ArticleFrontiers in pharmacology2025
Proton pump inhibitors use and risk of type 2 diabetes mellitus: correlation analysis, prediction model construction, and key genes identification.
Article in Frontiers in pharmacology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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Who cites it
1 citing paper in PubMed.
- Comparative evaluation of pregnancy-related adverse events associated with proton pump inhibitors using the FDA adverse event reporting system database.International journal of clinical pharmacy · 2025Article
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2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
Introduction: Prior cohort studies reported paradoxical results between proton pump inhibitor (PPI) usage and the risk of type 2 diabetes mellitus (T2DM). We investigated the correlation between the use of PPIs and T2DM risk, constructed predictive models, and identified the key genes involved. Methods: In the correlation analysis, we extracted and analyzed the data from the National Health and Nutrition Examination Survey (NHANES) database and the FDA Adverse Event Reporting System (FAERS) database to examine the relationship between the use of PPIs and T2DM risk. Then, a nomogram was constructed to estimate the T2DM risk probability in patients treated with PPIs by using the optimal predictors identified by the least absolute shrinkage and selection operator and logistic regression methods. Finally, we investigated the key genes modulated by PPI usage in patients with T2DM by combining various bioinformatics techniques such as network pharmacology, difference analysis, and weighted gene co-expression network analysis. Results: In the NHANES database, regardless of whether PPI usage was merely included or used to adjust for covariates, the binomial regression models indicated a positive correlation between PPI usage and T2DM risk (all p < 0.001). In the FAERS database, the T2DM signal for patients using PPIs was significant (lower limit of the reporting odds ratio was greater than 1). Sex, race, age, educational level, obesity, hypertension, and high cholesterol were included in the nomogram to predict the probability of PPI usage-induced T2DM risk (all p < 0.05). By intersecting the key cluster and the intersection of PPI usage-related genes and T2DM-related genes, we finally identified two crucial genes, AGT and JAK2, that may be involved in PPI usage-induced T2DM risk. Discussion: Our findings revealed that PPI treatment can increase the risk of T2DM. Additionally, we were successful in constructing a new nomogram to identify individuals at high risk of developing T2DM among patients using PPIs and completed a preliminary exploration of possible gene targets and mechanisms. Our study will be useful in alerting clinicians to the T2DM risk involved in PPI treatment and allowing them to take early prevention and intervention measures.
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