Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine

Author:

Gan Xiao12345ORCID,Shu Zixin6ORCID,Wang Xinyan6ORCID,Yan Dengying6ORCID,Li Jun7ORCID,Ofaim Shany2ORCID,Albert Réka45ORCID,Li Xiaodong78ORCID,Liu Baoyan9ORCID,Zhou Xuezhong6ORCID,Barabási Albert-László210ORCID

Affiliation:

1. Institute for AI in Medicine, School of Artificial Intelligence, Nanjing University of Information Science and Technology, Nanjing 210044, China.

2. Network Science Institute, Northeastern University, Boston, MA 02115, USA.

3. Channing Division of Network Medicine, Department of Medicine, Brigham and Women’s Hospital, Harvard Medical School, Boston, MA 02115, USA.

4. Department of Physics, Pennsylvania State University, University Park, PA 16802, USA.

5. Department of Biology, Pennsylvania State University, University Park, PA 16802, USA.

6. Institute of Medical Intelligence, School of Computer and Information Technology, Beijing Jiaotong University, Beijing 100063, China.

7. Hubei University of Chinese Medicine, Wuhan 430065, China.

8. Hubei Provincial Hospital of Traditional Chinese Medicine (Affiliated Hospital of Hubei University of Traditional Chinese Medicine, Hubei Academy of Chinese Medicine, Wuhan 430061, China.

9. China Academy of Chinese Medical Sciences, Beijing 100700, China.

10. Department of Network and Data Science, Central European University, Budapest 1051, Hungary.

Abstract

Understanding natural and traditional medicine can lead to world-changing drug discoveries. Despite the therapeutic effectiveness of individual herbs, traditional Chinese medicine (TCM) lacks a scientific foundation and is often considered a myth. In this study, we establish a network medicine framework and reveal the general TCM treatment principle as the topological relationship between disease symptoms and TCM herb targets on the human protein interactome. We find that proteins associated with a symptom form a network module, and the network proximity of an herb’s targets to a symptom module is predictive of the herb’s effectiveness in treating the symptom. These findings are validated using patient data from a hospital. We highlight the translational value of our framework by predicting herb-symptom treatments with therapeutic potential. Our network medicine framework reveals the scientific foundation of TCM and establishes a paradigm for understanding the molecular basis of natural medicine and predicting disease treatments.

Publisher

American Association for the Advancement of Science (AAAS)

Subject

Multidisciplinary

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