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Defining the disease liability of variants in the cystic fibrosis transmembrane conductance regulator gene

Allelic heterogeneity in disease-causing genes presents a substantial challenge to the translation of genomic variation to clinical practice. Few of the almost 2,000 variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene have empirical evidence that they cause cystic fibrosi...

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Detalles Bibliográficos
Autores principales: Sosnay, Patrick R, Siklosi, Karen R, Van Goor, Fredrick, Kaniecki, Kyle, Yu, Haihui, Sharma, Neeraj, Ramalho, Anabela S, Amaral, Margarida D, Dorfman, Ruslan, Zielenski, Julian, Masica, David L, Karchin, Rachel, Millen, Linda, Thomas, Philip J, Patrinos, George P, Corey, Mary, Lewis, Michelle H, Rommens, Johanna M, Castellani, Carlo, Penland, Christopher M, Cutting, Garry R
Formato: Online Artículo Texto
Lenguaje:English
Publicado: 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3874936/
https://www.ncbi.nlm.nih.gov/pubmed/23974870
http://dx.doi.org/10.1038/ng.2745
Descripción
Sumario:Allelic heterogeneity in disease-causing genes presents a substantial challenge to the translation of genomic variation to clinical practice. Few of the almost 2,000 variants in the cystic fibrosis transmembrane conductance regulator (CFTR) gene have empirical evidence that they cause cystic fibrosis. To address this gap, we collected both genotype and phenotype data for 39,696 cystic fibrosis patients in registries and clinics in North America and Europe. Among these patients, 159 CFTR variants had an allele frequency of ≥0.01%. These variants were evaluated for both clinical severity and functional consequence with 127 (80%) meeting both clinical and functional criteria consistent with disease. Assessment of disease penetrance in 2,188 fathers of cystic fibrosis patients enabled assignment of 12 of the remaining 32 variants as neutral while the other 20 variants remained indeterminate. This study illustrates that sourcing data directly from well-phenotyped subjects can address the gap in our ability to interpret clinically-relevant genomic variation.