Metabolic profiling of idiopathic pulmonary fibrosis in a mouse model: implications for pathogenesis and biomarker discovery

被引:0
作者
Zhang, Yu-zhu [1 ]
Jia, Xiu-juan [1 ]
Xu, Wen-juan [2 ]
Ding, Xiao-qian [2 ]
Wang, Xiao-meng [1 ]
Chi, Xiao-sa [1 ]
Hu, Yi [1 ]
Yang, Xiao-hui [2 ]
机构
[1] Qingdao Univ, Affiliated Hosp, Dept Geriatr, Qingdao, Peoples R China
[2] Qingdao Univ, Affiliated Hosp, Dept Resp & Crit Care Med, Qingdao, Peoples R China
关键词
pulmonary fibrosis; metabolites; machine learning; biomarkers; mice; MYOFIBROBLAST DIFFERENTIATION; METALLOPROTEINASES; INFLAMMATION; ACTIVATION; DIAGNOSIS;
D O I
10.3389/fmed.2024.1410051
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
Background Alterations in metabolites and metabolic pathways are thought to be important triggers of idiopathic pulmonary fibrosis (IPF), but our lack of a comprehensive understanding of this process has hampered the development of IPF-targeted drugs.Methods To fully understand the metabolic profile of IPF, C57BL/6 J male mice were injected intratracheally with bleomycin so that it could be used to construct a mouse model of IPF, and lung tissues from 28-day and control IPF mice were analyzed by pathology and immunohistochemistry. In addition, serum metabolites from IPF mice were examined using LC-ESI-MS/MS, and the differential metabolites were analyzed for KEGG metabolic pathways and screened for biomarkers using machine learning algorithms.Results In total, the levels of 1465 metabolites were detected, of which 104 metabolites were significantly altered after IPF formation. In IPF mouse serum, 52% of metabolite expression was downregulated, with lipids (e.g., GP, FA) and organic acids and their derivatives together accounting for more than 70% of the downregulated differentially expressed metabolites. In contrast, FA and oxidised lipids together accounted for 60% of the up-regulated differentially expressed metabolites. KEGG pathway enrichment analyses of differential metabolites were mainly enriched in the biosynthesis of unsaturated fatty acids, pentose phosphate pathway, and alanine, aspartate, and glutamate metabolism. Seven metabolites were screened by machine learning LASSO models and evaluated as ideal diagnostic tools by receiver operating characteristic curves (ROCs).Discussion In conclusion, the serum metabolic disorders found to be associated with pulmonary fibrosis formation will help to deepen our understanding of the pathogenesis of pulmonary fibrosis.
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页数:9
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