Clinical validity of phenotype-driven analysis software PhenoVar as a diagnostic aid for clinical geneticists in the interpretation of whole-exome sequencing data

Abstract

Purpose: We sought to determine the diagnostic yield of whole-exome sequencing (WES) combined with phenotype-driven analysis of variants in patients with suspected genetic disorders.

Methods: WES was performed on a cohort of 51 patients presenting dysmorphisms with or without neurodevelopmental disorders of undetermined etiology. For each patient, a clinical geneticist reviewed the phenotypes and used the phenotype-driven analysis software PhenoVar (http://phenovar.med.usherbrooke.ca/) to analyze WES variants. The prioritized list of potential diagnoses returned was reviewed by the clinical geneticist, who selected candidate variants to be confirmed by segregation analysis. Conventional analysis of the individual variants was performed in parallel. The resulting candidate variants were subsequently reviewed by the same geneticist, to identify any additional potential diagnoses.

Results: A molecular diagnosis was identified in 35% of the patients using the conventional analysis, and 17 of these 18 diagnoses were independently identified using PhenoVar. The only diagnosis initially missed by PhenoVar was rescued when the optional "minimal phenotypic cutoff" filter was omitted. PhenoVar reduced by half the number of potential diagnoses per patient compared with the conventional analysis.

Conclusion: Phenotype-driven software prioritizes WES variants, provides an efficient diagnostic aid to clinical geneticists and laboratories, and should be incorporated in clinical practice.

Keywords: Exomiser; PhenoVar; diagnosis; exome; whole-exome sequencing (WES).