2658-6533Research Results in Biomedicine2658-653310.18413/2658-6533-2024-10-1-0-23333Genetics<strong>Mendelian randomization in eye disorders (review)</strong><strong>Mendelian randomization in eye disorders (review)</strong>PlotnikovDenis Y.PlotnikovDenis Y.denis.plotnikov@kazangmu.ruAshryatovaLiana Sh.AshryatovaLiana Sh.lili.pop@mail.ruPankratovaSofya A.PankratovaSofya A.sofo4kapankratova@gmail.com202410100

Background: Mendelian randomization (MR) is an analytic approach in genetic epidemiology which uses the results of genome-wide association studies (GWAS) to assess causal relationships between various risk factors and phenotypes of interest (or diseases) in ophthalmology. The aim of the study: To describe the current opportunities for the use of MR in ophthalmic research. Materials and methods: We searched Scopus, Medline and Web of Science journals up to August 2022 using the PRISMA protocol &ldquo;Preferred Reporting Items for Systematic Review and Meta-Analysis&rdquo;. The following information was extracted: identified risk factor(s) and disease(s), design of Mendelian randomization study, sensitivity analysis(es) performed if any, genetic instrument(s) used, and also whether the causal relationship between risk and outcome was confirmed by the results of the study. Results: The current review included a total of 37 publications that tested 211 associations of a risk factor with an ophthalmic disease. The articles included were published in peer-reviewed journals up to August 2022 with 25 of them (67,5%) published in 2020 or later. The MR method indicated the causal role of blood serum lipids, C-reactive protein, free thyroxine, smoking and alcohol intake in the development of age-related macular degeneration. For glaucoma, type 2 diabetes, serum glucose, refractive abnormalities, and elevated intraocular pressure have been shown to be significant. MR analysis revealed the role of elevated intraocular pressure, level of education, body weight at birth in the development of refractive errors. The role of type 2 diabetes, hypertension and smoking in the development of cataracts was determined using the MR method. Conclusion: The results of 97 MR analyses in ophthalmology have revealed a significant role of a number of risk factors in the development of eye diseases, which will serve as a guideline for clinical trials and drug development.

Background: Mendelian randomization (MR) is an analytic approach in genetic epidemiology which uses the results of genome-wide association studies (GWAS) to assess causal relationships between various risk factors and phenotypes of interest (or diseases) in ophthalmology. The aim of the study: To describe the current opportunities for the use of MR in ophthalmic research. Materials and methods: We searched Scopus, Medline and Web of Science journals up to August 2022 using the PRISMA protocol &ldquo;Preferred Reporting Items for Systematic Review and Meta-Analysis&rdquo;. The following information was extracted: identified risk factor(s) and disease(s), design of Mendelian randomization study, sensitivity analysis(es) performed if any, genetic instrument(s) used, and also whether the causal relationship between risk and outcome was confirmed by the results of the study. Results: The current review included a total of 37 publications that tested 211 associations of a risk factor with an ophthalmic disease. The articles included were published in peer-reviewed journals up to August 2022 with 25 of them (67,5%) published in 2020 or later. The MR method indicated the causal role of blood serum lipids, C-reactive protein, free thyroxine, smoking and alcohol intake in the development of age-related macular degeneration. For glaucoma, type 2 diabetes, serum glucose, refractive abnormalities, and elevated intraocular pressure have been shown to be significant. MR analysis revealed the role of elevated intraocular pressure, level of education, body weight at birth in the development of refractive errors. The role of type 2 diabetes, hypertension and smoking in the development of cataracts was determined using the MR method. Conclusion: The results of 97 MR analyses in ophthalmology have revealed a significant role of a number of risk factors in the development of eye diseases, which will serve as a guideline for clinical trials and drug development.

Mendelian randomizationSNPGWASeye disordersMendelian randomizationSNPGWASeye disordersСписок литературыBourne RRA, Jonas JB, Bron AM, et al. Prevalence and causes of vision loss in high-income countries and in Eastern and Central Europe in 2015: magnitude, temporal trends and projections. British Journal of Ophthalmology. 2018;102(5):575-585. DOI: https://doi.org/10.1136/bjophthalmol-2017-311258Bikbov MM, Gilmanshin TR, Iakupova EM, et al. Fundamentals of epidemiology. Epidemiology in ophthalmology (literature review). Current problems of health care and medical statistics. 2021;31(4):364-387. Russian. DOI: https://doi.org/10.24412/2312-2935-2021-4-364-387Zolotarev AV, Karlova EV, Miroshnichenko EV. Influence of eye diseases on the mortality rate of the population. Ophthalmology Journal. 2018;11(1):47-53. Russian. DOI: https://doi.org/10.17816/OV11147-53Ebrahim S, Davey Smith G. Mendelian randomization: can genetic epidemiology help redress the failures of observational epidemiology? Human Genetics. 2008;123(1):15-33. DOI: https://doi.org/10.1007/s00439-007-0448-6Dwan K, Gamble C, Williamson PR, et al. Systematic Review of the Empirical Evidence of Study Publication Bias and Outcome Reporting Bias &mdash; An Updated Review. PLoS ONE. 2013;8(7):e66844. DOI: https://doi.org/10.1371/journal.pone.0066844Hariton E, Locascio JJ. Randomised controlled trials - the gold standard for effectiveness research: Study design: randomised controlled trials. BJOG: An International Journal of Obstetrics and Gynaecology. 2018;125(13):1716. DOI: https://doi.org/10.1111/1471-0528.15199Narkevich AN, Vinogradov KA. Medical study design [Internet].&nbsp; Social aspects of population health 2019 [cited 2022 October 26];65(5):13. Available from: http://vestnik.mednet.ru/content/view/1108/30/lang,ru/. Russian. DOI: https://doi.org/10.21045/2071-5021-2019-65-5-13Lawlor DA, Harbord RM, Sterne JAC, et al. Mendelian randomization: Using genes as instruments for making causal inferences in epidemiology. Statistics in Medicine. 2008;27(8):1133-1163. DOI: https://doi.org/10.1002/sim.3034Davey Smith G, Hemani G. Mendelian randomization: genetic anchors for causal inference in epidemiological studies. Human Molecular Genetics. 2014;23(R1):R89-R98. DOI: https://doi.org/10.1093/hmg/ddu328Katan MB. Apolipoprotein E isoforms, serum cholesterol, and cancer. The Lancet. 1986;327(8479):507-508. DOI: https://doi.org/10.1016/S0140-6736(86)92972-7Gray R, Wheatley K. How to avoid bias when comparing bone marrow transplantation with chemotherapy. Bone Marrow Transplantation. 1991;7(3):9-12.Davey Smith G, Ebrahim S. &lsquo;Mendelian randomization&rsquo;: can genetic epidemiology contribute to understanding environmental determinants of disease? International Journal of Epidemiology. 2003;32(1):1-22. DOI: https://doi.org/10.1093/ije/dyg070Eliseeva NV, Churnosov MI. Etiopathogenesis of primary open-angle glaucoma. Vestnik Oftalmologii. 2020;136(3):79‑86. Russian. DOI: https://doi.org/10.17116/oftalma202013603179Bowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. International Journal of Epidemiology. 2015;44(2):512-525. DOI: https://doi.org/10.1093/ije/dyv080Hartwig FP, Davey Smith G, Bowden J. Robust inference in summary data Mendelian randomization via the zero modal pleiotropy assumption. International Journal of Epidemiology. 2017;46(6):1985-1998. DOI: https://doi.org/10.1093/ije/dyx102Verbanck M, Chen CY, Neale B, et al. Detection of widespread horizontal pleiotropy in causal relationships inferred from Mendelian randomization between complex traits and diseases. Nature Genetics. 2018;50(5):693-698. DOI: https://doi.org/10.1038/s41588-018-0099-7Buniello A, MacArthur JAL, Cerezo M, et al. The NHGRI-EBI GWAS Catalog of published genome-wide association studies, targeted arrays and summary statistics 2019. Nucleic Acids Research. 2019;47(D1):D1005-D1012. DOI: https://doi.org/10.1093/nar/gky1120Oettinger AP, Zharova ME. What is evidence-based medicine? Russian Journal of Evidence-Based Gastroenterology. 2021;10(1):38‑48. Russian. DOI: https://doi.org/10.17116/dokgastro20211001138Lawlor DA. Commentary: Two-sample Mendelian randomization: opportunities and challenges. International Journal of Epidemiology. 2016;45(3):908-915. DOI: https://doi.org/10.1093/ije/dyw127Plotnikov D, Guggenheim JA. Mendelian randomisation and the goal of inferring causation from observational studies in the vision sciences. Ophthalmic and Physiological Optics. 2019;39(1):11-25. DOI: https://doi.org/10.1111/opo.12596Moher D, Liberati A, Tetzlaff J, et al. Preferred reporting items for systematic reviews and meta-analyses: the PRISMA statement. The BMJ. 2009;339:b2535-b2535. DOI: https://doi.org/10.1136/bmj.b2535Zagidullina ASh. Phenotypes of primary glaucoma. Meditsinskii vestnik Bashkorkostana. 2015;2(56):162-165. Russian.The International Schizophrenia Consortium. Common polygenic variation contributes to risk of schizophrenia and bipolar disorder. Nature. 2009;460(7256):748-752. DOI: https://doi.org/10.1038/nature08185Burgess S, Davey Smith G. Mendelian Randomization Implicates High-Density Lipoprotein Cholesterol&ndash;Associated Mechanisms in Etiology of Age-Related Macular Degeneration. Ophthalmology. 2017;124(8):1165-1174. DOI: https://doi.org/10.1016/j.ophtha.2017.03.042Fan Q, Maranville JC, Fritsche L, et al. HDL-cholesterol levels and risk of age-related macular degeneration: a multiethnic genetic study using Mendelian randomization. International Journal of Epidemiology. 2017;46(6):1891-1902. DOI: https://doi.org/10.1093/ije/dyx189Han X, Ong JS, Hewitt AW, et al. The effects of eight serum lipid biomarkers on age-related macular degeneration risk: a Mendelian randomization study. International Journal of Epidemiology. 2021;50(1):325-336. DOI: https://doi.org/10.1093/ije/dyaa178Han X, Ong JS, An J, et al. Using Mendelian randomization to evaluate the causal relationship between serum C-reactive protein levels and age-related macular degeneration. European Journal of Epidemiology. 2020;35(2):139-146. DOI: https://doi.org/10.1007/s10654-019-00598-zKuan V, Warwick A, Hingorani A, et al. Association of Smoking, Alcohol Consumption, Blood Pressure, Body Mass Index, and Glycemic Risk Factors With Age-Related Macular Degeneration: A Mendelian Randomization Study. JAMA Ophthalmology. 2021;139(12):1299. DOI: https://doi.org/10.1001/jamaophthalmol.2021.4601Wang K, Zhong Y, Yang F, et al. Causal Effects of N-6 Polyunsaturated Fatty Acids on Age-related Macular Degeneration: A Mendelian Randomization Study. Journal of Clinical Endocrinology and Metabolism. 2021;106(9):e3565-e3572. DOI: https://doi.org/10.1210/clinem/dgab338Wood A, Guggenheim JA. Refractive Error Has Minimal Influence on the Risk of Age-Related Macular Degeneration: A Mendelian Randomization Study. American Journal of Ophthalmology. 2019;206:87-93. DOI: https://doi.org/10.1016/j.ajo.2019.03.018Li X, Li H, Cheng J, et al. Causal Associations of Thyroid Function and Age-Related Macular Degeneration: A Two-Sample Mendelian Randomization Study. American Journal of Ophthalmology. 2022;239:108-114. DOI: https://doi.org/10.1016/j.ajo.2022.01.026Klein RJ, Zeiss C, Chew EY, et al. Complement Factor H Polymorphism in Age-Related Macular Degeneration. Science. 2005;308(5720):385-389. DOI: https://doi.org/10.1126/science.1109557Miller JW. Age-Related Macular Degeneration Revisited &ndash; Piecing the Puzzle: The LXIX Edward Jackson Memorial Lecture. American Journal of Ophthalmology. 2013;155(1):1-35. DOI: https://doi.org/10.1016/j.ajo.2012.10.018Shen L, Walter S, Melles RB, et al. Diabetes Pathology and Risk of Primary Open-Angle Glaucoma: Evaluating Causal Mechanisms by Using Genetic Information. American Journal of Epidemiology. 2015;183(2):147-155. DOI: https://doi.org/10.1093/aje/kwv204Tan X, Zhong Z, Wang Q, et al. Genetically predicted fasting blood glucose level plays a causal role in intraocular pressure: A Mendelian randomisation study. Clinical and Experimental Ophthalmology. 2022;50(5):534-542. DOI: https://doi.org/10.1111/ceo.14067Lin Y, Zhu X, Luo W, et al. The Causal Association Between Obesity and Primary Open-Angle Glaucoma: A Two-Sample Mendelian Randomization Study. Frontiers in Genetics. 2022;13:835524. DOI: https://doi.org/10.3389/fgene.2022.835524Bao J, Yang Z, Zheng S, et al. Circulating fatty acids and risk of primary open-angle glaucoma: A mendelian randomization study. Gene. 2022;811:146078. DOI: https://doi.org/10.1016/j.gene.2021.146078Choquet H, Melles RB, Yin J, et al. A multiethnic genome-wide analysis of 44,039 individuals identifies 41 new loci associated with central corneal thickness. Communications Biology. 2020;3(1):301. DOI: https://doi.org/10.1038/s42003-020-1037-7Simcoe MJ, Khawaja AP, Hysi PG, et al. Genome-wide association study of corneal biomechanical properties identifies over 200 loci providing insight into the genetic etiology of ocular diseases. Human Molecular Genetics. 2020;29(18):3154-3164. DOI: https://doi.org/10.1093/hmg/ddaa155Currant H, Hysi P, Fitzgerald TW, et al. Genetic variation affects morphological retinal phenotypes extracted from UK Biobank optical coherence tomography images. PLoS Genetics. 2021;17(5):e1009497. DOI: https://doi.org/10.1371/journal.pgen.1009497Simcoe MJ, Shah A, Fan B, et al. Genome-Wide Association Study Identifies Two Common Loci Associated with Pigment Dispersion Syndrome/Pigmentary Glaucoma and Implicates Myopia in its Development. Ophthalmology. 2022;129(6):626-636. DOI: https://doi.org/10.1016/j.ophtha.2022.01.005Nusinovici S, Li H, Thakur S, et al. High-Density Lipoprotein 3 Cholesterol and Primary Open-Angle Glaucoma. Ophthalmology. 2022;129(3):285-294 DOI: https://doi.org/10.1016/j.ophtha.2021.09.013Xu M, Li S, Zhu J, et al. Plasma lipid levels and risk of primary open angle glaucoma: a genetic study using Mendelian randomization. BMC Ophthalmology. 2020;20:390. DOI: https://doi.org/10.1186/s12886-020-01661-0Hysi PG, Khawaja AP, Menni C, et al. Ascorbic acid metabolites are involved in intraocular pressure control in the general population. Redox Biology. 2019;20:349-353. DOI: https://doi.org/10.1016/j.redox.2018.10.004Hayat SA, Luben R, Keevil VL, et al. Cohort Profile: A prospective cohort study of objective physical and cognitive capability and visual health in an ageing population of men and women in Norfolk (EPIC-Norfolk 3). International Journal of Epidemiology. 2014;43(4):1063-1072.&nbsp; DOI: https://doi.org/10.1093/ije/dyt086Ingold N, Campos AI, Han X, et al. Is Genetic Risk for Sleep Apnea Causally Linked With Glaucoma Susceptibility? Investigative Ophthalmology and Visual Science. 2022;63(1):25. DOI: https://doi.org/10.1167/iovs.63.1.25Kim J, Aschard H, Kang JH, et al. Intraocular Pressure, Glaucoma, and Dietary Caffeine Consumption. Ophthalmology. 2021;128(6):866-876. DOI: https://doi.org/10.1016/j.ophtha.2020.12.009Choquet H, Khawaja AP, Jiang C, et al. Association Between Myopic Refractive Error and Primary Open-Angle Glaucoma: A 2-Sample Mendelian Randomization Study. JAMA Ophthalmology. 2022;140(9):864-871. DOI: https://doi.org/10.1001/jamaophthalmol.2022.2762Plotnikov D, Huang Y, Khawaja AP, et al. High Blood Pressure and Intraocular Pressure: A Mendelian Randomization Study. Investigative Ophthalmology and Visual Science. 2022;63(6):29. DOI: https://doi.org/10.1167/iovs.63.6.29Hysi PG, Choquet H, Khawaja AP, et al. Meta-analysis of 542,934 subjects of European ancestry identifies new genes and mechanisms predisposing to refractive error and myopia. Nature Genetics. 2020;52(4):401-407. DOI: https://doi.org/10.1038/s41588-020-0599-0Mountjoy E, Davies NM, Plotnikov D, et al. Education and myopia: assessing the direction of causality by mendelian randomisation. The BMJ. 2018;361:k2022. DOI: https://doi.org/10.1136/bmj.k2022Patasova K, Khawaja AP, Tamraz B, et al. Association Between Medication-Taking and Refractive Error in a Large General Population-Based Cohort. Investigative Ophthalmology and Visual Science. 2021;62(2):15. DOI: https://doi.org/10.1167/iovs.62.2.15Plotnikov D, Williams C, Guggenheim JA. Association between birth weight and refractive error in adulthood: a Mendelian randomisation study. British Journal of Ophthalmology 2020;104:214-219. DOI: https://doi.org/10.1136/bjophthalmol-2018-313640Cuellar-Partida G, Williams KM, Yazar S, et al. Genetically low vitamin D concentrations and myopic refractive error: a Mendelian randomization study. International Journal of Epidemiology. 2017;46(6):1882-1890. DOI: https://doi.org/10.1093/ije/dyx068Cuellar-Partida G, Lu Y, Kho PF, et al. Assessing the Genetic Predisposition of Education on Myopia: A Mendelian Randomization Study: Assessing the Genetic Predisposition of Education on Myopia. Genetic Epidemiology. 2016;40(1):66-72. DOI: https://doi.org/10.1002/gepi.21936Zhang H, Xiu X, Xue A, et al. Mendelian randomization study reveals a population-specific putative causal effect of type 2 diabetes in risk of cataract. International Journal of Epidemiology. 2022;50(6):2024-2037. DOI: https://doi.org/10.1093/ije/dyab175Yuan S, Wolk A, Larsson SC. Metabolic and lifestyle factors in relation to senile cataract: a Mendelian randomization study. Scientific Reports. 2022;12:409. DOI: https://doi.org/10.1038/s41598-021-04515-xTan AG, Kifley A, Flood VM, et al. Evaluating the associations between obesity and age-related cataract: a Mendelian randomization study. American Journal of Clinical Nutrition. 2019;110(4):969-976. DOI: https://doi.org/10.1093/ajcn/nqz167Kurki MI, Karjalainen J, Palta P, et al. FinnGen: Unique Genetic Insights from Combining Isolated Population and National Health Register Data. Genetic and Genomic Medicine. medRxiv; 2022. DOI: https://doi.org/10.1101/2022.03.03.22271360Han X, Ong JS, An J, et al. Association of Myopia and Intraocular Pressure With Retinal Detachment in European Descent Participants of the UK Biobank Cohort: A Mendelian Randomization Study. JAMA Ophthalmology. 2020;138(6):671-678. DOI: https://doi.org/10.1001/jamaophthalmol.2020.1231Kaye RA, Patasova K, Patel PJ, et al. Macular thickness varies with age-related macular degeneration genetic risk variants in the UK Biobank cohort. Scientific Reports. 2021;11:23255. DOI: https://doi.org/10.1038/s41598-021-02631-2Li LJ, Liao J, Cheung CYL, et al. Assessing the Causality between Blood Pressure and Retinal Vascular Caliber through Mendelian Randomisation. Scientific Reports. 2016;6:22031. DOI: https://doi.org/10.1038/srep22031