| Analysis of 60 Reported Glioma Risk SNPs Replicates Published GWAS Findings but Fails to Replicate Associations From Published Candidate-Gene Studies. | |
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MedLine Citation:
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PMID: 23280628 Owner: NLM Status: Publisher |
Abstract/OtherAbstract:
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Genomewide association studies (GWAS) and candidate-gene studies have implicated single-nucleotide polymorphisms (SNPs) in at least 45 different genes as putative glioma risk factors. Attempts to validate these associations have yielded variable results and few genetic risk factors have been consistently replicated. We conducted a case-control study of Caucasian glioma cases and controls from the University of California San Francisco (810 cases, 512 controls) and the Mayo Clinic (852 cases, 789 controls) in an attempt to replicate previously reported genetic risk factors for glioma. Sixty SNPs selected from the literature (eight from GWAS and 52 from candidate-gene studies) were successfully genotyped on an Illumina custom genotyping panel. Eight SNPs in/near seven different genes (TERT, EGFR, CCDC26, CDKN2A, PHLDB1, RTEL1, TP53) were significantly associated with glioma risk in the combined dataset (P < 0.05), with all associations in the same direction as in previous reports. Several SNP associations showed considerable differences across histologic subtype. All eight successfully replicated associations were first identified by GWAS, although none of the putative risk SNPs from candidate-gene studies was associated in the full case-control sample (all P values > 0.05). Although several confirmed associations are located near genes long known to be involved in gliomagenesis (e.g., EGFR, CDKN2A, TP53), these associations were first discovered by the GWAS approach and are in noncoding regions. These results highlight that the deficiencies of the candidate-gene approach lay in selecting both appropriate genes and relevant SNPs within these genes. |
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Authors:
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Kyle M Walsh; Erik Anderson; Helen M Hansen; Paul A Decker; Matt L Kosel; Thomas Kollmeyer; Terri Rice; Shichun Zheng; Yuanyuan Xiao; Jeffrey S Chang; Lucie S McCoy; Paige M Bracci; Joe L Wiemels; Alexander R Pico; Ivan Smirnov; Daniel H Lachance; Hugues Sicotte; Jeanette E Eckel-Passow; John K Wiencke; Robert B Jenkins; Margaret R Wrensch |
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Publication Detail:
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Type: JOURNAL ARTICLE Date: 2012-12-31 |
Journal Detail:
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Title: Genetic epidemiology Volume: - ISSN: 1098-2272 ISO Abbreviation: Genet. Epidemiol. Publication Date: 2012 Dec |
Date Detail:
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Created Date: 2013-1-2 Completed Date: - Revised Date: - |
Medline Journal Info:
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Nlm Unique ID: 8411723 Medline TA: Genet Epidemiol Country: - |
Other Details:
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Languages: ENG Pagination: - Citation Subset: - |
Copyright Information:
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© 2012 Wiley-Liss, Inc. |
Affiliation:
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Department of Neurological Surgery, University of California, San Francisco, San Francisco, California; Program in Cancer Genetics, Helen Diller Family Comprehensive Cancer Center, University of California, San Francisco, San Francisco, California; Department of Epidemiology and Biostatistics, University of California, San Francisco, San Francisco, California. |
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From MEDLINE®/PubMed®, a database of the U.S. National Library of Medicine
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