A Proteomic Approach for the Diagnosis of ‘Oketsu’ (blood stasis), a Pathophysiologic Concept of Japanese Traditional (Kampo) Medicine
Open Access
- 13 April 2007
- journal article
- website
- Published by Wiley in Evidence-Based Complementary and Alternative Medicine
- Vol. 5 (4) , 463-474
- https://doi.org/10.1093/ecam/nem049
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.Keywords
Funding Information
- Ministry of Education, Culture, Sports, Science and Technology
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