Study links TCM with effects on protein networks

The framework, validated with hospital patient data, is among the first to provide a scientific foundation to evaluate the therapeutic efficacy of TCM herbs.In contrast to the western world's targeted personalised medicine approach, TCM provides an empirical holistic approach to medicine - thus can widen medical understanding of disease

TCM is a traditional treatment approach, based in ancient Chinese practices, that uses a variety of personalized herbal remedies and methods to treat ailments. TCM approaches are often considered pseudoscientific because researchers have been unable to explain its effects scientifically. Some studies have investigated the effectiveness of single TCM herbs or prescriptions for treating specific symptoms, but researchers had yet to develop a framework to evaluate their effectiveness more generally.

Now, Xiao Gan and colleagues from Central European University at Budapestassessed how a variety of herbs commonly used in TCM interact with human proteins. The researchers used symptom-gene association data containing 11,362 diseases, 13,271 genes, and 110,407 associations to derive relationships between proteins targeted by TCM herbs and proteins associated with symptoms such as fever, insomnia, and poor appetite. They mapped these symptom-associated genes onto 18,505 human proteins, almost all human proteins, and 327,924 protein-protein interactions and found that symptoms that frequently coincide, such as fever and diarrhea, neighbored each other in the human protein interaction network.

Moreover, TCM herbs that target proteins in these protein “neighborhoods” could treat those general symptoms. They validated the findings using clinical records of 1,936 in-patients who were prescribed herbal remedies in a TCM hospital. “In contrast to existing network pharmacology approaches, which often assume that herb/drug targets must directly target diseases/symptoms, our whole-interactome approach is more general, as we have observed that herbs/drugs can be effective even if they act on the appropriate network neighborhood,” Gan and Albert-László Barabási write in Science Advances (doi: 10.1126/sciadv.adh0215).

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