A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes
dc.contributor.author | Chang, Christine Q. | |
dc.contributor.author | Yesupriya, Ajay | |
dc.contributor.author | Rowell, Jessica L. | |
dc.contributor.author | Pimentel, Camilla B. | |
dc.contributor.author | Clyne, Melinda | |
dc.contributor.author | Gwinn, Marta | |
dc.contributor.author | Khoury, Muin J. | |
dc.contributor.author | Wulf, Anja | |
dc.contributor.author | Schully, Sheri D. | |
dc.date | 2022-08-11T08:08:30.000 | |
dc.date.accessioned | 2022-08-23T15:57:28Z | |
dc.date.available | 2022-08-23T15:57:28Z | |
dc.date.issued | 2014-03-01 | |
dc.date.submitted | 2014-10-24 | |
dc.identifier.citation | Eur J Hum Genet. 2014 Mar;22(3):402-8. doi: 10.1038/ejhg.2013.161. <a href="http://dx.doi.org/10.1038/ejhg.2013.161">Link to article on publisher's site</a> | |
dc.identifier.issn | 1018-4813 (Linking) | |
dc.identifier.doi | 10.1038/ejhg.2013.161 | |
dc.identifier.pmid | 23881057 | |
dc.identifier.uri | http://hdl.handle.net/20.500.14038/30204 | |
dc.description.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 | |
dc.language.iso | en_US | |
dc.relation | <a href="http://www.ncbi.nlm.nih.gov/entrez/query.fcgi?db=pubmed&cmd=Retrieve&list_uids=23881057&dopt=Abstract">Link to Article in PubMed</a> | |
dc.relation.url | http://dx.doi.org/10.1038/ejhg.2013.161 | |
dc.subject | Case-Control Studies | |
dc.subject | *Genome-Wide Association Study | |
dc.subject | Humans | |
dc.subject | Neoplasms | |
dc.subject | Cancer Biology | |
dc.subject | Genomics | |
dc.subject | Molecular Genetics | |
dc.subject | Neoplasms | |
dc.title | A systematic review of cancer GWAS and candidate gene meta-analyses reveals limited overlap but similar effect sizes | |
dc.type | Journal Article | |
dc.source.journaltitle | European journal of human genetics : EJHG | |
dc.source.volume | 22 | |
dc.source.issue | 3 | |
dc.identifier.legacycoverpage | https://escholarship.umassmed.edu/faculty_pubs/450 | |
dc.identifier.contextkey | 6282104 | |
html.description.abstract | <p>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</p> | |
dc.identifier.submissionpath | faculty_pubs/450 | |
dc.contributor.department | Graduate School of Biomedical Sciences, Clinical and Population Health Research Program | |
dc.source.pages | 402-8 |