BMC Medical Genomics (Feb 2018)

Targeted sequencing reveals complex, phenotype-correlated genotypes in cystic fibrosis

  • Maxim Ivanov,
  • Alina Matsvay,
  • Olga Glazova,
  • Stanislav Krasovskiy,
  • Mariya Usacheva,
  • Elena Amelina,
  • Aleksandr Chernyak,
  • Mikhail Ivanov,
  • Sergey Musienko,
  • Timofey Prodanov,
  • Sergey Kovalenko,
  • Ancha Baranova,
  • Kamil Khafizov

DOI
https://doi.org/10.1186/s12920-018-0328-z
Journal volume & issue
Vol. 11, no. S1
pp. 21 – 32

Abstract

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Abstract Background Cystic fibrosis (CF) is one of the most common life-threatening genetic disorders. Around 2000 variants in the CFTR gene have been identified, with some proportion known to be pathogenic and 300 disease-causing mutations have been characterized in detail by CFTR2 database, which complicates its analysis with conventional methods. Methods We conducted next-generation sequencing (NGS) in a cohort of 89 adult patients negative for p.Phe508del homozygosity. Complete clinical and demographic information were available for 84 patients. Results By combining MLPA with NGS, we identified disease-causing alleles in all the CF patients. Importantly, in 10% of cases, standard bioinformatics pipelines were inefficient in identifying causative mutations. Class IV-V mutations were observed in 38 (45%) cases, predominantly ones with pancreatic sufficient CF disease; rest of the patients had Class I-III mutations. Diabetes was seen only in patients homozygous for class I-III mutations. We found that 12% of the patients were heterozygous for more than two pathogenic CFTR mutations. Two patients were observed with p.[Arg1070Gln, Ser466*] complex allele which was associated with milder pulmonary obstructions (FVC 107 and 109% versus 67%, CI 95%: 63-72%; FEV 90 and 111% versus 47%, CI 95%: 37-48%). For the first time p.[Phe508del, Leu467Phe] complex allele was reported, observed in four patients (5%). Conclusion NGS can be a more information-gaining technology compared to standard methods. Combined with its equivalent diagnostic performance, it can therefore be implemented in the clinical practice, although careful validation is still required.

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