Benchmarking AlphaMissense Pathogenicity Predictions Against Cystic Fibrosis Variants.
Journal
bioRxiv : the preprint server for biology
Titre abrégé: bioRxiv
Pays: United States
ID NLM: 101680187
Informations de publication
Date de publication:
09 Oct 2023
09 Oct 2023
Historique:
pubmed:
24
10
2023
medline:
24
10
2023
entrez:
24
10
2023
Statut:
epublish
Résumé
Mutations in cystic fibrosis transmembrane conductance regulator (CFTR) result in cystic fibrosis - a lethal genetic disease. Missense mutations that alter a single amino acid in the CFTR protein are among the most common cystic fibrosis mutations. AlphaMissense (AM) is a new technology that predicts the pathogenicity of missense mutations based on dual learned protein structure and evolutionary features. We evaluated the ability of AM to predict the pathogenicity of CFTR missense variants. AM predicted a high pathogenicity for CFTR residues overall, resulting in a high false positive rate and fair classification performance on CF variants from the CFTR2.org database. AM pathogenicity score correlated modestly with pathogenicity metrics from persons with CF including sweat chloride level, pancreatic insufficiency rate, and pseudomonas infection rate. Correlation was also modest with CFTR trafficking and folding competency
Identifiants
pubmed: 37873426
doi: 10.1101/2023.10.05.561147
pmc: PMC10592606
pii:
doi:
Types de publication
Preprint
Langues
eng
Subventions
Organisme : NHLBI NIH HHS
ID : F31 HL162483
Pays : United States
Organisme : NIGMS NIH HHS
ID : R35 GM133552
Pays : United States
Organisme : NHLBI NIH HHS
ID : R00 HL151965
Pays : United States
Organisme : NHLBI NIH HHS
ID : R01 HL167046
Pays : United States
Organisme : NIGMS NIH HHS
ID : T32 GM065086
Pays : United States
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