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Eur J Hum Genet. 2014 Mar;22(3):402-8. doi: 10.1038/ejhg.2013.161. Epub 2013 Jul 24.

A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes.

Author information

1
Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland, USA.
2
Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
3
Department of Epidemiology, Rollins School of Public Health, Emory University, Atlanta, Georgia, USA.
4
University of Massachusetts Medical School, Graduate School of Biomedical Sciences, Clinical and Population Health Research Program, Worcester, Massachusetts, USA.
5
McKing Consulting Corporation, Atlanta, Georgia, USA.
6
1] Division of Cancer Control and Population Sciences, National Cancer Institute, Bethesda, Maryland, USA [2] Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.
7
Office of Public Health Genomics, Centers for Disease Control and Prevention, Atlanta, Georgia, USA.

Abstract

Candidate gene and genome-wide association studies (GWAS) represent two complementary approaches to uncovering genetic contributions to common diseases. We systematically reviewed the contributions of these approaches to our knowledge of genetic associations with cancer risk by analyzing the data in the Cancer Genome-wide Association and Meta Analyses database (Cancer GAMAdb). The database catalogs studies published since January 1, 2000, by study and cancer type. In all, we found that meta-analyses and pooled analyses of candidate genes reported 349 statistically significant associations and GWAS reported 269, for a total of 577 unique associations. Only 41 (7.1%) associations were reported in both candidate gene meta-analyses and GWAS, usually with similar effect sizes. When considering only noteworthy associations (defined as those with false-positive report probabilities≤0.2) and accounting for indirect overlap, we found 202 associations, with 27 of those appearing in both meta-analyses and GWAS. Our findings suggest that meta-analyses of well-conducted candidate gene studies may continue to add to our understanding of the genetic associations in the post-GWAS era.

PMID:
23881057
PMCID:
PMC3925284
DOI:
10.1038/ejhg.2013.161
[Indexed for MEDLINE]
Free PMC Article

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