Resolving Uncertainty in Alagille Syndrome Diagnostics - PROJECT SUMMARY/ABSTRACT Uncertainty in genomic diagnostics creates a barrier to realizing the full potential of genomic medicine. Uncertainty is evident in: 1) our inability to determine if some DNA variants are pathogenic or benign and 2) our inability to predict to what extent a person with a disease-causing variant will be affected, due to variable expressivity. This proposal will study both phenomena for the autosomal dominant disorder Alagille syndrome, caused by mutations in one of two genes in the Notch signaling pathway, the ligand JAGGED1 (JAG1) or the receptor, NOTCH2. Alagille syndrome is characterized by pediatric liver, heart, vertebral, renal, ocular, and facial anomalies with highly variable expressivity. The mechanism of disease for JAG1-related Alagille syndrome is haploinsufficiency whereas the mechanism for NOTCH2-related Alagille syndrome is less clear, with fewer reported variants, less functional characterization, and a higher prevalence of missense variants (>50%). Missense variants are difficult to classify, often requiring functional validation to support or reject pathogenicity. In Alagille syndrome, functional characterization has been carried out for only 19/125 reported missense mutations, thus, despite a high detection rate, the diagnostic rate is lower due to this uncertainty. We propose to resolve uncertainty in the diagnostics of Alagille syndrome using assays designed to characterize the pathogenicity of JAG1 and NOTCH2 missense variants and analysis of gene expression data from patient liver samples to identify gene expression signatures that can be used for genotype-phenotype evaluations. In Aim 1, we will design a Site Saturation Variant Library of all possible nucleotide permutations at each nucleotide position across a region with high missense variant uncertainty in the JAG1 C-terminus and test this library by developing a Multiplexed Assay for Variant Effects (MAVEs) that will measure cellular localization of JAG1 as a readout of protein function. In Aim 2, we will use FFPE liver tissue samples to analyze gene expression differences between Alagille syndrome patients and controls, as well as between Alagille syndrome patients with mild versus severe liver disease. In Aim 3, we will study the molecular basis of NOTCH2 variants through functional, expression, and enzymatic assays using mutant cell lines. We hypothesize that these proposed assays will identify a high-throughput method to test missense pathogenicity (Aim 1), identify gene expression differences between Alagille syndrome patients and controls as well as gene expression signatures that are different between Alagille syndrome patients with mild versus severe liver disease (Aim 2), and determine the mechanism by which NOTCH2 variants cause Alagille syndrome through functional analysis (Aim 3). Ultimately, these data will improve variant analysis for Alagille syndrome, improve our understanding of the molecular basis of liver disease in Alagille syndrome, and establish a framework for scalable classification of missense variants, delivering diagnostic information that can directly help clinicians.
