Causal relationship between lipid-lowering drugs and ocular disorders: A drug-targeted Mendelian randomization study

Causal relationship between lipid-lowering drugs and ocular disorders: A drug-targeted Mendelian randomization study | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Causal relationship between lipid-lowering drugs and ocular disorders: A drug-targeted Mendelian randomization study Yilan Huang, Wenjie Dong, Min Zhong, Qiuyu Li, Longyang Jiang This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4437336/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Background Most ocular diseases are associated with lipid metabolism, but the exact mechanisms are unclear. Statins, PCSK9 inhibitors and NPC1L1 inhibitors are common lipid-modulating agents. The aim of this study was to explore the causal relationship between common lipid-lowering drugs and ocular diseases through Mendelian randomization analysis. Methods In this study, we used the summary-data-based Mendelian randomization (SMR) method and inverse-variance-weighted Mendelian randomization (IVW-MR). Low-density lipoprotein cholesterol (LDL-C) was used as a biomarker. We then obtained instrumental variables (IVs) from the Global Lipids Genetics Consortium (GLGC) (n = 173082) and UK Biobank (n = 440546). The 3-Hydroxy-9-methylglutaryl-coenzyme A reductase (HMGCR) expression quantitative trait loci (eQTL) was obtained from a cohort study containing 31,684 blood samples. Summary data for ocular diseases were obtained from the Integrative Epidemiology Unit (IEU) database. Results IVW-MR showed that statins increased the risk of allergic conjunctivitis (OR = 1.96, 95% CI: 1.30–2.95, P = 0.001) and diabetic retinopathy (OR = 2.58, 95% CI: 1.67–3.99, P < 0.001). PCSK9 inhibitors reduced the risk of allergic conjunctivitis (OR = 0.67, 95% CI: 0.47–0.95, P = 0.02) but increased the risk of glaucoma (OR = 1.23, 95% CI: 1.06–1.43, P = 0.006). The SMR approach showed that inhibition of HMGCR significantly elevated the risk of allergic conjunctivitis (OR = 1.28, 95% CI: 1.11–1.45, P < 0.001) and diabetic retinopathy (OR = 1.56, 95% CI: 1.33–1.84, P < 0.001). Conclusion The study found that statin elevated the risk of allergic conjunctivitis and diabetic retinopathy. PCSK9 inhibitors reduced the risk of allergic conjunctivitis but elevated the risk of glaucoma. But more mechanisms remain to be further explored. Health sciences/Medical research Health sciences/Medical research/Outcomes research HMGCR PCSK9 NPC1L1 Mendelian randomization allergic conjunctivitis diabetic retinopathy glaucoma Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 1. Introduction The main causes of blindness are ocular disorders, which include cataract, diabetic retinopathy, glaucoma, and macular degeneration, among others(1). The quest for pertinent etiological factors and novel therapeutic targets has become crucial in the treatment of ocular illnesses due to the scarcity of medications currently accessible for this purpose. Nowadays, lipid-lowering medications play a significant role in the prevention of hyperlipidemia. 3-Hydroxy-9-methylglutaryl-coenzyme A reductase (HMGCR) inhibitors, such as Rosuvastatin and Atorvastatin, have multiple lipid-lowering effects and have demonstrated safety and efficacy (2, 3). Statins include anti-inflammatory, antioxidant, thromboprophylactic, immunomodulatory, and anticancer properties in addition to reducing cholesterol (2, 4, 5). Its application to ocular disorders is debatable, though. Statins were linked to an increased risk of developing eye illness, according to a meta-analysis of statin side effects (6). On the other hand, statins were discovered to be protective against uveitis and macular degeneration in Lymperopoulou's systematic review, among other things (7). Nowadays, Proprotein convertase subtilis kexin 9 (PCSK9) is a key target for the treatment of hypercholesterolemia because it prevents low-density lipoprotein cholesterol (LDL-C) from being recycled, which raises LDL-C levels (8). According to a prior study, PCSK9 inhibition improved Graves' ophthalmopathy (GO) by lowering oxidative stress and inflammatory factor expression (9). However, major ocular adverse effects with PCSK9 inhibitors (including evolocumab and alirocumab) have already been reported through the FDA Adverse Event Reporting System (FAERS) in the United States (10). Transmembrane protein Niemann-Pick C1-Like 1 (NPC1L1) is found in enterocyte membranes and is primarily involved in the transfer of cholesterol (11). Inhibition of NPC1L1 lowers cholesterol absorption and manages hyperlipidemia(12). However, NPC1L1 inhibitors and ocular illness have not been linked in any research. In conclusion, despite a wealth of evidence supporting their effects, lipid-lowering medications' association with ocular diseases is still up for debate. Thus, the purpose of this study was to clarify the causal relationship between lipid-lowering medications and ocular disorders and to offer support for the diagnosis, management, and prevention of ocular diseases. The value of evidence provided by Mendelian randomization (MR) is second only to that of randomized clinical trials, and it is currently routinely employed in causality analyses for a host of disorders (13). The present investigation employed two-sample MR to examine the causal relationship between lipid-lowering medications and various conditions such as cataract, glaucoma, uveitis, macular degeneration, allergic conjunctivitis and diabetic retinopathy. Additionally, a range of sensitivity analyses were conducted. 2. Methods 2.1 Study overview The genome-wide association study (GWAS) pooled data used in this investigation are freely accessible. MR analysis is based on three assumptions: (1) IVs are not correlated with confounders. (2) Instrumental variables (IVs) are strongly correlated with exposure factors. (3) IVs act through exposure factors with the outcome. The research framework was presented in Fig. 1 . 2.2 Instrumental variables selection Since it had been demonstrated that all three of the lipid-lowering medications we looked at lower LDL-C levels, we employed LDL-C as a biomarker. The summary data for LDL-C were obtained from the GWAS of The Global Lipids Genetics Consortium (GLGC) (ieu-a-300)(14) and UK Biobank (ieu-b-5089)(15). Following that, three target genes for lipid-lowering medications were found in the drugbank database ( https://go.drugbank.com/ ). Table 1 displayed the specifics of these findings. Single nucleotide polymorphisms (SNPs) that were substantially linked to LDL-C and were located within ± 100 kb of the target gene were selected (P 0.01) as IVs. The eQTLGen Consortium ( https://www.eqtlgen.org/cis-eqtls.html ) provided the expression quantitative trait loci (eQTL) data for HMGCR, which comprised the upstream and downstream effects of trait-related genetic variations from 31,684 blood samples. As a precaution against linkage disequilibrium (LD), r 2 was adjusted to 0.3. After removing SNPs that were either clearly linked to the result or ambiguous, SNPs for MR analysis were identified (Additional file: Table S1 ) . Table 1 Target genes of lipid-lowering drugs from DrugBank Drugs Target Gene location Statins HMGCR Chr5: 74632933–74657941 Evolocumab/Alirocumab PCSK9 Chr1: 55505221–55530525 Ezetimibe NPC1L1 Chr7: 44552134–44580929 2.3 Outcomes Outcome data were taken from the Integrative Epidemiology Unit (IEU) database, which is accessible to the general public ( https://gwas.mrcieu.ac.uk/ ). Glaucoma, uveitis, diabetic retinopathy, allergic conjunctivitis, macular degeneration and cataracts were among the main outcomes. We employed hyperlipidemia and CHD as positive controls to confirm the validity of the instrumental variables. 2.4 Data analysis In this work, weighted mode, inverse variance weighted (IVW), weighted median, weighted egger, and simple mode were employed as analysis methods. We used IVW as the primary technique of analysis and expound on the outcomes produced by the IVW method because it was most frequently employed in MR analysis(16). Results obtained by the other four methods were as reference. IVW estimates the average effect of genetic variants on causality by means of a weighted linear regression model, and the results of IVW are unbiased if there is no horizontal pleiotropy(17, 18). Weighted median is appropriate for datasets with fewer than 50% effective SNPs, whereas MR Egger is mostly utilized for datasets with numerous effects(19, 20). The IVs were validated using summary data on total cholesterol, hyperlipidemia, and coronary heart disease as positive controls. IVW and MR Egger methods were used to detect heterogeneity of results. We concentrated on the Cochrane’s Q value, where a considerable heterogeneity is indicated if Q_ P < 0.05. To evaluate horizontal pleiotropy, MR Egger intercept method was employed. Significant horizontal pleiotropy is seen when P < 0.05. Furthermore, the MR-PRESSO method was employed to identify any outliers. Finally, we applied the leave-one-out technique to a sensitivity analysis: One SNP at a time was eliminated, and the stability of the remaining SNPs was observed(21). In the summary-data-based Mendelian randomization (SMR), cis-eqtls of HMGCR were used as IVs. R version 4.3.2 was utilized to conduct all statistical analyses. Twosample MR and MR-PRESSO packages were used. 3. Results 3.1 Positive control analysis The IVW-MR method showed that genetic inhibition of HMGCR, NPC1L1 and PCSK9 significantly lowered the risk of CHD [(OR = 0.69, 95% CI: 0.59–0.81, P < 0.001), (OR = 0.60, 95% CI: 0.44–0.83, P = 0.002), (OR = 0.60, 95% CI: 0.52–0.69, P < 0.001)] and hyperlipidemia [(OR = 0.41, 95% CI: 0.28–0.60, P < 0.001), (OR = 0.27, 95% CI: 0.10–0.72, P = 0.009), (OR = 0.34, 95% CI: 0.26–0.44, P < 0.001)] by analyzing the GLGC dataset. Comparable to what was previously mentioned, the analysis conducted on the UK Biobank dataset provided the same results ( Fig. 2 ) . 3.2 The causal relationship between lipid-lowering drugs and ocular disorders Analysis of the dataset from GLGC showed that genetic inhibition of HMGCR resulted in an increased risk of allergic conjunctivitis (OR = 1.96, 95% CI: 1.30–2.95, P = 0.001) and diabetic retinopathy (OR = 2.58, 95% CI: 1.67–3.99, P < 0.001). However, there may be a decreased risk of uveitis (OR = 0.60, 95% CI: 0.37–0.99, P = 0.04). In addition, genetic inhibition of PCSK9 resulted in an increased risk of glaucoma (OR = 1.23, 95% CI: 1.06–1.43, P = 0.006). While, genetic inhibition of NPC1L1 resulted in an increased risk of uveitis (OR = 4.43, 95% CI: 1.36–14.4, P = 0.01) ( Fig. 3 ) . Analysis of the dataset from UK Biobank showed that genetic inhibition of HMGCR resulted in an increased risk of allergic conjunctivitis (OR = 1.65, 95% CI: 1.17–2.31, P = 0.004) and diabetic retinopathy (OR = 2.00, 95% CI: 1.26–3.18, P = 0.003). Genetic inhibition of PCSK9 resulted in an increased risk of glaucoma (OR = 1.14, 95% CI: 1.02–1.29, P = 0.03) and a decreased risk of allergic conjunctivitis (OR = 0.67, 95% CI: 0.47–0.95, P = 0.02) ( Fig. 4 ) . The results of the SMR analysis showed that inhibition of HMGCR significantly elevated the risk of diabetic retinopathy (OR = 1.56, 95% CI: 1.33–1.84, P < 0.001) and allergic conjunctivitis (OR = 1.28, 95% CI: 1.11–1.45, P < 0.001) ( Fig. 5 ) . Otherwise, no significant causal relationship was found between lipid-lowering drugs and cataracts or macular degeneration. 3.3 Sensitivity analysis Cochrane’s Q and MR Egger intercepts were used to assess heterogeneity and horizontal pleiotropy. There was no significant heterogeneity or horizontal pleiotropy in the reanalysis after the SNPs that affected the results were eliminated (Additional file: Table S2 and S3) . The stability of the SNPs employed in MR analysis was demonstrated by the leave-one-out method (Additional file: Figure S1 , S2, S3, S4 ,S5 and S6) . 4. Discussion According to this MR research, HMGCR inhibition elevates the risk of allergic conjunctivitis and diabetic retinopathy. And PCSK9 inhibition elevates the risk of glaucoma but may be protective against allergic conjunctivitis. Significantly, examination of the GLGC dataset revealed a correlation between the inhibition of HMGCR and PCSK9 and the likelihood of developing uveitis. However, the analysis of the UK Biobank dataset did not yield similar results. Furthermore, no conclusive evidence was discovered regarding the correlation between lipid-lowering medicines and the development of cataracts and macular degeneration. Diabetic retinopathy is a prevalent microvascular consequence of diabetes mellitus and a significant contributor to vision loss(22, 23). Dyslipidaemia is a significant risk factor for the development of diabetic retinopathy(24, 25). Statins are conventional lipid-modifying medications that effectively reduce LDL levels. Multiple observational studies have documented beneficial outcomes of statins on diabetic retinopathy. Animal studies have demonstrated that statins can enhance the treatment of diabetic retinopathy by inhibiting neovascularization(26, 27). However, the amount of evidence remained rather insufficient. Cohort research also found that statins have a beneficial effect on diabetic retinopathy(28). Nevertheless, the criteria used to choose participants for the study might have influenced the outcomes in a biased manner. Therefore, the precise impact of statin on diabetic retinopathy is still uncertain. In this work, we employed genetic big data mining to determine the correlation between statin usage and the likelihood of developing diabetic retinopathy. The MR analysis is conducted based on three assumptions, effectively mitigating the influence of confounding factors in the studies. In addition, we conducted a set of sensitivity studies and validated the eQTLs. Chen et al. similarly obtained similar results to ours(29). Furthermore, research found that statin medication results in increased levels of vascular endothelial growth factor (VEGF) in the vitreous of individuals with diabetic retinopathy. This, in turn, caused damage to the blood-retinal barrier, worsening the condition of diabetic retinopathy(30). It is debatable how statins affect eye health, but our study is the first to show that taking them raises the risk of allergic conjunctivitis. Several investigations have demonstrated that statins have important immunomodulatory effects in addition to decreasing cholesterol levels (31, 32). Its immunomodulatory activities, however, have a double-edged effect: while they raise the body's regulatory T cell (Treg) concentration, they also disturb the immune environment (33). This could be among the factors contributing to the increased risk of allergic conjunctivitis. Furthermore, our research indicated that PCSK9 inhibitors reduced the risk of allergic conjunctivitis, providing patients with a guidance for selecting lipid-lowering drugs. The role of PCSK9 inhibitors in ocular disease is also currently unclear. However, evidence from FAERS suggested that ocular adverse effects from PCSK9 inhibitors should be taken seriously. These adverse events included tearing, eye surgery, and seasonal allergies. Though the precise mechanism is unknown, it raises the question of whether PCSK9 inhibitors are beneficial or detrimental for eye illness, and whether they are genuinely linked to an increased risk of glaucoma? Since no prior research has demonstrated a link between PCSK9 inhibitors and glaucoma, we believe the findings of this investigation to be trustworthy. However, given the positive effects of lipid-lowering drugs in lowering cholesterol, we recommend that the results of this study be viewed with caution. To determine which course of treatment is best for patients, doctors and pharmacists should weigh the advantages and disadvantages while also applying their understanding of pharmacoeconomics. Our study also has some shortcomings Firstly, we explored the causal relationship between lipid-lowering drugs and ocular diseases through gene-mimicking drug inhibitors, and we were unable to assess their pharmacological effects and physiological mechanisms. Secondly, we were only able to analyze the genetic data of European populations because of the restricted resources of the GWAS data. Furthermore, we were unable to validate the involvement of PCSK9 inhibitors in glaucoma because to the absence of PCSK9 eqtl data. Lastly, we were unable to stratify analyses for variables including age, sex, and disease subtype since we employed GWAS pooled data. 5. Conclusion In conclusion, our study found that HMGCR inhibitors lead to an increased risk of diabetic retinopathy and allergic conjunctivitis, whereas PCSK9 inhibitors induced glaucoma at the same time as they led to a decreased risk of allergic conjunctivitis. Further clinical trials and animal research are need to identify the precise mechanisms, though. We advise carefully weighing the advantages and disadvantages when selecting lipid-lowering medications because the results are solely based on Mendelian randomization study. Abbreviations SMR summary-data-based Mendelian randomization SNP Single nucleotide polymorphism IVW Inverse variance weighted IV Instrumental variable LD Linkage disequilibrium HMGCR 3-Hydroxy-9-methylglutaryl-coenzyme A reductase PCSK9 Proprotein convertase subtilisin kexin-9 NPC1L1 Niemann-Pick C1-Like 1 LDL-C Low-density lipoprotein cholesterol CI Confidence interval OR Odds ratio GLGC Global Lipids Genetics Consortium MAF Minor allele frequency GWAS Genome-wide association study FDA Food and Drug Administration CHD Coronary heart disease eQTL Expression quantitative trait loci VEGF Vascular endothelial growth factor IEU Integrative Epidemiology Unit GO Graves' ophthalmopathy FAERS FDA Adverse Event Reporting System Declarations Competing interests The authors declare no competing interests. Ethics approval and consent to participate The study used the large publicly available GWAS database, which has received approval from their relevant ethical review board and participants. Competing interest The authors have declared that there are no commercial or financial conflicts of interest in this work. Funding This work was supported by the Doctoral Research Initiation Fund of Affiliated Hospital of Southwest Medical University. Author contributions WD, YH and LJ contributed to the research design, statistical analysis. MZ and QL contributed to the drafting and revision of the article. The final manuscript has been read and approved by all the listed authors. Acknowledgements This study used public data from the GLGC, UK Biobank and IEU databases. We sincerely appreciate all participants and investigators for their valuable contribution in making statistics accessible and publicly available. Availability of data and materials No original data were generated in the present study. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4437336","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":328865460,"identity":"5a4a8999-1edc-42e9-b6f7-576f9685e4b5","order_by":0,"name":"Yilan Huang","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1UlEQVRIie3QsQrCMBCA4SuF6nBSJ4ko9BVSHFQo+CoNQmfHjoVKXXyAFl/C0bFyg0vAVXBp8QUydrQdXWxGwfzzfdwlACbTD8bBTqswZujZdlmqRotYGa9kMPcPjrgWRz2STOt9FMAdFzR0NMiSiYSLhNBKUREgeO6k/E7WuUgqcSEc2KMz7VbgF6ew57BHt0V2W1qSI4T8qUGYyAiBsCJ09EnUEdAkss54KAP0U4e3n8w03nLbUt3EbOO59FKqCTx31kNg/DnAesa73FJjyGQymf67N3bcS0xbLs/kAAAAAElFTkSuQmCC","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":true,"prefix":"","firstName":"Yilan","middleName":"","lastName":"Huang","suffix":""},{"id":328865461,"identity":"2dc2e11b-2962-45bd-af5e-ece34c41b9f8","order_by":1,"name":"Wenjie Dong","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Wenjie","middleName":"","lastName":"Dong","suffix":""},{"id":328865462,"identity":"3bf89b05-bf9b-4471-9f99-b331dab38145","order_by":2,"name":"Min Zhong","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Min","middleName":"","lastName":"Zhong","suffix":""},{"id":328865463,"identity":"eb7f6c6b-82cf-479a-bfbe-57ea5ee99451","order_by":3,"name":"Qiuyu Li","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qiuyu","middleName":"","lastName":"Li","suffix":""},{"id":328865464,"identity":"f2270456-087a-40bb-99f7-bb885b4f982f","order_by":4,"name":"Longyang Jiang","email":"","orcid":"","institution":"The Affiliated Hospital of Southwest Medical University","correspondingAuthor":false,"prefix":"","firstName":"Longyang","middleName":"","lastName":"Jiang","suffix":""}],"badges":[],"createdAt":"2024-05-17 14:26:23","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4437336/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4437336/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":62396135,"identity":"b9a4934a-1712-4bd0-93d4-f26feee8c3c9","added_by":"auto","created_at":"2024-08-13 17:12:57","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":739578,"visible":true,"origin":"","legend":"\u003cp\u003eWorkflow diagram for Mendelian randomization analysis of drug targets. MR is based on three assumptions: (1) the instrumental variable is uncorrelated with confounders, (2) the instrumental variable is strongly correlated with exposure, (3) the instrumental variable must have an effect on the outcome through exposure. SNPs: Single nucleotide polymorphism; LDL-C: Low-density lipoprotein cholesterol; GLGC: Global Lipids Genetics Consortium; HMGCR: 3-Hydroxy-9-methylglutaryl-coenzyme A reductase; PCSK9: Proprotein convertase subtilisin kexin-9; IVW: Inverse variance weighted; NPC1L1: Niemann-Pick C1-Like 1.\u003c/p\u003e","description":"","filename":"Figure1.png","url":"https://assets-eu.researchsquare.com/files/rs-4437336/v1/a1a3237d02a419a0f4384c4f.png"},{"id":62396134,"identity":"06334ee1-402e-4a1d-b402-2e848028af3a","added_by":"auto","created_at":"2024-08-13 17:12:57","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":440510,"visible":true,"origin":"","legend":"\u003cp\u003eThe effects of HMGCR, PCSK9 and NPC1L1 inhibitors on coronary heart disease and hyperlipidemiabased on the exposure data derived from the GLGC and the UK Biobank. CI: Confidence interval; OR: Odds ratio; HMGCR: 3-Hydroxy-9-methylglutaryl-coenzyme A reductase; PCSK9: Proprotein convertase subtilisin kexin-9; NPC1L1: Niemann-Pick C1-Like 1.\u003c/p\u003e","description":"","filename":"Figure2.png","url":"https://assets-eu.researchsquare.com/files/rs-4437336/v1/472ec545696e9fdde2268e56.png"},{"id":62396136,"identity":"c70d077d-1834-4bb7-bf3c-23746dd7d603","added_by":"auto","created_at":"2024-08-13 17:12:57","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":583897,"visible":true,"origin":"","legend":"\u003cp\u003eThe effects of HMGCR, PCSK9 and NPC1L1 inhibitors on ocular disorders based on the exposure data derived from the GLGC. CI: Confidence interval; OR: Odds ratio; HMGCR: 3-Hydroxy-9-methylglutaryl-coenzyme A reductase; PCSK9: Proprotein convertase subtilisin kexin-9; NPC1L1: Niemann-Pick C1-Like 1.\u003c/p\u003e","description":"","filename":"Figure3.png","url":"https://assets-eu.researchsquare.com/files/rs-4437336/v1/5af19f6f57e61045d1b0c357.png"},{"id":62396382,"identity":"db91aacd-bc3b-49fd-a738-d27b5d181aeb","added_by":"auto","created_at":"2024-08-13 17:20:57","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":573721,"visible":true,"origin":"","legend":"\u003cp\u003eThe effects of HMGCR, PCSK9 and NPC1L1 inhibitors on ocular disorders based on the exposure data derived from the UK Biobank. CI: Confidence interval; OR: Odds ratio; HMGCR: 3-Hydroxy-9-methylglutaryl-coenzyme A reductase; PCSK9: Proprotein convertase subtilisin kexin-9; NPC1L1: Niemann-Pick C1-Like 1.\u003c/p\u003e","description":"","filename":"Figure4.png","url":"https://assets-eu.researchsquare.com/files/rs-4437336/v1/3446b62eb0fbb5c152a8552f.png"},{"id":62396138,"identity":"543c04c0-ea71-4b05-bbb0-619796d3ea6b","added_by":"auto","created_at":"2024-08-13 17:12:57","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":147513,"visible":true,"origin":"","legend":"\u003cp\u003eSMR reveals causal relationship between cis-eqtls of HMGCR and allergic conjunctivitis and diabetic retinopathy. CI: Confidence interval; OR: Odds ratio; HMGCR: 3-Hydroxy-9-methylglutaryl-coenzyme A reductase.\u003c/p\u003e","description":"","filename":"Figure5.png","url":"https://assets-eu.researchsquare.com/files/rs-4437336/v1/e807f458538d6324f4041b25.png"},{"id":65828422,"identity":"36dc637a-d3d1-48b6-b3b9-9cad7aa4e00d","added_by":"auto","created_at":"2024-10-03 09:08:44","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":2560750,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4437336/v1/8080d0d2-0f03-42b8-8ccc-dbdd8bebddc3.pdf"},{"id":62396140,"identity":"414fc65c-1d10-4679-8109-b8d54870a47a","added_by":"auto","created_at":"2024-08-13 17:12:57","extension":"pdf","order_by":8,"title":"","display":"","copyAsset":false,"role":"supplement","size":5063295,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalmaterialFigure.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4437336/v1/475d98c28923fcc063360f38.pdf"},{"id":62396139,"identity":"7ad71630-ecaf-4be0-b45e-33dacd24be21","added_by":"auto","created_at":"2024-08-13 17:12:57","extension":"docx","order_by":9,"title":"","display":"","copyAsset":false,"role":"supplement","size":111564,"visible":true,"origin":"","legend":"","description":"","filename":"SupplementalmaterialTable.docx","url":"https://assets-eu.researchsquare.com/files/rs-4437336/v1/5960c37a86cbaf4a2859aae5.docx"}],"financialInterests":"There is no conflict of interest","formattedTitle":"Causal relationship between lipid-lowering drugs and ocular disorders: A drug-targeted Mendelian randomization study","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eThe main causes of blindness are ocular disorders, which include cataract, diabetic retinopathy, glaucoma, and macular degeneration, among others(1). The quest for pertinent etiological factors and novel therapeutic targets has become crucial in the treatment of ocular illnesses due to the scarcity of medications currently accessible for this purpose.\u003c/p\u003e \u003cp\u003eNowadays, lipid-lowering medications play a significant role in the prevention of hyperlipidemia. 3-Hydroxy-9-methylglutaryl-coenzyme A reductase (HMGCR) inhibitors, such as Rosuvastatin and Atorvastatin, have multiple lipid-lowering effects and have demonstrated safety and efficacy (2, 3). Statins include anti-inflammatory, antioxidant, thromboprophylactic, immunomodulatory, and anticancer properties in addition to reducing cholesterol (2, 4, 5). Its application to ocular disorders is debatable, though. Statins were linked to an increased risk of developing eye illness, according to a meta-analysis of statin side effects (6). On the other hand, statins were discovered to be protective against uveitis and macular degeneration in Lymperopoulou's systematic review, among other things (7). Nowadays, Proprotein convertase subtilis kexin 9 (PCSK9) is a key target for the treatment of hypercholesterolemia because it prevents low-density lipoprotein cholesterol (LDL-C) from being recycled, which raises LDL-C levels (8). According to a prior study, PCSK9 inhibition improved Graves' ophthalmopathy (GO) by lowering oxidative stress and inflammatory factor expression (9). However, major ocular adverse effects with PCSK9 inhibitors (including evolocumab and alirocumab) have already been reported through the FDA Adverse Event Reporting System (FAERS) in the United States (10). Transmembrane protein Niemann-Pick C1-Like 1 (NPC1L1) is found in enterocyte membranes and is primarily involved in the transfer of cholesterol (11). Inhibition of NPC1L1 lowers cholesterol absorption and manages hyperlipidemia(12). However, NPC1L1 inhibitors and ocular illness have not been linked in any research.\u003c/p\u003e \u003cp\u003eIn conclusion, despite a wealth of evidence supporting their effects, lipid-lowering medications' association with ocular diseases is still up for debate. Thus, the purpose of this study was to clarify the causal relationship between lipid-lowering medications and ocular disorders and to offer support for the diagnosis, management, and prevention of ocular diseases.\u003c/p\u003e \u003cp\u003eThe value of evidence provided by Mendelian randomization (MR) is second only to that of randomized clinical trials, and it is currently routinely employed in causality analyses for a host of disorders (13). The present investigation employed two-sample MR to examine the causal relationship between lipid-lowering medications and various conditions such as cataract, glaucoma, uveitis, macular degeneration, allergic conjunctivitis and diabetic retinopathy. Additionally, a range of sensitivity analyses were conducted.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e \u003ch2\u003e2.1 Study overview\u003c/h2\u003e \u003cp\u003eThe genome-wide association study (GWAS) pooled data used in this investigation are freely accessible. MR analysis is based on three assumptions: (1) IVs are not correlated with confounders. (2) Instrumental variables (IVs) are strongly correlated with exposure factors. (3) IVs act through exposure factors with the outcome. The research framework was presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec4\" class=\"Section2\"\u003e \u003ch2\u003e2.2 Instrumental variables selection\u003c/h2\u003e \u003cp\u003eSince it had been demonstrated that all three of the lipid-lowering medications we looked at lower LDL-C levels, we employed LDL-C as a biomarker. The summary data for LDL-C were obtained from the GWAS of The Global Lipids Genetics Consortium (GLGC) (ieu-a-300)(14) and UK Biobank (ieu-b-5089)(15). Following that, three target genes for lipid-lowering medications were found in the drugbank database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://go.drugbank.com/\u003c/span\u003e\u003cspan address=\"https://go.drugbank.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Table\u0026nbsp;\u003cspan refid=\"Tab1\" class=\"InternalRef\"\u003e1\u003c/span\u003e displayed the specifics of these findings. Single nucleotide polymorphisms (SNPs) that were substantially linked to LDL-C and were located within \u0026plusmn;\u0026thinsp;100 kb of the target gene were selected (P\u0026thinsp;\u0026lt;\u0026thinsp;5x10\u003csup\u003e\u0026minus;\u0026thinsp;8\u003c/sup\u003e, MAF\u0026thinsp;\u0026gt;\u0026thinsp;0.01) as IVs. The eQTLGen Consortium (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.eqtlgen.org/cis-eqtls.html\u003c/span\u003e\u003cspan address=\"https://www.eqtlgen.org/cis-eqtls.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e) provided the expression quantitative trait loci (eQTL) data for HMGCR, which comprised the upstream and downstream effects of trait-related genetic variations from 31,684 blood samples. As a precaution against linkage disequilibrium (LD), r\u003csup\u003e2\u003c/sup\u003e was adjusted to 0.3. After removing SNPs that were either clearly linked to the result or ambiguous, SNPs for MR analysis were identified \u003cb\u003e(Additional file: Table \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003cdiv class=\"gridtable\"\u003e\u003ctable float=\"Yes\" id=\"Tab1\" border=\"1\"\u003e \u003ccaption language=\"En\"\u003e \u003cdiv class=\"CaptionNumber\"\u003eTable 1\u003c/div\u003e \u003cdiv class=\"CaptionContent\"\u003e \u003cp\u003eTarget genes of lipid-lowering drugs from DrugBank\u003c/p\u003e \u003c/div\u003e \u003c/caption\u003e \u003ccolgroup cols=\"3\"\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c1\" colnum=\"1\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c2\" colnum=\"2\"\u003e\u003c/div\u003e \u003cdiv align=\"left\" class=\"colspec\" colname=\"c3\" colnum=\"3\"\u003e\u003c/div\u003e \u003cthead\u003e \u003ctr\u003e \u003cth align=\"left\" colname=\"c1\"\u003e \u003cp\u003eDrugs\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c2\"\u003e \u003cp\u003eTarget\u003c/p\u003e \u003c/th\u003e \u003cth align=\"left\" colname=\"c3\"\u003e \u003cp\u003eGene location\u003c/p\u003e \u003c/th\u003e \u003c/tr\u003e \u003c/thead\u003e \u003ctbody\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eStatins\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eHMGCR\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChr5: 74632933\u0026ndash;74657941\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEvolocumab/Alirocumab\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003ePCSK9\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChr1: 55505221\u0026ndash;55530525\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003ctr\u003e \u003ctd align=\"left\" colname=\"c1\"\u003e \u003cp\u003eEzetimibe\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c2\"\u003e \u003cp\u003eNPC1L1\u003c/p\u003e \u003c/td\u003e \u003ctd align=\"left\" colname=\"c3\"\u003e \u003cp\u003eChr7: 44552134\u0026ndash;44580929\u003c/p\u003e \u003c/td\u003e \u003c/tr\u003e \u003c/tbody\u003e \u003c/colgroup\u003e \u003c/table\u003e\u003c/div\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec5\" class=\"Section2\"\u003e \u003ch2\u003e2.3 Outcomes\u003c/h2\u003e \u003cp\u003eOutcome data were taken from the Integrative Epidemiology Unit (IEU) database, which is accessible to the general public (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Glaucoma, uveitis, diabetic retinopathy, allergic conjunctivitis, macular degeneration and cataracts were among the main outcomes. We employed hyperlipidemia and CHD as positive controls to confirm the validity of the instrumental variables.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec6\" class=\"Section2\"\u003e \u003ch2\u003e2.4 Data analysis\u003c/h2\u003e \u003cp\u003eIn this work, weighted mode, inverse variance weighted (IVW), weighted median, weighted egger, and simple mode were employed as analysis methods. We used IVW as the primary technique of analysis and expound on the outcomes produced by the IVW method because it was most frequently employed in MR analysis(16). Results obtained by the other four methods were as reference. IVW estimates the average effect of genetic variants on causality by means of a weighted linear regression model, and the results of IVW are unbiased if there is no horizontal pleiotropy(17, 18). Weighted median is appropriate for datasets with fewer than 50% effective SNPs, whereas MR Egger is mostly utilized for datasets with numerous effects(19, 20). The IVs were validated using summary data on total cholesterol, hyperlipidemia, and coronary heart disease as positive controls. IVW and MR Egger methods were used to detect heterogeneity of results. We concentrated on the Cochrane\u0026rsquo;s Q value, where a considerable heterogeneity is indicated if Q_\u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. To evaluate horizontal pleiotropy, MR Egger intercept method was employed. Significant horizontal pleiotropy is seen when \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.05. Furthermore, the MR-PRESSO method was employed to identify any outliers. Finally, we applied the leave-one-out technique to a sensitivity analysis: One SNP at a time was eliminated, and the stability of the remaining SNPs was observed(21).\u003c/p\u003e \u003cp\u003eIn the summary-data-based Mendelian randomization (SMR), cis-eqtls of HMGCR were used as IVs.\u003c/p\u003e \u003cp\u003eR version 4.3.2 was utilized to conduct all statistical analyses. Twosample MR and MR-PRESSO packages were used.\u003c/p\u003e \u003c/div\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Positive control analysis\u003c/h2\u003e \u003cp\u003eThe IVW-MR method showed that genetic inhibition of HMGCR, NPC1L1 and PCSK9 significantly lowered the risk of CHD [(OR\u0026thinsp;=\u0026thinsp;0.69, 95% CI: 0.59\u0026ndash;0.81, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), (OR\u0026thinsp;=\u0026thinsp;0.60, 95% CI: 0.44\u0026ndash;0.83, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.002), (OR\u0026thinsp;=\u0026thinsp;0.60, 95% CI: 0.52\u0026ndash;0.69, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001)] and hyperlipidemia [(OR\u0026thinsp;=\u0026thinsp;0.41, 95% CI: 0.28\u0026ndash;0.60, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001), (OR\u0026thinsp;=\u0026thinsp;0.27, 95% CI: 0.10\u0026ndash;0.72, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.009), (OR\u0026thinsp;=\u0026thinsp;0.34, 95% CI: 0.26\u0026ndash;0.44, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001)] by analyzing the GLGC dataset. Comparable to what was previously mentioned, the analysis conducted on the UK Biobank dataset provided the same results \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec9\" class=\"Section2\"\u003e \u003ch2\u003e3.2 The causal relationship between lipid-lowering drugs and ocular disorders\u003c/h2\u003e \u003cp\u003eAnalysis of the dataset from GLGC showed that genetic inhibition of HMGCR resulted in an increased risk of allergic conjunctivitis (OR\u0026thinsp;=\u0026thinsp;1.96, 95% CI: 1.30\u0026ndash;2.95, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and diabetic retinopathy (OR\u0026thinsp;=\u0026thinsp;2.58, 95% CI: 1.67\u0026ndash;3.99, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). However, there may be a decreased risk of uveitis (OR\u0026thinsp;=\u0026thinsp;0.60, 95% CI: 0.37\u0026ndash;0.99, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.04). In addition, genetic inhibition of PCSK9 resulted in an increased risk of glaucoma (OR\u0026thinsp;=\u0026thinsp;1.23, 95% CI: 1.06\u0026ndash;1.43, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006). While, genetic inhibition of NPC1L1 resulted in an increased risk of uveitis (OR\u0026thinsp;=\u0026thinsp;4.43, 95% CI: 1.36\u0026ndash;14.4, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.01) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. Analysis of the dataset from UK Biobank showed that genetic inhibition of HMGCR resulted in an increased risk of allergic conjunctivitis (OR\u0026thinsp;=\u0026thinsp;1.65, 95% CI: 1.17\u0026ndash;2.31, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.004) and diabetic retinopathy (OR\u0026thinsp;=\u0026thinsp;2.00, 95% CI: 1.26\u0026ndash;3.18, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.003). Genetic inhibition of PCSK9 resulted in an increased risk of glaucoma (OR\u0026thinsp;=\u0026thinsp;1.14, 95% CI: 1.02\u0026ndash;1.29, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.03) and a decreased risk of allergic conjunctivitis (OR\u0026thinsp;=\u0026thinsp;0.67, 95% CI: 0.47\u0026ndash;0.95, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e. The results of the SMR analysis showed that inhibition of HMGCR significantly elevated the risk of diabetic retinopathy (OR\u0026thinsp;=\u0026thinsp;1.56, 95% CI: 1.33\u0026ndash;1.84, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and allergic conjunctivitis (OR\u0026thinsp;=\u0026thinsp;1.28, 95% CI: 1.11\u0026ndash;1.45, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) \u003cb\u003e(\u003c/b\u003eFig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e\u003cb\u003e)\u003c/b\u003e.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003e \u003c/p\u003e \u003cp\u003eOtherwise, no significant causal relationship was found between lipid-lowering drugs and cataracts or macular degeneration.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec10\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Sensitivity analysis\u003c/h2\u003e \u003cp\u003eCochrane\u0026rsquo;s Q and MR Egger intercepts were used to assess heterogeneity and horizontal pleiotropy. There was no significant heterogeneity or horizontal pleiotropy in the reanalysis after the SNPs that affected the results were eliminated \u003cb\u003e(Additional file: Table \u003cspan refid=\"MOESM2\" class=\"InternalRef\"\u003eS2\u003c/span\u003e and S3)\u003c/b\u003e. The stability of the SNPs employed in MR analysis was demonstrated by the leave-one-out method \u003cb\u003e(Additional file: Figure \u003cspan refid=\"MOESM1\" class=\"InternalRef\"\u003eS1\u003c/span\u003e, S2, S3, S4 ,S5 and S6)\u003c/b\u003e.\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eAccording to this MR research, HMGCR inhibition elevates the risk of allergic conjunctivitis and diabetic retinopathy. And PCSK9 inhibition elevates the risk of glaucoma but may be protective against allergic conjunctivitis. Significantly, examination of the GLGC dataset revealed a correlation between the inhibition of HMGCR and PCSK9 and the likelihood of developing uveitis. However, the analysis of the UK Biobank dataset did not yield similar results. Furthermore, no conclusive evidence was discovered regarding the correlation between lipid-lowering medicines and the development of cataracts and macular degeneration.\u003c/p\u003e \u003cp\u003eDiabetic retinopathy is a prevalent microvascular consequence of diabetes mellitus and a significant contributor to vision loss(22, 23). Dyslipidaemia is a significant risk factor for the development of diabetic retinopathy(24, 25). Statins are conventional lipid-modifying medications that effectively reduce LDL levels. Multiple observational studies have documented beneficial outcomes of statins on diabetic retinopathy. Animal studies have demonstrated that statins can enhance the treatment of diabetic retinopathy by inhibiting neovascularization(26, 27). However, the amount of evidence remained rather insufficient. Cohort research also found that statins have a beneficial effect on diabetic retinopathy(28). Nevertheless, the criteria used to choose participants for the study might have influenced the outcomes in a biased manner. Therefore, the precise impact of statin on diabetic retinopathy is still uncertain. In this work, we employed genetic big data mining to determine the correlation between statin usage and the likelihood of developing diabetic retinopathy. The MR analysis is conducted based on three assumptions, effectively mitigating the influence of confounding factors in the studies. In addition, we conducted a set of sensitivity studies and validated the eQTLs. Chen et al. similarly obtained similar results to ours(29). Furthermore, research found that statin medication results in increased levels of vascular endothelial growth factor (VEGF) in the vitreous of individuals with diabetic retinopathy. This, in turn, caused damage to the blood-retinal barrier, worsening the condition of diabetic retinopathy(30).\u003c/p\u003e \u003cp\u003eIt is debatable how statins affect eye health, but our study is the first to show that taking them raises the risk of allergic conjunctivitis. Several investigations have demonstrated that statins have important immunomodulatory effects in addition to decreasing cholesterol levels (31, 32). Its immunomodulatory activities, however, have a double-edged effect: while they raise the body's regulatory T cell (Treg) concentration, they also disturb the immune environment (33). This could be among the factors contributing to the increased risk of allergic conjunctivitis. Furthermore, our research indicated that PCSK9 inhibitors reduced the risk of allergic conjunctivitis, providing patients with a guidance for selecting lipid-lowering drugs.\u003c/p\u003e \u003cp\u003eThe role of PCSK9 inhibitors in ocular disease is also currently unclear. However, evidence from FAERS suggested that ocular adverse effects from PCSK9 inhibitors should be taken seriously. These adverse events included tearing, eye surgery, and seasonal allergies. Though the precise mechanism is unknown, it raises the question of whether PCSK9 inhibitors are beneficial or detrimental for eye illness, and whether they are genuinely linked to an increased risk of glaucoma? Since no prior research has demonstrated a link between PCSK9 inhibitors and glaucoma, we believe the findings of this investigation to be trustworthy. However, given the positive effects of lipid-lowering drugs in lowering cholesterol, we recommend that the results of this study be viewed with caution. To determine which course of treatment is best for patients, doctors and pharmacists should weigh the advantages and disadvantages while also applying their understanding of pharmacoeconomics.\u003c/p\u003e \u003cp\u003eOur study also has some shortcomings Firstly, we explored the causal relationship between lipid-lowering drugs and ocular diseases through gene-mimicking drug inhibitors, and we were unable to assess their pharmacological effects and physiological mechanisms. Secondly, we were only able to analyze the genetic data of European populations because of the restricted resources of the GWAS data. Furthermore, we were unable to validate the involvement of PCSK9 inhibitors in glaucoma because to the absence of PCSK9 eqtl data. Lastly, we were unable to stratify analyses for variables including age, sex, and disease subtype since we employed GWAS pooled data.\u003c/p\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn conclusion, our study found that HMGCR inhibitors lead to an increased risk of diabetic retinopathy and allergic conjunctivitis, whereas PCSK9 inhibitors induced glaucoma at the same time as they led to a decreased risk of allergic conjunctivitis. Further clinical trials and animal research are need to identify the precise mechanisms, though. We advise carefully weighing the advantages and disadvantages when selecting lipid-lowering medications because the results are solely based on Mendelian randomization study.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eSMR \u0026nbsp; \u0026nbsp; \u0026nbsp;summary-data-based Mendelian randomization\u003c/p\u003e\n\u003cp\u003eSNP \u0026nbsp; \u0026nbsp; \u0026nbsp;Single nucleotide polymorphism\u003c/p\u003e\n\u003cp\u003eIVW \u0026nbsp; \u0026nbsp; \u0026nbsp;Inverse variance weighted\u003c/p\u003e\n\u003cp\u003eIV \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Instrumental variable\u003c/p\u003e\n\u003cp\u003eLD \u0026nbsp; \u0026nbsp; \u0026nbsp; Linkage disequilibrium\u003c/p\u003e\n\u003cp\u003eHMGCR \u0026nbsp; 3-Hydroxy-9-methylglutaryl-coenzyme A reductase\u003c/p\u003e\n\u003cp\u003ePCSK9 \u0026nbsp; \u0026nbsp;Proprotein convertase subtilisin kexin-9\u003c/p\u003e\n\u003cp\u003eNPC1L1 \u0026nbsp; Niemann-Pick C1-Like 1\u003c/p\u003e\n\u003cp\u003eLDL-C \u0026nbsp; \u0026nbsp; Low-density lipoprotein cholesterol\u003c/p\u003e\n\u003cp\u003eCI \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; Confidence interval\u003c/p\u003e\n\u003cp\u003eOR \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Odds ratio\u003c/p\u003e\n\u003cp\u003eGLGC \u0026nbsp; \u0026nbsp; Global Lipids Genetics Consortium\u003c/p\u003e\n\u003cp\u003eMAF \u0026nbsp; \u0026nbsp; \u0026nbsp;Minor allele frequency\u003c/p\u003e\n\u003cp\u003eGWAS \u0026nbsp; \u0026nbsp; Genome-wide association study\u003c/p\u003e\n\u003cp\u003eFDA \u0026nbsp; \u0026nbsp; \u0026nbsp; Food and Drug Administration\u003c/p\u003e\n\u003cp\u003eCHD\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Coronary heart disease\u003c/p\u003e\n\u003cp\u003eeQTL \u0026nbsp; \u0026nbsp; \u0026nbsp;Expression quantitative trait loci\u003c/p\u003e\n\u003cp\u003eVEGF \u0026nbsp; \u0026nbsp;\u0026nbsp;Vascular endothelial growth factor\u003c/p\u003e\n\u003cp\u003eIEU \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Integrative Epidemiology Unit\u003c/p\u003e\n\u003cp\u003eGO \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Graves\u0026apos; ophthalmopathy\u003c/p\u003e\n\u003cp\u003eFAERS \u0026nbsp; \u0026nbsp; FDA Adverse Event Reporting System\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e \u003cstrong\u003eCompeting interests\u003c/strong\u003e \u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eEthics approval and consent to participate\u003c/strong\u003e \u003cp\u003eThe study used the large publicly available GWAS database, which has received approval from their relevant ethical review board and participants.\u003c/p\u003e \u003c/p\u003e \u003cp\u003e \u003cstrong\u003eCompeting interest\u003c/strong\u003e \u003cp\u003eThe authors have declared that there are no commercial or financial conflicts of interest in this work.\u003c/p\u003e \u003c/p\u003e\u003ch2\u003eFunding\u003c/h2\u003e \u003cp\u003eThis work was supported by the Doctoral Research Initiation Fund of Affiliated Hospital of Southwest Medical University.\u003c/p\u003e\u003ch2\u003eAuthor contributions\u003c/h2\u003e \u003cp\u003eWD, YH and LJ contributed to the research design, statistical analysis. MZ and QL contributed to the drafting and revision of the article. The final manuscript has been read and approved by all the listed authors.\u003c/p\u003e\u003ch2\u003eAcknowledgements\u003c/h2\u003e \u003cp\u003eThis study used public data from the GLGC, UK Biobank and IEU databases. We sincerely appreciate all participants and investigators for their valuable contribution in making statistics accessible and publicly available.\u003c/p\u003e\u003ch2\u003eAvailability of data and materials\u003c/h2\u003e \u003cp\u003eNo original data were generated in the present study. The datasets mentioned in this article are publicly available in the IEU database (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://gwas.mrcieu.ac.uk/).Geneti\u003c/span\u003e\u003cspan address=\"https://gwas.mrcieu.ac.uk/).Geneti\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003ec information on drug targets was derived from drugbank (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://go.drugbank.com/\u003c/span\u003e\u003cspan address=\"https://go.drugbank.com/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e). Cis-eqtls for HMGCR were obtained from (\u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.eqtlgen.org/cis-eqtls.html\u003c/span\u003e\u003cspan address=\"https://www.eqtlgen.org/cis-eqtls.html\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e).\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eFoster A, Gilbert C, Johnson G. Changing patterns in global blindness: 1988-2008. Community eye health. 2008;21(67):37-9.\u003c/li\u003e\n\u003cli\u003eAhmadi M, Amiri S, Pecic S, Machaj F, Rosik J, Łos MJ, et al. Pleiotropic effects of statins: A focus on cancer. Biochimica et biophysica acta Molecular basis of disease. 2020;1866(12):165968.\u003c/li\u003e\n\u003cli\u003eGuan ZW, Wu KR, Li R, Yin Y, Li XL, Zhang SF, et al. Pharmacogenetics of statins treatment: Efficacy and safety. 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Survey of ophthalmology. 2019;64(3):401-32.\u003c/li\u003e\n\u003cli\u003eHummelgaard S, Vilstrup JP, Gustafsen C, Glerup S, Weyer K. Targeting PCSK9 to tackle cardiovascular disease. Pharmacol Ther. 2023;249:108480.\u003c/li\u003e\n\u003cli\u003eLee GE, Kim J, Lee JS, Ko J, Lee EJ, Yoon JS. Role of Proprotein Convertase Subtilisin/Kexin Type 9 in the Pathogenesis of Graves' Orbitopathy in Orbital Fibroblasts. Front Endocrinol (Lausanne). 2020;11:607144.\u003c/li\u003e\n\u003cli\u003eZhao X, Wu J, Zhu S. Ocular disorders associated with PCSK9 inhibitors: A pharmacovigilance disproportionality analysis. British journal of clinical pharmacology. 2023;89(2):458-69.\u003c/li\u003e\n\u003cli\u003eJia L, Betters JL, Yu L. Niemann-pick C1-like 1 (NPC1L1) protein in intestinal and hepatic cholesterol transport. Annual review of physiology. 2011;73:239-59.\u003c/li\u003e\n\u003cli\u003eThang SK, Chen PY, Gao WY, Wu MJ, Pan MH, Yen JH. Xanthohumol Suppresses NPC1L1 Gene Expression through Downregulation of HNF-4\u0026alpha; and Inhibits Cholesterol Uptake in Caco-2 Cells. Journal of agricultural and food chemistry. 2019;67(40):11119-28.\u003c/li\u003e\n\u003cli\u003eDavies NM, Holmes MV, Davey Smith G. Reading Mendelian randomisation studies: a guide, glossary, and checklist for clinicians. BMJ (Clinical research ed). 2018;362:k601.\u003c/li\u003e\n\u003cli\u003eWiller CJ, Schmidt EM, Sengupta S, Peloso GM, Gustafsson S, Kanoni S, et al. Discovery and refinement of loci associated with lipid levels. Nature genetics. 2013;45(11):1274-83.\u003c/li\u003e\n\u003cli\u003eRichardson TG, Sanderson E, Palmer TM, Ala-Korpela M, Ference BA, Davey Smith G, et al. Evaluating the relationship between circulating lipoprotein lipids and apolipoproteins with risk of coronary heart disease: A multivariable Mendelian randomisation analysis. PLoS medicine. 2020;17(3):e1003062.\u003c/li\u003e\n\u003cli\u003eWang XF, Xu WJ, Wang FF, Leng R, Yang XK, Ling HZ, et al. Telomere Length and Development of Systemic Lupus Erythematosus: A Mendelian Randomization Study. Arthritis \u0026amp; rheumatology (Hoboken, NJ). 2022;74(12):1984-90.\u003c/li\u003e\n\u003cli\u003eBurgess S, Scott RA, Timpson NJ, Davey Smith G, Thompson SG. Using published data in Mendelian randomization: a blueprint for efficient identification of causal risk factors. European journal of epidemiology. 2015;30(7):543-52.\u003c/li\u003e\n\u003cli\u003eBurgess S, Dudbridge F, Thompson SG. Combining information on multiple instrumental variables in Mendelian randomization: comparison of allele score and summarized data methods. Statistics in medicine. 2016;35(11):1880-906.\u003c/li\u003e\n\u003cli\u003eBowden J, Davey Smith G, Burgess S. Mendelian randomization with invalid instruments: effect estimation and bias detection through Egger regression. 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Association of the Serum Total Cholesterol to Triglyceride Ratio with Diabetic Retinopathy in Chinese Patients with Type 2 Diabetes: A Community-Based Study. Diabetes Ther. 2019;10(2):597-604.\u003c/li\u003e\n\u003cli\u003eBusik JV. Lipid metabolism dysregulation in diabetic retinopathy. Journal of lipid research. 2021;62:100017.\u003c/li\u003e\n\u003cli\u003eWeis M, Heeschen C, Glassford AJ, Cooke JP. Statins have biphasic effects on angiogenesis. Circulation. 2002;105(6):739-45.\u003c/li\u003e\n\u003cli\u003eMiyahara S, Kiryu J, Yamashiro K, Miyamoto K, Hirose F, Tamura H, et al. Simvastatin inhibits leukocyte accumulation and vascular permeability in the retinas of rats with streptozotocin-induced diabetes. The American journal of pathology. 2004;164(5):1697-706.\u003c/li\u003e\n\u003cli\u003ePranata R, Vania R, Victor AA. Statin reduces the incidence of diabetic retinopathy and its need for intervention: A systematic review and meta-analysis. European journal of ophthalmology. 2021;31(3):1216-24.\u003c/li\u003e\n\u003cli\u003eChen C, Zhang H, Lan Y, Yan W, Liu S, Chen Y, et al. Statins as a risk factor for diabetic retinopathy: a Mendelian randomization and cross-sectional observational study. Journal of translational medicine. 2024;22(1):298.\u003c/li\u003e\n\u003cli\u003eSim\u0026oacute; R, Sundstrom JM, Antonetti DA. Ocular Anti-VEGF therapy for diabetic retinopathy: the role of VEGF in the pathogenesis of diabetic retinopathy. Diabetes care. 2014;37(4):893-9.\u003c/li\u003e\n\u003cli\u003eDehnavi S, Sohrabi N, Sadeghi M, Lansberg P, Banach M, Al-Rasadi K, et al. Statins and autoimmunity: State-of-the-art. Pharmacol Ther. 2020;214:107614.\u003c/li\u003e\n\u003cli\u003ePirmohamed M. Statins, immunomodulation, and infections: a complex and unresolved relationship. Clinical infectious diseases : an official publication of the Infectious Diseases Society of America. 2014;58(3):357-8.\u003c/li\u003e\n\u003cli\u003eGoldstein MR, Mascitelli L, Pezzetta F. The double-edged sword of statin immunomodulation. International journal of cardiology. 2009;135(1):128-30.\u003c/li\u003e\n\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"HMGCR, PCSK9, NPC1L1, Mendelian randomization, allergic conjunctivitis, diabetic retinopathy, glaucoma","lastPublishedDoi":"10.21203/rs.3.rs-4437336/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4437336/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eMost ocular diseases are associated with lipid metabolism, but the exact mechanisms are unclear. Statins, PCSK9 inhibitors and NPC1L1 inhibitors are common lipid-modulating agents. The aim of this study was to explore the causal relationship between common lipid-lowering drugs and ocular diseases through Mendelian randomization analysis.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eIn this study, we used the summary-data-based Mendelian randomization (SMR) method and inverse-variance-weighted Mendelian randomization (IVW-MR). Low-density lipoprotein cholesterol (LDL-C) was used as a biomarker. We then obtained instrumental variables (IVs) from the Global Lipids Genetics Consortium (GLGC) (n\u0026thinsp;=\u0026thinsp;173082) and UK Biobank (n\u0026thinsp;=\u0026thinsp;440546). The 3-Hydroxy-9-methylglutaryl-coenzyme A reductase (HMGCR) expression quantitative trait loci (eQTL) was obtained from a cohort study containing 31,684 blood samples. Summary data for ocular diseases were obtained from the Integrative Epidemiology Unit (IEU) database.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eIVW-MR showed that statins increased the risk of allergic conjunctivitis (OR\u0026thinsp;=\u0026thinsp;1.96, 95% CI: 1.30\u0026ndash;2.95, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.001) and diabetic retinopathy (OR\u0026thinsp;=\u0026thinsp;2.58, 95% CI: 1.67\u0026ndash;3.99, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001). PCSK9 inhibitors reduced the risk of allergic conjunctivitis (OR\u0026thinsp;=\u0026thinsp;0.67, 95% CI: 0.47\u0026ndash;0.95, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.02) but increased the risk of glaucoma (OR\u0026thinsp;=\u0026thinsp;1.23, 95% CI: 1.06\u0026ndash;1.43, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.006). The SMR approach showed that inhibition of HMGCR significantly elevated the risk of allergic conjunctivitis (OR\u0026thinsp;=\u0026thinsp;1.28, 95% CI: 1.11\u0026ndash;1.45, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001) and diabetic retinopathy (OR\u0026thinsp;=\u0026thinsp;1.56, 95% CI: 1.33\u0026ndash;1.84, \u003cem\u003eP\u003c/em\u003e\u0026thinsp;\u0026lt;\u0026thinsp;0.001).\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e \u003cp\u003eThe study found that statin elevated the risk of allergic conjunctivitis and diabetic retinopathy. PCSK9 inhibitors reduced the risk of allergic conjunctivitis but elevated the risk of glaucoma. But more mechanisms remain to be further explored.\u003c/p\u003e","manuscriptTitle":"Causal relationship between lipid-lowering drugs and ocular disorders: A drug-targeted Mendelian randomization study","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-08-13 17:12:52","doi":"10.21203/rs.3.rs-4437336/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"363ea597-507e-4032-9356-ab7f46a81cf2","owner":[],"postedDate":"August 13th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":34812263,"name":"Health sciences/Medical research"},{"id":34812264,"name":"Health sciences/Medical research/Outcomes research"}],"tags":[],"updatedAt":"2024-10-03T09:00:32+00:00","versionOfRecord":[],"versionCreatedAt":"2024-08-13 17:12:52","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4437336","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4437336","identity":"rs-4437336","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}