Artificial Intelligence for the Prioritization of Genetic Background in Brugada Syndrome (AI4Cardio)

The Use of Artificial Intelligence for the Prioritization of Causative Genetic Background in a Brugada Syndrome Cohort: an Observational Retrospective Study

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.

Study Overview

• Status: Completed
• Conditions: Brugada Syndrome

Detailed Description

Brugada Syndrome (BS) is an inherited cardiac electrical disorder that can cause syncope and sudden cardiac arrest in young asymptomatic individuals. It is suspected to contribute to 4-12% of cases of sudden cardiac death in the general population. Diagnosis relies on identifying a type I ECG pattern characterized by ST-segment elevation with a coved morphology in the right precordial leads. The prevalence in Western countries is estimated at 1:5000. Currently, implantation of a cardioverter defibrillator (ICD) is the only treatment option, but risk stratification guidelines remain incomplete, particularly for asymptomatic individuals.

BS is inherited as an autosomal dominant trait with incomplete penetrance. While 23 genes have been associated with BS susceptibility, 70% of patients remain genetically uncharacterized, suggesting a more complex inheritance pattern. Genetics have not been incorporated into risk stratification guidelines, despite evidence linking certain genetic variants to higher arrhythmic risk. This knowledge gap underscores the importance of expanding our understanding of BS genetics to enhance diagnostic sensitivity and patient management.

This protocol builds upon preliminary data from a study granted by the Italian Ministry of Health (GR-2016-02362316), in which next-generation sequencing (NGS) was used to investigate the entire coding regions (Whole Exome Sequencing_WES) of 200 BS patients. The study aimed to identify new BS candidate genes and characterize the genetic basis of the condition.

The cohort was selected based on the presence of a type I ECG, confirmed either spontaneously or induced by flecainide or ajmaline. Patients underwent thorough cardiac evaluations to rule out other conditions. Follow-up included yearly assessments and more frequent evaluations for patients with a higher risk of ventricular tachycardia.

A large number of genetic variants were identified by exploiting WES, prompting the use of Artificial Intelligence (AI) to prioritize the sequencing data. AI techniques, including advanced algorithms and machine learning, can streamline the identification of potentially disease-causing genetic variations by filtering out common variants, predicting pathogenicity, and integrating clinical data.

Given that over 70% of BS patients remain genetically undiagnosed, high-throughput sequencing approaches are crucial for a comprehensive understanding of BS genetics. This study aims to contribute to the identification of new genetic factors and improve risk stratification for affected patients. All sequencing data for this project have been generated and will be analyzed using AI, with no further patients to be enrolled or sequenced.

• Study Type: Observational
• Enrollment (Actual): 200

Contacts and Locations

Study Locations

• Italy
  • Milan, Italy, 20132
    • IRCCS San Raffaele
  • Milan, Italy
    • Milano-Bicocca University

Participation Criteria

Eligibility Criteria

• Ages Eligible for Study: Adult; Older Adult
• Accepts Healthy Volunteers: No

• Sampling Method: Non-Probability Sample

Study Population

200 BS patients.

Description

Inclusion Criteria:

• 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.

Exclusion Criteria:

• No exclusion criteria are adopted for this study. The entire previously sequenced cohort of 200 BS patients will be investigated and considered, exploiting AI approach for the prioritization of the sequencing available data.

Study Plan

How is the study designed?

Number of groups / cohorts

1

Cohorts and Interventions

Group / Cohort

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.

What is the study measuring?

Primary Outcome Measures

Outcome Measure	Measure Description	Time Frame
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 Outcome Measures

Outcome Measure	Measure Description	Time Frame
Identification of genetic risk factors associated with the worse phenotype.	Correlation of the new putative genes and the clinical variables, previously collected in a comprehensive database for this study.	1 year

Collaborators and Investigators

• Sponsor: IRCCS San Raffaele
• Investigators: Principal Investigator: Chiara Di Resta, PhD, IRCCS San Raffaele Hospital

Publications and helpful links

General Publications

• 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.
• 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.
• 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.

Study record dates

Study Major Dates

• Study Start (Actual): December 19, 2018
• Primary Completion (Actual): June 6, 2022
• Study Completion (Actual): June 6, 2022

Study Registration Dates

• First Submitted: April 16, 2024
• First Submitted That Met QC Criteria: April 18, 2024
• First Posted (Actual): April 19, 2024

Study Record Updates

• Last Update Posted (Actual): April 19, 2024
• Last Update Submitted That Met QC Criteria: April 18, 2024
• Last Verified: April 1, 2024

More Information

Terms related to this study

• Additional Relevant MeSH Terms: Pathologic Processes; Heart Diseases; Cardiovascular Diseases; Disease; Genetic Diseases, Inborn; Arrhythmias, Cardiac; Cardiac Conduction System Disease; Syndrome; Brugada Syndrome
• Other Study ID Numbers: AI4Cardio

Plan for Individual participant data (IPD)

• Plan to Share Individual Participant Data (IPD)?: UNDECIDED

Drug and device information, study documents

• Studies a U.S. FDA-regulated drug product: No
• Studies a U.S. FDA-regulated device product: No