Polycystic ovary syndrome is a multifactorial condition associated with reproductive and endocrine organs and might cause infertility and metabolic abnormalities in childbearing age. PCOS seems to be a multifactorial disorder resulting from the combination of several genetic and environmental factors. Little research has been conducted to date on the impact of polymorphisms in infertility. We aim to review the appearance of polymorphisms in females of diverse ethnicities and their effect on infertility in the population with polycystic ovary syndrome. There have been numerous reports of the importance of the steroidogenesis pathway and genetic variants in PCOS pathogenesis. The most important genes that play a role in the aetiology of PCOS are CYP11A1, CYP17A1, and CYP19A1. We evaluated the occurrence of polymorphisms in various ethnicities in the CYP11A1, CYP17A1, and CYP19A1 genes and their efficacy on increasing PCOS risk with infertility. Our findings revealed that polymorphisms in various ethnicities are associated with the risk of PCOS with infertility. Although conflicting results regarding CYP11A1, CYP17A1, and CYP19A1 polymorphisms and their influence on PCOS with infertility have been reported in a small number of papers, the authors feel this may be attributable to the sample size and ethnic composition of the examined populations. In conclusion, our study strongly suggests that the CYP11A1, CYP17A1, and CYP19A1 genes might significantly enhance the probability of developing PCOS with infertility.

Polycystic ovary syndrome (PCOS) affects reproductive-age women. This condition causes infertility, insulin resistance, obesity, and heart difficulties. The molecular basis and mechanism of PCOS might potentially generate effective treatments. Long non-coding RNAs (lncRNAs) show control over multifactorial disorders’ growth and incidence. Numerous studies have emphasized its significance and alterations in PCOS. We used bioinformatic methods to find novel dysregulated lncRNAs in PCOS. To achieve this objective, the gene expression profile of GSE48301, comprising PCOS patients and normal control tissue samples, was evaluated using the R limma package with the following cut-off criterion: p-value < 0.05. Firstly, weighted gene co-expression network analysis (WGCNA) was used to determine the co-expression genes of lncRNAs; subsequently, hub gene identification and pathway enrichment analysis were used. With the defined criteria, nine novel dysregulated lncRNAs were identified. In WGCNA, different colors represent different modules. In the current study, WGCNA resulted in turquoise, gray, blue, and black co-expression modules with dysregulated lncRNAs. The pathway enrichment analysis of these co-expressed modules revealed enrichment in PCOS-associated pathways, including gene expression, signal transduction, metabolism, and apoptosis. In addition, CCT7, EFTUD2, ESR1, JUN, NDUFAB1, CTTNB1, GRB2, and CTNNB1 were identified as hub genes, and some of them have been investigated in PCOS. This study uncovered nine novel PCOS-related lncRNAs. To confirm how these lncRNAs control translational modification in PCOS, functional studies are required.

Polycystic ovary syndrome (PCOS) is the most common condition affecting women of reproductive age globally. PCOS continues to be the largest contributing factor to female infertility despite significant progress in our knowledge of the molecular underpinnings and treatment of the condition. The fact that PCOS is a very diverse condition makes it one of the key reasons why we haven't been able to overcome it. Non-coding RNAs (ncRNAs) are implicated in the development of PCOS, according to growing evidence. However, it is unclear how the complex regulatory relationships between the many ncRNA types contribute to the growth of this malignancy. Competing endogenous RNA (ceRNA), a recently identified mechanism in the RNA world, suggests regulatory interactions between various RNAs, including long non-coding RNAs (lncRNAs), microRNAs (miRNAs), transcribed pseudogenes, and circular RNAs (circRNAs). Recent studies on PCOS have shown that dysregulation of multiple ceRNA networks (ceRNETs) between these ncRNAs plays crucial roles in developing the defining characteristics of PCOS development. And it is believed that such a finding may open a new door for a deeper comprehension of PCOS's unexplored facets. In addition, it may be able to provide fresh biomarkers and effective therapy targets for PCOS. This review will go over the body of information that exists about the primary roles of ceRNETs before highlighting the developing involvement of several newly found ceRNETs in a number of PCOS characteristics.

Vitamin D receptor (VDR) gene polymorphisms have been implicated in polycystic ovary syndrome (PCOS). Despite VDR gene polymorphisms importance and their risk for PCOS, they have not been extensively studied. The main objective was to evaluate the associations between VDR gene polymorphisms and risk for PCOS. The current systematic review and meta-analysis examined VDR gene polymorphisms with PCOS in case-control and cohort studies. Relevant keywords were used to search Scopus, Web of Science, PubMed, MEDLINE, ScienceDirect, and Google Scholar for peer-reviewed publications until July 1, 2024. Selected papers were assessed for risk bias and quality using the Modified Newcastle-Ottawa scale. A meta-analysis was conducted using a random-effect model. The association between VDR gene polymorphism(s) and PCOS in women was reported as odds ratios (ORs) with 95 % confidence intervals (CIs). Twenty eligible studies, including 5618 subjects, were included in systematic review and meta-analysis. This study revealed a significant association between ApaI (rs7975232; OR = 1.18, 95 % CI = 1.06–1.30, p < 0.01), BsmI (rs1544410; OR = 1.22, 95 % CI = 1.08–1.37, p < 0.01), Cdx2 (rs11568820; OR = 1.15, 95 % CI = 0.97–1.38, p < 0.01), and TaqI (rs731236; OR = 1.25, 95 % CI = 1.13–1.39, p < 0.01). However, there was no significant association in the FokI (rs22228570; OR = 1.01, 95 % CI = 0.91–1.112, p = 0.12) polymorphism with PCOS risk. The present systematic review and meta-analysis shows that women with ApaI, BsmI, Cdx2, and TaqI VDR gene polymorphisms may have a higher risk of PCOS. This study was registered on the Prospective International Registry of Systematic Reviews (PROSPERO) with registration number CRD42024564851.

Background: Polycystic ovary syndrome (PCOS) affects women of reproductive age globally with an incidence rate of 5% - 26%. Growing evidence reports important roles for microRNAs (miRNAs) in the pathophysiology of granulosa cells (GCs) in PCOS. Objectives: The objectives of this study were to identify the top differentially expressed miRNAs (DE-miRNAs) and their corresponding targets in hub gene-miRNA networks, as well as identify novel DE-miRNAs by analyzing three distinct microarray datasets. Additionally, functional enrichment analysis was performed using bioinformatics approaches. Finally, interactions between the 5 top-ranked hub genes and drugs were investigated. Methods: Using bioinformatics approaches, three GC profiles from the gene expression omnibus (GEO), namely gene expression omnibus series (GSE)-34526, GSE114419, and GSE137684, were analyzed. Targets of the top DE-miRNAs were predicted using the multiMiR R package, and only miRNAs with validated results were retrieved. Genes that were common between the “DE-miRNA prediction results” and the “existing tissue DE-mRNAs” were designated as differentially expressed genes (DEGs). Gene ontology (GO) and pathway enrichment analyses were implemented for DEGs. In order to identify hub genes and hub DE-miRNAs, the protein-protein interaction (PPI) network and miRNA-mRNA interaction network were constructed using Cytoscape software. The drug-gene interaction database (DGIdb) database was utilized to identify interactions between the top-ranked hub genes and drugs. Results: Out of the top 20 DE-miRNAs that were retrieved from the GSE114419 and GSE34526 microarray datasets, only 13 of them had “validated results” through the multiMiR prediction method. Among the 13 DE-miRNAs investigated, only 5, namely hsa-miR-8085, hsa-miR-548w, hsa-miR-612, hsa-miR-1470, and hsa-miR-644a, demonstrated interactions with the 10 hub genes in the hub gene-miRNA networks in our study. Except for hsa-miR-612, the other 4 DE-miRNAs, including hsa-miR-8085, hsa-miR-548w, hsa-miR-1470, and hsa-miR-644a, are novel and had not been reported in PCOS pathogenesis before. Also, GO and pathway enrichment analyses identified “pathogenic E. coli infection” in the Kyoto encyclopedia of genes and genomes (KEGG) and “regulation of Rac1 activity” in FunRich as the top pathways. The drug-hub gene interaction network identified ACTB, JUN, PTEN, KRAS, and MAPK1 as potential targets to treat PCOS with therapeutic drugs. Conclusions: The findings from this study might assist researchers in uncovering new biomarkers and potential therapeutic drug targets in PCOS treatment.