Genes Differentially Expressed Across Major Arteries Are Enriched in Endothelial Dysfunction-Related Gene Sets: Implications for Relative Inter-artery Atherosclerosis Risk

Abstract

Atherosclerosis differs across major arteries. Although the biological basis is not fully understood, limited evidence of genetic differences has been documented. This study, therefore, was aimed to identify differentially expressed genes between clinically relevant major arteries and investigate their enrichment in endothelial dysfunction-related gene sets. A bioinformatic analysis of publicly available gene-level read counts for coronary, aortic, and tibial arteries was performed. Differential gene expression was conducted with DeSeq2 at a false discovery rate of 0.05. Differentially expressed genes were then subjected to over-representation analysis and active-subnetwork-oriented enrichment analysis, both at a false discovery rate of 0.005. Enriched terms common to both analyses were categorized for each contrast into immunity/inflammation-, membrane biology-, lipid metabolism-, and coagulation-related terms, and the top differentially expressed genes validated against Swiss Institute of Bioinformatics' Bgee database. There was mostly upregulation of differentially expressed genes for the coronary/tibial and aorta/tibial contrasts, but milder changes for the coronary/aorta contrast. Transcriptomic differences between coronary or aortic versus tibial samples largely involved immunity/inflammation-, membrane biology-, lipid metabolism-, and coagulation-related genes, suggesting potential to modulate endothelial dysfunction and atherosclerosis. These results imply atheroprone coronary and aortic environments compared with tibial artery tissue, which may explain observed relative inter-artery atherosclerosis risk.

Keywords: Differential gene expression; aorta; coronary plaque; endothelium; peripheral artery disease.

Figure 1.

Descriptive analysis: (A) Sex distribution. (B) Age distribution. (C) Hardy category distribution. (D) Principal component analysis of the grouping variable (SMTSD: tissue type).

Figure 2.

CT contrast DEGs: Overview and enrichment terms. (A) Heatmap of 3006 DEGs. (B) Top 20 GO terms. (C) Top clustered ASOEA terms. (D) Heatmap of 840 DEGs associated with both enriched GO and ASOEA terms.

Figure 3.

CT contrast: endothelial dysfunction-related DEGs. Heatmaps of common GO/ASOEA-related DEGs associated with (A) immunity/inflammation, (B) membrane biology, (C) lipid metabolism, and (D) coagulation, with the top up- and down-regulated genes labeled (up and down arrows respectively).

Figure 4.

AT contrast DEGs: overview and enrichment terms. (A) Heatmap of 2547 DEGs. (B) Top 20 GO terms. (C) Top clustered ASOEA terms. (D) Heatmap of 515 DEGs associated with both enriched GO and ASOEA terms.

Figure 5.

AT contrast: endothelial dysfunction-related DEGs. Heatmaps of common GO/ASOEA-related DEGs associated with (A) immunity/inflammation, (B) membrane biology, (C) lipid metabolism, and (D) coagulation, with the top up- and down-regulated genes labeled (up and down arrows respectively).

Figure 6.

CA contrast DEGs: overview and enrichment terms. (A) Heatmap of 1990 DEGs. (B) Top 20 GO terms. (C) Top clustered ASOEA terms. (D) Heatmap of 314 DEGs associated with both enriched GO and ASOEA terms.

Figure 7.

CA contrast: endothelial dysfunction-related DEGs. Heatmaps of common GO/ASOEA-related DEGs associated with (A) immunity/inflammation, (B) membrane biology, and (C) lipid metabolism, with the top up- and down-regulated genes labeled (up and down arrows respectively).

Figure 8.

Proposed model of genetic basis of relative inter-artery atherosclerosis risk.