Clinical trial NCT06889662: GEAM Study Aims At Assessing the Role of Genetic Testing in Patients with Arrhythmic Myocarditis.
Official title: GEAM: Yield of GEnetic Testing in Arrhythmic Myocarditis
Study type: OBSERVATIONAL
Overall status: RECRUITING
Conditions: Myocarditis
Ventricular Arrythmia
Keywords: Arrhythmogenic cardiomyopathy
Ventricular arrhythmias
Myocardial inflammation
Lead sponsor: Scientific Institute San Raffaele
Sponsor class: OTHER
First posted: 2025-03-21
Enrollment: 262
Sex: ALL
Minimum age (years): 10
Maximum age (years): 80
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Observational model: CASE_CONTROL
Time perspective: OTHER
Sampling method: PROBABILITY_SAMPLE
Study population: Statistical analyses will be performed by certified programs (i.e. SPSS, R). For risk stratification, conventional statistical methods, including Kaplan-Meier survival analysis, univariable and multivariable logistic regression, Cox regression model, and mixed models will be used. In addition, machine learning and artificial intelligence will be applied for the setting-up of cost-effective prediction models. The best indexes for descriptive statistics, as well as optimal tests for comparing quantitative and qualitative variables, will be chosen depending on the distribution of data, as appropriate. Confidence intervals will be set at 95%. Statistical significance threshold will be set at p \<0.05 (two-sided).

Brief summary: 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.

Detailed description: 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.

Eligibility criteria: Inclusion Criteria:

Patients with ventricular arrhythmias (VA+) and without (VA-)

* Diagnosis of myocarditis proven by EMB (ESC criteria) and/or CMR (updated Lake Louise criteria)
* Age ≥ 10 years
* Baseline ECG telemonitoring
* Written informed consent Healthy controls
* Provided a negative known history of myocarditis
* The sample must have been biobanked as part of the study IMMUNORADAR

Exclusion Criteria:

Patients with ventricular arrhythmias (VA+) and without (VA-)

* Obstructive coronary artery disease, or lack of coronary angiography/computed tomography (CT) scan in patients \>40 years.
* Absent informed consent.

Primary outcomes:
measure: To provide baseline characterization of VA in the study cohort.
timeFrame: Baseline
measure: To provide baseline characterization of VA in the study cohort.
timeFrame: baseline
measure: To provide baseline characterization of VA in the study cohort.
timeFrame: baseline
measure: To provide follow-up characterization of VA in study cohort.
timeFrame: 12 months
measure: To provide follow-up characterization of VA in study cohort.
timeFrame: 12 months
measure: To screen for CGVs in study groups
timeFrame: 6 months
measure: To screen for CGVs in study groups vs healthy controls
timeFrame: 6 months
measure: To investigate the pathophysiological basis of arrhythmic myocarditis in study group (exploratory endpoint)
timeFrame: during the procedure
Secondary outcomes:
measure: To provide baseline characterization of VA according to sex
timeFrame: Baseline
measure: To provide baseline characterization of VA according to sex
timeFrame: baseline
measure: To provide baseline characterization of VA according to sex
timeFrame: baseline
measure: To provide follow-up characterization of VA according to sex
timeFrame: 12 months
measure: To provide follow-up characterization of VA according to sex
timeFrame: 12 months
measure: To screen for CGVs in study groups
timeFrame: 6 months
measure: To screen for CGVs in study groups vs healthy controls
timeFrame: 6 months
measure: To investigate the pathophysiological basis of arrhythmic myocarditis according to sex (exploratory endpoint)
timeFrame: during the procedure
Other outcomes:
Locations:
city: Milan
country: Italy
facility: Scientific Institute San Raffaele
state: Italy/Milan
Study officials:
affiliation: Scientific Institute San Raffaele, Milan, Italy
name: Paolo Della Bella, MD
role: STUDY_CHAIR
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