Evidence map›Paper›PMID 23483893›Full record

ArticlePloS one2013

The identification of pathway markers in intracranial aneurysm using genome-wide association data from two different populations.

Burcu Bakir-Gungor, Osman Ugur Sezerman

Abstract read
In one paragraph

Article in PloS one, 2013. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. 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

2 authors.

Burcu Bakir-GungorDepartment of Genetics and Bioinformatics, Faculty of Arts and Sciences, Bahcesehir University, Istanbul, Turkey. burcu.gungor@bahcesehir.edu.tr
Osman Ugur Sezerman

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

The identification of significant individual factors causing complex diseases is challenging in genome-wide association studies (GWAS) since each factor has only a modest effect on the disease development mechanism. In this study, we hypothesize that the biological pathways that are targeted by these individual factors show higher conservation within and across populations. To test this hypothesis, we searched for the disease related pathways on two intracranial aneurysm GWAS in European and Japanese case-control cohorts. Even though there were a few significantly conserved SNPs within and between populations, seven of the top ten affected pathways were found significant in both populations. The probability of random occurrence of such an event is 2.44E-36. We therefore claim that even though each individual has a unique combination of factors involved in the mechanism of disease development, most targeted pathways that need to be altered by these factors are, for the most part, the same. These pathways can serve as disease markers. Individuals, for example, can be scanned for factors affecting the genes in marker pathways. Hence, individual factors of disease development can be determined; and this knowledge can be exploited for drug development and personalized therapeutic applications. Here, we discuss the potential avenues of pathway markers in medicine and their translation to preventive and individualized health care.

Indexed as

Genetic Predisposition to DiseaseGenome-Wide Association StudyAsian PeopleBiomarkersCalcium SignalingGenetics, PopulationHumansIntracranial AneurysmMAP Kinase Signaling SystemPolymorphism, Single NucleotideSignal TransductionTransforming Growth Factor betaWhite PeopleBiomarkersTransforming Growth Factor beta

Identifiers

PMID23483893
PMCPMC3590201

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.