Personalized computational heart models with T1-mapped fibrotic remodeling predict sudden death risk in patients with hypertrophic cardiomyopathy.
Ontology highlight
ABSTRACT:
SUBMITTER: O'Hara RP
PROVIDER: S-EPMC8789259 | biostudies-literature |
REPOSITORIES: biostudies-literature
Similar Datasets
Project description:BackgroundHypertrophic cardiomyopathy (HCM) is an autosomal dominant genetic disorder, characterized by cardiomyocyte hypertrophy, cardiomyocyte disarray and fibrosis, which has a prevalence of ∼1: 200-500 and predisposes individuals to heart failure and sudden death. The mechanisms through which diverse HCM-causing mutations cause cardiac dysfunction remain mostly unknown and their identification may reveal new therapeutic avenues. MicroRNAs (miRNAs) have emerged as critical regulators of gene expression and disease phenotype in various pathologies. We explored whether miRNAs could play a role in HCM pathogenesis and offer potential therapeutic targets.Methods and resultsUsing high-throughput miRNA expression profiling and qPCR analysis in two distinct mouse models of HCM, we found that miR-199a-3p expression levels are upregulated in mutant mice compared to age- and treatment-matched wild-type mice. We also found that miR-199a-3p expression is enriched in cardiac non-myocytes compared to cardiomyocytes. When we expressed miR-199a-3p mimic in cultured murine primary cardiac fibroblasts and analyzed the conditioned media by proteomics, we found that several extracellular matrix (ECM) proteins (e.g., TSP2, FBLN3, COL11A1, LYOX) were differentially secreted (data are available via ProteomeXchange with identifier PXD042904). We confirmed our proteomics findings by qPCR analysis of selected mRNAs and demonstrated that miR-199a-3p mimic expression in cardiac fibroblasts drives upregulation of ECM gene expression, including Tsp2, Fbln3, Pcoc1, Col1a1 and Col3a1. To examine the role of miR-199a-3p in vivo, we inhibited its function using lock-nucleic acid (LNA)-based inhibitors (antimiR-199a-3p) in an HCM mouse model. Our results revealed that progression of cardiac fibrosis is attenuated when miR-199a-3p function is inhibited in mild-to-moderate HCM. Finally, guided by computational target prediction algorithms, we identified mRNAs Cd151 and Itga3 as direct targets of miR-199a-3p and have shown that miR-199a-3p mimic expression negatively regulates AKT activation in cardiac fibroblasts.ConclusionsAltogether, our results suggest that miR-199a-3p may contribute to cardiac fibrosis in HCM through its actions in cardiac fibroblasts. Thus, inhibition of miR-199a-3p in mild-to-moderate HCM may offer therapeutic benefit in combination with complementary approaches that target the primary defect in cardiac myocytes.
| S-EPMC10739604 | biostudies-literature
Project description:Objectives: To identify significant radiomics features derived from late gadolinium enhancement (LGE) images in participants with hypertrophic cardiomyopathy (HCM) and assess their prognostic value in predicting sudden cardiac death (SCD) endpoint. Method: The 157 radiomic features of 379 sequential participants with HCM who underwent cardiovascular magnetic resonance imaging (MRI) were extracted. CoxNet (Least Absolute Shrinkage and Selection Operator (LASSO) and Elastic Net) and Random Forest models were applied to optimize feature selection for the SCD risk prediction and cross-validation was performed. Results: During a median follow-up of 29 months (interquartile range, 20-42 months), 27 participants with HCM experienced SCD events. Cox analysis revealed that two selected features, local binary patterns (LBP) (19) (hazard ratio (HR), 1.028, 95% CI: 1.032-1.134; P = 0.001) and Moment (1) (HR, 1.212, 95%CI: 1.032-1.423; P = 0.02) provided significant prognostic value to predict the SCD endpoints after adjustment for the clinical risk predictors and late gadolinium enhancement. Furthermore, the univariately significant risk predictor was improved by the addition of the selected radiomics features, LBP (19) and Moment (1), to predict SCD events (P < 0.05). Conclusion: The radiomics features of LBP (19) and Moment (1) extracted from LGE images, reflecting scar heterogeneity, have independent prognostic value in identifying high SCD risk patients with HCM.
| S-EPMC8702805 | biostudies-literature
Project description:Background: MRI native T1 mapping and extracellular volume fraction (ECV) are quantitative values that could reflect various myocardial tissue characterization. The role of these parameters in predicting the risk of sudden cardiac death (SCD) in hypertrophic cardiomyopathy (HCM) is still poorly understood. Aim: This study aims to investigate the ability of native T1 mapping and ECV values to predict major adverse cardiovascular events (MACE) in HCM, and its incremental values over the 2014 European Society of Cardiology (ESC) and enhanced American College of Cardiology/American Heart Association (ACC/AHA) guidelines. Methods: Between July 2016 and October 2020, HCM patients and healthy individuals with sex and age matched who underwent cardiac MRI were prospectively enrolled. The native T1 and ECV parameters were measured. The SCD risk was evaluated by the 2014 ESC guidelines and enhanced ACC/AHA guidelines. MACE included cardiac death, transplantation, heart failure admission, and implantable cardioverter-defibrillator implantation. Results: A total of 203 HCM patients (54.2 ± 14.9 years) and 101 healthy individuals (53.2 ± 14.7 years) were evaluated. During a median follow-up of 15 months, 25 patients (12.3%) had MACE. In multivariate Cox regression analysis, global native T1 mapping (hazard ratio (HR): 1.446; 95% confidence interval (CI): 1.195-1.749; P < 0.001) and non-sustained ventricular tachycardia (NSVT) (HR: 4.949; 95% CI, 2.033-12.047; P < 0.001) were independently associated with MACE. Ten of 86 patients (11.6%) with low SCD risk assessed by the two guidelines had MACE. In this subgroup of patients, multivariate Cox regression analysis showed that global native T1 mapping was independently associated with MACE (HR: 1.532; 95% CI: 1.221-1.922; P < 0.001). In 85 patients with conflicting results assessed by the two guidelines, end-stage systolic dysfunction was independently associated with MACE (HR: 7.942, 95% CI: 1.322-47.707, P = 0.023). In 32 patients with high SCD risk assessed by the two guidelines, NSVT was independently associated with MACE (HR: 9.779, 95% CI: 1.953-48.964, P = 0.006). Conclusion: The global native T1 mapping could provide incremental values and serve as potential supplements to the current guidelines in the prediction of MACE.
| S-EPMC8217449 | biostudies-literature
Project description: Not available
| S-EPMC1767009 | biostudies-literature
Project description:Background: Hypertrophic cardiomyopathy (HCM) is an autosomal dominant genetic disorder, characterized by cardiomyocyte hypertrophy, cardiomyocyte disarray and fibrosis, which has a prevalence of ~1:200-500 and predisposes individuals to sudden death and heart failure. The mechanisms through which diverse HCM-causing mutations cause cardiac dysfunction remain mostly unknown and their identification may reveal new therapeutic avenues. MicroRNAs have emerged as critical regulators of gene expression and disease phenotype in various pathologies. We explored whether miRNAs could play a role in HCM pathogenesis and offer potential therapeutic targets. Methods and Results: Using high-throughput miRNA expression profiling and qPCR analysis in two distinct mouse models of HCM, we found that miR-199a-3p expression levels are upregulated in mutant mice compared to age- and treatment-matched wild-type mice. We also found that miR-199a-3p expression is enriched in cardiac non-myocytes compared to cardiomyocytes. When we expressed miR-199a-3p mimic in cultured primary cardiac non-myocytes and analyzed the conditioned media by proteomics, we found that several ECM proteins (e.g., TSP2, FBLN3, COL11A1, LYOX) were differentially expressed. We confirmed our proteomics findings by qPCR analysis of selected mRNAs and demonstrated that miR-199a-3p mimic expression in cardiac non-myocytes drives upregulation of ECM genes including Tsp2, Fbln3, Pcoc1, Col1a1 and Col3a1. To examine the role of miR-199a-3p in vivo, we inhibited its function using lock-nucleic acid (LNA)-based inhibitors (antimiR-199a-3p) in an HCM mouse model. Our results revealed that progression of cardiac fibrosis is attenuated when miR-199a-3p function is inhibited in mild-to-moderate HCM. Finally, guided by computational target prediction algorithms, we identified mRNAs Cd151 and Itga3 as direct targets of miR-199a-3p and have shown that miR-199a-3p mimic expression negatively regulates AKT activation in cardiac non-myocytes. Conclusions: Altogether, our results suggest that miR-199a-3p may contribute to cardiac fibrosis in HCM through its actions in cardiac non-myocytes. Thus, inhibition of miR-199a-3p in mild-to-moderate HCM may offer therapeutic benefit in combination with complementary approaches that target the primary defect in cardiac myocytes.
2024-01-26 | PXD042904 | Pride
Project description:AimsAssessment of ECG-features as predictors of sudden death in adults with hypertrophic cardiomyopathy (HCM).Methods and resultsECG-amplitude sums were measured in 44 normals, 34 athletes, a hospital-cohort of 87 HCM-patients, and 29 HCM-patients with sudden death or cardiac arrest (HCM-CA). HCM-patients with sudden death or cardiac arrest had substantially higher ECG-amplitudes than the HCM-cohort for limb-lead and 12-lead QRS-amplitude sums, and amplitude-duration products (P = 0.00003-P = 0.000002). Separation of HCM-CA from the HCM-cohort is obtained by limb-lead QRS-amplitude sum >or=7.7 mV (odds ratio 18.8, sensitivity 87%, negative predictive value (NPV) 94%, P < 0.0001), 12-lead amplitude-duration product >or=2.2 mV s (odds ratio 31.0, sensitivity 92%, NPV 97%, P < 0.0001), and limb-lead amplitude-duration product >or=0.70 mV s (odds ratio 31.5, sensitivity 93%, NPV 96%, P < 0.0001). Sensitivity in HCM-patients <40 years is 90, 100, and 100% for those ECG-variables, respectively. Qualitative analysis showed correlation with cardiac arrest for pathological T-wave-inversion (P = 0.0003), ST-depression (P = 0.0010), and dominant S-wave in V(4) (P = 0.0048). A risk score is proposed; a score >or=6 gives a sensitivity of 85% but a higher positive predictive value than above measures. Optimal separation between HCM-CA <40 years and athletes is obtained by a risk score >or=6 (odds ratio 345, sensitivity 85%, specificity 100%, P < 0.0001).ConclusionTwelve-lead ECG is a powerful instrument for risk-stratification in HCM.
| S-EPMC2821628 | biostudies-literature
Project description:RationaleSusceptibility to VT/VF (ventricular tachycardia/fibrillation) is difficult to predict in patients with ischemic cardiomyopathy either by clinical tools or by attempting to translate cellular mechanisms to the bedside.ObjectiveTo develop computational phenotypes of patients with ischemic cardiomyopathy, by training then interpreting machine learning of ventricular monophasic action potentials (MAPs) to reveal phenotypes that predict long-term outcomes.Methods and resultsWe recorded 5706 ventricular MAPs in 42 patients with coronary artery disease and left ventricular ejection fraction ≤40% during steady-state pacing. Patients were randomly allocated to independent training and testing cohorts in a 70:30 ratio, repeated K=10-fold. Support vector machines and convolutional neural networks were trained to 2 end points: (1) sustained VT/VF or (2) mortality at 3 years. Support vector machines provided superior classification. For patient-level predictions, we computed personalized MAP scores as the proportion of MAP beats predicting each end point. Patient-level predictions in independent test cohorts yielded c-statistics of 0.90 for sustained VT/VF (95% CI, 0.76-1.00) and 0.91 for mortality (95% CI, 0.83-1.00) and were the most significant multivariate predictors. Interpreting trained support vector machine revealed MAP morphologies that, using in silico modeling, revealed higher L-type calcium current or sodium-calcium exchanger as predominant phenotypes for VT/VF.ConclusionsMachine learning of action potential recordings in patients revealed novel phenotypes for long-term outcomes in ischemic cardiomyopathy. Such computational phenotypes provide an approach which may reveal cellular mechanisms for clinical outcomes and could be applied to other conditions.
| S-EPMC7855939 | biostudies-literature
Project description:Chronic pressure or volume overload can cause the vertebrate heart to remodel. The hearts of fish remodel in response to seasonal temperature change. Here we focus on the passive properties of the fish heart. Building upon our previous work on thermal-remodeling of the rainbow trout ventricle, we hypothesized that chronic cooling would initiate fibrotic cardiac remodeling, with increased myocardial stiffness, similar to that seen with pathological hypertrophy in mammals. We hypothesized that, in contrast to pathological hypertrophy in mammals, the remodeling response in fish would be plastic and the opposite response would occur following chronic warming. Rainbow trout held at 10°C (control group) were chronically (>8 weeks) exposed to cooling (5°C) or warming (18°C). Chronic cold induced hypertrophy in the highly trabeculated inner layer of the fish heart, with a 41% increase in myocyte bundle cross-sectional area, and an up-regulation of hypertrophic marker genes. Cold acclimation also increased collagen deposition by 1.7-fold and caused an up-regulation of collagen promoting genes. In contrast, chronic warming reduced myocyte bundle cross-sectional area, expression of hypertrophic markers and collagen deposition. Functionally, the cold-induced fibrosis and hypertrophy were associated with increased passive stiffness of the whole ventricle and with increased micromechanical stiffness of tissue sections. The opposite occurred with chronic warming. These findings suggest chronic cooling in the trout heart invokes a hypertrophic phenotype with increased cardiac stiffness and fibrosis that are associated with pathological hypertrophy in the mammalian heart. The loss of collagen and increased compliance following warming is particularly interesting as it suggests fibrosis may oscillate seasonally in the fish heart, revealing a more dynamic nature than the fibrosis associated with dysfunction in mammals.
| S-EPMC4720793 | biostudies-literature
Project description:Hypertrophic cardiomyopathy (HCM) is a genetic heart disease that is associated with many pathological features, such as a reduction in global longitudinal strain (GLS), myofiber disarray and hypertrophy. The effects of these features on left ventricle (LV) function are, however, not clear in two phenotypes of HCM, namely, obstructive and non-obstructive. To address this issue, we developed patient-specific computational models of the LV using clinical measurements from 2 female HCM patients and a control subject. Left ventricular mechanics was described using an active stress formulation and myofiber disarray was described using a structural tensor in the constitutive models. Unloaded LV configuration for each subject was first determined from their respective end-diastole LV geometries segmented from the cardiac magnetic resonance images, and an empirical single-beat estimation of the end-diastolic pressure volume relationship. The LV was then connected to a closed-loop circulatory model and calibrated using the clinically measured LV pressure and volume waveforms, peak GLS and blood pressure. Without consideration of myofiber disarray, peak myofiber tension was found to be lowest in the obstructive HCM subject (60 kPa), followed by the non-obstructive subject (242 kPa) and the control subject (375 kPa). With increasing myofiber disarray, we found that peak tension has to increase in the HCM models to match the clinical measurements. In the obstructive HCM patient, however, peak tension was still depressed (cf. normal subject) at the largest degree of myofiber disarray found in the clinic. The computational modeling workflow proposed here can be used in future studies with more HCM patient data.
| S-EPMC9849405 | biostudies-literature
Project description:We explored whether radiomic features from T1 maps by cardiac magnetic resonance (CMR) could enhance the diagnostic value of T1 mapping in distinguishing health from disease and classifying cardiac disease phenotypes. A total of 149 patients (n = 30 with no heart disease, n = 30 with LVH, n = 61 with hypertrophic cardiomyopathy (HCM) and n = 28 with cardiac amyloidosis) undergoing a CMR scan were included in this study. We extracted a total of 850 radiomic features and explored their value in disease classification. We applied principal component analysis and unsupervised clustering in exploratory analysis, and then machine learning for feature selection of the best radiomic features that maximized the diagnostic value for cardiac disease classification. The first three principal components of the T1 radiomics were distinctively correlated with cardiac disease type. Unsupervised hierarchical clustering of the population by myocardial T1 radiomics was significantly associated with myocardial disease type (chi2 = 55.98, p < 0.0001). After feature selection, internal validation and external testing, a model of T1 radiomics had good diagnostic performance (AUC 0.753) for multinomial classification of disease phenotype (normal vs. LVH vs. HCM vs. cardiac amyloid). A subset of six radiomic features outperformed mean native T1 values for classification between myocardial health vs. disease and HCM phenocopies (AUC of T1 vs. radiomics model, for normal: 0.549 vs. 0.888; for LVH: 0.645 vs. 0.790; for HCM 0.541 vs. 0.638; and for cardiac amyloid 0.769 vs. 0.840). We show that myocardial texture assessed by native T1 maps is linked to features of cardiac disease. Myocardial radiomic phenotyping could enhance the diagnostic yield of T1 mapping for myocardial disease detection and classification.
| S-EPMC8654857 | biostudies-literature