Metabolic Profiling Regarding Pathogenesis of Idiopathic Pulmonary Fibrosis

Idiopathic pulmonary fibrosis (IPF) is a progressive, eventually fatal disease characterized by fibrosis of the lung parenchyma and loss of lung function. IPF is believed to be caused by repetitive alveolar epithelial cell injury and dysregulated repair process including uncontrolled proliferation o...

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Published in:Journal of proteome research 2016-05, Vol.15 (5), p.1717-1724
Main Authors: Kang, Yun Pyo, Lee, Sae Bom, Lee, Ji-min, Kim, Hyung Min, Hong, Ji Yeon, Lee, Won Jun, Choi, Chang Woo, Shin, Hwa Kyun, Kim, Do-Jin, Koh, Eun Suk, Park, Choon-Sik, Kwon, Sung Won, Park, Sung-Woo
Format: Article
Language:English
Subjects:
Case-Control Studies
Cells, Cultured
Discriminant Analysis
Gas Chromatography-Mass Spectrometry
Humans
Idiopathic Pulmonary Fibrosis - metabolism
Idiopathic Pulmonary Fibrosis - pathology
Metabolic Networks and Pathways
Metabolomics - methods
Myofibroblasts - metabolism
Myofibroblasts - pathology
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Summary:Idiopathic pulmonary fibrosis (IPF) is a progressive, eventually fatal disease characterized by fibrosis of the lung parenchyma and loss of lung function. IPF is believed to be caused by repetitive alveolar epithelial cell injury and dysregulated repair process including uncontrolled proliferation of lung (myo) fibroblasts and excessive deposition of extracellular matrix proteins in the interstitial space; however, the pathogenic pathways involved in IPF have not been fully elucidated. In this study, we attempted to characterize metabolic changes of lung tissues involved in the pathogenesis of IPF using gas chromatography–mass spectrometry-based metabolic profiling. Partial least-squares discriminant analysis (PLS-DA) model generated from metabolite data was able to discriminate between the control subjects and IPF patients (R 2 X = 0.37, R 2 Y = 0.613 and Q 2 (cumulative) = 0.54, receiver operator characteristic AUC > 0.9). We discovered 25 metabolite signatures of IPF using both univariate and multivariate statistical analyses (FDR < 0.05 and VIP score of PLS-DA > 1). These metabolite signatures indicated alteration in metabolic pathways: adenosine triphosphate degradation pathway, glycolysis pathway, glutathione biosynthesis pathway, and ornithine aminotransferase pathway. The results could provide additional insight into understanding the disease and potential for developing biomarkers.
ISSN:1535-3893
1535-3907
DOI:10.1021/acs.jproteome.6b00156