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Analyzing the genes and pathways related to major depressive disorder via a systems biology approach

INTRODUCTION: Major depressive disorder (MDD) is a mental disorder caused by the combination of genetic, environmental, and psychological factors. Over the years, a number of genes potentially associated with MDD have been identified. However, in many cases, the role of these genes and their relatio...

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Autores principales: Fan, Ting, Hu, Ying, Xin, Juncai, Zhao, Mengwen, Wang, Ju
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010578/
https://www.ncbi.nlm.nih.gov/pubmed/31875662
http://dx.doi.org/10.1002/brb3.1502
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author Fan, Ting
Hu, Ying
Xin, Juncai
Zhao, Mengwen
Wang, Ju
author_facet Fan, Ting
Hu, Ying
Xin, Juncai
Zhao, Mengwen
Wang, Ju
author_sort Fan, Ting
collection PubMed
description INTRODUCTION: Major depressive disorder (MDD) is a mental disorder caused by the combination of genetic, environmental, and psychological factors. Over the years, a number of genes potentially associated with MDD have been identified. However, in many cases, the role of these genes and their relationship in the etiology and development of MDD remains unclear. Under such situation, a systems biology approach focusing on the function correlation and interaction of the candidate genes in the context of MDD will provide useful information on exploring the molecular mechanisms underlying the disease. METHODS: We collected genes potentially related to MDD by screening the human genetic studies deposited in PubMed (https://www.ncbi.nlm.nih.gov/pubmed). The main biological themes within the genes were explored by function and pathway enrichment analysis. Then, the interaction of genes was analyzed in the context of protein–protein interaction network and a MDD‐specific network was built by Steiner minimal tree algorithm. RESULTS: We collected 255 candidate genes reported to be associated with MDD from available publications. Functional analysis revealed that biological processes and biochemical pathways related to neuronal development, endocrine, cell growth and/or survivals, and immunology were enriched in these genes. The pathways could be largely grouped into three modules involved in biological procedures related to nervous system, the immune system, and the endocrine system, respectively. From the MDD‐specific network, 35 novel genes potentially associated with the disease were identified. CONCLUSION: By means of network‐ and pathway‐based methods, we explored the molecular mechanism underlying the pathogenesis of MDD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular features of MDD.
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spelling pubmed-70105782020-02-13 Analyzing the genes and pathways related to major depressive disorder via a systems biology approach Fan, Ting Hu, Ying Xin, Juncai Zhao, Mengwen Wang, Ju Brain Behav Original Research INTRODUCTION: Major depressive disorder (MDD) is a mental disorder caused by the combination of genetic, environmental, and psychological factors. Over the years, a number of genes potentially associated with MDD have been identified. However, in many cases, the role of these genes and their relationship in the etiology and development of MDD remains unclear. Under such situation, a systems biology approach focusing on the function correlation and interaction of the candidate genes in the context of MDD will provide useful information on exploring the molecular mechanisms underlying the disease. METHODS: We collected genes potentially related to MDD by screening the human genetic studies deposited in PubMed (https://www.ncbi.nlm.nih.gov/pubmed). The main biological themes within the genes were explored by function and pathway enrichment analysis. Then, the interaction of genes was analyzed in the context of protein–protein interaction network and a MDD‐specific network was built by Steiner minimal tree algorithm. RESULTS: We collected 255 candidate genes reported to be associated with MDD from available publications. Functional analysis revealed that biological processes and biochemical pathways related to neuronal development, endocrine, cell growth and/or survivals, and immunology were enriched in these genes. The pathways could be largely grouped into three modules involved in biological procedures related to nervous system, the immune system, and the endocrine system, respectively. From the MDD‐specific network, 35 novel genes potentially associated with the disease were identified. CONCLUSION: By means of network‐ and pathway‐based methods, we explored the molecular mechanism underlying the pathogenesis of MDD at a systems biology level. Results from our work could provide valuable clues for understanding the molecular features of MDD. John Wiley and Sons Inc. 2019-12-25 /pmc/articles/PMC7010578/ /pubmed/31875662 http://dx.doi.org/10.1002/brb3.1502 Text en © 2019 The Authors. Brain and Behavior published by Wiley Periodicals, Inc. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Research
Fan, Ting
Hu, Ying
Xin, Juncai
Zhao, Mengwen
Wang, Ju
Analyzing the genes and pathways related to major depressive disorder via a systems biology approach
title Analyzing the genes and pathways related to major depressive disorder via a systems biology approach
title_full Analyzing the genes and pathways related to major depressive disorder via a systems biology approach
title_fullStr Analyzing the genes and pathways related to major depressive disorder via a systems biology approach
title_full_unstemmed Analyzing the genes and pathways related to major depressive disorder via a systems biology approach
title_short Analyzing the genes and pathways related to major depressive disorder via a systems biology approach
title_sort analyzing the genes and pathways related to major depressive disorder via a systems biology approach
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7010578/
https://www.ncbi.nlm.nih.gov/pubmed/31875662
http://dx.doi.org/10.1002/brb3.1502
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