Metformin in Diabetic Retinopathy: Mechanisms, Therapeutic Potential, and Barriers
Abstract
The primary aim of diabetic retinopathy (DR) management is to prevent or slow the decline of vision loss. While current treatments for DR are effective in the advanced stages, they may not be as effective in the early phases of the disease. Metformin is among the most widely used antidiabetic medications and has recently shown promising outcomes in DR, as it has been found to affect several pathological mechanisms involved in DR, including oxidative stress, angiogenesis, and inflammation. Multiple clinical and preclinical studies demonstrated its potential role in reducing DR development and progression. However, the potential adverse effects, safety concerns, especially in patients with renal impairment, and the lack of large-scale studies supporting this evidence remain a barrier. This review explores the mechanisms through which metformin may exert its therapeutic effects in DR, discusses the clinical evidence, and identifies the limitations of metformin's potential use in DR treatment.
Read the paper
Related studies
- Increased expression of circulating miRNA-93 in women with polycystic ovary syndrome may represent a novel, non-invasive biomarker for diagnosis
- Identification of key genes associated with polycystic ovary syndrome (PCOS) and ovarian cancer using an integrated bioinformatics analysis
- Identification of key pathways and genes in polycystic ovary syndrome via integrated bioinformatics analysis and prediction of small therapeutic molecules
- Regulation of Androgen Receptor Expression Alters AMPK Phosphorylation in the Endometrium: In Vivo and In Vitro Studies in Women with Polycystic Ovary Syndrome
- Effect of oral administration of low-dose follicle stimulating hormone on hyperandrogenized mice as a model of polycystic ovary syndrome
- Systems pharmacology to investigate the interaction of berberine and other drugs in treating polycystic ovary syndrome
Go deeper in Evidence Hub
Evidence Hub adds a study data sheet (design, sample size, evidence level, key numbers), an AI summary and a chat grounded in the paper's text.