Genomics

Dataset Information

0

Rheumatoid arthritis and rheumatoid synovium


ABSTRACT: Rheumatoid arthritis (RA) is a heterogeneous disease. We used cDNA microarray technology to subclassify RA patients and disclose disease pathways in rheumatoid synovium. Hierarchical clustering of gene expression data identified two main groups of tissues (RA-I and RA-II). A total of 121 genes were significantly higher expressed in the RA-I tissues, whereas 39 genes were overexpressed in the RA-II tissues. Among the 121 genes overexpressed in RA-I tissues, a relative majority of nine genes are located on chromosome 6p21.3. An interpretation of biological processes that take place revealed that the gene expression profile in RA-I tissues is indicative for an adaptive immune response. The RA-II group showed expression of genes suggestive for fibroblast dedifferentiation. Within the RA-I group, two subgroups could be distinguished; the RA-Ia group showed predominantly immune-related gene activity, while the RA-Ib group showed an additional higher activity of genes indicative for the classical pathway of complement activation. All tissues except the RA-Ia subgroup showed elevated expression of genes involved in tissue remodeling. 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 based on molecular criteria. An all pairs experiment design type is where all labeled extracts are compared to every other labeled extract. Keywords: all_pairs

ORGANISM(S): Homo sapiens

PROVIDER: GSE3824 | GEO | 2005/12/15

SECONDARY ACCESSION(S): PRJNA94043

REPOSITORIES: GEO

Similar Datasets

2005-10-11 | E-SMDB-1874 | biostudies-arrayexpress
2005-12-14 | E-GEOD-3824 | biostudies-arrayexpress
2024-01-07 | PXD038584 | Pride
2004-11-04 | GSE1919 | GEO
2017-07-29 | GSE71841 | GEO
2015-01-14 | E-GEOD-64922 | biostudies-arrayexpress
2020-11-01 | GSE122616 | GEO
2014-09-25 | BIOMD0000000550 | BioModels
2020-11-10 | GSE159117 | GEO
2016-01-27 | GSE77298 | GEO