Prioritization and evaluation of depression candidate genes by combining multidimensional data resources.

<h4>Background</h4>Large scale and individual genetic studies have suggested numerous susceptible genes for depression in the past decade without conclusive results. There is a strong need to review and integrate multi-dimensional data for follow up validation. The present study aimed to...

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Autores principales:	Chung-Feng Kao, Yu-Sheng Fang, Zhongming Zhao, Po-Hsiu Kuo
Formato:	article
Lenguaje:	EN
Publicado:	Public Library of Science (PLoS) 2011
Materias:	Medicine R Science Q
Acceso en línea:	https://doaj.org/article/368e8e1395e948cba45eedb1c7b7f642
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spelling	oai:doaj.org-article:368e8e1395e948cba45eedb1c7b7f6422021-11-18T06:56:10ZPrioritization and evaluation of depression candidate genes by combining multidimensional data resources.1932-620310.1371/journal.pone.0018696https://doaj.org/article/368e8e1395e948cba45eedb1c7b7f6422011-04-01T00:00:00Zhttps://www.ncbi.nlm.nih.gov/pmc/articles/pmid/21494644/?tool=EBIhttps://doaj.org/toc/1932-6203<h4>Background</h4>Large scale and individual genetic studies have suggested numerous susceptible genes for depression in the past decade without conclusive results. There is a strong need to review and integrate multi-dimensional data for follow up validation. The present study aimed to apply prioritization procedures to build-up an evidence-based candidate genes dataset for depression.<h4>Methods</h4>Depression candidate genes were collected in human and animal studies across various data resources. Each gene was scored according to its magnitude of evidence related to depression and was multiplied by a source-specific weight to form a combined score measure. All genes were evaluated through a prioritization system to obtain an optimal weight matrix to rank their relative importance with depression using the combined scores. The resulting candidate gene list for depression (DEPgenes) was further evaluated by a genome-wide association (GWA) dataset and microarray gene expression in human tissues.<h4>Results</h4>A total of 5,055 candidate genes (4,850 genes from human and 387 genes from animal studies with 182 being overlapped) were included from seven data sources. Through the prioritization procedures, we identified 169 DEPgenes, which exhibited high chance to be associated with depression in GWA dataset (Wilcoxon rank-sum test, p = 0.00005). Additionally, the DEPgenes had a higher percentage to express in human brain or nerve related tissues than non-DEPgenes, supporting the neurotransmitter and neuroplasticity theories in depression.<h4>Conclusions</h4>With comprehensive data collection and curation and an application of integrative approach, we successfully generated DEPgenes through an effective gene prioritization system. The prioritized DEPgenes are promising for future biological experiments or replication efforts to discover the underlying molecular mechanisms for depression.Chung-Feng KaoYu-Sheng FangZhongming ZhaoPo-Hsiu KuoPublic Library of Science (PLoS)articleMedicineRScienceQENPLoS ONE, Vol 6, Iss 4, p e18696 (2011)
institution	DOAJ
collection	DOAJ
language	EN
topic	Medicine R Science Q
spellingShingle	Medicine R Science Q Chung-Feng Kao Yu-Sheng Fang Zhongming Zhao Po-Hsiu Kuo Prioritization and evaluation of depression candidate genes by combining multidimensional data resources.
description	<h4>Background</h4>Large scale and individual genetic studies have suggested numerous susceptible genes for depression in the past decade without conclusive results. There is a strong need to review and integrate multi-dimensional data for follow up validation. The present study aimed to apply prioritization procedures to build-up an evidence-based candidate genes dataset for depression.<h4>Methods</h4>Depression candidate genes were collected in human and animal studies across various data resources. Each gene was scored according to its magnitude of evidence related to depression and was multiplied by a source-specific weight to form a combined score measure. All genes were evaluated through a prioritization system to obtain an optimal weight matrix to rank their relative importance with depression using the combined scores. The resulting candidate gene list for depression (DEPgenes) was further evaluated by a genome-wide association (GWA) dataset and microarray gene expression in human tissues.<h4>Results</h4>A total of 5,055 candidate genes (4,850 genes from human and 387 genes from animal studies with 182 being overlapped) were included from seven data sources. Through the prioritization procedures, we identified 169 DEPgenes, which exhibited high chance to be associated with depression in GWA dataset (Wilcoxon rank-sum test, p = 0.00005). Additionally, the DEPgenes had a higher percentage to express in human brain or nerve related tissues than non-DEPgenes, supporting the neurotransmitter and neuroplasticity theories in depression.<h4>Conclusions</h4>With comprehensive data collection and curation and an application of integrative approach, we successfully generated DEPgenes through an effective gene prioritization system. The prioritized DEPgenes are promising for future biological experiments or replication efforts to discover the underlying molecular mechanisms for depression.
format	article
author	Chung-Feng Kao Yu-Sheng Fang Zhongming Zhao Po-Hsiu Kuo
author_facet	Chung-Feng Kao Yu-Sheng Fang Zhongming Zhao Po-Hsiu Kuo
author_sort	Chung-Feng Kao
title	Prioritization and evaluation of depression candidate genes by combining multidimensional data resources.
title_short	Prioritization and evaluation of depression candidate genes by combining multidimensional data resources.
title_full	Prioritization and evaluation of depression candidate genes by combining multidimensional data resources.
title_fullStr	Prioritization and evaluation of depression candidate genes by combining multidimensional data resources.
title_full_unstemmed	Prioritization and evaluation of depression candidate genes by combining multidimensional data resources.
title_sort	prioritization and evaluation of depression candidate genes by combining multidimensional data resources.
publisher	Public Library of Science (PLoS)
publishDate	2011
url	https://doaj.org/article/368e8e1395e948cba45eedb1c7b7f642
work_keys_str_mv	AT chungfengkao prioritizationandevaluationofdepressioncandidategenesbycombiningmultidimensionaldataresources AT yushengfang prioritizationandevaluationofdepressioncandidategenesbycombiningmultidimensionaldataresources AT zhongmingzhao prioritizationandevaluationofdepressioncandidategenesbycombiningmultidimensionaldataresources AT pohsiukuo prioritizationandevaluationofdepressioncandidategenesbycombiningmultidimensionaldataresources
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Prioritization and evaluation of depression candidate genes by combining multidimensional data resources.

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