miRNAs may play a major role in the control of gene expression in key pathobiological processes in Chagas disease cardiomyopathy

Abstract

Chronic Chagas disease cardiomyopathy (CCC), an especially aggressive inflammatory dilated cardiomyopathy caused by lifelong infection with the protozoan Trypanosoma cruzi, is a major cause of cardiomyopathy in Latin America. Although chronic myocarditis may play a major pathogenetic role, little is known about the molecular mechanisms responsible for its severity. The aim of this study is to study the genes and microRNAs expression in tissues and their connections in regards to the pathobiological processes. To do so, we integrated for the first time global microRNA and mRNA expression profiling from myocardial tissue of CCC patients employing pathways and network analyses. We observed an enrichment in biological processes and pathways associated with the immune response and metabolism. IFNγ, TNF and NFkB were the top upstream regulators. The intersections between differentially expressed microRNAs and differentially expressed target mRNAs showed an enrichment in biological processes such as Inflammation, inflammation, Th1/IFN-γ-inducible genes, fibrosis, hypertrophy, and mitochondrial/oxidative stress/antioxidant response. MicroRNAs also played a role in the regulation of gene expression involved in the key cardiomyopathy-related processes fibrosis, hypertrophy, myocarditis and arrhythmia. Significantly, a discrete number of differentially expressed microRNAs targeted a high number of differentially expressed mRNAs (>20) in multiple processes. Our results suggest that miRNAs orchestrate expression of multiple genes in the major pathophysiological processes in CCC heart tissue. This may have a bearing on pathogenesis, biomarkers and therapy.

Fig 1. Principal component analysis (PCA) plots.

Principal component analysis (PCA) plot of samples was performed based (A) on 1535 differentially expressed genes (DEGs) between CCC and controls. The two main principal components have the largest possible variance (68.8%). The 1535 DEGs had an equal contribution to the first component (ranging from 6.0E-3% to 0.1%). For the second component, 25 DEGs had a contribution over 0.25% (GAB3, WBSCR27, LOC100130930, C1orf35, ISLR2, SLC25A34, NOTCH2, TSPAN32, ATP1A1OS, C11orf65, ZNF214, APCDD1, C1QTNF6, RANBP17, MNS1, APBB3, ANGPTL1, BEND6, LTB, MMP9, ITGB2, PIK3R1, NOTCH2NL, TRMT5 and XLOC_005730); (B) or on 80 differentially expressed miRNAs (DEMs) between CCC and controls. The two main components explain 84.7% of the variance. For the first component, the 80 DEMS had an equal contribution (ranging from 0.24% to1.74%). For the second component, even if all the DEMs contribute, six of the DEMs have a main contribution (hsa-miR-155: 12.8%; hsa-miR-146a: 9.0%; hsa-miR-302d: 8.8%; hsa-miR-378: 8.1%; hsa-miR-486: 7.0%; and hsa-miR-221: 5.2%).

Fig 2. DEGs and DEM-targeted DEGs present in relevant canonical pathways and pathophysiological processes.

The stacked bar chart displays the number of DEG (blue) and DEM-targeted DEGs (red) present in each pathway. A. Ingenuity Pathway Analysis (IPA) canonical pathways representative of the most significantly enriched in the heart of CCC patients. B. DEG and DEM-targeted DEGs in specific biological processes relevant for the CCC pathogenesis. The numerical value in the parentheses in front of each pathway name represents the total number of genes in that pathway/process.

Fig 3. Enrichment analysis of cell subset and tissue signatures.

Signatures of different tissues and cell types from ARCHS4 tissue database enriched with up-regulated (red nodes) or down-regulated (blue nodes) genes compared to controls (Adjusted P-value < 0.001). The width of edges (connecting lines) is proportional to the number of genes shared by two signatures. The size of nodes is proportional to the -log10 Adjusted P-value.

Fig 4. DEM-DEG network related to the main Chagas disease pathobiological features.

Networks with DEMs and DEGs related to myocarditis, fibrosis, arrhythmia and hypertrophy were built using IPA software. Each built network contains molecules represented as nodes, and the biological relationship between two nodes is represented as an edge (line). All edges (connecting lines) are interactions supported by at least one reference from the literature or from canonical information stored in the IPA Ingenuity Knowledge Base (IKB). Full lines are direct interactions, dotted lines are indirect interactions. Upregulated microRNAs and mRNAs are colored in hues of red, and downregulated molecules are colored in hues of green according to the intensity of expression. Each node shape represents one type of molecule.