AI Article Synopsis

  • Metformin is commonly used to treat type 2 diabetes, but individual responses to the drug can vary significantly, potentially due to genetic differences.
  • A study analyzed the effects of specific genetic variants on metformin response in 299 patients, identifying the rs12208357 variant as significantly impacting treatment outcomes.
  • Machine learning models incorporating genetic and clinical factors, like gender and body measurements, were developed to better predict metformin response, showing potential for personalized diabetes treatment approaches.

Article Abstract

Metformin is an oral hypoglycemic agent widely used in clinical practice for treatment of patients with type 2 diabetes mellitus (T2DM). The wide interindividual variability of response to metformin therapy was shown, and recently the impact of several genetic variants was reported. To assess the independent and combined effect of the genetic polymorphism on glycemic response to metformin, we performed an association analysis of the variants in , , , and genes with metformin response in 299 patients with T2DM. Likewise, the distribution of allele and genotype frequencies of the studied gene variants was analyzed in an extended group of patients with T2DM ( = 464) and a population group ( = 129). According to our results, one variant, rs12208357 in the gene, had a significant impact on response to metformin in T2DM patients. Carriers of genotype and allele had a lower response to metformin compared to carriers of / genotypes and allele (-value = 0.0246, -value = 0.0059, respectively). To identify the parameters that had the greatest importance for the prediction of the therapy response to metformin, we next built a set of machine learning models, based on the various combinations of genetic and phenotypic characteristics. The model based on a set of four parameters, including gender, rs12208357 genotype, familial T2DM background, and waist-hip ratio (WHR) showed the highest prediction accuracy for the response to metformin therapy in patients with T2DM (AUC = 0.62 in cross-validation). Further pharmacogenetic studies may aid in the discovery of the fundamental mechanisms of type 2 diabetes, the identification of new drug targets, and finally, it could advance the development of personalized treatment.

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Source
http://www.ncbi.nlm.nih.gov/pmc/articles/PMC9330240PMC
http://dx.doi.org/10.3390/genes13081310DOI Listing

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