p.Ser1235Arg should no longer be considered as a cystic fibrosis mutation: results from a large collaborative study

The multi-faceted nature of 15 CFTR exonic variations: Impact on their functional classification and perspectives for therapy

BACKGROUND

The majority of variants of unknown clinical significance (VUCS) in the CFTR gene are missense variants. While change on the CFTR protein structure or function is often suspected, impact on splicing may be neglected. Such undetected splicing default of variants may complicate the interpretation of genetic analyses and the use of an appropriate pharmacotherapy.

METHODS

We selected 15 variants suspected to impact CFTR splicing after in silico predictions on 319 missense variants (214 VUCS), reported in the CFTR-France database. Six specialized laboratories assessed the impact of nucleotide substitutions on splicing (minigenes), mRNA expression levels (quantitative PCR), synthesis and maturation (western blot), cellular localization (immunofluorescence) and channel function (patch clamp) of the CFTR protein. We also studied maturation and function of the truncated protein, consecutive to in-frame aberrant splicing, on additional plasmid constructs.

RESULTS

Six of the 15 variants had a major impact on CFTR splicing by in-frame (n = 3) or out-of-frame (n = 3) exon skipping. We reclassified variants into: splicing variants; variants causing a splicing defect and the impairment of CFTR folding and/or function related to the amino acid substitution; deleterious missense variants that impair CFTR folding and/or function; and variants with no consequence on the different processes tested.

CONCLUSION

The 15 variants have been reclassified by our comprehensive approach of in vitro experiments that should be used to properly interpret very rare exonic variants of the CFTR gene. Targeted therapies may thus be adapted to the molecular defects regarding the results of laboratory experiments.

Disease-relevant mutations alter amino acid co-evolution networks in the second nucleotide binding domain of CFTR

Cystic Fibrosis (CF) is an inherited disease caused by mutations in the cystic fibrosis transmembrane conductance regulator (CFTR) ion channel. Mutations in CFTR cause impaired chloride ion transport in the epithelial tissues of patients leading to cardiopulmonary decline and pancreatic insufficiency in the most severely affected patients. CFTR is composed of twelve membrane-spanning domains, two nucleotide-binding domains (NBDs), and a regulatory domain. The most common mutation in CFTR is a deletion of phenylalanine at position 508 (ΔF508) in NBD1. Previous research has primarily concentrated on the structure and dynamics of the NBD1 domain; However numerous pathological mutations have also been found in the lesser-studied NBD2 domain. We have investigated the amino acid co-evolved network of interactions in NBD2, and the changes that occur in that network upon the introduction of CF and CF-related mutations (S1251N(T), S1235R, D1270N, N1303K(T)). Extensive coupling between the α- and β-subdomains were identified with residues in, or near Walker A, Walker B, H-loop and C-loop motifs. Alterations in the predicted residue network varied from moderate for the S1251T perturbation to more severe for N1303T. The S1235R and D1270N networks varied greatly compared to the wildtype, but these CF mutations only affect ion transport preference and do not severely disrupt CFTR function, suggesting dynamic flexibility in the network of interactions in NBD2. Our results also suggest that inappropriate interactions between the β-subdomain and Q-loop could be detrimental. We also identified mutations predicted to stabilize the NBD2 residue network upon introduction of the CF and CF-related mutations, and these predicted mutations are scored as benign by the MUTPRED2 algorithm. Our results suggest the level of disruption of the co-evolution predictions of the amino acid networks in NBD2 does not have a straightforward correlation with the severity of the CF phenotypes observed.

Novel, rare and common pathogenic variants in the CFTR gene screened by high-throughput sequencing technology and predicted by in silico tools

Cystic fibrosis (CF) is caused by ~300 pathogenic CFTR variants. The heterogeneity of which, challenges molecular diagnosis and precision medicine approaches in CF. Our objective was to identify CFTR variants through high-throughput sequencing (HTS) and to predict the pathogenicity of novel variants through in 8 silico tools. Two guidelines were followed to deduce the pathogenicity. A total of 169 CF patients had genomic DNA submitted to a Targeted Gene Sequencing and we identified 63 variants (three patients had three variants). The most frequent alleles were: F508del (n = 192), G542* (n = 26), N1303K (n = 11), R1162* and R334W (n = 9). The screened variants were classified as follows: 41 - pathogenic variants [classified as (I) n = 23, (II) n = 6, (III) n = 1, (IV) n = 6, (IV/V) n = 1 and (VI) n = 4]; 14 - variants of uncertain significance; and seven novel variants. To the novel variants we suggested the classification of 6b-16 exon duplication, G646* and 3557delA as Class I. There was concordance among the predictors as likely pathogenic for L935Q, cDNA.5808T>A and I1427I. Also, Y325F presented two discordant results among the predictors. HTS and in silico analysis can identify pathogenic CFTR variants and will open the door to integration of precision medicine into routine clinical practice in the near future.

A classification model relative to splicing for variants of unknown clinical significance: application to the CFTR gene

Molecular diagnosis of cystic fibrosis and cystic fibrosis transmembrane regulator (CFTR)-related disorders led to the worldwide identification of nearly 1,900 sequence variations in the CFTR gene that consist mainly of private point mutations and small insertions/deletions. Establishing their effect on the function of the encoded protein and therefore their involvement in the disease is still challenging and directly impacts genetic counseling. In this context, we built a decision tree following the international guidelines for the classification of variants of unknown clinical significance (VUCS) in the CFTR gene specifically focused on their consequences on splicing. We applied general and specific criteria, including comprehensive review of literature and databases, familial genetics data, and thorough in silico studies. This model was tested on 15 intronic and exonic VUCS identified in our cohort. Six variants were classified as probably nonpathogenic considering their impact on splicing and eight as probably pathogenic, which include two apparent missense mutations. We assessed the validity of our method by performing minigenes studies and confirmed that 93% (14/15) were correctly classified. We provide in this study a high-performance method that can play a full role in interpreting the results of molecular diagnosis in emergency context, when functional studies are not achievable.