Pathogenic variants damage cell composition and single cell transcription in cardiomyopathies

Patterns of unwanted biological and technical expression variation among 49 human tissues

Tissue gene expression studies are impacted by biological and technical sources of variation, which can be broadly classified into wanted and unwanted variation. The latter, if not addressed, results in misleading biological conclusions. Methods have been proposed to reduce unwanted variation, such as normalization and batch correction. A more accurate understanding of all causes of variation could significantly improve the ability of these methods to remove unwanted variation while retaining variation corresponding to the biological question of interest. We used 17,282 samples from 49 human tissues in the Genotype Tissue Expression (GTEx) dataset (v8) to investigate patterns and causes of expression variation. Transcript expression was transformed to z-scores and only the most variable 2% of transcripts were evaluated and clustered based on co-expression patterns. Clustered gene sets were assigned to different biological or technical causes based on histologic appearances and metadata elements. We identified 522 variable transcript clusters (median 11 per tissue) among the samples. Of these, 63% were confidently explained, 16% were likely explained, 7% were low confidence explanations and 14% had no clear cause. Histologic analysis annotated 46 clusters. Other common causes of variability included sex, sequencing contamination, immunoglobulin diversity, and compositional tissue differences. Less common biological causes included death interval (Hardy score), disease status, and age. Technical causes included blood draw timing and harvesting differences. Many of the causes of variation in bulk tissue expression were identifiable in the Tabula Sapiens dataset of single cell expression. This is among the largest explorations of the underlying sources of tissue expression variation. It uncovered expected and unexpected causes of variable gene expression and demonstrated the utility of matched histologic specimens. It further demonstrated the value of acquiring meaningful tissue harvesting metadata elements to use for improved normalization, batch correction, and analysis of both bulk and single cell RNA-seq data.

PBX/Knotted 1 homeobox-2 (PKNOX2) is a novel regulator of myocardial fibrosis

Much effort has been made to uncover the cellular heterogeneities of human hearts by single-nucleus RNA sequencing. However, the cardiac transcriptional regulation networks have not been systematically described because of the limitations in detecting transcription factors. In this study, we optimized a pipeline for isolating nuclei and conducting single-nucleus RNA sequencing targeted to detect a higher number of cell signal genes and an optimal number of transcription factors. With this unbiased protocol, we characterized the cellular composition of healthy human hearts and investigated the transcriptional regulation networks involved in determining the cellular identities and functions of the main cardiac cell subtypes. Particularly in fibroblasts, a novel regulator, PKNOX2, was identified as being associated with physiological fibroblast activation in healthy hearts. To validate the roles of these transcription factors in maintaining homeostasis, we used single-nucleus RNA-sequencing analysis of transplanted failing hearts focusing on fibroblast remodelling. The trajectory analysis suggested that PKNOX2 was abnormally decreased from fibroblast activation to pathological myofibroblast formation. Both gain- and loss-of-function in vitro experiments demonstrated the inhibitory role of PKNOX2 in pathological fibrosis remodelling. Moreover, fibroblast-specific overexpression and knockout of PKNOX2 in a heart failure mouse model induced by transverse aortic constriction surgery significantly improved and aggravated myocardial fibrosis, respectively. In summary, this study established a high-quality pipeline for single-nucleus RNA-sequencing analysis of heart muscle. With this optimized protocol, we described the transcriptional regulation networks of the main cardiac cell subtypes and identified PKNOX2 as a novel regulator in suppressing fibrosis and a potential therapeutic target for future translational studies.

A Multimodal Omics Framework to Empower Target Discovery for Cardiovascular Regeneration

Ischaemic heart disease is a global healthcare challenge with high morbidity and mortality. Early revascularisation in acute myocardial infarction has improved survival; however, limited regenerative capacity and microvascular dysfunction often lead to impaired function and the development of heart failure. New mechanistic insights are required to identify robust targets for the development of novel strategies to promote regeneration. Single-cell RNA sequencing (scRNA-seq) has enabled profiling and analysis of the transcriptomes of individual cells at high resolution. Applications of scRNA-seq have generated single-cell atlases for multiple species, revealed distinct cellular compositions for different regions of the heart, and defined multiple mechanisms involved in myocardial injury-induced regeneration. In this review, we summarise findings from studies of healthy and injured hearts in multiple species and spanning different developmental stages. Based on this transformative technology, we propose a multi-species, multi-omics, meta-analysis framework to drive the discovery of new targets to promote cardiovascular regeneration.

Deciphering the role of SMARCA4 in cardiac disorders: Insights from single-cell studies on dilated cardiomyopathy and coronary heart disease

BACKGROUND

Dilated cardiomyopathy (DCM) and coronary heart disease (CHD) stand as two of the foremost causes of mortality. However, the comprehensive comprehension of the regulatory mechanisms governing DCM and CHD remains limited, particularly from the vantage point of single-cell transcriptional analysis.

METHOD

We used the GSE121893 dataset from the GEO database, analyzing single-cell expressions with tools like DropletUtils, Seurat, and Monocle. We also utilized the GSVA package for comparing gene roles in DCM and CHD, Finally, we conducted qRT-PCR and Western blot analyses to measure the expression levels of SMARCA4, Col1A1, Col3A1 and α-SMA, and the role of SMARCA4 on fibroblasts were explored by EdU and Transwell assay.

RESULTS

Our analysis identified six cell types in heart tissue, with fibroblasts showing the most interaction with other cells. DEGs in fibroblasts were linked to muscle development and morphogenesis. Pseudotime analysis revealed the dynamics of fibroblast changes in both the normal and disease groups and many transcription factors (TFs) potentially involved in this process. Among these TFs, SMARCA4 which was translated into protein BRG1, showed the most significantly difference. In vivo experiments have demonstrated that SMARCA4 indeed promoted fibroblasts proliferation and migration.

CONCLUSION

This study provides a clearer understanding of cell-type dynamics in heart diseases, emphasizing the role of fibroblasts and the significance of SMARCA4 in their function. Our results offer insights into the cellular mechanisms underlying DCM and CHD, potentially guiding future therapeutic strategies.

AAV9:PKP2 improves heart function and survival in a Pkp2-deficient mouse model of arrhythmogenic right ventricular cardiomyopathy

BACKGROUND

Arrhythmogenic right ventricular cardiomyopathy (ARVC) is a familial cardiac disease associated with ventricular arrhythmias and an increased risk of sudden cardiac death. Currently, there are no approved treatments that address the underlying genetic cause of this disease, representing a significant unmet need. Mutations in Plakophilin-2 (PKP2), encoding a desmosomal protein, account for approximately 40% of ARVC cases and result in reduced gene expression.

METHODS

Our goal is to examine the feasibility and the efficacy of adeno-associated virus 9 (AAV9)-mediated restoration of PKP2 expression in a cardiac specific knock-out mouse model of Pkp2.

RESULTS

We show that a single dose of AAV9:PKP2 gene delivery prevents disease development before the onset of cardiomyopathy and attenuates disease progression after overt cardiomyopathy. Restoration of PKP2 expression leads to a significant extension of lifespan by restoring cellular structures of desmosomes and gap junctions, preventing or halting decline in left ventricular ejection fraction, preventing or reversing dilation of the right ventricle, ameliorating ventricular arrhythmia event frequency and severity, and preventing adverse fibrotic remodeling. RNA sequencing analyses show that restoration of PKP2 expression leads to highly coordinated and durable correction of PKP2-associated transcriptional networks beyond desmosomes, revealing a broad spectrum of biological perturbances behind ARVC disease etiology.

CONCLUSIONS

We identify fundamental mechanisms of PKP2-associated ARVC beyond disruption of desmosome function. The observed PKP2 dose-function relationship indicates that cardiac-selective AAV9:PKP2 gene therapy may be a promising therapeutic approach to treat ARVC patients with PKP2 mutations.

Microfluidic platform for omics analysis on single cells with diverse morphology and size: A review

BACKGROUND

Microfluidic techniques have emerged as powerful tools in single-cell research, facilitating the exploration of omics information from individual cells. Cell morphology is crucial for gene expression and physiological processes. However, there is currently a lack of integrated analysis of morphology and single-cell omics information. A critical challenge remains: what platform technologies are the best option to decode omics data of cells that are complex in morphology and size?

RESULTS

This review highlights achievements in microfluidic-based single-cell omics and isolation of cells based on morphology, along with other cell sorting methods based on physical characteristics. Various microfluidic platforms for single-cell isolation are systematically presented, showcasing their diversity and adaptability. The discussion focuses on microfluidic devices tailored to the distinct single-cell isolation requirements in plants and animals, emphasizing the significance of considering cell morphology and cell size in optimizing single-cell omics strategies. Simultaneously, it explores the application of microfluidic single-cell sorting technologies to single-cell sequencing, aiming to effectively integrate information about cell shape and size.

SIGNIFICANCE AND NOVELTY

The novelty lies in presenting a comprehensive overview of recent accomplishments in microfluidic-based single-cell omics, emphasizing the integration of different microfluidic platforms and their implications for cell morphology-based isolation. By underscoring the pivotal role of the specialized morphology of different cells in single-cell research, this review provides robust support for delving deeper into the exploration of single-cell omics data.

Brooklyn plots to identify co-expression dysregulation in single cell sequencing

Altered open chromatin regions, impacting gene expression, is a feature of some human disorders. We discovered it is possible to detect global changes in genomically-related adjacent gene co-expression within single cell RNA sequencing (scRNA-seq) data. We built a software package to generate and test non-randomness using 'Brooklyn plots' to identify the percent of genes significantly co-expressed from the same chromosome in ∼10 MB intervals across the genome. These plots establish an expected low baseline of co-expression in scRNA-seq from most cell types, but, as seen in dilated cardiomyopathy cardiomyocytes, altered patterns of open chromatin appear. These may relate to larger regions of transcriptional bursting, observable in single cell, but not bulk datasets.

Comparison of the negative effect of remimazolam and propofol on cardiac contractility: Analysis of a randomised parallel-group trial and a preclinical ex vivo study

Remimazolam is a newly developed ultra-short-acting benzodiazepine that exerts sedative effects. This study aimed to clarify the effects of remimazolam on cardiac contractility. In a randomised-parallel group trial, haemodynamic parameters were compared between propofol (n = 11) and remimazolam (n = 12) groups during the induction of general anaesthesia in patients undergoing non-cardiac surgery. In a preclinical study, the direct effects of remimazolam on cardiac contractility were also evaluated using isolated rat hearts. RNA sequence data obtained from rat and human hearts were analysed to assess the expression patterns of the cardiac γ-aminobutyric acid type A (GABAA ) receptor subunits. In a clinical study, the proportional change of the maximum rate of arterial pressure rise was milder during the study period in the remimazolam group (propofol: -52.6 [10.2] (mean [standard deviation])% vs. remimazolam: -39.7% [10.5%], p = 0.007). In a preclinical study, remimazolam did not exert a negative effect on left ventricle developed pressure, whereas propofol did exert a negative effect after bolus administration of a high dose (propofol: -26.9% [3.5%] vs. remimazolam: -1.1 [6.9%], p < 0.001). Analysis of the RNA sequence revealed a lack of γ subunits, which are part of the major benzodiazepine binding site of the GABAA receptor, in rat and human hearts. These results indicate that remimazolam does not have a direct negative effect on cardiac contractility, which might contribute to its milder effect on cardiac contractility during the induction of general anaesthesia. The expression patterns of cardiac GABAA receptor subunits might be associated with the unique pharmacokinetics of benzodiazepines in the heart.

Enrichment on steps, not genes, improves inference of differentially expressed pathways

Enrichment analysis is frequently used in combination with differential expression data to investigate potential commonalities amongst lists of genes and generate hypotheses for further experiments. However, current enrichment analysis approaches on pathways ignore the functional relationships between genes in a pathway, particularly OR logic that occurs when a set of proteins can each individually perform the same step in a pathway. As a result, these approaches miss pathways with large or multiple sets because of an inflation of pathway size (when measured as the total gene count) relative to the number of steps. We address this problem by enriching on step-enabling entities in pathways. We treat sets of protein-coding genes as single entities, and we also weight sets to account for the number of genes in them using the multivariate Fisher's noncentral hypergeometric distribution. We then show three examples of pathways that are recovered with this method and find that the results have significant proportions of pathways not found in gene list enrichment analysis.

Detection of gene mutation in the prognosis of a patient with arrhythmogenic right ventricular cardiomyopathy: a case report

BACKGROUND

Arrhythmogenic right ventricular cardiomyopathy (ARVC), or more recently known as arrhythmogenic cardiomyopathy (ACM), is an heritable disorder of the myocardium characterized by progressive fibrofatty replacement the heart muscle and risk of ventricular arrhythmias and sudden cardiac death (SCD). We report a case study to demonstrate the role of gene mutation detection in risk stratification for primary prevention of SCD in a young patient diagnosed with ARVC.

CASE PRESENTATION

A 15-year-old Asian (Vietnamese) male patient with no history of documented tachyarrhythmia or syncope and a family history of potential SCD was admitted due to palpitations. Clinical findings and work-up including cardiac magnetic resonance imaging (MRI) were highly suggestive of ARVC. Gene sequencing was performed for SCD risk stratification, during which PKP2 gene mutation was found. Based on the individualized risk stratification, an ICD was implanted for primary prevention of SCD. At 6 months post ICD implantation, the device detected and successfully delivered an appropriate shock to terminate an episode of potentially fatal ventricular arrhythmia. ICD implantation was therefore proven to be appropriate in this patient.

CONCLUSIONS

While gene mutations are known to be an important factor in the diagnosis of ARVC according to the 2010 Task Force Criteria and recent clinical guidelines, their role in risk stratification of SCD remains controversial. Our case demonstrated that when used with other clinical factors and family history, this information could be helpful in identifying appropriate indication for ICD implantation.

Activated fibroblasts drive cellular interactions in end-stage pediatric hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a relatively rare but debilitating diagnosis in the pediatric population and patients with end-stage HCM require heart transplantation. In this study, we performed single-nucleus RNA sequencing on pediatric HCM and control myocardium. We identified distinct underling cellular processes in pediatric, end-stage HCM in cardiomyocytes, fibroblasts, endothelial cells, and myeloid cells, compared to controls. Pediatric HCM was enriched in cardiomyocytes exhibiting "stressed" myocardium gene signatures and underlying pathways associated with cardiac hypertrophy. Cardiac fibroblasts exhibited clear activation signatures and heightened downstream processes associated with fibrosis, more so than adult counterparts. There was notable depletion of tissue-resident macrophages, and increased vascular remodeling in endothelial cells. Our analysis provides the first single nuclei analysis focused on end-stage pediatric HCM.

Spatial multi-omics: novel tools to study the complexity of cardiovascular diseases

Spatial multi-omic studies have emerged as a promising approach to comprehensively analyze cells in tissues, enabling the joint analysis of multiple data modalities like transcriptome, epigenome, proteome, and metabolome in parallel or even the same tissue section. This review focuses on the recent advancements in spatial multi-omics technologies, including novel data modalities and computational approaches. We discuss the advancements in low-resolution and high-resolution spatial multi-omics methods which can resolve up to 10,000 of individual molecules at subcellular level. By applying and integrating these techniques, researchers have recently gained valuable insights into the molecular circuits and mechanisms which govern cell biology along the cardiovascular disease spectrum. We provide an overview of current data analysis approaches, with a focus on data integration of multi-omic datasets, highlighting strengths and weaknesses of various computational pipelines. These tools play a crucial role in analyzing and interpreting spatial multi-omics datasets, facilitating the discovery of new findings, and enhancing translational cardiovascular research. Despite nontrivial challenges, such as the need for standardization of experimental setups, data analysis, and improved computational tools, the application of spatial multi-omics holds tremendous potential in revolutionizing our understanding of human disease processes and the identification of novel biomarkers and therapeutic targets. Exciting opportunities lie ahead for the spatial multi-omics field and will likely contribute to the advancement of personalized medicine for cardiovascular diseases.

Myocardial B cells have specific gene expression and predicted interactions in Dilated Cardiomyopathy and Arrhythmogenic Right Ventricular Cardiomyopathy

Introduction

Growing evidence from animal models indicates that the myocardium hosts a population of B cells that play a role in the development of cardiomyopathy. However, there is minimal data on human myocardial B cells in the context of cardiomyopathy.

Methods

We integrated single-cell and single-nuclei datasets from 45 healthy human hearts, 70 hearts with dilated cardiomyopathy (DCM), and 8 hearts with Arrhythmogenic Right Ventricular Cardiomyopathy (ARVC). Interactions between B cells and other cell types were investigated using the CellChat Package. Differential gene expression analysis comparing B cells across conditions was performed using DESeq2. Pathway analysis was performed using Ingenuity, KEGG, and GO pathways analysis.

Results

We identified 1,100 B cells, including naive B cells and plasma cells. B cells showed an extensive network of interactions within the healthy myocardium that included outgoing signaling to macrophages, T cells, endothelial cells, and pericytes, and incoming signaling from endothelial cells, pericytes, and fibroblasts. This niche relied on ECM-receptor, contact, and paracrine interaction; and changed significantly in the context of cardiomyopathy, displaying disease-specific features. Differential gene expression analysis showed that in the context of DCM both naive and plasma B cells upregulated several pathways related to immune activation, including upregulation of oxidative phosphorylation, upregulation of leukocyte extravasation, and, in naive B cells, antigen presentation.

Discussion

The human myocardium contains naive B cells and plasma cells, integrated into a diverse and dynamic niche that has distinctive features in healthy myocardium, DCM, and ARVC. Naive myocardial-associated B cells likely contribute to the pathogenesis of human DCM.

CardiOmics signatures reveal therapeutically actionable targets and drugs for cardiovascular diseases

Cardiovascular diseases are the leading cause of death worldwide, with heart failure being a complex condition that affects millions of individuals. Single-nucleus RNA sequencing has recently emerged as a powerful tool for unraveling the molecular mechanisms behind cardiovascular diseases. This cutting-edge technology enables the identification of molecular signatures, intracellular networks, and spatial relationships among cardiac cells, including cardiomyocytes, mast cells, lymphocytes, macrophages, lymphatic endothelial cells, endocardial cells, endothelial cells, epicardial cells, adipocytes, fibroblasts, neuronal cells, pericytes, and vascular smooth muscle cells. Despite these advancements, the discovery of essential therapeutic targets and drugs for precision cardiology remains a challenge. To bridge this gap, we conducted comprehensive in silico analyses of single-nucleus RNA sequencing data, functional enrichment, protein interactome network, and identification of the shortest pathways to physiological phenotypes. This integrated multi-omics analysis generated CardiOmics signatures, which allowed us to pinpoint three therapeutically actionable targets (ADRA1A1, PPARG, and ROCK2) and 15 effective drugs, including adrenergic receptor agonists, adrenergic receptor antagonists, norepinephrine precursors, PPAR receptor agonists, and Rho-associated kinase inhibitors, involved in late-stage cardiovascular disease clinical trials.

Single-cell RNA sequencing in donor and end-stage heart failure patients identifies NLRP3 as a therapeutic target for arrhythmogenic right ventricular cardiomyopathy

BACKGROUND

Dilation may be the first right ventricular change and accelerates the progression of threatening ventricular tachyarrhythmias and heart failure for patients with arrhythmogenic right ventricular cardiomyopathy (ARVC), but the treatment for right ventricular dilation remains limited.

METHODS

Single-cell RNA sequencing (scRNA-seq) of blood and biventricular myocardium from 8 study participants was performed, including 6 end-stage heart failure patients with ARVC and 2 normal controls. ScRNA-seq data was then deeply analyzed, including cluster annotation, cellular proportion calculation, and characterization of cellular developmental trajectories and interactions. An integrative analysis of our single-cell data and published genome-wide association study-based data provided insights into the cell-specific contributions to the cardiac arrhythmia phenotype of ARVC. Desmoglein 2 (Dsg2)mut/mut mice were used as the ARVC model to verify the therapeutic effects of pharmacological intervention on identified cellular cluster.

RESULTS

Right ventricle of ARVC was enriched of CCL3+ proinflammatory macrophages and TNMD+ fibroblasts. Fibroblasts were preferentially affected in ARVC and perturbations associated with ARVC overlap with those reside in genetic variants associated with cardiac arrhythmia. Proinflammatory macrophages strongly interact with fibroblast. Pharmacological inhibition of Nod-like receptor protein 3 (NLRP3), a transcriptional factor predominantly expressed by the CCL3+ proinflammatory macrophages and several other myeloid subclusters, could significantly alleviate right ventricular dilation and dysfunction in Dsg2mut/mut mice (an ARVC mouse model).

CONCLUSIONS

This study provided a comprehensive analysis of the lineage-specific changes in the blood and myocardium from ARVC patients at a single-cell resolution. Pharmacological inhibition of NLRP3 could prevent right ventricular dilation and dysfunction of mice with ARVC.

Single nucleus transcriptome of a "Super RV" shows increased insulin and angiogenesis signaling

The right ventricle (RV) is one of the four pumping chambers of the heart, pumping blood to the lungs. In severe forms of congenital heart disease and pulmonary hypertension, the RV is made to pump into the systemic circulation. Such systemic RVs typically display early failure due to pressure overload. In rare cases a systemic RV persists into later decades of life - colloquially called a 'Super RV'. Here we present the single-nucleus transcriptome of a systemic RV from a 60-year-old with congenitally corrected transposition of great arteries (ccTGA). Our data shows two specific signaling pathways enriched in the ccTGA RV myocardium. First, we show increased insulin like growth factor (IGF1) signaling within the systemic RV myocardium: there is increased expression of the main receptor IGFR1 within the cardiomyocytes, and IGF1 ligands within the cardiofibroblasts and macrophages. Second, we find increased VEGF and Wnt9 ligand expression in cardiomyocytes and increased VEGF1R and Wnt9 receptors in endothelial cells, which are implicated in angiogenesis. We show that increased insulin and angiogenesis signaling are potentially beneficial RV adaptations to increased pressure overload. This study of an adult systemic RV provides an important framework for understanding RV remodeling to systemic pressures in congenital heart disease and pulmonary hypertension.

Profiling cardiomyocytes at single cell resolution reveals COX7B could be a potential target for attenuating heart failure in cardiac hypertrophy

Cardiac hypertrophy can develop to end-stage heart failure (HF), which inevitably leading to heart transplantation or death. Preserving cardiac function in cardiomyocytes (CMs) is essential for improving prognosis in hypertrophic cardiomyopathy (HCM) patients. Therefore, understanding transcriptomic heterogeneity of CMs in HCM would be indispensable to aid potential therapeutic targets investigation. We isolated primary CM from HCM patients who had extended septal myectomy, and obtained transcriptomes in 338 human primary CM with single-cell tagged reverse transcription (STRT-seq) approach. Our results revealed that CMs could be categorized into three subsets in nonfailing HCM heart: high energy synthesis cluster, high cellular metabolism cluster and intermediate cluster. The expression of electron transport chain (ETC) was up-regulated in larger-sized CMs from high energy synthesis cluster. Of note, we found the expression of Cytochrome c oxidase subunit 7B (COX7B), a subunit of Complex IV in ETC had trends of positively correlation with CMs size. Further, by assessing COX7B expression in HCM patients, we speculated that COX7B was compensatory up-regulated at early-stage but down-regulated in failing HCM heart. To test the hypothesis that COX7B might participate both in hypertrophy and HF progression, we used adeno associated virus 9 (AAV9) to mediate the expression of Cox7b in pressure overload-induced mice. Mice in vivo data supported that knockdown of Cox7b would accelerate HF and Cox7b overexpression could restore partial cardiac function in hypertrophy. Our result highlights targeting COX7B and preserving energy synthesis in hypertrophic CMs could be a promising translational direction for HF therapeutic strategy.

NAT10 Is Involved in Cardiac Remodeling Through ac4C-Mediated Transcriptomic Regulation

BACKGROUND

Heart failure, characterized by cardiac remodeling, is associated with abnormal epigenetic processes and aberrant gene expression. Here, we aimed to elucidate the effects and mechanisms of NAT10 (N-acetyltransferase 10)-mediated N4-acetylcytidine (ac4C) acetylation during cardiac remodeling.

METHODS

NAT10 and ac4C expression were detected in both human and mouse subjects with cardiac remodeling through multiple assays. Subsequently, acetylated RNA immunoprecipitation and sequencing, thiol-linked alkylation for the metabolic sequencing of RNA (SLAM-seq), and ribosome sequencing (Ribo-seq) were employed to elucidate the role of ac4C-modified posttranscriptional regulation in cardiac remodeling. Additionally, functional experiments involving the overexpression or knockdown of NAT10 were conducted in mice models challenged with Ang II (angiotensin II) and transverse aortic constriction.

RESULTS

NAT10 expression and RNA ac4C levels were increased in in vitro and in vivo cardiac remodeling models, as well as in patients with cardiac hypertrophy. Silencing and inhibiting NAT10 attenuated Ang II-induced cardiomyocyte hypertrophy and cardiofibroblast activation. Next-generation sequencing revealed ac4C changes in both mice and humans with cardiac hypertrophy were associated with changes in global mRNA abundance, stability, and translation efficiency. Mechanistically, NAT10 could enhance the stability and translation efficiency of CD47 and ROCK2 transcripts by upregulating their mRNA ac4C modification, thereby resulting in an increase in their protein expression during cardiac remodeling. Furthermore, the administration of Remodelin, a NAT10 inhibitor, has been shown to prevent cardiac functional impairments in mice subjected to transverse aortic constriction by suppressing cardiac fibrosis, hypertrophy, and inflammatory responses, while also regulating the expression levels of CD47 and ROCK2 (Rho associated coiled-coil containing protein kinase 2).

CONCLUSIONS

Therefore, our data suggest that modulating epitranscriptomic processes, such as ac4C acetylation through NAT10, may be a promising therapeutic target against cardiac remodeling.

Single-Cell Atlas of Neonatal Mouse Hearts Reveals an Unexpected Cardiomyocyte

BACKGROUND

Single-cell RNA sequencing is widely used in cancer research and organ development because of its powerful ability to analyze cellular heterogeneity. However, its application in cardiomyocytes is dissatisfactory mainly because the cardiomyocytes are too large and fragile to withstand traditional single-cell approaches.

METHODS AND RESULTS

Through designing the isolation procedure of neonatal mouse cardiac cells, we provide detailed cellular atlases of the heart at single-cell resolution across 4 different stages after birth. We have obtained 10 000 cardiomyocytes; to our knowledge, this is the most extensive reference framework to date. Moreover, we have discovered unexpected erythrocyte-like cardiomyocyte-terminal cardiomyocytes, comprising more than a third of all cardiomyocytes. Only a few genes are highly expressed in these cardiomyocytes. They are highly differentiated cardiomyocytes that function as contraction pumps. In addition, we have identified 2 cardiomyocyte-like conducting cells, lending support to the theory that the sinoatrial node pacemaker cells are specialized cardiomyocytes. Notably, we provide an initial blueprint for comprehensive interactions between cardiomyocytes and other cardiac cells.

CONCLUSIONS

This mouse cardiac cell atlas improves our understanding of cardiomyocyte heterogeneity and provides a valuable reference in response to varying physiological conditions and diseases.

Dexmedetomidine as a cardioprotective drug: a narrative review

Dexmedetomidine (DEX), a highly selective alpha2-adrenoceptors agonist, is not only a sedative drug used during mechanical ventilation in the intensive care unit but also a cardio-protective drug against ischemia-reperfusion injury (IRI). Numerous preclinical in vivo and ex vivo studies, mostly evaluating the effect of DEX pretreatment in healthy rodents, have shown the efficacy of DEX in protecting the hearts from IRI. However, whether DEX can maintain its cardio-protective effect in hearts with comorbidities such as diabetes has not been fully elucidated. Multiple clinical trials have reported promising results, showing that pretreatment with DEX can attenuate cardiac damage in patients undergoing cardiac surgery. However, evidence of the post-treatment effects of DEX in clinical practice remains limited. In this narrative review, we summarize the previously reported evidence of DEX-induced cardio-protection against IRI and clarify the condition of the hearts and the timing of DEX administration that has not been tested. With further investigations evaluating these knowledge gaps, the use of DEX as a cardio-protective drug could be further facilitated in the management of patients undergoing cardiac surgery and might be considered in a broader area of clinical settings beyond cardiac surgery, including patients with acute myocardial infarction.

Multicellular factor analysis of single-cell data for a tissue-centric understanding of disease

Biomedical single-cell atlases describe disease at the cellular level. However, analysis of this data commonly focuses on cell-type-centric pairwise cross-condition comparisons, disregarding the multicellular nature of disease processes. Here, we propose multicellular factor analysis for the unsupervised analysis of samples from cross-condition single-cell atlases and the identification of multicellular programs associated with disease. Our strategy, which repurposes group factor analysis as implemented in multi-omics factor analysis, incorporates the variation of patient samples across cell-types or other tissue-centric features, such as cell compositions or spatial relationships, and enables the joint analysis of multiple patient cohorts, facilitating the integration of atlases. We applied our framework to a collection of acute and chronic human heart failure atlases and described multicellular processes of cardiac remodeling, independent to cellular compositions and their local organization, that were conserved in independent spatial and bulk transcriptomics datasets. In sum, our framework serves as an exploratory tool for unsupervised analysis of cross-condition single-cell atlases and allows for the integration of the measurements of patient cohorts across distinct data modalities.

Insights into the Interaction of Heart Failure with Preserved Ejection Fraction and Sleep-Disordered Breathing

Heart failure with preserved ejection fraction (HFpEF) is emerging as a widespread disease with global socioeconomic impact. Patients with HFpEF show a dramatically increased morbidity and mortality, and, unfortunately, specific treatment options are limited. This is due to the various etiologies that promote HFpEF development. Indeed, cluster analyses with common HFpEF comorbidities revealed the existence of several HFpEF phenotypes. One especially frequent, yet underappreciated, comorbidity is sleep-disordered breathing (SDB), which is closely intertwined with the development and progression of the "obese HFpEF phenotype". The following review article aims to provide an overview of the common HFpEF etiologies and phenotypes, especially in the context of SDB. As general HFpEF therapies are often not successful, patient- and phenotype-individualized therapeutic strategies are warranted. Therefore, for the "obese HFpEF phenotype", a better understanding of the mechanistic parallels between both HFpEF and SDB is required, which may help to identify potential phenotype-individualized therapeutic strategies. Novel technologies like single-cell transcriptomics or CRISPR-Cas9 gene editing further broaden the groundwork for deeper insights into pathomechanisms and precision medicine.

Short-term Pre-operative Methionine Restriction Induces Browning of Perivascular Adipose Tissue and Improves Vein Graft Remodeling in Mice

Short-term preoperative methionine restriction (MetR) shows promise as a translatable strategy to modulate the body's response to surgical injury. Its application, however, to improve post-interventional vascular remodeling remains underexplored. Here, we find that MetR protects from arterial intimal hyperplasia in a focal stenosis model and adverse vascular remodeling after vein graft surgery. RNA sequencing reveals that MetR enhances the brown adipose tissue phenotype in arterial perivascular adipose tissue (PVAT) and induces it in venous PVAT. Specifically, PPAR-α was highly upregulated in PVAT-adipocytes. Furthermore, MetR dampens the post-operative pro-inflammatory response to surgery in PVAT-macrophages in vivo and in vitro . This study shows for the first time that the detrimental effects of dysfunctional PVAT on vascular remodeling can be reversed by MetR, and identifies pathways involved in browning of PVAT. Furthermore, we demonstrate the potential of short-term pre-operative MetR as a simple intervention to ameliorate vascular remodeling after vascular surgery.

Multi-omic analyses and network biology in cardiovascular disease

Heart disease remains a leading cause of death in North America and worldwide. Despite advances in therapies, the chronic nature of cardiovascular diseases ultimately results in frequent hospitalizations and steady rates of mortality. Systems biology approaches have provided a new frontier toward unraveling the underlying mechanisms of cell, tissue, and organ dysfunction in disease. Mapping the complex networks of molecular functions across the genome, transcriptome, proteome, and metabolome has enormous potential to advance our understanding of cardiovascular disease, discover new disease biomarkers, and develop novel therapies. Computational workflows to interpret these data-intensive analyses as well as integration between different levels of interrogation remain important challenges in the advancement and application of systems biology-based analyses in cardiovascular research. This review will focus on summarizing the recent developments in network biology-level profiling in the heart, with particular emphasis on modeling of human heart failure. We will provide new perspectives on integration between different levels of large "omics" datasets, including integration of gene regulatory networks, protein-protein interactions, signaling networks, and metabolic networks in the heart.

Precise identification of cell states altered in disease using healthy single-cell references

Joint analysis of single-cell genomics data from diseased tissues and a healthy reference can reveal altered cell states. We investigate whether integrated collections of data from healthy individuals (cell atlases) are suitable references for disease-state identification and whether matched control samples are needed to minimize false discoveries. We demonstrate that using a reference atlas for latent space learning followed by differential analysis against matched controls leads to improved identification of disease-associated cells, especially with multiple perturbed cell types. Additionally, when an atlas is available, reducing control sample numbers does not increase false discovery rates. Jointly analyzing data from a COVID-19 cohort and a blood cell atlas, we improve detection of infection-related cell states linked to distinct clinical severities. Similarly, we studied disease states in pulmonary fibrosis using a healthy lung atlas, characterizing two distinct aberrant basal states. Our analysis provides guidelines for designing disease cohort studies and optimizing cell atlas use.

The Role of Autoantibodies in Companion Animal Cardiac Disease

Clinical studies exploring the role of autoimmune diseases in cardiac dysfunction have become increasingly common in both human and veterinary literature. Autoantibodies (AABs) specific to cardiac receptors have been found in human and canine dilated cardiomyopathy, and circulating autoantibodies have been suggested as a sensitive biomarker for arrhythmogenic right ventricular cardiomyopathy in people and Boxer dogs. In this article, we will summarize recent literature on AABs and their role in cardiac diseases of small animals. Despite the potential for new discoveries in veterinary cardiology, current data in veterinary medicine are limited and further studies are needed.

In need of age-appropriate cardiac models: Impact of cell age on extracellular matrix therapy outcomes

Aging is the main risk factor for cardiovascular disease (CVD). As the world's population ages rapidly and CVD rates rise, there is a growing need for physiologically relevant models of aging hearts to better understand cardiac aging. Translational research relies heavily on young animal models; however, these models correspond to early ages in human life, therefore cannot fully capture the pathophysiology of age-related CVD. Here, we first investigated the transcriptomic and proteomic changes that occur with human cardiac aging. We then chronologically aged human induced pluripotent stem cell-derived cardiomyocytes (iCMs) and showed that 14-month-old iCMs exhibited a similar aging profile to the human CMs and recapitulated age-related disease hallmarks. Using aged iCMs, we studied the effect of cell age on the young extracellular matrix (ECM) therapy, an emerging approach for myocardial infarction (MI) treatment and prevention. Young ECM decreased oxidative stress, improved survival, and post-MI beating in aged iCMs. In the absence of stress, young ECM improved beating and reversed aging-associated expressions in 3-month-old iCMs while causing the opposite effect on 14-month-old iCMs. The same young ECM treatment surprisingly increased SASP and impaired beating in advanced aged iCMs. Overall, we showed that young ECM therapy had a positive effect on post-MI recovery; however, cell age was determinant in the treatment outcomes without any stress conditions. Therefore, "one-size-fits-all" approaches to ECM treatments fail, and cardiac tissue engineered models with age-matched human iCMs are valuable in translational basic research for determining the appropriate treatment, particularly for the elderly.

DMD-Associated Dilated Cardiomyopathy: Genotypes, Phenotypes, and Phenocopies

BACKGROUND

Variants in the DMD gene, that encodes the cytoskeletal protein, dystrophin, cause a severe form of dilated cardiomyopathy (DCM) associated with high rates of heart failure, heart transplantation, and ventricular arrhythmias. Improved early detection of individuals at risk is needed.

METHODS

Genetic testing of 40 male probands with a potential X-linked genetic cause of primary DCM was undertaken using multi-gene panel sequencing, multiplex polymerase chain reaction, and array comparative genomic hybridization. Variant location was assessed with respect to dystrophin isoform patterns and exon usage. Telomere length was evaluated as a marker of myocardial dysfunction in left ventricular tissue and blood.

RESULTS

Four pathogenic/likely pathogenic DMD variants were found in 5 probands (5/40: 12.5%). Only one rare variant was identified by gene panel testing with 3 additional multi-exon deletion/duplications found following targeted assays for structural variants. All of the pathogenic/likely pathogenic DMD variants involved dystrophin exons that had percent spliced-in scores >90, indicating high levels of constitutive expression in the human adult heart. Fifteen DMD variant-negative probands (15/40: 37.5%) had variants in autosomal genes including TTN, BAG3, LMNA, and RBM20. Myocardial telomere length was reduced in patients with DCM irrespective of genotype. No differences in blood telomere length were observed between genotype-positive family members with/without DCM and controls.

CONCLUSIONS

Primary genetic testing using multi-gene panels has a low yield and specific assays for structural variants are required if DMD-associated cardiomyopathy is suspected. Distinguishing X-linked causes of DCM from autosomal genes that show sex differences in clinical presentation is crucial for informed family management.

Dilated cardiomyopathy: causes, mechanisms, and current and future treatment approaches

Dilated cardiomyopathy is conventionally defined as the presence of left ventricular or biventricular dilatation or systolic dysfunction in the absence of abnormal loading conditions (eg, primary valve disease) or significant coronary artery disease sufficient to cause ventricular remodelling. This definition has been recognised as overly restrictive, as left ventricular hypokinesis without dilation could be the initial presentation of dilated cardiomyopathy. The causes of dilated cardiomyopathy comprise genetic (primary dilated cardiomyopathy) or acquired factors (secondary dilated cardiomyopathy). Acquired factors include infections, toxins, cancer treatment, endocrinopathies, pregnancy, tachyarrhythmias, and immune-mediated diseases. 5-15% of patients with acquired dilated cardiomyopathy harbour a likely pathogenic or pathogenic gene variant (ie, gene mutation). Therefore, the diagnostic tests and therapeutic approach should always consider both genetic and acquired factors. This Seminar will focus on the current multidimensional diagnostic and therapeutic approach and discuss the underlying pathophysiology that could drive future treatments aiming to repair or replace the existing gene mutation, or target the specific inflammatory, metabolic, or pro-fibrotic drivers of genetic or acquired dilated cardiomyopathy.

Immunology of human fibrosis

Fibrosis, defined by the excess deposition of structural and matricellular proteins in the extracellular space, underlies tissue dysfunction in multiple chronic diseases. Approved antifibrotics have proven modest in efficacy, and the immune compartment remains, for the most part, an untapped therapeutic opportunity. Recent single-cell analyses have interrogated human fibrotic tissues, including immune cells. These studies have revealed a conserved profile of scar-associated macrophages, which localize to the fibrotic niche and interact with mesenchymal cells that produce pathological extracellular matrix. Here we review recent advances in the understanding of the fibrotic microenvironment in human diseases, with a focus on immune cell profiles and functional immune-stromal interactions. We also discuss the key role of the immune system in mediating fibrosis regression and highlight avenues for future study to elucidate potential approaches to targeting inflammatory cells in fibrotic disorders.

The heterocellular heart: identities, interactions, and implications for cardiology

The heterocellular nature of the heart has been receiving increasing attention in recent years. In addition to cardiomyocytes as the prototypical cell type of the heart, non-myocytes such as endothelial cells, fibroblasts, or immune cells are coming more into focus. The rise of single-cell sequencing technologies enables  identification of ever more subtle differences and has reignited the question of what defines a cell's identity. Here we provide an overview of the major cardiac cell types, describe their roles in homeostasis, and outline recent findings on non-canonical functions that may be of relevance for cardiology. We highlight modes of biochemical and biophysical interactions between different cardiac cell types and discuss the potential implications of the heterocellular nature of the heart for basic research and therapeutic interventions.

Diversity of cells and signals in the cardiovascular system

This white paper is the outcome of the seventh UC Davis Cardiovascular Research Symposium on Systems Approach to Understanding Cardiovascular Disease and Arrhythmia. This biannual meeting aims to bring together leading experts in subfields of cardiovascular biomedicine to focus on topics of importance to the field. The theme of the 2022 Symposium was 'Cell Diversity in the Cardiovascular System, cell-autonomous and cell-cell signalling'. Experts in the field contributed their experimental and mathematical modelling perspectives and discussed emerging questions, controversies, and challenges in examining cell and signal diversity, co-ordination and interrelationships involved in cardiovascular function. This paper originates from the topics of formal presentations and informal discussions from the Symposium, which aimed to develop a holistic view of how the multiple cell types in the cardiovascular system integrate to influence cardiovascular function, disease progression and therapeutic strategies. The first section describes the major cell types (e.g. cardiomyocytes, vascular smooth muscle and endothelial cells, fibroblasts, neurons, immune cells, etc.) and the signals involved in cardiovascular function. The second section emphasizes the complexity at the subcellular, cellular and system levels in the context of cardiovascular development, ageing and disease. Finally, the third section surveys the technological innovations that allow the interrogation of this diversity and advancing our understanding of the integrated cardiovascular function and dysfunction.

Spatially resolved multiomics of human cardiac niches

The function of a cell is defined by its intrinsic characteristics and its niche: the tissue microenvironment in which it dwells. Here we combine single-cell and spatial transcriptomics data to discover cellular niches within eight regions of the human heart. We map cells to microanatomical locations and integrate knowledge-based and unsupervised structural annotations. We also profile the cells of the human cardiac conduction system1. The results revealed their distinctive repertoire of ion channels, G-protein-coupled receptors (GPCRs) and regulatory networks, and implicated FOXP2 in the pacemaker phenotype. We show that the sinoatrial node is compartmentalized, with a core of pacemaker cells, fibroblasts and glial cells supporting glutamatergic signalling. Using a custom CellPhoneDB.org module, we identify trans-synaptic pacemaker cell interactions with glia. We introduce a druggable target prediction tool, drug2cell, which leverages single-cell profiles and drug-target interactions to provide mechanistic insights into the chronotropic effects of drugs, including GLP-1 analogues. In the epicardium, we show enrichment of both IgG+ and IgA+ plasma cells forming immune niches that may contribute to infection defence. Overall, we provide new clarity to cardiac electro-anatomy and immunology, and our suite of computational approaches can be applied to other tissues and organs.

Striated muscle-specific base editing enables correction of mutations causing dilated cardiomyopathy

Dilated cardiomyopathy is the second most common cause for heart failure with no cure except a high-risk heart transplantation. Approximately 30% of patients harbor heritable mutations which are amenable to CRISPR-based gene therapy. However, challenges related to delivery of the editing complex and off-target concerns hamper the broad applicability of CRISPR agents in the heart. We employ a combination of the viral vector AAVMYO with superior targeting specificity of heart muscle tissue and CRISPR base editors to repair patient mutations in the cardiac splice factor Rbm20, which cause aggressive dilated cardiomyopathy. Using optimized conditions, we repair >70% of cardiomyocytes in two Rbm20 knock-in mouse models that we have generated to serve as an in vivo platform of our editing strategy. Treatment of juvenile mice restores the localization defect of RBM20 in 75% of cells and splicing of RBM20 targets including TTN. Three months after injection, cardiac dilation and ejection fraction reach wild-type levels. Single-nuclei RNA sequencing uncovers restoration of the transcriptional profile across all major cardiac cell types and whole-genome sequencing reveals no evidence for aberrant off-target editing. Our study highlights the potential of base editors combined with AAVMYO to achieve gene repair for treatment of hereditary cardiac diseases.

Omics Analyses of Stromal Cells from ACM Patients Reveal Alterations in Chromatin Organization and Mitochondrial Homeostasis

Arrhythmogenic cardiomyopathy (ACM) is a genetic disorder characterized by ventricular arrhythmias, contractile dysfunctions and fibro-adipose replacement of myocardium. Cardiac mesenchymal stromal cells (CMSCs) participate in disease pathogenesis by differentiating towards adipocytes and myofibroblasts. Some altered pathways in ACM are known, but many are yet to be discovered. We aimed to enrich the understanding of ACM pathogenesis by comparing epigenetic and gene expression profiles of ACM-CMSCs with healthy control (HC)-CMSCs. Methylome analysis identified 74 differentially methylated nucleotides, most of them located on the mitochondrial genome. Transcriptome analysis revealed 327 genes that were more expressed and 202 genes that were less expressed in ACM- vs. HC-CMSCs. Among these, genes implicated in mitochondrial respiration and in epithelial-to-mesenchymal transition were more expressed, and cell cycle genes were less expressed in ACM- vs. HC-CMSCs. Through enrichment and gene network analyses, we identified differentially regulated pathways, some of which never associated with ACM, including mitochondrial functioning and chromatin organization, both in line with methylome results. Functional validations confirmed that ACM-CMSCs exhibited higher amounts of active mitochondria and ROS production, a lower proliferation rate and a more pronounced epicardial-to-mesenchymal transition compared to the controls. In conclusion, ACM-CMSC-omics revealed some additional altered molecular pathways, relevant in disease pathogenesis, which may constitute novel targets for specific therapies.

Recent Advances in Translational Research for Heart Failure in Japan

Despite decades of intensive research and therapeutic development, heart failure remains a leading cause of death worldwide. However, recent advances in several basic and translational research fields, such as genomic analysis and single-cell analysis, have increased the possibility of developing novel diagnostic approaches to heart failure. Most cardiovascular diseases that predispose individuals to heart failure are caused by genetic and environmental factors. It follows that genomic analysis can contribute to the diagnosis and prognostic stratification of patients with heart failure. In addition, single-cell analysis has shown great potential for unveiling the pathogenesis and/or pathophysiology and for discovering novel therapeutic targets for heart failure. Here, we summarize the recent advances in translational research on heart failure in Japan, based mainly on our studies.

Proteomics and phosphoproteomics of failing human left ventricle identifies dilated cardiomyopathy-associated phosphorylation of CTNNA3

The prognosis and treatment outcomes of heart failure (HF) patients rely heavily on disease etiology, yet the majority of underlying signaling mechanisms are complex and not fully elucidated. Phosphorylation is a major point of protein regulation with rapid and profound effects on the function and activity of protein networks. Currently, there is a lack of comprehensive proteomic and phosphoproteomic studies examining cardiac tissue from HF patients with either dilated dilated cardiomyopathy (DCM) or ischemic cardiomyopathy (ICM). Here, we used a combined proteomic and phosphoproteomic approach to identify and quantify more than 5,000 total proteins with greater than 13,000 corresponding phosphorylation sites across explanted left ventricle (LV) tissue samples, including HF patients with DCM vs. nonfailing controls (NFC), and left ventricular infarct vs. noninfarct, and periinfarct vs. noninfarct regions of HF patients with ICM. Each pair-wise comparison revealed unique global proteomic and phosphoproteomic profiles with both shared and etiology-specific perturbations. With this approach, we identified a DCM-associated hyperphosphorylation cluster in the cardiomyocyte intercalated disc (ICD) protein, αT-catenin (CTNNA3). We demonstrate using both ex vivo isolated cardiomyocytes and in vivo using an AAV9-mediated overexpression mouse model, that CTNNA3 phosphorylation at these residues plays a key role in maintaining protein localization at the cardiomyocyte ICD to regulate conductance and cell-cell adhesion. Collectively, this integrative proteomic/phosphoproteomic approach identifies region- and etiology-associated signaling pathways in human HF and describes a role for CTNNA3 phosphorylation in the pathophysiology of DCM.

Single-cell transcriptomics for the assessment of cardiac disease

Cardiovascular disease is the leading cause of death globally. An advanced understanding of cardiovascular disease mechanisms is required to improve therapeutic strategies and patient risk stratification. State-of-the-art, large-scale, single-cell and single-nucleus transcriptomics facilitate the exploration of the cardiac cellular landscape at an unprecedented level, beyond its descriptive features, and can further our understanding of the mechanisms of disease and guide functional studies. In this Review, we provide an overview of the technical challenges in the experimental design of single-cell and single-nucleus transcriptomics studies, as well as a discussion of the type of inferences that can be made from the data derived from these studies. Furthermore, we describe novel findings derived from transcriptomics studies for each major cardiac cell type in both health and disease, and from development to adulthood. This Review also provides a guide to interpreting the exhaustive list of newly identified cardiac cell types and states, and highlights the consensus and discordances in annotation, indicating an urgent need for standardization. We describe advanced applications such as integration of single-cell data with spatial transcriptomics to map genes and cells on tissue and define cellular microenvironments that regulate homeostasis and disease progression. Finally, we discuss current and future translational and clinical implications of novel transcriptomics approaches, and provide an outlook of how these technologies will change the way we diagnose and treat heart disease.

Role of MicroRNAs in Arrhythmogenic Cardiomyopathy: translation as biomarkers into clinical practice

Arrhythmogenic cardiomyopathy is a rare inherited entity, characterized by a progressive fibro-fatty replacement of the myocardium. It leads to malignant arrhythmias and a high risk of sudden cardiac death. Incomplete penetrance and variable expressivity are hallmarks of this arrhythmogenic cardiac disease, where the first manifestation may be syncope and sudden cardiac death, often triggered by physical exercise. Early identification of individuals at risk is crucial to adopt protective and ideally personalized measures to prevent lethal episodes. The genetic analysis identifies deleterious rare variants in nearly 70% of cases, mostly in genes encoding proteins of the desmosome. However, other factors may modulate the phenotype onset and outcome of disease, such as microRNAs. These small noncoding RNAs play a key role in gene expression regulation and the network of cellular processes. In recent years, data focused on the role of microRNAs as potential biomarkers in arrhythmogenic cardiomyopathy has progressively increased. A better understanding of the functions and interactions of microRNAs will likely have clinical implications. Herein, we propose an exhaustive review of the literature regarding these noncoding RNAs, their versatile mechanisms of gene regulation and present novel targets in arrhythmogenic cardiomyopathy.

Multiomics Network Medicine Approaches to Precision Medicine and Therapeutics in Cardiovascular Diseases

Cardiovascular diseases (CVD) are the leading cause of death worldwide and display complex phenotypic heterogeneity caused by many convergent processes, including interactions between genetic variation and environmental factors. Despite the identification of a large number of associated genes and genetic loci, the precise mechanisms by which these genes systematically influence the phenotypic heterogeneity of CVD are not well understood. In addition to DNA sequence, understanding the molecular mechanisms of CVD requires data from other omics levels, including the epigenome, the transcriptome, the proteome, as well as the metabolome. Recent advances in multiomics technologies have opened new precision medicine opportunities beyond genomics that can guide precise diagnosis and personalized treatment. At the same time, network medicine has emerged as an interdisciplinary field that integrates systems biology and network science to focus on the interactions among biological components in health and disease, providing an unbiased framework through which to integrate systematically these multiomics data. In this review, we briefly present such multiomics technologies, including bulk omics and single-cell omics technologies, and discuss how they can contribute to precision medicine. We then highlight network medicine-based integration of multiomics data for precision medicine and therapeutics in CVD. We also include a discussion of current challenges, potential limitations, and future directions in the study of CVD using multiomics network medicine approaches.

Cardiomyocyte hyperplasia and immaturity but not hypertrophy are characteristic features of patients with RASopathies

AIMS

RASopathies are caused by mutations in genes that alter the MAP kinase pathway and are marked by several malformations with cardiovascular disorders as the predominant cause of mortality. Mechanistic insights in the underlying pathogenesis in affected cardiac tissue are rare. The aim of the study was to assess the impact of RASopathy causing mutations on the human heart.

METHODS AND RESULTS

Using single cell approaches and histopathology we analyzed cardiac tissue from children with different RASopathy-associated mutations compared to age-matched dilated cardiomyopathy (DCM) and control hearts. The volume of cardiomyocytes was reduced in RASopathy conditions compared to controls and DCM patients, and the estimated number of cardiomyocytes per heart was ~4-10 times higher. Single nuclei RNA sequencing of a 13-year-old RASopathy patient (carrying a PTPN11 c.1528C > G mutation) revealed that myocardial cell composition and transcriptional patterns were similar to <1 year old DCM hearts. Additionally, immaturity of cardiomyocytes is shown by an increased MYH6/MYH7 expression ratio and reduced expression of genes associated with fatty acid metabolism. In the patient with the PTPN11 mutation activation of the MAP kinase pathway was not evident in cardiomyocytes, whereas increased phosphorylation of PDK1 and its downstream kinase Akt was detected.

CONCLUSION

In conclusion, an immature cardiomyocyte differentiation status appears to be preserved in juvenile RASopathy patients. The increased mass of the heart in such patients is due to an increase in cardiomyocyte number (hyperplasia) but not an enlargement of individual cardiomyocytes (hypertrophy).

Patterns of unwanted biological and technical expression variation across 49 human tissues

All tissue-based gene expression studies are impacted by biological and technical sources of variation. Numerous methods are used to normalize and batch correct these datasets. A more accurate understanding of all causes of variation could further optimize these approaches. We used 17,282 samples from 49 tissues in the Genotype Tissue Expression (GTEx) dataset (v8) to investigate patterns and causes of expression variation. Transcript expression was normalized to Z-scores and only the most variable 2% of transcripts were evaluated and clustered based on co-expression patterns. Clustered gene sets were solved to different biological or technical causes related to metadata elements and histologic images. We identified 522 variable transcript clusters (median 11 per tissue) across the samples. Of these, 64% were confidently explained, 15% were likely explained, 7% were low confidence explanations and 14% had no clear cause. Common causes included sex, sequencing contamination, immunoglobulin diversity, and compositional tissue differences. Less common biological causes included death interval (Hardy score), muscle atrophy, diabetes status, and menopause. Technical causes included brain pH and harvesting differences. Many of the causes of variation in bulk tissue expression were identifiable in the Tabula Sapiens dataset of single cell expression. This is the largest exploration of the underlying sources of tissue expression variation. It uncovered expected and unexpected causes of variable gene expression. These identified sources of variation will inform which metadata to acquire with tissue harvesting and can be used to improve normalization, batch correction, and analysis of both bulk and single cell RNA-seq data.

Digital Twins for Predictive, Preventive Personalized, and Participatory Treatment of Immune-Mediated Diseases

Digital twins are computational models of complex systems, which aim to understand and optimize those systems more effectively than would be possible in real life. Ideally, digital twins can be translated to individual patients, to characterize and computationally treat their diseases with thousands of drugs, to select the drug or drugs that cure the patients. The background problem is that many patients do not respond adequately to drug treatment. This problem reflects a wide gap between the complexity of diseases and clinical practice. Each disease may involve altered interactions between thousands of genes that vary between different cell types in different organs. To our knowledge, these altered interactions have not been characterized on a genome-, cellulome-, and organ-wide scale in any disease. Thus, clinical translation of the digital twin ideal for predictive, preventive, personalized and participatory treatment involves formidable challenges, which are close to the limits of, or beyond today's technologies. Here, I discuss recent developments and challenges in relation to that ideal focusing on immune-mediated inflammatory diseases, as well as examples from other diseases.

Application of Single-Cell Genomics in Cardiovascular Research

Cardiovascular diseases (CVDs) are the leading cause of death in the global world. The emergence of single-cell technologies has greatly facilitated the research on CVDs. Currently, those single-cell technologies have been widely applied in atherosclerosis, myocardial infarction, cardiac ischemia-reperfusion injury, arrhythmia, hypertrophy cardiomyopathy, and heart failure, which are extremely helpful in elucidating the underlying mechanisms of CVDs from physiological and pathological perspectives at DNA, RNA, protein, post-transcriptional, post-translational, and metabolite levels. In this review, we would like to briefly introduce the current single-cell technologies, and will focus on the utilization of single-cell genomics in various heart diseases. Single-cell technologies have great potential in exploration of CVDs, and widespread application of single-cell genomics will promote the understanding and therapeutic treatments for CVDs.

Integration of Single-Cell RNA-Seq Datasets: A Review of Computational Methods

With the increased number of single-cell RNA sequencing (scRNA-seq) datasets in public repositories, integrative analysis of multiple scRNA-seq datasets has become commonplace. Batch effects among different datasets are inevitable because of differences in cell isolation and handling protocols, library preparation technology, and sequencing platforms. To remove these batch effects for effective integration of multiple scRNA-seq datasets, a number of methodologies have been developed based on diverse concepts and approaches. These methods have proven useful for examining whether cellular features, such as cell subpopulations and marker genes, identified from a certain dataset, are consistently present, or whether their condition-dependent variations, such as increases in cell subpopulations in particular disease-related conditions, are consistently observed in different datasets generated under similar or distinct conditions. In this review, we summarize the concepts and approaches of the integration methods and their pros and cons as has been reported in previous literature.

Single-cell RNA sequencing to identify cellular heterogeneity and targets in cardiovascular diseases: from bench to bedside

The mechanisms of cardiovascular diseases (CVDs) remain incompletely elucidated. Single-cell RNA sequencing (scRNA-seq) has enabled the profiling of single-cell transcriptomes at unprecedented resolution and throughput, which is critical for deciphering cardiovascular cellular heterogeneity and underlying disease mechanisms, thereby facilitating the development of therapeutic strategies. In this review, we summarize cellular heterogeneity in cardiovascular homeostasis and diseases as well as the discovery of potential disease targets based on scRNA-seq, and yield new insights into the promise of scRNA-seq technology in precision medicine and clinical application.