Next-Generation Sequencing for Screening Analysis of Cystic Fibrosis: Spectrum and Novel Variants in a South–Central Italian Cohort

• Published in: Genes Vol. 14; no. 8; p. 1608
• Main Authors: De Paolis, Elisa, Tilocca, Bruno, Lombardi, Carla, De Bonis, Maria, Concolino, Paola, Onori, Maria Elisabetta, Ricciardi Tenore, Claudio, Perrucci, Alessia, Roncada, Paola, Capoluongo, Ettore, Urbani, Andrea, Minucci, Angelo, Santonocito, Concetta
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 11.08.2023; MDPI
• Subjects: alleles; Bioinformatics; Cystic fibrosis; Cystic fibrosis transmembrane conductance regulator; Data analysis; Forecasts and trends; Genetic testing; heterozygosity; Information management; Italy; Mutation; Next-generation sequencing; Pathogenicity; prediction; Proteins; White people; United States > US; Italy
• ISSN: 2073-4425; 2073-4425
• DOI: 10.3390/genes14081608

The incidence of cystic fibrosis (CF) and the spectrum of cystic fibrosis transmembrane conductance regulator (CFTR) gene variants differ among geographic regions. Differences in CF carrier distribution are also reported among Italian regions. We described the spectrum of the CFTR variants observed in a large group of subjects belonging from central–southern Italy. We also provide a predictive evaluation of the novel variants identified. CFTR screening was performed in a south–central Italian cohort of 770 subjects. We adopted a next-generation sequencing (NGS) approach using the Devyser CFTR NGS kit on the Illumina MiSeq System coupled with Amplicon Suite data analysis. Bioinformatics evaluation of the impact of novel variants was described. Overall, the presence of at least one alternative allele in the CFTR gene was recorded for 23% of the subjects, with a carrier frequency of CF pathogenic variants of 1:12. The largest sub-group corresponded to the heterozygous carriers of a variant with a conflicting interpretation of pathogenicity. The common CFTR p.(Phe508del) pathogenic variants were identified in 37% of mutated subjects. Bioinformatics prediction supported a potential damaging effect for the three novel CFTR variants identified: p.(Leu1187Phe), p.(Pro22Thr), and c.744-3C > G. NGS applied to CF screening had the benefit of: effectively identifying asymptomatic carriers. It lies in a wide overview of CFTR variants and gives a comprehensive picture of the carrier prevalence. The identification of a high number of unclassified variants may represent a challenge whilst at the same time being of interest and relevance for clinicians.