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 similar to 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.
Persistent Hypoglycemia in Children: Targeted Gene Panel Improves the Diagnosis of Hypoglycemia Due to Inborn Errors of Metabolism
Novelli, Antonio;
2018-01-01
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 similar to 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.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.