Most of the 2,000 variants identified in the CFTR (cystic fibrosis transmembrane regulator) gene are rare or private. Their interpretation is hampered by the lack of available data and resources, making patient care and genetic counseling challenging. We developed a patient-based database dedicated to the annotations of rare CFTR variants in the context of their cis- and trans-allelic combinations. Based on almost 30 years of experience of CFTR testing, CFTR-France (https://cftr.iurc.montp.inserm.fr/cftr) currently compiles 16,819 variant records from 4,615 individuals with cystic fibrosis (CF) or CFTR-RD (related disorders), fetuses with ultrasound bowel anomalies, newborns awaiting clinical diagnosis, and asymptomatic compound heterozygotes. For each of the 736 different variants reported in the database, patient characteristics and genetic information (other variations in cis or in trans) have been thoroughly checked by a dedicated curator. Combining updated clinical, epidemiological, in silico, or in vitro functional data helps to the interpretation of unclassified and the reassessment of misclassified variants. This comprehensive CFTR database is now an invaluable tool for diagnostic laboratories gathering information on rare variants, especially in the context of genetic counseling, prenatal and preimplantation genetic diagnosis. CFTR-France is thus highly complementary to the international database CFTR2 focused so far on the most common CF-causing alleles.

Our data confirm the importance of analyzing noncoding regions to find unidentified mutations, which is essential to designing targeted therapeutic approaches.

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.