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      Post-inflammatory behavioural despair in male mice is associated with reduced cortical glutamate-glutamine ratios, and circulating lipid and energy metabolites

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          Abstract

          Post-inflammatory behaviours in rodents are widely used to model human depression and to test the efficacy of novel anti-depressants. Mice injected with lipopolysaccharide (LPS) display a depressive-like phenotype twenty-four hours after endotoxin administration. Despite the widespread use of this model, the mechanisms that underlie the persistent behavioural changes after the transient peripheral inflammatory response remain elusive. The study of the metabolome, the collection of all the small molecule metabolites in a sample, combined with multivariate statistical techniques provides a way of studying biochemical pathways influenced by an LPS challenge. Adult male CD-1 mice received an intraperitoneal injection of either LPS (0.83 mg/kg) or saline, and were assessed for depressive-like behaviour 24 h later. In a separate mouse cohort, pro-inflammatory cytokine gene expression and 1H nuclear magnetic resonance (NMR) metabolomics measurements were made in brain tissue and blood. Statistical analyses included Independent Sample t-tests for gene expression data, and supervised multi-variate analysis using orthogonal partial least squares discriminant analysis for metabolomics. Both plasma and brain metabolites in male mice were altered following a single peripheral LPS challenge that led to depressive-like behaviour in the forced swim test. The plasma metabolites altered by LPS are involved in energy metabolism, including lipoproteins, glucose, creatine, and isoleucine. In the brain, glutamate, serine, and N-acetylaspartate (NAA) were reduced after LPS, whereas glutamine was increased. Serine-modulated glutamatergic signalling and changes in bioenergetics may mediate the behavioural phenotype induced by LPS. In light of other data supporting a central imbalance of glutamate-glutamine cycling in depression, our results suggest that aberrant central glutaminergic signalling may underpin the depressive-like behaviours that result from both inflammation and non-immune pathophysiology. Normalising glutaminergic signalling, rather than seeking to increase serotonergic signalling, might prove to be a more coherent approach to the development of new treatments for mood disorder.

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          Analysis of the Human Adult Urinary Metabolome Variations with Age, Body Mass Index, and Gender by Implementing a Comprehensive Workflow for Univariate and OPLS Statistical Analyses.

          Urine metabolomics is widely used for biomarker research in the fields of medicine and toxicology. As a consequence, characterization of the variations of the urine metabolome under basal conditions becomes critical in order to avoid confounding effects in cohort studies. Such physiological information is however very scarce in the literature and in metabolomics databases so far. Here we studied the influence of age, body mass index (BMI), and gender on metabolite concentrations in a large cohort of 183 adults by using liquid chromatography coupled with high-resolution mass spectrometry (LC-HRMS). We implemented a comprehensive statistical workflow for univariate hypothesis testing and modeling by orthogonal partial least-squares (OPLS), which we made available to the metabolomics community within the online Workflow4Metabolomics.org resource. We found 108 urine metabolites displaying concentration variations with either age, BMI, or gender, by integrating the results from univariate p-values and multivariate variable importance in projection (VIP). Several metabolite clusters were further evidenced by correlation analysis, and they allowed stratification of the cohort. In conclusion, our study highlights the impact of gender and age on the urinary metabolome, and thus it indicates that these factors should be taken into account for the design of metabolomics studies.
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            HMDB 3.0—The Human Metabolome Database in 2013

            The Human Metabolome Database (HMDB) (www.hmdb.ca) is a resource dedicated to providing scientists with the most current and comprehensive coverage of the human metabolome. Since its first release in 2007, the HMDB has been used to facilitate research for nearly 1000 published studies in metabolomics, clinical biochemistry and systems biology. The most recent release of HMDB (version 3.0) has been significantly expanded and enhanced over the 2009 release (version 2.0). In particular, the number of annotated metabolite entries has grown from 6500 to more than 40 000 (a 600% increase). This enormous expansion is a result of the inclusion of both ‘detected’ metabolites (those with measured concentrations or experimental confirmation of their existence) and ‘expected’ metabolites (those for which biochemical pathways are known or human intake/exposure is frequent but the compound has yet to be detected in the body). The latest release also has greatly increased the number of metabolites with biofluid or tissue concentration data, the number of compounds with reference spectra and the number of data fields per entry. In addition to this expansion in data quantity, new database visualization tools and new data content have been added or enhanced. These include better spectral viewing tools, more powerful chemical substructure searches, an improved chemical taxonomy and better, more interactive pathway maps. This article describes these enhancements to the HMDB, which was previously featured in the 2009 NAR Database Issue. (Note to referees, HMDB 3.0 will go live on 18 September 2012.).
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              Prevalence of low-grade inflammation in depression: a systematic review and meta-analysis of CRP levels

              Background Peripheral low-grade inflammation in depression is increasingly seen as a therapeutic target. We aimed to establish the prevalence of low-grade inflammation in depression, using different C-reactive protein (CRP) levels, through a systematic literature review and meta-analysis. Methods We searched the PubMed database from its inception to July 2018, and selected studies that assessed depression using a validated tool/scale, and allowed the calculation of the proportion of patients with low-grade inflammation (CRP >3 mg/L) or elevated CRP (>1 mg/L). Results After quality assessment, 37 studies comprising 13 541 depressed patients and 155 728 controls were included. Based on the meta-analysis of 30 studies, the prevalence of low-grade inflammation (CRP >3 mg/L) in depression was 27% (95% CI 21–34%); this prevalence was not associated with sample source (inpatient, outpatient or population-based), antidepressant treatment, participant age, BMI or ethnicity. Based on the meta-analysis of 17 studies of depression and matched healthy controls, the odds ratio for low-grade inflammation in depression was 1.46 (95% CI 1.22–1.75). The prevalence of elevated CRP (>1 mg/L) in depression was 58% (95% CI 47–69%), and the meta-analytic odds ratio for elevated CRP in depression compared with controls was 1.47 (95% CI 1.18–1.82). Conclusions About a quarter of patients with depression show evidence of low-grade inflammation, and over half of patients show mildly elevated CRP levels. There are significant differences in the prevalence of low-grade inflammation between patients and matched healthy controls. These findings suggest that inflammation could be relevant to a large number of patients with depression.
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                Author and article information

                Contributors
                phil.burnet@psych.ox.ac.uk
                Journal
                Sci Rep
                Sci Rep
                Scientific Reports
                Nature Publishing Group UK (London )
                2045-2322
                8 October 2020
                8 October 2020
                2020
                : 10
                : 16857
                Affiliations
                [1 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Department of Psychiatry, Warneford Hospital, , University of Oxford, ; Warneford Lane, Oxford, OX3 7JX UK
                [2 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Department of Pharmacology, , University of Oxford, ; Oxford, OX1 3QT UK
                [3 ]GRID grid.4991.5, ISNI 0000 0004 1936 8948, Department of Chemistry, , University of Oxford, ; Oxford, OX1 3TA UK
                [4 ]GRID grid.240206.2, ISNI 0000 0000 8795 072X, Present Address: Psychosis Neurobiology Lab, , McLean Hospital, ; Belmont, MA 02478 USA
                Article
                74008
                10.1038/s41598-020-74008-w
                7545201
                33033375
                a7696a22-6a22-472e-8cbf-5e41272a974d
                © The Author(s) 2020

                Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/.

                History
                : 3 April 2020
                : 10 September 2020
                Categories
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                © The Author(s) 2020

                Uncategorized
                biomarkers,biological techniques,biological models,metabolomics,neuroscience,emotion,neuroimmunology

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