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Type 2 diabetes mellitus is one of the leading causes of morbidity and mortality in the world. The two main components of the mechanism underlying T2DM are insulin resistance and impaired insulin secretion. The current algorithmic approach to the treatment of the disease does not take the individual genetic makeup of patients into consideration. However, multiple gene variants affect the efficacy and metabolism of anti-diabetes medications. For example, MATE1 works in conjunction with OCT1 and OCT2 to regulate metformin elimination, the rs1801282 (Pro12Ala) single nucleotide polymorphism is associated with a better therapeutic response to pioglitazone across different populations, and the K allele of KCNJ11 rs5219 (E23K) polymorphism is associated with a greater HbA1c reduction in Caucasian and Chinese patients treated with gliclazide, a sulfonylurea. Modern genetic techniques have ushered in the era of pharmacogenomics and precision medicine, identifying genetic variations that can be translated into personalized treatment approaches, improved diabetes risk prediction, ethnic-specific insights, identification of new drug targets, and reduction of adverse drug reactions. Challenges in the implementation of pharmacogenomics in the treatment of Type 2 diabetes include modest effect sizes of many genetic variants, heterogeneity of the disease due to complex interactions between genetics, environment, and lifestyles, and the cost of genetic testing and analysis. Therefore, this review summarizes the genetic variations affecting each major class of non-insulin anti-diabetes medications.
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