Clinical and genetic spectrum of monogenic liver diseases in children diagnosed using next generation sequencing: a single centre experience from Kerala

Autor: Bindu Sarojam, Sankar Vaikom Hariharan, Prasanth Sobhan
Rok vydání: 2021
Předmět:
Zdroj: International Journal of Contemporary Pediatrics. 8:1776
ISSN: 2349-3291
2349-3283
Popis: Background: Children presenting with chronic liver disease have a high likelihood of an underlying genetic disorder. There is a delay in establishing a diagnosis of monogenic liver diseases if relied on typical clinical phenotypes and conventional laboratory investigations or imaging studies alone. Early diagnosis improves patient outcome through timely and adequate therapy.Methods: This study retrospectively analyzed the clinical and genetic spectra of monogenic liver disease in children diagnosed using next-generation sequencing (NGS) in a tertiary care teaching hospital in Kerala. Patients were classified into five groups according to their clinical presentation: neonatal/infantile cholestasis, hepatomegaly/ hepatosplenomegaly, progressive cholestasis (beyond infancy), acute liver failure and decompensated chronic liver disease.Results: There were 31 children enrolled, 14 (45.16%) males and 17 (54.84%) females. The median age at genetic diagnosis was 25.74 months. NGS identified 20 distinct genes related to varying clinical presentation. Six genes were identified in Group A, nine genes were identified in Group B, three genes were identified in Group C and two genes each in Group D and E. JAG1, ABCB4 and PYL1 (13 % each) were the top three genes related to monogenic liver disease in this study.Conclusions: Patients with hepatomegaly or hepatosplenomegaly constituted the major clinical presentation of genetic disorders followed by neonatal/infantile cholestasis in our study. Genetic cholestatic disorders and glycogen storage disorders were the most common monogenic liver diseases. NGS has an important role in the diagnosis of monogenic liver disease in children and can facilitate early medical treatment and predict the prognosis.
Databáze: OpenAIRE