A Proteomic Approach for the Diagnosis of 'Oketsu' (blood stasis), a Pathophysiologic Concept of Japanese Traditional (Kampo) Medicine. Issue 4 (2008) - Matsumoto, Chinami; Kojima, Tetsuko; Ogawa, Kazuo; Kamegai, Satoshi; Oyama, Takuya; Shibagaki, Yukari; Kawasaki, Tetsuo; Fujinaga, Hiroshi; Takahashi, Kozo; Hikiami, Hiroaki; Goto, Hirozo; Kiga, Chizuru; et al.
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.