ORIGINAL RESEARCH article
Front. Endocrinol.
Sec. Diabetes: Molecular Mechanisms
Volume 16 - 2025 | doi: 10.3389/fendo.2025.1632691
This article is part of the Research TopicEnhancing Research on Drug Small Molecules and Target Proteins for the Treatment of Genetic DiseasesView all 5 articles
Development of targeted drugs for diabetic retinopathy using Mendelian randomized pharmacogenomics
Provisionally accepted
- Fourth Affiliated Hospital of Harbin Medical University, Harbin, China
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Purpose: This study aims to utilize genetic instrumental variables - protein quantitative trait loci (pQTL), and through analysis methods such as Mendelian randomization (MR), systematically screen and validate druggable proteins that have a causal relationship with diabetic retinopathy (DR), and further explore related drug targets, providing genetic evidence and new directions for the drug development of this disease. Methods: The research was based on large-scale public databases to conduct two-sample Mendelian randomization (MR) analysis. Firstly, 511 encoded proteins were selected from the known 4,479 druggable genes as initial exposure factors, with the summary data of GWAS for diabetic retinopathy as the outcome. MR analysis was conducted using the inverse variance weighted (IVW) method and the Wald ratio method, and strict screening was performed through Bonferroni correction. For the significantly associated proteins, heterogeneity tests, pleiotropy tests, leave-one-out analysis, and Steiger directionality tests were further conducted to verify the robustness of the results. Additionally, summary MR (SMR) analysis and colocalization analysis (coloc) were used to confirm the reliability of the causal relationship. Finally, a protein-protein interaction (PPI) network was constructed using the STRING database, and potential targeted drugs were mined from the DrugBank and DSigDB databases.
Keywords: Diabetic Retinopathy, drug target, Mendelian Randomization, Latest updated articles, Network analysis
Received: 22 May 2025; Accepted: 15 Sep 2025.
Copyright: © 2025 Liu, Tian, Li, Wang, Zhang, Bai and Zhang. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence: Guodan Liu, lgdeye@126.com
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