Literature DB >> 25910067

A Genotypic-Oriented View of CFTR Genetics Highlights Specific Mutational Patterns Underlying Clinical Macrocategories of Cystic Fibrosis.

Marco Lucarelli1,2,3, Sabina Maria Bruno1, Silvia Pierandrei1,2, Giampiero Ferraguti1, Antonella Stamato3,4,5, Fabiana Narzi3,4,5, Annalisa Amato3,4,5, Giuseppe Cimino3,5, Serenella Bertasi3,5, Serena Quattrucci3,4,5, Roberto Strom1,3.   

Abstract

Cystic fibrosis (CF) is a monogenic disease caused by mutations of the cystic fibrosis transmembrane conductance regulator (CFTR) gene. The genotype-phenotype relationship in this disease is still unclear, and diagnostic, prognostic and therapeutic challenges persist. We enrolled 610 patients with different forms of CF and studied them from a clinical, biochemical, microbiological and genetic point of view. Overall, there were 125 different mutated alleles (11 with novel mutations and 10 with complex mutations) and 225 genotypes. A strong correlation between mutational patterns at the genotypic level and phenotypic macrocategories emerged. This specificity appears to largely depend on rare and individual mutations, as well as on the varying prevalence of common alleles in different clinical macrocategories. However, 19 genotypes appeared to underlie different clinical forms of the disease. The dissection of the pathway from the CFTR mutated genotype to the clinical phenotype allowed to identify at least two components of the variability usually found in the genotype-phenotype relationship. One component seems to depend on the genetic variation of CFTR, the other component on the cumulative effect of variations in other genes and cellular pathways independent from CFTR. The experimental dissection of the overall biological CFTR pathway appears to be a powerful approach for a better comprehension of the genotype-phenotype relationship. However, a change from an allele-oriented to a genotypic-oriented view of CFTR genetics is mandatory, as well as a better assessment of sources of variability within the CFTR pathway.

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Year:  2015        PMID: 25910067      PMCID: PMC4503653          DOI: 10.2119/molmed.2014.00229

Source DB:  PubMed          Journal:  Mol Med        ISSN: 1076-1551            Impact factor:   6.354


  47 in total

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