Categories
Nevin Manimala Statistics

Drug-gene interactions and the risk of diabetic microvascular complications: A population-based cohort study

Diabetes Obes Metab. 2026 Jan 26. doi: 10.1111/dom.70501. Online ahead of print.

ABSTRACT

AIMS: Drug-gene interactions (DGIs) modify drug response and safety, yet their influence on diabetic microvascular complications remains unclear. This study aimed to elucidate the role of DGIs in these complications.

MATERIALS AND METHODS: Using UK Biobank (UKB) data, we identified medications frequently prescribed to individuals with diabetes and defined DGIs based on the Food and Drug Administration (FDA) and the Clinical Pharmacogenetics Implementation Consortium (CPIC) guidelines. Associations between DGIs and diabetic microvascular complications were evaluated using Cox proportional hazards models, which are suited for longitudinal time-to-event data. Two complementary analyses were performed: (1) a therapeutic class-level analysis among medication users, and (2) a genotype-level analysis among individuals with non-normal metabolizer phenotypes who used the corresponding medications.

RESULTS: We identified 368 medications preferentially used among participants with diabetes, primarily cardiovascular agents and detected 55 clinically relevant DGIs implicating 30 medications and 7 genes. Among users of antithrombotic agents, the presence of DGIs was associated with diabetic kidney disease (DKD) (hazard ratio [HR]: 1.44, 95% confidence interval [CI]: 1.12-1.86) and diabetic neuropathy (DN) (HR: 2.13, 95% CI: 1.39-3.28). Likewise, among individuals with non-normal metabolizer status for CYP2C19 or CYP2D6, DGIs conferred elevated risks for DKD and DN (HR range: 1.26-2.11). However, no significant association was found between DGI and DR.

CONCLUSION: This study provides the first comprehensive assessment of DGIs and diabetic microvascular complications. DGIs involving antithrombotic agents and non-normal CYP2C19 or CYP2D6 metabolizers were significantly linked to higher risks of DKD and DN. These findings underscore the potential of pharmacogenomic-guided prescribing to enhance drug safety.

PMID:41582657 | DOI:10.1111/dom.70501

By Nevin Manimala

Portfolio Website for Nevin Manimala