Do common in silico tools predict the clinical consequences of amino-acid substitutions in the CFTR gene?

• Published in: Clinical genetics Vol. 77; no. 5; pp. 464 - 473
• Main Authors: Dorfman, R, Nalpathamkalam, T, Taylor, C, Gonska, T, Keenan, K, Yuan, XW, Corey, M, Tsui, L-C, Zielenski, J, Durie, P
• Format: Journal Article
• Language: English
• Published: Oxford, UK Blackwell Publishing Ltd 01.05.2010; Wiley-Blackwell
• Subjects: Algorithms; Amino acid substitution; Amino Acid Substitution - genetics; Amino acids; Biological and medical sciences; Canada; CBAVD; CFTR; CFTR-related disease; Clinical trials; Computational Biology - methods; Computer applications; Computer programs; Cystic fibrosis; Cystic Fibrosis - diagnosis; Cystic Fibrosis - genetics; Cystic Fibrosis - pathology; Cystic fibrosis transmembrane conductance regulator; Cystic Fibrosis Transmembrane Conductance Regulator - genetics; disease severity; Errors of metabolism; Evolutionary conservation; Exocrine Pancreatic Insufficiency - genetics; Fundamental and applied biological sciences. Psychology; General aspects. Genetic counseling; Genes; Genetics of eukaryotes. Biological and molecular evolution; Humans; Medical genetics; Medical sciences; Metabolic diseases; Miscellaneous hereditary metabolic disorders; Missense mutation; Molecular and cellular biology; Mutation, Missense - genetics; Neonates; Pancreas - pathology; pancreatic insufficiency; PANTHER; Phenotype; PolyPhen; Protein structure; ROC Curve; SIFT; Statistical analysis; Canada; Human; SIFT; Respiratory disease; Metabolic diseases; Cystic fibrosis; POLYPHEN; Genetic disease; PANTHER; Missense mutation; Gene; Substitution; pancreatic insufficiency; Aminoacid; Digestive diseases; Genetics; Predictive factor; Pancreas; Cystic fibrosis transmembrane conductance regulator; disease severity; CFTR; Pancreatic disease; CBAVD; CFTR-related disease
• ISSN: 0009-9163; 1399-0004
• DOI: 10.1111/j.1399-0004.2009.01351.x

Dorfman R, Nalpathamkalam T, Taylor C, Gonska T, Keenan K, Yuan XW, Corey M, Tsui L‐C, Zielenski J, Durie P. Do common in silico tools predict the clinical consequences of amino‐acid substitutions in the CFTR gene? Computational methods are used to predict the molecular consequences of amino‐acid substitutions on the basis of evolutionary conservation or protein structure, but their utility in clinical diagnosis or prediction of disease outcome has not been well validated. We evaluated three popular computer programs, namely, PANTHER, SIFT and PolyPhen, by comparing the predicted clinical outcomes for a group of known CFTR missense mutations against the diagnosis of cystic fibrosis (CF) and clinical manifestations in cohorts of subjects with CF‐disease and CFTR‐related disorders carrying these mutations. Owing to poor specificity, none of tools reliably distinguished between individual mutations that confer CF disease from mutations found in subjects with a CFTR‐related disorder or no disease. Prediction scores for CFTR mutations derived from PANTHER showed a significant overall statistical correlation with the spectrum of disease severity associated with mutations in the CFTR gene. In contrast, PolyPhen‐ and SIFT‐derived scores only showed significant differences between CF‐causing and non‐CF variants. Current computational methods are not recommended for establishing or excluding a CF diagnosis, notably as a newborn screening strategy or in patients with equivocal test results.