Cardiomyopathies: Myocardial fibrosis assessed by CMR to predict events in HCM

Cardiac Fibrosis Automated Diagnosis Based on FibrosisNet Network Using CMR Ischemic Cardiomyopathy

Ischemic heart condition is one of the most prevalent causes of death that can be treated more effectively and lead to fewer fatalities if identified early. Heart muscle fibrosis affects the diastolic and systolic function of the heart and is linked to unfavorable cardiovascular outcomes. Cardiac magnetic resonance (CMR) scarring, a risk factor for ischemic heart disease, may be accurately identified by magnetic resonance imaging (MRI) to recognize fibrosis. In the past few decades, numerous methods based on MRI have been employed to identify and categorize cardiac fibrosis. Because they increase the therapeutic advantages and the likelihood that patients will survive, developing these approaches is essential and has significant medical benefits. A brand-new method that uses MRI has been suggested to help with diagnosing. Advances in deep learning (DL) networks contribute to the early and accurate diagnosis of heart muscle fibrosis. This study introduces a new deep network known as FibrosisNet, which detects and classifies fibrosis if it is present. It includes some of 17 various series layers to achieve the fibrosis detection target. The introduced classification system is trained and evaluated for the best performance results. In addition, deep transfer-learning models are applied to the different famous convolution neural networks to find fibrosis detection architectures. The FibrosisNet architecture achieves an accuracy of 96.05%, a sensitivity of 97.56%, and an F1-Score of 96.54%. The experimental results show that FibrosisNet has numerous benefits and produces higher results than current state-of-the-art methods and other advanced CNN approaches.

Kindlin-2 suppresses transcription factor GATA4 through interaction with SUV39H1 to attenuate hypertrophy

Kindlin-2 plays an important role in the regulation of cardiac structure and function. Depletion of Kindlin-2 contributes to cardiac hypertrophy and progressive heart failure, however, the precise mechanisms involved in this process remain unclear. GATA4 is a critical transcription factor in regulating cardiogenesis. We found that Kindlin-2 suppresses the expression of GATA4 through binding to its promoter and prevents cardiomyocytes from hypertrophy induced by isoproterenol (ISO) treatment. Mechanistically, Kindlin-2 interacts with histone methyltransferase SUV39H1 and recruits it to GATA4 promoter leading to the occupancy of histone H3K9 di- and tri-methylation. Furthermore, to confirm the function of Kindlin-2 in vivo, we generated mice with targeted deletion of cardiac Kindlin-2. We found that 6-month-old Kindlin-2 cKO mice have developed hypertrophic cardiomyopathy and that this pathological process can be accelerated by ISO-treatment. GATA4 expression was markedly activated in cardiac tissues of Kindlin-2 cKO mice compared to wild-type animals. Collectively, our data revealed that Kindlin-2 suppresses GATA4 expression by triggering histone H3K9 methylation in part and protects heart from pathological hypertrophy.

Mechanisms of disease: hypertrophic cardiomyopathy

Hypertrophic cardiomyopathy (HCM) is the most-common monogenically inherited form of heart disease, characterized by thickening of the left ventricular wall, contractile dysfunction, and potentially fatal arrhythmias. HCM is also the most-common cause of sudden cardiac death in individuals younger than 35 years of age. Much progress has been made in the elucidation of the genetic basis of HCM, resulting in the identification of more than 900 individual mutations in over 20 genes. Interestingly, most of these genes encode sarcomeric proteins, such as myosin-7 (also known as cardiac muscle β-myosin heavy chain; MYH7), cardiac myosin-binding protein C (MYBPC3), and cardiac muscle troponin T (TNNT2). However, the molecular events that ultimately lead to the clinical phenotype of HCM are still unclear. We discuss several potential pathways, which include altered calcium cycling and sarcomeric calcium sensitivity, increased fibrosis, disturbed biomechanical stress sensing, and impaired cardiac energy homeostasis. An improved understanding of the pathological mechanisms involved will result in greater specificity and success of therapies for patients with HCM.