Statins as a risk factor for diabetic retinopathy: a Mendelian randomization and cross-sectional observational study

Cheung N, Mitchell P, Wong TY. Diabetic retinopathy. Lancet. 2010;376(9735):124–36.

Article  PubMed  Google Scholar 

Lee R, Wong TY, Sabanayagam C. Epidemiology of diabetic retinopathy, diabetic macular edema and related vision loss. Eye Vis (Lond). 2015;2:17.

Article  PubMed  Google Scholar 

Teo ZL, et al. Global prevalence of diabetic retinopathy and projection of burden through 2045: systematic review and meta-analysis. Ophthalmology. 2021;128(11):1580–91.

Article  PubMed  Google Scholar 

Saeedi P, et al. Global and regional diabetes prevalence estimates for 2019 and projections for 2030 and 2045: results from the International Diabetes Federation Diabetes Atlas, 9(th) edition. Diabetes Res Clin Pract. 2019;157: 107843.

Article  PubMed  Google Scholar 

Chen C, et al. Pharmacological roles of lncRNAs in diabetic retinopathy with a focus on oxidative stress and inflammation. Biochem Pharmacol. 2023;214: 115643.

Article  CAS  PubMed  Google Scholar 

Chen C, et al. Anti-VEGF combined with ocular corticosteroids therapy versus anti-VEGF monotherapy for diabetic macular edema focusing on drugs injection times and confounding factors of pseudophakic eyes: a systematic review and meta-analysis. Pharmacol Res. 2023;196: 106904.

Article  CAS  PubMed  Google Scholar 

Gauldin D, et al. Exposure of contralateral eyes to laser radiation during retinal photocoagulation. Curr Eye Res. 2021;46(9):1424–7.

Article  CAS  PubMed  Google Scholar 

Wang JH, Roberts GE, Liu GS. Updates on gene therapy for diabetic retinopathy. Curr Diab Rep. 2020;20(7):22.

Article  PubMed  PubMed Central  Google Scholar 

Fraser-Bell S, et al. Bevacizumab or dexamethasone implants for DME: 2-year results (the BEVORDEX study). Ophthalmology. 2016;123(6):1399–401.

Article  PubMed  Google Scholar 

Wong TY, et al. Guidelines on diabetic eye care: the international council of ophthalmology recommendations for screening, follow-up, referral, and treatment based on resource settings. Ophthalmology. 2018;125(10):1608–22.

Article  PubMed  Google Scholar 

Taylor FC, Huffman M, Ebrahim S. Statin therapy for primary prevention of cardiovascular disease. JAMA. 2013;310(22):2451–2.

Article  CAS  PubMed  Google Scholar 

Istvan ES, Deisenhofer J. Structural mechanism for statin inhibition of HMG-CoA reductase. Science. 2001;292(5519):1160–4.

Article  CAS  PubMed  Google Scholar 

Nielsen SF, Nordestgaard BG. Statin use before diabetes diagnosis and risk of microvascular disease: a nationwide nested matched study. Lancet Diabetes Endocrinol. 2014;2(11):894–900.

Article  CAS  PubMed  Google Scholar 

Hammer SS, et al. Cholesterol crystal formation is a unifying pathogenic mechanism in the development of diabetic retinopathy. Diabetologia. 2023. https://doi.org/10.1007/s00125-023-05949-w.

Article  PubMed  PubMed Central  Google Scholar 

Kang EY, et al. Association of statin therapy with prevention of vision-threatening diabetic retinopathy. JAMA Ophthalmol. 2019;137(4):363–71.

Article  PubMed  PubMed Central  Google Scholar 

Mozetic V, et al. Statins and/or fibrates for diabetic retinopathy: a systematic review and meta-analysis. Diabetol Metab Syndr. 2019;11:92.

Article  PubMed  PubMed Central  Google Scholar 

Meer E, et al. Statin use and the risk of progression to vision threatening diabetic retinopathy. Pharmacoepidemiol Drug Saf. 2022;31(6):652–60.

Article  PubMed  PubMed Central  Google Scholar 

Lawlor DA, et al. Mendelian randomization: using genes as instruments for making causal inferences in epidemiology. Stat Med. 2008;27(8):1133–63.

Article  PubMed  Google Scholar 

Burgess S, Small DS, Thompson SG. A review of instrumental variable estimators for Mendelian randomization. Stat Methods Med Res. 2017;26(5):2333–55.

Article  PubMed  Google Scholar 

Burgess S, Butterworth A, Thompson SG. Mendelian randomization analysis with multiple genetic variants using summarized data. Genet Epidemiol. 2013;37(7):658–65.

Article  PubMed  PubMed Central  Google Scholar 

Smith GD, Ebrahim S. “Mendelian randomization”: can genetic epidemiology contribute to understanding environmental determinants of disease? Int J Epidemiol. 2003;32(1):1–22.

Article  PubMed  Google Scholar 

Hemani G, et al. The MR-Base platform supports systematic causal inference across the human phenome. Elife. 2018;7: e34408.

Article  PubMed  PubMed Central  Google Scholar 

Võsa U, et al. Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nat Genet. 2021;53(9):1300–10.

Article  PubMed  PubMed Central  Google Scholar 

Richardson TG, et al. Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: a multivariable Mendelian randomisation analysis. PLoS Med. 2020;17(3): e1003062.

Article  PubMed  PubMed Central  Google Scholar 

Huang W, et al. Association of lipid-lowering drugs with COVID-19 outcomes from a Mendelian randomization study. Elife. 2021;10: e73873.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Chen C, et al. Causal effects of diabetic retinopathy on depression, anxiety and bipolar disorder in the European population: a Mendelian randomization study. J Endocrinol Invest. 2023. https://doi.org/10.1007/s40618-023-02176-3.

Article  PubMed  PubMed Central  Google Scholar 

Nicholls SJ, et al. Statins, high-density lipoprotein cholesterol, and regression of coronary atherosclerosis. JAMA. 2007;297(5):499–508.

Article  CAS  PubMed  Google Scholar 

Mortensen MB, et al. Low-density lipoprotein cholesterol is predominantly associated with atherosclerotic cardiovascular disease events in patients with evidence of coronary atherosclerosis: the Western Denmark heart registry. Circulation. 2023;147(14):1053–63.

Article  CAS  PubMed  Google Scholar 

Skrivankova VW, et al. Strengthening the reporting of observational studies in epidemiology using Mendelian randomization: the STROBE-MR statement. JAMA. 2021;326(16):1614–21.

Article  PubMed  Google Scholar 

Boef AG, Dekkers OM, le Cessie S. Mendelian randomization studies: a review of the approaches used and the quality of reporting. Int J Epidemiol. 2015;44(2):496–511.

Article  PubMed  Google Scholar 

Palmer TM, et al. Using multiple genetic variants as instrumental variables for modifiable risk factors. Stat Methods Med Res. 2012;21(3):223–42.

Article  PubMed  PubMed Central  Google Scholar 

Burgess S, Thompson SG. Avoiding bias from weak instruments in Mendelian randomization studies. Int J Epidemiol. 2011;40(3):755–64.

Article  PubMed  Google Scholar 

Li S, et al. Ankylosing spondylitis and glaucoma in European population: a Mendelian randomization study. Front Immunol. 2023;14:1120742.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Verbanck M, et al. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nat Genet. 2018;50(5):693–8.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Hartwig FP, Davey Smith G, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. Int J Epidemiol. 2017;46(6):1985–98.

Article  PubMed  PubMed Central  Google Scholar 

Hemani G, Bowden J, Davey Smith G. Evaluating the potential role of pleiotropy in Mendelian randomization studies. Hum Mol Genet. 2018;27(R2):R195-r208.

Article  CAS  PubMed  PubMed Central  Google Scholar 

Bowden J, Holmes MV. Meta-analysis and Mendelian randomization: a review. Res Synth Methods. 2019;10(4):486–96.

Article  PubMed  PubMed Central  Google Scholar 

Burgess S, Thompson SG. Interpreting findings from Mendelian randomization using the MR-Egger method. Eur J Epidemiol. 2017;32(5):377–89.

Article  PubMed  PubMed Central  Google Scholar 

Bowden J, et al. Improving the accuracy of two-sample summary-data Mendelian

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