Citation

Xia Z, Liu W, Zheng F, Huang W, Xing Z, Peng W, Tang T, Luo J, Yi L, Wang Y. ASN Neuro 2020; 12: e1759091420910957.

Affiliation

Department of Integrated Traditional Chinese and Western Medicine, Xiangya Hospital, Central South University.

Copyright

(Copyright © 2020, SAGE Publishing)

DOI

10.1177/1759091420910957

PMID

32146828

Abstract

Metabolomics is an emerging tool to uncover the complex pathogenesis of disease, as well as the multitargets of traditional Chinese medicines, with chemometric analysis being a key step. However, conventional algorithms are not suitable for directly analyzing data at all times. The variable iterative space shrinkage approach-partial least squares-discriminant analysis, a novel algorithm for data mining, was first explored to screen metabolic varieties to reveal the multitargets of Xuefu Zhuyu decoction (XFZY) against traumatic brain injury (TBI) by the 7th day. Rat plasma from Sham, Vehicle, and XFZY groups was used for gas chromatography/mass spectrometry-based metabolomics. This method showed an improved discrimination ability (area under the curve = 93.64%). Threonine, trans-4-hydroxyproline, and creatinine were identified as the direct metabolic targets of XFZY against TBI. Five metabolic pathways affected by XFZY in TBI rats, were enriched using Metabolic Pathway Analysis web tool (i.e., phenylalanine, tyrosine, and tryptophan biosynthesis; phenylalanine metabolism; galactose metabolism; alanine, aspartate, and glutamate metabolism; and tryptophan metabolism). In conclusion, metabolomics coupled with variable iterative space shrinkage approach-partial least squares-discriminant analysis model may be a valuable tool for identifying the holistic molecular mechanisms involved in the effects of traditional Chinese medicine, such as XFZY.

Language: en

Keywords

VISSA-PLS-DA; Xuefu Zhuyu decoction; gas chromatography/mass spectrometry; metabolomics; traumatic brain injury