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Updated: Sep 23, 2025

Determining the Likelihood of Variant Pathogenicity Using Amino Acid-level Signal-to-Noise Analysis of Genetic Variation
Published on: January 16, 2019
Defining pathogenicity of NOTCH2 variants for diagnosis of Alagille syndrome type 2 using a large cohort of patients
Zhong-Die Li1, Kuerbanjiang Abuduxikuer1, Li Wang1
1The Center for Pediatric Liver Diseases, Children's Hospital of Fudan University, Shanghai, China.
Background And Aims:
Alagille syndrome (ALGS) type 2 caused by mutations in NOTCH2 has genotypic and phenotypic heterogeneity. Diagnosis in some atypical patients with isolated hepatic presentation could be missed.
Methods:
Using 2087 patients with paediatric liver manifestations, NOTCH2 allele frequencies, in-silico prediction, protein domains and clinical features were analysed to define the pathogenicity of NOTCH2 variants for diagnosis of ALGS type 2.
Results:
Among 2087 patients with paediatric liver manifestations, significantly more NOTCH2 variants were absent in gnomAD in patients with elevated γ-glutamyltransferase (GGT) (p = .041). Significantly more NOTCH2 variants which were absent in gnomAD were located in protein functional domains (p = .038). When missense variants were absent in gnomAD and predicted to be pathogenic by at least three out of seven in-silico tools, they were found to be significantly associated with liver manifestations with elevated GGT (p = .003). Comparing this to patients with likely benign (LB) variants, the patients with likely-pathogenic (LP) variants have significantly more liver manifestations with elevated GGT (p = .0001). Significantly more patients with LP variants had extra-hepatic phenotypes of ALGS compared with those patients with LB variants (p = .0004).
Conclusion:
When NOTCH2 variants are absent in gnomAD, null variants and missense variants which were predicted to be pathogenic by at least three in-silico tools could be considered pathogenic in patients with high GGT chronic liver diseases.
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