Potential disease biomarkers for diabetic retinopathy identified through Mendelian randomization analysis

Abstract

BackgroundDiabetic 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.MethodsWe 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.ResultsOur 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 = 1.31×10-4) and SIRPG (OR = 1.15; 95% CI = 0.071-0.201, FDR = 1.46×10-2) were associated with higher DR risk, while increased levels of ALDOC (OR = 1.56; 95% CI = 0.246-0.637, FDR = 5.48×10-3) and SIRPG (OR = 1.15; 95% CI = 0.068-0.208, FDR = 4.73×10-2) were associated with higher PDR risk. These findings were corroborated by strong colocalization evidence.ConclusionsOur 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.