Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathways
Autor(a) principal: | |
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Data de Publicação: | 2018 |
Outros Autores: | , |
Tipo de documento: | Artigo |
Idioma: | eng |
Título da fonte: | Brazilian Journal of Medical and Biological Research |
Texto Completo: | http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2018000100607 |
Resumo: | Given that the pathogenesis of ankylosing spondylitis (AS) remains unclear, the aim of this study was to detect the potentially functional pathway cross-talk in AS to further reveal the pathogenesis of this disease. Using microarray profile of AS and biological pathways as study objects, Monte Carlo cross-validation method was used to identify the significant pathway cross-talks. In the process of Monte Carlo cross-validation, all steps were iterated 50 times. For each run, detection of differentially expressed genes (DEGs) between two groups was conducted. The extraction of the potential disrupted pathways enriched by DEGs was then implemented. Subsequently, we established a discriminating score (DS) for each pathway pair according to the distribution of gene expression levels. After that, we utilized random forest (RF) classification model to screen out the top 10 paired pathways with the highest area under the curve (AUCs), which was computed using 10-fold cross-validation approach. After 50 bootstrap, the best pairs of pathways were identified. According to their AUC values, the pair of pathways, antigen presentation pathway and fMLP signaling in neutrophils, achieved the best AUC value of 1.000, which indicated that this pathway cross-talk could distinguish AS patients from normal subjects. Moreover, the paired pathways of SAPK/JNK signaling and mitochondrial dysfunction were involved in 5 bootstraps. Two paired pathways (antigen presentation pathway and fMLP signaling in neutrophil, as well as SAPK/JNK signaling and mitochondrial dysfunction) can accurately distinguish AS and control samples. These paired pathways may be helpful to identify patients with AS for early intervention. |
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Brazilian Journal of Medical and Biological Research |
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Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathwaysAnkylosing spondylitisMonte Carlo cross-validationDifferentially expressed genesRandom forest classificationPathway cross-talkGiven that the pathogenesis of ankylosing spondylitis (AS) remains unclear, the aim of this study was to detect the potentially functional pathway cross-talk in AS to further reveal the pathogenesis of this disease. Using microarray profile of AS and biological pathways as study objects, Monte Carlo cross-validation method was used to identify the significant pathway cross-talks. In the process of Monte Carlo cross-validation, all steps were iterated 50 times. For each run, detection of differentially expressed genes (DEGs) between two groups was conducted. The extraction of the potential disrupted pathways enriched by DEGs was then implemented. Subsequently, we established a discriminating score (DS) for each pathway pair according to the distribution of gene expression levels. After that, we utilized random forest (RF) classification model to screen out the top 10 paired pathways with the highest area under the curve (AUCs), which was computed using 10-fold cross-validation approach. After 50 bootstrap, the best pairs of pathways were identified. According to their AUC values, the pair of pathways, antigen presentation pathway and fMLP signaling in neutrophils, achieved the best AUC value of 1.000, which indicated that this pathway cross-talk could distinguish AS patients from normal subjects. Moreover, the paired pathways of SAPK/JNK signaling and mitochondrial dysfunction were involved in 5 bootstraps. Two paired pathways (antigen presentation pathway and fMLP signaling in neutrophil, as well as SAPK/JNK signaling and mitochondrial dysfunction) can accurately distinguish AS and control samples. These paired pathways may be helpful to identify patients with AS for early intervention.Associação Brasileira de Divulgação Científica2018-01-01info:eu-repo/semantics/articleinfo:eu-repo/semantics/publishedVersiontext/htmlhttp://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2018000100607Brazilian Journal of Medical and Biological Research v.51 n.1 2018reponame:Brazilian Journal of Medical and Biological Researchinstname:Associação Brasileira de Divulgação Científica (ABDC)instacron:ABDC10.1590/1414-431x20176698info:eu-repo/semantics/openAccessGu,XiangLiu,Cong-JianWei,Jian-Jieeng2019-03-19T00:00:00Zoai:scielo:S0100-879X2018000100607Revistahttps://www.bjournal.org/https://old.scielo.br/oai/scielo-oai.phpbjournal@terra.com.br||bjournal@terra.com.br1414-431X0100-879Xopendoar:2019-03-19T00:00Brazilian Journal of Medical and Biological Research - Associação Brasileira de Divulgação Científica (ABDC)false |
dc.title.none.fl_str_mv |
Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathways |
title |
Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathways |
spellingShingle |
Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathways Gu,Xiang Ankylosing spondylitis Monte Carlo cross-validation Differentially expressed genes Random forest classification Pathway cross-talk |
title_short |
Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathways |
title_full |
Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathways |
title_fullStr |
Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathways |
title_full_unstemmed |
Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathways |
title_sort |
Predicting pathway cross-talks in ankylosing spondylitis through investigating the interactions among pathways |
author |
Gu,Xiang |
author_facet |
Gu,Xiang Liu,Cong-Jian Wei,Jian-Jie |
author_role |
author |
author2 |
Liu,Cong-Jian Wei,Jian-Jie |
author2_role |
author author |
dc.contributor.author.fl_str_mv |
Gu,Xiang Liu,Cong-Jian Wei,Jian-Jie |
dc.subject.por.fl_str_mv |
Ankylosing spondylitis Monte Carlo cross-validation Differentially expressed genes Random forest classification Pathway cross-talk |
topic |
Ankylosing spondylitis Monte Carlo cross-validation Differentially expressed genes Random forest classification Pathway cross-talk |
description |
Given that the pathogenesis of ankylosing spondylitis (AS) remains unclear, the aim of this study was to detect the potentially functional pathway cross-talk in AS to further reveal the pathogenesis of this disease. Using microarray profile of AS and biological pathways as study objects, Monte Carlo cross-validation method was used to identify the significant pathway cross-talks. In the process of Monte Carlo cross-validation, all steps were iterated 50 times. For each run, detection of differentially expressed genes (DEGs) between two groups was conducted. The extraction of the potential disrupted pathways enriched by DEGs was then implemented. Subsequently, we established a discriminating score (DS) for each pathway pair according to the distribution of gene expression levels. After that, we utilized random forest (RF) classification model to screen out the top 10 paired pathways with the highest area under the curve (AUCs), which was computed using 10-fold cross-validation approach. After 50 bootstrap, the best pairs of pathways were identified. According to their AUC values, the pair of pathways, antigen presentation pathway and fMLP signaling in neutrophils, achieved the best AUC value of 1.000, which indicated that this pathway cross-talk could distinguish AS patients from normal subjects. Moreover, the paired pathways of SAPK/JNK signaling and mitochondrial dysfunction were involved in 5 bootstraps. Two paired pathways (antigen presentation pathway and fMLP signaling in neutrophil, as well as SAPK/JNK signaling and mitochondrial dysfunction) can accurately distinguish AS and control samples. These paired pathways may be helpful to identify patients with AS for early intervention. |
publishDate |
2018 |
dc.date.none.fl_str_mv |
2018-01-01 |
dc.type.driver.fl_str_mv |
info:eu-repo/semantics/article |
dc.type.status.fl_str_mv |
info:eu-repo/semantics/publishedVersion |
format |
article |
status_str |
publishedVersion |
dc.identifier.uri.fl_str_mv |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2018000100607 |
url |
http://old.scielo.br/scielo.php?script=sci_arttext&pid=S0100-879X2018000100607 |
dc.language.iso.fl_str_mv |
eng |
language |
eng |
dc.relation.none.fl_str_mv |
10.1590/1414-431x20176698 |
dc.rights.driver.fl_str_mv |
info:eu-repo/semantics/openAccess |
eu_rights_str_mv |
openAccess |
dc.format.none.fl_str_mv |
text/html |
dc.publisher.none.fl_str_mv |
Associação Brasileira de Divulgação Científica |
publisher.none.fl_str_mv |
Associação Brasileira de Divulgação Científica |
dc.source.none.fl_str_mv |
Brazilian Journal of Medical and Biological Research v.51 n.1 2018 reponame:Brazilian Journal of Medical and Biological Research instname:Associação Brasileira de Divulgação Científica (ABDC) instacron:ABDC |
instname_str |
Associação Brasileira de Divulgação Científica (ABDC) |
instacron_str |
ABDC |
institution |
ABDC |
reponame_str |
Brazilian Journal of Medical and Biological Research |
collection |
Brazilian Journal of Medical and Biological Research |
repository.name.fl_str_mv |
Brazilian Journal of Medical and Biological Research - Associação Brasileira de Divulgação Científica (ABDC) |
repository.mail.fl_str_mv |
bjournal@terra.com.br||bjournal@terra.com.br |
_version_ |
1754302945947549696 |