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Understanding Cold and Hot Pattern Classification Based on Systems Biology

시스템 생리학에 기반한 한열 변증의 이해

  • Lee, Soojin (Department of Physiology, College of Korean Medicine, Sangji University)
  • 이수진 (상지대학교 한의과대학 생리학교실)
  • Received : 2016.11.25
  • Accepted : 2016.12.19
  • Published : 2016.12.25

Abstract

Systems biology is an emerging field aiming at a systems level understanding of living organisms and focusing on the characteristics of the whole network of them. The emergence of systems biology is partly because of the availability of huge amounts of data on organisms and the extensive support of computational technologies as the tools for understanding complex biological systems. The scientific understanding of Korean medicine has been obstructed because of the lack of proper methods examining the complex nature and the unique property of it. However, systems biology could give a chance understanding Korean medicine objectively and scientifically. Pattern classification is a unique tool of Korean medicine to diagnose and treat patients and systems biology would give a useful tool to interpret pattern classification. Various omics technologies has been used to explain the relations between pattern classification and biological factors and then many characteristics of pattern classification in various diseases have been discovered. Therefore, pattern classification could be a bridge to understand the features and differences of western medicine and Korean medicine and it could be a basis to develop pattern-based personalized medicine.

Keywords

References

  1. Barabasi, A.L., Gulbahce, N., Loscalzo, J. Network Medicine: A Network-based Approach to Human Disease. Nat Rev Genet 12(1):56-68, 2011. https://doi.org/10.1038/nrg2918
  2. Kitano, H. Looking Beyond the Details: A Rise in System-oriented Approaches in Genetics and Molecular Biology. Curr Genet 41(1):1-10, 2002. https://doi.org/10.1007/s00294-002-0285-z
  3. Baik, Y.S. A Study on the Changes of Concept of Syndrome Differentiation in the History of Traditional Medicine - Focusing on Meaning and Process -. J Korean Med Classics 27(4):133-151, 2014. https://doi.org/10.14369/skmc.2014.27.4.133
  4. Lee, S. Systems Biology - A Pivotal Research Methodology for Understanding the Mechanisms of Traditional Medicine. J of Pharmacopuncture 18(3):11-18, 2015. https://doi.org/10.3831/KPI.2015.18.020
  5. Chambliss, A.B., Chan, D.W. Precision Medicine: from Pharmacogenomics to Pharmacoproteomics. Clin Proteom 13: 25, 2016. https://doi.org/10.1186/s12014-016-9127-8
  6. Lu, A., Jiang, M., Zhang, C., Chan, K. An Integrative Approach of Linking Traditional Chinese Medicine Pattern Classification and Biomedicine Diagnosis. J Ethnopharmacol 141(2):549-556, 2012. https://doi.org/10.1016/j.jep.2011.08.045
  7. Oriental Medicine Advanced Searching Integrated System (OASIS) [Internet]. Korean Institute of Oriental Medicine. Available from https://oasis.kiom.re.kr/index.jsp
  8. He, Y., Lu, A., Lu, C., Zha, Y., Yan, X., Song, Y., Zeng, S., Liu, W., Zhu, W., Su, L., Feng, X., Qian, X., Tsang, I. Symptom Combinations Assessed in Traditional Chinese Medicine and Its Predictive Role in ACR20 Efficacy Response in Rheumatoid Arthritis. Am J Chinese Med 36(4):675-683, 2008. https://doi.org/10.1142/S0192415X08006144
  9. Manheimer, E., Wieland, S., Kimbrough, E., Cheng, K., Berman, BM. Evidence from the Cochrane Collaboration for Traditional Chinese Medicine Therapies. J Alt Compl Med 15(9):1001-1014, 2009. https://doi.org/10.1089/acm.2008.0414
  10. Kim, C.K., Kim, D.H., Lee, M.S. Randomized Controlled Trials on Complementary and Traditional Medicine in the Korean Literature. Evid-Based Compl Alt 194047, 2014.
  11. Liang, L., Leung, EL., Tian, X. Perspective: The Clinical Trial Barriers. Nature 480: S100, 2011. https://doi.org/10.1038/480S100a
  12. Tsang, I.K.Y. Establishing the Efficacy of Traditional Chinese Medicine. Nat Clin Pract Rheum 3(2):60-61, 2007. https://doi.org/10.1038/ncprheum0406
  13. Lee, S. Computer Simulation Study of the Potential Anti-arrhythmic Properties of Paeonol. J Physiol Pathol Korean Med 29(4):305-312, 2015. https://doi.org/10.15188/kjopp.2015.08.29.4.305
  14. Zhang, Q., Wu, Z., Feng, Y., Shi, J. Levels of Sexual Hormones in Relation with Syndrome-differentiation of TCM in Patients of Chronic Renal Failure. J Trad Chinese Med 10(2):132-135, 1990.
  15. Takeichi, M, Sato, T. Computerized Color Analysis of "Sue Yu" (Blood Stasis) in the Sublingual Vein Using a New Technology. Am J Chinese Med 25(2):213-219, 1997. https://doi.org/10.1142/S0192415X97000251
  16. Cheng, L., Yuanyan, L., Cheng, X., Miao, J., Qinglin, Z., Aiping, L. Biological Basis of Cold and Heat Pattern of Rheumatoid Arthritis in Traditional Chinese Medicine. World Sci Tech 12(5):814-817, 2010. https://doi.org/10.1016/S1876-3553(11)60028-8
  17. Wang, H.L., Jiang, Q., Feng, X.H., Zhang, H.D., Ge, L., Luo, C.G., Gong, X., Li, B. Tripterygium Wilfordii Hook F versus Conventional Synthetic Disease-modifying Anti-rheumatic Drugs as Monotherapy for Rheumatoid Arthritis: A Systematic Review and Network Meta-analysis. BMC Complem Altern Med 16: 215, 2016. https://doi.org/10.1186/s12906-016-1194-x
  18. Li, S., Zhang, Z.Q., Wu, L.J., Zhang, X.G., Li, Y.D., Wang, Y.Y. Understanding ZHENG in Traditional Chinese Medicine in the Context of Neuro-endocrine-immune Network. IET Syst Biol 1(1):51-60, 2007. https://doi.org/10.1049/iet-syb:20060032
  19. Chen, G., Lu, C., Zha, Q., Xiao, C., Xu, S., Ju, D., et al. A network-based analysis of traditional Chinese medicine cold and hot patterns in rheumatoid arthritis. Complement Ther Med 20(1-2):23-30, 2012. https://doi.org/10.1016/j.ctim.2011.10.005
  20. Ma, T., Tan, C., Zhang, H., Wang, M., Ding, W., Li, S. Bridging the Gap between Traditional Chinese Medicine and Systems Biology: the Connection of Cold Syndrome and NEI Network. Mol Biosyst 6(4):613-619, 2010. https://doi.org/10.1039/b914024g
  21. Lu, C., Xiao, C., Chen, G., Jiang, M., Zha, Q., Yan, X., Kong, W., Lu, A. Cold and Heat Pattern of Rheumatoid Arthritis in Traditional Chinese Medicine: Distinct Molecular Signatures Indentified by Microarray Expression Profiles in CD4-positive T cell. Rheumatol Int 32(1):61-68, 2012. https://doi.org/10.1007/s00296-010-1546-7
  22. van Wietmarschen, H., Yuan, K., Lu, C., Gao, P., Wang, J., Xiao, C., Yan, X,. Wang, M., Schroen, J., Lu, A., Xu, G., van der Greef, J. Systems Biology Guided by Chinese Medicine Reveals New Markers for Sub-typing Rheumatoid Arthritis Patients. J Clin Rheumatol 15(7):330-337, 2009. https://doi.org/10.1097/RHU.0b013e3181ba3926
  23. Jiang, M., Xiao, C., Chen, G., Lu, C., Zha, Q., Yan, X., Kong, W., Xu, S., Ju, D., Xu, P., Zou, Y., Lu, A. Correlation Between Cold and Hot Pattern in Traditional Chinese Medicine and Gene Expression Profiles in Rheumatoid Arthritis. Front Med 5(2):219-228, 2011. https://doi.org/10.1007/s11684-011-0133-y
  24. Guo, H., Niu, X., Gu, Y., Lu, C., Xiao, C., Yue, K., Zhang, G., Pan, X., Jiang, M., Tan, Y., Kong, H., Liu, Z., Xu, G., Lu, A. Differential Amino Acid, Carbohydrate and Lipid Metabolism Perpetuations Involved in a Subtype of Rheumatoid Arthritis with Chinese Medicine Cold Pattern. Int J Mol Sci 17(10):E1757, 2016. https://doi.org/10.3390/ijms17101757
  25. Wu, Y., Cun, Y., Dong, J., Shao, J., Luo, S., Nie, S., Yu, H., Zheng, B., Wang, Q., Xiao, C. Polymorphisms in PPARD, PPARG and APM1 Associated with Four Types of Traditional Chinese Medicine Constitutions. J Genet Genomics 37(6):371-379, 2010. https://doi.org/10.1016/S1673-8527(09)60055-2
  26. Li, X., Luo, X., Lu, X., Duan, J., Xu, G. Metabolomics Study of Diabetic Retinopathy Using Gas Chromatography-Mass Spectrometry: A Comparison of Stages and Subtypes Diagnosed by Western and Chinese Medicine. Mol Biosyst 7(7):2228-2237, 2011. https://doi.org/10.1039/c0mb00341g
  27. Lu, X., Xiong, Z., Li, J., Zheng, S., Huo, T., Li, F. Metabonomic Study on 'Kidney-Yang Deficiency Syndrome' and Intervention Effects of Rhizoma Drynariae Extracts in Rats Using Ultra Performance Liquid Chromatography Coupled with Mass Spectrometry. Talanta. 83(3):700-708, 2011. https://doi.org/10.1016/j.talanta.2010.09.026
  28. Wang, P., Sun, H., Lv, H., Sun, W., Yuan, Y., Han, Y., Wang, D., Zhang, A., Wang, X. Thyroxine and Reserpine-Induced Changes in Metabolic Profiles of Rat Urine and the Therapeutic Effect of Liu Wei Di Huang Wan Detected by UPLC-HDMS. J Pharm Biomed Anal 53(3):631-645, 2010. https://doi.org/10.1016/j.jpba.2010.04.032
  29. Jiang, N., Liu, H.F., Li, S.D., Zhou, W.X., Zhang, Y.X., Zhang, Q., Yan, X.Z. An Integrated Metabonomic and Proteomic Study on Kidney-Yin Deficiency Syndrome Patients with Diabetes Mellitus in China. Acta pharmacol Sin 36(6):689-698, 2015. https://doi.org/10.1038/aps.2014.169
  30. Li, Q.Y., Guo, Z.Z., Liang, J., Zhang, W., Xu, L.M., Gao, Y.Q., Wang, X.S., Xue, D.Y., Su, S.B. Interleukin-10 Genotype Correlated to Deficiency Syndrome in Hepatitis B Cirrhosis. Evid Based Complement Alternat Med 2012: 298925, 2012.
  31. Song, Y.N., Zhang, H., Guan, Y., Peng, J.H., Lu, Y.Y., Hu, Y.Y., Su, S.B. Classification of Traditional Chinese Medicine Syndromes in Patients with Chronic Hepatitis B by SELDI-Based ProteinChip Analysis. Evid Based Complement Alternat Med 2012: 626320, 2012.
  32. Wu, T., Yang, M., Wei, H.F., He, S.H., Wang, S.C., Ji, G. Application of metabolomics in traditional chinese medicine differentiation of deficiency and excess syndromes in patients with diabetes mellitus. Evid Based Complement Alternat Med 2012: 968083, 2012.
  33. Sun, S., Dai, J., Wang, W., Cao, H., Fang, J., Hu, Y.Y., Su, S., Zhang, Y. Metabonomic Evaluation of ZHENG Differentiation and Treatment by Fuzhenghuayu Tablet in Hepatitis-B-Caused Cirrhosis. Evid Based Complement Alternat Med 2012: 453503, 2012.
  34. Zhao, L., Wan, L., Qiu, X., Li, R., Liu, S., Wang, D. A Metabonomics Profiling Study on Phlegm Syndrome and Blood-Stasis Syndrome in Coronary Heart Disease Patients Using Liquid Chromatography/Quadrupole Time-of-Flight Mass Spectrometry. Evid Based Complement Alternat Med 2014: 385102, 2014.
  35. Guan, Y., Zhang, H., Zhang, W., Su, S.B. Analysis of differential gene expression profile in peripheral blood of patients with chronic hepatitis B and syndromes of dual deficiency of liver and kidney yin and accumulation of dampness heat. J Chinese Integr Med 10(7):751-756, 2012. https://doi.org/10.3736/jcim20120705
  36. Wang, Y.Q., Li, F.F., Wang, W.J., Zhao, L.Y., Guo, L., Wang, H.F. Serum proteomics study of chronic gastritis with dampness syndrome in traditional Chinese medicine. J Chinese Integr Med 5(5):514-516, 2007. https://doi.org/10.3736/jcim20070507
  37. Kim, S.W., Hwang, D.G., Choi, Y.K., Lee, H.S., Park, D.H., Lee, S.S., Kim, G.W., Lee, S.G., Lee, S.J. Improvement of Pulse Diagnostic Apparatus with Array Sensor of Magnetic Tunneling Junctions. J Appl Phys 99(8):08R908, 2006. https://doi.org/10.1063/1.2177388
  38. Ryu, H.H., Lee, H.J., Jang, E.S., Choi, S.M., Lee, S.G., Lee, S. Study on Development of Cold-Heat Pattern Questionnaire. J Physiol Pathol Korean Med 22(6):1410-1415, 2008.
  39. Dai, J., Fang, J., Sun, S., Chen, Q., Cao, H., Zheng, N., Zhang, Y., Lu, A. ZHENG-Omics Application in ZHENG Classification and Treatment: Chinese Personalized Medicine. Evid-Based Compl Alt 2013: 235969, 2013.
  40. Group E-bmw. Evidence-based medicine. A new approach to teaching the practice of medicine. JAMA. 268(17):2420-2425, 1992 https://doi.org/10.1001/jama.1992.03490170092032
  41. Jain, K. Textbook of personalized medicine. 2nd, editor. New York, USA: Springer; 2009.
  42. Ginsburg, G.S., McCarthy, J.J. Personalized medicine: revolutionizing drug discovery and patient care. Trends in biotechnology. 19(12):491-496, 2001 https://doi.org/10.1016/S0167-7799(01)01814-5
  43. The Precision Medicine Initiative Working Group. The Precision Medicine Initiative Cohort Program -Building a Research Foundation for 21st Century Medicine. Maryland, USA. National Institutes of Health pp 6-7, 2015.
  44. Kim, W.,H. Principles of Korean Medicine. Seoul, Korea, Seongbosa. pp 31-34, 2007.

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