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Constructing a ceRNA-immunoregulatory network associated with the development and prognosis of human atherosclerosis through weighted gene co-expression network analysis.

ABSTRACT: There is now overwhelming experimental and clinical evidence that atherosclerosis (AS) is a chronic inflammatory disease. The recent discovery of a new group of mediators known as competing endogenous RNA (ceRNA) offers a unique opportunity for investigating immunoregulation in AS. In this study, we used gene expression profiles from GEO database to construct a lncRNA-miRNA-mRNA ceRNA network during AS plaque development through weighted gene co-expression network analysis (WGCNA). GO annotation and pathway enrichment analysis suggested that the ceRNA network was mainly involved in the immune response. CIBERSORT and GSVA were used to calculate the immune cell infiltration score and identified macrophage as hub immunocyte in plaque development. A macrophage related ceRNA subnetwork was constructed through correlation analysis. Samples from Biobank of Karolinska Endarterectomy (BiKE) were used to identify prognostic factors from the subnetwork and yielded 7 hub factors that can predict ischemic events including macrophage GSVA score and expression value of AL138756.1, CTSB, MAFB, LYN, GRK3, and BID. A nomogram based on the key factors was established. GSEA identified that the PD1 signaling pathway was negatively associated with these prognostic factors which may explain the cardiovascular side effect of immune checkpoint therapy in anti-tumor treatment.

SUBMITTER: Liu Y

PROVIDER: S-EPMC7880393 | biostudies-literature | 2021 Jan

REPOSITORIES: biostudies-literature

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Constructing a ceRNA-immunoregulatory network associated with the development and prognosis of human atherosclerosis through weighted gene co-expression network analysis.

Liu Yaozhong Y Liu Na N Liu Qiming Q

Aging 20210117 2

There is now overwhelming experimental and clinical evidence that atherosclerosis (AS) is a chronic inflammatory disease. The recent discovery of a new group of mediators known as competing endogenous RNA (ceRNA) offers a unique opportunity for investigating immunoregulation in AS. In this study, we used gene expression profiles from GEO database to construct a lncRNA-miRNA-mRNA ceRNA network during AS plaque development through weighted gene co-expression network analysis (WGCNA). GO annotation ...[more]

PMID: 33460396

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Project description:BackgroundTo date, vascular dementia (VaD) lacks effective treatment in clinical practice. There is also growing evidence that VaD may be closely related to the immune response. The development of high-throughput technology, and the recently discovered group of new mediators called competitive endogenous RNAs (ceRNA), provides a unique opportunity to study the immunomodulation of VaD.MethodsIn this study, we used gene expression profiles in the Gene Expression Omnibus (GEO) database to obtain immune-related gene coexpression modules through a weighted gene coexpression network analysis (WGCNA) and gene enrichment analysis. We extracted and merged long non-coding RNA (lncRNA) and microRNA (miRNA) expressions from the GEO database and mapped them with related databases. Subsequently, we used Cytoscape to construct a lncRNA-miRNA-mRNA network, and then we performed an enrichment analysis on the mRNAs in the network to determine their regulatory function. Subsequently, we used an ImmuCellAI immune infiltration analysis and constructed a ceRNA sub-network of related immune cells. Finally, we conducted a gene set enrichment analysis (GSEA) to determine the potential regulatory pathways of the key factors.ResultsAs a result, we identified the blue module as the key module of immunity and constructed the related CeRNA network. Immune infiltration analysis showed that natural killer T (NKT) cells may be the key immune cells of VaD. Using a Pearson correlation analysis, we identified that B4GALT1, PPP1R3B, MICB, HHAT, DSC2, DNA2, SCARA3, and lncRNA NEAT1 may be the key factors of VaD. Our subsequent GSEA analysis showed that lncRNA NEAT1 may be regulated by NK cells and toll-like receptors.ConclusionsOur research provides new therapeutic targets for vascular dementia from the immunological perspective for the first time, including B4GALT1, PPP1R3B, MICB, HHAT, DSC2, DNA2, SCARA3, and lncRNA NEAT1, and our research hopes to provide new treatment options for VaD.

Project description:Background: Atrial fibrillation (AF) is the most common arrhythmia. We aimed to construct competing endogenous RNA (ceRNA) networks associated with the susceptibility and persistence of AF by applying the weighted gene co-expression network analysis (WGCNA) and prioritize key genes using the random walk with restart on multiplex networks (RWR-M) algorithm. Methods: RNA sequencing results from 235 left atrial appendage samples were downloaded from the GEO database. The top 5,000 lncRNAs/mRNAs with the highest variance were used to construct a gene co-expression network using the WGCNA method. AF susceptibility- or persistence-associated modules were identified by correlating the module eigengene with the atrial rhythm phenotype. Using a module-specific manner, ceRNA pairs of lncRNA-mRNA were predicted. The RWR-M algorithm was applied to calculate the proximity between lncRNAs and known AF protein-coding genes. Random forest classifiers, based on the expression value of key lncRNA-associated ceRNA pairs, were constructed and validated against an independent data set. Results: From the 21 identified modules, magenta and tan modules were associated with AF susceptibility, whereas turquoise and yellow modules were associated with AF persistence. ceRNA networks in magenta and tan modules were primarily involved in the inflammatory process, whereas ceRNA networks in turquoise and yellow modules were primarily associated with electrical remodeling. A total of 106 previously identified AF-associated protein-coding genes were found in the ceRNA networks, including 16 that were previously implicated in the genome-wide association study. Myocardial infarction-associated transcript (MIAT) and LINC00964 were prioritized as key lncRNAs through RWR-M. The classifiers based on their associated ceRNA pairs were able to distinguish AF from sinus rhythm with respective AUC values of 0.810 and 0.940 in the training set and 0.870 and 0.922 in the independent test set. The AF-related single-nucleotide polymorphism rs35006907 was found in the intronic region of LINC00964 and negatively regulated the LINC00964 expression. Conclusion: Our study constructed AF susceptibility- and persistence-associated ceRNA networks, linked genetics with epigenetics, identified MIAT and LINC00964 as key lncRNAs, and constructed random forest classifiers based on their associated ceRNA pairs. These results will help us to better understand the mechanisms underlying AF from the ceRNA perspective and provide candidate therapeutic and diagnostic tools.

Project description:BackgroundSalt sensitivity of blood pressure (SSBP) is an independent risk factor for cardiovascular disease. The pathogenic mechanisms of SSBP are still uncertain. This study aimed to construct the co-regulatory network of SSBP and data mining strategy based on the competitive endogenous RNA (ceRNA) theory.MethodsLncRNA and mRNA microarray was performed to screen for candidate RNAs. Four criteria were used to select the potential differently expressed RNAs. The weighted correlation network analysis (WGCNA) package of R software and target miRNA and mRNA prediction online databases were used to construct the ceRNA co-regulatory network and discover the pathways related to SSBP. Gene ontology enrichment, gene set enrichment analysis (GSEA) and KEGG pathway analysis were performed to explore the functions of hub genes in networks.ResultsThere were 274 lncRNAs and 36 mRNAs that differently expressed between salt-sensitive and salt-resistant groups (P < 0.05). Using WGCNA analysis, two modules were identified (blue and turquoise). The blue module had a positive relationship with salt-sensitivity (R = 0.7, P < 0.01), high-density lipoprotein (HDL) (R = 0.53, P = 0.02), and total cholesterol (TC) (R = 0.55, P = 0.01). The turquoise module was positively related with triglyceride (TG) (R = 0.8, P < 0.01) and low-density lipoprotein (LDL) (R = 0.54, P = 0.01). Furthermore, 84 ceRNA loops were identified and one loop may be of great importance for involving in pathogenesis of SSBP. KEGG analysis showed that differently expressed mRNAs were mostly enriched in the SSBP-related pathways. However, the enrichment results of GSEA were mainly focused on basic physical metabolic processes.ConclusionThe microarray data mining process based on WGCNA co-expression analysis had identified 84 ceRNA loops that closely related with known SSBP pathogenesis. The results of our study provide implications for further understanding of the pathogenesis of SSBP and facilitate the precise diagnosis and therapeutics.

Project description:Aim: To identify functional long noncoding RNAs (lncRNAs) by constructing a NAFLD-related lncRNA-miRNA-mRNA network (NLMMN) based on the hypothesis that lncRNAs, as competitive endogenous RNAs (ceRNAs), are able to regulate mRNA functions by competitive binding to shared miRNAs. Methods: The "Limma R package" was used to identify differentially expressed lncRNAs and mRNAs (DElncRNAs and DEmRNAs). The "miRcode online tool" was used to predict the potential interactions between DElncRNAs or DEmRNAs using Perl, and "multiMiR R package" was used to predict the potential interactions between DElncRNAs and miRNAs. The NLMMN was viewed by Cytoscape. The DEmRNAs were further analyzed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis. The real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) was used to identify functional lncRNAs in human liver tissue and FFAs-induced fat-overloading HepG2 cells. The role of functional lncRNA was explored in the HepG2 cell line. Results: A total of 336 DElncRNAs (154 upregulated and 182 downregulated, |log 2 (fold change) |>0.655 and P < 0.05) and 399 DEmRNAs (152 upregulated and 247 downregulated, |log 2 (fold change) |>0.608 and P < 0.05) were identified. A total of 142 DElncRNA-miRNA interaction pairs and 643 miRNA-DEmRNA interaction pairs were retained to construct the NLMMN, which contained 19 lncRNAs, 47 miRNAs, and 228 mRNAs. The results of GO and KEGG enrichment analyses were related to an extracellular matrix (ECM). Two upregulated lncRNAs (LINC00240 and RBMS3-AS3) and one downregulated lncRNA (ALG9-IT1) were identified by qRT-PCR in liver tissues. But only LINC00240 was significantly upregulated in fat-overloading HepG2 cells. Overexpression of LINC00240 did not affect lipid accumulation but increased the reactive oxygen species (ROS) content in HepG2 cells. Conclusion: LINC00240, RBMS3-AS3, and ALG9-IT1 might be novel functional lncRNAs that attenuate liver fibrosis in NAFLD by influencing the ECM through the ceRNA network. Among them, LINC00240 might have a key role.

Project description:Background Glioblastoma (GBM) is the most common malignant tumor in the central system with a poor prognosis. Due to the complexity of its molecular mechanism, the recurrence rate and mortality rate of GBM patients are still high. Therefore, there is an urgent need to screen GBM biomarkers to prove the therapeutic effect and improve the prognosis. Results We extracted data from GBM patients from the Gene Expression Integration Database (GEO), analyzed differentially expressed genes in GEO and identified key modules by weighted gene co-expression network analysis (WGCNA). GSE145128 data was obtained from the GEO database, and the darkturquoise module was determined to be the most relevant to the GBM prognosis by WGCNA (r = − 0.62, p = 0.01). We performed enrichment analysis of Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) to reveal the interaction activity in the selected modules. Then Kaplan-Meier survival curve analysis was used to extract genes closely related to GBM prognosis. We used Kaplan-Meier survival curves to analyze the 139 genes in the darkturquoise module, identified four genes (DARS/GDI2/P4HA2/TRUB1) associated with prognostic GBM. Low expression of DARS/GDI2/TRUB1 and high expression of P4HA2 had a poor prognosis. Finally, we used tumor genome map (TCGA) data, verified the characteristics of hub genes through Co-expression analysis, Drug sensitivity analysis, TIMER database analysis and GSVA analysis. We downloaded the data of GBM from the TCGA database, the results of co-expression analysis showed that DARS/GDI2/P4HA2/TRUB1 could regulate the development of GBM by affecting genes such as CDC73/CDC123/B4GALT1/CUL2. Drug sensitivity analysis showed that genes are involved in many classic Cancer-related pathways including TSC/mTOR, RAS/MAPK.TIMER database analysis showed DARS expression is positively correlated with tumor purity (cor = 0.125, p = 1.07e−02)), P4HA2 expression is negatively correlated with tumor purity (cor =−0.279, p = 6.06e−09). Finally, GSVA analysis found that DARS/GDI2/P4HA2/TRUB1 gene sets are closely related to the occurrence of cancer. Conclusion We used two public databases to identify four valuable biomarkers for GBM prognosis, namely DARS/GDI2/P4HA2/TRUB1, which have potential clinical application value and can be used as prognostic markers for GBM.

Dataset Information

Constructing a ceRNA-immunoregulatory network associated with the development and prognosis of human atherosclerosis through weighted gene co-expression network analysis.

Publications

Constructing a ceRNA-immunoregulatory network associated with the development and prognosis of human atherosclerosis through weighted gene co-expression network analysis.

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