CFTR pathogenic variants spectrum in a cohort of Mexican patients with cystic fibrosis
Angélica Martínez-Hernández,
Elvia C. Mendoza-Caamal,
Namibia G. Mendiola-Vidal,
Francisco Barajas-Olmos,
José Rafael Villafan-Bernal,
Juan Luis Jiménez-Ruiz,
Tulia Monge-Cazares,
Humberto García-Ortiz,
Cecilia Contreras- Cubas,
Federico Centeno-Cruz,
Carmen Alaez-Verson,
Soraya Ortega-Torres,
Adriana del C. Luna-Castañeda,
Vicente Baca,
José Luis Lezana,
Lorena Orozco
Affiliations
Angélica Martínez-Hernández
Immunogenomics and Metabolic Disease Laboratory, Instituto Nacional de Medicina Genomica, SS, Tlalpan, 14610, Mexico City, Mexico
Elvia C. Mendoza-Caamal
Clinical Area, Instituto Nacional de Medicina Genómica, SS, Tlalpan, 14610, CDMX, Mexico City, Mexico
Namibia G. Mendiola-Vidal
Immunogenomics and Metabolic Disease Laboratory, Instituto Nacional de Medicina Genomica, SS, Tlalpan, 14610, Mexico City, Mexico; Maestría en Ciencias Médicas. PMDCMOS. Sede: HGGEA, UNAM. Coyoacan, 04510, Mexico City, Mexico
Francisco Barajas-Olmos
Immunogenomics and Metabolic Disease Laboratory, Instituto Nacional de Medicina Genomica, SS, Tlalpan, 14610, Mexico City, Mexico
José Rafael Villafan-Bernal
Immunogenomics and Metabolic Disease Laboratory, Instituto Nacional de Medicina Genomica, SS, Tlalpan, 14610, Mexico City, Mexico; Investigador por Mexico, Consejo Nacional de Humanidades, Ciencia y Tecnología (CONAHCYT), Benito Juarez, 03940, Mexico City, Mexico
Juan Luis Jiménez-Ruiz
Immunogenomics and Metabolic Disease Laboratory, Instituto Nacional de Medicina Genomica, SS, Tlalpan, 14610, Mexico City, Mexico
Tulia Monge-Cazares
Immunogenomics and Metabolic Disease Laboratory, Instituto Nacional de Medicina Genomica, SS, Tlalpan, 14610, Mexico City, Mexico
Humberto García-Ortiz
Immunogenomics and Metabolic Disease Laboratory, Instituto Nacional de Medicina Genomica, SS, Tlalpan, 14610, Mexico City, Mexico
Cecilia Contreras- Cubas
Immunogenomics and Metabolic Disease Laboratory, Instituto Nacional de Medicina Genomica, SS, Tlalpan, 14610, Mexico City, Mexico
Federico Centeno-Cruz
Immunogenomics and Metabolic Disease Laboratory, Instituto Nacional de Medicina Genomica, SS, Tlalpan, 14610, Mexico City, Mexico
Carmen Alaez-Verson
Genomic Diagnostic Laboratory, Instituto Nacional de Medicina Genomica, SS, Tlalpan, 14610, CDMX, Mexico City, Mexico
Soraya Ortega-Torres
Curso de Alta Especialidad en Medicina Genómica, Instituto Nacional de Medicina Genomica, Facultad de Medicina, Universidad Nacional Autonoma de Mexico, Coyoacan, 04510, Mexico City, Mexico
Adriana del C. Luna-Castañeda
Neumology Department, Hospital de Pediatría, CMN Siglo XXI IMSS, Cuauhtemoc, 06720, Mexico City, Mexico
Vicente Baca
Rheumatology Department, Hospital de Pediatría, CMN Siglo XXI IMSS, Cuauhtemoc, 06720, Mexico City, Mexico
José Luis Lezana
Cystic Fibrosis Clinic and Pulmonary Physiology Laboratory. Hospital Infantil de Mexico Federico Gómez, SS, Cuauhtemoc, 06720, Mexico City, Mexico; Asociacion Mexicana de Fibrosis Quistica, A.C. Benito Juarez, 03700, Mexico City, Mexico
Lorena Orozco
Immunogenomics and Metabolic Disease Laboratory, Instituto Nacional de Medicina Genomica, SS, Tlalpan, 14610, Mexico City, Mexico; Corresponding author.
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.