An Update on MYBPC3 Gene Mutation in Hypertrophic Cardiomyopathy.

Hypertrophic cardiomyopathy (HCM) is the most prevalent genetically inherited cardiomyopathy that follows an autosomal dominant inheritance pattern. The majority of HCM cases can be attributed to mutation of the MYBPC3 gene, which encodes cMyBP-C, a crucial structural protein of the cardiac muscle. The manifestation of HCM's morphological, histological, and clinical symptoms is subject to the complex interplay of various determinants, including genetic mutation and environmental factors. Approximately half of MYBPC3 mutations give rise to truncated protein products, while the remaining mutations cause insertion/deletion, frameshift, or missense mutations of single amino acids. In addition, the onset of HCM may be attributed to disturbances in the protein and transcript quality control systems, namely, the ubiquitin-proteasome system and nonsense-mediated RNA dysfunctions. The aforementioned genetic modifications, which appear to be associated with unfavorable lifelong outcomes and are largely influenced by the type of mutation, exhibit a unique array of clinical manifestations ranging from asymptomatic to arrhythmic syncope and even sudden cardiac death. Although the current understanding of the MYBPC3 mutation does not comprehensively explain the varied phenotypic manifestations witnessed in patients with HCM, patients with pathogenic MYBPC3 mutations can exhibit an array of clinical manifestations ranging from asymptomatic to advanced heart failure and sudden cardiac death, leading to a higher rate of adverse clinical outcomes. This review focuses on MYBPC3 mutation and its characteristics as a prognostic determinant for disease onset and related clinical consequences in HCM.

A Systematic Review on the Risk Modulators of Myocardial Infarction in the "Young"-Implications of Lipoprotein (a).

The presence of a myocardial infarction at a younger age is of special interest, considering the psychological and socioeconomic impact, as well as long-term morbidity and mortality. However, this group has a unique risk profile, with less traditional cardiovascular risk factors that are not well studied. This systematic review aims to evaluate traditional risk factors of myocardial infarction in the "young", highlighting the clinical implications of lipoprotein (a). We performed a comprehensive search using Preferred Reporting Items for Systematic Reviews and Meta-analyses (PRISMA) standards; we systematically searched the PubMed, EMBASE, and Science Direct Scopus databases, using the terms: "myocardial infarction", "young", "lipoprotein (a)", "low-density lipoprotein", "risk factors". The search identified 334 articles which were screened, and, at the end, 9 original research articles regarding the implications of lipoprotein (a) in myocardial infarction in the "young" were included in the qualitative synthesis. Elevated lipoprotein (a) levels were independently associated with an increased risk of coronary artery disease, especially in young patients, where this risk increased by threefold. Thus, it is recommended to measure the lipoprotein (a) levels in individuals with suspected familial hypercholesterolaemia or with premature atherosclerotic cardiovascular disease and no other identifiable risk factors, in order to identify patients who might benefit from a more intensive therapeutic approach and follow-up.

The Challenge of High Coronary Thrombotic Events in Patients with ST-Segment Elevation Myocardial Infarction and COVID-19.

The aim of this observational study was to describe the characteristics and outcomes of coronavirus disease 2019 (COVID-19)-positive patients with ST-segment elevation myocardial infarction (STEMI), with a special focus on factors associated with a high risk of coronary thrombosis and in-hospital mortality. Comparing the two groups of patients with STEMI separated according to the presence of SARS-CoV-2 infections, it was observed that COVID-19 patients were more likely to present with dyspnea (82.43% vs. 61.41%, p = 0.048) and cardiogenic shock (10.52% vs. 5.40%, p = 0.012). A longer total ischemia time was observed in COVID-19 patients, and they were twice as likely to undergo coronary angiography more than 12 hours after the onset of symptoms (19.29% vs. 10.13%, p = 0.024). In 10 of 57 COVID-19-positive patients, a primary PCI was not necessary, and only thromboaspiration was performed (17.54% vs. 2.70%, p < 0.001). Platelet level was inversely correlated (r = −0.512, p = 0.025) with a higher risk of coronary thrombosis without an atherosclerotic lesion. Using a cut-off value of 740 ng/ml, D-dimers predicted a higher risk of coronary thrombosis, with a sensitivity of 80% and a specificity of 66% (ROC area under the curve: 0.826, 95% CI: 0.716−0.935, p = 0.001). These are novel findings that raise the question of whether more aggressive antithrombotic therapy is necessary for selected COVID-19 and STEMI patients.

From Classic to Modern Prognostic Biomarkers in Patients with Acute Myocardial Infarction.

Despite all the important advances in its diagnosis and treatment, acute myocardial infarction (AMI) is still one of the most prominent causes of morbidity and mortality worldwide. Early identification of patients at high risk of poor outcomes through the measurement of various biomarker concentrations might contribute to more accurate risk stratification and help to guide more individualized therapeutic strategies, thus improving prognoses. The aim of this article is to provide an overview of the role and applications of cardiac biomarkers in risk stratification and prognostic assessment for patients with myocardial infarction. Although there is no ideal biomarker that can provide prognostic information for risk assessment in patients with AMI, the results obtained in recent years are promising. Several novel biomarkers related to the pathophysiological processes found in patients with myocardial infarction, such as inflammation, neurohormonal activation, myocardial stress, myocardial necrosis, cardiac remodeling and vasoactive processes, have been identified; they may bring additional value for AMI prognosis when included in multi-biomarker strategies. Furthermore, the use of artificial intelligence algorithms for risk stratification and prognostic assessment in these patients may have an extremely important role in improving outcomes.