Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis

Abstract Background: Multiple sclerosis (MS) is a central nervous system disease with a high disability rate. Modern molecular biology techniques have identified a number of key genes and diagnostic markers to MS, but the etiology and pathogenesis of MS remain unknown. Results: In this study, the...

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Autores principales: Chen,Xin, Hou,Huiqing, Qiao,Huimin, Fan,Haolong, Zhao,Tianyi, Dong,Mei
Lenguaje:English
Publicado: Sociedad de Biología de Chile 2021
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Acceso en línea:http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602021000100212
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spelling oai:scielo:S0716-976020210001002122021-04-28Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosisChen,XinHou,HuiqingQiao,HuiminFan,HaolongZhao,TianyiDong,Mei Biomarker Support vector machine approach Multiple sclerosis Bioinformatics Protein&#8211;protein interaction Abstract Background: Multiple sclerosis (MS) is a central nervous system disease with a high disability rate. Modern molecular biology techniques have identified a number of key genes and diagnostic markers to MS, but the etiology and pathogenesis of MS remain unknown. Results: In this study, the integration of three peripheral blood mononuclear cell (PBMC) microarray datasets and one peripheral blood T cells microarray dataset allowed comprehensive network and pathway analyses of the biological functions of MS-related genes. Differential expression analysis identified 78 significantly aberrantly expressed genes in MS, and further functional enrichment analysis showed that these genes were associated with innate immune response-activating signal transduction (p = 0.0017), neutrophil mediated immunity (p = 0.002), positive regulation of innate immune response (p = 0.004), IL-17 signaling pathway (p < 0.035) and other immune-related signaling pathways. In addition, a network of MS-specific protein&#8211;protein interactions (PPI) was constructed based on differential genes. Subsequent analysis of network topology properties identified the up-regulated CXCR4, ITGAM, ACTB, RHOA, RPS27A, UBA52, and RPL8 genes as the hub genes of the network, and they were also potential biomarkers of MS through Rap1 signaling pathway or leukocyte transendothelial migration. RT-qPCR results demonstrated that CXCR4 was obviously up-regulated, while ACTB, RHOA, and ITGAM were down-regulated in MS patient PBMC in comparison with normal samples. Finally, support vector machine was employed to establish a diagnostic model of MS with a high prediction performance in internal and external datasets (mean AUC = 0.97) and in different chip platform datasets (AUC = (0.93). Conclusion: This study provides new understanding for the etiology/pathogenesis of MS, facilitating an early identification and prediction of MS.info:eu-repo/semantics/openAccessSociedad de Biología de ChileBiological Research v.54 20212021-01-01text/htmlhttp://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602021000100212en10.1186/s40659-021-00334-6
institution Scielo Chile
collection Scielo Chile
language English
topic Biomarker
Support vector machine approach
Multiple sclerosis
Bioinformatics
Protein&#8211;protein interaction
spellingShingle Biomarker
Support vector machine approach
Multiple sclerosis
Bioinformatics
Protein&#8211;protein interaction
Chen,Xin
Hou,Huiqing
Qiao,Huimin
Fan,Haolong
Zhao,Tianyi
Dong,Mei
Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis
description Abstract Background: Multiple sclerosis (MS) is a central nervous system disease with a high disability rate. Modern molecular biology techniques have identified a number of key genes and diagnostic markers to MS, but the etiology and pathogenesis of MS remain unknown. Results: In this study, the integration of three peripheral blood mononuclear cell (PBMC) microarray datasets and one peripheral blood T cells microarray dataset allowed comprehensive network and pathway analyses of the biological functions of MS-related genes. Differential expression analysis identified 78 significantly aberrantly expressed genes in MS, and further functional enrichment analysis showed that these genes were associated with innate immune response-activating signal transduction (p = 0.0017), neutrophil mediated immunity (p = 0.002), positive regulation of innate immune response (p = 0.004), IL-17 signaling pathway (p < 0.035) and other immune-related signaling pathways. In addition, a network of MS-specific protein&#8211;protein interactions (PPI) was constructed based on differential genes. Subsequent analysis of network topology properties identified the up-regulated CXCR4, ITGAM, ACTB, RHOA, RPS27A, UBA52, and RPL8 genes as the hub genes of the network, and they were also potential biomarkers of MS through Rap1 signaling pathway or leukocyte transendothelial migration. RT-qPCR results demonstrated that CXCR4 was obviously up-regulated, while ACTB, RHOA, and ITGAM were down-regulated in MS patient PBMC in comparison with normal samples. Finally, support vector machine was employed to establish a diagnostic model of MS with a high prediction performance in internal and external datasets (mean AUC = 0.97) and in different chip platform datasets (AUC = (0.93). Conclusion: This study provides new understanding for the etiology/pathogenesis of MS, facilitating an early identification and prediction of MS.
author Chen,Xin
Hou,Huiqing
Qiao,Huimin
Fan,Haolong
Zhao,Tianyi
Dong,Mei
author_facet Chen,Xin
Hou,Huiqing
Qiao,Huimin
Fan,Haolong
Zhao,Tianyi
Dong,Mei
author_sort Chen,Xin
title Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis
title_short Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis
title_full Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis
title_fullStr Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis
title_full_unstemmed Identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis
title_sort identification of blood-derived candidate gene markers and a new 7-gene diagnostic model for multiple sclerosis
publisher Sociedad de Biología de Chile
publishDate 2021
url http://www.scielo.cl/scielo.php?script=sci_arttext&pid=S0716-97602021000100212
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AT houhuiqing identificationofbloodderivedcandidategenemarkersandanew7genediagnosticmodelformultiplesclerosis
AT qiaohuimin identificationofbloodderivedcandidategenemarkersandanew7genediagnosticmodelformultiplesclerosis
AT fanhaolong identificationofbloodderivedcandidategenemarkersandanew7genediagnosticmodelformultiplesclerosis
AT zhaotianyi identificationofbloodderivedcandidategenemarkersandanew7genediagnosticmodelformultiplesclerosis
AT dongmei identificationofbloodderivedcandidategenemarkersandanew7genediagnosticmodelformultiplesclerosis
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