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dc.contributor.authorMichels, Marcus Silvapt_BR
dc.contributor.authorMatte, Ursula da Silveirapt_BR
dc.contributor.authorFraga, Lucas Rosapt_BR
dc.contributor.authorMancuso, Aline Castello Brancopt_BR
dc.contributor.authorBraun, Rodrigo Ligabuept_BR
dc.contributor.authorBerneira, Elias Figueroa Rodriguespt_BR
dc.contributor.authorSiebert, Marinapt_BR
dc.contributor.authorSanseverino, Maria Teresa Vieirapt_BR
dc.date.accessioned2020-02-01T04:14:29Zpt_BR
dc.date.issued2019pt_BR
dc.identifier.issn1415-4757pt_BR
dc.identifier.urihttp://hdl.handle.net/10183/205299pt_BR
dc.description.abstractPathogenic variants in the Cystic Fibrosis Transmembrane Conductance Regulator gene (CFTR) are responsible for cystic fibrosis (CF), the commonest monogenic autosomal recessive disease, and CFTR-related disorders in infants and youth. Diagnosis of such diseases relies on clinical, functional, and molecular studies. To date, over 2,000 variants have been described on CFTR (~40% missense). Since few of them have confirmed pathogenicity, in silico analysis could help molecular diagnosis and genetic counseling. Here, the pathogenicity of 779 CFTR missense variants was predicted by consensus predictor PredictSNP and compared to annotations on CFTR2 and ClinVar. Sensitivity and specificity analysis was divided into modeling and validation phases using just variants annotated on CFTR2 and/or ClinVar that were not in the validation datasets of the analyzed predictors. After validation phase, MAPP and PhDSNP achieved maximum specificity but low sensitivity. Otherwise, SNAP had maximum sensitivity but null specificity. PredictSNP, PolyPhen-1, PolyPhen-2, SIFT, nsSNPAnalyzer had either low sensitivity or specificity, or both. Results showed that most predictors were not reliable when analyzing CFTR missense variants, ratifying the importance of clinical information when asserting the pathogenicity of CFTR missense variants. Our results should contribute to clarify decision making when classifying the pathogenicity of CFTR missense variants.en
dc.format.mimetypeapplication/pdfpt_BR
dc.language.isoengpt_BR
dc.relation.ispartofGenetics and molecular biology. Ribeirão Preto. Vol. 42, no. 3 (2019), p. 560-570pt_BR
dc.rightsOpen Accessen
dc.subjectFibrose císticapt_BR
dc.subjectCFTRen
dc.subjectMissense varianten
dc.subjectBiomarcadorespt_BR
dc.subjectPredictionen
dc.subjectPrognósticopt_BR
dc.subjectRegulador de condutância transmembrana em fibrose císticapt_BR
dc.subjectBioinformaticsen
dc.subjectBiologia computacionalpt_BR
dc.subjectCystic fibrosisen
dc.subjectRNA mensageiropt_BR
dc.titleDetermining the pathogenicity of CFTR missense variants : multiple comparisons of in silico predictors and variant annotation databasespt_BR
dc.typeArtigo de periódicopt_BR
dc.identifier.nrb001107880pt_BR
dc.type.originNacionalpt_BR


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