Genetic Testing in Brugada Syndrome: A 30-Year Experience.

BACKGROUND: A pathogenic/likely pathogenic variant can be found in 20% to 25% of patients with Brugada syndrome (BrS) and a pathogenic/likely pathogenic variant in SCN5A is associated with a worse prognosis. The aim of this study is to define the diagnostic yield of a large gene panel with American College of Medical Genetics and Genomics variant classification and to assess prognosis of SCN5A and non-SCN5A variants. METHODS: All patients with BrS, were prospectively enrolled in the Universitair Ziekenhuis Brussel registry between 1992 and 2022. Inclusion criteria for the study were (1) BrS diagnosis; (2) genetic analysis performed with a large gene panel; (3) classification of variants following American College of Medical Genetics and Genomics guidelines. Patients with a pathogenic/likely pathogenic variant in SCN5A were defined as SCN5A+. Patients with a reported variant in a non-SCN5A gene or with no reported variants were defined as patients with SCN5A-. All variants were classified as missense or predicted loss of function. RESULTS: A total of 500 BrS patients were analyzed. A total of 104 patients (20.8%) were SCN5A+ and 396 patients (79.2%) were SCN5A-. A non-SCN5A gene variant was found in 75 patients (15.0%), of whom, 58 patients (77.3%) had a missense variant and 17 patients (22.7%) had a predicted loss of function variant. At a follow-up of 84.0 months, 48 patients (9.6%) experienced a ventricular arrhythmia (VA). Patients without any variant had higher VA-free survival, compared with carriers of a predicted loss of function variant in SCN5A+ or non-SCN5A genes. There was no difference in VA-free survival between patients without any variant and missense variant carriers in SCN5A+ or non-SCN5A genes. At Cox analysis, SCN5A+ or non-SCN5A predicted loss of function variant was an independent predictor of VA. CONCLUSIONS: In a large BrS cohort, the yield for SCN5A+ is 20.8%. A predicted loss of function variant carrier is an independent predictor of VA.

Genetics in Probands With Idiopathic Ventricular Fibrillation: A Multicenter Study.

BACKGROUND: Different genes have been associated with idiopathic ventricular fibrillation (IVF); however, there are no studies correlating genotype with phenotype. OBJECTIVES: The aim of this study was to define the genetic background of probands with IVF using large gene panel analysis and to correlate genetics with long-term clinical outcomes. METHODS: All consecutive probands with a diagnosis of IVF were included in a multicenter retrospective study. All patients had: 1) IVF diagnosis throughout the follow-up; and 2) genetic analysis with a broad gene panel. All genetic variants were classified as pathogenic/likely pathogenic (P+), variants of unknown significance (VUS) or no variants (NO-V), following current guidelines of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology. The primary endpoint was occurrence of ventricular arrhythmias (VA). RESULTS: Forty-five consecutive patients were included. A variant was found in 12 patients, 3 P+ and 9 VUS carriers. After a mean follow-up time of 105.0 months, there were no deaths and 16 patients (35.6%) experienced a VA. NO-V patients had higher VA free survival during the follow-up, compared with both VUS (72.7% vs 55.6%, log-rank P < 0.001) and P+ (72.7% vs 0%, log-rank P = 0.013). At Cox analysis, P+ or VUS carrier status was a predictor of VA occurrence. CONCLUSIONS: In probands with IVF, undergoing genetic analysis with a broad panel, the diagnostic yield for P+ is 6.7%. P+ or VUS carrier status is a predictor of VA occurrence.

Genetic testing in children with Brugada syndrome: results from a large prospective registry.

AIMS: A pathogenic/likely pathogenic (P/LP) variant in SCN5A is found in 20-25% of patients with Brugada syndrome (BrS). However, the diagnostic yield and prognosis of gene panel testing in paediatric BrS is unclear. The aim of this study is to define the diagnostic yield and outcomes of SCN5A gene testing with ACMG variant classification in paediatric BrS patients compared with adults. METHODS AND RESULTS: All consecutive patients diagnosed with BrS, between 1992 and 2022, were prospectively enrolled in the UZ Brussel BrS registry. Inclusion criteria were: (i) BrS diagnosis; (ii) genetic analysis performed with a large gene panel; and (iii) classification of gene variants following ACMG guidelines. Paediatric patients were defined as ≤16 years of age. The primary endpoint was ventricular arrhythmias (VAs). A total of 500 BrS patients were included, with 63 paediatric patients and 437 adult patients. Among children with BrS, 29 patients (46%) had a P/LP variant (P+) in SCN5A and no variants were found in 34 (54%) patients (P-). After a mean follow-up of 125.9 months, 8 children (12.7%) experienced a VA, treated with implanted cardioverter defibrillator shock. At survival analysis, P- paediatric patients had higher VA-free survival during the follow-up, compared with P+ paediatric patients. P+ status was an independent predictor of VA. There was no difference in VA-free survival between paediatric and adult BrS patients for both P- and P+. CONCLUSION: In a large BrS cohort, the diagnostic yield for P/LP variants in the paediatric population is 46%. P+ children with BrS have a worse arrhythmic prognosis.

EDIR: exome database of interspersed repeats.

MOTIVATION: Intragenic exonic deletions are known to contribute to genetic diseases and are often flanked by regions of homology. RESULTS: In order to get a more clear view of these interspersed repeats encompassing a coding sequence, we have developed EDIR (Exome Database of Interspersed Repeats) which contains the positions of these structures within the human exome. EDIR has been calculated by an inductive strategy, rather than by a brute force approach and can be queried through an R/Bioconductor package or a web interface allowing the per-gene rapid extraction of homology-flanked sequences throughout the exome. AVAILABILITY AND IMPLEMENTATION: The code used to compile EDIR can be found at https://github.com/lauravongoc/EDIR. The full dataset of EDIR can be queried via an Rshiny application at http://193.70.34.71:3857/edir/. The R package for querying EDIR is called 'EDIRquery' and is available on Bioconductor. The full EDIR dataset can be downloaded from https://osf.io/m3gvx/ or http://193.70.34.71/EDIR.tar.gz. SUPPLEMENTARY INFORMATION: Supplementary data are available at Bioinformatics online.