Cardiac conduction disorders in young adults: Clinical characteristics and genetic background of an underestimated population.

BACKGROUND: Cardiac conduction disorder (CCD) in patients <50 years old is a rare and mostly unknown condition. OBJECTIVE: We aimed to assess clinical characteristics and genetic background of patients <50 years old with CCD of unknown origin. METHODS: We retrospectively reviewed a consecutive series of patients with a diagnosis of CCD before the age of 50 years referred to our center between January 2019 and December 2021. Patients underwent complete clinical examination and genetic evaluation. RESULTS: We enrolled 39 patients with a median age of 40 years (28-47 years) at the onset of symptoms. A cardiac implantable electronic device was implanted in 69% of the patients. In 15 of 39 CCD index patients (38%), we found a total of 13 different gene variations (3 pathogenic, 6 likely pathogenic, and 4 variants of uncertain significance), mostly in 3 genes (SCN5A, TRPM4, and LMNA). In our cohort, genetic testing led to the decision to implant an implantable cardioverter-defibrillator in 2 patients for the increased risk of sudden cardiac death. CONCLUSION: Patients with the occurrence of CCD before the age of 50 years present with a high rate of pathologic gene variations, mostly in 3 genes (SCN5A, TRPM4, and LMNA). The presence of pathogenic variations may add information about the prognosis and lead to an individualized therapeutic approach.

SCN5A mutation is associated with a higher Shanghai Score in patients with type 1 Brugada ECG pattern.

AIMS: Brugada syndrome (BrS) is an inherited arrhythmic disease characterized by a coved ST-segment elevation in the right precordial electrocardiogram leads (type 1 ECG pattern) and is associated with a risk of malignant ventricular arrhythmias and sudden cardiac death. In order to assess the predictive value of the Shanghai Score System for the presence of a SCN5A mutation in clinical practice, we studied a cohort of 125 patients with spontaneous or fever/drug-induced BrS type 1 ECG pattern, variably associated with symptoms and a positive family history. METHODS: The Shanghai Score System items were collected for each patient and PR and QRS complex intervals were measured. Patients were genotyped through a next-generation sequencing (NGS) custom panel for the presence of SCN5A mutations and the common SCN5A polymorphism (H558R). RESULTS: The total Shanghai Score was higher in SCN5A+ patients than in SCN5A- patients. The 81% of SCN5A+ patients and the 100% of patients with a SCN5A truncating variant exhibit a spontaneous type 1 ECG pattern. A significant increase in PR (P = 0.006) and QRS (P = 0.02) was detected in the SCN5A+ group. The presence of the common H558R polymorphism did not significantly correlate with any of the items of the Shanghai Score, nor with the total score of the system. CONCLUSION: Data from our study suggest the usefulness of Shanghai Score collection in clinical practice in order to maximize genetic test appropriateness. Our data further highlight SCN5A mutations as a cause of conduction impairment in BrS patients.

Ethnicity-related DMD Genotype Landscapes in European and Non-European Countries.

OBJECTIVE: Genetic diagnosis and mutation identification are now compulsory for Duchenne (DMD) and Becker muscular dystrophies (BMD), which are due to dystrophin (DMD) gene mutations, either for disease prevention or personalized therapies. To evaluate the ethnic-related genetic assortments of DMD mutations, which may impact on DMD genetic diagnosis pipelines, we studied 328 patients with DMD and BMD from non-European countries. METHODS: We performed a full DMD mutation detection in 328 patients from 10 Eastern European countries (Poland, Hungary, Lithuania, Romania, Serbia, Croatia, Bosnia, Bulgaria, Ukraine, and Russia) and 2 non-European countries (Cyprus and Algeria). We used both conventional methods (multiplex ligation-dependent probe amplification [MLPA] followed by gene-specific sequencing) and whole-exome sequencing (WES) as a pivotal study ran in 28 patients where DMD mutations were already identified by standard techniques. WES output was also interrogated for DMD gene modifiers. RESULTS: We identified DMD gene mutations in 222 male patients. We identified a remarkable allele heterogeneity among different populations with a mutation landscape often country specific. We also showed that WES is effective for picking up all DMD deletions and small mutations and its adoption could allow a detection rate close to 90% of all occurring mutations. Gene modifiers haplotypes were identified with some ethnic-specific configurations. CONCLUSIONS: Our data provide unreported mutation landscapes in different countries, suggesting that ethnicity may orient genetic diagnosis flowchart, which can be adjusted depending on the mutation type frequency, with impact in drug eligibility.

The Genetic Landscape of Dystrophin Mutations in Italy: A Nationwide Study.

Dystrophinopathies are inherited diseases caused by mutations in the dystrophin (DMD) gene for which testing is mandatory for genetic diagnosis, reproductive choices and eligibility for personalized trials. We genotyped the DMD gene in our Italian cohort of 1902 patients (BMD n = 740, 39%; DMD n =1162, 61%) within a nationwide study involving 11 diagnostic centers in a 10-year window (2008-2017). In DMD patients, we found deletions in 57%, duplications in 11% and small mutations in 32%. In BMD, we found deletions in 78%, duplications in 9% and small mutations in 13%. In BMD, there are a higher number of deletions, and small mutations are more frequent than duplications. Among small mutations that are generally frequent in both phenotypes, 44% of DMD and 36% of BMD are nonsense, thus, eligible for stop codon read-through therapy; 63% of all out-of-frame deletions are eligible for single exon skipping. Patients were also assigned to Italian regions and showed interesting regional differences in mutation distribution. The full genetic characterization in this large, nationwide cohort has allowed us to draw several correlations between DMD/BMD genotype landscapes and mutation frequency, mutation types, mutation locations along the gene, exon/intron architecture, and relevant protein domain, with effects on population genetic characteristics and new personalized therapies.