five

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

收藏
NIAID Data Ecosystem2026-05-10 收录
下载链接:
https://figshare.com/articles/dataset/Untargeted_Metabolomic_and_Lipidomic_Profiling_in_Cystic_Fibrosis_Patients_Using_UPLC-QTOF-MS/31646259
下载链接
链接失效反馈
官方服务:
资源简介:
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.
创建时间:
2026-03-11
5,000+
优质数据集
54 个
任务类型
进入经典数据集
二维码
社区交流群

面向社区/商业的数据集话题

二维码
科研交流群

面向高校/科研机构的开源数据集话题

数据驱动未来

携手共赢发展

商业合作