Evidence map›Paper›PMID 23112813›Full record

ArticlePloS one2012

Characterizing the network of drugs and their affected metabolic subpathways.

Chunquan Li, Desi Shang, Yan Wang, Jing Li, Junwei Han, Shuyuan Wang, Qianlan Yao, Yingying Wang, Yunpeng Zhang, Chunlong Zhang and 3 more

Open access · goldAbstract read
In one paragraph

Article in PloS one, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
4.5field-weighted citation impact, top 5% 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

21 citing papers in PubMed, 38 citations in OpenAlex.

  1. Article
  2. Construction and Analysis of Human Diseases and Metabolites Network.Frontiers in bioengineering and biotechnology · 2020
    Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
  11. Article
  12. Article
  13. A subpathway-based method of drug reposition for polycystic ovary syndrome.Reproductive sciences (Thousand Oaks, Calif.) · 2015
    Article
  14. Article
  15. Article
  16. Article
  17. A sub-pathway based method to identify candidate drugs for glioblastomas.Medical oncology (Northwood, London, England) · 2014
    Article
  18. Review
  19. Article
  20. Article
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

13 authors at 1 institution in 1 country.

Chunquan LiCollege of Bioinformatics Science and Technology, Harbin Medical University, Harbin, People's Republic of China.
Desi Shang
Yan Wang
Jing Li
Junwei Han
Shuyuan Wang
Qianlan Yao
Yingying Wang
Yunpeng Zhang
Chunlong Zhang
Yanjun Xu
Wei Jiang
Xia Li
Harbin Medical University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

A fundamental issue in biology and medicine is illustration of the overall drug impact which is always the consequence of changes in local regions of metabolic pathways (subpathways). To gain insights into the global relationship between drugs and their affected metabolic subpathways, we constructed a drug-metabolic subpathway network (DRSN). This network included 3925 significant drug-metabolic subpathway associations representing drug dual effects. Through analyses based on network biology, we found that if drugs were linked to the same subpathways in the DRSN, they tended to share the same indications and side effects. Furthermore, if drugs shared more subpathways, they tended to share more side effects. We then calculated the association score by integrating drug-affected subpathways and disease-related subpathways to quantify the extent of the associations between each drug class and disease class. The results showed some close drug-disease associations such as sex hormone drugs and cancer suggesting drug dual effects. Surprisingly, most drugs displayed close associations with their side effects rather than their indications. To further investigate the mechanism of drug dual effects, we classified all the subpathways in the DRSN into therapeutic and non-therapeutic subpathways representing drug therapeutic effects and side effects. Compared to drug side effects, the therapeutic effects tended to work through tissue-specific genes and these genes tend to be expressed in the adrenal gland, liver and kidney; while drug side effects always occurred in the liver, bone marrow and trachea. Taken together, the DRSN could provide great insights into understanding the global relationship between drugs and metabolic subpathways.

Indexed as

Drug-Related Side Effects and Adverse ReactionsAdrenal GlandsBone MarrowGene Expression RegulationHumansKidneyLiverMetabolic Networks and PathwaysModels, BiologicalPharmacologyTrachea

Identifiers

PMID23112813
PMCPMC3480395
OpenAlexW1976907771

What OpenQuestion holds

Textmetadata
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.