Artificial Intelligence for the Prioritization of Genetic Background in Brugada Syndrome

NCT06376552 | Completed

• 1 other identifier: AI4Cardio
• Study Type: observational
• Target: 200
• Locations: 1 country
• Sites: 2

Brief Summary

Brugada Syndrome (BS) is an inherited heart condition that can cause sudden cardiac arrest in young individuals. It's diagnosed through specific changes seen on an electrocardiogram (ECG). Currently, the only treatment option is a cardioverter defibrillator (ICD). Despite advances, much about BS remains unclear, including its genetic basis. This study aims to use advanced genetic sequencing and artificial intelligence to uncover new genetic factors contributing to BS. By understanding these factors better, we hope to improve risk assessment and treatment for affected individuals.

Conditions

Brugada Syndrome

Outcome Measures

Primary Outcomes (1)

• New candidate genes, likely associated with Brugada Syndrome using an AI based approach.

  Prioritization of genetic variations underlying the BS phenotype: the whole exome data of 200 BS previously sequenced will be prioritized using an AI- based approach, developed by the collaborators in UniMIB.

  1 year

Secondary Outcomes (1)

• Identification of genetic risk factors associated with the worse phenotype.

  1 year

Study Arms (1)

BrS Patients

The 200 BS patients have been selected and clinically evaluated by Department of Cardiac Electrophysiology and Arrhythmology, San Raffaele Hospital, for the presence of a type I electrocardiogram (ECG), either spontaneous or induced by flecainide or ajmaline. Morphologic and functional characteristics of the heart have been analysed in all patients by trans-thoracic echocardiography and stress test to rule out patients with Arrhythmogenic Right Ventricular Dysplasia and ischemic heart disease. Among clinical characteristics, 12-lead signal averaged ECG parameters and all possible risk factors have been evaluated. Electrophysiological study has been performed in spontaneous BS pattern 1 ECG patients or patients with induced BS pattern 1 ECG and at least one risk factor. In patients with higher susceptibility for the induced Ventricular Tachycardia, ICD has been implanted.

Eligibility Criteria

• Age: 18 Years+
• Sex: all
• Healthy Volunteers: No
• Age Groups: Adult (18-64), Older Adult (65+)
• Sampling Method: Non-Probability Sample

Study Population

200 BS patients.

You may qualify if:

• The 200 BS patients have been selected and clinically evaluated based on the presence of a type I electrocardiogram (ECG), either spontaneous or induced by flecainide or ajmaline.

Sponsors & Collaborators

• IRCCS San Raffaele: lead

Study Sites (2)

IRCCS San Raffaele

Milan, 20132, Italy

Location

Milano-Bicocca University

Milan, Italy

Location

Related Publications (3)

• Di Resta C, Pietrelli A, Sala S, Della Bella P, De Bellis G, Ferrari M, Bordoni R, Benedetti S. High-throughput genetic characterization of a cohort of Brugada syndrome patients. Hum Mol Genet. 2015 Oct 15;24(20):5828-35. doi: 10.1093/hmg/ddv302. Epub 2015 Jul 28.

  PMID: 26220970 BACKGROUND

• Sommariva E, Pappone C, Martinelli Boneschi F, Di Resta C, Rosaria Carbone M, Salvi E, Vergara P, Sala S, Cusi D, Ferrari M, Benedetti S. Genetics can contribute to the prognosis of Brugada syndrome: a pilot model for risk stratification. Eur J Hum Genet. 2013 Sep;21(9):911-7. doi: 10.1038/ejhg.2012.289. Epub 2013 Jan 16.

  PMID: 23321620 BACKGROUND

• Di Resta C, Berg J, Villatore A, Maia M, Pili G, Fioravanti F, Tomaiuolo R, Sala S, Benedetti S, Peretto G. Concealed Substrates in Brugada Syndrome: Isolated Channelopathy or Associated Cardiomyopathy? Genes (Basel). 2022 Sep 28;13(10):1755. doi: 10.3390/genes13101755.

  PMID: 36292641 BACKGROUND

Biospecimen

Retention: SAMPLES WITH DNA

whole blood

MeSH Terms

Conditions

Brugada Syndrome

Condition Hierarchy (Ancestors)

Arrhythmias, Cardiac; Heart Diseases; Cardiovascular Diseases; Cardiac Conduction System Disease; Genetic Diseases, Inborn; Congenital, Hereditary, and Neonatal Diseases and Abnormalities

Study Officials

• Chiara Di Resta, PhD

  IRCCS San Raffaele Hospital

  PRINCIPAL INVESTIGATOR

Study Design

• Study Type: observational
• Observational Model: COHORT
• Time Perspective: RETROSPECTIVE
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PhD

Study Record Dates

• First Submitted: April 16, 2024
• First Posted: April 19, 2024
• Study Start: December 19, 2018
• Primary Completion: June 6, 2022
• Study Completion: June 6, 2022
• Last Updated: April 19, 2024

Record last verified: 2024-04

Locations

IT (2)