1 - Unit of Diagnosis and Treatment of Congenital Metabolic Diseases, Department of Paediatrics, IDIS-Health Research Institute of Santiago de Compostela, Centro de Investigación Biomédica en Red de Enfermedades Raras (CIBERER), European Reference Network for Hereditary Metabolic Disorders (MetabERN), Santiago de Compostela University Clinical Hospital, 15704 Santiago de Compostela, Spain;
2 - Department of Clinical Biochemistry, Puerta de Hierro-Majadahonda University Hospital, 28222 Majadahonda, Spain;
3 - Biochemical Genetics Unit, Centro de Genética Médica Doutor Jacinto Magalhães, 4050-466 Porto, Portugal;
4 - Centro Materno-Infantil do Norte, Centro Hospitalar Universitário do Porto (CHUP), Coordinator of the Centro de Referência de Doenças Hereditárias do Metabolismo do CHUP, 4050-466 Porto, Portugal;
5 - Hospital D. Estefânia, Centro Hospitalar de Lisboa Central (CHLC), Coordinator of the Centro de Referência de Doenças Hereditárias do Metabolismo do CHLC, 1169-050 Lisboa, Portugal;
6 - Neonatology Unit, Pediatrics Department, Complexo Hospitalario Universitario de A Coruña, SERGAS, 15006 A Coruña, Spain;
- Genes 2021, 12, 1262. https://doi.org/10.3390/genes12081262
Resumo: Next-generation sequencing (NGS) technologies have been proposed as a first-line test for the diagnosis of inborn errors of metabolism (IEM), a group of genetically heterogeneous disorders with overlapping or nonspecific phenotypes. Over a 3-year period, we prospectively analyzed 311 pediatric patients with a suspected IEM using four targeted gene panels. The rate of positive diagnosis was 61.86% for intermediary metabolism defects, 32.84% for complex molecular defects, 19% for hypoglycemic/hyperglycemic events, and 17% for mitochondrial diseases, and a conclusive molecular diagnosis was established in 2-4 weeks. Forty-one patients for whom negative results were obtained with the mitochondrial diseases panel underwent subsequent analyses using the NeuroSeq panel, which groups all genes from the individual panels together with genes associated with neurological disorders (1870 genes in total). This achieved a diagnostic rate of 32%. We next evaluated the utility of a tool, Phenomizer, for differential diagnosis, and established a correlation between phenotype and molecular findings in 39.3% of patients. Finally, we evaluated the mutational architecture of the genes analyzed by determining z-scores, loss-of-function observed/expected upper bound fraction (LOEUF), and haploinsufficiency (HI) scores. In summary, targeted gene panels for specific groups of IEMs enabled rapid and effective diagnosis, which is critical for the therapeutic management of IEM patients.