Using next-generation RNA sequencing to examine ischemic changes induced by cold blood cardioplegia on the human left ventricular myocardium transcriptome

Abstract

Background: The exact mechanisms that underlie the pathological processes of myocardial ischemia in humans are unclear. Cardiopulmonary bypass with cardioplegic arrest allows the authors to examine the whole transcriptional profile of human left ventricular myocardium at baseline and after exposure to cold cardioplegia-induced ischemia as a human ischemia model.

Methods: The authors obtained biopsies from 45 patients undergoing aortic valve replacement surgery at baseline and after an average of 79 min of cold cardioplegic arrest. Samples were RNA sequenced and analyzed with the Partek Genomics Suite (Partek Inc., St. Louis, MO) for differential expression. Ingenuity Pathway Analysis (Ingenuity Systems, Redwood City, CA) and Biobase ExPlain (Biobase GmbH, Wolfenbuettel, Germany) systems were used for functional and pathway analyses.

Results: Of the 4,098 genes with a mean expression value greater than 5, 90% were down-regulated and 9.1% were up-regulated. Of those, 1,241 were significantly differentially expressed. Gene ontology analysis revealed significant down-regulation in immune inflammatory response and complement activation categories and highly consistent was the down-regulation of intelectin 1, proteoglycan, and secretory leukocyte peptidase inhibitor. Up-regulated genes of interest were FBJ murine osteosarcoma viral oncogene homolog and the hemoglobin genes hemoglobin α1 (HBA1) and hemoglobin β. In addition, analysis of transcription factor-binding sites revealed interesting targets in factors regulating reactive oxygen species production, apoptosis, immunity, cytokine production, and inflammatory response.

Conclusions: The authors have shown that the human left ventricle exhibits significant changes in gene expression in response to cold cardioplegia-induced ischemia during cardiopulmonary bypass, which provides great insight into the pathophysiology of ventricular ischemia, and thus, may help guide efforts to reduce myocardial damage during surgery.

Figure 1. Sample acquisition timeline

The baseline sample is acquired within minutes of the first dose of cardioplegia and application of the aortic cross-clamp. The postischemia sample is obtained shortly before the end of aortic cross-clamping. The red arrows show the timed application of cardioplegia every 20 min.

Figure 2. Volcano plot

Fold change on X-axis plotted against P-value on Y-axis. The horizontal line marks the unadjusted P = 0.05 and the red vertical lines mark a fold change of ±1.5. All dots in the upper left and right quadrant are considered significant before adjusting for multiple comparisons.

Figure 3. Gene Ontology (GO) group disruption a) Oxidoreductase activity and b) Oxygen transport

Shown are the two groups with the most pronounced disruption of a functional category in the GO ANOVA, implying changes in the pattern of gene expression within the functional group and potential disruption of normal operation of the group. The hemoglobin genes hemoglobin α1 (HBA1) and hemoglobin beta (HBB) disrupt the molecular function group oxidoreductase activity and oxygen transport. While the expression of the majority of genes in these categories is very similar between baseline and postischemia, HBB and HBA1 are significantly upregulated compared to all other genes in this category (disruption P < 0.001).

Figure 3. Gene Ontology (GO) group disruption a) Oxidoreductase activity and b) Oxygen transport

Shown are the two groups with the most pronounced disruption of a functional category in the GO ANOVA, implying changes in the pattern of gene expression within the functional group and potential disruption of normal operation of the group. The hemoglobin genes hemoglobin α1 (HBA1) and hemoglobin beta (HBB) disrupt the molecular function group oxidoreductase activity and oxygen transport. While the expression of the majority of genes in these categories is very similar between baseline and postischemia, HBB and HBA1 are significantly upregulated compared to all other genes in this category (disruption P < 0.001).

Figure 4. Gene Ontology (GO)-Enrichment

Forest Plot of postischemia compared to baseline in response to stress category. Green bar shows downregulation, red bar show upregulation with dark colors showing percent of significantly down- or upregulated genes (False discovery rate [FDR] < 0.05).

Figure 5. Oxidative stress Tox List in Ingenuity Pathway Analysis

Shown are groups with percent downregulation (green) and upregulation (red) matching the dataset. The numbers represent the number of genes in each category and the orange line represents the negative logarithmic P-value. PPARα = Peroxisome proliferator-activated receptor alpha.

Figure 6. TRANSFAC® (TRANScription FACtor) database positional weight matrices in promoters

Shown are maps of predicted binding sites of selected TRANSFAC® (Biobase GmbH, Wolfenbuettel, Germany) positional weight matrices in promoters of genes downregulated in response to ischemia. TSS = transcription start site.

Figure 7. Digital droplet (ddPCR) validation

Fluorescence amplitude plots for Carboxyfluorescein (FAM) labeled droplets in a representative A) baseline and B) postischemia sample for the intelectin 1 (ITLN1) gene. Each dot represents a single droplet, or event. The event number is displayed on the horizontal axis while the fluorescence amplitude is shown on the vertical axis. The blue dots represent high fluorescence intensity (positive droplets) while the black dots represent low intensity (negative droplets).