Loading clinical trials...
Loading clinical trials...
GEAM: Yield of GEnetic Testing in Arrhythmic Myocarditis
This study aims to answer multiple unsolved questions in the field of arrhythmic myocarditis. * Improving the diagnostic work-up. While endomyocardial biopsy (EMB) and cardiac magnetic resonance (CMR) constitute the gold standard diagnostic techniques for myocarditis, the role of genetic testing is still unclear. Identifying the subset of patients with CGVs, will contribute to justifying the application of genetic testing in myocarditis. * Generating models for risk prediction. Outcomes and arrhythmic risk stratification remain uncertain for myocarditis. Based on an advanced multimodal work-up, multiparametric risk scores may be created and subsequently validated, in order to predict the arrhythmic risk of specific myocarditis, especially in the case of CGVs. * Identifying disease-specific and genotype-specific signatures. Genotype-phenotype associations are expected to benefit from a multimodal and multiparametric approach, in order to allow etiology-specific features in arrhythmic myocarditis. Most of the current signatures are limited to combined EMB-CMR studies. Signatures would likely benefit from implementing additional parameters, including arrhythmia features and myocardial inflammatory status. * Tailoring treatment strategies. Transcriptional analysis will identify overexpressed genes associated with myocarditis and arrhythmias, representing a possible therapeutic target. A multimodal and multidisciplinary model will integrate phenotype, genotype, and transcriptional profile for a personalized treatment.
Arrhythmic myocarditis is responsible for a significant proportion of out-of-hospital cardiac arrest and death in the young population. Although considered an uncommon feature, arrhythmias may present in myocarditis in both acute and chronic phase, leading to sudden cardiac death (SCD), especially in young males. Overall, the prevalence of undiagnosed myocarditis in post-mortem series ranges from 9% to 44%, involving 2% of infants, 5% of children, and 4-8% of athletes \<40-year-old. Ventricular arrhythmias (VAs) are reported secondary to lymphocytic myocarditis. However, they are more commonly associated with giant cell myocarditis (GCM) and cardiac sarcoidosis (CS), with prevalence of 29% and 55%, respectively In addition, genetically-determined susceptibility might underlie arrhythmic myocarditis. First, recent reports suggest that pathogenic variants in genes associated with nonischemic cardiomyopathies (NICM), hereby defined as cardiomyopathic gene variants (CGVs) are frequently found in patients with myocarditis proven by CMR and/or EMB, complicated by ventricular arrhythmias (VA). NICM constitute a heterogeneous group of diseases characterized by distinct structural and functional myocardial abnormalities in the absence of obstructive epicardial coronary artery disease. The main NICM overlapping with myocarditis are dilated (DCM) and arrhythmogenic cardiomyopathy (ACM). Second, myocardial inflammation (M-Infl) has also been recently described in NICM complicated by arrhythmias. Preclinical data support a relevant role of M-Infl in the pathophysiology of AINICM, and its association with adverse outcomes. Furthermore, there is a growing interest in transcriptomics in the setting of inflammatory and genetic cardiomyopathies. Cardiac transcriptome revealed specific subgroups of patients with early and overt DCM. In animal models of experimental autoimmune myocarditis, transcriptomics, transcriptomics allowed to depict the single-cell landscape of the cardiac immune cells in different phases of the disease. The addition of the cardiac transcriptome to the genotype and phenotype of patients increases the possibility for individualized medicine.
Age
10 - 80 years
Sex
ALL
Healthy Volunteers
Yes
Scientific Institute San Raffaele
Milan, Italy/Milan, Italy
Start Date
February 25, 2025
Primary Completion Date
September 1, 2027
Completion Date
December 1, 2027
Last Updated
March 21, 2025
262
ESTIMATED participants
Lead Sponsor
Scientific Institute San Raffaele
Data Source & Attribution
This clinical trial information is sourced from ClinicalTrials.gov, a service of the U.S. National Institutes of Health.
Modifications: This data has been reformatted for display purposes. Eligibility criteria have been parsed into inclusion/exclusion sections. Location data has been geocoded to enable distance-based search. For the authoritative and most current information, please visit ClinicalTrials.gov.
Neither the United States Government nor Clareo Health make any warranties regarding the data. Check ClinicalTrials.gov frequently for updates.
View ClinicalTrials.gov Terms and ConditionsNCT07354646