Enhanced Exome Sequencing Improves the Genetic Diagnosis of Deafblindness

TL;DR

Enhanced exome sequencing improves genetic diagnosis of deafblindness by combining whole-exome and targeted probes.

Contribution

The study introduces an enhanced exome sequencing strategy that improves diagnostic yield for deafblindness.

Findings

The enhanced exome approach identified causative variants in 10 out of 10 known cases and 3 out of 10 previously undiagnosed cases.

The method achieved high coverage of target regions and outperformed commercial platforms in variant prioritization.

Both bioinformatics platforms failed to correctly call one causative variant.

Abstract

Background/Objectives: The combination of hearing loss and visual impairment in a single patient strongly suggests a genetic aetiology. However, after conventional testing, a considerable proportion of deafblindness cases remain without a genetic diagnosis. The aim of this study was to address this diagnostic gap. Methods: We developed an enhanced exome strategy that uses a whole-exome backbone complemented by spike-in capture probes for (i) low-coverage coding segments and clinically validated, non-coding regions (including deep intronic splice-altering sites and untranslated exonic sequences) across 659 genes associated with hearing loss and/or visual impairment, and (ii) mitochondrial DNA. Results: With 66.6 million paired-end reads per sample, this methodology achieved coverage of at least 20 reads per base at 99.3% of target coding and non-coding positions of genes associated with deafness and/or blindness, as well as 98.8% of the whole exome. The enhanced exome approach correctly identified the genetic variants causative of deafness and/or blindness in 10 out of 10 cases with a previously known genetic cause, in 3 out of 10 additional cases that remained undiagnosed after extensive panel sequencing, and in 4 out of 4 cases that had not been genetically studied before. Comparison of the performance of two commercial bioinformatics platforms for enhanced exome interpretation revealed that eVAI consistently prioritised causative variants higher than, or as high as, VarSome Clinical, resulting in a tendency toward shorter interpretation times using the former. Both platforms offered the same diagnostic yield and both failed to correctly call one of the causative variants. Conclusions: In an era where many centres operate exome analysis through virtual panels, enhanced exome sequencing leverages the advantages of whole-exome and custom panel sequencing: it provides panel-like sensitivity for clinically actionable loci, while offering the flexibility to periodically reanalyse data and discover candidate genes.

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