This study hypothesized that paroxysmal atrial fibrillation (PAF) reflects the presence of a more severe cardiac hypertrophic cardiomyopathy (HCM) phenotype. HCM is characterized by myocyte hypertrophy, fibrosis, and a high prevalence of PAF. It is currently unresolved whether atrial fibrillation (AF) is a marker or a mediator of adverse outcomes in HCM. This study retrospectively examined 45 HCM patients who underwent cardiovascular magnetic resonance (CMR) imaging in sinus rhythm. The function of all 4 cardiac chambers was assessed, as well as late gadolinium enhancement (LGE) in the left atrium (LA) and left ventricle (LV), as indicators of fibrosis. A fat-saturated, 3-dimensional inversion recovery-prepared, fast-spoiled, gradient-recalled echo sequence, and the image intensity ratio method were used to measure LA-LGE; LGE in the LV was quantified using a semi-automated threshold technique. HCM patients (n = 45) were divided into 2 groups (PAF, no AF) based on history of PAF. All HCM patients had LGE in the LA posterior wall. The PAF group (n = 18) had higher LA volume, a lower LA ejection fraction, a lower global peak longitudinal LA strain (PLAS), and a higher amount of LA-LGE compared with the no AF group (n = 27). A modest inverse association was noted between the LA ejection fraction, PLAS, and LA-LGE; a positive association was present between LV-LGE and LA-LGE. The PAF group had lower ejection fractions in the LV, right atrium, and right ventricle compared with those in the no AF group. PAF is associated with a greater degree of structural LA remodeling and global myopathy, which suggests a more severe cardiac HCM phenotype.

Clinical risk stratification for sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HC) employs rules derived from American College of Cardiology Foundation/American Heart Association (ACCF/AHA) guidelines or the HCM Risk-SCD model (C-index ∼0.69), which utilize a few clinical variables. We assessed whether data-driven machine learning methods that consider a wider range of variables can effectively identify HC patients with ventricular arrhythmias (VAr) that lead to SCD. We scanned the electronic health records of 711 HC patients for sustained ventricular tachycardia or ventricular fibrillation. Patients with ventricular tachycardia or ventricular fibrillation (n = 61) were tagged as VAr cases and the remaining (n = 650) as non-VAr. The 2-sample ttest and information gain criterion were used to identify the most informative clinical variables that distinguish VAr from non-VAr; patient records were reduced to include only these variables. Data imbalance stemming from low number of VAr cases was addressed by applying a combination of over- and undersampling strategies. We trained and tested multiple classifiers under this sampling approach, showing effective classification. We evaluated 93 clinical variables, of which 22 proved predictive of VAr. The ensemble of logistic regression and naïve Bayes classifiers, trained based on these 22 variables and corrected for data imbalance, was most effective in separating VAr from non-VAr cases (sensitivity = 0.73, specificity = 0.76, C-index = 0.83). Our method (HCM-VAr-Risk Model) identified 12 new predictors of VAr, in addition to 10 established SCD predictors. In conclusion, this is the first application of machine learning for identifying HC patients with VAr, using clinical attributes. Our model demonstrates good performance (C-index) compared with currently employed SCD prediction algorithms, while addressing imbalance inherent in clinical data.

Background: Hypertrophic cardiomyopathy (HCM) is characterized by myocyte hypertrophy and fibrosis. Studies in two mouse models (R92W-TnT/R403Q-MyHC) at early HCM stage revealed upregulation of endothelin (ET1) signaling in both mutants, but TGFβ signaling only in TnT mutants. Dysregulation of miR-29 expression has been implicated in cardiac fibrosis. But it is unknown whether expression of miR-29a/b/c and profibrotic genes is commonly regulated in mouse and human HCM. Methods: In order to understand mechanisms underlying fibrosis in HCM, and examine similarities/differences in expression of miR-29a/b/c and several profibrotic genes in mouse and human HCM, we performed parallel studies in rat cardiac myocyte/fibroblast cultures, examined gene expression in two mouse models of (non-obstructive) HCM (R92W-TnT, R403Q-MyHC)/controls at early (5 weeks) and established (24 weeks) disease stage, and analyzed publicly available mRNA/miRNA expression data from obstructive-HCM patients undergoing septal myectomy/controls (unused donor hearts). Results: Myocyte cultures: ET1 increased superoxide/H₂O₂, stimulated TGFβ expression/secretion, and suppressed miR-29a expression in myocytes. The effect of ET1 on miR-29 and TGFβ expression/secretion was antagonized by N-acetyl-cysteine, a reactive oxygen species scavenger. Fibroblast cultures: ET1 had no effect on pro-fibrotic gene expression in fibroblasts. TGFβ1/TGFβ2 suppressed miR-29a and increased collagen expression, which was abolished by miR-29a overexpression. Mouse and human HCM: Expression of miR-29a/b/c was lower, and TGFB1/collagen gene expression was higher in TnT mutant-LV at 5 and 24 weeks; no difference was observed in expression of these genes in MyHC mutant-LV and in human myectomy tissue. TGFB2 expression was higher in LV of both mutant mice and human myectomy tissue. ACE2, a negative regulator of the renin-angiotensin-aldosterone system, was the most upregulated transcript in human myectomy tissue. Pathway analysis predicted upregulation of the anti-hypertrophic/anti-fibrotic liver X receptor/retinoid X receptor (LXR/RXR) pathway only in human myectomy tissue. Conclusions: Our in vitro studies suggest that activation of ET1 signaling in cardiac myocytes increases reactive oxygen species and stimulates TGFβ secretion, which downregulates miR-29a and increases collagen in fibroblasts, thus contributing to fibrosis. Our gene expression studies in mouse and human HCM reveal allele-specific differences in miR-29 family/profibrotic gene expression in mouse HCM, and activation of anti-hypertrophic/anti-fibrotic genes and pathways in human HCM.

Hypertrophic cardiomyopathy (HCM) is characterized by phenotypic heterogeneity. We investigated the molecular basis of the cardiac phenotype in two mouse models at established disease stage (mouse-HCM), and human myectomy tissue (human-HCM). We analyzed the transcriptome in 2 mouse models with non-obstructive HCM (R403Q-MyHC, R92W-TnT)/littermate-control hearts at 24 weeks of age, and in myectomy tissue of patients with obstructive HCM/control hearts (GSE36961, GSE36946). Additionally, we examined myocyte redox, cardiac mitochondrial DNA copy number (mtDNA-CN), mt-respiration, mt-ROS generation/scavenging and mt-Ca²⁺ handling in mice. We identified distinct allele-specific gene expression in mouse-HCM, and marked differences between mouse-HCM and human-HCM. Only two genes (CASQ1, GPT1) were similarly dysregulated in both mutant mice and human-HCM. No signaling pathway or transcription factor was predicted to be similarly dysregulated (by Ingenuity Pathway Analysis) in both mutant mice and human-HCM. Losartan was a predicted therapy only in TnT-mutant mice. KEGG pathway analysis revealed enrichment for several metabolic pathways, but only pyruvate metabolism was enriched in both mutant mice and human-HCM. Both mutant mouse myocytes demonstrated evidence of an oxidized redox environment. Mitochondrial complex I RCR was lower in both mutant mice compared to controls. MyHC-mutant mice had similar mtDNA-CN and mt-Ca²⁺ handling, but TnT-mutant mice exhibited lower mtDNA-CN and impaired mt-Ca²⁺ handling, compared to littermate-controls. Molecular profiling reveals differences in gene expression, transcriptional regulation, intracellular signaling and mt-number/function in 2 mouse models at established disease stage. Further studies are needed to confirm differences in gene expression between mouse and human-HCM, and to examine whether cardiac phenotype, genotype and/or species differences underlie the divergence in molecular profiles.