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

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 frame...

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Autores principales: Gan, Xiao, Shu, Zixin, Wang, Xinyan, Yan, Dengying, Li, Jun, Ofaim, Shany, Albert, Réka, Li, Xiaodong, Liu, Baoyan, Zhou, Xuezhong, Barabási, Albert-László
Formato: Online Artículo Texto
Lenguaje:English
Publicado: American Association for the Advancement of Science 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610911/
https://www.ncbi.nlm.nih.gov/pubmed/37889962
http://dx.doi.org/10.1126/sciadv.adh0215
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author Gan, Xiao
Shu, Zixin
Wang, Xinyan
Yan, Dengying
Li, Jun
Ofaim, Shany
Albert, Réka
Li, Xiaodong
Liu, Baoyan
Zhou, Xuezhong
Barabási, Albert-László
author_facet Gan, Xiao
Shu, Zixin
Wang, Xinyan
Yan, Dengying
Li, Jun
Ofaim, Shany
Albert, Réka
Li, Xiaodong
Liu, Baoyan
Zhou, Xuezhong
Barabási, Albert-László
author_sort Gan, Xiao
collection PubMed
description 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.
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spelling pubmed-106109112023-10-28 Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine Gan, Xiao Shu, Zixin Wang, Xinyan Yan, Dengying Li, Jun Ofaim, Shany Albert, Réka Li, Xiaodong Liu, Baoyan Zhou, Xuezhong Barabási, Albert-László Sci Adv Social and Interdisciplinary Sciences 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. American Association for the Advancement of Science 2023-10-27 /pmc/articles/PMC10610911/ /pubmed/37889962 http://dx.doi.org/10.1126/sciadv.adh0215 Text en Copyright © 2023 The Authors, some rights reserved; exclusive licensee American Association for the Advancement of Science. No claim to original U.S. Government Works. Distributed under a Creative Commons Attribution NonCommercial License 4.0 (CC BY-NC). https://creativecommons.org/licenses/by-nc/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution-NonCommercial license (https://creativecommons.org/licenses/by-nc/4.0/) , which permits use, distribution, and reproduction in any medium, so long as the resultant use is not for commercial advantage and provided the original work is properly cited.
spellingShingle Social and Interdisciplinary Sciences
Gan, Xiao
Shu, Zixin
Wang, Xinyan
Yan, Dengying
Li, Jun
Ofaim, Shany
Albert, Réka
Li, Xiaodong
Liu, Baoyan
Zhou, Xuezhong
Barabási, Albert-László
Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine
title Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine
title_full Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine
title_fullStr Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine
title_full_unstemmed Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine
title_short Network medicine framework reveals generic herb-symptom effectiveness of traditional Chinese medicine
title_sort network medicine framework reveals generic herb-symptom effectiveness of traditional chinese medicine
topic Social and Interdisciplinary Sciences
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10610911/
https://www.ncbi.nlm.nih.gov/pubmed/37889962
http://dx.doi.org/10.1126/sciadv.adh0215
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