@article{3056806,
    title = "Targeted next generation sequencing in patients with inborn errors of metabolism",
    author = "Yubero, D. and Brandi, N. and Ormazabal, A. and Garcia-Cazorla, À. and Pérez-Dueñas, B. and Campistol, J. and Ribes, A. and Palau, F. and Artuch, R. and Armstrong, J. and Nascimento, A. and Ortigoza, J.D. and Castejón, E. and Meavilla, S. and García-Àlix, A. and Fons, C. and Ramos, F.J. and Ortez, C.I. and Jou, C. and Serrano, M. and O'Callaghan, M.M. and Jimenez, C. and Casado, M. and Sierra, C. and Molero, M. and Montero, R. and Vidal, S. and Blasco, L. and Gerotina, E. and Pacheco, P. and Garcia-Villòria, J. and Coll, M.J. and Girós, M. and Pons, R. and Cáceres, C. and Szlago, M. and Grimalt, M.A. and Rosell, J. and De Azua, B. and Olivé, M. and Martínez, F. and Martín, L. and Pérez-Poyato, M.S. and Sariego, A. and Málaga, I. and Marti, I. and López-Laso, E. and Yapici, Z. and Kiziltan, G. and Arellano, M. and Molera, C. and Quintero, J. and Working Group",
    journal = "PLOS ONE",
    year = "2016",
    volume = "11",
    number = "5",
    publisher = "Public Library of Science",
    doi = "10.1371/journal.pone.0156359",
    keywords = "biological marker;  genomic DNA;  genetic marker, adolescent;  Article;  blood analysis;  cerebrospinal fluid analysis;  child;  cohort analysis;  diagnostic test accuracy study;  disease classification;  DNA extraction;  female;  gene targeting;  human;  inborn error of metabolism;  major clinical study;  male;  molecular diagnosis;  next generation sequencing;  urinalysis;  validation process;  classification;  dna mutational analysis;  genetic marker;  genetics;  high throughput sequencing;  Metabolism, Inborn Errors;  mutation;  procedures, DNA Mutational Analysis;  Genetic Markers;  High-Throughput Nucleotide Sequencing;  Humans;  Metabolism, Inborn Errors;  Mutation",
    abstract = "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 (χ2 = 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. © 2016 Yubero et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited."
}