WIPI1 is a conserved mediator of right ventricular failure

Comparison of the stage-dependent mitochondrial changes in response to pressure overload between the diseased right and left ventricle in the rat

The right ventricle (RV) differs developmentally, anatomically and functionally from the left ventricle (LV). Therefore, characteristics of LV adaptation to chronic pressure overload cannot easily be extrapolated to the RV. Mitochondrial abnormalities are considered a crucial contributor in heart failure (HF), but have never been compared directly between RV and LV tissues and cardiomyocytes. To identify ventricle-specific mitochondrial molecular and functional signatures, we established rat models with two slowly developing disease stages (compensated and decompensated) in response to pulmonary artery banding (PAB) or ascending aortic banding (AOB). Genome-wide transcriptomic and proteomic analyses were used to identify differentially expressed mitochondrial genes and proteins and were accompanied by a detailed characterization of mitochondrial function and morphology. Two clearly distinguishable disease stages, which culminated in a comparable systolic impairment of the respective ventricle, were observed. Mitochondrial respiration was similarly impaired at the decompensated stage, while respiratory chain activity or mitochondrial biogenesis were more severely deteriorated in the failing LV. Bioinformatics analyses of the RNA-seq. and proteomic data sets identified specifically deregulated mitochondrial components and pathways. Although the top regulated mitochondrial genes and proteins differed between the RV and LV, the overall changes in tissue and cardiomyocyte gene expression were highly similar. In conclusion, mitochondrial dysfuntion contributes to disease progression in right and left heart failure. Ventricle-specific differences in mitochondrial gene and protein expression are mostly related to the extent of observed changes, suggesting that despite developmental, anatomical and functional differences mitochondrial adaptations to chronic pressure overload are comparable in both ventricles.

Using Omics to Identify Novel Therapeutic Targets in Heart Failure

Omics refers to the measurement and analysis of the totality of molecules or biological processes involved within an organism. Examples of omics data include genomics, transcriptomics, epigenomics, proteomics, metabolomics, and more. In this review, we present the available literature reporting omics data on heart failure that can inform the development of novel treatments or innovative treatment strategies for this disease. This includes polygenic risk scores to improve prediction of genomic data and the potential of multiomics to more efficiently identify potential treatment targets for further study. We also discuss the limitations of omic analyses and the barriers that must be overcome to maximize the utility of these types of studies. Finally, we address the current state of the field and future opportunities for using multiomics to better personalize heart failure treatment strategies.

Extracellular Matrix Instability and Chronic Inflammation Underlie Maladaptive Right Ventricular Pressure Overload Remodeling and Failure in Male Mice

Background

Right ventricular dysfunction (RVD) portends increased death risk for heart failure (HF) and pulmonary arterial hypertension (PAH) patients, regardless of left ventricular function or etiology. In both, RVD arises from the chronic RV pressure overload, and represents advanced cardiopulmonary disease. RV remodeling responses and survival rates of HF and PAH patients, however, differ by sex. Men develop more severe RVD and die at younger ages than do women. Mechanistic details of this sexual dimorphism in RV remodeling are incompletely understood. We sought to elucidate the cardiac pathophysiology underlying the sex-specific RV remodeling phenotypes, RV failure (RVF) versus compensated RVD.

Methods

We subjected male (M-) and female (F-) adult mice to moderate pulmonary artery banding (PAB) for 9wks. Mice underwent serial echocardiography, cardiac MRI, RV pressure-volume loop recordings, histologic and molecular analyses.

Results

M-PAB developed severe RVD with RVF, increased RV collagen deposition and degradation, extracellular matrix (ECM) instability, and activation and recruitment of macrophages. Despite the same severity and chronicity of RV pressure overload, F-PAB had more stable ECM, lacked chronic inflammation, and developed mild RVD without RVF.

Conclusions

ECM destabilization and chronic activation of recruited macrophages are associated with maladaptive RV remodeling and RVF in male PAB mice. Adaptive RV remodeling of female PAB mice lacked these histopathologic changes. Our findings suggest that these two pathophysiologic processes likely contribute to the sexual dimorphism of RV pressure overload remodeling. Further mechanistic studies are needed to assess their pathogenic roles and potential as targets for RVD therapy and RVF prevention.

CLINICAL PERSPECTIVE

What is new?: In a mouse model of pure PH, males but not females showed an association between ECM instability, chronic inflammation with activation of recruited macrophages, and severe RV dysfunction and failure.What are the clinical implications?: In male HF and PH patients, enhancing ECM stability and countering the recruitment and activation of macrophages may help preserve RV function such that RVF can be prevented or delayed. Further preclinical mechanistic studies are needed to assess the therapeutic potential of such approaches.

RESEARCH PERSPECTIVE

What new question does this study raise? What question should be addressed next?: What mechanisms regulate RV ECM stability and macrophage recruitment and activation in response to chronic RV pressure overload? Are these regulatory mechanisms dependent upon or independent of sex hormone signaling?

Machine learning algorithms assisted identification of post-stroke depression associated biological features

Objectives

Post-stroke depression (PSD) is a common and serious psychiatric complication which hinders functional recovery and social participation of stroke patients. Stroke is characterized by dynamic changes in metabolism and hemodynamics, however, there is still a lack of metabolism-associated effective and reliable diagnostic markers and therapeutic targets for PSD. Our study was dedicated to the discovery of metabolism related diagnostic and therapeutic biomarkers for PSD.

Methods

Expression profiles of GSE140275, GSE122709, and GSE180470 were obtained from GEO database. Differentially expressed genes (DEGs) were detected in GSE140275 and GSE122709. Functional enrichment analysis was performed for DEGs in GSE140275. Weighted gene co-expression network analysis (WGCNA) was constructed in GSE122709 to identify key module genes. Moreover, correlation analysis was performed to obtain metabolism related genes. Interaction analysis of key module genes, metabolism related genes, and DEGs in GSE122709 was performed to obtain candidate hub genes. Two machine learning algorithms, least absolute shrinkage and selection operator (LASSO) and random forest, were used to identify signature genes. Expression of signature genes was validated in GSE140275, GSE122709, and GSE180470. Gene set enrichment analysis (GSEA) was applied on signature genes. Based on signature genes, a nomogram model was constructed in our PSD cohort (27 PSD patients vs. 54 controls). ROC curves were performed for the estimation of its diagnostic value. Finally, correlation analysis between expression of signature genes and several clinical traits was performed.

Results

Functional enrichment analysis indicated that DEGs in GSE140275 enriched in metabolism pathway. A total of 8,188 metabolism associated genes were identified by correlation analysis. WGCNA analysis was constructed to obtain 3,471 key module genes. A total of 557 candidate hub genes were identified by interaction analysis. Furthermore, two signature genes (SDHD and FERMT3) were selected using LASSO and random forest analysis. GSEA analysis found that two signature genes had major roles in depression. Subsequently, PSD cohort was collected for constructing a PSD diagnosis. Nomogram model showed good reliability and validity. AUC values of receiver operating characteristic (ROC) curve of SDHD and FERMT3 were 0.896 and 0.964. ROC curves showed that two signature genes played a significant role in diagnosis of PSD. Correlation analysis found that SDHD (r = 0.653, P < 0.001) and FERM3 (r = 0.728, P < 0.001) were positively related to the Hamilton Depression Rating Scale 17-item (HAMD) score.

Conclusion

A total of 557 metabolism associated candidate hub genes were obtained by interaction with DEGs in GSE122709, key modules genes, and metabolism related genes. Based on machine learning algorithms, two signature genes (SDHD and FERMT3) were identified, they were proved to be valuable therapeutic and diagnostic biomarkers for PSD. Early diagnosis and prevention of PSD were made possible by our findings.

Identification of hub genes and transcription factor regulatory network for heart failure using RNA-seq data and robust rank aggregation analysis

Background

Heart failure (HF) is the end stage of various cardiovascular diseases with a high mortality rate. Novel diagnostic and therapeutic biomarkers for HF are urgently required. Our research aims to identify HF-related hub genes and regulatory networks using bioinformatics and validation assays.

Methods

Using four RNA-seq datasets in the Gene Expression Omnibus (GEO) database, we screened differentially expressed genes (DEGs) of HF using Removal of Unwanted Variation from RNA-seq data (RUVSeq) and the robust rank aggregation (RRA) method. Then, hub genes were recognized using the STRING database and Cytoscape software with cytoHubba plug-in. Furthermore, reliable hub genes were validated by the GEO microarray datasets and quantitative reverse transcription polymerase chain reaction (qRT-PCR) using heart tissues from patients with HF and non-failing donors (NFDs). In addition, R packages “clusterProfiler” and “GSVA” were utilized for enrichment analysis. Moreover, the transcription factor (TF)–DEG regulatory network was constructed by Cytoscape and verified in a microarray dataset.

Results

A total of 201 robust DEGs were identified in patients with HF and NFDs. STRING and Cytoscape analysis recognized six hub genes, among which ASPN, COL1A1, and FMOD were confirmed as reliable hub genes through microarray datasets and qRT-PCR validation. Functional analysis showed that the DEGs and hub genes were enriched in T-cell-mediated immune response and myocardial glucose metabolism, which were closely associated with myocardial fibrosis. In addition, the TF–DEG regulatory network was constructed, and 13 significant TF–DEG pairs were finally identified.

Conclusion

Our study integrated different RNA-seq datasets using RUVSeq and the RRA method and identified ASPN, COL1A1, and FMOD as potential diagnostic biomarkers for HF. The results provide new insights into the underlying mechanisms and effective treatments of HF.

WIPI proteins: Biological functions and related syndromes

WIPI (WD-repeat protein Interacting with PhosphoInositides) are important effectors in autophagy. These proteins bind phosphoinositides and recruit autophagy proteins. In mammals, there are four WIPI proteins: WIPI1, WIPI2, WIPI3 (WDR45B), and WIPI4 (WDR45). These proteins consist of a seven-bladed β-propeller structure. Recently, pathogenic variants in genes encoding these proteins have been recognized to cause human diseases with a predominant neurological phenotype. Defects in WIPI2 cause a disease characterized mainly by intellectual disability and variable other features while pathogenic variants in WDR45B and WDR45 have been recently reported to cause El-Hattab-Alkuraya syndrome and beta-propeller protein-associated neurodegeneration (BPAN), respectively. Whereas, there is no disease linked to WIPI1 yet, one study linked it neural tube defects (NTD). In this review, the role of WIPI proteins in autophagy is discussed first, then syndromes related to these proteins are summarized.

Bioinformatics and Experimental Analyses Reveal NFIC as an Upstream Transcriptional Regulator for Ischemic Cardiomyopathy

Ischemic cardiomyopathy (ICM) caused by coronary artery disease always leads to myocardial infarction and heart failure. Identification of novel transcriptional regulators in ICM is an effective method to establish new diagnostic and therapeutic strategies. In this study, we used two RNA-seq datasets and one microarray dataset from different studies, including 25 ICM and 21 non-failing control (NF) samples of human left ventricle tissues for further analysis. In total, 208 differentially expressed genes (DEGs) were found by combining two RNA-seq datasets with batch effects removed. GO and KEGG analyses of DEGs indicated that the response to wounding, positive regulation of smooth muscle contraction, chromatin, PI3K-Akt signaling pathway, and transporters pathways are involved in ICM. Simple Enrichment Analysis found that NFIC-binding motifs are enriched in promoter regions of downregulated genes. The Gene Importance Calculator further proved that NFIC is vital. NFIC and its downstream genes were verified in the validating microarray dataset. Meanwhile, in rat cardiomyocyte cell line H9C2 cells, two genes (Tspan1 and Hopx) were confirmed, which decreased significantly along with knocking down Nfic expression. In conclusion, NFIC participates in the ICM process by regulating TSPAN1 and HOPX. NFIC and its downstream genes may be marker genes and potential diagnostic and therapeutic targets for ICM.

Targeting Microtubules for the Treatment of Heart Disease

Heart disease remains the leading cause of morbidity and mortality worldwide. With the advancement of modern technology, the role(s) of microtubules in the pathogenesis of heart disease has become increasingly apparent, though currently there are limited treatments targeting microtubule-relevant mechanisms. Here, we review the functions of microtubules in the cardiovascular system and their specific adaptive and pathological phenotypes in cardiac disorders. We further explore the use of microtubule-targeting drugs and highlight promising druggable therapeutic targets for the future treatment of heart diseases.

Inflammatory Glycoprotein 130 Signaling Links Changes in Microtubules and Junctophilin-2 to Altered Mitochondrial Metabolism and Right Ventricular Contractility

BACKGROUND

Right ventricular dysfunction (RVD) is the leading cause of death in pulmonary arterial hypertension (PAH), but no RV-specific therapy exists. We showed microtubule-mediated junctophilin-2 dysregulation (MT-JPH2 pathway) causes t-tubule disruption and RVD in rodent PAH, but the druggable regulators of this critical pathway are unknown. GP130 (glycoprotein 130) activation induces cardiomyocyte microtubule remodeling in vitro; however, the effects of GP130 signaling on the MT-JPH2 pathway and RVD resulting from PAH are undefined.

METHODS

Immunoblots quantified protein abundance, quantitative proteomics defined RV microtubule-interacting proteins (MT-interactome), metabolomics evaluated the RV metabolic signature, and transmission electron microscopy assessed RV cardiomyocyte mitochondrial morphology in control, monocrotaline, and monocrotaline-SC-144 (GP130 antagonist) rats. Echocardiography and pressure-volume loops defined the effects of SC-144 on RV-pulmonary artery coupling in monocrotaline rats (8-16 rats per group). In 73 patients with PAH, the relationship between interleukin-6, a GP130 ligand, and RVD was evaluated.

RESULTS

SC-144 decreased GP130 activation, which normalized MT-JPH2 protein expression and t-tubule structure in the monocrotaline RV. Proteomics analysis revealed SC-144 restored RV MT-interactome regulation. Ingenuity pathway analysis of dysregulated MT-interacting proteins identified a link between microtubules and mitochondrial function. Specifically, SC-144 prevented dysregulation of electron transport chain, Krebs cycle, and the fatty acid oxidation pathway proteins. Metabolomics profiling suggested SC-144 reduced glycolytic dependence, glutaminolysis induction, and enhanced fatty acid metabolism. Transmission electron microscopy and immunoblots indicated increased mitochondrial fission in the monocrotaline RV, which SC-144 mitigated. GP130 antagonism reduced RV hypertrophy and fibrosis and augmented RV-pulmonary artery coupling without altering PAH severity. In patients with PAH, higher interleukin-6 levels were associated with more severe RVD (RV fractional area change 23±12% versus 30±10%, P=0.002).

CONCLUSIONS

GP130 antagonism reduces MT-JPH2 dysregulation, corrects metabolic derangements in the RV, and improves RVD in monocrotaline rats.

Exploration of Potential Genetic Biomarkers for Heart Failure: A Systematic Review

Patients with heart failure (HF) often present with signs and symptoms that are often nonspecific and with a wide differential diagnosis, making diagnosis and prognosis of HF by clinical presentation alone challenging. Our knowledge on genetic diversity is rapidly evolving with high-throughput DNA sequencing technology, which makes a great potential for genetic biomarker development. The present review attempts to provide a comprehensive review on the modification of major genetic components in HF patients and to explore the potential application of these components as clinical biomarkers in the diagnosis and in monitoring the progress of HF. The literature search was conducted using six databases, resulting in the inclusion of eighteen studies in the review. The findings of these studies were summarized narratively. An appraisal of the reporting quality of the included studies was conducted using a twelve-item checklist adapted from the Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) checklist. The findings showed that changes in genetic components in patients with HF compared to healthy controls could be noninvasive diagnostic or prognostic tools for HF with higher specificity and sensitivity in comparison with the traditional biomarkers. This review provided evidence for the potential of developing genetic biomarkers of HF.

EnRank: An Ensemble Method to Detect Pulmonary Hypertension Biomarkers Based on Feature Selection and Machine Learning Models

Pulmonary hypertension (PH) is a common disease that affects the normal functioning of the human pulmonary arteries. The peripheral blood mononuclear cells (PMBCs) served as an ideal source for a minimally invasive disease diagnosis. This study hypothesized that the transcriptional fluctuations in the PMBCs exposed to the PH arteries may stably reflect the disease. However, the dimension of a human transcriptome is much higher than the number of samples in all the existing datasets. So, an ensemble feature selection algorithm, EnRank, was proposed to integrate the ranking information of four popular feature selection algorithms, i.e., T-test (Ttest), Chi-squared test (Chi2), ridge regression (Ridge), and Least Absolute Shrinkage and Selection Operator (Lasso). Our results suggested that the EnRank-detected biomarkers provided useful information from these four feature selection algorithms and achieved very good prediction accuracy in predicting the PH patients. Many of the EnRank-detected biomarkers were also supported by the literature.

Identification of Circular RNA-MicroRNA-Messenger RNA Regulatory Network in Atrial Fibrillation by Integrated Analysis

BACKGROUND

Circular RNA (circRNA) is a noncoding RNA that forms a closed-loop structure, and its abnormal expression may cause disease. We aimed to find potential network for circRNA-related competitive endogenous RNA (ceRNA) in atrial fibrillation (AF).

METHODS

The circRNA, miRNA, and mRNA expression profiles in the heart tissue from AF patients were retrieved from the Gene Expression Omnibus database and analyzed comprehensively. Differentially expressed circRNAs (DEcircRNAs), differentially expressed miRNAs (DEmiRNAs), and differentially expressed mRNAs (DEmRNAs) were identified, followed by the establishment of DEcircRNA-DEmiRNA-DEmRNA regulatory network. Functional annotation analysis of host gene of DEcircRNAs and DEmRNAs in ceRNA regulatory network was performed. In vitro experiment and electronic validation were used to validate the expression of DEcircRNAs, DEmiRNAs, and DEmRNAs.

RESULTS

A total of 1611 DEcircRNAs, 51 DEmiRNAs, and 1250 DEmRNAs were identified in AF. The DEcircRNA-DEmiRNA-DEmRNA network contained 62 circRNAs, 14 miRNAs, and 728 mRNAs. Among which, two ceRNA regulatory pairs of hsa-circRNA-100053-hsa-miR-455-5p-TRPV1 and hsa-circRNA-005843-hsa-miR-188-5p-SPON1 were identified. In addition, six miRNA-mRNA regulatory pairs including hsa-miR-34c-5p-INMT, hsa-miR-1253-DDIT4L, hsa-miR-508-5p-SMOC2, hsa-miR-943-ACTA1, hsa-miR-338-3p-WIPI1, and hsa-miR-199a-3p-RAP1GAP2 were also obtained. MTOR was a significantly enriched signaling pathway of host gene of DEcircRNAs. In addition, arrhythmogenic right ventricular cardiomyopathy, dilated cardiomyopathy, and hypertrophic cardiomyopathy were remarkably enriched signaling pathways of DEmRNAs in DEcircRNA-DEmiRNA-DEmRNA regulatory network. The expression validation of hsa-circRNA-402565, hsa-miR-34c-5p, hsa-miR-188-5p, SPON1, DDIT4L, SMOC2, and WIPI1 was consistent with the integrated analysis.

CONCLUSION

We speculated that hsa-circRNA-100053-hsa-miR-455-5p-TRPV1 and hsa-circRNA-005843-hsa-miR-188-5p-SPON1 interaction pairs may be involved in AF.

Tissue-specific small heat shock protein 20 activation is not associated with traditional autophagy markers in Ossabaw swine with cardiometabolic heart failure

The small heat shock protein 20 (HSPB6) emerges as a potential upstream mediator of autophagy. Although autophagy is linked to several clinical disorders, how HSPB6 and autophagy are regulated in the setting of heart failure (HF) remains unknown. The goal of this study was to assess the activation of the HSPB6 and its association with other well-established autophagy markers in central and peripheral tissues from a preclinical Ossabaw swine model of cardiometabolic HF induced by Western diet and chronic cardiac pressure overload. We hypothesized HSPB6 would be activated in central and peripheral tissues, stimulating autophagy. We found that autophagy in the heart is interrupted at various stages of the process in a chamber-specific manner. Protein levels of HSPB6, Beclin 1, and p62 are increased in the right ventricle, whereas only HSPB6 was increased in the left ventricle. Unlike the heart, samples from the triceps brachii long head showed only an increase in the protein level of p62, highlighting interesting central versus peripheral differences in autophagy regulation. In the right coronary artery, total HSPB6 protein expression was decreased and associated with an increase in LC3B-II/LC3B-I ratio, demonstrating a different mechanism of autophagy dysregulation in the coronary vasculature. Thus, contrary to our hypothesis, activation of HSPB6 was differentially regulated in a tissue-specific manner and observed in parallel with variable states of autophagy markers assessed by protein levels of LC3B, p62, and Beclin 1. Our data provide insight into how the HSPB6/autophagy axis is regulated in a preclinical swine model with potential relevance to heart failure with preserved ejection fraction.NEW & NOTEWORTHY Our study shows that the activation of HSPB6 is tissue specific and associated with variable states of downstream markers of autophagy in a unique preclinical swine model of cardiometabolic HF with potential relevance to HFpEF. These findings suggest that targeted approaches could be an important consideration regarding the development of drugs aimed at this intracellular recycling process.

BCO App: tools for generating BioCompute Objects from next-generation sequencing workflows and computations

The BioCompute Object (BCO) standard is an IEEE standard (IEEE 2791-2020) designed to facilitate the communication of next-generation sequencing data analysis with applications across academia, government agencies, and industry. For example, the Food and Drug Administration (FDA) supports the standard for regulatory submissions and includes the standard in their Data Standards Catalog for the submission of HTS data. We created the BCO App to facilitate BCO generation in a range of computational environments and, in part, to participate in the Advanced Track of the precisionFDA BioCompute Object App-a-thon. The application facilitates the generation of BCOs from both workflow metadata provided as plaintext and from workflow contents written in the Common Workflow Language. The application can also access and ingest task execution results from the Cancer Genomics Cloud (CGC), an NCI funded computational platform. Creating a BCO from a CGC task significantly reduces the time required to generate a BCO on the CGC by auto-populating workflow information fields from CGC workflow and task execution results. The BCO App supports exporting BCOs as JSON or PDF files and publishing BCOs to both the CGC platform and to GitHub repositories.

Identification of Upstream Transcriptional Regulators of Ischemic Cardiomyopathy Using Cardiac RNA-Seq Meta-Analysis

Ischemic cardiomyopathy (ICM), characterized by pre-existing myocardial infarction or severe coronary artery disease, is the major cause of heart failure (HF). Identification of novel transcriptional regulators in ischemic HF can provide important biomarkers for developing new diagnostic and therapeutic strategies. In this study, we used four RNA-seq datasets from four different studies, including 41 ICM and 42 non-failing control (NF) samples of human left ventricle tissues, to perform the first RNA-seq meta-analysis in the field of clinical ICM, in order to identify important transcriptional regulators and their targeted genes involved in ICM. Our meta-analysis identified 911 differentially expressed genes (DEGs) with 582 downregulated and 329 upregulated. Interestingly, 54 new DEGs were detected only by meta-analysis but not in individual datasets. Upstream regulator analysis through Ingenuity Pathway Analysis (IPA) identified three key transcriptional regulators. TBX5 was identified as the only inhibited regulator (z-score = -2.89). F2R and SFRP4 were identified as the activated regulators (z-scores = 2.56 and 2.00, respectively). Multiple downstream genes regulated by TBX5, F2R, and SFRP4 were involved in ICM-related diseases such as HF and arrhythmia. Overall, our study is the first to perform an RNA-seq meta-analysis for clinical ICM and provides robust candidate genes, including three key transcriptional regulators, for future diagnostic and therapeutic applications in ischemic heart failure.

Transcriptomic profiles reveal differences between the right and left ventricle in normoxia and hypoxia

Chronic hypoxia from diseases in the lung, such as pulmonary hypertension, pulmonary fibrosis, and chronic obstructive pulmonary disease, can increase pulmonary vascular resistance, resulting in hypertrophy and dysfunction of the right ventricle (RV). In order to obtain insight into RV biology and perhaps uncover potentially novel therapeutic approaches for RV dysfunction, we performed RNA-sequencing (RNA-seq) of RV and LV tissue from rats in normal ambient conditions or subjected to hypoxia (10% O2 ) for 2 weeks. Gene ontology and pathway analysis of the RV and LV revealed multiple transcriptomic differences, in particular increased expression in the RV of genes related to immune function in both normoxia and hypoxia. Immune cell profiling by flow cytometry of cardiac digests revealed that in both conditions, the RV had a larger percentage than the LV of double-positive CD45+ /CD11b/c+ cells (which are predominantly macrophages and dendritic cells). Analysis of gene expression changes under hypoxic conditions identified multiple pathways that may contribute to hypoxia-induced changes in the RV, including increased expression of genes related to cell mitosis/proliferation and decreased expression of genes related to metabolic processes. Together, the findings indicate that the RV differs from the LV with respect to content of immune cells and expression of certain genes, thus suggesting the two ventricles differ in aspects of pathophysiology and in potential therapeutic targets for RV dysfunction.