Signal-to-Noise Analysis Can Inform the Likelihood That Incidentally Identified Variants in Sarcomeric Genes Are...

Area of Science:

• Genetics
• Cardiology
• Bioinformatics

Background:

• Hypertrophic cardiomyopathy (HCM) is a common inherited heart condition linked to sudden death.
• Pediatric HCM cases often involve pathogenic variants in sarcomeric genes.
• Clinical exome sequencing (ES) increasingly detects incidental variants in HCM-associated genes, necessitating accurate interpretation.

Purpose of the Study:

• To utilize amino acid-level signal-to-noise (S:N) analysis for identifying pathogenic hotspots in sarcomeric HCM genes.
• To refine the 2015 American College of Medical Genetics (ACMG) criteria for predicting incidental variant pathogenicity.

Main Methods:

• Incidental variants from a clinical ES database were compared with population and literature data.
• Signal-to-noise (S:N) ratios were calculated at gene and amino acid levels to pinpoint hotspots.
• Variants were re-classified using ACMG criteria, incorporating S:N analysis to reduce variants of uncertain significance.

Main Results:

• Incidental variants in HCM genes were common in clinical ES referrals, but most were not disease-associated.
• Amino acid-level S:N analysis identified pathogenic hotspots within HCM genes.
• Clinical validation showed most probands with cardiomyopathy or family history carried pathogenic or likely pathogenic variants.

Conclusions:

• Incidental variants in HCM-associated genes are frequently found via clinical ES.
• Amino acid-level S:N analysis can enhance the diagnostic power of ACMG criteria for HCM.
• This approach aids in identifying pathogenic hotspots and improving clinical management of patients.