Heliyon (Apr 2024)
CFTR pathogenic variants spectrum in a cohort of Mexican patients with cystic fibrosis
Abstract
Background: Molecular diagnosis of cystic fibrosis (CF) is challenging in Mexico due to the population's high genetic heterogeneity. To date, 46 pathogenic variants (PVs) have been reported, yielding a detection rate of 77%. We updated the spectrum and frequency of PVs responsible for this disease in mexican patients. Methods: We extracted genomic DNA from peripheral blood lymphocytes obtained from 297 CF patients and their parents. First, we analyzed the five most frequent PVs in the Mexican population using PCR-mediated site-directed mutagenesis. In patients with at least one identified allele, CFTR sequencing was performed using next-generation sequencing tools and multiplex ligation-dependent probe amplification. For variants not previously classified as pathogenic, we used a combination of in silico prediction, CFTR modeling, and clinical characteristics to determine a genotype–phenotype correlation. Results: We identified 95 PVs, increasing the detection rate to 87.04%. The most frequent variants were p.(PheF508del) (42.7%), followed by p.(Gly542*) (5.6%), p.(Ser945Leu) (2.9%), p.(Trp1204*) and p.(Ser549Asn) (2.5%), and CFTRdel25–26 and p.(Asn386Ilefs*3) (2.3%). The remaining variants had frequencies of <2.0%, and some were exclusive to one family. We identified 10 novel PVs localized in different exons (frequency range: 0.1–0.8%), all of which produced structural changes, deletions, or duplications in different domains of the protein, resulting in dysfunctional ion flow. The use of different in silico software and American College of Medical Genetics and Genomics (ACMG) and the Association for Molecular Pathology (AMP) criteria allowed us to assume that all of these PVs were pathogenic, causing a severe phenotype. Conclusions: In a highly heterogeneous population, combinations of different tools are needed to identify the variants responsible for CF and enable the establishment of appropriate strategies for CF diagnosis, prevention, and treatment.
