scope: when selection bias can substantially influence observed associations
Munafò, M. R., Tilling, K., Taylor, A. E., Evans, D. M., & Davey Smith, G. (2018) · International Journal of Epidemiology · doi:10.1093/ije/dyx206 · Cited by 813 · see citing works
Fedak, K. M., Bernal, A. J., Capshaw, Z. A., & Gross, S. A. (2015) · Emerging Themes in Epidemiology · doi:10.1186/s12982-015-0037-4 · Cited by 682 · see citing works
An atlas of genetic associations in UK Biobank
Canela‐Xandri, O., Rawlik, K., & Tenesa, A. (2018) · Nature Genetics · doi:10.1038/s41588-018-0248-z · Cited by 657 · see citing works
Gong, Q., Zhang, P., Wang, J., Ma, J., An, Y., Chen, Y., Zhang, B., Feng, X., Li, H., Chen, X., et al. (2019) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(19)30093-2 · Cited by 615 · see citing works
Molecular and Cellular Mechanisms of Cardiovascular Disorders in Diabetes
Shah, M. S., & Brownlee, M. (2016) · Circulation Research · doi:10.1161/circresaha.116.306923 · Cited by 601 · 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
Use of allele scores as instrumental variables for Mendelian randomization
Burgess, S., & Thompson, S. G. (2013) · International Journal of Epidemiology · doi:10.1093/ije/dyt093 · Cited by 452 · see citing works
Microvascular Dysfunction and Hyperglycemia: A Vicious Cycle With Widespread Consequences
Stehouwer, C. D. A. (2018) · Diabetes · doi:10.2337/dbi17-0044 · Cited by 304 · see citing works
Prediabetes and Type 2 Diabetes Are Associated With Generalized Microvascular Dysfunction
Sörensen, B. M., Houben, A. J. H. M., Berendschot, T. T. J. M., Schouten, J., Kroon, A. A., Kallen, C., Henry, R. M. A., Koster, A., Sep, S. J. S., Dagnelie, P. C., et al. (2016) · Circulation · doi:10.1161/circulationaha.116.023446 · Cited by 246 · see citing works
the Metascreen Writing Committee (2006) · Diabetes Care · doi:10.2337/dc06-0942 · Cited by 188 · see citing works
Azmi, S., Ferdousi, M., Petropoulos, I. N., Ponirakis, G., Alam, U., Fadavi, H., Asghar, O., Marshall, A., Atkinson, A. J., Jones, W., et al. (2015) · Diabetes Care · doi:10.2337/dc14-2733 · Cited by 148 · see citing works
Benn, M., & Nordestgaard, B. G. (2018) · Cardiovascular Research · doi:10.1093/cvr/cvy045 · Cited by 131 · see citing works
Self-citationWe Can Change the Natural History of Type 2 Diabetes
Phillips, L. S., Ratner, R. E., Buse, J. B., & Kahn, S. E. (2014) · Diabetes Care · doi:10.2337/dc14-0817 · Cited by 105 · see citing works
Susceptibility of LDL and its subfractions to glycation
Soran, H., & Durrington, P. N. (2011) · Current Opinion in Lipidology · doi:10.1097/mol.0b013e328348a43f · Cited by 89 · see citing works
Nonfasting Glucose, Ischemic Heart Disease, and Myocardial Infarction
Benn, M., Tybjærg‐Hansen, A., McCarthy, M. I., Jensen, G. B., Grande, P., & Nordestgaard, B. G. (2012) · Journal of the American College of Cardiology · doi:10.1016/j.jacc.2012.02.043 · Cited by 84 · see citing works
Self-citationAssociation of a Fasting Glucose Genetic Risk Score With Subclinical Atherosclerosis
Rasmussen‐Torvik, L. J., Li, M., Kao, W. H., Couper, D. J., Boerwinkle, E., Bielinski, S. J., Folsom, A. R., & Pankow, J. S. (2010) · Diabetes · doi:10.2337/db10-0839 · Cited by 50 · see citing works
Prediabetes and risk of diabetes and associated complications
Abdul‐Ghani, M. A., DeFronzo, R. A., & Jayyousi, A. (2016) · Current Opinion in Clinical Nutrition & Metabolic Care · doi:10.1097/mco.0000000000000307 · Cited by 44 · see citing works
Hribal, M. L., Presta, I., Procopio, T., Marini, M. A., Stančáková, A., Kuusisto, J., Andreozzi, F., Hammarstedt, A., Jansson, P., Grarup, N., et al. (2011) · Diabetologia · doi:10.1007/s00125-010-2038-8 · Cited by 43 · see citing works
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Sorted by citations
Sacks, D. B., Arnold, M., Bakris, G. L., Bruns, D. E., Horvath, A. R., Lernmark, Å., Metzger, B. E., Nathan, D. M., & Kirkman, M. S. (2023) · Diabetes Care · doi:10.2337/dci23-0036 · Cited by 351 · see citing works
Sacks, D. B., Arnold, M. A., Bakris, G. L., Bruns, D. E., Horvath, A. R., Lernmark, Å., Metzger, B. E., Nathan, D. M., & Kirkman, M. S. (2023) · Clinical Chemistry · doi:10.1093/clinchem/hvad080 · Cited by 157 · 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
Si, S., Li, J., Li, Y., Li, W., Chen, X., Yuan, T., Liu, C., Li, H., Hou, L., Wang, B., et al. (2021) · Frontiers in Cardiovascular Medicine · doi:10.3389/fcvm.2020.583473 · Cited by 87 · see citing works
Chase-Vilchez, A., Chan, I. H. Y., Peters, S. A. E., & Woodward, M. (2020) · Cardiovascular Diabetology · doi:10.1186/s12933-020-01130-4 · Cited by 53 · see citing works
Research Progress on Mitochondrial Dysfunction in Diabetic Retinopathy
Wu, Y., & Zou, H. (2022) · Antioxidants · doi:10.3390/antiox11112250 · Cited by 51 · see citing works
Benn, M., Emanuelsson, F., Tybjærg-Hansen, A., & Nordestgaard, B. G. (2021) · Diabetologia · doi:10.1007/s00125-021-05436-0 · Cited by 41 · see citing works
Self-citationZhang, X., Zhao, S., Huang, Y., Ma, M., Li, B., Li, C., Zhu, X., Xu, X., Chen, H., Zhang, Y. Z., et al. (2024) · Journal of the American Heart Association · doi:10.1161/jaha.123.032626 · Cited by 39 · see citing works
Park, S., Lee, S., Kim, Y., Lee, Y., Kang, M. W., Han, K., Lee, H., Lee, J. P., Joo, K. W., Lim, C. S., et al. (2020) · Kidney Research and Clinical Practice · doi:10.23876/j.krcp.20.016 · Cited by 37 · see citing works
Therapeutic Potential of Hibiscus sabdariffa Linn. in Attenuating Cardiovascular Risk Factors
Sapian, S., Mze, A. A. I., Jubaidi, F. F., Nor, N. A. M., Taib, I. S., Hamid, Z. A., Zainalabidin, S., Anuar, N. N. M., Katas, H., Latip, J., et al. (2023) · Pharmaceuticals · doi:10.3390/ph16060807 · Cited by 36 · see citing works
Huang, Y., Zhang, X., Li, B., Zhu, X., Li, C., Zhou, C., Gu, C., Wang, Y., Ma, M., Fan, Y., et al. (2023) · Diabetes Research and Clinical Practice · doi:10.1016/j.diabres.2023.110975 · Cited by 34 · see citing works
Emanuelsson, F., Afzal, S., Jørgensen, N. R., Nordestgaard, B. G., & Benn, M. (2023) · Diabetologia · doi:10.1007/s00125-023-06054-8 · Cited by 33 · see citing works
Self-citationLi, J., Li, C., Huang, Y., Guan, P., Huang, D., Yu, H., Yang, X., & Liu, L. (2022) · Journal of Translational Medicine · doi:10.1186/s12967-022-03822-9 · Cited by 33 · see citing works
Giaretta, J., Zulli, R., Prabhakar, T., Rath, R. J., Naficy, S., Spilimbergo, S., Weiss, P. S., Farajikhah, S., & Dehghani, F. (2024) · Advanced Sensor Research · doi:10.1002/adsr.202400065 · Cited by 31 · see citing works
Zhou, G., Ren, X., Tang, Z., Li, W., Chen, W., He, Y., Wei, B., Zhang, H., Ma, F., Chen, X., et al. (2023) · Frontiers in Immunology · doi:10.3389/fimmu.2023.1043380 · Cited by 27 · see citing works
Yu, H., Zhang, J., Qian, F., Yao, P., Xu, K., Wu, P., Li, R., Qiu, Z., Li, R., Zhu, K., et al. (2025) · Diabetes Care · doi:10.2337/dc24-1696 · Cited by 25 · see citing works
Yuan, S., Mason, A. M., Burgess, S., & Larsson, S. C. (2022) · Diabetes · doi:10.2337/db21-0905 · Cited by 25 · see citing works
Nguyen, A., Khafagy, R. T. M., Gao, Y., Meerasa, A., Roshandel, D., Anvari, M., Lin, B., Cherney, D. Z. I., Farkouh, M. E., Shah, B. R., et al. (2023) · Diabetes · doi:10.2337/db22-0696 · Cited by 25 · see citing works
Gavidia, K., & Kalayjian, T. (2021) · Frontiers in Nutrition · doi:10.3389/fnut.2021.687081 · Cited by 18 · see citing works
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Emanuelsson, F., & Benn, M. (2020) · Clinical Chemistry · doi:10.1093/clinchem/hvaa242 · Cited by 18 · see citing works
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Gardemann, C., Knowles, S., & Marquardt, T. (2023) · Endocrinology Diabetes and Metabolism Case Reports · doi:10.1530/edm-23-0008 · Cited by 13 · see citing works
Chen, C., Liu, L., Huang, J., Yu, Y., Lo, K. K.-H., Huang, Y., & Feng, Y. (2020) · Diabetes Metabolic Syndrome and Obesity · doi:10.2147/dmso.s260990 · Cited by 12 · see citing works
Han, Y., Wang, X., Sun, G., Luo, J., Cao, X., Yin, P., Yu, R., He, S., Yang, F., Myers, F. L., et al. (2022) · Translational Vision Science & Technology · doi:10.1167/tvst.11.4.20 · Cited by 12 · see citing works
Ahmed, A., Sattar, N., & Yaghootkar, H. (2022) · Diabetic Medicine · doi:10.1111/dme.14982 · Cited by 10 · see citing works
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Wen, C., Chen, L., Jia, D., Liu, Z., Lin, Y., Liu, G., Zhang, S., & Gao, B. (2024) · Renal Failure · doi:10.1080/0886022x.2024.2319712 · Cited by 11 · see citing works
Sinclair, S. H., & Schwartz, S. S. (2020) · Vide Leaf, Hyderabad eBooks · doi:10.37247/paendo.1.2020.4 · Cited by 11 · see citing works
Jamal, A. A., Tharkar, S., Babaier, W. S., Alsomali, S. F., Alsulayhim, A. S., Alayuni, M. A., Aldakheel, N. A., Al-Osaimi, S. S., Alshehri, N., & Batais, M. A. (2021) · JMIR Diabetes · doi:10.2196/29178 · Cited by 9 · see citing works
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Gerstein, H. C., & Pigeyre, M. (2024) · The Lancet Diabetes & Endocrinology · doi:10.1016/s2213-8587(24)00059-7 · Cited by 5 · see citing works
Vermunt, J. V., Bragg, F., Halsey, J., Yang, L., Chen, Y., Yu, C., Du, H., Meng, F., Pei, P., Yu, C., et al. (2021) · BMJ Open Diabetes Research & Care · doi:10.1136/bmjdrc-2021-002495 · Cited by 5 · see citing works
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Gerstein, H. C. (2022) · Circulation · doi:10.1161/circulationaha.122.060026 · Cited by 5 · see citing works
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Benn, M., Emanuelsson, F., Tybjærg‐Hansen, A., & Nordestgaard, B. G. (2024) · European Heart Journal Open · doi:10.1093/ehjopen/oeaf009 · Cited by 4 · see citing works
Self-citationChang, Y.-S., Lee, L.-Y., & Lee, I. (2021) · Diabetes Metabolic Syndrome and Obesity · doi:10.2147/dmso.s330606 · Cited by 4 · see citing works
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Liu, Z., Zhang, Z., & Li, T. (2025) · VASA · doi:10.1024/0301-1526/a001169 · Cited by 2 · see citing works
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Gounden, V., & Moodley, N. (2025) · Journal of the Colleges of Medicine of South Africa · doi:10.4102/jcmsa.v3i1.148 · Cited by 1 · see citing works
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Wang, Y., Sargent, J. L., Mathieu, C., Arreola, E. V., Perreault, L., Loos, R. J. F., Lim, L., Sandforth, L., Hanson, R. L., Kullmann, S., et al. (2026) · Nature Medicine · doi:10.1038/s41591-026-04550-z · Cited by 1 · see citing works
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Herscovici, D., & Scaduto, J. M. (2023) · Springer eBooks · doi:10.1007/978-3-031-33537-2_16 · Cited by 1 · 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) · SSRN Electronic Journal · doi:10.2139/ssrn.3861555 · Cited by 1 · see citing works
Systolic blood pressure and all-cause mortality in normoglycemia, prediabetes, and diabetesPreprint
Chen, C., Liu, L., Huang, J., Yu, Y., Lo, K., Huang, Y., & Feng, Y. (2020) · doi:10.21203/rs.3.rs-25078/v1
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(2020) · Diabetologie und Stoffwechsel · doi:10.1055/a-1201-9035
Al-Batarny, M. M. S. A., Elhawary, P. A. E. M. M., Kandil, P. Y. M. R., & Ahmed, M. S. (2023) · Journal Of Advanced Zoology · doi:10.17762/jaz.v44is6.2028
Sharma, A., Shekhawat, S., Shalini, F., Kaushik, S., & Arora, S. (2025) · International Journal of Advanced Medical and Health Research · doi:10.4103/ijamr.ijamr_165_24
Lin, C., Li, C., Liu, C.-S., Lin, C., Yang, S.-Y., & Lin, C. (2025) · Diabetology & Metabolic Syndrome · doi:10.1186/s13098-025-01728-2
Chase-Vilchez, A., Chan, I. H. Y., Peters, S. A. E., & Woodward, M. (2020) · Figshare · doi:10.6084/m9.figshare.13011852
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Rethinking the Pre in Prediabetes
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- Authors
- Emanuelsson, F., Marott, S., Tybjærg-Hansen, A., Nordestgaard, B. G., & Benn, M.
- Affiliations
- University of Copenhagen (DK)
- Department of Clinical Biochemistry, Rigshospitalet, Copenhagen University Hospital, Copenhagen, Denmark
- Corresponding author
- Benn, Marianne
- Venue
- Diabetes Care
- Publisher
- American Diabetes Association
- Published
- 2020-02-13
- Volume
- 43
- Issue
- 4
- Pages
- 894-902
- ISSN
- 0149-5992 (ISSN-L)
- 1935-5548
- OpenAlex
- W3005608069
- Semantic Scholar
- d216b1ffb385d81034c158417e551512258eedad
- Cited by
- 59
- References
- 39
- Citations by year
- 2026: 7 · 2025: 5 · 2024: 6 · 2023: 10 · 2022: 6 · 2021: 8 · 2020: 17
- FWCI
- 6.00
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- Diabetes Care (publishedVersion)
- PubMed (publishedVersion)
- Research at the University of Copenhagen (University of Copenhagen) (submittedVersion)
- Funders
- Det Frie Forskningsråd (#4183-00171B)
- 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 › Endocrinology, Diabetes and Metabolism › Diabetes Management and Research
- Keywords
- hyperglycemia, retinopathy, diabetic neuropathy, diabetic nephropathy, chronic kidney disease, peripheral arterial disease, myocardial infarction, microangiopathy, macroangiopathy, estimated glomerular filtration rate, hyperglycemia prevention, diabetes prevention, glycemic targets
- MeSH terms
- Aged, Blood Glucose, Denmark, Female, Genotype, Humans, Male, Middle Aged, Myocardial Infarction, Peripheral Nervous System Diseases, Retinal Diseases, Risk Factors, Diabetes Complications, Renal Insufficiency, Chronic, Mendelian Randomization Analysis, Peripheral Arterial Disease
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