Dataset Information

A competing endogenous RNA network reveals key lncRNAs associated with sepsis.

ABSTRACT:

Background

This study set out to determine key lncRNAs correlated with sepsis via constructing competing endogenous RNA (ceRNA) network.

Methods

Three septic patients and three healthy controls were recruited to obtain lncRNA profiles in this current study. Combined with the mRNA profiles by RNA-sequencing, an integrated analysis of mRNA expression profiles downloaded from GEO was performed to obtain the differentially expressed mRNAs (DEmRNAs). Based on differentially expressed lncRNAs (DElncRNAs) and DEmRNAs acquired in this present study and differentially expressed miRNAs (DEmiRNAs) acquired in previous study, a ceRNA network was constructed. Furthermore, LINC00963 was validated in THP-1 cells by performing loss of function assays.

Results

In this analysis, a total of 290 DEmRNAs and 46 DElncRNAs were detected in sepsis. Parkinson's disease, Oxidative phosphorylation and Cardiac muscle contraction were significantly enriched KEGG pathways in sepsis. XPO1, CUL4A, and NEDD8 were three hub proteins of sepsis-specific PPI network. A ceRNA network, which contained 16 DElncRNA-DEmiRNA pairs and 82 DEmiRNA-DEmRNA pairs, involving 5 lncRNAs, 10 miRNAs, and 60 mRNAs, was obtained. The function experiments indicated that knockdown of LINC00963 could promote cell proliferation, reduce cytokine expression, and suppress inflammasome activation and phagocytosis in LPS-induced THP-1 cells.

Conclusion

This study determined key lncRNAs involved in sepsis, which may contribute to the development for novel treatment strategy of sepsis.

SUBMITTER: Guo X

PROVIDER: S-EPMC7963432 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Publications

A competing endogenous RNA network reveals key lncRNAs associated with sepsis.

Guo Xuan X Qin Yanjun Y Wang Lili L Dong Shimin S Yan Yan Y Bian Xiaohua X Zhao Caiyan C

Molecular genetics & genomic medicine 20201125 1

<h4>Background</h4>This study set out to determine key lncRNAs correlated with sepsis via constructing competing endogenous RNA (ceRNA) network.<h4>Methods</h4>Three septic patients and three healthy controls were recruited to obtain lncRNA profiles in this current study. Combined with the mRNA profiles by RNA-sequencing, an integrated analysis of mRNA expression profiles downloaded from GEO was performed to obtain the differentially expressed mRNAs (DEmRNAs). Based on differentially expressed l ...[more]

PMID: 33237630

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Project description:Schizophrenia (SCZ) is a serious psychiatric condition with a 1% lifetime risk. SCZ is one of the top ten global causes of disabilities. Despite numerous attempts to understand the function of genetic factors in SCZ development, genetic components in SCZ pathophysiology remain unknown. The competing endogenous RNA (ceRNA) network has been demonstrated to be involved in the development of many kinds of diseases. The ceRNA hypothesis states that cross-talks between coding and non-coding RNAs, including long non-coding RNAs (lncRNAs), via miRNA complementary sequences known as miRNA response elements, creates a large regulatory network across the transcriptome. In the present study, we developed a lncRNA-related ceRNA network to elucidate molecular regulatory mechanisms involved in SCZ. Microarray datasets associated with brain regions (GSE53987) and lymphoblasts (LBs) derived from peripheral blood (sample set B from GSE73129) of SCZ patients and control subjects containing information about both mRNAs and lncRNAs were downloaded from the Gene Expression Omnibus database. The GSE53987 comprised 48 brain samples taken from SCZ patients (15 HPC: hippocampus, 15 BA46: Brodmann area 46, 18 STR: striatum) and 55 brain samples taken from control subjects (18 HPC, 19 BA46, 18 STR). The sample set B of GSE73129 comprised 30 LB samples (15 patients with SCZ and 15 controls). Differentially expressed mRNAs (DEmRNAs) and lncRNAs (DElncRNAs) were identified using the limma package of the R software. Using DIANA-LncBase, Human MicroRNA Disease Database (HMDD), and miRTarBase, the lncRNA- associated ceRNA network was generated. Pathway enrichment of DEmRNAs was performed using the Enrichr tool. We developed a protein-protein interaction network of DEmRNAs and identified the top five hub genes by the use of STRING and Cytoscape, respectively. Eventually, the hub genes, DElncRNAs, and predictive miRNAs were chosen to reconstruct the subceRNA networks. Our bioinformatics analysis showed that twelve key DEmRNAs, including BDNF, VEGFA, FGF2, FOS, CD44, SOX2, NRAS, SPARC, ZFP36, FGG, ELAVL1, and STARD13, participate in the ceRNA network in SCZ. We also identified DLX6-AS1, NEAT1, MINCR, LINC01094, DLGAP1-AS1, BABAM2-AS1, PAX8-AS1, ZFHX4-AS1, XIST, and MALAT1 as key DElncRNAs regulating the genes mentioned above. Furthermore, expression of 15 DEmRNAs (e.g., ADM and HLA-DRB1) and one DElncRNA (XIST) were changed in both the brain and LB, suggesting that they could be regarded as candidates for future biomarker studies. The study indicated that ceRNAs could be research candidates for investigating SCZ molecular pathways.

Dataset Information

A competing endogenous RNA network reveals key lncRNAs associated with sepsis.

Background

Methods

Results

Conclusion

Publications

A competing endogenous RNA network reveals key lncRNAs associated with sepsis.

Similar Datasets

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