Identification and Validation of Candidate Gene Module Along With Immune Cells Infiltration Patterns in Atherosclerosis Progression to Plaque Rupture via Transcriptome Analysis

• DOI: 10.3389/fcvm.2022.894879
• Publication Date: 2022-06-22T06:52:23Z
• Authors: Jing Xu; Cheng Chen; Yuejin Yang
• Keywords: Fold change

To explore the differentially expressed genes (DEGs) along with infiltrating immune cells landscape and their potential mechanisms in progression of atherosclerosis from onset to plaque rupture.In this study, three atherosclerosis-related microarray datasets were downloaded NCBI-GEO database. The gene set enrichment analysis (GSEA) was performed for interpreting biological insights expression data. CIBERSORTx algorithm applied infer relative proportions atherosclerotic samples. DEGs screened using R. protein interaction network constructed via STRING. cluster analyzed by Cytoscape software. Gene ontology (GO) geneontology.org. least absolute shrinkage selection operator (LASSO) logistic regression receiver operating characteristics (ROC) analyses build machine learning models differentiating status. Pearson correlation carried out illustrate relationship between cells. levels validated two external cohorts. Transcriptional factors drug-gene investigate promising targets intervention.Pathways related immunoinflammatory responses identified according GSEA analysis, detailed fractions compared early advanced atherosclerosis. Additionally, we 170 (|log2FC|≥1 adjusted p < 0.05). They mainly enriched GO terms relating inflammatory response innate response. A nine genes, such as ITGB2, C1QC, LY86, CTSS, C1QA, CSF1R, LAPTM5, VSIG4, CD163, found be significant, correlations calculated. also upregulated Moreover, C1QA ITGB2 may exert pathogenic functions entire process atherogenesis.We reanalyzed transcriptomic signature development rupture cell, well revealed new specific prospective investigation disease-associated dynamic molecular processes regulations