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Exome sequencing used for molecular diagnosis of Mendelian disorders considerably increases the number of missense variants of unclear significance, whose pathogenicity can be assessed by a variety of prediction tools. As the performance of algorithms may vary according to the datasets, complementary specific resources are needed to improve variant interpretation. As a model, we were interested in the cystic fibrosis transmembrane conductance regulator gene (CFTR) causing cystic fibrosis, in which at least 40% of missense variants are reported. Cystic fibrosis missense analysis (CYSMA) is a new web server designed for online estimation of the pathological relevance of CFTR missense variants. CYSMA generates a set of computationally derived data, ranging from evolutionary conservation to functional observations from three-dimensional structures, provides all available allelic frequencies, clinical observations, and references for functional studies. Compared to software classically used in analysis pipelines on a dataset of 141 well-characterized missense variants, CYSMA was the most efficient tool to discriminate benign missense variants, with a specificity of 85%, and very good sensitivity of 89%. These results suggest that such integrative tools could be adapted to numbers of genes involved in Mendelian disorders to improve the interpretation of missense variants identified in the context of diagnosis., (© 2019 Wiley Periodicals, Inc.)

Whole-exome/genome sequencing analyses lead to detect disease-causing variants that are unrelated to the initial clinical question. Irrespective of any actionable gene list, only pathogenic variants should be considered. The pathogenicity of 55 cystic fibrosis transmembrane conductance regulator (CFTR) variants of known various impacts was assessed by a group of experts by comparing data from specialized databases CFTR-France and CFTR2 with those of general clinical databases ClinVar and Human Gene Mutation Database (HGMD®) Professional and data aggregators VarSome and InterVar. The assessment of cystic fibrosis (CF) variants was correct with ClinVar and HGMD® Professional while less reliable with VarSome and InterVar. Conversely, the risk of overclassifying variants as CF-causing was up to 82% with HGMD® Professional. The concordance between data aggregators was only 50%. The use of general databases and aggregators is thus associated with a substantial risk of misclassifying variants. This evaluation may be extrapolated to other disease conditions and incites to remain cautious in interpreting and disclosing incidental findings., (© 2019 Wiley Periodicals, Inc.)

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., (© 2017 Wiley Periodicals, Inc.)

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., (© 2013 Wiley Periodicals, Inc.)