Integrated multi-omic characterization of congenital heart disease

Comparative proteomics reveals that fatty acid metabolism is involved in myocardial adaptation to chronic hypoxic injury

Congenital heart disease (CHD) is the most serious form of heart disease, and chronic hypoxia is the basic physiological process underlying CHD. Some patients with CHD do not undergo surgery, and thus, they remain susceptible to chronic hypoxia, suggesting that some protective mechanism might exist in CHD patients. However, the mechanism underlying myocardial adaptation to chronic hypoxia remains unclear. Proteomics was used to identify the differentially expressed proteins in cardiomyocytes cultured under hypoxia for different durations. Western blotting assays were used to verify protein expression. A Real-Time Cell Analyzer (RTCA) was used to analyze cell growth. In this study, 3881 proteins were identified by proteomics. Subsequent bioinformatics analysis revealed that proteins were enriched in regulating oxidoreductase activity. Functional similarity cluster analyses showed that chronic hypoxia resulted in proteins enrichment in the mitochondrial metabolic pathway. Further KEGG analyses found that the proteins involved in fatty acid metabolism, the TCA cycle and oxidative phosphorylation were markedly upregulated. Moreover, knockdown of CPT1A or ECI1, which is critical for fatty acid degradation, suppressed the growth of cardiomyocytes under chronic hypoxia. The results of our study revealed that chronic hypoxia activates fatty acid metabolism to maintain the growth of cardiomyocytes.

Expanding the phenotype of UPF3B-related disorder: Case reports and literature review

UPF3B encodes the Regulator of nonsense transcripts 3B protein, a core-member of the nonsense-mediated mRNA decay pathway, protecting the cells from the potentially deleterious actions of transcripts with premature termination codons. Hemizygous variants in the UPF3B gene cause a spectrum of neuropsychiatric issues including intellectual disability, autism spectrum disorder, attention deficit hyperactivity disorder, and schizophrenia/childhood-onset schizophrenia (COS). The number of patients reported to date is very limited, often lacking an extensive phenotypical and neuroradiological description of this ultra-rare syndrome. Here we report three subjects harboring UPF3B variants, presenting with variable clinical pictures, including cognitive impairment, central hypotonia, and syndromic features. Patients 1 and 2 harbored novel UPF3B variants-the p.(Lys207*) and p.(Asp429Serfs*27) ones, respectively-while the p.(Arg225Lysfs*229) variant, identified in Patient 3, was already reported in the literature. Novel features in our patients are represented by microcephaly, midface hypoplasia, and brain malformations. Then, we reviewed pertinent literature and compared previously reported subjects to our cases, providing possible insights into genotype-phenotype correlations in this emerging condition. Overall, the detailed phenotypic description of three patients carrying UPF3B variants is useful not only to expand the genotypic and phenotypic spectrum of UPF3B-related disorders, but also to ameliorate the clinical management of affected individuals.

The Macrophage Landscape Across the Lifespan of a Human Cardiac Allograft

BACKGROUND

Much of our knowledge of organ rejection after transplantation is derived from rodent models.

METHODS

We used single-nucleus RNA sequencing to investigate the inflammatory myocardial microenvironment in human pediatric cardiac allografts at different stages after transplantation. We distinguished donor- from recipient-derived cells using naturally occurring genetic variants embedded in single-nucleus RNA sequencing data.

RESULTS

Donor-derived tissue resident macrophages, which accompany the allograft into the recipient, are lost over time after transplantation. In contrast, monocyte-derived macrophages from the recipient populate the heart within days after transplantation and form 2 macrophage populations: recipient MP1 and recipient MP2. Recipient MP2s have cell signatures similar to donor-derived resident macrophages; however, they lack signatures of pro-reparative phagocytic activity typical of donor-derived resident macrophages and instead express profibrotic genes. In contrast, recipient MP1s express genes consistent with hallmarks of cellular rejection. Our data suggest that recipient MP1s activate a subset of natural killer cells, turning them into a cytotoxic cell population through feed-forward signaling between recipient MP1s and natural killer cells.

CONCLUSIONS

Our findings reveal an imbalance of donor-derived and recipient-derived macrophages in the pediatric cardiac allograft that contributes to allograft failure.

egr3 is a mechanosensitive transcription factor gene required for cardiac valve morphogenesis

Biomechanical forces, and their molecular transducers, including key mechanosensitive transcription factor genes, such as KLF2, are required for cardiac valve morphogenesis. However, klf2 mutants fail to completely recapitulate the valveless phenotype observed under no-flow conditions. Here, we identify the transcription factor EGR3 as a conserved biomechanical force transducer critical for cardiac valve formation. We first show that egr3 null zebrafish display a complete and highly penetrant loss of valve leaflets, leading to severe blood regurgitation. Using tissue-specific loss- and gain-of-function tools, we find that during cardiac valve formation, Egr3 functions cell-autonomously in endothelial cells, and identify one of its effectors, the nuclear receptor Nr4a2b. We further find that mechanical forces up-regulate egr3/EGR3 expression in the developing zebrafish heart and in porcine valvular endothelial cells, as well as during human aortic valve remodeling. Altogether, these findings reveal that EGR3 is necessary to transduce the biomechanical cues required for zebrafish cardiac valve morphogenesis, and potentially for pathological aortic valve remodeling in humans.

Discovery and functional investigation of BMP4 as a new causative gene for human congenital heart disease

OBJECTIVE

Aggregating evidence highlights the strong genetic basis underpinning congenital heart disease (CHD). Here BMP4 was chosen as a prime candidate gene causative of human CHD predominantly because BMP4 was amply expressed in the embryonic hearts and knockout of Bmp4 in mice led to embryonic demise mainly from multiple cardiovascular developmental malformations. The aim of this retrospective investigation was to discover a novel BMP4 mutation underlying human CHD and explore its functional impact.

METHODS

A sequencing examination of BMP4 was implemented in 212 index patients suffering from CHD and 236 unrelated non-CHD individuals as well as the family members available from the proband carrying a discovered BMP4 mutation. The impacts of the discovered CHD-causing mutation on the expression of NKX2-5 and TBX20 induced by BMP4 were measured by employing a dual-luciferase analysis system.

RESULTS

A new heterozygous BMP4 mutation, NM_001202.6:c.318T>G;p.(Tyr106*), was found in a female proband affected with familial CHD. Genetic research of the mutation carrier's relatives unveiled that the truncating mutation was in co-segregation with CHD in the pedigree. The nonsense mutation was absent from 236 unrelated non-CHD control persons. Quantitative biologic measurement revealed that Tyr106*-mutant BMP4 failed to induce the expression of NKX2-5 and TBX20, two genes whose expression is lost in CHD.

CONCLUSION

The current findings indicate BMP4 as a new gene predisposing to human CHD, allowing for improved prenatal genetic counseling along with personalized treatment of CHD patients.

Diffusion Tensor Phenomapping of the Healthy and Pressure-Overloaded Human Heart

Current techniques to image the microstructure of the heart with diffusion tensor MRI (DTI) are highly under-resolved. We present a technique to improve the spatial resolution of cardiac DTI by almost 10-fold and leverage this to measure local gradients in cardiomyocyte alignment or helix angle (HA). We further introduce a phenomapping approach based on voxel-wise hierarchical clustering of these gradients to identify distinct microstructural microenvironments in the heart. Initial development was performed in healthy volunteers (n=8). Thereader, subjects with severe but well-compensated aortic stenosis (AS, n=10) were compared to age-matched controls (CTL, n=10). Radial HA gradient was significantly reduced in AS (8.0±0.8°/mm vs. 10.2±1.8°/mm, p=0.001) but the other HA gradients did not change significantly. Four distinct microstructural clusters could be idenJfied in both the CTL and AS subjects and did not differ significantly in their properties or distribution. Despite marked hypertrophy, our data suggest that the myocardium in well-compensated AS can maintain its microstructural coherence. The described phenomapping approach can be used to characterize microstructural plasticity and perturbation in any organ system and disease.

Exploring machine learning strategies for predicting cardiovascular disease risk factors from multi-omic data

BACKGROUND

Machine learning (ML) classifiers are increasingly used for predicting cardiovascular disease (CVD) and related risk factors using omics data, although these outcomes often exhibit categorical nature and class imbalances. However, little is known about which ML classifier, omics data, or upstream dimension reduction strategy has the strongest influence on prediction quality in such settings. Our study aimed to illustrate and compare different machine learning strategies to predict CVD risk factors under different scenarios.

METHODS

We compared the use of six ML classifiers in predicting CVD risk factors using blood-derived metabolomics, epigenetics and transcriptomics data. Upstream omic dimension reduction was performed using either unsupervised or semi-supervised autoencoders, whose downstream ML classifier performance we compared. CVD risk factors included systolic and diastolic blood pressure measurements and ultrasound-based biomarkers of left ventricular diastolic dysfunction (LVDD; E/e' ratio, E/A ratio, LAVI) collected from 1,249 Finnish participants, of which 80% were used for model fitting. We predicted individuals with low, high or average levels of CVD risk factors, the latter class being the most common. We constructed multi-omic predictions using a meta-learner that weighted single-omic predictions. Model performance comparisons were based on the F1 score. Finally, we investigated whether learned omic representations from pre-trained semi-supervised autoencoders could improve outcome prediction in an external cohort using transfer learning.

RESULTS

Depending on the ML classifier or omic used, the quality of single-omic predictions varied. Multi-omics predictions outperformed single-omics predictions in most cases, particularly in the prediction of individuals with high or low CVD risk factor levels. Semi-supervised autoencoders improved downstream predictions compared to the use of unsupervised autoencoders. In addition, median gains in Area Under the Curve by transfer learning compared to modelling from scratch ranged from 0.09 to 0.14 and 0.07 to 0.11 units for transcriptomic and metabolomic data, respectively.

CONCLUSIONS

By illustrating the use of different machine learning strategies in different scenarios, our study provides a platform for researchers to evaluate how the choice of omics, ML classifiers, and dimension reduction can influence the quality of CVD risk factor predictions.

The role of ferroptosis in cardio-oncology

With the rapid development of new generations of antitumor therapies, the average survival time of cancer patients is expected to be continuously prolonged. However, these therapies often lead to cardiotoxicity, resulting in a growing number of tumor survivors with cardiovascular disease. Therefore, a new interdisciplinary subspecialty called "cardio-oncology" has emerged, aiming to detect and treat cardiovascular diseases associated with tumors and antitumor therapies. Recent studies have highlighted the role of ferroptosis in both cardiovascular and neoplastic diseases. The balance between intracellular oxidative stress and antioxidant defense is crucial in regulating ferroptosis. Tumor cells can evade ferroptosis by upregulating multiple antioxidant defense pathways, while many antitumor therapies rely on downregulating antioxidant defense and promoting ferroptosis in cancer cells. Unfortunately, these ferroptosis-inducing antitumor therapies often lack tissue specificity and can also cause injury to the heart, resulting in ferroptosis-induced cardiotoxicity. A range of cardioprotective agents exert cardioprotective effects by inhibiting ferroptosis. However, these cardioprotective agents might diminish the efficacy of antitumor treatment due to their antiferroptotic effects. Most current research on ferroptosis only focuses on either tumor treatment or heart protection but rarely considers both in concert. Therefore, further research is needed to study how to protect the heart during antitumor therapies by regulating ferroptosis. In this review, we summarized the role of ferroptosis in the treatment of neoplastic diseases and cardiovascular diseases and also attempted to propose further research directions for ferroptosis in the field of cardio-oncology.

Spatially organized cellular communities form the developing human heart

The heart, which is the first organ to develop, is highly dependent on its form to function1,2. However, how diverse cardiac cell types spatially coordinate to create the complex morphological structures that are crucial for heart function remains unclear. Here we integrated single-cell RNA-sequencing with high-resolution multiplexed error-robust fluorescence in situ hybridization to resolve the identity of the cardiac cell types that develop the human heart. This approach also provided a spatial mapping of individual cells that enables illumination of their organization into cellular communities that form distinct cardiac structures. We discovered that many of these cardiac cell types further specified into subpopulations exclusive to specific communities, which support their specialization according to the cellular ecosystem and anatomical region. In particular, ventricular cardiomyocyte subpopulations displayed an unexpected complex laminar organization across the ventricular wall and formed, with other cell subpopulations, several cellular communities. Interrogating cell-cell interactions within these communities using in vivo conditional genetic mouse models and in vitro human pluripotent stem cell systems revealed multicellular signalling pathways that orchestrate the spatial organization of cardiac cell subpopulations during ventricular wall morphogenesis. These detailed findings into the cellular social interactions and specialization of cardiac cell types constructing and remodelling the human heart offer new insights into structural heart diseases and the engineering of complex multicellular tissues for human heart repair.

Mapping Cell Atlases at the Single-Cell Level

Recent advancements in single-cell technologies have led to rapid developments in the construction of cell atlases. These atlases have the potential to provide detailed information about every cell type in different organisms, enabling the characterization of cellular diversity at the single-cell level. Global efforts in developing comprehensive cell atlases have profound implications for both basic research and clinical applications. This review provides a broad overview of the cellular diversity and dynamics across various biological systems. In addition, the incorporation of machine learning techniques into cell atlas analyses opens up exciting prospects for the field of integrative biology.

Thrombospondin 1 and Reelin act through Vldlr to regulate cardiac growth and repair

Adult mammalian cardiomyocytes have minimal cell cycle capacity, which leads to poor regeneration after cardiac injury such as myocardial infarction. Many positive regulators of cardiomyocyte cell cycle and cardioprotective signals have been identified, but extracellular signals that suppress cardiomyocyte proliferation are poorly understood. We profiled receptors enriched in postnatal cardiomyocytes, and found that very-low-density-lipoprotein receptor (Vldlr) inhibits neonatal cardiomyocyte cell cycle. Paradoxically, Reelin, the well-known Vldlr ligand, expressed in cardiac Schwann cells and lymphatic endothelial cells, promotes neonatal cardiomyocyte proliferation. Thrombospondin1 (TSP-1), another ligand of Vldlr highly expressed in adult heart, was then found to inhibit cardiomyocyte proliferation through Vldlr, and may contribute to Vldlr's overall repression on proliferation. Mechanistically, Rac1 and subsequent Yap phosphorylation and nucleus translocation mediate the regulation of the cardiomyocyte cell cycle by TSP-1/Reelin-Vldlr signaling. Importantly, Reln mutant neonatal mice displayed impaired cardiomyocyte proliferation and cardiac regeneration after apical resection, while cardiac-specific Thbs1 deletion and cardiomyocyte-specific Vldlr deletion promote cardiomyocyte proliferation and are cardioprotective after myocardial infarction. Our results identified a novel role of Vldlr in consolidating extracellular signals to regulate cardiomyocyte cell cycle activity and survival, and the overall suppressive TSP-1-Vldlr signal may contribute to the poor cardiac repair capacity of adult mammals.

Endothelial cells adopt a pro-reparative immune responsive signature during cardiac injury

Modulation of the heart's immune microenvironment is crucial for recovery after ischemic events such as myocardial infarction (MI). Endothelial cells (ECs) can have immune regulatory functions; however, interactions between ECs and the immune environment in the heart after MI remain poorly understood. We identified an EC-specific IFN responsive and immune regulatory gene signature in adult and pediatric heart failure (HF) tissues. Single-cell transcriptomic analysis of murine hearts subjected to MI uncovered an EC population (IFN-ECs) with immunologic gene signatures similar to those in human HF. IFN-ECs were enriched in regenerative-stage mouse hearts and expressed genes encoding immune responsive transcription factors (Irf7, Batf2, and Stat1). Single-cell chromatin accessibility studies revealed an enrichment of these TF motifs at IFN-EC signature genes. Expression of immune regulatory ligand genes by IFN-ECs suggests bidirectional signaling between IFN-ECs and macrophages in regenerative-stage hearts. Our data suggest that ECs may adopt immune regulatory signatures after cardiac injury to accompany the reparative response. The presence of these signatures in human HF and murine MI models suggests a potential role for EC-mediated immune regulation in responding to stress induced by acute injury in MI and chronic adverse remodeling in HF.

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.

Discovery of BMP10 as a new gene underpinning congenital heart defects

OBJECTIVE

Aggregating evidence convincingly establishes the predominant genetic basis underlying congenital heart defects (CHD), though the heritable determinants contributing to CHD in the majority of cases remain elusive. In the current investigation, BMP10 was selected as a prime candidate gene for human CHD mainly due to cardiovascular developmental abnormalities in Bmp10-knockout animals. The objective of this retrospective study was to identify a new BMP10 mutation responsible for CHD and characterize the functional effect of the identified CHD-causing BMP10 mutation.

METHODS

Sequencing assay of BMP10 was fulfilled in a cohort of 276 probands with various CHD and a total of 288 non-CHD volunteers. The available family members from the proband harboring an identified BMP10 mutation were also BMP10-genotyped. The effect of the identified CHD-causative BMP10 mutation on the transactivation of TBX20 and NKX2.5 by BMP10 was quantitatively analyzed in maintained HeLa cells utilizing a dual-luciferase reporter assay system.

RESULTS

A novel heterozygous BMP10 mutation, NM_014482.3:c.247G>T;p.(Glu83*), was identified in one proband with patent ductus arteriosus (PDA), which was confirmed to co-segregate with the PDA phenotype in the mutation carrier's family. The nonsense mutation was not observed in 288 non-CHD volunteers. Functional analysis unveiled that Glu83*-mutant BMP10 had no transactivation on its two representative target genes TBX20 and NKX2.5, which were both reported to cause CHD.

CONCLUSION

These findings provide strong evidence indicating that genetically compromised BMP10 predisposes human beings to CHD, which sheds light on the new molecular mechanism that underlies CHD and allows for antenatal genetic counseling and individualized precise management of CHD.

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.

A combined analysis of TyG index, SII index, and SIRI index: positive association with CHD risk and coronary atherosclerosis severity in patients with NAFLD

Background

Insulin resistance(IR) and inflammation have been regarded as common potential mechanisms in coronary heart disease (CHD) and non-alcoholic fatty liver disease (NAFLD). Triglyceride-glucose (TyG) index is a novel biomarker of insulin resistance, System immune-inflammation index(SII) and Systemic inflammation response index(SIRI) are novel biomarkers of inflammation, these biomarkers have not been studied in CHD with NAFLD patients. This study investigated the correlation between the TyG index, SII index, and SIRI index and CHD risk among NAFLD patients.

Methods

This cross-sectional study included 407 patients with NAFLD in the Department of Cardiology, The Second Hospital of Shanxi Medical University. Of these, 250 patients with CHD were enrolled in the NAFLD+CHD group and 157 patients without CHD were enrolled as NAFLD control. To balance covariates between groups, 144 patients were selected from each group in a 1:1 ratio based on propensity score matching (PSM). Potential influences were screened using Lasso regression analysis. Univariate and multivariate logistic regression analyses and the Least Absolute Shrinkage and Selection Operator (LASSO) regression were used to assess independent risk and protective factors for CHD. Construction of nomogram using independent risk factors screened by machine learning. The receiver operating characteristic(ROC) curve was used to assess the ability of these independent risk factors to predict coronary heart disease. The relationship between the Gensini score and independent risk factors was reflected using the Sankey diagram.

Results

The LASSO logistic regression analysis and Logistic regression analyses suggest that TyG index (OR, 2.193; 95% CI, 1.242-3.873; P = 0.007), SII index (OR, 1.002; 95% CI, 1.001-29 1.003; P <0.001), and SIRI index (OR,1.483;95%CI,1.058-2.079,P=0.022) are independent risk factors for CHD. At the same time, Neutrophils, TG, and LDL-C were also found to be independent risk factors in patients, HDL-C was a protective factor for CHD in patients with NAFLD. Further analysis using three machine learning algorithms found these independent risk factors to have good predictive value for disease diagnosis, SII index shows the highest predictive value. ROC curve analysis demonstrated that combining the SII index, SIRI index, and TyG index can improve the diagnostic ability of non-alcoholic liver cirrhosis patients with CHD.ROC curve analysis showed that the combined analysis of these independent risk factors improved the predictive value of CHD(AUC: 0.751; 95% CI: 0.704-0.798; P <0.001).

Conclusion

TyG index, SII index, and SIRI index are all independent risk factors for CHD in patients with NAFLD and are strongly associated with prediction and the severity of CHD.

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.

KCTD1/KCTD15 complexes control ectodermal and neural crest cell functions, and their impairment causes aplasia cutis

Aplasia cutis congenita (ACC) is a congenital epidermal defect of the midline scalp and has been proposed to be due to a primary keratinocyte abnormality. Why it forms mainly at this anatomic site has remained a long-standing enigma. KCTD1 mutations cause ACC, ectodermal abnormalities, and kidney fibrosis, whereas KCTD15 mutations cause ACC and cardiac outflow tract abnormalities. Here, we found that KCTD1 and KCTD15 can form multimeric complexes and can compensate for each other's loss and that disease mutations are dominant negative, resulting in lack of KCTD1/KCTD15 function. We demonstrated that KCTD15 is critical for cardiac outflow tract development, whereas KCTD1 regulates distal nephron function. Combined inactivation of KCTD1/KCTD15 in keratinocytes resulted in abnormal skin appendages but not in ACC. Instead, KCTD1/KCTD15 inactivation in neural crest cells resulted in ACC linked to midline skull defects, demonstrating that ACC is not caused by a primary defect in keratinocytes but is a secondary consequence of impaired cranial neural crest cells, giving rise to midline cranial suture cells that express keratinocyte-promoting growth factors. Our findings explain the clinical observations in patients with KCTD1 versus KCTD15 mutations, establish KCTD1/KCTD15 complexes as critical regulators of ectodermal and neural crest cell functions, and define ACC as a neurocristopathy.

Transcriptome studies of congenital heart diseases: identifying current gaps and therapeutic frontiers

Congenital heart disease (CHD) are genetically complex and comprise a wide range of structural defects that often predispose to - early heart failure, a common cause of neonatal morbidity and mortality. Transcriptome studies of CHD in human pediatric patients indicated a broad spectrum of diverse molecular signatures across various types of CHD. In order to advance research on congenital heart diseases (CHDs), we conducted a detailed review of transcriptome studies on this topic. Our analysis identified gaps in the literature, with a particular focus on the cardiac transcriptome signatures found in various biological specimens across different types of CHDs. In addition to translational studies involving human subjects, we also examined transcriptomic analyses of CHDs in a range of model systems, including iPSCs and animal models. We concluded that RNA-seq technology has revolutionized medical research and many of the discoveries from CHD transcriptome studies draw attention to biological pathways that concurrently open the door to a better understanding of cardiac development and related therapeutic avenue. While some crucial impediments to perfectly studying CHDs in this context remain obtaining pediatric cardiac tissue samples, phenotypic variation, and the lack of anatomical/spatial context with model systems. Combining model systems, RNA-seq technology, and integrating algorithms for analyzing transcriptomic data at both single-cell and high throughput spatial resolution is expected to continue uncovering unique biological pathways that are perturbed in CHDs, thus facilitating the development of novel therapy for congenital heart disease.

Single-cell reconstruction and mutation enrichment analysis identifies dysregulated cardiomyocyte and endothelial cells in congenital heart disease

Congenital heart disease (CHD) is one of the most prevalent neonatal congenital anomalies. To catalog the putative candidate CHD risk genes, we collected 16,349 variants [single-nucleotide variants (SNVs) and Indels] impacting 8,308 genes in 3,166 CHD cases for a comprehensive meta-analysis. Using American College of Medical Genetics (ACMG) guidelines, we excluded the 0.1% of benign/likely benign variants and the resulting dataset consisted of 83% predicted loss of function variants and 17% missense variants. Seventeen percent were de novo variants. A stepwise analysis identified 90 variant-enriched CHD genes, of which six (GPATCH1, NYNRIN, TCLD2, CEP95, MAP3K19, and TTC36) were novel candidate CHD genes. Single-cell transcriptome cluster reconstruction analysis on six CHD tissues and four controls revealed upregulation of the top 10 frequently mutated genes primarily in cardiomyocytes. NOTCH1 (highest number of variants) and MYH6 (highest number of recurrent variants) expression was elevated in endocardial cells and cardiomyocytes, respectively, and 60% of these gene variants were associated with tetralogy of Fallot and coarctation of the aorta, respectively. Pseudobulk analysis using the single-cell transcriptome revealed significant (P < 0.05) upregulation of both NOTCH1 (endocardial cells) and MYH6 (cardiomyocytes) in the control heart data. We observed nine different subpopulations of CHD heart cardiomyocytes of which only four were observed in the control heart. This is the first comprehensive meta-analysis combining genomics and CHD single-cell transcriptomics, identifying the most frequently mutated CHD genes, and demonstrating CHD gene heterogeneity, suggesting that multiple genes contribute to the phenotypic heterogeneity of CHD. Cardiomyocytes and endocardial cells are identified as major CHD-related cell types.NEW & NOTEWORTHY Congential heart disease (CHD) is one of the most prevalent neonatal congenital anomalies. We present a comprehensive analysis combining genomics and CHD single-cell transcriptome. Our study identifies 90 potential candidate CHD risk genes of which 6 are novel. The risk genes have heterogenous expression suggestive of multiple genes contributing to the phenotypic heterogeneity of CHD. Cardiomyocytes and endocardial cells are identified as major CHD-related cell types.

Uncovering the Genetic Basis of Congenital Heart Disease: Recent Advancements and Implications for Clinical Management

Congenital heart disease (CHD) is the most prevalent hereditary disorder, affecting approximately 1% of all live births. A reduction in morbidity and mortality has been achieved with advancements in surgical intervention, yet challenges in managing complications, extracardiac abnormalities, and comorbidities still exist. To address these, a more comprehensive understanding of the genetic basis underlying CHD is required to establish how certain variants are associated with the clinical outcomes. This will enable clinicians to provide personalized treatments by predicting the risk and prognosis, which might improve the therapeutic results and the patient's quality of life. We review how advancements in genome sequencing are changing our understanding of the genetic basis of CHD, discuss experimental approaches to determine the significance of novel variants, and identify barriers to use this knowledge in the clinics. Next-generation sequencing technologies are unravelling the role of oligogenic inheritance, epigenetic modification, genetic mosaicism, and noncoding variants in controlling the expression of candidate CHD-associated genes. However, clinical risk prediction based on these factors remains challenging. Therefore, studies involving human-induced pluripotent stem cells and single-cell sequencing help create preclinical frameworks for determining the significance of novel genetic variants. Clinicians should be aware of the benefits and implications of the responsible use of genomics. To facilitate and accelerate the clinical integration of these novel technologies, clinicians should actively engage in the latest scientific and technical developments to provide better, more personalized management plans for patients.

The Imageable Genome

Understanding human disease on a molecular level, and translating this understanding into targeted diagnostics and therapies are central tenets of molecular medicine1. Realizing this doctrine requires an efficient adaptation of molecular discoveries into the clinic. We present an approach to facilitate this process by describing the Imageable Genome, the part of the human genome whose expression can be assessed via molecular imaging. Using a deep learning-based hybrid human-AI pipeline, we bridge individual genes and their relevance in human diseases with specific molecular imaging methods. Cross-referencing the Imageable Genome with RNA-seq data from over 60,000 individuals reveals diagnostic, prognostic and predictive imageable genes for a wide variety of major human diseases. Having both the critical size and focus to be altered in its expression during the development and progression of any human disease, the Imageable Genome will generate new imaging tools that improve the understanding, diagnosis and management of human diseases.

From heart to gut: Exploring the gut microbiome in congenital heart disease

Congenital heart disease (CHD) is a prevalent birth defect and a significant contributor to childhood mortality. The major characteristics of CHD include cardiovascular malformations and hemodynamical disorders. However, the impact of CHD extends beyond the circulatory system. Evidence has identified dysbiosis of the gut microbiome in patients with CHD. Chronic hypoxia and inflammation associated with CHD affect the gut microbiome, leading to alterations in its number, abundance, and composition. The gut microbiome, aside from providing essential nutrients, engages in direct interactions with the host immune system and indirect interactions via metabolites. The abnormal gut microbiome or its products can translocate into the bloodstream through an impaired gut barrier, leading to an inflammatory state. Metabolites of the gut microbiome, such as short-chain fatty acids and trimethylamine N-oxide, also play important roles in the development, treatment, and prognosis of CHD. This review discusses the role of the gut microbiome in immunity, gut barrier, neurodevelopment, and perioperative period in CHD. By fostering a better understanding of the cross-talk between CHD and the gut microbiome, this review aims to contribute to improve clinical management and outcomes for CHD patients.

Perturbation of 3D nuclear architecture, epigenomic dysregulation and aging, and cannabinoid synaptopathy reconfigures conceptualization of cannabinoid pathophysiology: part 1-aging and epigenomics

Much recent attention has been directed toward the spatial organization of the cell nucleus and the manner in which three-dimensional topologically associated domains and transcription factories are epigenetically coordinated to precisely bring enhancers into close proximity with promoters to control gene expression. Twenty lines of evidence robustly implicate cannabinoid exposure with accelerated organismal and cellular aging. Aging has recently been shown to be caused by increased DNA breaks. These breaks rearrange and maldistribute the epigenomic machinery to weaken and reverse cellular differentiation, cause genome-wide DNA demethylation, reduce gene transcription, and lead to the inhibition of developmental pathways, which contribute to the progressive loss of function and chronic immune stimulation that characterize cellular aging. Both cell lineage-defining superenhancers and the superanchors that control them are weakened. Cannabis exposure phenocopies the elements of this process and reproduces DNA and chromatin breakages, reduces the DNA, RNA protein and histone synthesis, interferes with the epigenomic machinery controlling both DNA and histone modifications, induces general DNA hypomethylation, and epigenomically disrupts both the critical boundary elements and the cohesin motors that create chromatin loops. This pattern of widespread interference with developmental programs and relative cellular dedifferentiation (which is pro-oncogenic) is reinforced by cannabinoid impairment of intermediate metabolism (which locks in the stem cell-like hyper-replicative state) and cannabinoid immune stimulation (which perpetuates and increases aging and senescence programs, DNA damage, DNA hypomethylation, genomic instability, and oncogenesis), which together account for the diverse pattern of teratologic and carcinogenic outcomes reported in recent large epidemiologic studies in Europe, the USA, and elsewhere. It also accounts for the prominent aging phenotype observed clinically in long-term cannabis use disorder and the 20 characteristics of aging that it manifests. Increasing daily cannabis use, increasing use in pregnancy, and exponential dose-response effects heighten the epidemiologic and clinical urgency of these findings. Together, these findings indicate that cannabinoid genotoxicity and epigenotoxicity are prominent features of cannabis dependence and strongly indicate coordinated multiomics investigations of cannabinoid genome-epigenome-transcriptome-metabolome, chromatin conformation, and 3D nuclear architecture. Considering the well-established exponential dose-response relationships, the diversity of cannabinoids, and the multigenerational nature of the implications, great caution is warranted in community cannabinoid penetration.

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.

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.

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).

Application of Nanomaterials in Stem Cell-Based Therapeutics for Cardiac Repair and Regeneration

Cardiovascular disease is a leading cause of disability and death worldwide. Although the survival rate of patients with heart diseases can be improved with contemporary pharmacological treatments and surgical procedures, none of these therapies provide a significant improvement in cardiac repair and regeneration. Stem cell-based therapies are a promising approach for functional recovery of damaged myocardium. However, the available stem cells are difficult to differentiate into cardiomyocytes, which result in the extremely low transplantation efficiency. Nanomaterials are widely used to regulate the myocardial differentiation of stem cells, and play a very important role in cardiac tissue engineering. This study discusses the current status and limitations of stem cells and cell-derived exosomes/micro RNAs based cardiac therapy, describes the cardiac repair mechanism of nanomaterials, summarizes the recent advances in nanomaterials used in cardiac repair and regeneration, and evaluates the advantages and disadvantages of the relevant nanomaterials. Besides discussing the potential clinical applications of nanomaterials in cardiac therapy, the perspectives and challenges of nanomaterials used in stem cell-based cardiac repair and regeneration are also considered. Finally, new research directions in this field are proposed, and future research trends are highlighted.

Precision and genomic medicine for dilated and hypertrophic cardiomyopathy

Cardiomyopathy develops through an interaction of genetic and environmental factors. The clinical manifestations of both dilated cardiomyopathy and hypertrophic cardiomyopathy are diverse, but genetic testing defines the causative genes in about half of cases and can predict clinical prognosis. It has become clear that cardiomyopathy is caused not only by single rare variants but also by combinations of multiple common variants, and genome-wide genetic research is important for accurate disease risk assessment. Single-cell analysis research aimed at understanding the pathophysiology of cardiomyopathy is progressing rapidly, and it is expected that genomic analysis and single-cell molecular profiling will be combined to contribute to more detailed stratification of cardiomyopathy.

Impact of the Human Cell Atlas on medicine

Single-cell atlases promise to provide a 'missing link' between genes, diseases and therapies. By identifying the specific cell types, states, programs and contexts where disease-implicated genes act, we will understand the mechanisms of disease at the cellular and tissue levels and can use this understanding to develop powerful disease diagnostics; identify promising new drug targets; predict their efficacy, toxicity and resistance mechanisms; and empower new kinds of therapies, from cancer therapies to regenerative medicine. Here, we lay out a vision for the potential of cell atlases to impact the future of medicine, and describe how advances over the past decade have begun to realize this potential in common complex diseases, infectious diseases (including COVID-19), rare diseases and cancer.

Non-cardiomyocytes in the heart in embryo development, health, and disease, a single-cell perspective

Recent single-cell atlases of the heart gave unprecedented details about the diversity of cell types and states during heart development in health and disease conditions. Beyond a profiling tool, researchers also use single-cell analyses to dissect the mechanism of diseases in animal models. The new knowledge from these studies revealed that beating cardiomyocytes account for less than 50% of the total heart cell population. In contrast, non-cardiomyocytes (NCMs), such as cardiac fibroblasts, endothelial cells, and immune cells, make up the remaining proportion and have indispensable roles in structural support, homeostasis maintenance, and injury repair of the heart. In this review, we categorize the composition and characteristics of NCMs from the latest single-cell studies of the heart in various contexts and compare the findings from both human samples and mouse models. This information will enrich our understanding of the cellular basis of heart development and diseases and provide insights into the potential therapeutic targets in NCMs to repair the heart.

Transcriptional plasticity of fibroblasts in heart disease

Cardiac fibroblasts play an essential role in maintaining the structural framework of the heart. Upon stress, fibroblasts undergo a cell state transition to activated fibroblasts (also referred to as myofibroblasts), a highly synthetic cell type that proliferates, migrates, and secrets both extracellular matrix as well as signaling factors that can modulate cellular crosstalk [J. Clin. Invest. 132, e148554]. Activated fibroblasts are critical regulators of cardiac wound healing after injury, but their excessive and persistent activation promote tissue fibrosis, a hallmark feature of the pathological remodeling of the heart. While much of the previous work in cardiac fibroblast biology has focused on the role of canonical signaling pathways or components of the extracellular matrix, recent efforts have been focused on deciphering the gene regulatory principles governing fibroblast activation. A better understanding of the molecular mechanisms that trigger and sustain the fibrotic process in heart disease has the potential to accelerate the development of therapies that specifically target the cardiac activated fibroblasts, which are at the moment unavailable. This concise review focuses on the mechanisms underlying the chromatin and transcriptional regulation of cardiac fibroblast activation. We discuss recent work from our group and others in this space, highlighting the application of single-cell genomics in the characterization of fibroblast function and diversity, and provide an overview on the prospects of targeting cardiac fibroblasts in heart disease and the associated challenges.

Considering the Genetic Architecture of Hypoplastic Left Heart Syndrome

Hypoplastic left heart syndrome (HLHS) is among the most severe cardiovascular malformations and understanding its causes is crucial to making progress in prevention and treatment. Genetic analysis is a broadly useful tool for dissecting complex causal mechanisms and it is playing a significant role in HLHS research. However, unlike classical Mendelian disorders where a relatively small number of genes are largely determinative of the occurrence and severity of the disease, the picture in HLHS is complex. De novo single-gene and copy number variant (CNV) disorders make an important contribution, but there is emerging evidence for causal contributions from lower penetrance and common variation. Integrating this emerging knowledge into clinical diagnostics and translating the findings into effective prevention and treatment remain challenges for the future.