Mutations of the CFTR gene and novel variants in Turkish patients with cystic fibrosis: 24-years experience

Dayangaç-Erden D., Atalay M., Emiralioğlu N., Hızal M., Polat S., Özçelik U., ...More

Clinica Chimica Acta, vol.510, pp.252-259, 2020 (SCI-Expanded) identifier identifier identifier

  • Publication Type: Article / Article
  • Volume: 510
  • Publication Date: 2020
  • Doi Number: 10.1016/j.cca.2020.07.033
  • Journal Name: Clinica Chimica Acta
  • Journal Indexes: Science Citation Index Expanded (SCI-EXPANDED), Scopus, Academic Search Premier, BIOSIS, CAB Abstracts, Chemical Abstracts Core, Chimica, EMBASE, MEDLINE, Veterinary Science Database
  • Page Numbers: pp.252-259
  • Keywords: Cystic fibrosis, Genetic screening, Novel variants, In silico analysis, Genotype- phenotype correlation, Personalized medicine
  • Hacettepe University Affiliated: Yes


© 2020 Elsevier B.V.Background: Cystic fibrosis, the most prevalent autosomal recessive genetic disease, is caused by mutations in the CFTR gene. The spectrum and frequency of CFTR mutations in Turkish patients show heterogeneity. Methods: We investigated CFTR gene mutations in samples from 604 cystic fibrosis patients diagnosed at Hacettepe University, the largest referral CF center in Turkey, by different techniques such as strip assay and direct sequencing. We also analyzed the effects of novel variants and predicted pathogenicity by integrating information from different insilico tools. Results: We showed that mutation detection rate increased to 76.7% with direct sequencing of the coding region and exon/intron boundaries. Ten variants were described for the first time. All variants except T788R were reported as pathogenic. Conclusion: Characterization of patients with CFTR mutations that occur at very low frequencies is necessary for mutation-based treatments. Population specific genetic screening panels should be designed since none of them are suitable for Turkish patients due to heterogeneous mutation distribution. The preliminary data obtained from in silico results of novel variants will pave the way for functional analysis by using samples obtained from patients. These observations will facilitate the discovery and development of new targeted and personalized therapies.