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Coronary Progenitor Cells and Soluble Biomarkers in Cardiovascular Prognosis after Coronary Angioplasty
Published on: January 28, 2020
Systematic analysis of coronary artery disease datasets revealed the potential biomarker and treatment target
Yan Shi1, Sijin Yang2, Man Luo3
1Department of Emergency, The Affiliated Huai'an Hospital of Xuzhou Medical University and The Second People's Hospital of Huai'an, Huai'an, China.
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.
Insights
Coronary artery disease (CAD) is a leading cause of death. This study identified nine key genes and immune response pathways, particularly neutrophil degranulation, linked to CAD through meta-analysis for early prevention strategies.
Area of Science:
- Genomics and Bioinformatics
- Cardiovascular Disease Research
Background:
- Coronary artery disease (CAD) accounts for a significant portion of deaths in the United States.
- Early prevention of CAD holds potential for reducing incidence and mortality.
- Identifying genetic factors is crucial for understanding CAD pathogenesis.
Purpose of the Study:
- To identify genes involved in coronary artery disease using a meta-analysis approach.
- To explore the biological pathways associated with differentially expressed genes in CAD.
- To analyze protein-protein interactions among identified candidate genes.
Main Methods:
- Retrieved and preprocessed five coronary heart disease gene expression datasets from the GEO series.
- Utilized moderated t-test for single-dataset differential gene expression analysis.
- Performed meta-analysis using MetaDE for combined p-value calculation and pathway enrichment analysis with Reactome database.
Main Results:
- A total of 238 cases and 189 controls from five microarray datasets were analyzed.
- Nine differentially expressed genes (LFNG, ID3, PLA2G7, FOLR3, PADI4, ARG1, IL1R2, NFIL3, MGAM) were identified using a False Discovery Rate (FDR) cut-off of 0.1.
- These genes exhibited close protein-protein interactions, and 24 Reactome pathways were found to be related to coronary artery disease.
Conclusions:
- Immune response pathways, specifically neutrophil degranulation, are significantly associated with coronary heart disease.
- The identified genes and pathways provide potential targets for early CAD prevention and therapeutic strategies.
- Meta-analysis is a robust method for identifying genetic markers in complex diseases like CAD.
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