Evidence map›Paper›PMID 30405409›Full record

ArticleFrontiers in pharmacology2018

Systems-Mapping of Herbal Effects on Complex Diseases Using the Network-Perturbation Signatures.

Xuetong Chen, Chunli Zheng, Chun Wang, Zihu Guo, Shuo Gao, Zhangchi Ning, Chao Huang, Cheng Lu, Yingxue Fu, Daogang Guan and 2 more

Open access · goldAbstract read
In one paragraph

Article in Frontiers in pharmacology, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers.

0numbers the graph read from it
0cells of the map it votes in
5citing papers in PubMed
0.9field-weighted citation impact, top 23% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

5 citing papers in PubMed, 9 citations in OpenAlex.

  1. Review
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  4. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

12 authors at 3 institutions in 2 countries.

Xuetong ChenCenter of Bioinformatics, College of Life Science, Northwest A & F University, Yangling, China.
Chunli ZhengCenter of Bioinformatics, College of Life Science, Northwest A & F University, Yangling, China.
Chun WangSchool of Chinese Medicine, Institute of Integrated Bioinformedicine and Translational Science, Hong Kong Baptist University, Hong Kong, Hong Kong.
Zihu GuoCenter of Bioinformatics, College of Life Science, Northwest A & F University, Yangling, China.
Shuo GaoCenter of Bioinformatics, College of Life Science, Northwest A & F University, Yangling, China.
Zhangchi NingInstitute of Basic Theory for Chinese Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Chao HuangCenter of Bioinformatics, College of Life Science, Northwest A & F University, Yangling, China.
Cheng LuInstitute of Basic Research in Clinical Medicine, China Academy of Chinese Medical Sciences, Beijing, China.
Yingxue FuCenter of Bioinformatics, College of Life Science, Northwest A & F University, Yangling, China.
Daogang GuanSchool of Chinese Medicine, Institute of Integrated Bioinformedicine and Translational Science, Hong Kong Baptist University, Hong Kong, Hong Kong.
Aiping LuSchool of Chinese Medicine, Institute of Integrated Bioinformedicine and Translational Science, Hong Kong Baptist University, Hong Kong, Hong Kong.
Yonghua WangCenter of Bioinformatics, College of Life Science, Northwest A & F University, Yangling, China.
Northwest A&F University · CNChinese Academy of Medical Sciences & Peking Union Medical College · CNHong Kong Baptist University · HK

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The herbs have proven to hold great potential to improve people's health and wellness during clinical practice over the past millennia. However, herbal medicine for the personalized treatment of disease is still under investigation owing to the complex multi-component interactions in herbs. To reveal the valuable insights for herbal synergistic therapy, we have chosen Traditional Chinese Medicine (TCM) as a case to illustrate the art and science behind the complicated multi-molecular, multi-genes interaction systems, and how the good practices of herbal combination therapy are applicable to personalized treatment. Here, we design system-wide interaction map strategy to provide a generic solution to establish the links between diseases and herbs based on comprehensive testing of molecular signatures in herb-disease pairs. Firstly, we integrated gene expression profiles from 189 diseases to characterize the disease-pathological feature. Then, we generated the perturbation signatures from the huge chemical informatics data and pharmacological data for each herb, which were represented the targets affected by the ingredients in the herb. So that we could assess the effects of herbs on the individual. Finally, we integrated the data of 189 diseases and 502 herbs, yielding the optimal herbal combinations for the diseases based on the strategy, and verifying the reliability of the strategy through the permutation testing and literature verification. Furthermore, we propose a novel formula as a candidate therapeutic drugs of rheumatoid arthritis and demonstrate its therapeutic mechanism through the systematic analysis of the influencing targets and biological processes. Overall, this computational method provides a systematic approach, which blended herbal medicine and omics data sets, allowing for the development of novel drug combinations for complex human diseases.

Indexed as

herbal medicinesmathematical modelingnetwork pharmacologypersonalized medicineperturbation signaturessystems pharmacology

Identifiers

PMID30405409
PMCPMC6201628
OpenAlexW2892965372

What OpenQuestion holds

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LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.