Abstract：
:Major depressive disorder (MDD) is a debilitating illness. However, the underlying molecular mechanisms of depression remain largely unknown. Increasing evidence supports that inflammatory cytokine disturbances may be associated with the pathophysiology of depression in humans. Systemic administration of lipopolysaccharide (LPS) has been used to study inflammation-associated neurobehavioral changes in rodents, but no metabonomic study has been conducted to assess differential metabolites in the prefrontal cortex (PFC) of a LPS-induced mouse model of depression. Here, we employed a gas chromatography-mass spectrometry-based metabonomic approach in the LPS-induced mouse model of depression to investigate any significant metabolic changes in the PFC. Multivariate statistical analysis, including principal component analysis (PCA), partial least squares-discriminate analysis (PLS-DA), and pair-wise orthogonal projections to latent structures discriminant analysis (OPLS-DA), was implemented to identify differential PFC metabolites between LPS-induced depressed mice and healthy controls. A total of 20 differential metabolites were identified. Compared with control mice, LPS-treated mice were characterized by six lower level metabolites and 14 higher level metabolites. These molecular changes were closely related to perturbations in neurotransmitter metabolism, energy metabolism, oxidative stress, and lipid metabolism, which might be evolved in the pathogenesis of MDD. These findings provide insight into the pathophysiological mechanisms underlying MDD and could be of valuable assistance in the clinical diagnosis of MDD.
journal_name
Behav Brain Resjournal_title
Behavioural brain researchauthors
Wu Y,Fu Y,Rao C,Li W,Liang Z,Zhou C,Shen P,Cheng P,Zeng L,Zhu D,Zhao L,Xie Pdoi
10.1016/j.bbr.2016.04.032subject
Has Abstractpub_date
2016-07-15 00:00:00pages
115-27eissn
0166-4328issn
1872-7549pii
S0166-4328(16)30234-0journal_volume
308pub_type
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