The involvement of polymorphisms in the MALAT1 and NEAT1 lncRNA genes in PCOS etiology

Abstract Background Hormonal imbalance and metabolic inefficiency are hallmarks of the common complicated endocrine condition known as polycystic ovary syndrome (PCOS). Long non-coding RNAs (lncRNAs) have emerged as critical regulators of gene expression and cellular processes in various diseases, including PCOS. This study aims to investigate the relationship between specific polymorphisms in the lncRNA genes MALAT1 (rs3200401) and NEAT1 (rs674485) and the likelihood of developing PCOS. A case-control study was conducted involving PCOS women and control undergoing in vitro fertilization (IVF) at the Center for Human Reproduction and IVF in Rostov-on-Don, Russia. Genotyping was conducted using an allele-specific real-time PCR approach. Results Our results suggest a possible association between MALAT1 rs3200401 and increased PCOS risk at the allelic level. While the difference observed in the GA genotype of NEAT1 rs674485 did not reach statistical significance and required confirmation in larger cohorts. In addition, deviation from the Hardy–Weinberg equilibrium was observed in control groups, which may reflect sample size limitations or population-specific effects. Bioinformatic analyses indicated that both variants may potentially influence the lncRNA secondary structure and microRNA binding sites; however, these findings are computational predictions and require experimental validation. Conclusion These findings underscore the potential of MALAT1 and NEAT1 genetic variants as biomarkers and therapeutic targets in PCOS.

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Publication Details

Journal
Egyptian Journal of Medical Human Genetics
Published
2026-09-28
DOI
https://doi.org/10.1186/s43042-026-00913-w
Primary Topic
Cancer-related molecular mechanisms research
Type
article
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article

The involvement of polymorphisms in the MALAT1 and NEAT1 lncRNA genes in PCOS etiology

Svetlana V. Lomteva, Manar Noor Aldeen Ammar, Karina Y. Sagamonova, А. А. Александрова et al.
Egyptian Journal of Medical Human Genetics
Cancer-related molecular mechanisms research
article

The involvement of polymorphisms in the MALAT1 and NEAT1 lncRNA genes in PCOS etiology

Svetlana V. Lomteva, Manar Noor Aldeen Ammar, Karina Y. Sagamonova, А. А. Александрова, Ruba Mohamed Ali, Sofya Yachneva
article en

Abstract

Abstract Background Hormonal imbalance and metabolic inefficiency are hallmarks of the common complicated endocrine condition known as polycystic ovary syndrome (PCOS). Long non-coding RNAs (lncRNAs) have emerged as critical regulators of gene expression and cellular processes in various diseases, including PCOS. This study aims to investigate the relationship between specific polymorphisms in the lncRNA genes MALAT1 (rs3200401) and NEAT1 (rs674485) and the likelihood of developing PCOS. A case-control study was conducted involving PCOS women and control undergoing in vitro fertilization (IVF) at the Center for Human Reproduction and IVF in Rostov-on-Don, Russia. Genotyping was conducted using an allele-specific real-time PCR approach. Results Our results suggest a possible association between MALAT1 rs3200401 and increased PCOS risk at the allelic level. While the difference observed in the GA genotype of NEAT1 rs674485 did not reach statistical significance and required confirmation in larger cohorts. In addition, deviation from the Hardy–Weinberg equilibrium was observed in control groups, which may reflect sample size limitations or population-specific effects. Bioinformatic analyses indicated that both variants may potentially influence the lncRNA secondary structure and microRNA binding sites; however, these findings are computational predictions and require experimental validation. Conclusion These findings underscore the potential of MALAT1 and NEAT1 genetic variants as biomarkers and therapeutic targets in PCOS.

Egyptian Journal of Medical Human GeneticsVol. 27(1)
Southern Federal University (RU), Rostov State Medical University (RU), Volgograd State University (RU)
Good health and well-being
Openalex Percentile: Top 16%
Cancer-related molecular mechanisms research
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