Diagnosis of lysosomal disorders (LDs) may be hampered by their clinical heterogeneity, phenotypic overlap, and variable age at onset. Conventional biological diagnostic procedures are based on a series of sequential investigations and require multiple sampling. Early diagnosis may allow for timely treatment and prevent clinical complications. In order to improve LDs diagnosis, we developed a capture-based next generation sequencing (NGS) panel allowing the detection of single nucleotide variants (SNVs), small insertions and deletions, and copy number variants (CNVs) in 51 genes related to LDs. The design of the LD panel covered at least coding regions, promoter region, and flanking intronic sequences for 51 genes. The validation of this panel consisted in testing 21 well-characterized samples and evaluating analytical and diagnostic performance metrics. Bioinformatics pipelines have been validated for SNVs, indels and CNVs. The clinical output of this panel was tested in five novel cases. This capture-based NGS panel provides an average coverage depth of 474× which allows the detection of SNVs and CNVs in one comprehensive assay. All the targeted regions were covered above the minimum required depth of 30×. To illustrate the clinical utility, five novel cases have been sequenced using this panel and the identified variants have been confirmed using Sanger sequencing or quantitative multiplex PCR of short fluorescent fragments (QMPSF). The application of NGS as first-line approach to analyze suspected LD cases may speed up the identification of alterations in LD-associated genes. NGS approaches combined with bioinformatics analyses, are a useful and cost-effective tool for identifying the causative variations in LDs.
Keywords: NGS; inborn errors of metabolism; lysosomal disorders; next generation sequencing.