Next-Generation Molecular Investigations in Lysosomal Diseases: Clinical Integration of a Comprehensive Targeted Panel
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...
| Main Authors: | , , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
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MDPI AG
2021-02-01
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| Series: | Diagnostics |
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| Online Access: | https://www.mdpi.com/2075-4418/11/2/294 |
| _version_ | 1797396712953741312 |
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| author | Bénédicte Sudrié-Arnaud Sarah Snanoudj Ivana Dabaj Hélène Dranguet Lenaig Abily-Donval Axel Lebas Myriam Vezain Bénédicte Héron Isabelle Marie Marc Duval-Arnould Stéphane Marret Abdellah Tebani Soumeya Bekri |
| author_facet | Bénédicte Sudrié-Arnaud Sarah Snanoudj Ivana Dabaj Hélène Dranguet Lenaig Abily-Donval Axel Lebas Myriam Vezain Bénédicte Héron Isabelle Marie Marc Duval-Arnould Stéphane Marret Abdellah Tebani Soumeya Bekri |
| author_sort | Bénédicte Sudrié-Arnaud |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T00:55:26Z |
| format | Article |
| id | doaj.art-4764e4163ff54fe0adc720d1a3774f8f |
| institution | Directory Open Access Journal |
| issn | 2075-4418 |
| language | English |
| last_indexed | 2024-03-09T00:55:26Z |
| publishDate | 2021-02-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Diagnostics |
| spelling | doaj.art-4764e4163ff54fe0adc720d1a3774f8f2023-12-11T16:55:17ZengMDPI AGDiagnostics2075-44182021-02-0111229410.3390/diagnostics11020294Next-Generation Molecular Investigations in Lysosomal Diseases: Clinical Integration of a Comprehensive Targeted PanelBénédicte Sudrié-Arnaud0Sarah Snanoudj1Ivana Dabaj2Hélène Dranguet3Lenaig Abily-Donval4Axel Lebas5Myriam Vezain6Bénédicte Héron7Isabelle Marie8Marc Duval-Arnould9Stéphane Marret10Abdellah Tebani11Soumeya Bekri12Department of Metabolic Biochemistry, Rouen University Hospital, 76000 Rouen, FranceDepartment of Metabolic Biochemistry, Rouen University Hospital, 76000 Rouen, FranceNormandie Univ, UNIROUEN, CHU Rouen, INSERM U1245, 76000 Rouen, FranceDepartment of Metabolic Biochemistry, Rouen University Hospital, 76000 Rouen, FranceNormandie Univ, UNIROUEN, CHU Rouen, INSERM U1245, 76000 Rouen, FranceDepartment of Neurophysiology, Rouen University Hospital, 76031 Rouen, FranceNormandie Univ, UNIROUEN, INSERM U1245, Department of Genetics and Reference Center for Developmental Disorders, Rouen University Hospital, Normandy Center for Genomic and Personalized Medicine, 76000 Rouen, FranceCentre de Référence des Maladies Lysosomales, Service de Neurologie Pédiatrique, CHU Armand Trousseau-La Roche Guyon, GHUEP, APHP, 75000 Paris, FranceDepartment of Internal Medicine, Rouen University Hospital, 76000 Rouen, FranceDepartment of Pediatrics, Bicetre Hospital, APHP, 75000 Paris, FranceNormandie Univ, UNIROUEN, CHU Rouen, INSERM U1245, 76000 Rouen, FranceDepartment of Metabolic Biochemistry, Rouen University Hospital, 76000 Rouen, FranceDepartment of Metabolic Biochemistry, Rouen University Hospital, 76000 Rouen, FranceDiagnosis 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.https://www.mdpi.com/2075-4418/11/2/294NGSnext generation sequencinginborn errors of metabolismlysosomal disorders |
| spellingShingle | Bénédicte Sudrié-Arnaud Sarah Snanoudj Ivana Dabaj Hélène Dranguet Lenaig Abily-Donval Axel Lebas Myriam Vezain Bénédicte Héron Isabelle Marie Marc Duval-Arnould Stéphane Marret Abdellah Tebani Soumeya Bekri Next-Generation Molecular Investigations in Lysosomal Diseases: Clinical Integration of a Comprehensive Targeted Panel Diagnostics NGS next generation sequencing inborn errors of metabolism lysosomal disorders |
| title | Next-Generation Molecular Investigations in Lysosomal Diseases: Clinical Integration of a Comprehensive Targeted Panel |
| title_full | Next-Generation Molecular Investigations in Lysosomal Diseases: Clinical Integration of a Comprehensive Targeted Panel |
| title_fullStr | Next-Generation Molecular Investigations in Lysosomal Diseases: Clinical Integration of a Comprehensive Targeted Panel |
| title_full_unstemmed | Next-Generation Molecular Investigations in Lysosomal Diseases: Clinical Integration of a Comprehensive Targeted Panel |
| title_short | Next-Generation Molecular Investigations in Lysosomal Diseases: Clinical Integration of a Comprehensive Targeted Panel |
| title_sort | next generation molecular investigations in lysosomal diseases clinical integration of a comprehensive targeted panel |
| topic | NGS next generation sequencing inborn errors of metabolism lysosomal disorders |
| url | https://www.mdpi.com/2075-4418/11/2/294 |
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