Glutathione S-transferase gene polymorphisms in diabetes mellitus: A bibliometric analysis and future directions

Glutathione S-transferases (GSTs) are key detoxification enzymes involved in cellular defense against oxidative stress. Polymorphisms in GST genes have been implicated in increased susceptibility to diabetes mellitus (DM) and its associated complications. Despite their clinical relevance, the global research landscape on this aspect remains insufficiently characterized. This analysis is significant as it represents the first attempt to map global research on GST polymorphisms in diabetes. The findings provide insights to guide future studies and support precision-medicine approaches. This study aimed to conduct a comprehensive bibliometric analysis of global literature on GST gene polymorphisms in the context of diabetes mellitus, highlighting trends, collaborations, and thematic developments. A bibliometric search was performed using the Scopus database for publications from 2000 to 2025. Articles were retrieved using defined keywords related to GST polymorphisms and diabetes. VOSviewer and Microsoft Excel were used for data processing, including co-authorship networks, institutional and journal productivity, and keyword co-occurrence analysis. Of the 170 documents retrieved, 125 were included in the final analysis. India contributed the highest proportion (31.76%) of publications, followed by the United States and Iran. Twelve countries formed two major collaborative clusters, with India exhibiting the strongest co-authorship links Geographically, India, the United States, and Iran were among the leading contributors, reflecting both regional disease burden and research capacity. Most studies were conducted in Asian populations, consistent with the high prevalence of diabetes in the region. Institutions such as the Biomedical Research Laboratories (Japan) and the Lund University Diabetes Centre (Sweden) ranked highest in citation impact. Keyword analysis revealed five major clusters related to oxidative stress, gene-environment interactions, gestational diabetes, meta-analyses, and GSTP1 SNPs. Overlay visualization indicated a shift from mechanistic research to clinical applications over time. The analysis is limited by reliance on a single bibliographic database, which may inherently underrepresent non-English publications. Research on GST polymorphisms in relevance with diabetes has evolved significantly, progressing toward translational relevance. Emerging themes reflect increasing complexity and underscore opportunities for precision medicine.