Gene expression signature in endemic osteoarthritis by microarray analysis
2015 (English)In: International Journal of Molecular Sciences, ISSN 1422-0067, Vol. 16, no 5, 11465-11481 p.Article in journal (Refereed) Published
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.
Place, publisher, year, edition, pages
Basel, Switzerland: MDPI , 2015. Vol. 16, no 5, 11465-11481 p.
Kashin-Beck disease, biomarker, gene expression signature, microarray, peripheral blood mononuclear cells
Medical Biotechnology (with a focus on Cell Biology (including Stem Cell Biology), Molecular Biology, Microbiology, Biochemistry or Biopharmacy)
Research subject Molecular Medicine; Genetics
IdentifiersURN: urn:nbn:se:umu:diva-103826DOI: 10.3390/ijms160511465ISI: 000356241400135OAI: oai:DiVA.org:umu-103826DiVA: diva2:815720