Organic cation transporter 1 variants and gastrointestinal side effects of metformin in patients with Type 2 diabetes

有机阳离子转运蛋白1变异体与2型糖尿病患者服用二甲双胍的胃肠道副作用

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Abstract

AIMS: Metformin is the most widely used oral anti-diabetes agent and has considerable benefits over other therapies, yet 20-30% of people develop gastrointestinal side effects, and 5% are unable to tolerate metformin due to the severity of these side effects. The mechanism for gastrointestinal side effects and their considerable inter-individual variability is unclear. We have recently shown the association between organic cation transporter 1 (OCT1) variants and severe intolerance to metformin in people with Type 2 diabetes. The aim of this study was to explore the association of OCT1 reduced-function polymorphisms with common metformin-induced gastrointestinal side effects in Type 2 diabetes. METHODS: This prospective observational cohort study included 92 patients with newly diagnosed Type 2 diabetes, incident users of metformin. Patients were genotyped for two common loss-of-function variants in the OCT1 gene (SLC22A1): R61C (rs12208357) and M420del (rs72552763). The association of OCT1 reduced-function alleles with gastrointestinal side effects was analysed using logistic regression. RESULTS: Forty-three patients (47%) experienced gastrointestinal adverse effects in the first 6 months of metformin treatment. Interestingly, the number of OCT1 reduced-function alleles was significantly associated with over two-fold higher odds of the common metformin-induced gastrointestinal side effects (odds ratio = 2.31, 95% confidence interval 1.07-5.01, P = 0.034). CONCLUSIONS: In conclusion, we showed for the first time the association between OCT1 variants and common metformin-induced gastrointestinal side effects. These results confirm recent findings related to the role of OCT1 in severe metformin intolerance, and suggest that high inter-individual variability in mild/moderate and severe gastrointestinal intolerance share a common underlying mechanism. These data could contribute to more personalized and safer metformin treatment.

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