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Introduction: Hypertrophic cardiomyopathy (HCM) results from pathogenic variants in sarcomeric protein genes that increase myocyte energy demand and lead to cardiac hypertrophy. However, it is unknown whether a common metabolic trait underlies cardiac phenotype at the early disease stage. To address this question and define cardiac biochemical pathology in early-stage HCM, we studied two HCM mouse models that express pathogenic variants in cardiac troponin T ( Tnt2 ) or myosin heavy chain ( Myh6 ) genes, and have marked differences in cardiac imaging phenotype, mitochondrial function at early disease stage., Methods: We used a combination of echocardiography, transcriptomics, mass spectrometry-based untargeted metabolomics (GC-TOF, HILIC, CSH-QTOF), and computational modeling (CardioNet) to examine cardiac structural and metabolic remodeling at early disease stage (5 weeks of age) in R92W-TnT +/- and R403Q-MyHC +/- mutant mice. Data from mutants was compared with respective littermate controls (WT)., Results: Allele-specific differences in cardiac phenotype, gene expression and metabolites were observed at early disease stage. LV diastolic dysfunction was prominent in TnT mutants. Differentially-expressed genes in TnT mutant hearts were predominantly enriched in the Krebs cycle, respiratory electron transport, and branched-chain amino acid metabolism, whereas MyHC mutants were enriched in mitochondrial biogenesis, calcium homeostasis, and liver-X-receptor signaling. Both mutant hearts demonstrated significant alterations in levels of purine nucleosides, trisaccharides, dicarboxylic acids, acylcarnitines, phosphatidylethanolamines, phosphatidylinositols, ceramides and triglycerides; 40.4 % of lipids and 24.7 % of metabolites were significantly different in TnT mutants, whereas 10.4 % of lipids and 5.8 % of metabolites were significantly different in MyHC mutants. Both mutant hearts had a lower abundance of unsaturated long-chain acyl-carnitines (18:1, 18:2, 20:1), but only TnT mutants showed enrichment of FA18:0 in ceramide and cardiolipin species. CardioNet predicted impaired energy substrate metabolism and greater phospholipid remodeling in TnT mutants than in MyHC mutants., Conclusions: Our systems biology approach revealed marked differences in metabolic remodeling in R92W-TnT and R403Q-MyHC mutant hearts, with TnT mutants showing greater derangements than MyHC mutants, at early disease stage. Changes in cardiolipin composition in TnT mutants could contribute to impairment of energy metabolism and diastolic dysfunction observed in this study, and predispose to energetic stress, ventricular arrhythmias under high workloads such as exercise., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Hypertrophic cardiomyopathy (HCM) is associated with phenotypic variability. To gain insights into transcriptional regulation of cardiac phenotype, single-nucleus linked RNA-/ATAC-seq was performed in 5-week-old control mouse-hearts (WT) and two HCM-models (R92W-TnT, R403Q-MyHC) that exhibit differences in heart size/function and fibrosis; mutant data was compared to WT. Analysis of 23,304 nuclei from mutant hearts, and 17,669 nuclei from WT, revealed similar dysregulation of gene expression, activation of AP-1 TFs (FOS, JUN) and the SWI/SNF complex in both mutant ventricular-myocytes. In contrast, marked differences were observed between mutants, for gene expression/TF enrichment, in fibroblasts, macrophages, endothelial cells. Cellchat predicted activation of pro-hypertrophic IGF-signaling in both mutant ventricular-myocytes, and profibrotic TGFβ-signaling only in mutant-TnT fibroblasts. In summary, our bioinformatics analyses suggest that activation of IGF-signaling, AP-1 TFs and the SWI/SNF chromatin remodeler complex promotes myocyte hypertrophy in early-stage HCM. Selective activation of TGFβ-signaling in mutant-TnT fibroblasts contributes to genotype-specific differences in cardiac fibrosis., Competing Interests: Competing Interests statement The authors declare no competing interests.

Backgorund: Quantification of myocardial blood flow (MBF) by positron emission tomography (PET) is important for investigation of angina in hypertrophic cardiomyopathy (HCM). Several software programs exist for MBF quantification, but they have been mostly evaluated in patients (with normal cardiac geometry), referred for evaluation of coronary artery disease (CAD). Software performance has not been evaluated in HCM patients who frequently have hyperdynamic LV function, LV outflow tract (LVOT) obstruction, small LV cavity size, and variation in the degree/location of LV hypertrophy., Aim: We compared results of MBF obtained using PMod, which permits manual segmentation, to those obtained by FDA-approved QPET software which has an automated segmentation algorithm., Methods: 13 N-ammonia PET perfusion data were acquired in list mode at rest and during pharmacologic vasodilation, in 76 HCM patients and 10 non-HCM patients referred for evaluation of CAD (CAD group.) Data were resampled to create static, ECG-gated and 36-frame-dynamic images. Myocardial flow reserve (MFR) and MBF (in ml/min/g) were calculated using QPET and PMod softwares., Results: All HCM patients had asymmetric septal hypertrophy, and 50% had evidence of LVOT obstruction, whereas non-HCM patients (CAD group) had normal wall thickness and ejection fraction. PMod yielded significantly higher values for global and regional stress-MBF and MFR than for QPET in HCM. Reasonably fair correlation was observed for global rest-MBF, stress-MBF, and MFR using these two softwares (rest-MBF: r = 0.78; stress-MBF: r = 0.66.; MFR: r = 0.7) in HCM patients. Agreement between global MBF and MFR values improved when HCM patients with high spillover fractions (> 0.65) were excluded from the analysis (rest-MBF: r = 0.84; stress-MBF: r = 0.72; MFR: r = 0.8.) Regionally, the highest agreement between PMod and QPET was observed in the LAD territory (rest-MBF: r = 0.82, Stress-MBF: r = 0.68) where spillover fraction was the lowest. Unlike HCM patients, the non-HCM patients (CAD group) demonstrated excellent agreement in MBF/MFR values, obtained by the two softwares, when patients with high spillover fractions were excluded (rest-MBF: r = 0.95; stress-MBF: r = 0.92; MFR: r = 0.95)., Conclusions: Anatomic characteristics specific to HCM hearts contribute to lower correlations between MBF/MFR values obtained by PMod and QPET, compared with non-HCM patients. These differences indicate that PMod and QPET cannot be used interchangeably for MBF/MFR analyses in HCM patients.