Evidence map›Paper›PMID 22549411›Full record

ArticleEuropean journal of human genetics : EJHG2012

Community of protein complexes impacts disease association.

Qianghu Wang, Weisha Liu, Shangwei Ning, Jingrun Ye, Teng Huang, Yan Li, Peng Wang, Hongbo Shi, Xia Li

Abstract read
In one paragraph

Article in European journal of human genetics : EJHG, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing papers in PubMed
–field-weighted citation impact
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

13 citing papers in PubMed.

  1. Article
  2. Exploring novel disease-disease associations based on multi-view fusion network.Computational and structural biotechnology journal · 2023
    Article
  3. Article
  4. Article
  5. Article
  6. Reforming disease classification system-are we there yet?Annals of translational medicine · 2018
    Article
  7. Review
  8. Article
  9. Article
  10. Article
  11. Review
  12. Article
  13. 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

9 authors.

Qianghu WangCollege of Bioinformatics Science and Technology and Bio-pharmaceutical Key Laboratory of Heilongjiang Province, Harbin Medical University, Harbin, China.
Weisha Liu
Shangwei Ning
Jingrun Ye
Teng Huang
Yan Li
Peng Wang
Hongbo Shi
Xia Li

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

One important challenge in the post-genomic era is uncovering the relationships among distinct pathophenotypes by using molecular signatures. Given the complex functional interdependencies between cellular components, a disease is seldom the consequence of a defect in a single gene product, instead reflecting the perturbations of a group of closely related gene products that carry out specific functions together. Therefore, it is meaningful to explore how the community of protein complexes impacts disease associations. Here, by integrating a large amount of information from protein complexes and the cellular basis of diseases, we built a human disease network in which two diseases are linked if they share common disease-related protein complex. A systemic analysis revealed that linked disease pairs exhibit higher comorbidity than those that have no links, and that the stronger association two diseases have based on protein complexes, the higher comorbidity they are prone to display. Moreover, more connected diseases tend to be malignant, which have high prevalence. We provide novel disease associations that cannot be identified through previous analysis. These findings will potentially provide biologists and clinicians new insights into the etiology, classification and treatment of diseases.

Indexed as

DiseaseGenetic Association StudiesGenome, HumanHumansMultiprotein ComplexesMultiprotein Complexes

Identifiers

PMID22549411
PMCPMC3476714

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

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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.