Whole-exome sequencing identifies rare genetic variants in Egyptian patients with hypertrophic cardiomyopathy: a...

Hypertrophic cardiomyopathy is a life-threatening disease with limited studies in Middle Eastern populations. This pilot study (n = 8) aimed to identify rare genetic variants to enable future presymptomatic diagnosis and primary prevention. While the sample size precludes establishing population-level prevalence, our findings provide a springboard for generating testable hypotheses for future multicenter trials.

Whole-exome sequencing was performed on eight unrelated Egyptian patients. We prioritised variants using stringent criteria: allele frequency < 0.01 in gnomAD, combined annotation dependent depletion (CADD) score > 10, and focused analysis of 29 genes with definitive or moderate evidence for hypertrophic cardiomyopathy causation according to Clinical Genome Resource (ClinGen). Variants were ACMG/AMP-classified and correlated with detailed clinical phenotypes.

We identified 21 rare variants across 10 hypertrophic cardiomyopathy-associated genes. Core sarcomeric genes accounted for seven variants: MYBPC3 (n = 2; one likely pathogenic, p.Gly1206Asp), MYH7 (n = 2; one pathogenic, p.Phe252Ser), and TNNT2 (n = 3; all variants of uncertain significance). Additionally, likely pathogenic variants were found in PLN (p.Arg25Cys) and KLHL24 (p.Arg103*). Patients with pathogenic or likely pathogenic sarcomeric variants exhibited severe phenotypes, including septal thickness up to 30 mm, left ventricular outflow tract gradients up to 60 mmHg, and a high arrhythmic burden, influencing decisions like implantable cardioverter-defibrillator implantation and myectomy. Notably, all three TNNT2 carriers manifested atrial fibrillation or non-sustained ventricular tachycardia, reinforcing its arrhythmic risk. Four novel or likely pathogenic variants were submitted to ClinVar.

As the first genetic study of hypertrophic cardiomyopathy in an Egyptian population, this work expands the global mutational spectrum, demonstrates the utility of genetic testing for risk stratification and personalised management, and underscores the need to diversify genomic datasets for equitable precision medicine.