Angiotensin-Converting Enzyme Gene Polymorphisms and Diabetic Neuropathy: Insights from a Scoping Review and Scientometric Analysis

血管紧张素转换酶基因多态性与糖尿病神经病变:范围界定综述和科学计量分析的启示

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Abstract

BACKGROUND/OBJECTIVES: Diabetic neuropathy (DN) is one of the most common and disabling complications of diabetes mellitus (DM), affecting motor, sensory, and autonomic nerves. Genetic factors, particularly polymorphisms in the Angiotensin-converting enzyme (ACE) gene, have been proposed as contributors to DN susceptibility. This study aimed to synthesize the scientific evidence on ACE gene polymorphisms and their association with DN through a scoping review combined with scientometric analysis. METHODS: A comprehensive search of PubMed, Scopus, and Web of Science was performed in February 2025, following JBI and PRISMA-ScR guidelines. Observational studies involving individuals with DN and the genotyping of ACE polymorphisms were included. Scientometric mapping was conducted using the Bibliometrix package in RStudio to identify publication trends and key thematic terms. RESULTS: From 100 screened articles, 11 met the inclusion criteria. Most studies (72.7%) addressed diabetic peripheral neuropathy, while 27.3% investigated cardiac autonomic neuropathy. All studies analyzed the I/D polymorphism in intron 16 of the ACE gene. The D allele and DD genotype were associated with increased susceptibility to DN in over half of the studies (6/11), while the II genotype was reported as protective in 3/11. Findings varied by ethnicity and study design. The scientometric analysis identified 'peripheral diabetic neuropathy', type 2 diabetes', and 'ACE gene polymorphism' as the most frequently co-occurring terms, indicating that research on this topic has been concentrated around these themes, while showing limited diversity in geographic origin and scope. CONCLUSIONS: ACE I/D polymorphism appears to modulate susceptibility to DN, though interethnic variability and methodological heterogeneity challenge definitive conclusions. Broader, standardized studies are needed to validate its utility as a predictive biomarker.

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