Risk factors of sudden cardiac death in hypertrophic cardiomyopathy

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.

Pediatric hypertrophic cardiomyopathy caused by a novel TNNI3 variant

TNNI3 is a gene that causes hypertrophic cardiomyopathy (HCM). A 14-year-old girl who was diagnosed with nonobstructive HCM presented with cardiopulmonary arrest due to ventricular fibrillation. Genetic testing revealed a novel de novo heterozygous missense variant in TNNI3, NM_000363.5:c.583A>T (p.Ile195Phe), which was determined to be the pathogenic variant. The patient exhibited progressive myocardial fibrosis, left ventricular remodeling, and life-threatening arrhythmias. Genetic testing within families is useful for risk stratification in pediatric HCM patients.

An Investigation of Metabolic Risk Factors and Gut Microbiota in Unexplained Syncope

BACKGROUND

The pathogenesis of many syncopal episodes remains unexplained. Intestinal dysbiosis could be involved in the pathophysiological mechanisms of syncope due to its connection with the central nervous system via the microbiota-gut-brain axis. This pilot study aimed to explore the specific cardiometabolic risk factors and gut microbiota in unexplained syncope (US), compared to other types of syncope, to assess their similarity or verify their different origins.

METHODS

We studied 86 participants with syncope, who were divided into four groups: an orthostatic syncope group (OH, n = 24), a neuromediated syncope group (NMS, n = 26), a cardiological syncope group (CS, n = 9), and an unexplained syncope group (US, n = 27). We evaluated the anthropometric, clinical, and metabolic characteristics of the four groups; the α- and β-diversity; and the differences in the abundance of the microbial taxa.

RESULTS

The US group had a lower incidence of systolic hypertension at the first visit and a lower frequency of patients with nocturnal hypertension than the CS group. Compared to the OH and NMS groups, the US group had a higher incidence of carotid plaques and greater carotid intima-media thickness, respectively. The microbiota differed significantly between the US and CS groups, but not between the US group and the OH or NMS group.

CONCLUSIONS

We observed significant differences in the gut microbiota between CS and US. Future studies are necessary to evaluate the involvement of the gut microbiota in the complex pathogenesis of syncope and whether its analysis could support the interpretation of the pathophysiological mechasnisms underlying some episodes classifiable as US.

Validation of the Risk Stratification for Sudden Cardiac Death in Chinese Patients With Hypertrophic Cardiomyopathy

Accurate identification of hypertrophic cardiomyopathy (HCM) patients at high risk of sudden cardiac death (SCD) event is challenging. The objective of this study was to validate the three SCD risk stratifications recommended by the 2014 European Society of Cardiology (ESC) guideline, the 2020 American Heart Association /American College of Cardiology (AHA/ACC) guideline, and the 2022 ESC guideline in Chinese patients with HCM. Our study population are made up of a cohort of 856 HCM patients without prior SCD events. The endpoint was defined as SCD or equivalent events (successful resuscitation after cardiac arrest or appropriate ICD shock for ventricular tachycardia or ventricular fibrillation). During a median follow-up of 43 months, SCD endpoints occurred in 44 (5.1%) patients. A total of 34 (77.3%) patients suffering from SCD events were classified correctly into high-risk groups by the 2020 AHA/ACC guideline, 27(61.4%) by the 2022 ESC guideline, and 13 (29.6%) by the 2014 ESC guideline. The C-statistic of the 2020 AHA/ACC guideline was 0.68 (95% CI, 0.60-0.76), which performed better than the 2022 ESC guideline (0.65: 95% CI, 0.56-0.73), and the 2014 ESC guideline (0.58: 95% CI, 0.48-0.67). The 2020 AHA/ACC guideline displayed better discrimination for SCD risk stratification in Chinese HCM patients than the other two guidelines, with a higher sensitivity but lower specificity.

Hypertrophic Cardiomyopathy: Genetic Foundations, Outcomes, Interconnections, and Their Modifiers

Hypertrophic cardiomyopathy (HCM) is the most prevalent heritable cardiomyopathy. HCM is considered to be caused by mutations in cardiac sarcomeric protein genes. Recent research suggests that the genetic foundation of HCM is much more complex than originally postulated. The clinical presentations of HCM are very variable. Some mutation carriers remain asymptomatic, while others develop severe HCM, terminal heart failure, or sudden cardiac death. Heterogeneity regarding both genetic mutations and the clinical course of HCM hinders the establishment of universal genotype-phenotype correlations. However, some trends have been identified. The presence of a mutation in some genes encoding sarcomeric proteins is associated with earlier HCM onset, more severe left ventricular hypertrophy, and worse clinical outcomes. There is a diversity in the mechanisms implicated in the pathogenesis of HCM. They may be classified into groups, but they are interrelated. The lack of known supplementary elements that control the progression of HCM indicates that molecular mechanisms that exist between genotype and clinical presentations may be crucial. Secondary molecular changes in pathways implicated in HCM pathogenesis, post-translational protein modifications, and epigenetic factors affect HCM phenotypes. Cardiac loading conditions, exercise, hypertension, diet, alcohol consumption, microbial infection, obstructive sleep apnea, obesity, and environmental factors are non-molecular aspects that change the HCM phenotype. Many mechanisms are implicated in the course of HCM. They are mostly interconnected and contribute to some extent to final outcomes.

Vasovagal syncope: An overview of pathophysiological mechanisms

Syncope is a short-term transient loss of consciousness, characterized by rapid onset and complete spontaneous recovery. According to the 2018 European Society of Cardiology guidelines, three different types of syncope have been identified. However, all forms of syncope share a common final pathophysiological event, global cerebral hypoperfusion, which results from the inability of the circulatory system to maintain blood pressure at the level required to efficiently supply blood to the brain. The vasovagal syncope (VVS) is the most common form of syncope. Although, VVS is generally harmless, its frequent occurrence can negatively affect quality of life and increase the risk of adverse events. The pathophysiological mechanisms underlying VVS remain obscure. The multifaceted nature of VVS presents a veritable challenge to understanding this condition and developing preventative strategies. Thus, the aim of this review was to discuss the factors contributing to the pathogenesis of VVS and provide guidance for future research.

Personalized Management of Sudden Death Risk in Primary Cardiomyopathies: From Clinical Evaluation and Multimodality Imaging to Ablation and Cardioverter-Defibrillator Implant

Sudden cardiac death represents the leading cause of death worldwide; although the majority of sudden deaths occur in an elderly population with coronary artery disease, some occur in young and otherwise healthy individuals, as is the case of cardiomyopathies. The aim of the present review is to provide a stepwise hierarchical approach for the global sudden death risk estimation in primary cardiomyopathies. Each individual risk factor is analyzed for its contribution to the overall risk of sudden death for each specific cardiomyopathy as well as across all primary myocardial diseases. This stepwise hierarchical and personalized approach starts from the clinical evaluation, subsequently passes through the role of electrocardiographic monitoring and multimodality imaging, and finally concludes with genetic evaluation and electro-anatomical mapping. In fact, the sudden cardiac death risk assessment in cardiomyopathies depends on a multiparametric approach. Moreover, current indications for ventricular arrhythmia ablation and defibrillator implantation are discussed.

Arrhythmic Risk Stratification among Patients with Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a cardiac muscle disorder characterized by generally asymmetric abnormal hypertrophy of the left ventricle without abnormal loading conditions (such as hypertension or valvular heart disease) accounting for the left ventricular wall thickness or mass. The incidence of sudden cardiac death (SCD) in HCM patients is about 1% yearly in adults, but it is far higher in adolescence. HCM is the most frequent cause of death in athletes in the Unites States of America. HCM is an autosomal-dominant genetic cardiomyopathy, and mutations in the genes encoding sarcomeric proteins are identified in 30-60% of cases. The presence of this genetic mutation carries more than 2-fold increased risk for all outcomes, including ventricular arrhythmias. Genetic and myocardial substrate, including fibrosis and intraventricular dispersion of conduction, ventricular hypertrophy and microvascular ischemia, increased myofilament calcium sensitivity and abnormal calcium handling, all play a role as arrhythmogenic determinants. Cardiac imaging studies provide important information for risk stratification. Transthoracic echocardiography can be helpful to evaluate left ventricular (LV) wall thickness, LV outflow-tract gradient and left atrial size. Additionally, cardiac magnetic resonance can evaluate the prevalence of late gadolinium enhancement, which when higher than 15% of LV mass is a prognostic maker of SCD. Age, family history of SCD, syncope and non-sustained ventricular tachycardia at Holter ECG have also been validated as independent prognostic markers of SCD. Arrhythmic risk stratification in HCM requires careful evaluation of several clinical aspects. Symptoms combined with electrocardiogram, cardiac imaging tools and genetic counselling are the modern cornerstone for proper risk stratification.

Magnetic Resonance Left Ventricle Mass-Index/Fibrosis: Long-Term Predictors for Ventricular Arrhythmia in Hypertrophic Cardiomyopathy—A Retrospective Registry

Objective: We aimed to study the long-term association of LV mass index (LVMI) and myocardial fibrosis with ventricular arrhythmia (VA) in a population of patients with confirmed hypertrophic cardiomyopathy (HCM) using cardiac magnetic resonance imaging (CMR). Methods: We retrospectively analyzed the data in consecutive HCM patients confirmed on CMR referred to an HCM clinic between January 2008 and October 2018. Patients were followed up yearly following diagnosis. Baseline demographics, risk factors and clinical outcomes from cardiac monitoring and an implanted cardioverter defibrillator (ICD) were analyzed for association of LVMI and LV late gadolinium enhancement (LVLGE) with VA. Patients were then allocated to one of two groups according to the presence of VA (Group A) or absence of VA (Group B) during the follow-up period. The transthoracic echocardiogram (TTE) and CMR parameters were compared between the two groups. Results: A total of 247 patients with confirmed HCM (age 56.2 ± 16.6, male = 71%) were studied over the follow-up period of 7 ± 3.3 years (95% CI = 6.6–7.4 years). LVMI derived from CMR was higher in Group A (91.1 ± 28.1 g/m2 vs. 78.8 ± 28.3 g/m2, p = 0.003) when compared to Group B. LVLGE was higher in Group A (7.3 ± 6.3% vs. 4.7 ± 4.3%, p = 0.001) when compared to Group B. Multivariable Cox regression analysis showed LVMI (hazard ratio (HR) = 1.02, 95% CI = 1.001–1.03, p = 0.03) and LVLGE (HR = 1.04, 95% CI = 1.001–1.08, p = 0.04) to be independent predictors for VA. Receiver operative curves showed higher LVMI and LVLGE with a cut-off of 85 g/m2 and 6%, respectively, to be associated with VA. Conclusions: LVMI and LVLGE are strongly associated with VA over long-term follow-up. LVMI requires more thorough studies to consider it as a risk stratification tool in patients with HCM.

Cardiac Multimodality Imaging in Hypertrophic Cardiomyopathy: What to Look for and When to Image

Hypertrophic cardiomyopathy (HCM), now recognized as a common cardiomyopathy of complex genomics and pathophysiology, is defined by the presence of left ventricular hypertrophy of various morphologies and severity, significant hemodynamic consequences, and diverse phenotypic, both structural and clinical, profiles. Advancements in cardiac multimodality imaging, including echocardiography, cardiac magnetic resonance imaging, and cardiac computed tomography, with and without angiography have greatly improved the diagnosis of HCM, and enable precise measurements of cardiac mass, volume, wall thickness, function, and physiology. Multimodality imaging provides comprehensive and complementary information and hasemerged as the bedrock for the diagnosis, clinical assessment, serial monitoring, and sudden cardiac death risk stratification of patients with HCM. This review highlights the role of cardiac multimodality imaging in the modern diagnosis and management of HCM.

Accelerated Idioventricular Rhythm in a Young Athlete: Physiology or Pathology?

An accelerated idioventricular rhythm was seen on a routine preparticipation electrocardiogram of a 19-year-old healthy and symptom-free athlete. Family history was negative for cardiac disease. Additional investigations revealed a hypertrophic cardiomyopathy, confirmed with cardiac magnetic resonance imaging and genetic analysis. Accelerated idioventricular rhythm in young athletes warrants careful clinical evaluation. (Level of Difficulty: Advanced.).

Clinical significance of genetic variation in hypertrophic cardiomyopathy: comparison of computational tools to prioritize missense variants

Hypertrophic cardiomyopathy (HCM) is a common heart disease associated with sudden cardiac death. Early diagnosis is critical to identify patients who may benefit from implantable cardioverter defibrillator therapy. Although genetic testing is an integral part of the clinical evaluation and management of patients with HCM and their families, in many cases the genetic analysis fails to identify a disease-causing mutation. This is in part due to difficulties in classifying newly detected rare genetic variants as well as variants-of-unknown-significance (VUS). Multiple computational algorithms have been developed to predict the potential pathogenicity of genetic variants, but their relative performance in HCM has not been comprehensively assessed. Here, we compared the performance of 39 currently available prediction tools in distinguishing between high-confidence HCM-causing missense variants and benign variants, and we developed an easy-to-use-tool to perform variant prediction benchmarks based on annotated VCF files (VETA). Our results show that tool performance increases after HCM-specific calibration of thresholds. After excluding potential biases due to circularity type I issues, we identified ClinPred, MISTIC, FATHMM, MPC and MetaLR as the five best performer tools in discriminating HCM-associated variants. We propose combining these tools in order to prioritize unknown HCM missense variants that should be closely followed-up in the clinic.