Urinary metabolomic study of systemic lupus erythematosus based on gas chromatography/mass spectrometry

2016 ◽  
Vol 30 (11) ◽  
pp. 1877-1881 ◽  
Author(s):  
Bei Yan ◽  
Jia Huang ◽  
Fan Dong ◽  
Liping Yang ◽  
Cibo Huang ◽  
...  
2018 ◽  
Vol 2018 ◽  
pp. 1-11
Author(s):  
Wei-ni Ma ◽  
Ming-mei Zhou ◽  
Xiao-jun Gou ◽  
Le Zhao ◽  
Fang Cen ◽  
...  

The urinary metabolomic study based on gas chromatography-mass spectrometry (GC-MS) had been developed to investigate the possible antidepressant mechanism of chlorogenic acid (CGA) in a rat model of sleep deprivation (SD). According to pattern recognition analysis, there was a clear separation among big platform group (BP), sleep deprivation group (SD), and the CGA (model + CGA), and CGA group was much closer to the BP group by showing a tendency of recovering towards BP group. Thirty-six significantly changed metabolites related to antidepressant by CGA were identified and used to explore the potential mechanism. Combined with the result of the classic behavioral tests and biochemical indices, CGA has significant antidepressant effects in a rat model of SD, suggesting that the mechanism of action of CGA might be involved in regulating the abnormal pathway of nicotinate and nicotinamide metabolism; glyoxylate and dicarboxylate metabolism; glycine, serine, and threonine metabolism; and arginine and proline metabolism. Our results also show that metabolomics analysis based on GC-MS is a useful tool for exploring biomarkers involved in depression and elucidating the potential therapeutic mechanisms of Chinese medicine.


2021 ◽  
Vol 2021 ◽  
pp. 1-17
Author(s):  
Li Zeng ◽  
Nian Chen ◽  
Junlin Liao ◽  
Xu Shen ◽  
Shenghua Song ◽  
...  

The biological mechanism underlying the pathogenesis of systemic lupus erythematosus (SLE) remains unclear. In this study, we found 21 proteins upregulated and 38 proteins downregulated by SLE relative to normal protein metabolism in our samples using liquid chromatography-mass spectrometry. By PPI network analysis, we identified 9 key proteins of SLE, including AHSG, VWF, IGF1, ORM2, ORM1, SERPINA1, IGF2, IGFBP3, and LEP. In addition, we identified 4569 differentially expressed metabolites in SLE sera, including 1145 reduced metabolites and 3424 induced metabolites. Bioinformatics analysis showed that protein alterations in SLE were associated with modulation of multiple immune pathways, TP53 signaling, and AMPK signaling. In addition, we found altered metabolites associated with valine, leucine, and isoleucine biosynthesis; one carbon pool by folate; tyrosine metabolism; arginine and proline metabolism; glycine, serine, and threonine metabolism; limonene and pinene degradation; tryptophan metabolism; caffeine metabolism; vitamin B6 metabolism. We also constructed differently expressed protein-metabolite network to reveal the interaction among differently expressed proteins and metabolites in SLE. A total of 481 proteins and 327 metabolites were included in this network. Although the role of altered metabolites and proteins in the diagnosis and therapy of SLE needs to be further investigated, the present study may provide new insights into the role of metabolites in SLE.


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