Abstracts from the 23rd Italian congress of Cystic Fibrosis and the 13th National congress of Cystic Fibrosis Italian Society: Alessandra Coiana: New technologies, new opportunities, new interpretative challenges in molecular genetics of Cystic Fibrosis

Cystic Fibrosis (CF) occurs most frequently in caucasian populations. Although less common, this disorder have been reported in all the ethnicities. Currently, there are more than 2000 described sequence variations in CFTR gene, uniformly distributed and including variants pathogenic and benign (CFTR1:www.genet.sickkids.on.ca/). To date,only a subset have been firmily established as variants annotated as disease-causing (CFTR2: www.cftr2.org). The spectrum and the frequency of individual CFTR variants, however, vary among specific ethnic groups and geographic areas. Genetic screening for CF with standard panels of CFTR mutations is widely used for the diagnosis of CF in newborns and symptomatic patients, and to diagnose CF carrier status. These screening panels have an high diagnostic sensitivity (around 85%) for CFTR mutations in caucasians populations but very low for non caucasians. Developed in the last decade, Next-Generation Sequencing (NGS) has been the last breakthrough technology in genetic studies with a substantial reduction in cost per sequenced base and a considerable enhancement of the sequence generation capabilities. Extended CFTR gene sequencing in NGS includes all the coding regions, the splicing sites and their flankig intronic regions, deep intronic regions where are localized known mutations,the promoter and the 5'-3' UTR regions. NGS allows the analysis of many samples concurrently in a shorter period of time compared to Sanger method . Moreover, NGS platforms are able to identify CFTR copy number variation (CNVs), not detected by Sanger sequencing. This technology has provided new and reliable approaches to molecular diagnosis of CF and CFTR-Related Disorders. It also allows to improve the diagnostic sensitivity of newborn and carrier screeningmolecular tests. In fact, bioinformatics tools suitable for all the NGS platforms can filter data generated from the gene sequencing, and analyze only mutations with well-established disease liability. This approach allows the development of targeted mutations panels with a higher number of frequent CF mutations for the target populationcompared to the standard panels and a consequent enhancement of the diagnostic sensitivity. Moreover, in the emerging challenge of diagnosing CF in non caucasians patients, the possibility of customize a NGS targeted mutations panel should increase the diagnostic sensitivity when the target population has different ethnicities.