Comprehensive Proteomics Profiling Reveals Circulating Biomarkers of Hypertrophic Cardiomyopathy

Machine learning and experimental validation of novel biomarkers for hypertrophic cardiomyopathy and cancers

Hypertrophic cardiomyopathy (HCM) is a hereditary cardiac disorder marked by anomalous thickening of the myocardium, representing a significant contributor to mortality. While the involvement of immune inflammation in the development of cardiac ailments is well-documented, its specific impact on HCM pathogenesis remains uncertain. Five distinct machine learning algorithms, namely LASSO, SVM, RF, Boruta and XGBoost, were utilized to discover new biomarkers associated with HCM. A unique nomogram was developed using two newly identified biomarkers and subsequently validated. Furthermore, samples of HCM and normal heart tissues were gathered from our institution to confirm the variance in expression levels and prognostic significance of GATM and MGST1. Five novel biomarkers (DARS2, GATM, MGST1, SDSL and ARG2) associated with HCM were identified. Subsequent validation revealed that GATM and MGST1 exhibited significant diagnostic utility for HCM in both the training and test cohorts, with all AUC values exceeding 0.8. Furthermore, a novel risk assessment model for HCM patients based on the expression levels of GATM and MGST1 demonstrated favourable performance in both the training (AUC = 0.88) and test cohorts (AUC = 0.9). Furthermore, our study revealed that GATM and MGST1 exhibited elevated expression levels in HCM tissues, demonstrating strong discriminatory ability between HCM and normal cardiac tissues (AUC of GATM = 0.79; MGST1 = 0.86). Our findings suggest that two specific cell types, monocytes and multipotent progenitors (MPP), may play crucial roles in the pathogenesis of HCM. Notably, GATM and MGST1 were found to be highly expressed in various tumours and showed significant prognostic implications. Functionally, GATM and MGST1 are likely involved in xenobiotic metabolism and epithelial mesenchymal transition in a wide range of cancer types. GATM and MGST1 have been identified as novel biomarkers implicated in the progression of both HCM and cancer. Additionally, monocytes and MPP may also play a role in facilitating the progression of HCM.

Clonal haematopoiesis is associated with major adverse cardiovascular events in patients with hypertrophic cardiomyopathy

AIMS

The heterogeneous phenotype of hypertrophic cardiomyopathy (HCM) is still not fully understood. Clonal haematopoiesis (CH) is emerging as a cardiovascular risk factor potentially associated with adverse clinical events. The prevalence, phenotype and outcomes related to CH in HCM patients were evaluated.

METHODS AND RESULTS

Patients with HCM and available biospecimens from the Peter Munk Cardiac Centre Cardiovascular Biobank were subjected to targeted sequencing for 35 myeloid genes associated with CH. CH prevalence, clinical characteristics, morphological phenotypes assessed by echocardiogram and cardiac magnetic resonance and outcomes were assessed. All patients were evaluated for a 71-plex cytokines/chemokines, troponin I and B-type natriuretic peptide analysis. Major adverse cardiovascular events (MACE) were defined as appropriate implantable cardioverter-defibrillator shock, stroke, cardiac arrest, orthotopic heart transplant and death. Among the 799 patients, CH was found in 183 (22.9%) HCM patients with sarcomeric germline mutations. HCM patients with CH were more symptomatic and with a higher burden of fibrosis than those without CH. CH was associated with MACE in those HCM patients with sarcomeric germline mutations (adjusted hazard ratio [HR] 6.89, 95% confidence interval [CI] 1.78-26.6; p = 0.005), with the highest risk among those that had DNMT3A, TET2 and ASXL1 mutations (adjusted HR 5.76, 95% CI 1.51-21.94; p = 0.010). Several cytokines (IL-1ra, IL-6, IL-17F, TGFα, CCL21, CCL1, CCL8, and CCL17), and troponin I were upregulated in gene-positive HCM patients with CH.

CONCLUSIONS

These results indicate that CH in patients with HCM is associated with worse clinical outcomes. In the absence of CH, gene-positive patients with HCM have lower rates of MACE.

Biomarkers and Proteomics in Sarcomeric Hypertrophic Cardiomyopathy in the Young-FGF-21 Highly Associated with Overt Disease

Background: Any difference in biomarkers between genotype-positive individuals with overt hypertrophic cardiomyopathy (HCM), and genotype-positive but phenotype-negative individuals (G+P-) in HCM-associated pathways might shed light on pathophysiological mechanisms. We studied this in young HCM patients. Methods: 29 HCM patients, 17 G+P--individuals, and age- and sex-matched controls were prospectively included. We analyzed 184 cardiovascular disease-associated proteins by two proximity extension assays, categorized into biological pathways, and analyzed with multivariate logistic regression analysis. Significant proteins were dichotomized into groups above/below median concentration in control group. Results: Dichotomized values of significant proteins showed high odds ratio (OR) in overt HCMphenotype for Fibroblast growth factor-21 (FGF-21) 10 (p = 0.001), P-selectin glycoprotein ligand-1 (PSGL-1) OR 8.6 (p = 0.005), and Galectin-9 (Gal-9) OR 5.91 (p = 0.004). For G+P-, however, angiopoietin-1 receptor (TIE2) was notably raised, OR 65.5 (p = 0.004), whereas metalloproteinase inhibitor 4 (TIMP4) involved in proteolysis, in contrast, had reduced OR 0.06 (p = 0.013). Conclusions: This study is one of the first in young HCM patients and G+P- individuals. We found significantly increased OR for HCM in FGF-21 involved in RAS-MAPK pathway, associated with cardiomyocyte hypertrophy. Upregulation of FGF-21 indicates involvement of the RAS-MAPK pathway in HCM regardless of genetic background, which is a novel finding.

Signaling Pathways Associated With Prior Cardiovascular Events in Hypertrophic Cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is the most common genetic cardiomyopathy. A subset of patients experience major adverse cardiovascular events (MACEs), including arrhythmias, strokes and heart failure. However, the molecular mechanisms underlying MACEs in HCM are still not well understood. Therefore, we conducted a multicenter case-control study of patients with HCM, comparing those with and without prior histories of MACEs to identify dysregulated signaling pathways through plasma proteomics profiling.

METHODS

We performed plasma proteomics profiling of 4986 proteins. We developed a proteomics-based discrimination model in patients enrolled at 1 institution (training set) and externally validated the model in patients enrolled at another institution (test set). We performed pathway analysis of proteins dysregulated in patients with prior MACEs.

RESULTS

A total of 402 patients were included, with 278 in the training set and 124 in the test set. In this cohort, 257 (64%) patients had prior MACEs (172 in the training set and 85 in the test set). Using the proteomics-based model from the training set, the area under the receiver operating characteristic curve was 0.82 (95% confidence interval, 0.75-0.90) in the test set. Patients with prior MACEs demonstrated dysregulation in pathways known to be associated with MACEs (eg, TGF-β) and novel pathways (eg, Ras-MAPK and associated pathways).

CONCLUSIONS

In this multicenter study of 402 patients with HCM, we identified both known and novel pathways dysregulated in a subset of patients with more advanced disease.

Deficiency of Transcription Factor Sp1 Contributes to Hypertrophic Cardiomyopathy

BACKGROUND

Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disorder. However, the pathogenesis of HCM, especially its nongenetic mechanisms, remains largely unclear. Transcription factors are known to be involved in various biological processes including cell growth. We hypothesized that SP1 (specificity protein 1), the first purified TF in mammals, plays a role in the cardiomyocyte growth and cardiac hypertrophy of HCM.

METHODS

Cardiac-specific conditional knockout of Sp1 mice were constructed to investigate the role of SP1 in the heart. The echocardiography, histochemical experiment, and transmission electron microscope were performed to analyze the cardiac phenotypes of cardiac-specific conditional knockout of Sp1 mice. RNA sequencing, chromatin immunoprecipitation sequencing, and adeno-associated virus experiments in vivo were performed to explore the downstream molecules of SP1. To examine the therapeutic effect of SP1 on HCM, an SP1 overexpression vector was constructed and injected into the mutant allele of Myh6 R404Q/+ (Myh6 c. 1211C>T) HCM mice. The human induced pluripotent stem cell-derived cardiomyocytes (hiPSC-CMs) from a patient with HCM were used to detect the potential therapeutic effects of SP1 in human HCM.

RESULTS

The cardiac-specific conditional knockout of Sp1 mice developed a typical HCM phenotype, displaying overt myocardial hypertrophy, interstitial fibrosis, and disordered myofilament. In addition, Sp1 knockdown dramatically increased the cell area of hiPSC-CMs and caused intracellular myofibrillar disorganization, which was similar to the hypertrophic cardiomyocytes of HCM. Mechanistically, Tuft1 was identified as the key target gene of SP1. The hypertrophic phenotypes induced by Sp1 knockdown in both hiPSC-CMs and mice could be rescued by TUFT1 (tuftelin 1) overexpression. Furthermore, SP1 overexpression suppressed the development of HCM in the mutant allele of Myh6 R404Q/+ mice and also reversed the hypertrophic phenotype of HCM hiPSC-CMs.

CONCLUSIONS

Our study demonstrates that SP1 deficiency leads to HCM. SP1 overexpression exhibits significant therapeutic effects on both HCM mice and HCM hiPSC-CMs, suggesting that SP1 could be a potential intervention target for HCM.

Identification and validation of pyroptosis-related genes as potential biomarkers for hypertrophic cardiomyopathy: A comprehensive bioinformatics analysis

Pyroptosis plays a key role in the death of cells including cardiomyocytes, and it is associated with a variety of cardiovascular diseases. However, the role of pyroptosis-related genes (PRGs) in hypertrophic cardiomyopathy (HCM) is not well characterized. This study aimed to identify key biomarkers and explore the molecular mechanisms underlying the functions of the PRGs in HCM. The differentially expressed genes were identified by GEO2R, and the differentially expressed pyroptosis-related genes (DEPRGs) of HCM were identified by combining with PRGs. Enrichment analysis was performed using the "clusterProfiler" package of the R software. Protein-protein interactions (PPI) network analysis was performed using the STRING database, and hub genes were screened using cytoHubba. TF-miRNA coregulatory networks and protein-chemical interactions were analyzed using NetworkAnalyst. RT-PCR/WB was used for expression validation of HCM diagnostic markers. Quantitative reverse transcription-polymerase chain reaction (qRT-PCR) and Western Blot (WB) were used to measure and compare the expression of the identified genes in the cardiac hypertrophy model and the control group. A total of 20 DEPRGs were identified, which primarily showed enrichment for the positive regulation of cytokine production, regulation of response to biotic stimulus, tumor necrosis factor production, and other biological processes. These processes primarily involved pathways related to Renin-angiotensin system, Adipocytokine signaling pathway and NF-kappa B signaling pathway. Then, a PPI network was constructed, and 8 hub genes were identified. After verification analysis, the finally identified HCM-related diagnostic markers were upregulated gene protein tyrosine phosphatase non-receptor type 11 (PTPN11), downregulated genes interleukin-1 receptor-associated kinase 3 (IRAK3), and annexin A2 (ANXA2). Further GSEA analysis revealed these 3 biomarkers primarily related to cardiac muscle contraction, hypertrophic cardiomyopathy, fatty acid degradation and ECM - receptor interaction. Moreover, we also elucidated the interaction network of these biomarkers with the miRNA network and known compounds, respectively. RT-PCR/WB results indicated that PTPN11 expression was significantly increased, and IRAK3 and ANXA2 expressions were significantly decreased in HCM. This study identified PTPN11, IRAK3, and ANXA2 as pyroptosis-associated biomarkers of HCM, with the potential to reveal the development and pathogenesis of HCM and could be potential therapeutic targets.

Prediction of worsening heart failure in hypertrophic cardiomyopathy using plasma proteomics

OBJECTIVE

Heart failure (HF) is one of the most common and lifestyle-limiting complications of hypertrophic cardiomyopathy (HCM). Prediction of worsening HF using clinical measures alone remains limited. Moreover, the mechanisms by which patients with HCM develop worsening HF have not been elucidated. Therefore, the aim of this study was to develop a plasma proteomics-based model to predict worsening HF among patients with HCM and to identify signalling pathways that are differentially regulated in those who subsequently develop worsening HF.

METHODS

In this multi-centre, prospective cohort study of 389 patients with HCM, plasma proteomics profiling of 4986 proteins was performed at enrolment. A proteomics-based random forest model was developed to predict worsening HF using data from one institution (training set, n=268). This model was externally validated in patients from a different institution (test set, n=121). Pathway analysis of proteins significantly dysregulated in patients who subsequently developed worsening HF compared with those who did not was executed, using a false discovery rate (FDR) threshold of <0.001.

RESULTS

Using the 11-protein proteomics-based model derived from the training set, the area under the receiver-operating characteristic curve to predict worsening HF was 0.87 (95% CI: 0.76 to 0.98) in the test set. Pathway analysis revealed that the Ras-MAPK pathway (FDR<0.00001) and related pathways were dysregulated in patients who subsequently developed worsening HF.

CONCLUSIONS

The present study with comprehensive plasma proteomics profiling demonstrated a high accuracy to predict worsening HF in patients with HCM and identified the Ras-MAPK and related signalling pathways as potential underlying mechanisms.

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.

Prognostic and Safety Implications of Renin-Angiotensin-Aldosterone System Inhibitors in Hypertrophic Cardiomyopathy: A Real-World Observation Over 2,000 Patients

BACKGROUND AND OBJECTIVES

The prognostic or safety implication of renin-angiotensin-aldosterone system inhibitors (RASi) in hypertrophic cardiomyopathy (HCM) are not well established, mainly due to concerns regarding left ventricular outflow tract (LVOT) obstruction aggravation. We investigated the implications of RASi in a sizable number of HCM patients.

METHODS

We enrolled 2,104 consecutive patients diagnosed with HCM in 2 tertiary university hospitals and followed up for five years. RASi use was defined as the administration of RASi after diagnostic confirmation of HCM. The primary and secondary outcomes were all-cause mortality and hospitalization for heart failure (HHF).

RESULTS

RASi were prescribed to 762 patients (36.2%). During a median follow-up of 48.1 months, 112 patients (5.3%) died, and 94 patients (4.5%) experienced HHF. Patients using RASi had less favorable baseline characteristics than those not using RASi, such as older age, more frequent history of comorbidities, and lower ejection fraction. Nonetheless, there was no difference in clinical outcomes between patients with and without RASi use (log-rank p=0.368 for all-cause mortality and log-rank p=0.443 for HHF). In multivariable analysis, patients taking RASi showed a comparable risk of all-cause mortality (hazard ratio [HR], 0.70, 95% confidence interval [CI], 0.43-1.14, p=0.150) and HHF (HR, 1.03, 95% CI, 0.63-1.70, p=0.900). In the subgroup analysis, there was no significant interaction of RASi use between subgroups stratified by LVOT obstruction, left ventricular (LV) ejection fraction, or maximal LV wall thickness.

CONCLUSIONS

RASi use was not associated with worse clinical outcomes. It might be safely administered in patients with HCM if clinically indicated.

Proteomic and phosphoproteomic analyses of myectomy tissue reveals difference between sarcomeric and genotype-negative hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is a genetically heterogenous condition with about half of cases remaining genetically elusive or non-genetic in origin. HCM patients with a positive genetic test (HCMSarc) present earlier and with more severe disease than those with a negative genetic test (HCMNeg). We hypothesized these differences may be due to and/or reflect proteomic and phosphoproteomic differences between the two groups. TMT-labeled mass spectrometry was performed on 15 HCMSarc, 8 HCMNeg, and 7 control samples. There were 243 proteins differentially expressed and 257 proteins differentially phosphorylated between HCMSarc and HCMNeg. About 90% of pathways altered between genotypes were in disease-related pathways and HCMSarc showed enhanced proteomic and phosphoproteomic alterations in these pathways. Thus, we show HCMSarc has enhanced proteomic and phosphoproteomic dysregulation observed which may contribute to the more severe disease phenotype.

Inflammation across the spectrum of hypertrophic cardiac phenotypes

The hypertrophic cardiomyopathy phenotype encompasses a heterogeneous spectrum of genetic and acquired diseases characterized by the presence of left ventricular hypertrophy in the absence of abnormal cardiac loading conditions. This "umbrella diagnosis" includes the "classic" hypertrophic cardiomyopathy (HCM), due to sarcomere protein gene mutations, and its phenocopies caused by intra- or extracellular deposits, such as Fabry disease (FD) and cardiac amyloidosis (CA). All these conditions share a wide phenotypic variability which results from the combination of genetic and environmental factors and whose pathogenic mediators are poorly understood so far. Accumulating evidence suggests that inflammation plays a critical role in a broad spectrum of cardiovascular conditions, including cardiomyopathies. Indeed, inflammation can trigger molecular pathways which contribute to cardiomyocyte hypertrophy and dysfunction, extracellular matrix accumulation, and microvascular dysfunction. Growing evidence suggests that systemic inflammation is a possible key pathophysiologic process potentially involved in the pathogenesis of cardiac disease progression, influencing the severity of the phenotype and clinical outcome, including heart failure. In this review, we summarize current knowledge regarding the prevalence, clinical significance, and potential therapeutic implications of inflammation in HCM and two of its most important phenocopies, FD and CA.

Multi-Omics Profiling of Hypertrophic Cardiomyopathy Reveals Altered Mechanisms in Mitochondrial Dynamics and Excitation-Contraction Coupling

Hypertrophic cardiomyopathy is one of the most common inherited cardiomyopathies and a leading cause of sudden cardiac death in young adults. Despite profound insights into the genetics, there is imperfect correlation between mutation and clinical prognosis, suggesting complex molecular cascades driving pathogenesis. To investigate this, we performed an integrated quantitative multi-omics (proteomic, phosphoproteomic, and metabolomic) analysis to illuminate the early and direct consequences of mutations in myosin heavy chain in engineered human induced pluripotent stem-cell-derived cardiomyocytes relative to late-stage disease using patient myectomies. We captured hundreds of differential features, which map to distinct molecular mechanisms modulating mitochondrial homeostasis at the earliest stages of pathobiology, as well as stage-specific metabolic and excitation-coupling maladaptation. Collectively, this study fills in gaps from previous studies by expanding knowledge of the initial responses to mutations that protect cells against the early stress prior to contractile dysfunction and overt disease.

Dysfunctional network of hub genes in hypertrophic cardiomyopathy patients

BACKGROUND

Considering it is one of the major causes of sudden cardiac arrest, the proper management of hypertrophic cardiomyopathy (HCM) is essential. However, efficient treatment options for this disease are still lacking. The discovery of HCM-associated hub genes may help in diagnosis and offer a reliable tool for developing effective therapeutic strategies.

METHODS

We examined HCM-based gene expression datasets (GSE36961) from the Gene Expression Omnibus (GEO) database for the identification of differentially expressed genes (DEGs), PPI network development, module screening, and shortlisting of hub genes via GEOR2, STRING, and Cytoscape. Moreover, we also used another HCM-based gene expression dataset (GSE32453) for the expression validation of hub genes. Following this, we constructed the lncRNA-cricRNA-miRNA-mRNA regulatory network after retrieving information from the miRTarBase, miRDB, and MiRcode databases. Finally, we used DAVID to perform functional and pathway analysis of the hub genes.

RESULTS

From GSE36961, a total of the 262 most significant DEGs, including 162 down-regulated and 76 up-regulated, were identified between HCM patients and normal individuals. Among these DEGs, a total of 10 significantly down-regulated DEGs, including cluster of differentiation 14 (CD14), beta2 Integrin Gene (ITGB2), C1q subcomponent subunit B (C1QB), Cluster of Differentiation 163 (CD163), Hematopoietic Cell-Specific Lyn Substrate 1 (HCLS1), Arachidonate 5-Lipoxygenase Activating Protein (ALOX5AP), Pleckstrin (PLEK), Complement C1q C Chain (C1QC), Fc fragment Of IgE receptor Ig (FCER1G), and tyrosine kinase binding protein (TYROBP), were shortlisted as the hub genes. Pathway enrichment analysis showed that the identified hub genes were involved in the dysregulation of some diverse pathways in HCM patients. Such as, Pertussis, Complement and coagulation cascade, Legnionellosis, Asthma, Staphylococcus aureus infection, etc. Lastly, we also explored hub genes' regulatory 2 MicroRNAs (miRNAs, has-mir-7-5p and has-mir-27a-3p), one Long non-coding RNAs (lncRNA, OIP5-AS1-201), and one Circular RNA (cricRNA, CDR1as) via lncRNA-cricRNA-miRNA-mRNA regulatory network.

CONCLUSION

Our study revealed that ten hub genes (CD14, ITGB2, C1QB, CD163, HCLS1, ALOX5AP, PLEK, C1QC, FCER1G, and TYROBP) are involved in the development and progression of HCM. These genes can potentially be used as biomarkers and therapeutic targets for HCM patients.

Circulating Biomarkers in Hypertrophic Cardiomyopathy

Hypertrophic cardiomyopathy is the most common genetic heart disease. Biomarkers, molecules measurable in the blood, could inform the clinician by aiding in diagnosis, directing treatment, and predicting outcomes. We present an updated review of circulating biomarkers in hypertrophic cardiomyopathy representing key pathologic processes including wall stretch, myocardial necrosis, fibrosis, inflammation, hypertrophy, and endothelial dysfunction, in addition to their clinical significance.

Prediction of Major Adverse Cardiovascular Events in Patients With Hypertrophic Cardiomyopathy Using Proteomics Profiling

BACKGROUND

Hypertrophic cardiomyopathy often causes major adverse cardiovascular events (MACE), for example, arrhythmias, stroke, heart failure, and sudden cardiac death. Currently, there are no models available to predict MACE. Furthermore, it remains unclear which signaling pathways mediate MACE. Therefore, we aimed to prospectively determine protein biomarkers that predict MACE in hypertrophic cardiomyopathy and to identify signaling pathways differentially regulated in patients who subsequently develop MACE.

METHODS

In this multi-centre prospective cohort study of patients with hypertrophic cardiomyopathy, we conducted plasma proteomics profiling of 4979 proteins upon enrollment. We developed a proteomics-based model to predict MACE using data from one institution (training set). We tested the predictive ability in independent samples from the other institution (test set) and performed time-to-event analysis. Additionally, we executed pathway analysis of predictive proteins using a false discovery rate threshold of <0.001.

RESULTS

The study included 245 patients (n=174 in the training set and n=71 in the test set). Using the proteomics-based model to predict MACE derived from the training set, the area under the receiver-operating-characteristic curve was 0.81 (95% CI, 0.68-0.93) in the test set. In the test set, the high-risk group determined by the proteomics-based predictive model had a significantly higher rate of developing MACE (hazard ratio, 13.6 [95% CI, 1.7-107]; P=0.01). The Ras-MAPK (mitogen-activated protein kinase) pathway was upregulated in patients who subsequently developed MACE (false discovery rate<1.0×10-7). Pathways involved in inflammation and fibrosis-for example, the TGF (transforming growth factor)-β pathway-were also upregulated.

CONCLUSIONS

This study serves as the first to demonstrate the ability of proteomics profiling to predict MACE in hypertrophic cardiomyopathy, exhibiting both novel (eg, Ras-MAPK) and known (eg, TGF-β) pathways differentially regulated in patients who subsequently experience MACE.

Proteomics profiling reveals a distinct high-risk molecular subtype of hypertrophic cardiomyopathy

OBJECTIVE

Hypertrophic cardiomyopathy (HCM) is a heterogeneous disease, likely encompassing several subtypes of disease with distinct biological mechanisms (ie, molecular subtypes). Current models based solely on clinical data have yielded limited accuracy in predicting the risk of major adverse cardiovascular events (MACE). Our aim in this study was to derive molecular subtypes in our multicentre prospective cohort of patients with HCM using proteomics profiling and to examine their longitudinal associations with MACE.

METHODS

We applied unsupervised machine learning methods to plasma proteomics profiling data of 1681 proteins from 258 patients with HCM who were prospectively followed for a median of 2.8 years. The primary outcome was MACE, defined as a composite of arrhythmia, heart failure, stroke and sudden cardiac death.

RESULTS

We identified four molecular subtypes of HCM. Time-to-event analysis revealed significant differences in MACE-free survival among the four molecular subtypes (plogrank=0.007). Compared with the reference group with the lowest risk of MACE (molecular subtype A), patients in molecular subtype D had a higher risk of subsequently developing MACE, with an HR of 3.41 (95% CI 1.54 to 7.55, p=0.003). Pathway analysis of proteins differentially regulated in molecular subtype D demonstrated an upregulation of the Ras/mitogen-activated protein kinase and associated pathways, as well as pathways related to inflammation and fibrosis (eg, transforming growth factor-β pathway).

CONCLUSIONS

Our prospective plasma proteomics study not only exhibited the presence of HCM molecular subtypes but also identified pathobiological mechanisms associated with a distinct high-risk subtype of HCM.

Prospects for remodeling the hypertrophic heart with myosin modulators

Hypertrophic cardiomyopathy (HCM) is a complex but relatively common genetic disease that usually arises from pathogenic variants that disrupt sarcomere function and lead to variable structural, hypertrophic, and fibrotic remodeling of the heart which result in substantial adverse clinical outcomes including arrhythmias, heart failure, and sudden cardiac death. HCM has had few effective treatments with the potential to ameliorate disease progression until the recent advent of inhibitory myosin modulators like mavacamten. Preclinical investigations and clinical trials utilizing this treatment targeted to this specific pathophysiological mechanism of sarcomere hypercontractility in HCM have confirmed that myosin modulators can alter disease expression and attenuate hypertrophic remodeling. Here, we summarize the state of hypertrophic remodeling and consider the arguments for and against salutary HCM disease modification using targeted myosin modulators. Further, we consider critical unanswered questions for future investigative and therapeutic avenues in HCM disease modification. We are at the precipice of a new era in understanding and treating HCM, with the potential to target agents toward modifying disease expression and natural history of this most common inherited disease of the heart.

Blood-based biomarkers for the prediction of hypertrophic cardiomyopathy prognosis: a systematic review and meta-analysis

AIMS

Hypertrophic cardiomyopathy (HCM) is the most prevalent monogenic heart disease. HCM is an important cause of sudden cardiac death and may also lead to outflow tract obstruction and heart failure. Disease severity is highly variable and risk stratification remains limited. Therefore, we aimed to review current knowledge of prognostic blood-based biomarkers in HCM.

METHODS AND RESULTS

A systematic literature search was performed on PubMed, Embase, and the Cochrane library to identify studies assessing plasma or serum biomarkers for outcomes involving malignant ventricular arrhythmia, outflow tract obstruction, and heart failure. Risk of bias was assessed using the QUIPS tool. Meta-analyses were performed using the random effects method. A total of 26 unique cohort studies assessing 42 biomarkers were identified. Overall risk of bias was moderate. Thirty-two biomarkers were significantly associated to an HCM outcome in at least one study (nine biomarkers in at least two studies). In pooled analyses, cardiovascular mortality was predicted by N-terminal prohormone of brain natriuretic peptide (hazard ratio [HR] 5.38 per log[pg/mL], 95% confidence interval [CI] 2.07-14.03, P < 0.001, I2  = 0%) and high-sensitivity C-reactive protein (HR 1.30 per μg/mL, 95% CI 1.00-1.68, P = 0.05, I2  = 78%), all-cause mortality by low-density lipoprotein cholesterol (HR 0.63 per μmol/mL, 95% CI 0.49-0.80, P < 0.001, I2  = 0%), and a combined congestive heart failure, malignant ventricular arrhythmia, and stroke outcome by high-sensitivity cardiac troponin T (pooled HR 4.19 for ≥0.014 ng/mL, 95% CI 2.22-7.88, P < 0.001, I2  = 0%). Quality of evidence was low-moderate.

CONCLUSIONS

Several blood-based biomarkers were identified as predictors of HCM outcomes. Additional studies are required to validate their prognostic utility within current risk stratification models.

Hypertrophic cardiomyopathy: an up-to-date snapshot of the clinical drug development pipeline

INTRODUCTION

Hypertrophic cardiomyopathy (HCM) is a complex cardiac disease with highly variable phenotypic expression and clinical course most often caused by sarcomeric gene mutations resulting in left ventricular hypertrophy, fibrosis, hypercontractility, and diastolic dysfunction. For almost 60 years, HCM has remained an orphan disease and still lacks a disease-specific treatment.

AREAS COVERED

This review summarizes recent preclinical and clinical trials with repurposed drugs and new emerging pharmacological and gene-based therapies for the treatment of HCM.

EXPERT OPINION

The off-label drugs routinely used alleviate symptoms but do not target the core pathophysiology of HCM or prevent or revert the phenotype. Recent advances in the genetics and pathophysiology of HCM led to the development of cardiac myosin adenosine triphosphatase inhibitors specifically directed to counteract the hypercontractility associated with HCM-causing mutations. Mavacamten, the first drug specifically developed for HCM successfully tested in a phase 3 trial, represents the major advance for the treatment of HCM. This opens new horizons for the development of novel drugs targeting HCM molecular substrates which hopefully modify the natural history of the disease. The role of current drugs in development and genetic-based approaches for the treatment of HCM are also discussed.

Comprehensive Proteomics Profiling Identifies Patients With Late Gadolinium Enhancement on Cardiac Magnetic Resonance Imaging in the Hypertrophic Cardiomyopathy Population

Introduction

In hypertrophic cardiomyopathy (HCM), late gadolinium enhancement (LGE) on cardiac magnetic resonance imaging (CMR) represents myocardial fibrosis and is associated with sudden cardiac death. However, CMR requires particular expertise and is expensive and time-consuming. Therefore, it is important to specify patients with a high pre-test probability of having LGE as the utility of CMR is higher in such cases. The objective was to determine whether plasma proteomics profiling can distinguish patients with and without LGE on CMR in the HCM population.

Materials and Methods

We performed a multicenter case-control (LGE vs. no LGE) study of 147 patients with HCM. We performed plasma proteomics profiling of 4,979 proteins. Using the 17 most discriminant proteins, we performed logistic regression analysis with elastic net regularization to develop a discrimination model with data from one institution (the training set; n = 111) and tested the discriminative ability in independent samples from the other institution (the test set; n = 36). We calculated the area under the receiver-operating-characteristic curve (AUC), sensitivity, and specificity.

Results

Overall, 82 of the 147 patients (56%) had LGE on CMR. The AUC of the 17-protein model was 0.83 (95% confidence interval [CI], 0.75–0.90) in the training set and 0.71 in the independent test set for validation (95% CI, 0.54–0.88). The sensitivity of the training model was 0.72 (95% CI, 0.61–0.83) and the specificity was 0.78 (95% CI, 0.66–0.90). The sensitivity was 0.71 (95% CI, 0.49–0.92) and the specificity was 0.74 (95% CI, 0.54–0.93) in the test set. Based on the discrimination model derived from the training set, patients in the test set who had high probability of having LGE had a significantly higher odds of having LGE compared to those who had low probability (odds ratio 29.6; 95% CI, 1.6–948.5; p = 0.03).

Conclusions

In this multi-center case-control study of patients with HCM, comprehensive proteomics profiling of 4,979 proteins demonstrated a high discriminative ability to distinguish patients with and without LGE. By identifying patients with a high pretest probability of having LGE, the present study serves as the first step to establishing a panel of circulating protein biomarkers to better inform clinical decisions regarding CMR utilization.

Pediatric Hypertrophic Cardiomyopathy: Exploring the Genotype-Phenotype Association

Pediatric hypertrophic cardiomyopathy (HCM) is the most common form of cardiomyopathy in children and a leading cause of sudden cardiac death. Yet, the association between genotype variation, phenotype expression, and adverse events in pediatric HCM has not been fully elucidated. Although the literature on this topic is evolving in adult HCM, the evidence in children is lacking. Solidifying our understanding of this relationship could improve risk stratification as well as improve our comprehension of the underlying pathophysiological characteristics of pediatric HCM. In this state-of-the-art review, we examine the current literature on genetic variations in HCM and their association with outcomes in children, discuss the current approaches to identifying cardiovascular phenotypes in pediatric HCM, and explore possible avenues that could improve sudden cardiac death risk assessment.

Pathophysiological pathways related to high plasma GDF-15 concentrations in patients with heart failure

AIMS

Elevated concentrations of Growth Differentiation factor 15 (GDF-15) in patients with heart failure (HF) have been consistently associated with worse clinical outcomes, but what disease mechanisms high GDF-15 concentrations represent remains unclear. Here, we aim to identify activated pathophysiological pathways related to elevated GDF-15 expression in patients with HF.

METHODS AND RESULTS

In 2279 patients with HF, we measured circulating levels of 363 biomarkers. Then, we performed a pathway over-representation analysis to identify key biological pathways between patients in the highest and lowest GDF-15 concentration quartiles. Data were validated in an independent cohort of 1705 patients with HF. In both cohorts, the strongest up-regulated biomarkers in those with high GDF-15 were fibroblast growth factor 23 (FGF-23), death receptor 5 (TRAIL-R2), WNT1-inducible-signaling pathway protein 1 (WISP-1), TNF Receptor Superfamily Member 11a (TNFRSF11A), leukocyte immunoglobulin-like receptor subfamily B member 4 (LILRB4), and Trefoil Factor 3 (TFF3). Pathway over-representation analysis revealed that high GDF-15 patients had increased activity of pathways related to inflammatory processes, notably positive regulation of chemokine production; response to interleukin 6 (IL-6); tumour necrosis factor (TNF) and death receptor activity; and positive regulation of T cell differentiation and inflammatory response. Furthermore, we found pathways involved in regulation of insulin-like growth factor (IGF) receptor signalling and regulatory pathways of tissue, bones, and branching structures. GDF-15 quartiles significantly predicted all-cause mortality and HF hospitalization.

CONCLUSION

Patients with HF and high plasma concentrations of GDF-15 are characterized by increased activation of inflammatory pathways and pathways related to IGF-1 regulation and bone/tissue remodelling.

Transforming growth factor-β in myocardial disease

Transforming growth factor-β (TGFβ) isoforms are upregulated and activated in myocardial diseases and have an important role in cardiac repair and remodelling, regulating the phenotype and function of cardiomyocytes, fibroblasts, immune cells and vascular cells. Cardiac injury triggers the generation of bioactive TGFβ from latent stores, through mechanisms involving proteases, integrins and specialized extracellular matrix (ECM) proteins. Activated TGFβ signals through the SMAD intracellular effectors or through non-SMAD cascades. In the infarcted heart, the anti-inflammatory and fibroblast-activating actions of TGFβ have an important role in repair; however, excessive or prolonged TGFβ signalling accentuates adverse remodelling, contributing to cardiac dysfunction. Cardiac pressure overload also activates TGFβ cascades, which initially can have a protective role, promoting an ECM-preserving phenotype in fibroblasts and preventing the generation of injurious, pro-inflammatory ECM fragments. However, prolonged and overactive TGFβ signalling in pressure-overloaded cardiomyocytes and fibroblasts can promote cardiac fibrosis and dysfunction. In the atria, TGFβ-mediated fibrosis can contribute to the pathogenic substrate for atrial fibrillation. Overactive or dysregulated TGFβ responses have also been implicated in cardiac ageing and in the pathogenesis of diabetic, genetic and inflammatory cardiomyopathies. This Review summarizes the current evidence on the role of TGFβ signalling in myocardial diseases, focusing on cellular targets and molecular mechanisms, and discussing challenges and opportunities for therapeutic translation.

Identification and Verification of Feature Immune-Related Genes in Patients With Hypertrophic Cardiomyopathy Based on Bioinformatics Analyses

Objective: To identify feature immune-related genes (IRGs) in patients with hypertrophic cardiomyopathy (HCM) and verify their ability to diagnose HCM.

Methods: The GSE160997 dataset on cardiac tissue from 18 HCM patients and 5 controls was downloaded from the Gene Expression Omnibus database. A false discovery rate <0.05 and |log2 fold change| >1 were the filters applied to identify the differentially expressed genes (DEGs). The differentially expressed IRGs were the intersection results between the DEGs and an IRG dataset from the IMMPORT database. The protein-protein interaction network of differentially expressed IRGs was constructed, and the top 20 hub genes with the most adjacent nodes in the network were selected. The least absolute shrinkage and selection operator regression algorithm and a random forest algorithm were used to identify the feature IRGs as biomarkers that were then verified against GSE36961.

Results: A total of 1079 DEGs were identified in GSE160997. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analyses indicated that immune-related mechanisms play an important role in the pathogenesis of HCM. A total of 121 differentially expressed IRGs were identified, and 5 feature IRGs were selected, 4 of which were confirmed as potential biomarkers of HCM by external verification with excellent discrimination ability. A diagnosis model of HCM based on the four feature IRGs was developed and visualized as a nomogram with a C-index of 0.925 (95% confidence interval 0.869–0.981).

Conclusion: Our study identified four feature IRGs as biomarkers for the diagnosis of HCM, offering an innovative perspective of the underlying immune-related pathological molecular mechanisms.

Pathogenic Mechanisms of Hypertrophic Cardiomyopathy beyond Sarcomere Dysfunction

Hypertrophic cardiomyopathy (HCM) is the most common inherited cardiovascular disorder, affecting 1 in 500 people in the general population. Although characterized by asymmetric left ventricular hypertrophy, cardiomyocyte disarray, and cardiac fibrosis, HCM is in fact a highly complex disease with heterogenous clinical presentation, onset, and complications. While HCM is generally accepted as a disease of the sarcomere, variable penetrance in families with identical genetic mutations challenges the monogenic origin of HCM and instead implies a multifactorial cause. Furthermore, large-scale genome sequencing studies revealed that many genes previously reported as causative of HCM in fact have little or no evidence of disease association. These findings thus call for a re-evaluation of the sarcomere-centered view of HCM pathogenesis. Here, we summarize our current understanding of sarcomere-independent mechanisms of cardiomyocyte hypertrophy, highlight the role of extracellular signals in cardiac fibrosis, and propose an alternative but integrated model of HCM pathogenesis.