GEAM Study Aims At Assessing the Role of Genetic Testing in Patients with Arrhythmic Myocarditis.

NCT06889662 | Recruiting

• 1 other identifier: GEAM
• Study Type: observational
• Target: 262
• Locations: 1 country
• Sites: 1

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.

Conditions

Myocarditis; Ventricular Arrythmia

Keywords

Arrhythmogenic cardiomyopathy; Ventricular arrhythmias; Myocardial inflammation

Outcome Measures

Primary Outcomes (8)

• To provide baseline characterization of VA in the study cohort.

  Prevalence of baseline VA

  Baseline

• To provide baseline characterization of VA in the study cohort.

  Type of VA

  baseline

• To provide baseline characterization of VA in the study cohort.

  Morphology of VA

  baseline

• To provide follow-up characterization of VA in study cohort.

  Occurrence of VA by 12 months

  12 months

• To provide follow-up characterization of VA in study cohort.

  Burden of VA (number of VA events per month)

  12 months

• To screen for CGVs in study groups

  Prevalence of CGVs in myocarditis with VA (VA+) vs. without VA (VA-)

  6 months

• To screen for CGVs in study groups vs healthy controls

  Prevalence of CGVs in myocarditis with VA (VA+) and without VA (VA-) vs. healthy controls

  6 months

• To investigate the pathophysiological basis of arrhythmic myocarditis in study group (exploratory endpoint)

  Comparison of gene expression profile on EMB in inflammatory group vs no inflammatory group

  during the procedure

Secondary Outcomes (8)

• To provide baseline characterization of VA according to sex

  Baseline

• To provide baseline characterization of VA according to sex

  baseline

• To provide baseline characterization of VA according to sex

  baseline

• To provide follow-up characterization of VA according to sex

  12 months

• To provide follow-up characterization of VA according to sex

  12 months

Study Arms (2)

VA+

with ventricular arrhythmias

VA-

without ventricular arrhythmias

Eligibility Criteria

• Age: 10 Years - 80 Years
• Sex: all
• Healthy Volunteers: Yes
• Age Groups: Child (0-17), Adult (18-64), Older Adult (65+)
• 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).

You may qualify if:

• 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

You may not qualify if:

• 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.

Sponsors & Collaborators

• Scientific Institute San Raffaele: lead

Study Sites (1)

Scientific Institute San Raffaele

Milan, Italy/Milan, 20132, Italy

RECRUITING

Related Publications (15)

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• Peretto G, Casella M, Merlo M, Benedetti S, Rizzo S, Cappelletto C, Di Resta C, Compagnucci P, De Gaspari M, Dello Russo A, Casari G, Basso C, Sala S, Sinagra G, Della Bella P, Cooper LT Jr. Inflammation on Endomyocardial Biopsy Predicts Risk of MACE in Undefined Left Ventricular Arrhythmogenic Cardiomyopathy. JACC Clin Electrophysiol. 2023 Jul;9(7 Pt 1):951-961. doi: 10.1016/j.jacep.2022.10.032. Epub 2023 Jan 18.

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  PMID: 25741868 BACKGROUND

• Peretto G, De Luca G, Villatore A, Di Resta C, Sala S, Palmisano A, Vignale D, Campochiaro C, Lazzeroni D, De Gaspari M, Rizzo S, Busnardo E, Ferro P, Gianolli L, Basso C, Dagna L, Esposito A, Benedetti S, Della Bella P. Multimodal Detection and Targeting of Biopsy-Proven Myocardial Inflammation in Genetic Cardiomyopathies: A Pilot Report. JACC Basic Transl Sci. 2023 Jul 5;8(7):755-765. doi: 10.1016/j.jacbts.2023.02.018. eCollection 2023 Jul.

  PMID: 37547072 BACKGROUND

• Peretto G, Sala S, Basso C, Rizzo S, Radinovic A, Frontera A, Limite LR, Paglino G, Bisceglia C, De Luca G, Campochiaro C, Sartorelli S, Palmisano A, Esposito A, Busnardo E, Villatore A, Baratto F, Cireddu M, Marzi A, D'Angelo G, Gulletta S, Vergara P, De Cobelli F, Dagna L, Mazzone P, Della Bella P. Inflammation as a Predictor of Recurrent Ventricular Tachycardia After Ablation in Patients With Myocarditis. J Am Coll Cardiol. 2020 Oct 6;76(14):1644-1656. doi: 10.1016/j.jacc.2020.08.012.

  PMID: 33004129 BACKGROUND

• Peretto G, Sala S, De Luca G, Marcolongo R, Campochiaro C, Sartorelli S, Tresoldi M, Foppoli L, Palmisano A, Esposito A, De Cobelli F, Rizzo S, Thiene G, Basso C, Dagna L, Caforio ALP, Della Bella P. Immunosuppressive Therapy and Risk Stratification of Patients With Myocarditis Presenting With Ventricular Arrhythmias. JACC Clin Electrophysiol. 2020 Oct;6(10):1221-1234. doi: 10.1016/j.jacep.2020.05.013. Epub 2020 Jun 24.

  PMID: 33092747 BACKGROUND

• Peretto G, Sala S, Rizzo S, Palmisano A, Esposito A, De Cobelli F, Campochiaro C, De Luca G, Foppoli L, Dagna L, Thiene G, Basso C, Della Bella P. Ventricular Arrhythmias in Myocarditis: Characterization and Relationships With Myocardial Inflammation. J Am Coll Cardiol. 2020 Mar 10;75(9):1046-1057. doi: 10.1016/j.jacc.2020.01.036.

  PMID: 32138965 BACKGROUND

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  PMID: 36970396 BACKGROUND

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  PMID: 36175056 BACKGROUND

• Peretto G, Sala S, Rizzo S, De Luca G, Campochiaro C, Sartorelli S, Benedetti G, Palmisano A, Esposito A, Tresoldi M, Thiene G, Basso C, Della Bella P. Arrhythmias in myocarditis: State of the art. Heart Rhythm. 2019 May;16(5):793-801. doi: 10.1016/j.hrthm.2018.11.024. Epub 2018 Nov 24.

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  PMID: 23824828 BACKGROUND

MeSH Terms

Conditions

Myocarditis

Condition Hierarchy (Ancestors)

Cardiomyopathies; Heart Diseases; Cardiovascular Diseases

Study Officials

• Paolo Della Bella, MD

  Scientific Institute San Raffaele, Milan, Italy

  STUDY CHAIR

Central Study Contacts

Giovanni Peretto, Medical Doctor, PhD

CONTACT

39+ 0226437340; peretto.giovanni@gmail.com

Study Design

• Study Type: observational
• Observational Model: CASE CONTROL
• Time Perspective: OTHER
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: Medical Doctor, PhD, Principal Investigator

Study Record Dates

• First Submitted: February 6, 2025
• First Posted: March 21, 2025
• Study Start: February 25, 2025
• Primary Completion (Estimated): September 1, 2027
• Study Completion (Estimated): December 1, 2027
• Last Updated: March 21, 2025

Record last verified: 2025-02

Locations

IT (1)