Emanuela Ponzi1, Arianna Maiorana1, Francesca Romana Lepri2, Mafalda Mucciolo2, Michela Semeraro1, Roberta Taurisano1, Giorgia Olivieri3, Antonio Novelli2, Carlo Dionisi-Vici4. 1. Division of Metabolic Diseases, Department of Pediatric Specialties, Bambino Gesù Children's Hospital, Rome, Italy. 2. Medical Genetics Unit, Medical Genetics Laboratory, Bambino Gesù Children's Hospital, Rome, Italy. 3. Division of Metabolic Diseases, Department of Pediatric Specialties, Bambino Gesù Children's Hospital, Rome, Italy; Unit of Child Neurology, Catholic University, Fondazione Policlinico A. Gemelli, Rome, Italy. 4. Division of Metabolic Diseases, Department of Pediatric Specialties, Bambino Gesù Children's Hospital, Rome, Italy. Electronic address: carlo.dionisivici@opbg.net.
Abstract
OBJECTIVES: To evaluate the role of next generation sequencing in genetic diagnosis of pediatric patients with persistent hypoglycemia. STUDY DESIGN: Sixty-four patients investigated through an extensive workup were divided in 3 diagnostic classes based on the likelihood of a genetic diagnosis: (1) single candidate gene (9/64); (2) multiple candidate genes (43/64); and (3) no candidate gene (12/64). Subsequently, patients were tested through a custom gene panel of 65 targeted genes, which included 5 disease categories: (1) hyperinsulinemic hypoglycemia, (2) fatty acid-oxidation defects and ketogenesis defects, (3) ketolysis defects, (4) glycogen storage diseases and other disorders of carbohydrate metabolism, and (5) mitochondrial disorders. Molecular data were compared with clinical and biochemical data. RESULTS: A proven diagnosis was obtained in 78% of patients with suspicion for a single candidate gene, in 49% with multiple candidate genes, and in 33% with no candidate gene. The diagnostic yield was 48% for hyperinsulinemic hypoglycemia, 66% per fatty acid-oxidation and ketogenesis defects, 59% for glycogen storage diseases and other carbohydrate disorders, and 67% for mitochondrial disorders. CONCLUSIONS: This approach provided a diagnosis in ~50% of patients in whom clinical and laboratory evaluation did not allow identification of a single candidate gene and a diagnosis was established in 33% of patients belonging to the no candidate gene class. Next generation sequencing technique is cost-effective compared with Sanger sequencing of multiple genes and represents a powerful tool for the diagnosis of inborn errors of metabolism presenting with persistent hypoglycemia.
OBJECTIVES: To evaluate the role of next generation sequencing in genetic diagnosis of pediatric patients with persistent hypoglycemia. STUDY DESIGN: Sixty-four patients investigated through an extensive workup were divided in 3 diagnostic classes based on the likelihood of a genetic diagnosis: (1) single candidate gene (9/64); (2) multiple candidate genes (43/64); and (3) no candidate gene (12/64). Subsequently, patients were tested through a custom gene panel of 65 targeted genes, which included 5 disease categories: (1) hyperinsulinemic hypoglycemia, (2) fatty acid-oxidation defects and ketogenesis defects, (3) ketolysis defects, (4) glycogen storage diseases and other disorders of carbohydrate metabolism, and (5) mitochondrial disorders. Molecular data were compared with clinical and biochemical data. RESULTS: A proven diagnosis was obtained in 78% of patients with suspicion for a single candidate gene, in 49% with multiple candidate genes, and in 33% with no candidate gene. The diagnostic yield was 48% for hyperinsulinemic hypoglycemia, 66% per fatty acid-oxidation and ketogenesis defects, 59% for glycogen storage diseases and other carbohydrate disorders, and 67% for mitochondrial disorders. CONCLUSIONS: This approach provided a diagnosis in ~50% of patients in whom clinical and laboratory evaluation did not allow identification of a single candidate gene and a diagnosis was established in 33% of patients belonging to the no candidate gene class. Next generation sequencing technique is cost-effective compared with Sanger sequencing of multiple genes and represents a powerful tool for the diagnosis of inborn errors of metabolism presenting with persistent hypoglycemia.
Authors: Sofia Barbosa-Gouveia; María E Vázquez-Mosquera; Emiliano González-Vioque; José V Álvarez; Roi Chans; Francisco Laranjeira; Esmeralda Martins; Ana Cristina Ferreira; Alejandro Avila-Alvarez; María L Couce Journal: Genes (Basel) Date: 2021-08-19 Impact factor: 4.096
Authors: Arianna Maiorana; Francesca Romana Lepri; Antonio Novelli; Carlo Dionisi-Vici Journal: Front Endocrinol (Lausanne) Date: 2022-03-29 Impact factor: 5.555
Authors: Sebastian Kummer; Susanne Rinné; Gunnar Seemann; Nadine Bachmann; Katherine Timothy; Paul S Thornton; Frank Pillekamp; Ertan Mayatepek; Carsten Bergmann; Thomas Meissner; Niels Decher Journal: Int J Mol Sci Date: 2022-07-22 Impact factor: 6.208