Contribution of Genome-Wide Association Studies to ... [PLoS One. 2012] - PubMed - NCBI

Contribution of Genome-Wide Association Studies to ... [PLoS One. 2012] - PubMed - NCBI

PLoS One. 2012;7(12):e51408. doi: 10.1371/journal.pone.0051408. Epub 2012 Dec 11.

Contribution of Genome-Wide Association Studies to Scientific Research: A Bibliometric Survey of the Citation Impacts of GWAS and Candidate Gene Studies Published during the Same Period and in the Same Journals.

Mansiaux Y, Carrat F.

Source

Epidemiology, Information System, Modeling, UMR-S 707, University Paris 6-UPMC, Paris, France ; Inserm U707, Paris, France.

Abstract

In genetic epidemiology, genome-wide association studies (GWAS) are used to rapidly scan a large set of genetic variants and thus to identify associations with a particular trait or disease. The GWAS philosophy is different to that of conventional candidate-gene-based approaches, which directly test the effects of genetic variants of potentially contributory genes in an association study. One controversial question is whether GWAS provide relevant scientific outcomes by comparison with candidate-gene studies. We thus performed a bibliometric study using two citation metrics to assess whether the GWAS have contributed a capital gain in knowledge discovery by comparison with candidate-gene approaches. We selected GWAS published between 2005 and 2009 and matched them with candidate-gene studies on the same topic and published in the same period of time. We observed that the GWAS papers have received, on average, 30±55 citations more than the candidate gene papers, 1 year after their publication date, and 39±58 citations more 2 years after their publication date. The GWAS papers were, on average, 2.8±2.4 and 2.9±2.4 times more cited than expected, 1 and 2 years after their publication date; whereas the candidate gene papers were 1.5±1.2 and 1.5±1.4 times more cited than expected. While the evaluation of the contribution to scientific research through citation metrics may be challenged, it cannot be denied that GWAS are great hypothesis generators, and are a powerful complement to candidate gene studies.

PMID:

23240019

[PubMed - in process]

PMCID:

PMC3519865

Free PMC Article