Untargeted Metabolomic and Lipidomic Profiling in Cystic Fibrosis Patients Using UPLC-QTOF-MS.

Cystic fibrosis (CF), also known as mucoviscidosis, is a rare, autosomal recessive genetic disease. It is caused by various mutations in the CFTR (Cystic Fibrosis Transmembrane Conductance Regulator) gene, which disrupt the normal function of the chloride ion channel. Clinical manifestations of CF typically include recurrent respiratory infections, chronic airway inflammation, a progressive decline in lung function, and intermittent pulmonary exacerbations. The primary aim of our study is to identify plasma biomarkers in patients with cystic fibrosis through untargeted metabolomic and lipidomic analyses, with the goal of enabling early detection, accurate diagnosis, and effective monitoring of the disease. Liquid chromatography (LC) coupled with time-of-flight mass spectrometry (TOF-MS) was employed to discriminate the 24 cystic fibrosis patients from the 26 age- and gender-matched healthy controls. Multivariate statistical and pathway enrichment analyses revealed dysregulation in galactose metabolism, glycolysis/gluconeogenesis, bile acid metabolism, fatty acid metabolism, steroid hormone biosynthesis, and amino acid catabolism. The quantification of the targeted cystic fibrosis biomarkers identified by combined lipidomic and metabolomic analyses will be valuable for early diagnosis and treatment.