Background: Heart failure is a prevalent and life-threatening medical condition characterized by abnormal atrial electrical activity, contributing to a higher risk of ischemic stroke. Atrial remodelling, driven by oxidative stress and structural changes, plays a central role in heart failure progression. Recent studies suggest that HACE1, a regulatory gene, may be involved in cardiac protection against heart failure.
Methods: Clinical data analysis involved heart failure patients, while an animal model utilized C57BL/6J mice. RT-PCR, microarray analysis, histological examination, ELISA, and Western blot assays were employed to assess gene and protein expression, oxidative stress, and cardiac function. Cell transfection and culture of mouse atrial fibroblasts were performed for experiments.
Results: HACE1 expression was reduced in heart failure patients and correlated negatively with collagen levels. In mouse models, HACE1 up-regulation reduced oxidative stress, mitigated fibrosis, and improved cardiac function. Conversely, HACE1 knockdown exacerbated oxidative stress, fibrosis, and cardiac dysfunction. HACE1 also protected against ferroptosis and mitochondrial damage. NRF2, a transcription factor implicated in oxidative stress, was identified as a target of HACE1, with HACE1 promoting NRF2 activity through ubiquitination.
Conclusions: HACE1 emerges as a potential therapeutic target and diagnostic marker for heart failure. It regulates oxidative stress, mitigates cardiac fibrosis, and protects against ferroptosis and mitochondrial damage. The study reveals that HACE1 achieves these effects, at least in part, through NRF2 activation via ubiquitination, offering insights into novel mechanisms for heart failure pathogenesis and potential interventions.
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http://dx.doi.org/10.18632/aging.205272 | DOI Listing |
Acta Pharm
December 2024
Department of Clinical Pharmacy, University Hospital Dubrava, 10000 Zagreb Croatia.
Cardiovascular diseases (CVDs) are the leading cause of mortality and morbidity globally. It is estimated that 17.9 million people died from CVDs in 2019, which represents 32 % of all deaths worldwide.
View Article and Find Full Text PDFEur Heart J Cardiovasc Imaging
January 2025
Department of Perioperative Cardiology and Cardiovascular Imaging, Centro Cardiologico Monzino IRCCS, Milan, Italy.
Aim: Computed tomography (CT)-derived extracellular volume fraction (ECV) is a non-invasive method to quantify myocardial fibrosis. Evaluating CT-ECV during aortic valve replacement (AVR) planning CT in severe aortic stenosis (AS) may aid prognostic stratification. This meta-analysis evaluated the prognostic significance of CT-ECV in severe AS necessitating AVR.
View Article and Find Full Text PDFASAIO J
December 2024
Cleveland Clinic Florida, Heart, Vascular and Thoracic Institute, Advanced Heart Failure Program, Weston, Florida.
We investigated the association of preimplant left ventricular end-diastolic diameter (LVEDD) with outcomes after HeartMate 3 (HM3) left ventricular assist device (LVAD) implantation. Patients from the European Registry for Patients with Mechanical Circulatory Support (EUROMACS) registry who underwent HM3 implantation from August 2014 to February 2023 (n = 834) were analyzed according to preoperative LVEDD: less than or equal to 65 (n = 251), 65-80 (n = 441), and greater than or equal to 80 mm (n = 142). The mean age was 54.
View Article and Find Full Text PDFJ Clin Endocrinol Metab
January 2025
Department of Neurosurgery and State Key Laboratory of Trauma, Burn and Combined Injury, Southwest Hospital; Chongqing Key Laboratory of Precision Neuromedicine and Neuroregenaration, Third Military Medical University (Army Medical University), 400038 Chongqing, China.
Background: Phthalates, widely used as chemical additives, are often found as mixtures in the environment. However, the combined impact of phthalate exposure on sarcopenia remains unclear.
Objective: This study aimed to investigate the relationships between phthalates and sarcopenia in adults.
Eur Heart J Acute Cardiovasc Care
January 2025
Department of Medical Informatics, Korea University College of Medicine, Seoul, Republic of Korea.
Background: Acute heart failure (AHF) poses significant diagnostic challenges in the emergency room (ER) because of its varied clinical presentation and limitations of traditional diagnostic methods. This study aimed to develop and evaluate a deep-learning model using electrocardiogram (ECG) data to enhance AHF identification in the ER.
Methods: In this retrospective cohort study, we analyzed the ECG data of 19,285 patients who visited ERs of three hospitals between 2016 and 2020; 9,119 with available left ventricular ejection fraction and N-terminal prohormone of brain natriuretic peptide level data and who were diagnosed with AHF were included in the study.
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