Osteoarthritis (OA) is a disease characterized by altered biomechanics, genetic susceptibility and hormonal influences. The disease process affects the entire joint structure, including cartilage, synovial membrane, subchondral bone, which are active sites of growth factor, cytokine, protease and inflammatory mediator production. Reliable biomarkers remain elusive in this disease. Recent studies in our laboratory revealed the unexpected and novel observation that peripheral blood leukocytes (PBMCs) in OA are activated. Using gene expression array, OA-PBMCs were shown to differentially express clusters of transcripts that were distinct from normal controls. Among the upregulated transcripts was COX-2; cytokine-induced production of PGE2 was 5-fold higher in OA-PBMCs than in normal. A cluster of 54 transcripts sensitive to pharmacological intervention (COX-2 specific inhibitors) could also be identified in OA-PBMCs. Independently, human OA affected cartilage showed a specific (proliferation/neoplastic) gene expression signature in OA, which differed from normal and RA cartilage. These findings suggest that there will be """"""""transcriptome-based biomarkers"""""""" in OA patients, in PBMCs and/or cartilage. We will utilize the HJD Arthritis Database and Tissue Bank of 500 OA patients to expand these studies. We will examine PBMCs to establish disease and stage specific gene expression signatures in early and late human OA. A cohort of 50 normals, 50 patients with early OA (OA-E) and 50 patients with late OA (OA-L) will be analyzed. RNA from these PBMCs will be stored. Using gene expression array technology we will identify common transcripts that are differentially expressed in early and/or late OA versus normal. These """"""""transcriptome biomarkers"""""""" will be confirmed by Real time PCR on three occasions over a six-month study period. In a second specific aim we will compare gene expression profile changes in human OA PBMCs and OA-affected cartilage and synovium. We hypothesis that bioinformatic analysis will: (a) show OA-PBMC """"""""transcriptome-based"""""""" biomarkers that distinguish OA vs. normal, as well as markers that identify early vs. late disease. (b) identify end stage OA specific """"""""cartilage dysfunctional transcripts"""""""", involved in joint destruction, which may also be differentially expressed in early and/or late OA PBMCs. Markers of OA-cartilage that are expressed in early disease will be of particular interest as candidates that predict disease progression. In summary, this proposal will utilize genomic technology to identify transcriptome-based biomarkers in OA-PBMC, which we propose act as circulating """"""""sensors"""""""" of complex metabolic and inflammatory processes within the diseased tissues of the OA joint. These studies will open the OA field to novel prognostic and pharmacogenomic future strategies.
