Cell biology and functional genomics of osteoarthritic chondrocytes

Introduction

Functional genomics represents a new challenging approach in order to analyze complex diseases such as osteoarthritis on a molecular level. In particular, the identification and characterization of new target molecules for therapeutic intervention is of interest. Also, potential molecular markers for diagnosis and monitoring of osteoarthritis will contribute to a more appropriate patient management.

Objectives

In our analyses, we attempt to establish a broader gene expression profile of osteoarthritic chondrocytes by modern screening technologies in order to characterize more properly the cellular events and regulatory pathways directly involved in cartilage destruction.

Methods

Cartilage from human femoral condyles of the normal knee joints were obtained from donors at autopsy. Late-stage osteoarthritic cartilage was obtained from patients undergoing total knee replacement surgery. Gene expression analysis was performed by various array technologies and by quantitative PCR. For normalization we applied a novel computational normalization method [1].

Results

Our first focus in looking at chondrocyte gene expression is always linked to the main function of this cell type, the preservation and turnover of the cartilage matrix. Thus, for a start, matrix components and matrix-degrading proteases were the focus of our interest [2]; the analysis of the extracellular matrix proteins showed the largely absent expression of cartilage collagens in normal cartilage and very much increased mRNA levels of several collagen genes in advanced osteoarthritis. With regard to the cartilage-matrix-degrading metalloproteinases, a characteristic pattern was observed in osteoarthritic cartilage versus normal articular cartilage. Future studies will focus on the investigation of pathogenetic pathways based on bioinformatic modelling of their involved genes.

Conclusions

Overall, cDNA technology offers cartilage research a powerful tool for investigating gene expression patterns of a high number of different genes simultaneously. Despite constitutive drawbacks of gene expression technologies, still existing technical problems, and the lack of broadly applicable tools in biostatistics and bioinformatics, even now gene arraying and subsequent technologies initiate new research strategies for understanding pathogenesis and development of drug targets.