Targeted Next Generation Sequencing in Patients with Inborn Errors of Metabolism
Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate the utility of NGS in the clinical field, a targeted genetic panel approach was designed for the diagnosis of a set of inborn errors of metabol...
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| Published in | PloS one Vol. 11; no. 5; p. e0156359 |
|---|---|
| Main Authors | , , , , , , , , , |
| Format | Journal Article |
| Language | English |
| Published |
United States
Public Library of Science
31.05.2016
Public Library of Science (PLoS) |
| Subjects | |
| Online Access | Get full text |
| ISSN | 1932-6203 1932-6203 |
| DOI | 10.1371/journal.pone.0156359 |
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| Abstract | Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate the utility of NGS in the clinical field, a targeted genetic panel approach was designed for the diagnosis of a set of inborn errors of metabolism (IEM). The final aim of the study was to compare the findings for the diagnostic yield of NGS in patients who presented with consistent clinical and biochemical suspicion of IEM with those obtained for patients who did not have specific biomarkers.
The subjects studied (n = 146) were classified into two categories: Group 1 (n = 81), which consisted of patients with clinical and biochemical suspicion of IEM, and Group 2 (n = 65), which consisted of IEM cases with clinical suspicion and unspecific biomarkers. A total of 171 genes were analyzed using a custom targeted panel of genes followed by Sanger validation.
Genetic diagnosis was achieved in 50% of patients (73/146). In addition, the diagnostic yield obtained for Group 1 was 78% (63/81), and this rate decreased to 15.4% (10/65) in Group 2 (X2 = 76.171; p < 0.0001).
A rapid and effective genetic diagnosis was achieved in our cohort, particularly the group that had both clinical and biochemical indications for the diagnosis. |
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| AbstractList | Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate the utility of NGS in the clinical field, a targeted genetic panel approach was designed for the diagnosis of a set of inborn errors of metabolism (IEM). The final aim of the study was to compare the findings for the diagnostic yield of NGS in patients who presented with consistent clinical and biochemical suspicion of IEM with those obtained for patients who did not have specific biomarkers. The subjects studied (n = 146) were classified into two categories: Group 1 (n = 81), which consisted of patients with clinical and biochemical suspicion of IEM, and Group 2 (n = 65), which consisted of IEM cases with clinical suspicion and unspecific biomarkers. A total of 171 genes were analyzed using a custom targeted panel of genes followed by Sanger validation. Genetic diagnosis was achieved in 50% of patients (73/146). In addition, the diagnostic yield obtained for Group 1 was 78% (63/81), and this rate decreased to 15.4% (10/65) in Group 2 (X.sup.2 = 76.171; p < 0.0001). A rapid and effective genetic diagnosis was achieved in our cohort, particularly the group that had both clinical and biochemical indications for the diagnosis. Background Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate the utility of NGS in the clinical field, a targeted genetic panel approach was designed for the diagnosis of a set of inborn errors of metabolism (IEM). The final aim of the study was to compare the findings for the diagnostic yield of NGS in patients who presented with consistent clinical and biochemical suspicion of IEM with those obtained for patients who did not have specific biomarkers. Methods The subjects studied (n = 146) were classified into two categories: Group 1 (n = 81), which consisted of patients with clinical and biochemical suspicion of IEM, and Group 2 (n = 65), which consisted of IEM cases with clinical suspicion and unspecific biomarkers. A total of 171 genes were analyzed using a custom targeted panel of genes followed by Sanger validation. Results Genetic diagnosis was achieved in 50% of patients (73/146). In addition, the diagnostic yield obtained for Group 1 was 78% (63/81), and this rate decreased to 15.4% (10/65) in Group 2 (X.sup.2 = 76.171; p < 0.0001). Conclusions A rapid and effective genetic diagnosis was achieved in our cohort, particularly the group that had both clinical and biochemical indications for the diagnosis. Background Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate the utility of NGS in the clinical field, a targeted genetic panel approach was designed for the diagnosis of a set of inborn errors of metabolism (IEM). The final aim of the study was to compare the findings for the diagnostic yield of NGS in patients who presented with consistent clinical and biochemical suspicion of IEM with those obtained for patients who did not have specific biomarkers. Methods The subjects studied (n = 146) were classified into two categories: Group 1 (n = 81), which consisted of patients with clinical and biochemical suspicion of IEM, and Group 2 (n = 65), which consisted of IEM cases with clinical suspicion and unspecific biomarkers. A total of 171 genes were analyzed using a custom targeted panel of genes followed by Sanger validation. Results Genetic diagnosis was achieved in 50% of patients (73/146). In addition, the diagnostic yield obtained for Group 1 was 78% (63/81), and this rate decreased to 15.4% (10/65) in Group 2 ( X 2 = 76.171; p < 0.0001). Conclusions A rapid and effective genetic diagnosis was achieved in our cohort, particularly the group that had both clinical and biochemical indications for the diagnosis. BACKGROUND: Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate the utility of NGS in the clinical field, a targeted genetic panel approach was designed for the diagnosis of a set of inborn errors of metabolism (IEM). The final aim of the study was to compare the findings for the diagnostic yield of NGS in patients who presented with consistent clinical and biochemical suspicion of IEM with those obtained for patients who did not have specific biomarkers. METHODS: The subjects studied (n = 146) were classified into two categories: Group 1 (n = 81), which consisted of patients with clinical and biochemical suspicion of IEM, and Group 2 (n = 65), which consisted of IEM cases with clinical suspicion and unspecific biomarkers. A total of 171 genes were analyzed using a custom targeted panel of genes followed by Sanger validation. RESULTS: Genetic diagnosis was achieved in 50% of patients (73/146). In addition, the diagnostic yield obtained for Group 1 was 78% (63/81), and this rate decreased to 15.4% (10/65) in Group 2 (X2 = 76.171; p < 0.0001). CONCLUSIONS: A rapid and effective genetic diagnosis was achieved in our cohort, particularly the group that had both clinical and biochemical indications for the diagnosis. Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate the utility of NGS in the clinical field, a targeted genetic panel approach was designed for the diagnosis of a set of inborn errors of metabolism (IEM). The final aim of the study was to compare the findings for the diagnostic yield of NGS in patients who presented with consistent clinical and biochemical suspicion of IEM with those obtained for patients who did not have specific biomarkers. The subjects studied (n = 146) were classified into two categories: Group 1 (n = 81), which consisted of patients with clinical and biochemical suspicion of IEM, and Group 2 (n = 65), which consisted of IEM cases with clinical suspicion and unspecific biomarkers. A total of 171 genes were analyzed using a custom targeted panel of genes followed by Sanger validation. Genetic diagnosis was achieved in 50% of patients (73/146). In addition, the diagnostic yield obtained for Group 1 was 78% (63/81), and this rate decreased to 15.4% (10/65) in Group 2 (X2 = 76.171; p < 0.0001). A rapid and effective genetic diagnosis was achieved in our cohort, particularly the group that had both clinical and biochemical indications for the diagnosis. Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate the utility of NGS in the clinical field, a targeted genetic panel approach was designed for the diagnosis of a set of inborn errors of metabolism (IEM). The final aim of the study was to compare the findings for the diagnostic yield of NGS in patients who presented with consistent clinical and biochemical suspicion of IEM with those obtained for patients who did not have specific biomarkers.BACKGROUNDNext-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate the utility of NGS in the clinical field, a targeted genetic panel approach was designed for the diagnosis of a set of inborn errors of metabolism (IEM). The final aim of the study was to compare the findings for the diagnostic yield of NGS in patients who presented with consistent clinical and biochemical suspicion of IEM with those obtained for patients who did not have specific biomarkers.The subjects studied (n = 146) were classified into two categories: Group 1 (n = 81), which consisted of patients with clinical and biochemical suspicion of IEM, and Group 2 (n = 65), which consisted of IEM cases with clinical suspicion and unspecific biomarkers. A total of 171 genes were analyzed using a custom targeted panel of genes followed by Sanger validation.METHODSThe subjects studied (n = 146) were classified into two categories: Group 1 (n = 81), which consisted of patients with clinical and biochemical suspicion of IEM, and Group 2 (n = 65), which consisted of IEM cases with clinical suspicion and unspecific biomarkers. A total of 171 genes were analyzed using a custom targeted panel of genes followed by Sanger validation.Genetic diagnosis was achieved in 50% of patients (73/146). In addition, the diagnostic yield obtained for Group 1 was 78% (63/81), and this rate decreased to 15.4% (10/65) in Group 2 (X2 = 76.171; p < 0.0001).RESULTSGenetic diagnosis was achieved in 50% of patients (73/146). In addition, the diagnostic yield obtained for Group 1 was 78% (63/81), and this rate decreased to 15.4% (10/65) in Group 2 (X2 = 76.171; p < 0.0001).A rapid and effective genetic diagnosis was achieved in our cohort, particularly the group that had both clinical and biochemical indications for the diagnosis.CONCLUSIONSA rapid and effective genetic diagnosis was achieved in our cohort, particularly the group that had both clinical and biochemical indications for the diagnosis. Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate the utility of NGS in the clinical field, a targeted genetic panel approach was designed for the diagnosis of a set of inborn errors of metabolism (IEM). The final aim of the study was to compare the findings for the diagnostic yield of NGS in patients who presented with consistent clinical and biochemical suspicion of IEM with those obtained for patients who did not have specific biomarkers.The subjects studied (n = 146) were classified into two categories: Group 1 (n = 81), which consisted of patients with clinical and biochemical suspicion of IEM, and Group 2 (n = 65), which consisted of IEM cases with clinical suspicion and unspecific biomarkers. A total of 171 genes were analyzed using a custom targeted panel of genes followed by Sanger validation.Genetic diagnosis was achieved in 50% of patients (73/146). In addition, the diagnostic yield obtained for Group 1 was 78% (63/81), and this rate decreased to 15.4% (10/65) in Group 2 (X2 = 76.171; p < 0.0001).A rapid and effective genetic diagnosis was achieved in our cohort, particularly the group that had both clinical and biochemical indications for the diagnosis. |
| Audience | Academic |
| Author | Palau, Francesc Garcia-Cazorla, Àngels Brandi, Núria Yubero, Dèlia Ormazabal, Aida Pérez-Dueñas, Belén Ribes, Antonia Campistol, Jaime Armstrong, Judith Artuch, Rafael |
| AuthorAffiliation | 5 Institut de Bioquímica Clínica, Hospital Clínic i Provincial, Barcelona, Spain 4 Department of Neurology, Hospital Sant Joan de Déu, Barcelona, Spain 2 Facultat de Medicina, Universitat de Barcelona, Barcelona, Spain Baylor Research Institute, UNITED STATES 1 Department of Clinical Biochemistry and Institut d’Investigació Sanitària Sant Joan de Déu, Hospital Sant Joan de Déu, Barcelona, Spain 3 Molecular and Genetics Medicine Section, Hospital Sant Joan de Déu, Barcelona, Spain 6 Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Barcelona, Spain |
| AuthorAffiliation_xml | – name: 4 Department of Neurology, Hospital Sant Joan de Déu, Barcelona, Spain – name: Baylor Research Institute, UNITED STATES – name: 5 Institut de Bioquímica Clínica, Hospital Clínic i Provincial, Barcelona, Spain – name: 1 Department of Clinical Biochemistry and Institut d’Investigació Sanitària Sant Joan de Déu, Hospital Sant Joan de Déu, Barcelona, Spain – name: 2 Facultat de Medicina, Universitat de Barcelona, Barcelona, Spain – name: 3 Molecular and Genetics Medicine Section, Hospital Sant Joan de Déu, Barcelona, Spain – name: 6 Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), Instituto de Salud Carlos III, Barcelona, Spain |
| Author_xml | – sequence: 1 givenname: Dèlia surname: Yubero fullname: Yubero, Dèlia – sequence: 2 givenname: Núria surname: Brandi fullname: Brandi, Núria – sequence: 3 givenname: Aida surname: Ormazabal fullname: Ormazabal, Aida – sequence: 4 givenname: Àngels surname: Garcia-Cazorla fullname: Garcia-Cazorla, Àngels – sequence: 5 givenname: Belén surname: Pérez-Dueñas fullname: Pérez-Dueñas, Belén – sequence: 6 givenname: Jaime surname: Campistol fullname: Campistol, Jaime – sequence: 7 givenname: Antonia surname: Ribes fullname: Ribes, Antonia – sequence: 8 givenname: Francesc surname: Palau fullname: Palau, Francesc – sequence: 9 givenname: Rafael surname: Artuch fullname: Artuch, Rafael – sequence: 10 givenname: Judith surname: Armstrong fullname: Armstrong, Judith |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/27243974$$D View this record in MEDLINE/PubMed |
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| Copyright | COPYRIGHT 2016 Public Library of Science 2016 Yubero et al. This is an open access article distributed under the terms of the Creative Commons Attribution License: http://creativecommons.org/licenses/by/4.0/ (the “License”), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Notwithstanding the ProQuest Terms and Conditions, you may use this content in accordance with the terms of the License. cc-by (c) Yubero Siles, Dèlia et al., 2016 info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by/3.0/es 2016 Yubero et al 2016 Yubero et al |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 The Working Group authors and the corresponding affiliations are provided in the Acknowledgments. Conceived and designed the experiments: DY JA RA. Performed the experiments: DY NB JA. Analyzed the data: DY JA. Contributed reagents/materials/analysis tools: DY NB AO AGC BPD JC AR FP RA JA. Wrote the paper: DY NB AO AGC BPD JC AR FP RA JA. Competing Interests: Dèlia Yubero, Núria Brandi, Aida Ormazabal, Àngels Garcia-Cazorla, Belén Pérez-Dueñas, Jaime Campistol, Antonia Ribes, Francesc Palau, Rafael Artuch and Judith Armstrong declare that they have no conflict of interest. |
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| Snippet | Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To evaluate... Background Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To... BACKGROUND: Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To... Background Next-generation sequencing (NGS) technology has allowed the promotion of genetic diagnosis and are becoming increasingly inexpensive and faster. To... |
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| SubjectTerms | ADN Amino acids Analysis Biochemistry Biology and Life Sciences Biomarkers Care and treatment Defects Development and progression Diagnosis Diagnostic systems DNA DNA Mutational Analysis DNA sequencing Enzymes Gene sequencing Genes Genetic aspects Genetic diseases Genetic disorders Genetic Markers Genetic screening Genetics Genotypes Genètica mèdica High-Throughput Nucleotide Sequencing - methods Humans Identification and classification Inborn errors of metabolism Innovations Laboratories Malalties hereditàries Medical diagnosis Medical genetics Medicine and Health Sciences Metabolism Metabolism, Inborn Errors - classification Metabolism, Inborn Errors - diagnosis Metabolism, Inborn Errors - genetics Metabolisme Metabolites Methods Molecular targeted therapy Mutació (Biologia) Mutation Mutation (Biology) Neurology Patients Research and analysis methods Singers Studies Working groups |
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| Title | Targeted Next Generation Sequencing in Patients with Inborn Errors of Metabolism |
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