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KMID : 1009020220200020211
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Clinical Psychopharmacology and Neuroscience
2022 Volume.20 No. 2 p.211 ~ p.227
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Potential Candidates for Biomarkers in Bipolar Disorder: A Proteomic Approach through Systems Biology
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Ziani Paola Rampelotto
Feiten Jacson Gabriel
Goularte Jeferson Ferraz
Colombo Rafael
Antqueviezc Barbara
Gea Luiza Paul
Rosa Adriane Ribeiro
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Abstract
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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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KEYWORD
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Blood, Biomarkers, Bipolar disorder, Proteomics, Systems biology
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