Identification of HIBCH as a Fatty Acid Metabolism-Related Biomarker in Aortic Valve Calcification Using Bioinformatics

Abstract

Objective. To identify fatty acid metabolism-related biomarkers of aortic valve calcification (AVC) using bioinformatics and to research the role of immune cell infiltration for AVC. Methods. The AVC dataset was retrieved from the Gene Expression Omnibus database. R package is used for differential expression genes analysis and weighted gene coexpression analysis. The differentially coexpressed genes were identified by the Venn diagram, followed by Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analyses of differentially coexpressed genes. Functions closely related to AVC were identified by GO and KEGG enrichment analyses of differentially coexpressed genes. Genes related to fatty acid metabolism were retrieved from the Molecular Signatures Database (MSigDB) database. After removing duplicate genes, least absolute shrinkage and selection operator (LASSO) regression analysis, support vector machine recursive feature elimination (SVM-RFE), and random forest were applied to recognize biomarkers related to fatty acid metabolism in AVC. The CIBERSORT tool was used to analyze infiltration of immune cells in normal and AVC samples. Correlations between biomarkers and immune cells were calculated. Finally, HIBCH-related pathway was predicted by single-gene gene set enrichment analysis (GSEA). Results. 2416 differentially expressed genes and one coexpression module were identified. A total of 1473 differentially coexpressed genes were acquired. GO and KEGG enrichment analyses demonstrated that differentially coexpressed genes were closely related to fatty acid metabolism. LASSO regression analysis, SVM-REF, and random forest revealed that 3-hydroxyisobutyryl-CoA hydrolase (HIBCH) was a biomarker of fatty acid metabolism-related genes in AVC. Significant high levels of memory B cells were found in AVC than normal samples, while activated natural killer (NK) cells were significantly low in AVC than normal samples. A significantly positive relevance was observed between HIBCH and activated NK cells, regulatory T cells, monocytes, naïve B cells, activated dendritic cells, resting memory CD4 T cells, resting NK cells, and CD8 T cells. A significantly negative relevance was observed between HIBCH and activated memory CD4 T cells, memory B cells, neutrophils, gamma delta T cells, M0 macrophages, and plasma cells. The single-gene GSEA results suggest that HIBCH may work through the inhibition of multiple immune-related pathways. Conclusion. HIBCH is closely relevant to immune cell infiltration in AVC and could be applied as a diagnostic marker for AVC.