Bioinformatics analysis of a disease-specific lncRNA-miRNA-mRNA regulatory network in recurrent spontaneous abortion (RSA)
Research Square
2023
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Example: if you select the 1-year option for an article published in 2019 and a metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019. If you select the 3-year option for the same article published in 2019 and the metric category shows 90%, that means that the article or review is performing better than 90% of the other articles/reviews published in that journal in 2019, 2018 and 2017.
Citation Benchmarking is provided by Scopus and SciVal and is different from the metrics context provided by PlumX Metrics.
Article Description
Background:This study investigated the molecular mechanisms of long non-coding RNAs (lncRNAs) in RSA using the lncRNA-miRNA-mRNA regulatory network. Methods: The present study obtained expression datasets of long non-coding RNAs (lncRNAs) (GSE179996), messenger RNAs (mRNAs) (GSE201469), and microRNAs (miRNAs) (GSE178619, GSE201442) from blood samples of individuals with RSA and healthy controls. The differentially expressed lncRNAs (DELs), mRNAs (DEMs), and miRNAs (DEmiRs) were revealed. Subsequently, the identification of miRNAs that interact with DELs and exhibit overlap with DEmiRs was conducted. The specific genes were achieved through the overlapping predicted target genes and DEmiRs. A regulatory network comprising lncRNA, miRNA, and mRNA was established, followed by a subsequent analysis of enrichment. Also, the enrichment analysis was performed, and a protein–protein interaction (PPI) network was constructed. Results: This study identified 57 DELs, 212 DEmiRs, and 301 DEMs regarding RSA. Subsequent analysis revealed a lncRNA-miRNA-mRNA network comprising nine upregulated lncRNAs, 14 downregulated miRNAs, and 65 mRNAs. The ceRNA network's genes were then subjected to functional enrichment and pathway analyses, which showed their association with various processes, such as cortisol and thyroid hormone synthesis and secretion, human cytomegalovirus infection, and parathyroid hormone synthesis. Furthermore, ten hub genes (ITGB3, GNAI2, GNAS, SRC, PLEC, CDC42, RHOA, RAC1, CTNND1, FN1) were identified based on the PPI network results. Conclusion: In summary, the outcomes of our study offer new understandings towards comprehending the potential pathogenic mechanism in RSA via the lncRNA-miRNA-mRNA network and reveal the possibility of identifying new lncRNAs and miRNAs as promising molecular biomarkers.
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