ArticleFrontiers in endocrinology2024
Unveiling the molecular landscape of PCOS: identifying hub genes and causal relationships through bioinformatics and Mendelian randomization.
Article in Frontiers in endocrinology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- CD93 in Health and Disease: Bridging Physiological Functions and Clinical Applications.International journal of molecular sciences · 2025Review
- Exploration of key genes associated with oxidative stress in polycystic ovary syndrome and experimental validation.Frontiers in medicine · 2025Article
Corrections and comments
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Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Polycystic ovary syndrome (PCOS) is a complex endocrine disorder with various contributing factors. Understanding the molecular mechanisms underlying PCOS is essential for developing effective treatments. This study aimed to identify hub genes and investigate potential molecular mechanisms associated with PCOS through a combination of bioinformatics analysis and Mendelian randomization (MR). Methods: This study employed bioinformatics analysis in conjunction with MR methods using publicly available databases to identify hub genes. We employed complementary MR methods, including inverse-variance weighted (IVW), to determine the causal relationship between the hub genes and PCOS. Sensitivity analyses were performed to ensure results reliability. Enrichment analysis and immune infiltration analysis were further conducted to assess the role and mechanisms of hub genes in the development of PCOS. Additionally, we validated hub gene expression in both an animal model and serum samples from PCOS patients using qRT-PCR. Results: IVW analysis revealed significant associations between 10 hub genes and the risk of PCOS: CD93 [ Conclusions: Our bioinformatics combined with MR analysis revealed that CD93, CYBB, DOCK8, IRF1, MBOAT1, MYO1F, NLRP1, NOD2, PIK3R1 increase the risk of PCOS, while PTER decreases the risk of PCOS. This discovery has implications for clinical decision-making in terms of disease diagnosis, prognosis, treatment strategies, and opens up novel avenues for drug development.
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Registered trials
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