Abstract

ABSTRACT Observational studies have been conducted to investigate the correlation between adiponectin and diabetic retinopathy (DR), but no consistent relationship has been established. In this study, we employed an integrative analysis that combined Mendelian randomization (MR) and bioinformatics analyses to comprehensively explore the association between DR and adiponectin, aiming to provide a unified answer of their relationship. Using the inverse-variance weighted (IVW) method, the odd ratio (OR) of developing DR per 1 mg/dL increment in genetically predicted log-transformed adiponectin concentration was estimated to be 0.949 (P = 0.557). Other robust MR methods produced consistent results, confirming the absence of a causal effect of adiponectin on DR. Additionally, the expression levels of the six adiponectin-related genes showed no significant differences among normal controls, individuals with diabetes but without DR, and those with DR Furthermore, the biological pathways enriched by these genes were not strongly relevant to DR. At both the individual gene and pathway levels, there were no overlaps between the adiponectin-related genes and the differentially expressed genes, indicating a lack of association between adiponectin and DR based on gene expression profiles. In summary, the integrative analysis, which combined MR and bioinformatics data mining, yielded compelling evidence supporting the notion that adiponectin is not a risk factor for DR.

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