Gene Expression Profiling in Rheumatology

In the last decade, the analysis of gene expression in tissues and cells has evolved from the analysis of a selected set of genes to an efficient high throughput whole-genome screening approach of potentially all genes expressed. Development of sophisticated methodologies such as microarray technology allows an open-ended survey to identify comprehensively the fraction of genes that are differentially expressed between samples and that define the samples’ unique biology. By a global analysis of the genes that are expressed in cells and tissues of an individual under different conditions and during disease, we can build up “gene expression profiles (signatures)” which characterize the dynamic functioning of the genome under pathophysiological conditions. This strategy also provides the means to subdivide patients that suffer from a complex heterogeneous disease into more homogeneous subgroups. Such discovery-based research identifies biological processes that may include new genes with unknown function or genes not previously known to be involved in this process. The latter category may hold surprises that sometimes urge us to redirect our thinking. We have used microarrays to disclose the heterogeneity of rheumatoid arthritis (RA) patients at the level of gene expression of the affected synovial tissues. Analysis of the expression profiles of synovial tissues from different patients with RA revealed considerable variability, resulting in the identification of at least two molecularly distinct forms of RA tissues. One is characterized by genes that indicate an active inflammatory infiltrate with high immunoglobulin production, whereas the other type shows little immune activation and instead shows a higher stromal cell activity. These results confirm the heterogeneous nature of RA and suggest the existence of distinct pathogenic mechanisms that contribute to RA. The differences in expression profiles provide opportunities to stratify patients for intervention therapies based on molecular criteria.