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

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.

Keywords: CFTR cystic fibrosis; NGS next generation sequencing.

Fig. 1

NGS data analysis results. a. Mean and median coverage for each CFTR exon across 84 samples b. Identified complex alleles mapped into CFTR gene product. MSD - membrane-spanning domains, NBD - nucleotide-binding domain 1 c. Total and unique mutation calls count by CFTR exon across 84 samples

Fig. 2

Capability of the semiconductor technology to detect mutations near homopolymer regions. a. Mutation c.2052dupA occur in (A)7 homopolymer region of the CFTR which is complicated to accurately discriminate with the semiconductor NGS technology b. Single sample carrying c.2052dupA mutation demonstrates presence of the variant (A)8 allele in sequencing reads (indicated by arrows) alongside with the (A)7, (A)6 and (A)5 alleles in contrast to sample without mutation, harboring predominantly (A)7, (A)6 and (A)5 alleles c. Distribution of (A)8 variant allele frequency across sequencing among all samples. The majority of samples are grouped below 10% allele frequency, while mutation carries have frequencies of 16, 18, 21 and 42%

Fig. 3

Impact of the primer trimming on variant calling. Detection of the p.Glu92Lys variant was complicated by presence of the technical sequences in data, which lead to false negative calls employing standard pipelines: a. Technical sequences (primers) result in reference allele overestimation and influence variant calling b. Trimming primers allow to detect mutation in all samples

Fig. 4

Missense substitutions and in-frame deletions/insertions annotated in accordance with used variant databases and computational tools. VUS stands for Variant of Uncertain Significance; D – pathogenic; N – benign/non CF-causing; U – annotation could not be assessed; VVS – variant of varying clinical significance according to CFRT2 variant classification