Dataset Information

Comprehensive Analysis of Differential Immunocyte Infiltration and Potential ceRNA Networks Involved in the Development of Atrial Fibrillation.

ABSTRACT: This study is aimed at identifying potential molecular mechanisms and candidate biomarkers in the left atrial regions for the diagnosis and treatment of valvular atrial fibrillation (VAF). Multibioinformatics methods, including linear models for microarray analysis (LIMMA), an SVA algorithm, CIBERSORT immune infiltration, and DNA methylation analysis, were employed. In addition, the protein-protein interaction (PPI) network, Gene Ontology (GO), and molecular pathways of differentially expressed genes (DEGs) or differential methylation regions were constructed. In all, compared with the normal rhythm group, 243 different mRNAs (29 downregulated and 214 upregulated) and 26 different lncRNAs (3 downregulated and 23 upregulated) were detected in the left atrium (LA) of atrial fibrillation (AF) patients, and the neutrophil and CD8+ T cell were infiltrated. Additionally, 199 different methylation sites (107 downregulated and 92 upregulated) were also identified based on DNA methylation analysis. After integration, ELOVL2, CCR2, and WEE1 were detected for differentially methylated and differentially transcribed genes. Among them, WEE1 was also a core gene identified by the competing endogenous RNA (ceRNA) network that included WEE1-KRBOX1-AS1-hsa-miR-17-5p, in VAF left atrial tissue. We combined the DNA methylation and transcriptional expression differential analysis and found that WEE1 (cg13365543) may well be a candidate gene regulated by DNA methylation modification. Moreover, KRBOX1-AS1 and WEE1 can compete endogenously and may mediate myocardial tissue infiltration into CD8+ T cells and participate in the AF process.

SUBMITTER: Wu J

PROVIDER: S-EPMC7525288 | biostudies-literature | 2020

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Comprehensive Analysis of Differential Immunocyte Infiltration and Potential ceRNA Networks Involved in the Development of Atrial Fibrillation.

Wu Jiafeng J Deng Huiming H Chen Qianghua Q Wu Qiang Q Li Xiaolong X Jiang Siwei S Wang Fengxin F Ye Fuyin F Ou Langhui L Gao Hong H

BioMed research international 20200919

This study is aimed at identifying potential molecular mechanisms and candidate biomarkers in the left atrial regions for the diagnosis and treatment of valvular atrial fibrillation (VAF). Multibioinformatics methods, including linear models for microarray analysis (LIMMA), an SVA algorithm, CIBERSORT immune infiltration, and DNA methylation analysis, were employed. In addition, the protein-protein interaction (PPI) network, Gene Ontology (GO), and molecular pathways of differentially expressed ...[more]

PMID: 33015181

Similar Datasets

Project description:BackgroundAt present, the mechanisms behind atrial fibrillation (AF) pathogenesis are still unclear. We construct a ceRNA immunoregulatory network to further understand the mechanism of AF.MethodsFour AF mRNA datasets from the Gene Expression Omnibus (GEO) database were integrated by SVA method. AF-related immune genes (AF-IRGs) were selected via combining ImmPort database with the genes in the module most associated with AF obtained by a weighted gene coexpression network analysis (WGCNA). Then, circRNA and miRNA expressions from the GEO database were extracted and mapped with related databases. Next, an immune-related circRNA-miRNA-mRNA ceRNA network was constructed and hub genes were filtered from a protein-protein interaction (PPI) network, and the differentially expressed (DE) hub genes in AF were further screened. Additionally, immune infiltration was investigated in AF by using CIBERSORT. Subsequently, the relationships between DE hub genes and AF-related infiltrating immune cells were performed by using Pearson correlation coefficients. Ulteriorly, the immune-cells-related ceRNA subnetwork in AF was built.ResultsA total of 95 AF-IRGs were detected, and an immune-related ceRNA network in AF was constructed with 12 circRNAs, 7 miRNAs and 50 mRNAs. The immune infiltration analysis indicated that a higher level of neutrophils, as well as a lower level of T cells regulatory (Tregs) and NK cells activated in AF. Four DE hub genes (CXCL12, IL7R, TNFSF13B, CD8A) were associated with Tregs or NK cells activated immune cells (P < 0.05). Tregs or NK cells activated immune cells-related ceRNA subnetwork including 5 circRNAs (has_circ_0001190, has_circ_0006725, has_circ_0079284, has_circ_0005299, and has_circ_0002103), 4 miRNAs (has-miR-198, has-miR-623, has-miR-1246, and has-miR-339-3p) and 4 DE hub genes was eventually constructed in AF.ConclusionOur results provide new insights into the molecular mechanisms governing AF progression from the perspective of immune-related ceRNA network.

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.

Dataset Information

Comprehensive Analysis of Differential Immunocyte Infiltration and Potential ceRNA Networks Involved in the Development of Atrial Fibrillation.

Publications

Comprehensive Analysis of Differential Immunocyte Infiltration and Potential ceRNA Networks Involved in the Development of Atrial Fibrillation.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets