Cystic Fibrosis: Systems Biology Analysis from Homozygous p.Phe508del Variant Patients’ Samples Reveals Perturbations in Tissue-Specific Pathways

Cystic fibrosis (CF) is an autosomal recessive disorder, caused by diverse genetic variants for the CF transmembrane conductance regulator (CFTR) protein. Among these, p.Phe508del is the most prevalent variant. The effects of this variant on the physiology of each tissue remains unknown. This study...

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Veröffentlicht in:BioMed research international 2021, Vol.2021, p.5262000-16
Hauptverfasser: de Faria Poloni, Joice, Rispoli, Thaiane, Rossetti, Maria Lucia, Trindade, Cristiano, Vargas, José Eduardo
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Sprache:eng
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Zusammenfassung:Cystic fibrosis (CF) is an autosomal recessive disorder, caused by diverse genetic variants for the CF transmembrane conductance regulator (CFTR) protein. Among these, p.Phe508del is the most prevalent variant. The effects of this variant on the physiology of each tissue remains unknown. This study is aimed at predicting cell signaling pathways present in different tissues of fibrocystic patients, homozygous for p.Phe508del. The study involved analysis of two microarray datasets, E-GEOD-15568 and E-MTAB-360 corresponding to the rectal and bronchial epithelium, respectively, obtained from the ArrayExpress repository. Particularly, differentially expressed genes (DEGs) were predicted, protein-protein interaction (PPI) networks were designed, and centrality and functional interaction networks were analyzed. The study reported that p.Phe508del-mutated CFTR-allele in homozygous state influenced the whole gene expression in each tissue differently. Interestingly, gene ontology (GO) term enrichment analysis revealed that only “neutrophil activation” was shared between both tissues; however, nonshared DEGs were grouped into the same GO term. For further verification, functional interaction networks were generated, wherein no shared nodes were reported between these tissues. These results suggested that the p.Phe508del-mutated CFTR-allele in homozygous state promoted tissue-specific pathways in fibrocystic patients. The generated data might further assist in prediction diagnosis to define biomarkers or devising therapeutic strategies.
ISSN:2314-6133
2314-6141
DOI:10.1155/2021/5262000