E-GEOD-51588 - Genome-wide Expression Profiles of Subchondral Bone in Osteoarthritis

Released on 24 October 2013, last updated on 3 June 2014
Homo sapiens
Samples (50)
Array (1)
Protocols (7)
To date, all of the prior osteoarthritic microarray studies in human tissue have focused on the overlying articular cartilage, meniscus, or synovium but not the underlying subchondral bone. In our previous study, our group developed a methodology for high quality RNA isolation from site-matched cartilage and bone from human knee joints, which allowed us to perform candidate gene expression analysis on the subchohndral bone (published on Osteoarthritis and Cartilage on Dec/5/2012 (doi: 10.1016/j.joca.2012.11.016). To the best of our knowledge, the current study is the first to successfully perform whole-genome microarray profiling analyses of human osteoarthritic subchondral bone. We believe our comprehensive microarray results can improve the understanding of the pathogenesis of osteoarthritis and could further contribute to the development of new biomarker and therapeutic strategies in osteoarthritis. Following histological assessment of the integrity of overlying cartilage and the severity of bone abnormality by microcomputed tomography, we isolated total RNA from regions of interest from human OA (n=20) and non-OA (n=5) knee lateral and medial tibial plateaus (LT and MT). A whole-genome profiling study was performed on an Agilent microarray platform and analyzed using Agilent GeneSpring GX11.5. Confirmatory quantitative reverse-transcription polymerase chain reaction (qRT-PCR) analysis was performed on samples from nine OA individuals to confirm differential expression of 85 genes identified by microarray. Ingenuity Pathway Analysis (IPA) was used to investigate canonical pathways and immunohistochemical staining was performed to validate protein expression levels in samples.
Experiment type
transcription profiling by array 
Ching-Heng Chou <chouchingheng@hotmail.com>, C C Wu, C H Chou, C H Lee, H P Chuang, I W Song, J H Chang, J Y Wu, L S Lu, M T Lee, S Y Kuo, V B Kraus, Y T Chen