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Phenotype-optimized sequence ensembles substantially improve prediction of disease-causing mutation in cystic fibrosis.

ABSTRACT: Cystic fibrosis transmembrane conductance regulator (CFTR) mutation is associated with a phenotypic spectrum that includes cystic fibrosis (CF). The disease liability of some common CFTR mutations is known, but rare mutations are seen in too few patients to categorize unequivocally, making genetic diagnosis difficult. Computational methods can predict the impact of mutation, but prediction specificity is often below that required for clinical utility. Here, we present a novel supervised learning approach for predicting CF from CFTR missense mutation. The algorithm begins by constructing custom multiple sequence alignments called phenotype-optimized sequence ensembles (POSEs). POSEs are constructed iteratively, by selecting sequences that optimize predictive performance on a training set of CFTR mutations of known clinical significance. Next, we predict CF disease liability from a different set of CFTR mutations (test-set mutations). This approach achieves improved prediction performance relative to popular methods recently assessed using the same test-set mutations. Of clinical significance, our method achieves 94% prediction specificity. Because databases such as HGMD and locus-specific mutation databases are growing rapidly, methods that automatically tailor their predictions for a specific phenotype may be of immediate utility. If the performance achieved here generalizes to other systems, the approach could be an excellent tool to help establish genetic diagnoses.

SUBMITTER: Masica DL

PROVIDER: S-EPMC4364283 | biostudies-literature | 2012 Aug

REPOSITORIES: biostudies-literature

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Phenotype-optimized sequence ensembles substantially improve prediction of disease-causing mutation in cystic fibrosis.

Masica David L DL Sosnay Patrick R PR Cutting Garry R GR Karchin Rachel R

Human mutation 20120522 8

Cystic fibrosis transmembrane conductance regulator (CFTR) mutation is associated with a phenotypic spectrum that includes cystic fibrosis (CF). The disease liability of some common CFTR mutations is known, but rare mutations are seen in too few patients to categorize unequivocally, making genetic diagnosis difficult. Computational methods can predict the impact of mutation, but prediction specificity is often below that required for clinical utility. Here, we present a novel supervised learning ...[more]

PMID: 22573477

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Project description:Cystic fibrosis (CF) is caused by mutations in the CFTR gene that impair the function of CFTR, a cAMP-regulated anion channel. In the small intestine loss of CFTR function creates a dehydrated, acidic luminal environment which is believed to cause an accumulation of mucus, a phenotype characteristic of CF. CF mice have small intestinal bacterial overgrowth, an altered innate immune response, and impaired intestinal transit. We investigated whether lubiprostone, which can activate the CLC2 Cl- channel, would improve the intestinal phenotype in CF mice.Cftr(tm1UNC) (CF) and wildtype (WT) littermate mice on the C57BL/6J background were used. Lubiprostone (10 ?g/kg-day) was administered by gavage for two weeks. Mucus accumulation was estimated from crypt lumen widths in periodic acid-Schiff base, Alcian blue stained sections. Luminal bacterial load was measured by qPCR for the bacterial 16S gene. Gastric emptying and small intestinal transit in fasted mice were assessed using gavaged rhodamine dextran. Gene expression was evaluated by Affymetrix Mouse430 2.0 microarray and qRT-PCR.Crypt width in control CF mice was 700% that of WT mice (P < 0.001). Lubiprostone did not affect WT crypt width but, unexpectedly, increased CF crypt width 22% (P = 0.001). Lubiprostone increased bacterial load in WT mice to 490% of WT control levels (P = 0.008). Conversely, lubiprostone decreased bacterial overgrowth in CF mice by 60% (P = 0.005). Lubiprostone increased gastric emptying at 20 min postgavage in both WT (P < 0.001) and CF mice (P < 0.001). Lubiprostone enhanced small intestinal transit in WT mice (P = 0.024) but not in CF mice (P = 0.377). Among other innate immune markers, expression of mast cell genes was elevated 4-to 40-fold in the CF intestine as compared to WT, and lubiprostone treatment of CF mice decreased expression to WT control levels.These results indicate that lubiprostone has some benefits for the CF intestinal phenotype, especially on bacterial overgrowth and the innate immune response. The unexpected observation of increased mucus accumulation in the crypts of lubiprostone-treated CF mice suggests the possibility that lubiprostone increases mucus secretion.

Dataset Information

Phenotype-optimized sequence ensembles substantially improve prediction of disease-causing mutation in cystic fibrosis.

Publications

Phenotype-optimized sequence ensembles substantially improve prediction of disease-causing mutation in cystic fibrosis.

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