Gene Expression Signature in Endemic Osteoarthritis by Microarray Analysis

被引:4
|
作者
Wang, Xi [1 ]
Ning, Yujie [1 ]
Zhang, Feng [1 ]
Yu, Fangfang [1 ]
Tan, Wuhong [1 ]
Lei, Yanxia [1 ]
Wu, Cuiyan [1 ]
Zheng, Jingjing [1 ]
Wang, Sen [1 ]
Yu, Hanjie [2 ]
Li, Zheng [2 ]
Lammi, Mikko J. [3 ]
Guo, Xiong [1 ]
机构
[1] Xi An Jiao Tong Univ, Key Lab Trace Elements & Endem Dis, Natl Hlth & Family Planning Commiss, Sch Publ Hlth,Hlth Sci Ctr, Xian 710061, Peoples R China
[2] NW Univ Xian, Natl Engn Res Ctr Miniaturized Detect Syst, Xian 710069, Peoples R China
[3] Umea Univ, Dept Integrat Med Biol, S-90187 Umea, Sweden
基金
中国国家自然科学基金;
关键词
Kashin-Beck disease; microarray; peripheral blood mononuclear cells; gene expression signature; KASHIN-BECK DISEASE; KAPPA-B; PROFILES; IDENTIFICATION; CARTILAGE; PROTEINS; VALIDATION; INHIBITORS; BINDING; CHINA;
D O I
10.3390/ijms160511465
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
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.
引用
收藏
页码:11465 / 11481
页数:17
相关论文
共 50 条
  • [21] UNIQUE GENE EXPRESSION PROFILE IN OSTEOARTHRITIS SYNOVIUM COMPARED WITH CARTILAGE; ANALYSIS OF PUBLICLY ACCESSIBLE MICROARRAY DATASETS
    Ji, J. D.
    Park, R.
    ANNALS OF THE RHEUMATIC DISEASES, 2016, 75 : A47 - A47
  • [22] Microarray analysis of differential gene expression in temporomandibular joint condylar cartilage after experimentally induced osteoarthritis
    Meng, JH
    Ma, XC
    Ma, DL
    Xu, CM
    OSTEOARTHRITIS AND CARTILAGE, 2005, 13 (12) : 1115 - 1125
  • [23] Unique gene expression profile in osteoarthritis synovium compared with cartilage: analysis of publicly accessible microarray datasets
    Park, Robin
    Ji, Jong Dae
    RHEUMATOLOGY INTERNATIONAL, 2016, 36 (06) : 819 - 827
  • [24] Microarray analysis reveals age-related differences in gene expression during the development of osteoarthritis in mice
    Amy Olex
    Richard Loeser
    Jeff Chou
    Mike Callahan
    Cristin Ferguson
    Jacquelyn S Fetrow
    Genome Biology, 11 (Suppl 1)
  • [25] Unique gene expression profile in osteoarthritis synovium compared with cartilage: analysis of publicly accessible microarray datasets
    Robin Park
    Jong Dae Ji
    Rheumatology International, 2016, 36 : 819 - 827
  • [26] Microarray analysis reveals age-related differences in gene expression during the development of osteoarthritis in mice
    Loeser, Richard F.
    Olex, Amy L.
    McNulty, Margaret A.
    Carlson, Cathy S.
    Callahan, Michael F.
    Ferguson, Cristin M.
    Chou, Jeff
    Leng, Xiaoyan
    Fetrow, Jacquelyn S.
    ARTHRITIS AND RHEUMATISM, 2012, 64 (03): : 705 - 717
  • [27] Microarray analysis reveals age-related differences in gene expression during the development of osteoarthritis in mice
    Olex, Amy
    Loeser, Richard
    Chou, Jeff
    Callahan, Mike
    Ferguson, Cristin
    Fetrow, Jacquelyn S.
    GENOME BIOLOGY, 2010, 11
  • [28] Analysis of variance for gene expression microarray data
    Kerr, MK
    Martin, M
    Churchill, GA
    JOURNAL OF COMPUTATIONAL BIOLOGY, 2000, 7 (06) : 819 - 837
  • [29] Microarray Gene Expression Analysis using R
    Petre, I.
    Buiu, C.
    INTERNATIONAL CONFERENCE ON ADVANCEMENTS OF MEDICINE AND HEALTH CARE THROUGH TECHNOLOGY, MEDITECH 2016, 2017, 59 : 358 - 361
  • [30] Microarray Data Analysis of Gene Expression Evolution
    Lin, Honghuang
    GENE REGULATION AND SYSTEMS BIOLOGY, 2009, 3 : 211 - 214