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Deciphering Potential Correlations between New Biomarkers and Pattern Classification in Chinese Medicine by Bioinformatics: Two Examples of Rheumatoid Arthritis

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Abstract

Biological complexity and the need for personalized medicine means that biomarker development has become increasingly challenging. Thus, new paradigms for research need to be created that bring together a different classifier of individuals. One potential solution is collaboration between biomarker development and Chinese medicine pattern classification. In this article, two examples of rheumatoid arthritis are discussed, including a new biomarker candidate casein kinase 2 interacting protein 1 (CKIP-1) and a micro RNA 214. The authors obtained a “snapshot” of pattern classification with disease in biomarker identification. Bioinformatics analyses revealed underlying biological functions of two biomarker candidates, in varying degrees, are correlated with Chinese medicine pattern of rheumatoid arthritis. The authors’ initial attempt can provide a new window for studying the win-win potential correlation between the biomarkers and pattern classification in Chinese medicine.

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References

  1. Trusheim MR, Berndt ER, Douglas FL. Stratified medicine: strategic and economic implications of combining drugs and clinical biomarkers. Nat Rev Drug Discov 2007;6:287–293.

    Article  CAS  Google Scholar 

  2. Freidlin B, McShane LM, Korn EL. Randomized clinical trials with biomarkers: design issues. J Natl Cancer Inst 2010;102:152–160.

    Article  CAS  Google Scholar 

  3. Roukos DH. Next-generation, genome sequencing-based biomarkers: concerns and challenges for medical practice. Biomark Med 2010;4:583–586.

    Article  Google Scholar 

  4. Wagner PD, Verma M, Srivastava S. Challenges for biomarkers in cancer detection. Ann NY Acad Sci 2004;1022:9–16.

    Article  CAS  Google Scholar 

  5. Mandrekar SJ, Sargent DJ. Clinical trial designs for predictive biomarker validation: theoretical considerations and practical challenges. J Clin Oncol 2009;27:4027–4034.

    Article  Google Scholar 

  6. Bensalah K, Montorsi F, Shariat SF. Challenges of cancer biomarker profiling. Eur Urol 2007;52:1601–1609.

    Article  Google Scholar 

  7. Zhang C, Jiang M, Zhang G, Bian ZX, Lu AP. Progress and perspectives of biomarker discovery in Chinese medicine research. Chin J Integr Med 2014;20:1–9.

    Google Scholar 

  8. Jiang M, Lu C, Zhang C, Yang J, Tan Y, Lu A, et al. Syndrome differentiation in modern research of traditional Chinese medicine. J Ethnopharmacol 2012;140:634–642.

    Article  Google Scholar 

  9. Lu A, Jiang M, Zhang C, Chan K. An integrative approach of linking traditional Chinese medicine pattern classification and biomedicine diagnosis. J Ethnopharmacol 2012;141:549–556.

    Article  Google Scholar 

  10. Zhang C, Zhang G, Chen KJ, Lu AP. Integration of Chinese medicine with Western medicine could lead to future medicine: molecular module medicine. Chin J Integr Med 2016;22:243–250.

    Article  Google Scholar 

  11. Jiang M, Yang J, Zhang C, Liu B, Chan K, Cao H, et al. Clinical studies with traditional Chinese medicine in the past decade and future research and development. Planta Med 2010;76:2048–2064.

    Article  CAS  Google Scholar 

  12. Zhang C, Jiang M, He XJ, Lu AP. Clinical trials of integrative medicine for rheumatoid arthritis: Issues and recommendations. Chin J Integr Med 2015;21:403–407.

    Article  CAS  Google Scholar 

  13. Jiang M, Zha Q, Zhang C, Lu C, Yan X, Zhu W, et al. Predicting and verifying outcome of Tripterygium wilfordii Hook F. based therapy in rheumatoid arthritis: from open to double-blinded randomized trial. Sci Reports 2015;5:9700.

    CAS  Google Scholar 

  14. Lu C, Niu X, Xiao C, Chen G, Zha Q, Guo H, et al. Networkbased gene expression biomarkers for cold and heat patterns of rheumatoid arthritis in traditional Chinese medicine. Evid Based Complement Alternat Med 2012;2012:203043.

    PubMed  PubMed Central  Google Scholar 

  15. Guo B, Zhang B, Zheng L, Tang T, Liu J, Wu H, et al. Therapeutic RNA interference targeting CKIP-1 with a cross-species sequence to stimulate bone formation. Bone 2014;59:76–88.

    Article  CAS  Google Scholar 

  16. Li D, Liu J, Guo B, Liang C, Dang L, Lu C, et al. Osteoclastderived exosomal miR-214-3p inhibits osteoblastic bone formation. Nat Commun 2016;7:10872.

    Article  CAS  Google Scholar 

  17. Wang X, Guo B, Li Q, Peng J, Yang Z, Wang A, et al. miR-214 targets ATF4 to inhibit bone formation. Nat Med 2013;19:93–100.

    Article  CAS  Google Scholar 

  18. Zhao L, Xiao C, Yan X, Wang J, Zhang Y, Li Q, et al. Correlation between heat or cold syndrome and cytokine, and laboratory index in women with early rheumatoid arthritis. Acta Univ Tradit Med Sinens Pharmacol Shanghai (Chin) 2006;20:21–24.

    CAS  Google Scholar 

  19. Sun Y, Zhong Q, Yao X, Liang S, Liu J, Xie K. A meta analysis on the correlation between cold syndrome, heat syndrome and inlfammation index in patients with rheumatoid arthritis. Rheunat Arthrit 2016;5:27–31.

    Google Scholar 

  20. Maciocia G. Diagnosis in Chinese medicine: A comprehensive guide. New York: Churchill Livingstone; 2003:27–28.

    Google Scholar 

  21. Tang JL. Research priorities in traditional Chinese medicine. BMJ 2006;333:391–394.

    Article  Google Scholar 

  22. Zheng G, Guo H, Guo Y, He X, Li Z, Lu A. Two dimensions data slicing algorithm, a new approach in mining rules of literature in traditional Chinese medicine. Communications Computer Inform Sci 2011;237:161–174.

    Article  Google Scholar 

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Correspondence to Ai-ping Lu.

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Supported by the National Natural Science Foundation of China (No. 81503449, 81673773)

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Zhang, C., Li, L., Zhang, G. et al. Deciphering Potential Correlations between New Biomarkers and Pattern Classification in Chinese Medicine by Bioinformatics: Two Examples of Rheumatoid Arthritis. Chin. J. Integr. Med. 27, 465–469 (2021). https://doi.org/10.1007/s11655-018-2571-8

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  • DOI: https://doi.org/10.1007/s11655-018-2571-8

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