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.
This exploratory study suggests that classification by Chinese Medicine (CM) as “RA heat” or “RA cold” may correlate with molecular differences and that CM features might identify subtypes of RA amenable to different therapies.
From the *Division of Analytical Biosciences, Leiden/Amsterdam Center for Drug Research, Leiden University, Leiden, The Netherlands; †Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, Dalian, Liaoning, China; ‡Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Dongzhimen, Beijing, China; §SU BioMedicine, Utrechtseweg, Zeist, The Netherlands; ¶Oxrider, Education and Research, Barmsijs, Nieuwegein, The Netherlands; and ∥TNO Netherlands Organization for Applied Scientific Research, TNO Pharma, Zeist, The Netherlands.
These authors H.V.W., K.Y., C.L. have equally contributed to this article.
Supported by the Sino-Dutch center for Preventive and Personalized Medicine sponsored by the Netherlands Genomics Initiative, Chinese Academy of Sciences, Ministry of Science and Technology (China), National Science Foundation of China [project No 90209002, 90709007], TNO (NL), Netherlands Metabolomics Center and the Osteo- and Rheumatoid Arthritis Foundation (NL) and also partly granted by the China International Science and Technology Cooperation Program [2007DFA31060 and 2009DFA41250], the National Key Project of Scientific and Technical Supporting Programs [2006BAK02A12] from the Ministry of Science and Technology of China.
Correspondence: Jan van der Greef, Division of Analytical Biosciences, Leiden/Amsterdam Center for Drug Research, Leiden University, PO Box 9502, 2300 RA Leiden, the Netherlands. E-mail: firstname.lastname@example.org; or Aiping Lu, Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Dongzhimen, Beijing 100700, China. E-mail: email@example.com; or Guowang Xu, Key Laboratory of Separation Science for Analytical Chemistry, Dalian Institute of Chemical Physics, Chinese Academy of Sciences, 457 Zhongshan Road, Dalian 116023, China. E-mail: firstname.lastname@example.org.