Panel-Based Next-Generation Sequencing for the Diagnosis of Cholestatic Genetic Liver Diseases: Clinical Utility and Challenges

• Published in: The Journal of pediatrics Vol. 205; pp. 153 - 159.e6
• Main Authors: Chen, Huey-Ling, Li, Huei-Ying, Wu, Jia-Feng, Wu, Shang-Hsin, Chen, Hui-Ling, Yang, Yu-Hsuan, Hsu, Yu-Hua, Liou, Bang-Yu, Chang, Mei-Hwei, Ni, Yen-Hsuan
• Format: Journal Article
• Language: English
• Published: United States Elsevier Inc 01.02.2019
• Subjects: gamma-glutamyl transferase; Jaundice; NR1H4 (FXR); progressive familial intrahepatic cholestasis; Jaundice; AST; UTR; GGT; PFIC; progressive familial intrahepatic cholestasis; ALT; NGS; gamma-glutamyl transferase; NR1H4 (FXR); dsDNA
• ISSN: 0022-3476; 1097-6833
• DOI: 10.1016/j.jpeds.2018.09.028

To test the application of a target enrichment next-generation sequencing (NGS) jaundice panel in genetic diagnosis of pediatric liver diseases. We developed a capture-based target enrichment NGS jaundice panel containing 42 known disease-causing genes associated with jaundice or cholestasis and 10 pathway-related genes. During 2015-2017, 102 pediatric patients with various forms of cholestasis or idiopathic liver diseases were tested, including patients with initial diagnosis of cholestasis in infancy, progressive familial intrahepatic cholestasis, syndromic cholestasis, Wilson disease, and others. Of the 102 patients, 137 mutations/variants in 44 different genes were identified in 84 patients. The genetic disease diagnosis rate was 33 of 102 (32.4%). A total of 79 of 102 (77.5%) of patients had at least 1 heterozygous genetic variation. Those with progressive intrahepatic cholestasis or syndromic cholestasis in infancy had a diagnostic rate of 62.5%. Disease-causing mutations, including ATP8B1, ABCB11, ABCB4, ABCC2, TJP2, NR1H4 (FXR), JAG1, AKR1D1, CYP7B1, PKHD1, ATP7B, and SLC25A13, were identified. Nine patients had unpredicted genetic diagnosis with atypical phenotype or novel mutations in the investigational genes. We propose an NGS diagnosis classification categorizing patients into high (n = 24), moderate (n = 9), or weak (n = 25) levels of genotype–phenotype correlations to facilitate patient management. This panel enabled high-throughput detection of genetic variants and disease diagnosis in patients with a long list of candidate causative genes. A NGS report with diagnosis classification may aid clinicians in data interpretation and patient management.