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<p>Polycystic ovary syndrome (PCOS) is a prevalent endocrine and metabolic disorder characterized by ovarian dysfunction, polycystic ovarian morphology, and hyperandrogenism. Genetic factors, including polymorphisms in microRNA (miRNAs) genes, are believed to influence its pathogenesis. This case-control study aimed to investigate the association between polymorphisms in <i>miR-196a-2</i> (rs11614913), <i>miR-146a</i> (rs6864584), and <i>miR-143/145</i> (rs41291957) and the risk of PCOS in women from Zahedan, Iran. The study comprised 286 participants: 143 women diagnosed with PCOS and 143 age-matched healthy controls. Genomic DNA was extracted from peripheral blood samples using the salting-out method. Target regions were amplified by polymerase chain reaction (PCR), and genotyping was performed by restriction fragment length polymorphism (RFLP) analysis using the enzymes <i>MspI</i> (rs11614913 and rs41291957) and <i>ApaI</i> (rs6864584). The <i>miR-146a</i> rs6864584 C allele significantly increased PCOS risk, with TC (OR = 2.51) and CC (OR = 2.71) genotypes conferring &gt; 2.5-fold higher risk versus TT. Conversely, the <i>miR-196a2</i> rs11614913 CT genotype showed a protective effect (42% reduced risk, OR = 0.58). No association was found for <i>miR-143/145</i> rs41291957. Both <i>miR-146a</i> and <i>miR-196a-2</i> variants were linked to metabolic disturbances (higher waist circumference, glucose, lipids, prolactin), while <i>miR-143/145</i> was associated with increased body mass index. Gene-gene interactions modulated risk: the GG-TT-CT combination reduced risk by 78%, whereas GG-TT-TT increased risk &gt; 3-fold. This study identifies <i>miR-146a</i> rs6864584 as a potential risk variant and <i>miR-196a2</i> rs11614913 (CT) as a protective genotype for PCOS. These findings highlight the role of miRNA polymorphisms in PCOS pathogenesis and their potential value as biomarkers for disease risk and mechanistic insight.</p> Graphical Abstract <p></p>

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Association of miR-196a-2, miR-146a, and miR-143/145 Polymorphisms with Polycystic Ovary Syndrome: A Case–Control Study

  • 期刊论文

  • 发表日期：

    2026年6月19日

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  • Narges Khatoun Mohagheghi,
  • Mahboobeh Sabeti Akbar-Abad,
  • Mahdi Majidpour,
  • Saman Sargazi,
  • Marzieh Ghasemi,
  • Ramin Saravani

摘要

Polycystic ovary syndrome (PCOS) is a prevalent endocrine and metabolic disorder characterized by ovarian dysfunction, polycystic ovarian morphology, and hyperandrogenism. Genetic factors, including polymorphisms in microRNA (miRNAs) genes, are believed to influence its pathogenesis. This case-control study aimed to investigate the association between polymorphisms in miR-196a-2 (rs11614913), miR-146a (rs6864584), and miR-143/145 (rs41291957) and the risk of PCOS in women from Zahedan, Iran. The study comprised 286 participants: 143 women diagnosed with PCOS and 143 age-matched healthy controls. Genomic DNA was extracted from peripheral blood samples using the salting-out method. Target regions were amplified by polymerase chain reaction (PCR), and genotyping was performed by restriction fragment length polymorphism (RFLP) analysis using the enzymes MspI (rs11614913 and rs41291957) and ApaI (rs6864584). The miR-146a rs6864584 C allele significantly increased PCOS risk, with TC (OR = 2.51) and CC (OR = 2.71) genotypes conferring > 2.5-fold higher risk versus TT. Conversely, the miR-196a2 rs11614913 CT genotype showed a protective effect (42% reduced risk, OR = 0.58). No association was found for miR-143/145 rs41291957. Both miR-146a and miR-196a-2 variants were linked to metabolic disturbances (higher waist circumference, glucose, lipids, prolactin), while miR-143/145 was associated with increased body mass index. Gene-gene interactions modulated risk: the GG-TT-CT combination reduced risk by 78%, whereas GG-TT-TT increased risk > 3-fold. This study identifies miR-146a rs6864584 as a potential risk variant and miR-196a2 rs11614913 (CT) as a protective genotype for PCOS. These findings highlight the role of miRNA polymorphisms in PCOS pathogenesis and their potential value as biomarkers for disease risk and mechanistic insight.

Graphical Abstract