Metabolomic Analysis Reveals Metabolic Disturbances In The Prefrontal Cortex Of The Lipopolysaccharide-induced Mouse Model Of Depression

BackgroundMajor depressive disorder(MDD) is a debilitating illness with a high recurrence and prevalence. MDD generates large social and economical burden to the humans. Therefore it is very meaningful to strengthen the prevention and treatment of MDD. Currently, diagnosis of depression primarily depends on subjective judgments of clinical symptoms presented by patients. Besides, the underlying molecular mechanisms of depression remain largely unknown. There have been various etiopathological hypotheses regarding depression such as monoamine deficiency, neurogenesis, hypothalamic pituitary adrenal axis dysfunction, and imbalance of glutaminergic neurotransmitter system hypotheses. However, depression is a heterogeneous disorder with a highly variable course, and none of the established hypotheses can independently account for the complex pathogenesis of MDD. Increasing evidence supports that inflammatory cytokine disturbances may be associated with the pathophysiology of depression in humans.Metabolomics, which is a quantitative measurement of the dynamic multiparametric metabolic response of living systems to pathophysiological stimuli or genetic modification, has emerged. This is an efficient approach for probing significant biochemical alterations, exploring potential pathophysiological mechanisms, and evaluating the therapeutic effects of drugs. Nowadays, metabolomics has been generally used in the field of neuropsychiatric disorders.Recent studies have pointed towards the prefrontal cortex(PFC) playing a significant role in regulating emotion, memory, cognition, and learned responses. A large number of functional imaging and brain stimulation studies have implicated the PFC in the pathophysiology of neuropsychiatric disorders, including inflammation related disorders such as depression. Therefore, it is greatly needed to carry out metabolomics study of PFC for depression, which could facilitate to develop diagnostic tools and find the mechanism for MDD. ObjectiveWe employed a gas chromatography-mass spectrometry(GC-MS)-based metabonomic approach in the LPS-induced mouse model of depression to investigate any significant metabolic changes and metabolic pathways associated with depression in the PFC. We tried to realize differences metabolite changes, which may be associated with depression, in the PFC of lipopolysaccharide(LPS)-induced mouse model of depression, and analyze the differences in metabolic molecular pathological physiology function. Further, we tried to analyze the relationships between metabolic changes and depression, and explore possible pathophysiological mechanism of inflammatory cytokines disorder and depression. Methods1. The LPS-induced mouse model of depression has been developed as a rodent model of cytokine-evoked depression. Thirty healthy male CD1 mice were randomly divided into the LPS(n = 15) and CON(n = 15) group. The animals were trained for 2 weeks. Depressive-like behaviors were then assessed 24 h following the intraperitoneal(i.p.) injection of LPS.2. we employed a GC-MS-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 metabolites between LPS-induced depressed mice and controls, clustering them by their function, analyzing the data by their metabolic pathway. Results1. In the present study, we constructed a valid LPS-induced mouse model of depression that exhibited marked weight loss, significant decreases in food intake and sucrose preference, and significant increases in immobility time in both the tail suspension test(TST) and forced swimming test(FST).2. There was a significant difference in metabolomics profile between the LPS and CON group. 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. ConclusionIn conclusion, employing a GC-MS approach, our results suggest that PFC metabolic profiling has great potential in differentiating LPS mice from CON mice. Our study revealed a series of differential metabolites associated with disturbed neurotransmitter, lipid, energy, and oxidative stress metabolism. These metabolic disturbances in the PFC of a mouse model of depression may provide insight into the mechanisms underlying inflammation-related MDD.