4.7 Article

Association between Polymorphisms of OCT1 and Metabolic Response to Metformin in Women with Polycystic Ovary Syndrome

Journal

Publisher

MDPI
DOI: 10.3390/ijms20071720

Keywords

polycystic ovary syndrome; metformin; polymorphisms; OCT1

Funding

  1. National Cheng Kung University Hospital [NCKUH-10407023]
  2. Ministry of Science and Technology of Taiwan [MOST 107-2320-B-006 -071]
  3. Headquarters of University Advancement at the National Cheng Kung University, Taiwan - Ministry of Education [D105-35A06]

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Insulin-sensitizer treatment with metformin is widely used in polycystic ovary syndrome (PCOS). However, the treatment effectiveness shows individual differences in PCOS patients. Organic cation transporter (OCT) 1 and 2 have been reported to mediate metformin transport in the liver and kidney, respectively. In this study, we investigated the association between the polymorphisms of OCT1 and OCT2 and the treatment effectiveness of metformin in PCOS patients. The single nucleotide polymorphisms (SNPs) of OCT1 (rs683369 and rs628031) and OCT2 (rs316019) were analyzed in 87 PCOS and 113 control women. Oral glucose tolerance tests (OGTTs), which represented metformin treatment response, were conducted at the start of treatment and after six-month treatment. The results demonstrated that the SNP frequencies of OCT1 and OCT2 were not associated with PCOS pathophysiology, and that the polymorphisms of OCT1 and OCT2 were not associated with the OGTT parameters at baseline. However, PCOS patients with the G allele of OCT1 rs683369 and/or with the A allele of OCT1 rs628031 had increased insulin sensitivity compared to those with wild-type genotype after receiving metformin treatment. Moreover, the interactions of metformin*SNP were significant in both OCT1 rs683369 (p < 0.001) and rs628031 (p = 0.001) during the treatment period. Taken together, genetic polymorphisms of OCT1 contributed to different metformin treatment responses, and further study is needed to establish personalized treatment programs using a pharmacogenomic algorithm approach in PCOS patients.

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