ArticleFrontiers in endocrinology2023
Potential disease biomarkers for diabetic retinopathy identified through Mendelian randomization analysis.
Article in Frontiers in endocrinology, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed, 11 citations in OpenAlex.
- Hormonal metabolic burden in diabetic retinopathy: the diabetic retina as an endocrine-responsive target organ.Frontiers in endocrinology · 2026Review
- The Causal Relationship and Association between Biomarkers, Dietary Intake, and Diabetic Retinopathy: Insights from Mendelian Randomization and Cross-Sectional Study.Diabetes & metabolism journal · 2025Article
- Article
- Enhancement of activation-induced T cell proliferation by SIRPG in a CD47-independent manner.Frontiers in immunology · 2025Article
- Pinpointing Novel Plasma and Brain Proteins for Common Ocular Diseases: A Comprehensive Cross-Omics Integration Analysis.International journal of molecular sciences · 2024Article
- Transcriptome sequencing and Mendelian randomization analysis identified biomarkers related to neutrophil extracellular traps in diabetic retinopathy.Frontiers in immunology · 2024Article
Corrections and comments
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Authors and funding
3 authors at 3 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Diabetic retinopathy (DR), a leading cause of vision loss, has limited options for effective prevention and treatment. This study aims to utilize genomics and proteomics data to identify potential drug targets for DR. Methods: We utilized plasma protein quantitative trait loci data from the Atherosclerosis Risk in Communities Study and the Icelandic Decoding Genetics Study for discovery and replication, respectively. Genetic associations with DR, including its subtypes, were derived from the FinnGen study. Mendelian Randomization (MR) analysis estimated associations between protein levels and DR risk, complemented by colocalization analysis to examine shared causal variants. Results: Our MR analysis identified significant associations of specific plasma proteins with DR and proliferative DR (PDR). Elevated genetically predicted levels of WARS (OR = 1.16; 95% CI = 0.095-0.208, FDR = 1.31×10 Conclusions: Our study highlights WARS, SIRPG, and ALDOC as significant proteins associated with DR and PDR, providing a basis for further exploration in drug development. Additional studies are needed to validate these proteins as disease biomarkers across diverse populations.
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