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Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis
Kashin-Beck Disease (KBD) is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based...
Autores principales: | , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2015
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4463711/ https://www.ncbi.nlm.nih.gov/pubmed/25997002 http://dx.doi.org/10.3390/ijms160511465 |
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author | Wang, Xi Ning, Yujie Zhang, Feng Yu, Fangfang Tan, Wuhong Lei, Yanxia Wu, Cuiyan Zheng, Jingjing Wang, Sen Yu, Hanjie Li, Zheng Lammi, Mikko J. Guo, Xiong |
author_facet | Wang, Xi Ning, Yujie Zhang, Feng Yu, Fangfang Tan, Wuhong Lei, Yanxia Wu, Cuiyan Zheng, Jingjing Wang, Sen Yu, Hanjie Li, Zheng Lammi, Mikko J. Guo, Xiong |
author_sort | Wang, Xi |
collection | PubMed |
description | Kashin-Beck Disease (KBD) is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs) from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR) algorithm and support vector machine (SVM) algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD. |
format | Online Article Text |
id | pubmed-4463711 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2015 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-44637112015-06-16 Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis Wang, Xi Ning, Yujie Zhang, Feng Yu, Fangfang Tan, Wuhong Lei, Yanxia Wu, Cuiyan Zheng, Jingjing Wang, Sen Yu, Hanjie Li, Zheng Lammi, Mikko J. Guo, Xiong Int J Mol Sci Article Kashin-Beck Disease (KBD) is an endemic osteochondropathy with an unknown pathogenesis. Diagnosis of KBD is effective only in advanced cases, which eliminates the possibility of early treatment and leads to an inevitable exacerbation of symptoms. Therefore, we aim to identify an accurate blood-based gene signature for the detection of KBD. Previously published gene expression profile data on cartilage and peripheral blood mononuclear cells (PBMCs) from adults with KBD were compared to select potential target genes. Microarray analysis was conducted to evaluate the expression of the target genes in a cohort of 100 KBD patients and 100 healthy controls. A gene expression signature was identified using a training set, which was subsequently validated using an independent test set with a minimum redundancy maximum relevance (mRMR) algorithm and support vector machine (SVM) algorithm. Fifty unique genes were differentially expressed between KBD patients and healthy controls. A 20-gene signature was identified that distinguished between KBD patients and controls with 90% accuracy, 85% sensitivity, and 95% specificity. This study identified a 20-gene signature that accurately distinguishes between patients with KBD and controls using peripheral blood samples. These results promote the further development of blood-based genetic biomarkers for detection of KBD. MDPI 2015-05-19 /pmc/articles/PMC4463711/ /pubmed/25997002 http://dx.doi.org/10.3390/ijms160511465 Text en © 2015 by the authors; licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Wang, Xi Ning, Yujie Zhang, Feng Yu, Fangfang Tan, Wuhong Lei, Yanxia Wu, Cuiyan Zheng, Jingjing Wang, Sen Yu, Hanjie Li, Zheng Lammi, Mikko J. Guo, Xiong Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis |
title | Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis |
title_full | Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis |
title_fullStr | Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis |
title_full_unstemmed | Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis |
title_short | Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis |
title_sort | gene expression signature in endemic osteoarthritis by microarray analysis |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4463711/ https://www.ncbi.nlm.nih.gov/pubmed/25997002 http://dx.doi.org/10.3390/ijms160511465 |
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