Genetic Spectrum of Left Ventricular Non-Compaction in Paediatric Patients.

INTRODUCTION: Left ventricular non-compaction (LVNC) represents a genetically heterogeneous cardiomyopathy which occurs in both children and adults. Its genetic spectrum overlaps with other types of cardiomyopathy. However, LVNC phenotypes in different age groups can have distinct genetic aetiologies. The aim of the study was to decipher the genetic spectrum of LVNC presented in childhood. Patient Group and Methods: Twenty patients under the age of 18 years diagnosed with LVNC were enrolled in the study. Target sequencing and whole-exome sequencing were performed using a panel of 108 cardiomyopathy-associated genes. Pathogenic, likely pathogenic, and variants of unknown significance found in genes highly expressed in cardiomyocytes were considered as variants of interest for further analysis. RESULTS: The median age at presentation was 8.0 (0.1-17) years, with 6 patients presenting before 1 year of age. Twelve (60%) patients demonstrated reduced ejection fraction. Right ventricular (RV) dilation was registered in 6 (30%), often in combination with reduced RV contractility (25%). Almost half (45%) of the patients demonstrated biventricular involvement already at disease presentation. For pathogenic and likely pathogenic variants, the positive genotyping rate was 45%, and these variants were found mainly in non-contractile structural sarcomeric genes (ACTN2, MYPN, and TTN) or in metabolic and signal transduction genes (BRAF and TAZ). Likely pathogenic TAZ variants were detected in all 5 patients suspected of having Barth syndrome. No pathogenic or likely pathogenic variants were found in genes encoding for sarcomeric contractile proteins, but variants of unknown significance were detected in 3 out of 20 patients (MYH6, MYH7, and MYLK2). In 4 patients, variants of unknown significance in ion-channel genes were detected. CONCLUSION: We detected a low burden of contractile sarcomeric variants in LVNC patients presenting below the age of 18 years, with the major number of variants residing in non-contractile structural sarcomeric genes. The identification of the variants in ion-channel and related genes not previously associated with LVNC in paediatric patients requires further examination of their functional role.

Analysis of Prevalence and Clinical Features of Aortic Stenosis in Patients with and without Bicuspid Aortic Valve Using Machine Learning Methods.

Aortic stenosis (AS) is the most commonly diagnosed valvular heart disease, and its prevalence increases with the aging of the general population. However, AS is often diagnosed at a severe stage, necessitating surgical treatment, due to its long asymptomatic period. The objective of this study was to analyze the frequency of AS in a population of cardiovascular patients using echocardiography (ECHO) and to identify clinical factors and features associated with these patient groups. We utilized machine learning methods to analyze 84,851 echocardiograms performed between 2010 and 2018 at the National Medical Research Center named after V.A. Almazov. The primary indications for ECHO were coronary artery disease (CAD) and hypertension (HP), accounting for 33.5% and 14.2% of the cases, respectively. The frequency of AS was found to be 13.26% among the patients (n = 11,252). Within our study, 1544 patients had a bicuspid aortic valve (BAV), while 83,316 patients had a tricuspid aortic valve (TAV). BAV patients were observed to be younger compared to TAV patients. AS was more prevalent in the BAV group (59%) compared to the TAV group (12%), with a p-value of <0.0001. By employing a machine learning algorithm, we randomly identified significant features present in AS patients, including age, hypertension (HP), aortic regurgitation (AR), ascending aortic dilatation (AscAD), and BAV. These findings could serve as additional indications for earlier observation and more frequent ECHO in specific patient groups for the earlier detection of developing AS.