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      Responder and nonresponder patients exhibit different peripheral transcriptional signatures during major depressive episode

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          Abstract

          To date, it remains impossible to guarantee that short-term treatment given to a patient suffering from a major depressive episode (MDE) will improve long-term efficacy. Objective biological measurements and biomarkers that could help in predicting the clinical evolution of MDE are still warranted. To better understand the reason nearly half of MDE patients respond poorly to current antidepressive treatments, we examined the gene expression profile of peripheral blood samples collected from 16 severe MDE patients and 13 matched controls. Using a naturalistic and longitudinal design, we ascertained mRNA and microRNA (miRNA) expression at baseline, 2 and 8 weeks later. On a genome-wide scale, we detected transcripts with roles in various biological processes as significantly dysregulated between MDE patients and controls, notably those involved in nucleotide binding and chromatin assembly. We also established putative interactions between dysregulated mRNAs and miRNAs that may contribute to MDE physiopathology. We selected a set of mRNA candidates for quantitative reverse transcriptase PCR (RT-qPCR) to validate that the transcriptional signatures observed in responders is different from nonresponders. Furthermore, we identified a combination of four mRNAs ( PPT1, TNF, IL1B and HIST1H1E) that could be predictive of treatment response. Altogether, these results highlight the importance of studies investigating the tight relationship between peripheral transcriptional changes and the dynamic clinical progression of MDE patients to provide biomarkers of MDE evolution and prognosis.

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          In silico prediction of protein-protein interactions in human macrophages

          Background: Protein-protein interaction (PPI) network analyses are highly valuable in deciphering and understanding the intricate organisation of cellular functions. Nevertheless, the majority of available protein-protein interaction networks are context-less, i.e. without any reference to the spatial, temporal or physiological conditions in which the interactions may occur. In this work, we are proposing a protocol to infer the most likely protein-protein interaction (PPI) network in human macrophages. Results: We integrated the PPI dataset from the Agile Protein Interaction DataAnalyzer (APID) with different meta-data to infer a contextualized macrophage-specific interactome using a combination of statistical methods. The obtained interactome is enriched in experimentally verified interactions and in proteins involved in macrophage-related biological processes (i.e. immune response activation, regulation of apoptosis). As a case study, we used the contextualized interactome to highlight the cellular processes induced upon Mycobacterium tuberculosis infection. Conclusion: Our work confirms that contextualizing interactomes improves the biological significance of bioinformatic analyses. More specifically, studying such inferred network rather than focusing at the gene expression level only, is informative on the processes involved in the host response. Indeed, important immune features such as apoptosis are solely highlighted when the spotlight is on the protein interaction level.
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            Major depressive disorder: new clinical, neurobiological, and treatment perspectives.

            In this Seminar we discuss developments from the past 5 years in the diagnosis, neurobiology, and treatment of major depressive disorder. For diagnosis, psychiatric and medical comorbidity have been emphasised as important factors in improving the appropriate assessment and management of depression. Advances in neurobiology have also increased, and we aim to indicate genetic, molecular, and neuroimaging studies that are relevant for assessment and treatment selection of this disorder. Further studies of depression-specific psychotherapies, the continued application of antidepressants, the development of new treatment compounds, and the status of new somatic treatments are also discussed. We address two treatment-related issues: suicide risk with selective serotonin reuptake inhibitors, and the safety of antidepressants in pregnancy. Although clear advances have been made, no fully satisfactory treatments for major depression are available. Copyright © 2012 Elsevier Ltd. All rights reserved.
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              Conceptualization and rationale for consensus definitions of terms in major depressive disorder. Remission, recovery, relapse, and recurrence.

              In 1988, the MacArthur Foundation Research Network on the Psychobiology of Depression convened a task force to examine the ways in which change points in the course of depressive illness had been described and the extent to which inconsistency in these descriptions might be impeding research on this disorder. We found considerable inconsistency across and even within research reports and concluded that research on depressive illness would be well served by greater consistency in the definition change points in the course of illness. We propose an internally consistent, empirically defined conceptual scheme for the terms remission, recovery, relapse, and recurrence. In addition, we propose tentative operational criteria for each term. Finally, we discuss ways to assess the usefulness of such operational criteria through reanalysis of existing data and the design and conduct of new experiments.
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                Author and article information

                Journal
                Transl Psychiatry
                Transl Psychiatry
                Translational Psychiatry
                Nature Publishing Group
                2158-3188
                November 2012
                13 November 2012
                1 November 2012
                : 2
                : 11
                : e185
                Affiliations
                [1 ]Aix Marseille Université, CNRS, CRN2M UMR 7286 , Marseille, France
                [2 ]APHM, Hôpital Sainte Marguerite, Pôle de Psychiatrie Universitaire Solaris , Marseille, France
                [3 ]FondaMental, Fondation de Recherche et de Soins en Santé Mentale , Paris, France
                [4 ]INSERM, TAGC UMR_S 1090 , Marseille, France
                [5 ]Aix Marseille Université, TAGC UMR_S 1090 , Marseille, France
                [6 ]INSERM, UNIS UMR_S 1072 , Marseille, France
                [7 ]Aix Marseille Université, UNIS UMR_S 1072 , Marseille, France
                [8 ]Aix Marseille Université, Faculté de Médecine Timone, Unité d'aide méthodologique , Marseille, France
                [9 ]Department of Public Health, APHM, Hôpital La Timone , Marseille, France
                [10 ]Aix Marseille Université, Research Unit EA 3279 , Marseille, France
                [11 ]APHM, Hôpital Nord, Laboratoire de Biochimie-Biologie Moléculaire , Marseille, France
                Author notes
                [* ]Aix Marseille Université, CNRS, CRN2M UMR 7286 , 51 Bd Pierre Dramard, 13344 Marseille Cedex 15, France. E-mail: el-cherif.ibrahim@ 123456univ-amu.fr
                Article
                tp2012112
                10.1038/tp.2012.112
                3565773
                23149449
                8c66fae8-144c-4913-9854-d622c3a9ee08
                Copyright © 2012 Macmillan Publishers Limited

                This work is licensed under the Creative Commons Attribution-NonCommercial-No Derivative Works 3.0 Unported License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-nd/3.0/

                History
                : 18 September 2012
                : 21 September 2012
                Categories
                Original Article

                Clinical Psychology & Psychiatry
                mood disorder,biomarker,transcriptome,mirna,antidepressant,pbmc
                Clinical Psychology & Psychiatry
                mood disorder, biomarker, transcriptome, mirna, antidepressant, pbmc

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