Abstract Alterations in energy metabolism are associated with depression. However, the role of glycolysis in the pathogenesis of depression and the underlying molecular mechanisms remain unexplored. Through an unbiased proteomic screen coupled with biochemical verifications, we show that the levels of glycolysis and lactate dehydrogenase A (LDHA), a glycolytic enzyme that catalyzes L-lactate production, are reduced in the dorsomedial prefrontal cortex (dmPFC) of stress-susceptible mice in chronic social defeat stress (CSDS) model. Conditional knockout of LDHA from the brain promotes depressive-like behaviors in both male and female mice, accompanied with reduced L-lactate levels and decreased neuronal excitability in the dmPFC. Moreover, these phenotypes could be duplicated by knockdown of LDHA in the dmPFC or specifically in astrocytes. In contrast, overexpression of LDHA reverses these phenotypic changes in CSDS-susceptible mice. Mechanistic studies demonstrate that L-lactate promotes neuronal excitability through monocarboxylic acid transporter 2 (MCT2) and by inhibiting large-conductance Ca 2+ -activated potassium (BK) channel. Together, these results reveal a role of LDHA in maintaining neuronal excitability to prevent depressive-like behaviors. 

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Astrocytic lactate dehydrogenase A regulates neuronal excitability and depressive-like behaviors through lactate homeostasis in mice

Major depressive disorder (MDD), also called depression, is a serious disease that impairs the quality of life of patients and has a high incidence, affecting approximately 3.8% of the world population. Its diagnosis is very subjective and is not supported by measurable biomarkers mainly due to the lack of biochemical markers. Recently, disturbance of lipid profiling has been recognized in MDD, in animal models of MDD or in depressed patients, which may contribute to unravel the etiology of the disease and find putative new biomarkers, for a diagnosis or for monitoring the disease and therapeutics outcomes. In this review, we provide an overview of current knowledge of lipidomics analysis, both in animal models of MDD (at the brain and plasma level) and in humans (in plasma and serum). Furthermore, studies of lipidomics analyses after antidepressant treatment in rodents (in brain, plasma, and serum), in primates (in the brain) and in humans (in plasma) were reviewed and give evidence that antidepressants seem to counteract the modification seen in lipids in MDD, giving some evidence that certain altered lipid profiles could be useful MDD biomarkers for future precision medicine.

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Adaptation of Lipid Profiling in Depression Disease and Treatment: A Critical Review

Early undernutrition has been found to be closely associated with subsequent neurodevelopment. However, studies examining crude growth in terms of body weight/tail length cannot clarify how diets might mediate associations between the gut microbiota and cognitive dysfunction. In the present study, Sprague-Dawley (SD) rats were fed a 7% protein diet and mung bean protein diet (MBPD) for 6 weeks to assess central nervous system functions. Bifidobacterium longum subsp, Alloprevotella, and Lactobacillus were significantly altered after supplementary MBPD. Additionally, tryptophan, tyrosine, and glycine significantly restored in the brain, and the choline system also improved. Moreover, mung bean supplementation also upregulated expression of the brain-derived neurotrophic factor, postsynaptic density 95 protein (PSD95), synaptosome-associated protein 25 (SNAP25), downregulated toll-like receptor 4 (TLR4), and nuclear factor kB (NF-kB). Metabolites in the serum also underwent changes. Together, these results showed that malnutrition perturbed neurodevelopment, while MBPD reversed this trend.

Mung Bean Protein Suppresses Undernutrition-Induced Growth Deficits and Cognitive Dysfunction in Rats via Gut Microbiota-TLR4/NF-kB Pathway.

In vivo magnetic resonance spectrometry imaging demonstrates comparable adaptation of brain energy metabolism to metabolic stress induced by 72 h of fasting in depressed patients and healthy volunteers.

Introduction Previous studies on transcriptional profiles suggested dysregulation of multiple RNA species in major depressive disorder (MDD). However, the interaction between different types of RNA was neglected. Therefore, integration of different RNA species in transcriptome analysis would be helpful for interpreting the functional readout of the transcriptome in MDD. Methods A whole transcriptome sequencing were performed on the peripheral blood of 15 patients with MDD and 15 matched healthy controls (HCs). The differential expression of miRNAs, lncRNAs, circRNAs, and mRNAs was examined between MDD and HCs using empirical analysis of digital gene expression data in R (edgeR). Weighted correlation network analysis (WGCNA) was used to identify RNA co-expression modules associated with MDD. A ceRNA network was constructed for interpretation of interactions between different RNA species. Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analyses were conducted to explore potential biological mechanisms associated with MDD. Results Multiple RNAs and co-expression modules were identified to be significantly dysregulated in MDD compared to HCs. Based on the differential RNAs, a ceRNA network that were dysregulated in MDD were constructed. The pathway networks that related to oxidative phosphorylation and the chemokine signaling were found to be associated with MDD. Conclusion Our results suggested that the processes of energy metabolism and inflammation may be involved in the pathophysiology of MDD.

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A Whole Transcriptome Analysis in Peripheral Blood Suggests That Energy Metabolism and Inflammation Are Involved in Major Depressive Disorder

Energy metabolism in major depressive disorder: Recent advances from omics technologies and imaging.

Background Given the clinical low efficient treatment based on mono-brain-target design in Alzheimer's disease (AD) and an increasing emphasis on microbiome-gut-brain axis which was considered as a crucial pathway to affect the progress of AD along with metabolic changes, integrative metabolomic signatures and microbiotic community profilings were applied on the early age (2-month) and mature age (6-month) of presenilin1/2 conditional double knockout (PS cDKO) mice which exhibit a series of AD-like phenotypes, comparing with gender and age-matched C57BL/6 wild-type (WT) mice to clarify the relationship between microbiota and metabolomic changes during the disease progression of AD. Materials and methods Urinary and fecal samples from PS cDKO mice and gender-matched C57BL/6 wild-type (WT) mice both at age of 2 and 6 months were collected. Urinary metabolomic signatures were measured by the gas chromatography-time-of-flight mass spectrometer, as well as 16S rRNA sequence analysis was performed to analyse the microbiota composition at both ages. Furthermore, combining microbiotic functional prediction and Spearman's correlation coefficient analysis to explore the relationship between differential urinary metabolites and gut microbiota. Results In addition to memory impairment, PS cDKO mice displayed metabolic and microbiotic changes at both of early and mature ages. By longitudinal study, xylitol and glycine were reduced at both ages. The disturbed metabolic pathways were involved in glycine, serine and threonine metabolism, glyoxylate and dicarboxylate metabolism, pentose and glucuronate interconversions, starch and sucrose metabolism, and citrate cycle, which were consistent with functional metabolic pathway predicted by the gut microbiome, including energy metabolism, lipid metabolism, glycan biosynthesis and metabolism. Besides reduced richness and evenness in gut microbiome, PS cDKO mice displayed increases in Lactobacillus, while decreases in norank_f_Muribaculaceae, Lachnospiraceae_NK4A136_group, Mucispirillum, and Odoribacter. Those altered microbiota were exceedingly associated with the levels of differential metabolites. Conclusions The urinary metabolomics of AD may be partially mediated by the gut microbiota. The integrated analysis between gut microbes and host metabolism may provide a reference for the pathogenesis of AD.

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Chenyi Xia

Papers

Energy metabolism in major depressive disorder: Recent advances from omics technologies and imaging.

Urinary metabolomic changes and microbiotic alterations in presenilin1/2 conditional double knockout mice.

Emerging application of metabolomics on Chinese herbal medicine for depressive disorder.