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Construction of a ceRNA-based lncRNA-mRNA network to identify functional lncRNAs in polycystic ovarian syndrome.

ABSTRACT: Polycystic ovary syndrome (PCOS) is a prevalent endocrine and metabolic disorder in women of childbearing age. Recent studies suggest important roles for lncRNAs in PCOS development. Based on the hypothesis that lncRNAs are able to regulate mRNA functions by competitive binding to shared miRNAs, the present work sought to construct a PCOS-related lncRNA-mRNA network (PCLMN) to identify key lncRNAs with dysregulated expression and potential prognostic and therapeutic relevance. A global background network was constructed after retrieving lncRNA-miRNA and miRNA-mRNA pairs from the lncRNASNP2, miRTarBase and StarBase databases. Based on gene expression profiles from ovarian granulosa cells from PCOS patients and controls in the GEO's GSE95728 dataset, the PCLMN was then constructed by applying hypergeometric testing. Using topological analysis, we identified 3 lncRNAs (LINC00667, AC073172.1 and H19) ranking within the top-ten gene lists for all three centrality measures. We then explored their subcellular localization, performed functional module analyses, and identified 4 sex hormone-related transcription factors as potential regulators of their expression. Significant associations with inflammation, oxidative stress, and apoptosis-related processes and pathways were revealed for the key lncRNAs in our PCMLN. Further studies verifying the mRNA/lncRNA relationships identified herein are needed to clarify their clinical significance.

SUBMITTER: Ma Y

PROVIDER: S-EPMC8034915 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description:Polycystic ovary syndrome (PCOS), a common and frustrating syndrome in women of reproductive age, is characterized by symptoms including hyperandrogenemia, ovulation dysfunction, and polycystic ovaries. The role of competitive endogenous RNA (ceRNA) networks is receiving increasing attention and has been reported in multiple complicated diseases, such as various carcinomas, endometriosis, and tubal factor infertility. However, the association of ceRNA networks with the pathogenesis of PCOS remains unclear. This study aimed to construct a ceRNA network orchestrated by exosomal lnRNA and circRNA in PCOS. We screened RNA data of 34 samples from the Gene Expression Omnibus (GEO) database for differentially expressed lncRNAs (DELs), miRNAs (DEMs), mRNAs (DEGs), and circRNA associated with the progression of PCOS (PCOS, n = 17 vs. normal, n = 17). A protein-protein interaction (PPI) network, gene set enrichment analysis (GSEA), and Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses were conducted. Importantly, the function of the ceRNA network was explored using GO and KEGG enrichment analyses. We identified 46 DELs (25 upregulated and 21 downregulated), 31 DEMs (20 upregulated and 11 downregulated), 165 DEGs (52 upregulated and 113 downregulated), and 1 differentially expressed circRNA. The PPI network had 79 nodes and 112 edges. The GSEA results showed that these genes were mainly related to oxidative phosphorylation; TNF signaling pathways; and valine, leucine, and isoleucine degradation. GO and KEGG analyses revealed that the DEGs were significantly enriched in lipid metabolism, peroxisome proliferator-activated receptor (PPAR) signaling pathways, and fatty acid metabolism. Additionally, we constructed a novel PCOS-associated lncRNA-miRNA-mRNA ceRNA triple network and a circRNA-related network. Thereafter, we described the potential roles played by follicular fluid exosomes in PCOS. Our present study describes the molecular pathogenesis of PCOS in human ovarian granulosa cells at the post-transcriptional level, which provides new insights for the clinical diagnosis and treatment of PCOS and further scientific research.

Project description:Polycystic ovary syndrome (PCOS) is a common metabolic and reproductive disorder with an increasing risk for type 2 diabetes. Insulin resistance is a common feature of women with PCOS, but the underlying molecular mechanism remains unclear. This study aimed to screen critical long non-coding RNAs (lncRNAs) that might play pivotal roles in insulin resistance, which could provide candidate biomarkers and potential therapeutic targets for PCOS. Gene expression profiles of the skeletal muscle in patients with PCOS accompanied by insulin resistance and healthy patients were obtained from the publicly available Gene Expression Omnibus (GEO) database. A global triple network including RNA-binding protein, mRNA, and lncRNAs was constructed based on the data from starBase. Then, we extracted an insulin resistance-associated lncRNA-mRNA network (IRLMN) by integrating the data from starBase and GEO. We also performed a weighted gene co-expression network analysis (WGCNA) on the differentially expressed genes between the women with and without PCOS, to identify hub lncRNAs. Additionally, the findings of key lncRNAs were examined in an independent GEO dataset. The expression level of lncRNA RP11-151A6.4 in ovarian granulosa cells was increased in patients with PCOS compared with that in control women. Levels were also increased in PCOS patients with higher BMI, hyperinsulinemia, and higher HOMA-IR values. As a result, RP11-151A6.4 was identified as a hub lncRNA based on IRLMN and WGCNA and was highly expressed in ovarian granulosa cells, skeletal muscle, and subcutaneous and omental adipose tissues of patients with insulin resistance. This study showed the differences between lncRNA and mRNA profiles from healthy women and women with PCOS and insulin resistance. Here, we demonstrated that RP11-151A6.4 might play a vital role in insulin resistance, androgen excess, and adipose dysfunction in patients with PCOS. Further study concerning RP11-151A6.4 could elucidate the underlying mechanisms of insulin resistance.

Project description:Long non-coding RNAs (lncRNAs) are ncRNA transcripts >200 nucleotides that are important genetic regulators. LncRNAs can directly regulate mRNA through a lncRNA-mRNA regulatory mode and can also regulate mRNA through competitive binding to micro (mi)RNA, which is generally known as the competitive endogenous RNA (ceRNA) network. The present study evaluated the functional roles and regulatory networks of lncRNAs in chronic glomerulonephritis (CGN). The proliferative ability of mouse glomerular mesangial cells (GMCs) induced by different concentrations of lipopolysaccharide (LPS) was assessed using the Cell Counting Kit-8 assay, and RNA sequencing (RNA-seq) was performed to identify differentially expressed lncRNAs in LPS-induced GMCs. Based on the sequencing results, six lncRNAs were selected for validation using reverse transcription-quantitative PCR (RT-qPCR). Furthermore, the lncRNA-mRNA regulatory network and the lncRNA-miRNA-mRNA ceRNA network were constructed to assess the role and mechanism of CGN-related lncRNAs. To elucidate the biological functions of lncRNAs, Gene Ontology (GO) biological process term enrichment and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed on all mRNAs involved in the lncRNA-mRNA regulatory network and in the ceRNA network. A total of 1,532 differentially expressed lncRNAs, including 594 upregulated lncRNAs and 938 downregulated lncRNAs, were identified using RNA-seq. The results of RT-qPCR validation were consistent with RNA-seq results. An lncRNA-mRNA regulatory network, including 236 lncRNAs and 556 mRNAs, and a ceRNA network, including 6 lncRNAs, 18 miRNAs and 419 mRNAs, were successfully constructed. The GO biological process term enrichment and KEGG pathway enrichment analyses demonstrated that those lncRNAs were often related to inflammatory response and substance metabolism. The present study identified key CGN-related lncRNAs in LPS-induced GMCs, and further demonstrated a global view of the lncRNA-mRNA regulatory network and ceRNA network involved in CGN. These results offered novel insights into the roles of lncRNAs in the pathogenesis of CGN and identified potential diagnostic biomarkers.

Project description:IntroductionPolycystic ovary syndrome (PCOS) is caused by the hormonal environment in utero, abnormal metabolism, and genetics, and it is common in women of childbearing age. A large number of studies have reported that lncRNA is important to the biological process of cancer and can be used as a potential prognostic biomarker. Thus, we studied lncRNAs' roles in PCOS in this article.MethodsWe obtained mRNAs', miRNAs', and lncRNAs' expression profiles in PCOS specimens and normal specimens from the National Biotechnology Information Gene Expression Comprehensive Center database. The EdgeR software package is used to distinguish the differentially expressed lncRNAs, miRNAs, and mRNAs. Functional enrichment analysis was carried out by the clusterProfiler R Package, and the lncRNA-miRNA-mRNA interaction ceRNA network was built in Cytoscape plug-in BiNGO and Database for Annotation, Visualization, and Integration Discovery (DAVID), respectively.ResultsWe distinguished differentially expressed RNAs, including 1087 lncRNAs, 14 miRNAs, and 566 mRNAs in PCOS. Among them, 410 lncRNAs, 11 miRNAs, and 185 mRNAs were contained in the ceRNA regulatory network. The outcomes from Gene Ontology (GO) analysis showed that the differentially expressed mRNAs (DEMs) were mainly enriched in response to the maternal process involved in female pregnancy, morphogenesis of embryonic epithelium, and the intracellular steroid hormone receptor signaling pathway. The Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis data showed that DEMs were primarily enriched in pathways related to the TGF-β signaling pathway, Type I diabetes mellitus, and glycolysis/gluconeogenesis. In addition, we chose NONHSAT123397, ENST00000564619, and NONHSAT077997 as key lncRNAs due to their high bearing on PCOS.ConclusionceRNA networks play an important role in PCOS. The research indicated that specific lncRNAs were related to PCOS development. NONHSAT123397, ENST00000564619, and NONHSAT077997 could be regarded as potential diagnostic mechanisms and biomarkers for PCOS. This discovery might provide more effective and more novel insights into the mechanisms of PCOS worthy of further exploration.

Project description:BackgroundPolycystic ovary syndrome (PCOS) is one of the most common endocrine abnormalities in women of reproductive age. In this study, we set out to construct a molecular long non-coding RNA (lncRNA)-microRNA (miRNA)-messenger RNA (mRNA) network according to the competitive endogenous RNA (ceRNA) theory and obtain insights into the related biological characteristics and pathways.MethodsWe downloaded two gene expression profile datasets of mural granulosa cells (MGCs) of women with PCOS and healthy women without PCOS (GSE84376 and GSE106724) from Gene Expression Omnibus (GEO) DataSets. Using GEO2R, we identified the mRNAs and non-coding RNAs with differential expression. The DIANA-microT-CDS algorithm was applied to predict the genes targeted by the differentially expressed miRNAs. The lncRNA-miRNA interactions were predicted using DIANA-LncBase v2. Then, we constructed the lncRNA-miRNA-mRNA network. The Database for Annotation, Visualization and Integrated Discovery (DAVID) was employed to identify the functions and enriched pathways of the genes. Subsequently, STRING was used to construct the protein-protein interaction (PPI) network. cytoHubba in Cytoscape was used to rank the hub genes, and finally, PPI modules were screened with Cytoscape MCODE.ResultsThere were 462 mRNAs, 2,464 lncRNAs, and 55 miRNAs which showed differential expression between the MGCs of patients with PCOS and those of healthy controls. Based on the PPI analysis, differentially expressed genes (DEGs) were significantly enriched in retinol metabolism, drug metabolism-cytochrome P450, malaria, the Hippo signaling pathway, and glycine, serine, and threonine metabolism. The ceRNA network contained 71 lncRNA nodes, 14 miRNA nodes, and 69 mRNA nodes, as well as 167 edges. We identified some novel genes and non-coding RNAs that might be involved in PCOS, including CD163, MRC1, VSIG4, CCL2, CCR2, SPP1, hsa-miR-3135b, hsa-miR-4649-3p, hsa-miR-1231, hsa-miR-3609, and hsa-miR-4433b-3p.ConclusionsThis study identified a novel lncRNA-miRNA-mRNA network based on the ceRNA mechanism in PCOS. Some novel genes and non-coding RNAs that may be involved in the occurrence and development of PCOS were excavated, including CD163, MRC1, VSIG4, CCL2, CCR2, SPP1, hsa-miR-3135b, hsa-miR-4649-3p, hsa-miR-1231, hsa-miR-3609, and hsa-miR-4433b-3p. However, our findings need to be validated by in vivo and in vitro experiments.

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Construction of a ceRNA-based lncRNA-mRNA network to identify functional lncRNAs in polycystic ovarian syndrome.

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