Ignite Creation Date:
2024-05-06 @ 8:25 PM
Last Modification Date:
2024-10-26 @ 3:27 PM
Study NCT ID:
NCT06376552
Status:
COMPLETED
Last Update Posted:
2024-04-19
First Post:
2024-04-16
Brief Title:
Artificial Intelligence for the Prioritization of Genetic Background in Brugada Syndrome
Sponsor:
IRCCS San Raffaele
Organization:
IRCCS San Raffaele
Study Overview
Official Title:
The Use of Artificial Intelligence for the Prioritization of Causative Genetic Background in a Brugada Syndrome Cohort an Observational Retrospective Study
Status:
COMPLETED
Status Verified Date:
2024-04
Last Known Status:
None
Delayed Posting:
No
If Stopped, Why?:
Not Stopped
Has Expanded Access:
False
If Expanded Access, NCT#:
N/A
Has Expanded Access, NCT# Status:
N/A
Acronym:
AI4Cardio
Brief Summary:
Brugada Syndrome BS is an inherited heart condition that can cause sudden cardiac arrest in young individuals Its 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
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 15000 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
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 Oversight
Has Oversight DMC:
None
Is a FDA Regulated Drug?:
False
Is a FDA Regulated Device?:
False
Is an Unapproved Device?:
None
Is a PPSD?:
None
Is a US Export?:
None
Is an FDA AA801 Violation?:
None