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A new bioinformatic insight into the associated proteins in psychiatric disorders

BACKGROUND: Psychiatric diseases severely affect the quality of patients’ lives and bring huge economic pressure to their families. Also, the great phenotypic variability among these patients makes it difficult to investigate the pathogenesis. Nowadays, bioinformatics is hopeful to be used as an eff...

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Autores principales: Zhao, Wenlong, Yang, Wenjing, Zheng, Shuanglin, Hu, Qiong, Qiu, Ping, Huang, Xinghua, Hong, Xiaoqian, Lan, Fenghua
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Springer International Publishing 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5108746/
https://www.ncbi.nlm.nih.gov/pubmed/27917343
http://dx.doi.org/10.1186/s40064-016-3655-6
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author Zhao, Wenlong
Yang, Wenjing
Zheng, Shuanglin
Hu, Qiong
Qiu, Ping
Huang, Xinghua
Hong, Xiaoqian
Lan, Fenghua
author_facet Zhao, Wenlong
Yang, Wenjing
Zheng, Shuanglin
Hu, Qiong
Qiu, Ping
Huang, Xinghua
Hong, Xiaoqian
Lan, Fenghua
author_sort Zhao, Wenlong
collection PubMed
description BACKGROUND: Psychiatric diseases severely affect the quality of patients’ lives and bring huge economic pressure to their families. Also, the great phenotypic variability among these patients makes it difficult to investigate the pathogenesis. Nowadays, bioinformatics is hopeful to be used as an effective tool for the diagnosis of psychiatric disorders, which can identify sensitive biomarkers and explore associated signaling pathways. METHODS: In this study, we performed an integrated bioinformatic analysis on 1945 mental-associated proteins including 91 secreted proteins and 593 membrane proteins, which were screened from the Universal Protein Resource (Uniport) database. Then the function and pathway enrichment analyses, ontological classification, and constructed PPI network were executed. RESULTS: Our present study revealed that the majority of mental proteins were closely related to metabolic processes and cellular processes. We also identified some significant molecular biomarkers in the progression of mental disorders, such as HRAS, ALS2, SLC6A1, SLC39A12, SIL1, IDUA, NEPH2 and XPO1. Furthermore, it was found that hub proteins, such as COMT, POMC, NPS and BDNF, might be the potential targets for mental disorders therapy. Finally, we demonstrated that psychiatric disorders may share the same signaling pathways with cancers, involving ESR1, BCL2 and MAPK3. CONCLUSION: Our data are expected to contribute to explaining the possible mechanisms of psychiatric diseases and providing a useful reference for the diagnosis and therapy of them.
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spelling pubmed-51087462016-12-02 A new bioinformatic insight into the associated proteins in psychiatric disorders Zhao, Wenlong Yang, Wenjing Zheng, Shuanglin Hu, Qiong Qiu, Ping Huang, Xinghua Hong, Xiaoqian Lan, Fenghua Springerplus Research BACKGROUND: Psychiatric diseases severely affect the quality of patients’ lives and bring huge economic pressure to their families. Also, the great phenotypic variability among these patients makes it difficult to investigate the pathogenesis. Nowadays, bioinformatics is hopeful to be used as an effective tool for the diagnosis of psychiatric disorders, which can identify sensitive biomarkers and explore associated signaling pathways. METHODS: In this study, we performed an integrated bioinformatic analysis on 1945 mental-associated proteins including 91 secreted proteins and 593 membrane proteins, which were screened from the Universal Protein Resource (Uniport) database. Then the function and pathway enrichment analyses, ontological classification, and constructed PPI network were executed. RESULTS: Our present study revealed that the majority of mental proteins were closely related to metabolic processes and cellular processes. We also identified some significant molecular biomarkers in the progression of mental disorders, such as HRAS, ALS2, SLC6A1, SLC39A12, SIL1, IDUA, NEPH2 and XPO1. Furthermore, it was found that hub proteins, such as COMT, POMC, NPS and BDNF, might be the potential targets for mental disorders therapy. Finally, we demonstrated that psychiatric disorders may share the same signaling pathways with cancers, involving ESR1, BCL2 and MAPK3. CONCLUSION: Our data are expected to contribute to explaining the possible mechanisms of psychiatric diseases and providing a useful reference for the diagnosis and therapy of them. Springer International Publishing 2016-11-14 /pmc/articles/PMC5108746/ /pubmed/27917343 http://dx.doi.org/10.1186/s40064-016-3655-6 Text en © The Author(s) 2016 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made.
spellingShingle Research
Zhao, Wenlong
Yang, Wenjing
Zheng, Shuanglin
Hu, Qiong
Qiu, Ping
Huang, Xinghua
Hong, Xiaoqian
Lan, Fenghua
A new bioinformatic insight into the associated proteins in psychiatric disorders
title A new bioinformatic insight into the associated proteins in psychiatric disorders
title_full A new bioinformatic insight into the associated proteins in psychiatric disorders
title_fullStr A new bioinformatic insight into the associated proteins in psychiatric disorders
title_full_unstemmed A new bioinformatic insight into the associated proteins in psychiatric disorders
title_short A new bioinformatic insight into the associated proteins in psychiatric disorders
title_sort new bioinformatic insight into the associated proteins in psychiatric disorders
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5108746/
https://www.ncbi.nlm.nih.gov/pubmed/27917343
http://dx.doi.org/10.1186/s40064-016-3655-6
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