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Analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach

The prevalence of tobacco use in people with schizophrenia is much higher than in general population, which indicates a close relationship between nicotine addiction and schizophrenia. However, the molecular mechanism underlying the high comorbidity of tobacco smoking and schizophrenia remains large...

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Autores principales: Hu, Ying, Fang, Zhonghai, Yang, Yichen, Rohlsen-Neal, Dekai, Cheng, Feng, Wang, Ju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Nature Publishing Group UK 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5811491/
https://www.ncbi.nlm.nih.gov/pubmed/29440730
http://dx.doi.org/10.1038/s41598-018-21297-x
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author Hu, Ying
Fang, Zhonghai
Yang, Yichen
Rohlsen-Neal, Dekai
Cheng, Feng
Wang, Ju
author_facet Hu, Ying
Fang, Zhonghai
Yang, Yichen
Rohlsen-Neal, Dekai
Cheng, Feng
Wang, Ju
author_sort Hu, Ying
collection PubMed
description The prevalence of tobacco use in people with schizophrenia is much higher than in general population, which indicates a close relationship between nicotine addiction and schizophrenia. However, the molecular mechanism underlying the high comorbidity of tobacco smoking and schizophrenia remains largely unclear. In this study, we conducted a pathway and network analysis on the genes potentially associated with nicotine addiction or schizophrenia to reveal the functional feature of these genes and their interactions. Of the 276 genes associated with nicotine addiction and 331 genes associated with schizophrenia, 52 genes were shared. From these genes, 12 significantly enriched pathways associated with both diseases were identified. These pathways included those related to synapse function and signaling transduction, and drug addiction. Further, we constructed a nicotine addiction-specific and schizophrenia-specific sub-network, identifying 11 novel candidate genes potentially associated with the two diseases. Finally, we built a schematic molecular network for nicotine addiction and schizophrenia based on the results of pathway and network analysis, providing a systematic view to understand the relationship between these two disorders. Our results illustrated that the biological processes underlying the comorbidity of nicotine addiction and schizophrenia was complex, and was likely induced by the dysfunction of multiple molecules and pathways.
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spelling pubmed-58114912018-02-16 Analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach Hu, Ying Fang, Zhonghai Yang, Yichen Rohlsen-Neal, Dekai Cheng, Feng Wang, Ju Sci Rep Article The prevalence of tobacco use in people with schizophrenia is much higher than in general population, which indicates a close relationship between nicotine addiction and schizophrenia. However, the molecular mechanism underlying the high comorbidity of tobacco smoking and schizophrenia remains largely unclear. In this study, we conducted a pathway and network analysis on the genes potentially associated with nicotine addiction or schizophrenia to reveal the functional feature of these genes and their interactions. Of the 276 genes associated with nicotine addiction and 331 genes associated with schizophrenia, 52 genes were shared. From these genes, 12 significantly enriched pathways associated with both diseases were identified. These pathways included those related to synapse function and signaling transduction, and drug addiction. Further, we constructed a nicotine addiction-specific and schizophrenia-specific sub-network, identifying 11 novel candidate genes potentially associated with the two diseases. Finally, we built a schematic molecular network for nicotine addiction and schizophrenia based on the results of pathway and network analysis, providing a systematic view to understand the relationship between these two disorders. Our results illustrated that the biological processes underlying the comorbidity of nicotine addiction and schizophrenia was complex, and was likely induced by the dysfunction of multiple molecules and pathways. Nature Publishing Group UK 2018-02-13 /pmc/articles/PMC5811491/ /pubmed/29440730 http://dx.doi.org/10.1038/s41598-018-21297-x Text en © The Author(s) 2018 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 license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license 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 license, visit http://creativecommons.org/licenses/by/4.0/.
spellingShingle Article
Hu, Ying
Fang, Zhonghai
Yang, Yichen
Rohlsen-Neal, Dekai
Cheng, Feng
Wang, Ju
Analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach
title Analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach
title_full Analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach
title_fullStr Analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach
title_full_unstemmed Analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach
title_short Analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach
title_sort analyzing the genes related to nicotine addiction or schizophrenia via a pathway and network based approach
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5811491/
https://www.ncbi.nlm.nih.gov/pubmed/29440730
http://dx.doi.org/10.1038/s41598-018-21297-x
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