What Causes Hypertrophic Cardiomyopathy?

ALPK3 heterozygous truncating variants cause late-onset hypertrophic cardiomyopathy with frequent apical involvement and apical aneurysm

Hypertrophic cardiomyopathy (HCM) is a genetically heterogeneous disorder with several established genotype-phenotype relationships. While biallelic truncating variants in the ALPK3 gene cause severe congenital HCM, recent studies have associated heterozygous truncating variants (ALPK3tv) with milder adult-onset HCM. Here we describe a multicenter cohort of 21 individuals with heterozygous ALPK3tv from 10 institutions in the United States, highlighting distinctive clinical characteristics compared to a control group of 132 patients with HCM caused by deleterious variants in sarcomeric genes. As compared to other HCM genotypes, ALPK3tv patients present at an older age (mean 57.25 years) with significantly lower left ventricular wall thickness (14.09 vs 19.78 mm with echocardiogram and 16.13 vs 21.13 mm with cardiac MRI), a lower prevalence of obstructive HCM (15% of ALPK3tv vs 45% of controls), and a strikingly higher incidence of apical aneurysm (22.22% vs. 2.40% in the control group). These results suggest a milder degree of hypertrophy in heterozygous ALPK3-related HCM as compared to other Mendelian causes of HCM, although the increased occurrence of apical aneurysms could have implications for ventricular arrhythmia risk. Our study underscores the importance of recognizing heterozygous ALPK3tv as a cause of adult-onset HCM and provides a comprehensive characterization of its clinical phenotype.

Considerations for drug trials in hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a heterogeneous condition with potentially serious manifestations. Management has traditionally comprised therapies to palliate symptoms and implantable cardioverter-defibrillators to prevent sudden cardiac death. The need for disease-modifying therapies has been recognized for decades. More recently, an increasing number of novel and repurposed therapies hypothesized to target HCM disease pathways have been evaluated, culminating in the recent regulatory approval of mavacamten, a novel oral myosin inhibitor. HCM poses several unique challenges for clinical trials, which are important to recognize when designing trials and interpreting findings. This manuscript discusses the key considerations in the context of recent and ongoing randomized trials, including the roles of genotype, phenotype and symptom status in patient selection, the evidence base for clinical and mechanistic outcome measurements, trial duration and sample size.

Austrian consensus statement on the diagnosis and management of hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is the most common inherited heart disease that is characterized by left ventricular hypertrophy unexplained by secondary causes. Based on international epidemiological data, around 20,000-40,000 patients are expected to be affected in Austria. Due to the wide variety of clinical and morphological manifestations the diagnosis can be difficult and the disease therefore often goes unrecognized. HCM is associated with a substantial reduction in quality of life and can lead to sudden cardiac death, especially in younger patients. Early and correct diagnosis, including genetic testing, is essential for comprehensive counselling of patients and their families and for effective treatment. The latter is especially true as an effective treatment of outflow tract obstruction has recently become available in the form of a first in class cardiac myosin ATPase inhibitor, as a noninvasive alternative to established septal reduction therapies. The aim of this Austrian consensus statement is to summarize the recommendations of international guidelines with respect to the genetic background, pathophysiology, diagnostics and management in the context of the Austrian healthcare system and resources, and to present them in easy to understand algorithms.

The Genetic Factors Influencing Cardiomyopathies and Heart Failure across the Allele Frequency Spectrum

Heart failure (HF) remains a major cause of mortality and morbidity worldwide. Understanding the genetic basis of HF allows for the development of disease-modifying therapies, more appropriate risk stratification, and personalised management of patients. The advent of next-generation sequencing has enabled genome-wide association studies; moving beyond rare variants identified in a Mendelian fashion and detecting common DNA variants associated with disease. We summarise the latest GWAS and rare variant data on mixed and refined HF aetiologies, and cardiomyopathies. We describe the recent understanding of the functional impact of titin variants and highlight FHOD3 as a novel cardiomyopathy-associated gene. We describe future directions of research in this field and how genetic data can be leveraged to improve the care of patients with HF.

Unveiling MiRNA-124 as a biomarker in hypertrophic cardiomyopathy: An innovative approach using machine learning and intelligent data analysis

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is a widespread hereditary cardiac pathology characterized by thickened heart walls and rearrangement of cardiomyocytes. Despite extensive research, the mechanisms underlying HCM development remain poorly understood, impeding the development of effective therapeutic and diagnostic strategies. Recent studies have suggested a polygenic nature of HCM development alongside monogenic forms. Transcriptomic profiling is a valuable tool for investigating such diseases. In this study, we propose a novel approach to study regulatory microRNAs (miRNAs) in the context of HCM, utilizing state-of-the-art data analysis tools.

METHODS AND RESULTS

Our method involves applying the Monte Carlo simulation and machine learning algorithm to transcriptomic data to generate high-capacity classifiers for HCM. From these classifiers, we extract key genes crucial for their performance, resulting in the identification of 16 key genes. Subsequently, we narrow down the pool of miRNAs by selecting those that may target the greatest number of key genes within the best models. We particularly focused on miR-124-3p, which we validated to have an association with HCM on an independent dataset. Subsequent investigation of its function revealed involvement of miR-124-3p in the RhoA signaling pathway.

CONCLUSIONS

In this study we propose a new approach to analyze transcriptomic data to search for microRNAs associated with a disease. Using this approach for transcriptomic profiling data of patients with HCM, we identified miR-124-3p as a potential regulator of the RhoA signaling pathway in the pathogenesis of HCM.

Pharmacokinetics and safety of mavacamten in healthy Chinese participants with different CYP2C19 phenotypes

Obstructive hypertrophic cardiomyopathy (oHCM) is a subtype of HCM characterized by left ventricular outflow tract obstruction resulting from cardiac muscle hypertrophy and anatomic alterations in the mitral valve and apparatus. Mavacamten, a cardiac myosin inhibitor metabolized primarily by CYP2C19 in the liver, is the first and only targeted medication approved for the treatment of symptomatic New York Heart Association (NYHA) class II-III oHCM. Previous pharmacokinetic (PK) results of mavacamten in healthy Caucasian, Japanese, and Asian participants demonstrated that mavacamten exposure was affected by CYP2C19 metabolism status. This open-label, parallel-group, phase I trial aimed to determine the PK and safety of mavacamten in healthy Chinese participants with different CYP2C19 genotypes. The primary outcome was to define the PK of mavacamten in healthy Chinese participants; the secondary outcome was to examine safety and tolerability. After a single oral dose of 15 or 25 mg mavacamten in fasted healthy adult Chinese individuals, Cmax was reached within a median Tmax of 0.6-1.5 h, indicating rapid absorption. Inter-individual variability was moderate, and individuals carrying non-functional CYP2C19 alleles (*2/*2, *3/*3, or *2/*3) exhibited longer half-life and increased total exposure. After stratification of CYP2C19 genotypes, total mavacamten exposures were similar among different ethnic groups when compared with prior PK studies. No significant adverse events were observed in this study. Single oral administration of mavacamten at 15 mg was well tolerated across all CYP2C19 genotypes, and 25 mg dose was well tolerated in healthy participants with CYP2C19 genotypes UM/RM/NM. The PK profile of mavacamten in the healthy Chinese population was consistent with that in other healthy populations.

Substrate mechanics unveil early structural and functional pathology in iPSC micro-tissue models of hypertrophic cardiomyopathy

Hypertension is a major cause of morbidity and mortality in patients with hypertrophic cardiomyopathy (HCM), suggesting a potential role for mechanics in HCM pathogenesis. Here, we developed an in vitro physiological model to investigate how mechanics acts together with HCM-linked myosin binding protein C (MYBPC3) mutations to trigger disease. Micro-heart muscles (μHM) were engineered from induced pluripotent stem cell (iPSC)-derived cardiomyocytes bearing MYBPC3+/- mutations and challenged to contract against substrates of different elasticity. μHMs that worked against substrates with stiffness at or exceeding the stiffness of healthy adult heart muscle exhibited several hallmarks of HCM, including cellular hypertrophy, impaired contractile energetics, and maladaptive calcium handling. Remarkably, we discovered changes in troponin C and T localization in MYBPC3+/- μHM that were entirely absent in 2D culture. Pharmacologic studies suggested that excessive Ca2+ intake through membrane-embedded channels underlie the observed electrophysiological abnormalities. These results illustrate the power of physiologically relevant engineered tissue models to study inherited disease with iPSC technology.

Necroptosis and immune infiltration in hypertrophic cardiomyopathy: novel insights from bioinformatics analyses

Background

Hypertrophic Cardiomyopathy (HCM), a widespread genetic heart disorder, is largely associated with sudden cardiac fatality. Necroptosis, an emerging type of programmed cell death, plays a fundamental role in several cardiovascular diseases.

Aim

This research utilized bioinformatics analysis to investigate necroptosis's implication in HCM.

Methods

The study retrieved RNA sequencing datasets GSE130036 and GSE141910 from the Gene Expression Omnibus (GEO) database. It detected necroptosis-linked differentially expressed genes (NRDEGs) by reviewing both the gene set for necroptosis and the differently expressed genes (DEGs). The enriched signaling pathway of HCM was assessed using GSEA, while common DEGs were studied through Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways. Concurrently, the Protein-Protein Interaction network (PPI) proved useful for identifying central genes. CIBERSORT facilitated evaluating the correlation between distinct immune cell-type prevalence and NRDEGs by analyzing immune infiltration patterns. Lastly, GSE141910 dataset validated the expression ranks of NRDEGs and immune-cell penetration.

Results

The investigation disclosed significant enrichment and activation of the necroptosis pathway in HCM specimens. Seventeen diverse genes, including CYBB, BCL2, and JAK2 among others, were identified in the process. PPI network scrutiny classified nine of these genes as central genes. Results from GO and KEGG enrichment analyses showed substantial connections of these genes to pathways pertaining to the HIF-1 signaling track, necroptosis, and NOD-like receptor signaling process. Moreover, an imbalance in M2 macrophage cells in HCM samples was observed. Finally, CYBB, BCL2, and JAK2 emerged as vital genes and were validated using the GSE141910 dataset.

Conclusion

These results indicate necroptosis as a probable underlying factor in HCM, with immune cell infiltration playing a part. Additionally, CYBB, BCL2, JAK2 could act as potential biomarkers for recognizing HCM. This information forms crucial insights into the basic mechanisms of HCM and could enhance its diagnosis and management.

Relationship Between Genotype Status and Clinical Outcome in Hypertrophic Cardiomyopathy

BACKGROUND

The genetic basis of hypertrophic cardiomyopathy (HCM) is complex, and the relationship between genotype status and clinical outcome is incompletely resolved.

METHODS AND RESULTS

We assessed a large international HCM cohort to define in contemporary terms natural history and clinical consequences of genotype. Consecutive patients (n=1468) with established HCM diagnosis underwent genetic testing. Patients with pathogenic (or likely pathogenic) variants were considered genotype positive (G+; n=312; 21%); those without definite disease-causing mutations (n=651; 44%) or variants of uncertain significance (n=505; 35%) were considered genotype negative (G-). Patients were followed up for a median of 7.8 years (interquartile range, 3.5-13.4 years); HCM end points were examined by cumulative event incidence. Over follow-up, 135 (9%) patients died, 33 from a variety of HCM-related causes. After adjusting for age, all-cause and HCM-related mortality did not differ between G- versus G+ patients (hazard ratio [HR], 0.78 [95% CI, 0.46-1.31]; P=0.37; HR, 0.93 [95% CI, 0.38-2.30]; P=0.87, respectively). Adverse event rates, including heart failure progression to class III/IV, heart transplant, or heart failure death, did not differ (G- versus G+) when adjusted for age (HR, 1.20 [95% CI, 0.63-2.26]; P=0.58), nor was genotype independently associated with sudden death event risk (HR, 1.39 [95% CI, 0.88-2.21]; P=0.16). In multivariable analysis, age was the only independent predictor of all-cause and HCM-related mortality, heart failure progression, and sudden death events.

CONCLUSIONS

In this large consecutive cohort of patients with HCM, genotype (G+ or G-) was not a predictor of clinical course, including all-cause and HCM-related mortality and risk for heart failure progression or sudden death. G+ status should not be used to dictate clinical management or predict outcome in HCM.

A Meta-Analysis Approach to Gene Regulatory Network Inference Identifies Key Regulators of Cardiovascular Diseases

Cardiovascular diseases (CVDs) represent a major concern for global health, whose mechanistic understanding is complicated by a complex interplay between genetic predisposition and environmental factors. Specifically, heart failure (HF), encompassing dilated cardiomyopathy (DC), ischemic cardiomyopathy (ICM), and hypertrophic cardiomyopathy (HCM), is a topic of substantial interest in basic and clinical research. Here, we used a Partial Correlation Coefficient-based algorithm (PCC) within the context of a meta-analysis framework to construct a Gene Regulatory Network (GRN) that identifies key regulators whose activity is perturbed in Heart Failure. By integrating data from multiple independent studies, our approach unveiled crucial regulatory associations between transcription factors (TFs) and structural genes, emphasizing their pivotal roles in regulating metabolic pathways, such as fatty acid metabolism, oxidative stress response, epithelial-to-mesenchymal transition, and coagulation. In addition to known associations, our analysis also identified novel regulators, including the identification of TFs FPM315 and OVOL2, which are implicated in dilated cardiomyopathies, and TEAD1 and TEAD2 in both dilated and ischemic cardiomyopathies. Moreover, we uncovered alterations in adipogenesis and oxidative phosphorylation pathways in hypertrophic cardiomyopathy and discovered a role for IL2 STAT5 signaling in heart failure. Our findings underscore the importance of TF activity in the initiation and progression of cardiac disease, highlighting their potential as pharmacological targets.

Transcriptomics data integration and analysis to uncover hallmark genes in hypertrophic cardiomyopathy

INTRODUCTION

Hypertrophic cardiomyopathy (HCM) is a heterogeneous disease that mainly affects the myocardium. In the current study, we aim to explore HCM-related hub genes through the analysis of differentially expressed genes (DEGs) between HCM and normal sample groups.

METHODS

The GSE68316 and GSE36961 expression profiles were obtained from the Gene Expression Omnibus (GEO) database for the identification of DEGs, to explore hub genes, and to perform their expression analysis. Clinical HCM and control tissue samples were taken for expression and promoter methylation validation analysis via RNA-sequencing (RNA-seq) and targeted bisulfite sequencing (bisulfite-seq) analyses. Then, other different bioinformatics tools were employed to perform STRING, lncRNA-miRNA-mRNA regulatory networks, gene enrichment, and drug prediction analyses.

RESULTS

In total, the top 20 DEGs, including 10 up-regulated and 10 down-regulated, were obtained from GSE68316. Out of the 20 DEGs, we subsequently identified the 8 most important hub genes including 5 up-regulated genes (EPB42, UQCRH, CA1, PFDN5, and LSM5) and 3 down-regulated genes (RPS24, TNS1, and RPL26). Expression and promoter methylation dysregulation of these genes were further validated on clinical HCM samples paired with controls. Next, we further investigated hub genes' regulatory 6 miRNAs (has-mir-1-3p, has-mir-129-5p, has-mir-16-5p, has-mir-23b-3p, has-mir-27-3p, and has-mir-182-5p) and miRNAs regulatory 4 lncRNAs (NUTMB2-AS1, NEAT1, XIST, and GABPB1-AS1) in this study via the lncRNA-cricRNA-miRNA-mRNA regulatory network. Later on, gene enrichment analysis revealed that hub genes were enriched in various important pathways including Nitrogen metabolism, Ribosome, RNA degradation, Cardiac muscle contraction, and Coronavirus disease, etc. Finally, the drug prediction analysis highlighted different potential candidate drugs for altering the expression of hub genes in the treatment of HCM.

CONCLUSION

In summary, the identification of key hub genes and their enrichment analysis in the current study may shed light on the mechanisms behind the occurrence and development of HCM.

Age-dependent association of metabolic dyslipidemia with clinical expression of hypertrophic cardiomyopathy

BACKGROUND

Previous studies have shown that the clinical expression of hypertrophic cardiomyopathy (HCM) can be determined by obesity and metabolic syndrome. The present study aimed to investigate the association between triglyceride and high-density lipoprotein cholesterol (HDLC) level, the two dyslipidemia-related components of metabolic syndrome, and the incidence of HCM. We also explored an age-dependent association between them.

METHODS

Individuals without previous HCM diagnosis who underwent a designated national health examination in 2009 were recruited. Individuals who used lipid-lowering medications within 1-year of the baseline were excluded. The outcome of interest was a newly diagnosed HCM.

RESULTS

Our cohort consisted of 8,652,709 individuals (mean 46 years, 55.6% men). During the median 9.3 years of follow-up, 5932 (0.07%) individuals were newly diagnosed with HCM. There was a gradual increase in the incidence of HCM towards higher triglyceride and lower HDL-C levels (log-rank p < 0.001). When stratified by age, the incidence of HCM was highest in individuals aged ≥65 years, followed by those aged 40-64 and 20-39 years (0.22% vs. 0.07% vs. 0.03%, log-rank p < 0.001). In individuals aged 20-39 years, a higher triglyceride level was associated with a higher incidence of HCM (i.e., ≥200 vs. <100 mg/dL: adjusted hazard ratio 2.28, 95% confidence interval 1.89-2.75), whereas there was no significant association in older groups (p-for-interaction<0.001). Similarly, a lower HDL-C level was associated with a higher incidence of HCM, particularly in individuals aged 20-39 years (p-for-interaction = 0.001).

CONCLUSIONS

High triglyceride and low HDL-C levels are associated with a higher incidence of HCM, particularly in young individuals.

Inverse Association between Exercising Blood Pressure Response and Left Ventricular Chamber Size and Mass in Women Who Habitually Resistance Train

Exercise is a major modifiable lifestyle factor that leads to temporarily increased systolic blood pressure (SBP), which is thought to influence left ventricular mass normalized to body surface area (LVM/BSA). This relationship has never been studied in women who habitually perform resistance exercise.

PURPOSE

To determine if a direct correlation exists between the SBP response to resistance exercise (change from rest; eSBP) and LVM/BSA in young healthy women who habitually resistance train.

METHODS

Leg extension resistance exercise was performed while continuously monitoring blood pressure using finger plethysmography. LVM was estimated using echocardiography. Data are shown as mean ± SD.

RESULTS

Thirty-one women participated (age 23 ± 3 years, height 164 ± 7 cm, body mass 63.7 ± 10.3 kg). Resting SBP (110 ± 8 mmHg, r = 0.355, p = 0.049) was shown to be directly correlated to LVM/BSA (72.0 ± 28.4 g/m2). Conversely, eSBP (30.8 ± 14.6 ∆mmHg, r = -0.437, p = 0.014) was inversely related to LVM/BSA. eSBP was not correlated to interventricular septum width (0.88 ± 0.12 cm, r = -0.137, p = 0.463) or posterior wall thickness (0.91 ± 0.15 cm, r = -0.084, p = 0.654). eSBP was inversely related to left ventricle internal diameter during diastole (LVIDd) (4.25 ± 0.33 cm, r = -0.411, p = 0.021).

CONCLUSION

Counter to the hypothesis, these data suggest an inverse association between eSBP during resistance exercise and LVM/BSA in healthy young women who resistance train. This relationship is due to a smaller LVIDd with greater eSBP.

Roles of the crucial mitochondrial DNA in hypertrophic cardiomyopathy prognosis and diagnosis: A review

Mitochondrial DNA is implicated in hypertrophic cardiomyopathy (HCM) development. We aimed to identify valuable mtDNAs that contribute to the development of HCM. Differentially expressed mitochondrial DNAs (DEMGs) between HCM and controls were screened. GO and KEGG functional enrichment analyses were performed, and the optimum genes were explored using the LASSO regression mode and SVM-RFE model. A diagnostic scoring model was constructed and verified using ROC curves. Mitochondria-based subtypes were identified. Immune performance among the subtypes including immune cells, immune checkpoint genes, and HLA family genes was analyzed. Finally, an mRNA-transcription factor (TF)-miRNA network was constructed using Cytoscape software. Twelve DEMGs in HCM were selected. Among them, 6 DEMGs, including PDK4, MGST1, TOMM40, LYPLAL1, GATM, and CPT1B were demonstrated as DEMGs at the point of intersection of Lasso regression and SVM-RFE. The ROC of the model for the training and validation datasets was 0.999 and 0.958, respectively. Two clusters were divided, and 4 immune cell types were significantly different between the 2 clusters, including resting mast cells, macrophages M2, and plasma cells. Nine upregulated KEGG pathways were enriched in cluster 1 vs. cluster 2 including O-glycan biosynthesis, the ErbB signaling pathway, and the GnRH signaling pathway. Meanwhile, 49 down-regulated pathways were enriched such as the toll-like signaling pathway and natural killer cell-mediated cytotoxicity pathway. The 6 gene-based mRNA-TF-miRNA networks included other 133 TFs and 18 miRNAs. Six DEMGs in HCM, including PDK4, MGST1, TOMM40, LYPLAL1, GATM, and CPT1B, can be indicative of HCM prognosis or disease progression.

Characterization of heterozygous and homozygous mouse models with the most common hypertrophic cardiomyopathy mutation MYBPC3c.2373InsG in the Netherlands

Hypertrophic cardiomyopathy (HCM) is frequently caused by mutations in the cardiac myosin binding protein-C (cMyBP-C) encoding gene MYBPC3. In the Netherlands, approximately 25% of patients carry the MYBPC3c.2373InsG founder mutation. Most patients are heterozygous (MYBPC3+/InsG) and have highly variable phenotypic expression, whereas homozygous (MYBPC3InsG/InsG) patients have severe HCM at a young age. To improve understanding of disease progression and genotype-phenotype relationship based on the hallmarks of human HCM, we characterized mice with CRISPR/Cas9-induced heterozygous and homozygous mutations. At 18-28 weeks of age, we assessed the cardiac phenotype of Mybpc3+/InsG and Mybpc3InsG/InsG mice with echocardiography, and performed histological analyses. Cytoskeletal proteins and cardiomyocyte contractility of 3-4 week old and 18-28 week old Mybpc3c.2373InsG mice were compared to wild-type (WT) mice. Expectedly, knock-in of Mybpc3c.2373InsG resulted in the absence of cMyBP-C and our 18-28 week old homozygous Mybpc3c.2373InsG model developed cardiac hypertrophy and severe left ventricular systolic and diastolic dysfunction, whereas HCM was not evident in Mybpc3+/InsG mice. Mybpc3InsG/InsG cardiomyocytes also presented with slowed contraction-relaxation kinetics, to a greater extent in 18-28 week old mice, partially due to increased levels of detyrosinated tubulin and desmin, and reduced cardiac troponin I (cTnI) phosphorylation. Impaired cardiomyocyte contraction-relaxation kinetics were successfully normalized in 18-28 week old Mybpc3InsG/InsG cardiomyocytes by combining detyrosination inhibitor parthenolide and β-adrenergic receptor agonist isoproterenol. Both the 3-4 week old and 18-28 week old Mybpc3InsG/InsG models recapitulate HCM, with a severe phenotype present in the 18-28 week old model.

Mechanical Resistance to Micro-Heart Tissue Contractility unveils early Structural and Functional Pathology in iPSC Models of Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy is the most common cause of sudden death in the young. Because the disease exhibits variable penetrance, there are likely nongenetic factors that contribute to the manifestation of the disease phenotype. Clinically, hypertension is a major cause of morbidity and mortality in patients with HCM, suggesting a potential synergistic role for the sarcomeric mutations associated with HCM and mechanical stress on the heart. We developed an in vitro physiological model to investigate how the afterload that the heart muscle works against during contraction acts together with HCM-linked MYBPC3 mutations to trigger a disease phenotype. Micro-heart muscle arrays (μHM) were engineered from iPSC-derived cardiomyocytes bearing MYBPC3 loss-of-function mutations and challenged to contract against mechanical resistance with substrates stiffnesses ranging from the of embryonic hearts (0.4 kPa) up to the stiffness of fibrotic adult hearts (114 kPa). Whereas MYBPC3 +/- iPSC-cardiomyocytes showed little signs of disease pathology in standard 2D culture, μHMs that included components of afterload revealed several hallmarks of HCM, including cellular hypertrophy, impaired contractile energetics, and maladaptive calcium handling. Remarkably, we discovered changes in troponin C and T localization in the MYBPC3 +/- μHM that were entirely absent in 2D culture. Pharmacologic studies suggested that excessive Ca 2+ intake through membrane-embedded channels, rather than sarcoplasmic reticulum Ca 2+ ATPase (SERCA) dysfunction or Ca 2+ buffering at myofilaments underlie the observed electrophysiological abnormalities. These results illustrate the power of physiologically relevant engineered tissue models to study inherited disease mechanisms with iPSC technology.

Myocardial Fibrosis in Hypertrophic Cardiomyopathy: A Perspective from Fibroblasts

Hypertrophic cardiomyopathy (HCM) is the most common inherited heart disease and the leading cause of sudden cardiac death in young people. Mutations in genes that encode structural proteins of the cardiac sarcomere are the more frequent genetic cause of HCM. The disease is characterized by cardiomyocyte hypertrophy and myocardial fibrosis, which is defined as the excessive deposition of extracellular matrix proteins, mainly collagen I and III, in the myocardium. The development of fibrotic tissue in the heart adversely affects cardiac function. In this review, we discuss the latest evidence on how cardiac fibrosis is promoted, the role of cardiac fibroblasts, their interaction with cardiomyocytes, and their activation via the TGF-β pathway, the primary intracellular signalling pathway regulating extracellular matrix turnover. Finally, we summarize new findings on profibrotic genes as well as genetic and non-genetic factors involved in the pathophysiology of HCM.

Serum C-terminal telopeptide of Type-I collagen (CTx) concentration and myocardial hyperechogenicity in cats with hypertrophic cardiomyopathy

Objective

This study sought to determine the serum concentrations of C-terminal telopeptide of Type-I collagen (CTx), a marker of collagen degradation, in a hospital population of cats with hypertrophic cardiomyopathy (HCM). The study also evaluated the prevalence of myocardial hyperechogenicity of the left ventricle (LV) in the same cats.

Animals and procedure

Cats brought to a university veterinary cardiology service entered the study when they had an echocardiographic diagnosis of HCM; echocardiographically normal cats served as controls. Serum CTx concentrations were assessed using ELISA.

Results

There was no difference in serum CTx concentrations between cats with HCM and controls (HCM: median 0.248 ng/mL, controls: median 0.253 ng/mL; P = 0.4). Significantly more cats with HCM (60%) showed echocardiographic LV myocardial hyperechogenicity compared to normal controls (17%; P = 0.0057), but serum CTx concentrations were not different between these 2 groups.

Conclusion and clinical relevance

These results indicate that, as in human patients with HCM and in contrast to earlier feline studies, there was no evidence of enhanced collagen degradation indicated by serum CTx concentrations in cats with HCM compared to normal controls.

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.

Genetic Insights from Consanguineous Cardiomyopathy Families

Inherited cardiomyopathies are a prevalent cause of heart failure and sudden cardiac death. Both hypertrophic (HCM) and dilated cardiomyopathy (DCM) are genetically heterogeneous and typically present with an autosomal dominant mode of transmission. Whole exome sequencing and autozygosity mapping was carried out in eight un-related probands from consanguineous Middle Eastern families presenting with HCM/DCM followed by bioinformatic and co-segregation analysis to predict the potential pathogenicity of candidate variants. We identified homozygous missense variants in TNNI3K, DSP, and RBCK1 linked with a dilated phenotype, in NRAP linked with a mixed phenotype of dilated/hypertrophic, and in KLHL24 linked with a mixed phenotype of dilated/hypertrophic and non-compaction features. Co-segregation analysis in family members confirmed autosomal recessive inheritance presenting in early childhood/early adulthood. Our findings add to the mutational spectrum of recessive cardiomyopathies, supporting inclusion of KLHL24, NRAP and RBCK1 as disease-causing genes. We also provide evidence for novel (recessive) modes of inheritance of a well-established gene TNNI3K and expand our knowledge of the clinical heterogeneity of cardiomyopathies. A greater understanding of the genetic causes of recessive cardiomyopathies has major implications for diagnosis and screening, particularly in underrepresented populations, such as those of the Middle East.

Subtypes and Mechanisms of Hypertrophic Cardiomyopathy Proposed by Machine Learning Algorithms

Hypertrophic cardiomyopathy (HCM) is a relatively common inherited cardiac disease that results in left ventricular hypertrophy. Machine learning uses algorithms to study patterns in data and develop models able to make predictions. The aim of this study is to identify HCM subtypes and examine the mechanisms of HCM using machine learning algorithms. Clinical and laboratory findings of 143 adult patients with a confirmed diagnosis of nonobstructive HCM are analyzed; HCM subtypes are determined by clustering, while the presence of different HCM features is predicted in classification machine learning tasks. Four clusters are determined as the optimal number of clusters for this dataset. Models that can predict the presence of particular HCM features from other genotypic and phenotypic information are generated, and subsets of features sufficient to predict the presence of other features of HCM are determined. This research proposes four subtypes of HCM assessed by machine learning algorithms and based on the overall phenotypic expression of the participants of the study. The identified subsets of features sufficient to determine the presence of particular HCM aspects could provide deeper insights into the mechanisms of HCM.