Brugada SyndromeAI4CardioNCT06376552
Artificial Intelligence for the Prioritization of Genetic Background in Brugada Syndrome
An observational study of Brugada Syndrome, run by IRCCS San Raffaele at 2 sites in Italy.
Trial 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). Read more about this study
- Who is it for?
- Ages 18 years and older
- Conditions the study is for
- Brugada Syndrome
- How many people
- 200 participants
- Where
- 2 sitesItaly
- Study dates
- 19 Dec 2018to 6 Jun 2022
- Phase
- Observational
- Are there results?
- None posted in the registry
Key requirements
Who can take part, as listed by the sponsor. Only the study team can confirm whether you are eligible, so take this list to your doctor.
- Ages 18 years and older
- All sexes
- No healthy volunteers
- Adult, Older adult
Study population: 200 BS patients.
Who may be able to join
- 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.
Who cannot join
- 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.
Trial locations and contacts
2 sites in 1 country.
About this study
Official title: 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.
Read the 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.
- Conditions
- Brugada Syndrome
- Medical subject headings
- Brugada Syndrome
What participants receive
What participants receive. In a randomised study each person is assigned to one group by chance.
| Study group | Role | What they receive |
|---|---|---|
| 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 being measured
The primary outcome is the main question the study is designed to answer.
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.
Measured: 1 year
Secondary outcomes (1)
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.
Measured: 1 year
Timeline
From the start of the study to its completion; the mark is today. Estimated dates are the sponsor’s plan.
- First posted19 Apr 2024
- Study start19 Dec 2018
- Primary completion6 Jun 2022
- Study completion6 Jun 2022
Resources
- Official record on ClinicalTrials.govThe registry entry this page is built from, with its full change history.
- Publications (3)Papers the sponsor has linked to this study.
- Other trials for Brugada SyndromeStudies of the same condition, open and under way.
- More trials run by IRCCS San RaffaeleThe sponsor's other registered studies.
- What the trial phases meanHow a treatment moves from first tests in people to approval.
More details
For doctors and researchers: how the study is designed, who runs it, and its registry IDs.
Study design
- Study type
- Observational
- Observational model
- Cohort
- Time perspective
- Retrospective
- Enrolment
- 200 participants (actual)
Sponsor and investigators
- Lead sponsor
- IRCCS San Raffaele
- Sponsor type
- University, hospital or other
- Responsible party
- Principal investigator, Chiara Di Resta, IRCCS San Raffaele
- Investigators
- Chiara Di Resta, PhD, Principal investigator, IRCCS San Raffaele Hospital
IDs, dates and publications
- ClinicalTrials.gov ID
- NCT06376552
- Sponsor's protocol ID
- AI4Cardio
- Acronym
- AI4Cardio
- Status last verified
- Apr 2024
- First submitted
- 16 Apr 2024
- Last updated
- 19 Apr 2024
- Results posted
- No
- Data monitoring committee
- No
- FDA-regulated drug
- No
- FDA-regulated device
- No
- Individual data sharing
- Undecided
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.
PubMed 26220970Sommariva 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.
PubMed 23321620Di 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.
PubMed 36292641
Study at a glance
From the registry record, last updated by the sponsor on 19 Apr 2024. Recruitment status is as the sponsor reported it: confirm with the study team.
- Official title
- The Use of Artificial Intelligence for the Prioritization of Causative Genetic Background in a Brugada Syndrome Cohort: an Observational Retrospective Study
- ClinicalTrials.gov ID
- NCT06376552
- Acronym / sponsor ID
- AI4Cardio / AI4Cardio
- Conditions
- Brugada Syndrome
- Study type
- Observational
- Recruitment status
- Completed
- Enrolment
- 200 participants (actual)
- Lead sponsor
- IRCCS San RaffaeleUniversity, hospital or other
- Study start
- 19 Dec 2018 (actual)
- Primary completion
- 6 Jun 2022 (actual)
- Study completion
- 6 Jun 2022 (actual)
- First posted
- 19 Apr 2024 (actual)
- Results
- Not posted in the source record
Clinical summary
The research question as the sponsor registered it. This describes what the study plans to test, not what it found.
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.
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 design
- Observational model
- Cohort
- Time perspective
- Retrospective
- Number of arms
- 1
| Arm | Type | Receives |
|---|---|---|
| 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. |
Who may qualify
- Ages
- 18 years and older
- Sex
- All
- Healthy volunteers
- Not accepted
- Age groups
- Adult, Older adult
- Study population
- 200 BS patients.
Key inclusion criteria (1 listed)
- 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.
Key exclusion criteria (1 listed)
- 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.
Eligibility is decided by the study team after screening; this overview does not establish that a patient qualifies. Full inclusion and exclusion criteria.
Primary outcome
New candidate genes, likely associated with Brugada Syndrome using an AI based approach.
Time frame: 1 year
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 secondary outcome
Identification of genetic risk factors associated with the worse phenotype.
Time frame: 1 year
Results and safety
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
Research links
- Official record on ClinicalTrials.govLast updated by the sponsor 19 Apr 2024.
- Background: PubMed 26220970Di 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.
- Background: PubMed 23321620Sommariva 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.
- Background: PubMed 36292641Di 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.
- Individual participant dataSharing planned: Undecided
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Referral and contact
AzTrials does not enrol participants or take referrals. Contact the study team or a site listed below; they decide who can take part. This study is not recruiting at the moment.
Chiara Di Resta, PhD principal investigator
IRCCS San Raffaele Hospital
2 sites in 1 country: see every site and its status.
Questions about this trial
What is this clinical trial studying?
An observational study of Brugada Syndrome, run by IRCCS San Raffaele at 2 sites in Italy.
The full registered description is in the About this study section and the official record.
Who may be eligible to take part?
The sponsor lists 1 inclusion and 1 exclusion criteria. Eligibility is decided by the study team after screening, so read the full criteria and contact a listed site.
Is this clinical trial currently recruiting?
The record says: finished, as of the sponsor's last update on 19 Apr 2024. Status can change between updates, so confirm with the study contact before making plans.
Where is the study taking place?
The record lists 2 sites in Italy. Whether a site is taking part right now should be confirmed with that site. See every site.
What are the possible benefits and risks?
They depend on the study and the treatment, and no study can promise a benefit. The study team explains the known risks during informed consent, before anyone joins; the record itself does not list them.
Are results available for this study?
The study is completed, but results are not available in the source record. That does not mean the treatment did or did not work.
How can a doctor refer a patient or contact the research team?
The record lists no contact. The official record names the sponsor, who can be asked directly. AzTrials does not enrol participants or take referrals.
What does the primary outcome measure?
New candidate genes, likely associated with Brugada Syndrome using an AI based approach. (time frame: 1 year). It is what the study was designed to measure, not a finding.
Where can I read the original study information?
On the ClinicalTrials.gov record for NCT06376552, which also lists 3 linked publications.
Does a listing mean the treatment is approved or proven to work?
No. A listing means the study is registered. It does not show that the treatment is safe, works, or is approved by a regulator.
How often is this information updated?
AzTrials copies changed records from ClinicalTrials.gov every night and reloads the whole registry every week. The sponsor last updated this record on 19 Apr 2024.