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Exploratory Cortex Metabolic Profiling Revealed the Sedative Effect of Amber in Pentylenetetrazole-Induced Epilepsy-Like Mice - PubMed

  • ️Tue Jan 01 2019

Exploratory Cortex Metabolic Profiling Revealed the Sedative Effect of Amber in Pentylenetetrazole-Induced Epilepsy-Like Mice

Zhenhua Zhu et al. Molecules. 2019.

Abstract

Epilepsy is a common clinical syndrome characterized by sudden and recurrent attacks and temporary central nervous system dysfunction caused by excessive discharge of neurons in the brain. Amber, a fossilized organic substance formed by the resins of conifers and leguminous plants, was prescribed to tranquilize the mind in China. In this paper, the antiepileptic effect of amber was evaluated by a pentylenetetrazole (PTZ)-induced epileptic model. An untargeted metabolomics approach was applied to investigate metabolic changes in the epileptic model, which was based on HILIC-UHPLC-MS/MS multivariate statistical analysis and metabolism network analysis. The outcome of this study suggested that 35 endogenous metabolites showed marked perturbations. Moreover, four metabolism pathways were mainly involved in epilepsy. After treatment by amber, the endogenous metabolites had a marked tendency to revert back to the situation of the control group which was consistent with phenobarbital. This study characterized the pentylenetetrazole-induced epileptic model and provided new evidence for the sedative effect of amber.

Keywords: LC/MS; amber; epilepsy; glycerophospholipid metabolism; metabolomics.

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Conflict of interest statement

The authors declare no conflict of interest.

Figures

Figure 1
Figure 1

The effect of amber on behavior in the seizure model induced by pentylenetetrazole. (A) The incubation time of each group. Control group and PB group had no incubation time, and used 900 s for analysis. Under the intervention of amber, the incubation period was significantly prolonged compared to the model group. (B) Under the intervention of amber, the level of seizures was significantly reduced compared to the model group. ** p < 0.01 for extremely significant difference.

Figure 2
Figure 2

Amber rescues CA1 pyramidal neurons from seizure-induced damage as revealed by Nissl staining. (A) Control group; (B) Model group (PTZ); (C) PB group (PTZ + Phenobarbital); (D) Amber group (PTZ + amber). Photomicrographs show sample CA1 subfields (magnification, ×400) in the coronal plane for each treatment group. A damaged cell body is indicated by red frame. These signs of neural damage were reduced by amber pre-treatment.

Figure 3
Figure 3

Base peak chromatograms (BPCs) of cortex samples of control group, model group, and amber group under ESI+ (A) and ESI (B) MS conditions.

Figure 4
Figure 4

PCA scores scatter plot for control group, model group and amber group. (A) positive mode, R2X (cum) = 0.641, Q2 (cum) = 0.461; (B) negative mode, R2X (cum) = 0.836, Q2 (cum) = 0.449.

Figure 5
Figure 5

OPLS-DA score plot and validation plot of the OPLS-DA model of control group and model group. OPLS-DA score plot for the first two components showed the separation between the control group and model group. The fitness (R2Y) and prediction power (Q2Y) of this two-component model were 0.979 and 0.918, respectively ((A) ESI+; (C) ESI). Validation plot of the OPLS-DA model of control group and model group were obtained from 200 permutation tests. The intercepts of R2 were lower than the original point to the right, whereas those of Q2 were negative, indicating no signs of overfit ((B) ESI+; (D) ESI).

Figure 6
Figure 6

Loading S-plots generated by OPLS-DA analysis in positive mode (A) and negative mode (B). The x-axis is a measure of the relative abundance of ions, and the y-axis is a measure of the correlation of each ion to the model.

Figure 7
Figure 7

Summary of pathway analysis with MetPA. (A) glycerophospholipid metabolism; (B) nicotinate and nicotinamide metabolism; (C) alanine, aspartate and glutamate metabolism; (D) pyruvate metabolism.

Figure 8
Figure 8

Boxplot of the metabolites associated with the four pathways in Figure 7.

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References

    1. Wei C., Li Y., Yao H., Liu H., Zhang X., Guo R. A metabonomics study of epilepsy in patients using gas chromatography coupled with mass spectrometry. Mol. Biosyst. 2012;8:2197–2204. doi: 10.1039/c2mb25105a. - DOI - PubMed
    1. Carpay J.A., Ferrari M.D. The adverse effects of antiepileptic drugs differ in patients with migraine. Lancet Neurol. 2012;11:935. doi: 10.1016/S1474-4422(12)70247-8. - DOI - PubMed
    1. Wolf P. Acute drug administration in epilepsy: A review. CNS Neurosci. Ther. 2011;17:442–448. doi: 10.1111/j.1755-5949.2010.00167.x. - DOI - PMC - PubMed
    1. Tomson T., Battino D., Bonizzoni E., Craig J., Lindhout D., Sabers A., Perucca E., Vajda F. Dose-dependent risk of malformations with antiepileptic drugs: An analysis of data from the EURAP epilepsy and pregnancy registry. Lancet Neurol. 2011;10:609–617. doi: 10.1016/S1474-4422(11)70107-7. - DOI - PubMed
    1. Chen B., Choi H., Hirsch L.J., Katz A., Legge A., Buchsbaum R., Detyniecki K. Psychiatric and behavioral side effects of antiepileptic drugs in adults with epilepsy. Epilepsy Behav. 2017;76:24–31. doi: 10.1016/j.yebeh.2017.08.039. - DOI - PubMed

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