Metabolomics,Unknown,Transcriptomics,Genomics,Proteomics

Dataset Information

Human bone marrow-derived mononuclear cells (BMMC): rheumatoid arthritis vs. osteoarthritis

ABSTRACT: Gene expression profiling of BMMC from patients with rheumatoid arthritis (RA) vs. osteoarthritis (OA). Bone marrow was obtained from patients with RA (n=9) or OA (n=10). The bone marrow samples from the 10 OA patients are used as controls.

ORGANISM(S): Homo sapiens

SUBMITTER: Norihiro Nishimoto

PROVIDER: E-GEOD-27390 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Publications

Abnormal networks of immune response-related molecules in bone marrow cells from patients with rheumatoid arthritis as revealed by DNA microarray analysis.

Lee Hooi-Ming HM Sugino Hidehiko H Aoki Chieko C Shimaoka Yasunori Y Suzuki Ryuji R Ochi Kensuke K Ochi Takahiro T Nishimoto Norihiro N

Arthritis research & therapy 20110616 3

<h4>Introduction</h4>Rheumatoid arthritis (RA) is a systemic autoimmune disease characterized by chronic synovitis that progresses to destruction of cartilage and bone. Bone marrow (BM) cells have been shown to contribute to this pathogenesis. In this study, we compared differentially expressed molecules in BM cells from RA and osteoarthritis (OA) patients and analyzed abnormal regulatory networks to identify the role of BM cells in RA.<h4>Methods</h4>Gene expression profiles (GEPs) in BM-derive ...[more]

PMID: 21679443

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Project description:Synovial fibroblasts in persistent inflammatory arthritis have been suggested to have parallels with cancer growth and wound healing, both of which involve a stereotypical serum response program. We tested the hypothesis that a serum response program can be used to classify diseased tissues, and investigated the serum response program in fibroblasts from multiple anatomical sites and two diseases. To test our hypothesis we utilized a bioinformatics approach to explore a publicly available microarray dataset including RA, OA and normal synovial tissue, then extended those findings in a new microarray dataset representing matched synovial, bone marrow and skin fibroblasts cultured from RA and OA patients undergoing arthroplasty. The classical fibroblast serum response program discretely classified RA, OA and normal synovial tissues. Analysis of low and high serum treated fibroblast microarray data revealed a hierarchy of control, with anatomical site the most powerful classifier followed by response to serum and then disease. In contrast to skin and bone marrow fibroblasts, exposure of synovial fibroblasts to serum led to convergence of RA and OA expression profiles. Pathway analysis revealed three inter-linked gene networks characterising OA synovial fibroblasts: Cell remodelling through insulin-like growth factors, differentiation and angiogenesis through ?3 integrin, and regulation of apoptosis through CD44. We have demonstrated that Fibroblast serum response signatures define disease at the tissue level, and that an OA specific, serum dependent repression of genes involved in cell adhesion, extracellular matrix remodelling and apoptosis is a critical discriminator between cultured OA and RA synovial fibroblasts. Fibroblasts were isolated from synovium, bone marrow and skin tissue samples taken at the time of knee or hip replacement surgery from 12 rheumatoid arthritis patients meeting the 1987 ACR criteria and 6 osteoarthritis patients diagnosed on the basis of characteristic x-ray findings and the absence of features suggestive of inflammatory arthritis. Only one hip sample was present in either disease group. Fibroblasts were maintained in fibroblast medium (consisting of 81.3% RPMI 1640, 10% FCS, 0.81x MEM non-essential amino acids, 0.81mM sodium orthopyruvate, 1.62mM glutamine, 810U/ml penicillin and 81?g/ml streptomycin) at 37°C in a humidified 5% CO2 atmosphere.

Dataset Information

Human bone marrow-derived mononuclear cells (BMMC): rheumatoid arthritis vs. osteoarthritis

Publications

Abnormal networks of immune response-related molecules in bone marrow cells from patients with rheumatoid arthritis as revealed by DNA microarray analysis.

Similar Datasets

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