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Systematic analysis of coronary artery disease datasets revealed the potential biomarker and treatment target.

ABSTRACT: Coronary artery disease caused about 1 of every 7 deaths in the United States and early prevention was potential to decrease the incidence and mortality. We aimed to figure the genes involving in the coronary artery disease using meta-anlaysis. Five datasets of coronary heart disease from GEO series were retrieved and data preprocessing and quality control were carried out. Moderated t-test was used to decide the differentially expressed genes for a single dataset. And the combined p-value using systematic-analysis methods were conducted using MetaDE. The pathway enrichment was carried out using Reactome database. Protein-protein interactions of the identified differentially expressed genes were also analyzed using STRING v10.0 online tool. After removing unidentified or intermediate samples and a total of 238 cases and 189 matched or partially matched control from five microarray datasets were retrieved from GEO. Six different quality control measures were calculated and PCA biplots were plotted in order to visualize the quantitative measure. The first two PCs captured 91% of the variance and we decided to include all of the datasets for systematic analysis. Using the FDR cut-off as 0.1, nine genes, including LFNG, ID3, PLA2G7, FOLR3, PADI4, ARG1, IL1R2, NFIL3 and MGAM, were differentially expressed according to maxP. Their protein-protein interactions showed that they were closely connected and 24 Reactome pathways were related to coronary artery disease. We concluded that pathways related to immune responses, especially neutrophil degranulation, were associated with coronary heart disease.

SUBMITTER: Shi Y

PROVIDER: S-EPMC5589605 | biostudies-literature | 2017 Aug

REPOSITORIES: biostudies-literature

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Systematic analysis of coronary artery disease datasets revealed the potential biomarker and treatment target.

Shi Yan Y Yang Sijin S Luo Man M Zhang Wei-Dong WD Ke Zun-Ping ZP

Oncotarget 20170426 33

Coronary artery disease caused about 1 of every 7 deaths in the United States and early prevention was potential to decrease the incidence and mortality. We aimed to figure the genes involving in the coronary artery disease using meta-anlaysis. Five datasets of coronary heart disease from GEO series were retrieved and data preprocessing and quality control were carried out. Moderated t-test was used to decide the differentially expressed genes for a single dataset. And the combined p-value using ...[more]

PMID: 28903366

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Project description:BackgroundThe expression profile of lncRNAs in coronary artery disease (CAD) patients has not yet been fully explored. Therefore, the current study aimed to investigate lncRNA-based prognostic biomarkers for CAD.MethodsThe expression profiles of lncRNA and messenger RNA (mRNA) were downloaded from the Gene Expression Omnibus (GEO) database. Differentially expressed lncRNA (DElncRNAs) and DEmRNAs were identified from CAD and normal samples, and weighted gene co-expression network analysis (WGCNA) was conducted. Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed to investigate the principal functions of significantly dysregulated genes. The potential drugs of new CAD-specific genes were identified by network distance method. Receiver operating characteristic (ROC) was used to verify the classification performance of genes.ResultsA total of 512 differentially expressed genes (DEGs) and 308 DElncRNAs were identified from GSE113079 dataset to classify CAD samples. Through WGCNA co-expression analysis, 24 co-expression modules were obtained. A total of 187 DElncRNAs and 253 DEGs were determined from 7 modules correlated with CAD. Functional enrichment analysis showed that these DEGs were mainly related to inflammatory and immune-related pathways. Furthermore, 36 regulatory pairs of significantly shared micro RNAs (miRNAs) were identified as dysregulated lncRNA-mRNA (LRM-CAD), which contained 11 lncRNAs and 33 genes. Compared with a single lncRNA or gene, LRM-CAD showed stronger classification performance [average area under the curve (AUC) =0.958]. We screened 3 potential therapeutic drugs, DB09105, DB12371, and DB12612, a by binding drug-target gene interaction network. Molecular docking verified that the S1PR1 gene bound relatively closely to DB12371 and DB12612. The ROC analysis on external data sets showed that S1PR1, AC012640.4, and S1PR1-AC012640.4 could effectively distinguish CAD samples from control samples.ConclusionsWe provided a transcriptome overview of abnormally expressed lncRNAs in CAD patients and identified novel biomarkers for diagnosing CAD.

Project description:The concept of hybrid coronary revascularization (HCR) combines the left internal mammary artery (LIMA)-left anterior descending (LAD) graft and percutaneous coronary intervention (PCI) to non-LAD vessels. Multiple comparative studies have evaluated the safety and feasibility of HCR and coronary artery bypass grafting (CABG) for multivessel coronary artery disease (MCAD). However, the sample size of each study was small, and evidences based on single-institutional experience. The purpose of this meta-analysis was to compare the short-term outcomes of HCR with those of CABG for MCAD.PubMed, EMBASE and Cochrane Library databases, as well as conference proceedings, were searched for eligible studies published up to March 2014. We calculated summary odds ratios (OR) for primary endpoints (death, stroke; myocardial infarction (MI); target vessel revascularization (TVR); major adverse cardiac or cerebrovascular events (MACCEs)) and secondary endpoints (atrial fibrillation (AF); renal failure; length of stay in the intensive care unit (LoS in ICU); length of stay in hospital (LoS in hospital); red blood cell (RBC) transfusion). Data from 6176 participants were derived from ten cohort studies.HCR was non-inferior to CABG in terms of MACCEs during hospitalization (odds ratio (OR), 0.68, 95% confidence interval (CI), 0.34-1.33)and at one-year follow-up(0.32, 0.05-1.89) , and no significant difference was found between HCR and CABG groups in in-hospital and one-year follow-up outcomes of death, MI, stroke, the prevalence of AF and renal failure, whereas HCR was associated with a lower requirement of RBC transfusion and shorter LoS in ICU and LoS in hospital than CABG (weighted mean difference (WMD) -1.25, 95% CI, -1.62 to -0.88; -17.47, -31.01 to -3.93; -1.77, -3.07 to -0.46; respectively).Our meta-analysis indicates that HCR is feasible, safe and effective for the treatment of MCAD, with similar in-hospital and one-year follow-up outcome, significantly lower requirement of RBC transfusion, and faster recovery compared with CABG.

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Systematic analysis of coronary artery disease datasets revealed the potential biomarker and treatment target.

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Systematic analysis of coronary artery disease datasets revealed the potential biomarker and treatment target.

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