Utility of AlphaMissense predictions in Asparagine Synthetase deficiency variant classification

Staklinski, Stephen J, Scheben, Armin, Siepel, Adam, Kilberg, Michael S (November 2023) Utility of AlphaMissense predictions in Asparagine Synthetase deficiency variant classification. bioRxiv. (Submitted)

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URL: https://www.ncbi.nlm.nih.gov/pubmed/37961642
DOI: 10.1101/2023.10.30.564808

Abstract

AlphaMissense is a recently developed method that is designed to classify missense variants into pathogenic, benign, or ambiguous categories across the entire human proteome. Asparagine Synthetase Deficiency (ASNSD) is a developmental disorder associated with severe symptoms, including congenital microcephaly, seizures, and premature death. Diagnosing ASNSD relies on identifying mutations in the asparagine synthetase (ASNS) gene through DNA sequencing and determining whether these variants are pathogenic or benign. Pathogenic ASNS variants are predicted to disrupt the protein’s structure and/or function, leading to asparagine depletion within cells and inhibition of cell growth. AlphaMissense offers a promising solution for the rapid classification of ASNS variants established by DNA sequencing and provides a community resource of pathogenicity scores and classifications for newly diagnosed ASNSD patients. Here, we assessed AlphaMissense’s utility in ASNSD by benchmarking it against known critical residues in ASNS and evaluating its performance against a list of previously reported ASNSD-associated variants. We also present a pipeline to calculate AlphaMissense scores for any protein in the UniProt database. AlphaMissense accurately attributed a high average pathogenicity score to known critical residues within the two ASNS active sites and the connecting intramolecular tunnel. The program successfully categorized 78.9% of known ASNSD-associated missense variants as pathogenic. The remaining variants were primarily labeled as ambiguous, with a smaller proportion classified as benign. This study underscores the potential role of AlphaMissense in classifying ASNS variants in suspected cases of ASNSD, potentially providing clarity to patients and their families grappling with ongoing diagnostic uncertainty.

Item Type: Paper
Subjects: bioinformatics > genomics and proteomics > annotation
bioinformatics
bioinformatics > genomics and proteomics
CSHL Authors:
Communities: CSHL labs > Siepel lab
School of Biological Sciences > Publications
SWORD Depositor: CSHL Elements
Depositing User: CSHL Elements
Date: 2 November 2023
Date Deposited: 17 Nov 2023 13:27
Last Modified: 29 Feb 2024 18:10
PMCID: PMC10634951
Related URLs:
URI: https://repository.cshl.edu/id/eprint/41312

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