Skip to main content

Advertisement

SpringerLink
Log in

Text Mining of Rheumatoid Arthritis and Diabetes Mellitus to Understand the Mechanisms of Chinese Medicine in Different Diseases with Same Treatment

  • Thinking and Methodology
  • Published:
Chinese Journal of Integrative Medicine Aims and scope Submit manuscript

Abstract

Objective

To identify the commonalities between rheumatoid arthritis (RA) and diabetes mellitus (DM) to understand the mechanisms of Chinese medicine (CM) in different diseases with the same treatment.

Methods

A text mining approach was adopted to analyze the commonalities between RA and DM according to CM and biological elements. The major commonalities were subsequently verified in RA and DM rat models, in which herbal formula for the treatment of both RA and DM identified via text mining was used as the intervention.

Results

Similarities were identified between RA and DM regarding the CM approach used for diagnosis and treatment, as well as the networks of biological activities affected by each disease, including the involvement of adhesion molecules, oxidative stress, cytokines, T-lymphocytes, apoptosis, and inflammation. The Ramulus Cinnamomi-Radix Paeoniae Alba-Rhizoma Anemarrhenae is an herbal combination used to treat RA and DM. This formula demonstrated similar effects on oxidative stress and inflammation in rats with collagen-induced arthritis, which supports the text mining results regarding the commonalities between RA and DM.

Conclusion

Commonalities between the biological activities involved in RA and DM were identified through text mining, and both RA and DM might be responsive to the same intervention at a specific stage.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  1. Eisenberg DM, Kaptchuk TJ, Laine C, Davidoff F. Complementary and alternative medicine—an annals series. Ann Intern Med 2001;135:208.

    Article  PubMed  CAS  Google Scholar 

  2. Lu AP, Jia HW, Xiao C, Lu QP. Theory of traditional Chinese medicine and therapeutic method of diseases. World J Gastroenterol 2004;10:1854–1856.

    Article  PubMed  PubMed Central  Google Scholar 

  3. Lu AP, Li S. Principle and application of Chinese medicine syndrome differentiation and disease classification. Chin J Integr Tradit West Med (Chin) 2010;30:84–86.

    Google Scholar 

  4. Jiang M, Xiao C, Chen G, Lu C, Zha Q, Yan X, et al. Correlation between cold and hot pattern in traditional Chinese medicine and gene expression profiles in rheumatoid arthritis. Front Med 2011;5:219–228.

    Article  PubMed  Google Scholar 

  5. Lu C, Zha Q, Chang A, He Y, Lu A. Pattern differentiation in traditional Chinese medicine can help define specific indications for biomedical therapy in the treatment of rheumatoid arthritis. J Altern Complement Med 2009;15:1021–1025.

    Article  PubMed  Google Scholar 

  6. Zheng G, Jiang M, He X, Zhao J, Guo H, Chen G, et al. Discrete derivative: a data slicing algorithm for exploration of sharing biological networks between rheumatoid arthritis and coronary heart disease. BioData Min 2011;4:18.

    Article  PubMed  PubMed Central  Google Scholar 

  7. Harmston N, Filsell W, Stumpf MP. What the papers say: text mining for genomics and systems biology. Human Genomics 2010;5:17–29.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  8. Wasko MC, Kay J, Hsia EC, Rahman MU. Diabetes mellitus and insulin resistance in patients with rheumatoid arthritis: risk reduction in a chronic inflammatory disease. Arthritis Care Res 2011;63:512–521.

    Article  CAS  Google Scholar 

  9. Liu YS. New usage of Zhibai Dihuang Pill. Gansu J Chin Med (Chin) 2010;23:11–12.

    CAS  Google Scholar 

  10. Berry M, Castellanos M, eds. Survey of text mining?. London: Springer Verlag; 2008:21–22.

    Book  Google Scholar 

  11. Agarwal P, Searls DB. Literature mining in support of drug discovery. Brief Bioinf 2008;9:479–492.

    Article  CAS  Google Scholar 

  12. Hopkins AL. Network pharmacology: the next paradigm in drug discovery. Nat Chem Biol 2008;4:682–690.

    Article  PubMed  CAS  Google Scholar 

  13. Li S, Zhang B, Zhang N. Network target for screening synergistic drug combinations with application to traditional Chinese medicine. BMC Syst Biol 2011;5(Suppl 1):S10.

    Article  PubMed  PubMed Central  Google Scholar 

  14. Xiao C, Li J, Dong X, He X, Niu X, Liu C, et al. Antioxidative and TNF-alpha suppressive activities of puerarin derivative (4AC) in RAW264.7 cells and collagen-induced arthritic rats. Eur J Pharm 2011;666:242–250.

    Article  CAS  Google Scholar 

  15. Reed MJ, Meszaros K, Entes LJ, Claypool MD, Pinkett JG, Gadbois TM, et al. A new rat model of type 2 diabetes: the fat-fed, streptozotocin-treated rat. Metabolism 2000;49:1390–1394.

    Article  PubMed  CAS  Google Scholar 

  16. Lu AP, Chen KJ. Pondering on syndrome differentiation of diseases. Chin J Integr Tradit West Med (Chin) 2005;25:843–845.

    CAS  Google Scholar 

  17. Gan XJ. Aplication of different diseases with same treatment in blood disease. J Emerg Tradit Chin Med (Chin) 2010;19:795.

    Google Scholar 

  18. Wang D, Shang XL. Prevention and control on the geriatrics with Liuwei Dihuang Pill. Chin J Gerontol (Chin) 2011;31:524–527.

    CAS  Google Scholar 

  19. Graf S, Schumm-Draeger PM. Diabetes and rheumatism: is diabetes mellitus also an inflammatory disease? Z Rheumatol 2011;70:747–751.

    Article  PubMed  CAS  Google Scholar 

  20. Li S, Zhang B, Jiang D, Wei YY, Zhang NB. Herb network construction and co-module analysis for uncovering the combination rule of traditional Chinese herbal formulae. BMC Bioinf 2010;11(Suppl 11):S6.

    Article  Google Scholar 

  21. Zaremba S, Ramos-Santacruz M, Hampton T, Shetty P, Fedorko J, Whitmore J, et al. Text-mining of PubMed abstracts by natural language processing to create a public knowledge base on molecular mechanisms of bacterial enteropathogens. BMC Bioinf 2009;10:177.

    Article  Google Scholar 

  22. Cohen AM, Hersh WR. A survey of current work in biomedical text mining. Brief Bioinf 2005;6:57–71.

    Article  CAS  Google Scholar 

  23. Angelotti F, Parma A, Cafaro G, Capecchi R, Alunno A, Puxeddu I. One year in review 2017: pathogenesis of rheumatoid arthritis. Clin Exp Rheumatol 2017;35:368–378.

    PubMed  Google Scholar 

  24. Xia C, Rao X, Zhong J. Role of T lymphocytes in type 2 diabetes and diabetes-associated inflammation. J Diabetes Res 2017;2017:6494795.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  25. Arend WP. Physiology of cytokine pathways in rheumatoid arthritis. Arthrit Rheum 2001;45:101–106.

    Article  CAS  Google Scholar 

  26. Hata H, Sakaguchi N, Yoshitomi H, Iwakura Y, Sekikawa K, Azuma Y, et al. Distinct contribution of IL-6, TNF-alpha, IL-1, and IL-10 to T cell-mediated spontaneous autoimmune arthritis in mice. J Clin Invest 2004;114:582–588.

    Article  PubMed  PubMed Central  CAS  Google Scholar 

  27. King GL. The role of inflammatory cytokines in diabetes and its complications. J Periodontol 2008;79:1527–1534.

    Article  PubMed  CAS  Google Scholar 

  28. Cardellini M, Perego L, D’Adamo M, Marini MA, Procopio C, Hribal ML, et al. C-174G polymorphism in the promoter of the interleukin-6 gene is associated with insulin resistance. Diabetes Care 2005;28:2007–2012.

    Article  PubMed  CAS  Google Scholar 

  29. Arroul-Lammali A, Rahal F, Chetouane R, Djeraba Z, Medjeber O, Ladjouze-Rezig A, et al. Ex vivo all-trans retinoic acid modulates NO production and regulates IL-6 effect during rheumatoid arthritis: a study in Algerian patients. Immunopharmacol Immunotoxicol 2017;39:87–96.

    Article  PubMed  CAS  Google Scholar 

  30. Kumar S, Singh RK, Bhardwaj TR. Therapeutic role of nitric oxide as emerging molecule. Biomed Pharmacother 2017;85:182–201.

    Article  PubMed  CAS  Google Scholar 

  31. Baier A, Meineckel I, Gay S, Pap T. Apoptosis in rheumatoid arthritis. Curr Opin Rheumatol 2003;15:274–279.

    Article  PubMed  CAS  Google Scholar 

  32. Pap T, Muller-Ladner U, Gay RE, Gay S. Fibroblast biology. Role of synovial fibroblasts in the pathogenesis of rheumatoid arthritis. Arthritis Res 2000;2:361–367.

    PubMed  CAS  Google Scholar 

  33. Davidson SM, Duchen MR. Endothelial mitochondria: contributing to vascular function and disease. Circ Res 2007;100:1128–1141.

    Article  PubMed  CAS  Google Scholar 

  34. Visser H. Early diagnosis of rheumatoid arthritis. Best Pract Res Clin Rheumatol 2005;19:55–72.

    Article  PubMed  Google Scholar 

  35. Lee YH, Bae SC. Intercellular adhesion molecule-1 polymorphisms, K469E and G261R and susceptibility to vasculitis and rheumatoid arthritis: a meta-analysis. Cell Mol Biol 2016;62:84–90.

    PubMed  CAS  Google Scholar 

  36. McMurray RW. Adhesion molecules in autoimmune disease. Semin Arthrit Rheum 1996;25:215–233.

    Article  CAS  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Institute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China

    Ning Zhao, Cheng Lu, Miao Jiang, Chi Zhang & Hong-tao Guo

  2. School of Information Science and Engineering, Lanzhou University, Lanzhou, 730000, China

    Guang Zheng

  3. School of Basic Medical Sciences, Beijing University of Chinese Medicine, Beijing, 100029, China

    Jian Li

  4. Institute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, 100700, China

    Hong-yan Zhao

  5. School of Chinese Medicine, Hong Kong Baptist University, Hong Kong SAR, China

    Ai-ping Lu

Authors
  1. Ning Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Guang Zheng
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jian Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Hong-yan Zhao
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Cheng Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Miao Jiang
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Chi Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. Hong-tao Guo
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Ai-ping Lu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ai-ping Lu.

Additional information

Supported by the National Natural Science Foundation of China (No. 81573845, 81473367, 81403209, 30825047), China Academy of Chinese Medical Sciences Project (No. Z0412), and Beijing Nova Program (No. xx2014B073)

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Zhao, N., Zheng, G., Li, J. et al. Text Mining of Rheumatoid Arthritis and Diabetes Mellitus to Understand the Mechanisms of Chinese Medicine in Different Diseases with Same Treatment. Chin. J. Integr. Med. 24, 777–784 (2018). https://doi.org/10.1007/s11655-018-2825-x

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s11655-018-2825-x

Keywords

Search

Navigation