Daily Cardiology Research Analysis
Three impactful cardiology papers stood out: a phase 3 randomized trial showing aficamten outperforms metoprolol across multiple clinically meaningful domains in obstructive hypertrophic cardiomyopathy; a large-scale, semi-supervised deep learning pipeline enabling reliable, vendor-agnostic pediatric echocardiographic strain analysis with strong predictive utility; and a mechanistic study linking KLHL24 gain-of-function to intermediate filament degradation, mitochondrial dysfunction, and fibrosi
Summary
Three impactful cardiology papers stood out: a phase 3 randomized trial showing aficamten outperforms metoprolol across multiple clinically meaningful domains in obstructive hypertrophic cardiomyopathy; a large-scale, semi-supervised deep learning pipeline enabling reliable, vendor-agnostic pediatric echocardiographic strain analysis with strong predictive utility; and a mechanistic study linking KLHL24 gain-of-function to intermediate filament degradation, mitochondrial dysfunction, and fibrosis in cardiomyopathy.
Research Themes
- Targeted myosin inhibition redefining first-line therapy in obstructive HCM
- AI-enabled, vendor-agnostic echocardiographic strain for early pediatric cardiac dysfunction detection
- Ubiquitin–proteasome-driven cytoskeletal and mitochondrial mechanisms in cardiomyopathy
Selected Articles
1. Aficamten in Obstructive Hypertrophic Cardiomyopathy: A Multidomain, Patient-Level Analysis of the MAPLE-HCM Trial.
In a randomized, active-comparator phase 3 trial, aficamten monotherapy achieved superior, rapid improvements versus metoprolol across multiple clinically relevant endpoints in obstructive HCM, including LVOT gradients, symptoms (NYHA), quality of life (KCCQ-CSS), NT-proBNP, and peak VO2. These patient-level, multidomain gains support aficamten as a potential monotherapy standard for symptomatic oHCM.
Impact: This head-to-head trial challenges decades of beta-blocker first-line practice by demonstrating multidomain superiority of a targeted myosin inhibitor. It directly informs therapeutic guidelines and everyday management of oHCM.
Clinical Implications: Aficamten may be considered as frontline monotherapy for symptomatic oHCM, with titration guided by vitals and echocardiography to reduce LVOT obstruction and improve functional status and quality of life.
Key Findings
- Aficamten achieved greater rates of target LVOT gradient reduction at rest and with Valsalva than metoprolol.
- Patient-centric outcomes improved more with aficamten, including ≥1 NYHA class improvement and ≥10-point KCCQ-CSS gains.
- Biomarker and exercise capacity gains favored aficamten, including ≥50% NT-proBNP reduction and ≥1.0 mL/kg/min increase in peak VO2.
- Benefits were rapid and observed across baseline subgroups.
Methodological Strengths
- Randomized, active-comparator phase 3 design with prespecified multidomain endpoints
- Dose titration guided by objective echocardiographic and vital sign criteria; trial registered (NCT05767346)
Limitations
- Follow-up duration and detailed safety outcomes are not specified in the abstract; long-term durability is unknown
- Comparison limited to metoprolol; broader comparisons to other standard therapies are needed
Future Directions: Longer-term outcomes, safety profiling, and head-to-head comparisons with other pharmacologic options (e.g., mavacamten, disopyramide) and device or surgical strategies will clarify positioning in oHCM care.
BACKGROUND: For >60 years, beta-blockers have been first-line therapy for symptomatic obstructive hypertrophic cardiomyopathy (oHCM), although limited data support this recommendation. The MAPLE-HCM trial showed greater improvement in exercise capacity and secondary endpoints for aficamten monotherapy vs metoprolol monotherapy. OBJECTIVES: The purpose of this study was to evaluate the effects of aficamten vs metoprolol across multiple clinically relevant and patient-centric measures of disease burden in oHCM. METHODS: Patients with oHCM and left ventricular outflow tract gradient (LVOT-G) ≥30 mm Hg at rest and/or ≥50 mm Hg with Valsalva were randomly assigned to aficamten (n = 88) or metoprolol (n = 87). Dose titration was based on vital signs and echocardiograms. Assessment of clinical response by treatment arm was based on improvement in multiple parameters reflecting oHCM disease burden: LVOT-G <30 mm Hg at rest and <50 mm Hg with Valsalva; ≥1 class improvement in NYHA functional class and/or ≥10-point improvement in Kansas City Cardiomyopathy Questionnaire-Clinical Summary Score (KCCQ-CSS); ≥50% reduction in N-terminal pro-B-type natriuretic peptide; ≥1.0 mL/kg/min increase in peak oxygen consumption (pVO RESULTS: Baseline characteristics were similar for both treatment groups. For the overall cohort, mean age was 58 ± 13.2 years; 73 (42%) were women, 103 (70%) were in NYHA functional class II and 52 (30%) in class III, mean pVO CONCLUSIONS: In patients with symptomatic oHCM, aficamten monotherapy led to superior and rapid treatment benefits across several clinically relevant outcome measures of disease burden compared with metoprolol. These observations support the emerging role of aficamten as monotherapy for oHCM. (Phase 3 Trial to Evaluate the Efficacy and Safety of Aficamten Compared to Metoprolol Succinate in Adults With Symptomatic oHCM [MAPLE-HCM]; NCT05767346).
2. Digital profile of children's hearts: automated echocardiogram strain analysis facilitates earlier detection of cardiac dysfunction.
A semi-supervised, vendor-agnostic deep learning pipeline delivered accurate and generalizable pediatric echocardiographic strain estimates with MAEs near 2% and strong correlations. Automated strain and motion features enabled high AUCs for predicting cardio-oncology dysfunction, late gadolinium enhancement, LVEF decline (outperforming manual strain), and myocardial infarction detection.
Impact: This study establishes a scalable, generalizable framework for pediatric strain analysis that can standardize measurements across vendors and image qualities while demonstrating strong clinical predictive utility.
Clinical Implications: Automated, robust pediatric strain analysis can enable earlier detection of subclinical dysfunction (e.g., cardio-oncology surveillance), support risk stratification, and reduce inter-operator variability across centers.
Key Findings
- Motion-Echo achieved MAEs of 2.099% (GLS) and 2.665% (GCS) with correlations of 0.799 and 0.781, respectively.
- Automated strain predicted cancer therapy-related cardiac dysfunction with AUC 0.906 and detected LGE with AUC 0.782.
- Forecasting LVEF decline outperformed manual strain (DeLong P < .001); motion flows improved MI detection to AUC 0.952.
- Framework trained on >22,000 echocardiograms across vendors and image qualities using minimal manual annotations.
Methodological Strengths
- Large, heterogeneous dataset with semi-supervised learning minimizing annotation burden
- Multiple downstream clinical validations demonstrating external utility across tasks
Limitations
- Retrospective design; prospective impact on clinical decision-making not yet demonstrated
- Generalizability to additional institutions and imaging protocols requires further validation
Future Directions: Prospective, multicenter trials to assess clinical workflow integration, patient outcomes, fairness across subpopulations, and regulatory-grade validation.
BACKGROUND AND AIMS: Paediatric myocardial strain analysis through echocardiography is often characterized by high variance and limited precision, highlighting the need for a standardized and vendor-agnostic approach applicable for diverse image qualities and populations, which could enhance cardiac function evaluation and enable early detection of cardiac impairment. METHODS: The Motion-Echo system was proposed, a semi-supervised deep learning framework built on 11 096 paediatric and 11 297 adult echocardiograms spanning diverse image qualities and vendors. It integrated context compensation and motion estimation modules for temporally coherent segmentation, myocardial motion estimation, and global strain assessment with minimal manual annotations. Clinical utility was further evaluated through downstream applications. RESULTS: Motion-Echo achieved mean absolute errors of 2.099% [95% confidence interval (CI) 1.803-2.401] and 2.665% (95% CI 2.339-3.026) for global longitudinal and circumferential strain assessments, with Pearson correlation coefficients of 0.799 (95% CI 0.715-0.871) and 0.781 (95% CI 0.687-0.844), respectively. To validate the clinical utility, automated strain values achieved an area under the curve (AUC) of 0.906 (95% CI 0.816-0.981) for cancer therapy-related cardiac dysfunction risk prediction. For late gadolinium enhancement detection, automated global longitudinal strain reached an AUC of 0.782 (95% CI 0.666-0.885). For left ventricular ejection fraction decline forecasting, the system outperformed manual strain values (DeLong P < .001). In addition, incorporating estimated motion flows yielded a remarkable AUC improvement to 0.952 (95% CI 0.917-0.980) for myocardial infarction detection. CONCLUSIONS: Leveraging a large-scale paediatric dataset, Motion-Echo provided a reliable and generalizable framework for myocardial strain analysis, demonstrating potential to facilitate earlier detection of cardiac dysfunction and generate digital cardiac function profiles of children.
3. KLHL24 mutation drives intermediate filament degradation, mitochondrial dysfunction and fibrosis in heart failure patients.
Across patient heart tissue and patient-specific hiPSC-derived cardiomyocytes, KLHL24 gain-of-function drives proteasome-dependent degradation of multiple intermediate filament proteins, mitochondrial mislocalization with enhanced mitophagy, reduced PKA activity, sarcomere shortening, and an early fibrotic signature. These convergent data establish a unifying mechanism for cardiomyopathy in KLHL24 mutation carriers.
Impact: This work links a ubiquitin–proteasome adaptor to multi-lineage cytoskeletal degradation and mitochondrial pathology in human cardiomyopathy, expanding therapeutic hypotheses beyond desmin to broader intermediate filaments and organelle quality control.
Clinical Implications: Genetic screening for KLHL24 variants in epidermolysis bullosa and unexplained cardiomyopathy may be warranted; therapeutic exploration could include proteasome modulation, stabilization of intermediate filaments, or mitochondrial protection strategies.
Key Findings
- Proteomics in patient LV tissue and patient-derived hiPSC-CMs showed reductions in multiple intermediate filament proteins (desmin, synemin, vimentin) and early fibrotic signatures.
- KLHL24 gain-of-function increased proteasomal activity, caused mitochondrial mislocalization with elevated mitophagy, reduced PKA activity, and induced sarcomere shortening in cardiomyocytes.
- Phenotypes were reproduced across cardiac cell types, including cardiomyocytes and fibroblasts, and aligned between in vitro models and end-stage explants.
Methodological Strengths
- Integrated multi-omic and multi-model approach combining human tissue proteomics with patient-specific hiPSC-derived cardiac models
- Convergent validation using mass spectrometry, flow cytometry, immunofluorescence, and Western blot across cell types
Limitations
- Human cohort limited to two patients; lack of in vivo rescue experiments or therapeutic modulation
- hiPSC models may not capture hemodynamic and multicellular tissue architecture present in vivo
Future Directions: Define the KLHL24 substrate landscape, test proteostasis and mitochondrial-targeted therapies in preclinical models, and expand clinical cohorts to link genotype, proteomic signatures, and phenotype severity.
AIMS: A striking aspect of epidermolysis bullosa patients with a mutation in KLHL24 (KLHL24mut) is their life-threatening deterioration of heart function. KLHL24 is a component of the ubiquitin-proteasome system and acts as a substrate-specific adaptor protein for E3 ubiquitin ligase. KLHL24mut is thought to represent a gain-of-function mutation, with associated cardiac and skin pathologies arising from the excessive degradation of its target proteins. Although reduced desmin levels in cardiomyocytes (CMs) have already been documented, the potential involvement of additional mechanisms in KLHL24mut -driven heart pathology remains unexplored. METHODS AND RESULTS: We report on two patients with KLHL24mut who recently manifested heart failure. To gain insights into their physiopathology, we integrated clinical data with proteomic analyses of heart tissue as well as human induced pluripotent stem cell (hiPSC) models carrying KLHL24mut. Mass spectrometry analysis of CMs differentiated from patient-derived hiPSCs mirrored the proteomic profile of their corresponding left ventricle tissue samples. KLHL24mut resulted in a reduction of several intermediate filaments (IF), mitochondrial and muscle fibre proteins as well as the emergence of an early fibrotic signature. By utilising various hiPSC-derived cardiac models along with flow cytometry, immunofluorescence, and western blot analyses, we confirmed that the excessive proteasomal activity of endogenous KLHL24mut caused a decrease in levels of desmin, synemin and vimentin, IF proteins of CMs and cardiac fibroblasts. Moreover, KLHL24mut led to mitochondrial mislocalization and increased mitophagy, reduced PKA activity, and sarcomere shortening in CMs. CONCLUSION: The deterioration of heart function in patients with KLHL24mut is driven by excessive proteasome-dependent degradation of multiple IF proteins across various cardiac cell types. Monotypic hiPSC-derived CMs and end-stage patient-derived cardiac explants from patients exhibit similar features, uncovering early pathological mechanisms and identifying a list of potential novel KLHL24mut target proteins. Finally, our findings validate that hiPSC-derived CMs represent a relevant model for future studies.