Complex chronic diseases such as rheumatoid arthritis have become a major challenge in medicine and for the pharmaceutical industry. New impulses for drug development are needed.
A systems biology approach is explored to find subtypes of rheumatoid arthritis patients enabling a development towards more personalized medicine.
Blood samples of 33 rheumatoid arthritis (RA) patients and 16 healthy volunteers were collected. The RA patients were diagnosed according to Chinese medicine (CM) theory and divided into 2 groups, the RA Heat and RA Cold group. CD4 T-cells were used for a total gene expression analysis. Metabolite profiles were measured in plasma using gas chromatography/mass spectrometry. Multivariate statistics was employed to find potential biomarkers for the RA Heat and RA Cold phenotype. A comprehensive biologic interpretation of the results is discussed.
The genomics and metabolomics analysis showed statistically relevant different gene expression and metabolite profiles between healthy controls and RA patients as well as between the RA Heat and RA Cold group. Differences were found in the regulation of apoptosis. In the RA Heat group caspase 8 activated apoptosis seems to be stimulated while in the RA Cold group apoptosis seems to be suppressed through the Nrf2 pathway.
RA patients could be divided in 2 groups according to CM theory. Molecular differences between the RA Cold and RA Heat groups were found which suggest differences in apoptotic activity. Subgrouping of patients according to CM diagnosis has the potential to provide opportunities for better treatment outcomes by targeting Western or CM treatment to specific groups of patients.