Early Diagnosis of ABCB11 Spectrum Liver Disorders by Next Generation Sequencing

Su Jeong Lee1, Jung Eun Kim1, Byung-Ho Choe1

  • 1Department of Pediatrics, Kyungpook National University School of Medicine, Daegu, Korea.

Insights

Early diagnosis of ABCB11 spectrum liver disorders, including benign recurrent intrahepatic cholestasis and progressive familial intrahepatic cholestasis, is crucial. Genetic analysis aids in accurate diagnosis and timely treatment, potentially preventing unnecessary liver transplants.

Area of Science:

  • Hepatology
  • Medical Genetics
  • Pediatric Gastroenterology

Background:

  • Neonatal cholestasis presents a diagnostic challenge with diverse etiologies.
  • ABCB11 spectrum liver disorders, including PFIC and BRIC, often exhibit overlapping clinical features.
  • Accurate diagnosis is essential for appropriate management and prognosis.

Purpose of the Study:

  • To achieve early diagnosis of ABCB11 spectrum liver disorders.
  • To differentiate between benign recurrent intrahepatic cholestasis and progressive familial intrahepatic cholestasis.
  • To evaluate the role of genetic analysis in managing neonatal cholestasis.

Main Methods:

  • Fifty patients with neonatal cholestasis underwent etiological evaluation.
  • Genetic analysis, including whole exome and Sanger sequencing, was performed on suspected cases.
  • Two families with confirmed ABCB11 spectrum liver disorders received genetic counseling.

Main Results:

  • Idiopathic/viral hepatitis (34%) and metabolic diseases (20%) were common causes of neonatal cholestasis.
  • Novel ABCB11 mutations were identified in patients with PFIC and atypical BRIC.
  • Genetic confirmation enabled timely liver transplantation for PFIC and prevented unnecessary transplantation for BRIC.

Conclusions:

  • ABCB11 spectrum liver disorders present with indistinguishable clinical signs during acute episodes.
  • Comprehensive genetic analysis is vital for accurate diagnosis and effective treatment strategies.
  • Genetic insights guide therapeutic decisions, optimizing patient outcomes.
Abstract

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