Eric D. Adler

BACKGROUND: Conflicting evidence exists about whether sarcomeric hypertrophic cardiomyopathy (HCM) caused by genes encoding thin filament proteins ( TNNT2, TNNI3, ACTC, TPM1 , TNNC1 ; thin filament HCM) has a distinct clinical presentation and natural history from disease caused by the more commonly involved thick filament genes ( MYH7 , MYBPC3 , MYL2 , MYL3 ; thick filament HCM). METHODS: Retrospective analysis of the Sarcomeric Human Cardiomyopathy Registry. RESULTS: Four hundred eighty-eight patients with thin filament HCM were compared with 3494 patients with thick filament HCM. After controlling for age at diagnosis, sex, and proband status, thin filament HCM was associated with a higher risk of composite ventricular arrhythmias (hazard ratio, 1.48 [95% CI, 1.09–2.01]), cardiac arrest (hazard ratio, 2.02 [95% CI, 1.33–3.06]), and heart transplant or left ventricular assist device implantation (hazard ratio, 2.18 [95% CI, 1.3–3.65]). Younger age at diagnosis was associated with an increased risk for the ventricular arrhythmia composite outcome in thin and thick filament HCM (hazard ratio, 0.93 [95% CI, 0.91–0.94]; hazard ratio, 0.93 [95% CI, 0.93–0.94]; age reported as 5-year increment). Within specific thin filament genes, an increased risk of arrhythmic events or heart transplant/left ventricular assist device implantation was evident for variants in TNNT2 amino acids 92 to 94 (odds ratio versus other TNNT2 variants; odds ratio, 3.02 [95% CI, 1.17–7.49]) and TNNI3 amino acids 191 to 210 (odds ratio versus other TNNI3 variants; odds ratio, 3.5 [95% CI, 1.58–8.02]). CONCLUSIONS: Thin filament HCM seems to carry a higher risk for ventricular arrhythmias and advanced heart failure compared with thick filament HCM. Integrating gene-level and intragene-level information may improve risk stratification in patients with HCM.

Glycogen storage diseases (GSDs) are a heterogeneous group of rare and often under-recognized causes of inherited cardiomyopathy characterized by pathological glycogen or autophagic vacuole accumulation of debris within various tissues, including the heart. These diseases often present as phenocopies of sarcomeric hypertrophic cardiomyopathy, though they may also manifest with dilated or mixed phenotypes. Key GSDs with cardiomyopathy include Pompe disease (GSD IIa), Danon disease (IIb), Cori/Forbes disease (GSD III), Andersen disease (GSD IV), Tarui disease (GSD VII), phosphorylase kinase deficiency (GSD IX), glycogenin-1 deficiency (GSD XV), and PRKAG2 syndrome, each presenting unique clinical trajectories. Accurate diagnosis requires integration of clinical red flags, multimodality cardiac imaging, and electrocardiography, alongside definitive diagnostic tools like enzyme screening, genetic testing, and endomyocardial biopsy. There is a dearth of evidence regarding specific treatment of each unique GSD cardiomyopathy, but emerging therapeutics across the spectrum of GSDs aim to address this need. This review covers current knowledge on the spectrum of GSD-related cardiomyopathies, discussing pathophysiology, diagnosis, and evolving treatment strategies.

BACKGROUND: Although adeno-associated virus (AAV) gene-replacement therapy is a potentially transformative therapy for severe genetic diseases, its cardiac immunotoxicity may challenge broad clinical use. METHODS: Medical Literature Analysis and Retrieval System Online, Embase, and PubMed databases were searched from January 2005 to March 2025. Studies including patients treated with AAV-replacement therapy were deemed eligible. Prespecified items (type of vector, dose, timing, and clinical significance of the adverse event) were extracted by 2 independent observers. Random-effects models were fitted using restricted maximum likelihood estimation and the method of Hartung, Knapp, Sidik, and Jonkman (International Prospective Register of Systematic Reviews [PROSPERO]. VigiBase and the US Food and Drug Administration Adverse Event Reporting System were searched for the occurrence of myocarditis with commercially available AAV-replacement drugs. RESULTS: Eighty studies including 1939 human patients were analyzed. A total of 734 adverse events were reported over 2122 patient-years of pooled observation. Seventy-one cases of myocarditis were identified. The pooled incidence rate per 100 patient-years was 8.6 (95% CI, 5.8–10.7; I ² =63.2%). Events occurred in patients with Duchenne muscular dystrophy, spinal muscular atrophy, and X-linked myotubular myopathy, with recombinant AAVs and adeno-associated virus serotype 8. All received an intravenous dose >10 ¹³ vector genomes per kilogram body weight. Myocardial injury peaked in week 1 after injection (90% [95% CI, 85.7%–96.2%]; I ² =43.2%), whereas myocarditis occurred mostly after week 2 (55% [95% CI, 48.7%–65.2%]; I ² =33.1%), with no cases after the first month. Most myocarditis/myocardial injury did not have a relevant clinical impact (62, 87%), with only 8 (12%) cases having transient left ventricular dysfunction. The latter recovered during the follow-up. The only death occurred in the setting of cytokine-mediated capillary leak syndrome with cardiac dysfunction. Myocarditis occurred in relation to delandistrogene moxeparvovec (1/16 [6%]) and onasemnogene abeparvovec (14/217 [6%]) in the Food and Drug Administration Adverse Event Reporting System and VigiBase. CONCLUSIONS: Immune-mediated myocarditis/myocardial injury after systemic AAV gene therapy occurred in 1×10 ^{1 3} vector genomes per kilogram body weight, clustered in neuromuscular programs, and were associated with certain recombinant capsids/serotypes. These data support intensive early cardiac monitoring, cautious dose selection, and delivery strategies to minimize systemic exposure. REGISTRATION: URL: https://www.crd.york.ac.uk/PROSPERO/ ; Unique identifier: CRD420251046546).

BACKGROUND: No large registries of patients with acute eosinophilic myocarditis (EM) are available. However, EM is perceived as a cardiac disease with high mortality, affecting mainly young and middle-aged adults according to small series and case reports. Awareness of the clinical presentation, associated systemic conditions, treatments, and outcomes of this uncommon condition is an unmet need. METHODS: In this international, multicenter, retrospective cohort study, 53 centers screened 193 patients with histologically proven acute EM between 1992 and 2023. After the exclusion of patients with insufficient data (n=10), symptoms lasting >30 days (n=19), or histological diagnosis not confirmed after review (n=8), 156 patients were included. RESULTS: Median age at presentation was 48 years (first to third quartile, 34–59 years) with male predominance (67.3%), and only 2 were pediatric cases (≤16 years of age; 1.3%). The main signs and symptoms at presentation were dyspnea (75.6%), fever (61.3%), and chest pain (53.2%). Unexpectedly, peripheral eosinophilia was reported in only 57.4% of cases, with a median cell count of 630 eosinophils/μL. The median left ventricular ejection fraction at presentation was 32% (first to third quartile, 25%–48%). The disorders most frequently associated with EM were eosinophilic granulomatosis with polyangiitis (22.4% of cases) and hypersensitivity forms (14.1%). Idiopathic/undefined forms accounted for 44.9% of cases, and miscellaneous causes accounted for 18.6%. In-hospital death or need for heart transplantation (HTx) occurred in 23 patients (14.7%; 22 deaths and 1 HTx), despite 43.6% being treated with temporary mechanical circulatory support and 92.9% being treated with immunosuppressive agents. Estimated rates of death or HTx at 1 and 3 years were 19.0% and 23.8%. Increased age, decreased left ventricular ejection fraction on admission, and no immunosuppressive therapy during hospitalization were independent predictors of death or HTx. A nonsignificant higher occurrence of deaths or HTx was observed in the hypersensitivity form (46.1%) compared with the eosinophilic granulomatosis with polyangiitis–associated form (13.1%) at 3 years ( P =0.15). CONCLUSIONS: Acute EM can often present without peripheral eosinophilia, and rates of in-hospital and midterm mortality or HTx are high. Endomyocardial biopsy is required to reach the final diagnosis of EM because relying on peripheral eosinophilia can lead to missing diagnosis. In-hospital immunosuppression is associated with HTx-free survival, although tailored immunosuppressive therapies are needed to improve outcomes. REGISTRATION: URL: https://www.clinicaltrials.gov ; Unique identifier: NCT06447935.

Aims: Right ventricular (RV) function is a key factor in the diagnosis and prognosis of heart disease. However, current advanced computed tomography (CT)-based assessments rely on semi-automated segmentation of the RV blood pool and manual delineation of the RV free and septal wall boundaries. These steps are time-consuming and prone to inter- and intra-observer variability. Methods and results: We developed and evaluated a fully automated pipeline consisting of two deep learning methods to automate volumetric and regional strain analysis of the RV from contrast-enhanced, electrocardiogram (ECG)-gated cineCT images. The Right Heart Blood Segmenter (RHBS) is a 3D high-resolution configuration of nnU-Net to define the endocardial boundary, while the Right Ventricular Wall Labeler (RVWL) is a 3D point cloud-based deep learning method to label the free and septal walls. We trained our models using a diverse cohort of patients with different RV phenotypes and tested them in an independent cohort of patients with aortic stenosis undergoing TAVR. Our approach demonstrated high accuracy in both cross-validation and independent validation cohorts. RHBS and RVWL both yielded Dice scores of 0.96 and accurate volumetry metrics. RVWL achieved high Dice scores (>0.90) and high accuracy (>93%) for wall labelling. The combination of RHBS + RVWL provided an accurate assessment of free and septal wall regional strain, with a median cosine similarity value of 0.97 in the independent cohort. Conclusion: A fully automated 3D cineCT-based RV regional strain analysis pipeline has the potential to significantly enhance the efficiency and reproducibility of RV function assessment, enabling the evaluation of large cohorts and multi-centre studies.

Background and Aims: Left ventricular assist devices (LVADs), including the HeartMate 3 (HM3), have improved outcomes in patients with advanced heart failure. Use of vitamin K antagonists (VKA) is mandated to reduce the risk of thrombotic events, but there is heterogeneity in management. Time in therapeutic range (TTR) is a crucial metric for assessing the quality of VKA management. The ARIES-HM3 trial demonstrated that aspirin can be safely omitted from the antithrombotic regimen, resulting in reduced bleeding without increased thrombosis. This pre-specified trial analysis explores the relationship of quality of VKA management assessed by TTR with haemocompatibility-related outcomes. Methods: ARIES-HM3 was an international, randomized, double-blind, placebo-controlled study of aspirin (100 mg/day) or placebo (1:1) with VKA therapy in patients with de-novo HM3 placement. Participants were stratified into low TTR or high TTR groups based on median levels (n = 554). Primary endpoint success and secondary endpoint rates were stratified based on TTR groups. Bleeding rates at 12 months were estimated using an Andersen–Gill model with TTR as a single continuous variable, and multivariable regression analysis was performed. Results: The percentage of patients with a TTR above or below the median of 56 was similar between the aspirin and placebo groups. More participants achieved primary endpoint success with TTR ≥56% (77% vs 66.9%, P = .01). Higher TTR was associated with lower bleeding rates at 12 months (26.4 vs 49.2 events per 100 participant-years; rate ratio 1.84, 95% confidence interval [CI] 1.37–2.53) without stroke increase (3.2 vs 2.8 events per 100 participant-years; rate ratio 0.88 [95% CI: 0.30–2.53]). No interaction was observed between the assigned treatment group and TTR. Modelling demonstrated a constant decrease in bleeding as a function of increasing TTR. Female sex and Black race were independent predictors of low TTR (odds ratio: 1.70 [95% CI: 1.12–2.57]; 1.62 [95% CI: 1.11–2.35], respectively), with more frequent INRs below the therapeutic range. Multivariable modelling identified age ≥65 years, aspirin use, TTR <56%, and blood urea nitrogen ≥30 mg/dL as predictors of non-surgical bleeding. Conclusions: The quality of VKA management as measured by TTR correlates with the occurrence of non-surgical bleeding in patients with the HM3 LVAD, with a lower TTR associated with an increased bleeding risk. These data provide new clinical direction to define a benchmark TTR to achieve further mitigation of residual risk of bleeding and enhance haemocompatibility with the HM3 LVAD.

Background: Right ventricular (RV) function is a key factor in the diagnosis and prognosis of heart disease. However, current advanced CT-based assessments rely on semi-automated segmentation of the RV blood pool and manual delineation of the RV free and septal wall boundaries. Both of these steps are time-consuming and prone to inter- and intra-observer variability. Methods: We developed and evaluated a fully automated pipeline consisting of two deep learning methods to automate volumetric and regional strain analysis of the RV from contrast-enhanced, ECG-gated cineCT images. The Right Heart Blood Segmenter (RHBS) is a 3D high resolution configuration of nnU-Net to define the endocardial boundary, while the Right Ventricular Wall Labeler (RVWL) is a 3D point cloud-based deep learning method to label the free and septal walls. We trained our models using a diverse cohort of patients with different RV phenotypes and tested in an independent cohort of patients with aortic stenosis undergoing TAVR. Results: Our approach demonstrated high accuracy in both cross-validation and independent validation cohorts. RHBS and RVWL both yielded Dice scores of 0.96, and accurate volumetry metrics. RVWL achieved high Dice scores (>0.90) and high accuracy (>93%) for wall labeling. The combination of RHBS and RVWL provided accurate assessment of free and septal wall regional strain, with a median cosine similarity value of 0.97 in the independent cohort. Conclusions: A fully automated 3D cineCT-based RV regional strain analysis pipeline has the potential to significantly enhance the efficiency and reproducibility of RV function assessment, enabling the evaluation of large cohorts and multi-center studies. Key Points: RV endocardial segmentation of contrast enhanced CT scans can be utilized to perform volumetry, and when paired with labeling of free and septal walls, regional evaluation of surface strain. However, this has previously been performed using time-intensive semi-automated segmentation methods and manually labeling free wall and septal wall regions.. Here, we describe an automated, deep learning-based approach which uses two separate DL models to define the endocardial boundary (in 3D) and then label the free and septal walls on the endocardial surface. Our approach facilitates rapid and automatic advanced phenotyping of patients. This reduces prior limitations of potential interobserver variability and challenges associated with evaluating large cohorts.