DESCRIPTION:

List of positional candidate genes after correcting for multiple testing and controlling the false discovery rate from genome wide association studies (GWAS) retrieved from the NHGRI-EBI Catalog of published genome-wide association studies (http://www.ebi.ac.uk/gwas/). The disease/trait examined in this study, as reported by the authors, was Prostate cancer (gene x gene interaction). The EFO term prostate carcinoma was annotated to this set after curation by NHGRI-EBI. Intergenic SNPS were mapped to both the upstream and downstream gene. P-value uploaded. This gene set was generated using gwas2gs v. 0.1.8 and the GWAS Catalog v. 1.0.1.

LABEL:

GWAS: prostate carcinoma

SCORE TYPE:

P-Value

DATE ADDED:

2017-05-02

DATE UPDATED:

2020-05-06

SPECIES:

AUTHORS:

S Tao, Z Wang, J Feng, FC Hsu, G Jin, ST Kim, Z Zhang, H Gronberg, LS Zheng, WB Isaacs, J Xu, J Sun

TITLE:

A genome-wide search for loci interacting with known prostate cancer risk-associated genetic variants.

JOURNAL:

Carcinogenesis Mar 2012, Vol 33, pp. 598-603

ABSTRACT:

Genome-wide association studies (GWAS) have identified ∼30 single-nucleotide polymorphisms (SNPs) consistently associated with prostate cancer (PCa) risk. To test the hypothesis that other sequence variants in the genome may interact with those 32 known PCa risk-associated SNPs identified from GWAS to affect PCa risk, we performed a systematic evaluation among three existing PCa GWAS populations: CAncer of the Prostate in Sweden population, a Johns Hopkins Hospital population, and the Cancer Genetic Markers of Susceptibility population, with a total sample size of 4723 PCa cases and 4792 control subjects. Meta-analysis of the interaction term between each of those 32 SNPs and SNPs in the genome was performed in three PCa GWAS populations. The most significant interaction detected was between rs12418451 in MYEOV and rs784411 in CEP152, with a P(interaction) of 1.15 × 10(-7) in the meta-analysis. In addition, we emphasized two pairs of interactions with potential biological implication, including an interaction between rs7127900 near insulin-like growth factor-2 (IGF2)/IGF2AS and rs12628051 in TNRC6B, with a P(interaction) of 3.39 × 10(-6) and an interaction between rs7679763 near TET2 and rs290258 in SYK, with a P(interaction) of 1.49 × 10(-6). Those results show statistical evidence for novel loci interacting with known risk-associated SNPs to modify PCa risk. The interacting loci identified provide hints on the underlying molecular mechanism of the associations with PCa risk for the known risk-associated SNPs. Additional studies are warranted to further confirm the interaction effects detected in this study. PUBMED: 22219177
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