medicine is a traditional Japanese medicine. It originates from a traditional Chinese medicine, but has developed into a unique form in Japan. Traditional Chinese and Kampo
medicines have special kinds of medical terminology for the diagnosis and treatment of diseases and ‘Oketsu’
is one of the pathophysiologic concepts that have been most frequently used in Kampo
medicine. Ancient Chinese medical texts describe a disorder of the blood circulation causing various symptoms, such as blood stasis, reduced blood flow and cessation of flow. This phenomenon is called ‘Oketsu’
in Japanese or ‘Yu Xue’
in Chinese. However, the meaning of ‘Oketsu’
differs slightly from that of ‘Yu Xue’
has gained a more important position in Kampo
medicines in Japan. The main cause of the stagnation in blood flow leading to ‘Oketsu’
syndrome is thought to be insufficient exercise or sleep, mental or physical stress, constipation or a high-calorie diet. At the present time, it may be not possible to translate ‘Oketsu’
accurately in terms of Western medicine. However, ‘Oketsu’
is known to be related to disorders in the peripheral microcirculation, including excessive sensitivity to cold, menstrual disorder and infertility, as well as refractory diseases, such as RA, systemic lupus erythematosus (SLE), disseminated intravascular coagulation (DIC) and various allergic responses (4
). Because ‘Oketsu’
is also a concept denoting ‘the preparatory state for developing recognizable diseases’, the diagnosis and treatment of ‘Oketsu’
not only will improve the symptoms of the manifest diseases, but also may prevent the development of these diseases. Kampo
medicines are formulations consisting of crude drugs that have been used in Japan for thousands of years for patients with a wide variety of disorders. Nowadays, more than 100 Kampo
medicines have been approved as ethical medicines by the Ministry of Health, Labour and Welfare of Japan. The drugs are manufactured on a modern industrial scale in which the quality and quantity of ingredients are standardized under strict guidelines. KBG is thought to be one of the most important prescriptions for improving ‘Oketsu’
syndrome. KBG has been used for the treatment of various types and stages of diseases (6
), from the stage prior to disorder to chronic intractable diseases that are untreatable even by a wide array of therapeutic strategies of modern Western medicine.
In an investigation of the effect of a Kampo medicine (e.g. KBG) on the ‘symptom’ (e.g. ‘Oketsu’ state) diagnosed by Kampo medicine, it is difficult to determine clearly the detailed efficacies and mechanisms of action of the medicine, because there are often multiple active ingredients and components and target sites, and mutual interactions of these multiple components. As described previously, disease concepts such as ‘Oketsu’ are the composite of different and multiple symptoms that can be influenced by environmental and genetic factors. Therefore, the molecular alterations induced in the ‘Oketsu’ state by KBG, in addition to its efficacy, would be mediated by complicated set of multimodal and multifactorial events. Conventional drug research has mainly focused on the mode of action of a relatively small number of molecules. Recent advances in “omics” technology have resulted in the development of extremely high-throughput and comprehensive techniques for functional genomics, proteomics and metabolomics. A powerful array of tools is available for investigating the intricate interplay of different signal-transduction pathways in the cell. It is conceivable that these technologies may offer a crucial contribution to clarification of the concepts and efficacy of Kampo medicine(s) in terms of molecular biology.
In the present study, we have investigated the expression of plasma protein in patients in the ‘Oketsu’
state by using a proteomics approach. We used the patients’ plasma to analyze protein expression for three main reasons. Firstly, collection of blood samples is performed routinely in medical practice and is minimally invasive. Secondly, the ‘Oketsu’
state is considered to be closely related to hemorheological and hemostasis abnormalities. Increases in fibrinogen level, erythrocyte aggregation and blood viscosity in ‘Oketsu’
syndrome and their amelioration by KBG treatment have been reported (8
). Thirdly, the abnormalities in hemostasis suggest that there are proteomic changes in the coagulation-fibrinolytic system in which a massive proteolysis cascade plays a critically important role. A cascade of this type may be involved in ‘Oketsu’
syndrome. Therefore, we focused our attention on the expression of proteins in the plasma rather than the serum, which is devoid of most of the proteins involved in the coagulation-fibrinolytic system. Thus, the adoption of proteomic analysis of plasma in ‘Oketsu’
patients would be reasonable both practically and theoretically.
The present study demonstrated that the ‘Oketsu’
’ states were classified into different clusters in terms of the plasma protein levels. Hierarchical clustering, a common method of the clustering analysis family continuously aggregates similar objects or ‘clusters’ into a larger cluster and eventually generates a single cluster that contains all objects. Therefore, the classification is constructed in a tree-like manner and is represented by a so-called ‘dendrogram’. The similarity between objects is defined by distance metrics such as Euclidean distance, Manhattan distance and lots of other proposed types of metrics. The more similar the objects/clusters are in the earlier stage, the more they are merged. In the present study, the objects to be classified (plasma samples) were represented as a proteomic pattern characterized by differentially expressed peaks, that is, an N-dimensional vector whose element values represent peak intensities. The similarity between two samples was calculated as the Tanimoto
distance between two vectors of proteomic patterns. By the successive aggregation of similar samples, we obtained sample classification (the upper horizontal row in the color map of ). Meanwhile, the given proteomic patterns provided another set of ‘objects’ to be classified, namely, peaks. The profile of each peak was composed by the peak intensities of 96 samples and the similarity of the profiles among 266 peaks was calculated as described above. By the successive aggregation of similar peaks, we obtained peak classification (the left vertical row in the color map of ). Such simultaneous clustering of an identical data set vertically and horizontally is called ‘two-way clustering’, an approach that has been reported to have potentially high performance in the identification of local groups of genes and/or proteins with similar expression patterns (29
). Our results indicate that a characteristic proteomic pattern may exist in the plasma of ‘Oketsu’
patients, although a larger-scale clinical trial will be necessary to validate this finding. Furthermore, the hierarchical clustering is a heuristic approach but may not provide any enough “evidence” in principle.
In general, statistical analysis of the world of ‘omics’ is now being developed. Although there are examples of statistical analyses of hierarchical clustering, the practical significance of such analyses is a complex and controversial issue. At present, ‘omics’ approaches are best-suited to create a new assumption/hypothesis and many researchers have pointed out that validation studies should be conducted in separate follow-up studies. In this case, validation studies with bigger cohorts, methodologic improvement and strictly defined protocols will be absolutely necessary, however, should future studies be undertaken.
Next, to develop a diagnostic criterion for ‘Oketsu’, a decision tree analysis was performed. A decision tree is a decision support tool used to identify the strategy most likely to reach a goal. In the present case, the algorithm searches and selects a certain SELDI peak as a classifier that most efficiently splits ‘Oketsu’ samples (>20 ‘Oketsu'scoring) from ‘non-Oketsu’ samples (≤20 ‘Oketsu’ scoring). Usually, the first classifier cannot give a complete classification. Instead, there is an ‘Oketsu’ -sample-rich group containing a smaller number of ‘non-Oketsu’ samples and a ‘non-Oketsu’-sample-rich group containing a smaller number of ‘Oketsu’ samples. For each group, the algorithm repeats the search for another (second) classifier. The combination of the first and second classifiers thus gives a more accurate classification. This process can be repeated until the tree classifies all of the samples correctly. Thus, the constructed decision tree gives the most efficient method of the classification of the given samples and in the next step; the tree can be used as a predictive model. When a new sample with SELDI data but without ‘Oketsu’ scores is given, it can be predicted whether it is ‘Oketsu’ or ‘non-Oketsu’ by examining the SELDI data in reference to the decision tree. The decision tree construction in the present study, however, remains a preliminary trial that should be improved by large-scale examination. Further studies with independently collected samples will be needed to verify the above points. Collectively, our finding at least addresses the possibility that this ancient and apparently very speculative concept ‘Oketsu’ might have a physical basis and that objective criteria for diagnosing ‘Oketsu’ can be established using a combination of ProteinChip technology and bioinformatics tools.
Several concerns have been raised related to the present approach. Firstly, various researchers have pointed out that, in not a few cases, SELDI-TOF protein patterns in serum are not reproducible across different experiments for reasons such as differences in base line correction, sample preparation protocol, spectrum analysis method, mass calibration method, etc (30
). In preceding studies, we have tested the effect of the ProteinChip lot, sample processing, measures taken at different times and analytical methods and constructed highly standardized protocols. These protocols contain a reliable peak detection algorithm (‘Cross Detector’) and robust methods for selecting significant peaks (‘Peak Separability Analysis’), which are now patent pending and will be described in a future paper. Thus, we think that it is possible that objective criteria for diagnosing ‘Oketsu’
can be established using a combination of ProteinChip technology and bioinformatics tools. Ray et al.
), by standardizing methodology on sample processing, reference specimen, acquisition procedure of mass data, analytical methods, etc. have also demonstrated the potential of the SELDI platform (ProteinChip) for reproducible and consistent analysis of serum/plasma across multiple sites.
Secondly, the availability and reproducibility of ‘profiles’ is highly dependent on the measuring equipment. Extensively standardized equipment, well-validated protocols and their assured execution are necessary. In contrast, measuring the concentration of the proteins identified usually requires relatively low-cost, convenient and highly reproducible means such as enzyme-linked immunosorbent assay and enzymatic biochemical analysis. In fact, we have conducted such a study in a narrower set of subjects with clear-cut symptoms. In that study, we have identified certain predictive biomarker proteins for the beneficial effects of KBG in RA (manuscript in preparation). These markers may be used to improve the responder rate for KBG in RA that is closely related to ‘Oketsu’. It may not be hopeful to identify a single or small number of candidates as markers for the whole ‘Oketsu’ syndrome, because it is related to a very broad array of disorders. However, the identified accumulation of such studies targeted or limited to subjects with subsets of ‘Oketsu’ syndrome will largely contribute to delineate the whole picture of ‘Oketsu’.
In summary, the present study raises the possibility that objective criteria for diagnosing ‘Oketsu’ can be established using a combination of ProteinChip technology and bioinformatics tools. Further studies will be required to identify suitable ‘Oketsu’ biomarkers in detail. Traditional medicine and complementary and alternative medicine (CAM), which are mainly based on an empirical approach, have not been fully accepted in the framework of modern medicine. Problems preventing the utilization of traditional medicines have been a lack of sufficient scientific evidence of their efficacy, standard diagnosis and treatment protocols and communication procedures through scientifically acceptable language. The present study may open the way to elucidating these traditional medical concepts from the viewpoint of modern science and medicine and may thus lead to the integration of traditional medicine/CAM and modern medicine.