Open Access
Open access
volume 11 issue S1 publication number 13

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

Maxim Ivanov 1, 2
Alina Matsvay 1, 3
Olga Glazova 1
Stanislav Krasovskiy 4
Mariya Usacheva 4
Elena Amelina 4
Aleksandr Chernyak 4
Mikhail Ivanov 1
Sergey Musienko 2
Timofey Prodanov 5
Sergey Kovalenko 6, 7
ANCHA BARANOVA 1, 2, 8, 9
Kamil Khafizov 1, 3
Publication typeJournal Article
Publication date2018-02-13
scimago Q3
wos Q3
SJR0.701
CiteScore3.7
Impact factor2.0
ISSN17558794
Genetics
Genetics (clinical)
Abstract
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. 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. 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%). 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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GOST Copy
Ivanov M. et al. Targeted sequencing reveals complex, phenotype-correlated genotypes in cystic fibrosis // BMC Medical Genomics. 2018. Vol. 11. No. S1. 13
GOST all authors (up to 50) Copy
Ivanov M., Matsvay A., Glazova O., Krasovskiy S., Usacheva M., Amelina E., Chernyak A., Ivanov M., Musienko S., Prodanov T., Kovalenko S., BARANOVA A., Khafizov K. Targeted sequencing reveals complex, phenotype-correlated genotypes in cystic fibrosis // BMC Medical Genomics. 2018. Vol. 11. No. S1. 13
RIS |
Cite this
RIS Copy
TY - JOUR
DO - 10.1186/s12920-018-0328-z
UR - https://doi.org/10.1186/s12920-018-0328-z
TI - Targeted sequencing reveals complex, phenotype-correlated genotypes in cystic fibrosis
T2 - BMC Medical Genomics
AU - Ivanov, Maxim
AU - Matsvay, Alina
AU - Glazova, Olga
AU - Krasovskiy, Stanislav
AU - Usacheva, Mariya
AU - Amelina, Elena
AU - Chernyak, Aleksandr
AU - Ivanov, Mikhail
AU - Musienko, Sergey
AU - Prodanov, Timofey
AU - Kovalenko, Sergey
AU - BARANOVA, ANCHA
AU - Khafizov, Kamil
PY - 2018
DA - 2018/02/13
PB - Springer Nature
IS - S1
VL - 11
PMID - 29504914
SN - 1755-8794
ER -
BibTex
Cite this
BibTex (up to 50 authors) Copy
@article{2018_Ivanov,
author = {Maxim Ivanov and Alina Matsvay and Olga Glazova and Stanislav Krasovskiy and Mariya Usacheva and Elena Amelina and Aleksandr Chernyak and Mikhail Ivanov and Sergey Musienko and Timofey Prodanov and Sergey Kovalenko and ANCHA BARANOVA and Kamil Khafizov},
title = {Targeted sequencing reveals complex, phenotype-correlated genotypes in cystic fibrosis},
journal = {BMC Medical Genomics},
year = {2018},
volume = {11},
publisher = {Springer Nature},
month = {feb},
url = {https://doi.org/10.1186/s12920-018-0328-z},
number = {S1},
pages = {13},
doi = {10.1186/s12920-018-0328-z}
}