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      Potential Candidates for Biomarkers in Bipolar Disorder: A Proteomic Approach through Systems Biology

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          Abstract

          Bipolar disorder (BD) is one of the most disabling diseases characterized by severe humor fluctuation. It is accompanied by cognitive and functional impairment in addiction to high suicide rates. BD is often underdiagnosed and treated incorrectly because many of the reported symptoms are not exclusive to the disorder. Once the diagnosis is exclusively clinical, it is not possible to state precisely. From that, proteomic approaches were used to identify, in a large scale, all proteins involved in cellular or tissue processes. This review aggregate data from blood proteomes, by using protein association network, of subjects with BD and healthy controls to suggest dysfunctional molecular pathways involved in disease. Original articles containing proteomic analysis were searched in PubMed. Seven studies were selected and data were extracted for posterior analysis. A protein-protein interaction network was created by STRING database. A final set of proteins in this network were employed as input in ClueGO and, the main biological process was visualized using R package pathview. The analysis revealed proteins associated with many biological processes, including growth and endocrine regulation, iron transportation, protease inhibition, protection against pathogens and cholesterol transport. Moreover, pathway analysis indicated the association of uncovered proteins with two main metabolic pathways: complement system and coagulation cascade. Thus, a better understanding on the pathophysiology of psychiatric disorders and the identification of potential biomarker candidates are essential to improve diagnostic, prognostic and design pharmacological strategies.

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          Most cited references121

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          Cytoscape: a software environment for integrated models of biomolecular interaction networks.

          Cytoscape is an open source software project for integrating biomolecular interaction networks with high-throughput expression data and other molecular states into a unified conceptual framework. Although applicable to any system of molecular components and interactions, Cytoscape is most powerful when used in conjunction with large databases of protein-protein, protein-DNA, and genetic interactions that are increasingly available for humans and model organisms. Cytoscape's software Core provides basic functionality to layout and query the network; to visually integrate the network with expression profiles, phenotypes, and other molecular states; and to link the network to databases of functional annotations. The Core is extensible through a straightforward plug-in architecture, allowing rapid development of additional computational analyses and features. Several case studies of Cytoscape plug-ins are surveyed, including a search for interaction pathways correlating with changes in gene expression, a study of protein complexes involved in cellular recovery to DNA damage, inference of a combined physical/functional interaction network for Halobacterium, and an interface to detailed stochastic/kinetic gene regulatory models.
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            STRING v11: protein–protein association networks with increased coverage, supporting functional discovery in genome-wide experimental datasets

            Abstract Proteins and their functional interactions form the backbone of the cellular machinery. Their connectivity network needs to be considered for the full understanding of biological phenomena, but the available information on protein–protein associations is incomplete and exhibits varying levels of annotation granularity and reliability. The STRING database aims to collect, score and integrate all publicly available sources of protein–protein interaction information, and to complement these with computational predictions. Its goal is to achieve a comprehensive and objective global network, including direct (physical) as well as indirect (functional) interactions. The latest version of STRING (11.0) more than doubles the number of organisms it covers, to 5090. The most important new feature is an option to upload entire, genome-wide datasets as input, allowing users to visualize subsets as interaction networks and to perform gene-set enrichment analysis on the entire input. For the enrichment analysis, STRING implements well-known classification systems such as Gene Ontology and KEGG, but also offers additional, new classification systems based on high-throughput text-mining as well as on a hierarchical clustering of the association network itself. The STRING resource is available online at https://string-db.org/.
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              ClueGO: a Cytoscape plug-in to decipher functionally grouped gene ontology and pathway annotation networks

              Summary: We have developed ClueGO, an easy to use Cytoscape plug-in that strongly improves biological interpretation of large lists of genes. ClueGO integrates Gene Ontology (GO) terms as well as KEGG/BioCarta pathways and creates a functionally organized GO/pathway term network. It can analyze one or compare two lists of genes and comprehensively visualizes functionally grouped terms. A one-click update option allows ClueGO to automatically download the most recent GO/KEGG release at any time. ClueGO provides an intuitive representation of the analysis results and can be optionally used in conjunction with the GOlorize plug-in. Availability: http://www.ici.upmc.fr/cluego/cluegoDownload.shtml Contact: jerome.galon@crc.jussieu.fr Supplementary information: Supplementary data are available at Bioinformatics online.
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                Author and article information

                Journal
                Clin Psychopharmacol Neurosci
                Clin Psychopharmacol Neurosci
                Clinical Psychopharmacology and Neuroscience
                Korean College of Neuropsychopharmacology
                1738-1088
                2093-4327
                31 May 2022
                31 May 2022
                31 May 2022
                : 20
                : 2
                : 211-227
                Affiliations
                [1 ]Laboratory of Molecular Psychiatry, Hospital Clinic of Porto Alegre, Porto Alegre, Brasil
                [2 ]Postgraduate Program in Biological Sciences: Pharmacology and Therapeutics - Institute of Basic Health Sciences, Federal University of Rio Grande do Sul, Porto Alegre, Brasil
                [3 ]Postgraduate Program in Psychiatry and Behavioral Sciences, Faculty of Medicine, Federal University of Rio Grande do Sul, Porto Alegre, Brasil
                [4 ]University of Caxias do Sul, Caxias do Sul, Brasil
                [5 ]Department of Psychiatry and Behavioural Neurosciences, McMaster University, Hamilton, ON, Canada
                Author notes
                Address for correspondence: Adriane Ribeiro Rosa Department of Pharmacology - Federal University of Rio Grande do Sul, Laboratory of Molecular Psychiatry - Hospital Clinic of Porto Alegre, Ramiro Barcelos 2350, Santa Cecília, Porto Alegre - RS, 90035-903, Brazil, E-mail: adrianerrosa@ 123456gmail.com , ORCID: https://orcid.org/0000-0001-8629-4625
                Author information
                https://orcid.org/0000-0003-3070-3535
                https://orcid.org/0000-0003-0414-6421
                https://orcid.org/0000-0002-1229-702X
                https://orcid.org/0000-0002-2794-0671
                https://orcid.org/0000-0003-0170-0597
                https://orcid.org/0000-0002-8465-0785
                https://orcid.org/0000-0001-8629-4625
                Article
                cpn-20-2-211
                10.9758/cpn.2022.20.2.211
                9048014
                35466093
                78be0d80-52dc-45bd-a780-9f6fd9081729
                Copyright© 2022, Korean College of Neuropsychopharmacology

                This is an open-access article distributed under the terms of the Creative Commons Attribution Non-Commercial License ( http://creativecommons.org/licenses/by-nc/4.0) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.

                History
                : 20 May 2021
                : 2 July 2021
                : 3 July 2021
                Categories
                Review

                blood,biomarkers,bipolar disorder,proteomics,systems biology

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