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Evidence-Based Complementary and Alternative Medicine
Volume 5, Issue 4, Pages 463-474
http://dx.doi.org/10.1093/ecam/nem049
Original Article

A Proteomic Approach for the Diagnosis of ‘Oketsu’ (blood stasis), a Pathophysiologic Concept of Japanese Traditional (Kampo) Medicine

1Central Research Laboratories, Tsumura & Co., Ibaraki, Japan
2Bioinformatics Division, INTEC Web and Genome Informatics Corporation, Toyama, Japan
3Department of Japanese Oriental Medicine, Toyama Prefectural Central Hospital, Toyama, Japan
4Toyama New Industry Organization, Toyama, Japan
5Division of Pathogenic Biochemistry, Institute of Natural Medicine, University of Toyama, Toyama, Japan
6Department of Kampo Medicine, Faculty of Medicine, University of Toyama, Toyama, Japan
7The 21st Century COE Program, University of Toyama, Toyama, Japan
8Department of Japanese-Oriental (Kampo) Medicine, Graduate School of Medicine, Chiba University, Chiba, Japan

Received 19 May 2006; Accepted 13 April 2007

Copyright © 2008 Chinami Matsumoto et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Abstract

‘Oketsu’ is a pathophysiologic concept in Japanese traditional (Kampo) medicine, primarily denoting blood stasis/stagnant syndrome. Here we have explored plasma protein biomarkers and/or diagnostic algorithms for ‘Oketsu’. Sixteen rheumatoid arthritis (RA) patients were treated with keishibukuryogan (KBG), a representative Kampo medicine for improving ‘Oketsu’. Plasma samples were diagnosed as either having an ‘Oketsu’ (n = 19) or ‘non-Oketsu’ (n = 29) state according to Terasawa's ‘Oketsu’ scoring system. Protein profiles were obtained by surface-enhanced laser desorption/ionization time-of-flight mass spectrometry (SELDI-TOF MS) and hierarchical clustering and decision tree analyses were performed. KBG treatment for 4 or 12 weeks decreased the ‘Oketsu’ scores significantly. SELDI protein profiles gave 266 protein peaks, whose expression was significantly different between the ‘Oketsu’ and ‘non-Oketsu’ states. Hierarchical clustering gave three major clusters (I, II, III). The majority (68.4%) of ‘Oketsu’ samples were clustered into one cluster as the principal component of cluster I. The remaining ‘Oketsu’ profiles constituted a minor component of cluster II and were all derived from patients cured of the ‘Oketsu’ state at 12 weeks. Construction of the decision tree addressed the possibility of developing a diagnostic algorithm for ‘Oketsu’. A reduction in measurement/pre-processing conditions (from 55 to 16) gave a similar outcome in the clustering and decision tree analyses. The present study suggests that the pathophysiologic concept of Kampo medicine ‘Oketsu’ has a physical basis in terms of the profile of blood proteins. It may be possible to establish a set of objective criteria for diagnosing ‘Oketsu’ using a combination of proteomic and bioinformatics-based classification methods.