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

30 October 2023

Summary

Symptom-associated proteins form modules in the protein In this study, we develop a network medicine framework that interactome theorizes the scientific basis of TCM as the topological relationship Connecting TCM to the modern biomedical literature is challeng- between symptom-associated proteins and herb targets on the ing, due to the absence of the concept of “disease” in TCM. [...] We discover that gap, we propose the use of symptom phenotypes to characterize proteins associated with a symptom tend to cluster into a local PPI the indications and effects of TCM and study the PPI pattern of module, and the network proximity between an herb’s targets and a symptoms. [...] The third column is the network proximity z score; the fourth column is the number of patients in the case/control group after propensity score matching; the fifth and sixth are the recovery rates of the case group and the control group; the last column is the P value for the recovery rate difference, from a chi-square test. [...] Network proximity distance and z score Metrics Given that T, the set of herb targets, and s, the set of symptom-as- LCC and LCC z score sociated proteins, denote dist(t0, s0) as the shortest path length We characterize the localization of a node set in the network with between nodes t0 ∈ T and s0 ∈ s in the network, we define the the z score of the node set’s largest connected component (LCC) netw. [...] We first compute the size of the LCC formed by the node tance d” in the main text) as the average distance over targets to set, and then compare the observed LCC size against the random their closest symptom-associated protein (17): expectation generated from simulations preserving the degree of X the nodes (17).

Pages
16
Published in
United States of America
CCNR
Center for Complex Network Research