Background: Calcified aortic valve disease (CAVD) is the most prevalent valvular disease that can be treated only through valve replacement. We aimed to explore potential biomarkers and the role of immune cell infiltration in CAVD progression through bioinformatics analysis.
Methods: Differentially ex-pressed genes (DEGs) were screened out based on three microarray datasets: GSE12644, GSE51472 and GSE83453. Gene Ontology (GO) and Kyoto Encyclopaedia of Genes and Genomes (KEGG) pathway enrichment analysis were performed to evaluate gene expression differences. Machine learning algorithms and DEGs were used to screen key gene. We used CIBERSORT to evaluate the immune cell infiltration of CAVD and evaluated the correlation between the biomarkers and infiltrating immune cells. We also compared bioinformatics analysis results with the valve interstitial cells (VICs) gene expression in single-cell RNA sequencing.
Results: Collagen triple helix repeat containing 1 (CTHRC1) was identified as the key gene of CAVD. We identified a cell subtype valve interstitial cells-fibroblast, which was closely associated with fibro-calcific progress of aortic valve. CTHRC1 highly expressed in the VIC subpopulation. Immune infiltration analysis demonstrated that mast cells, B cells, dendritic cells and eosinophils were involved in pathogenesis of CAVD. Correlation analysis demonstrated that CTHRC1 was correlated with mast cells mostly.
Conclusions: In summary, the study suggested that CTHRC1 was a key gene of CAVD and CTHRC1 might participate in the potential molecular pathways involved in the connection between infiltrating immune cells and myofibroblast phenotype VICs.
Keywords: Calcific aortic valve disease (CAVD); bioinformatics analysis; immune infiltration; machine learning algorithm; single-cell RNA sequencing.
2023 Journal of Thoracic Disease. All rights reserved.