Identification of a predictive biomarker for the beneficial effect of a Kampo (Japanese traditional) medicine keishibukuryogan in rheumatoid arthritis patients.

OBJECTIVES: Kampo (Japanese traditional herbal) medicines are now ethically used in Japan as pharmaceutical grade prescription drugs. However, there are distinct groups of responders and non-responders to Kampo medicines. We searched for biomarker candidates to discriminate responders from non-responders to keishibukuryogan (KBG); one of the most frequently used Kampo medicines. DESIGN AND METHODS: A combination of SELDI technology and a decision tree analysis with proprietary developed bioinformatics tools was applied to 41 (32 for tree construction and 9 for validation test) plasma samples obtained from rheumatoid arthritis (RA) patients. A candidate biomarker protein was identified using LC-MS/MS.
RESULTS: The constructed tree with measurable reliability contained only a single peak which was identified as haptoglobin alpha 1 chain (Hpalpha1).
CONCLUSION: Hpalpha1 is a biomarker candidate for discriminating responders from non-responders to KBG treatment for RA. The present results may open the way to the establishment of "evidence-based" complementary and alternative medicine.