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. 2010 Dec 1;70(16):1729-38.
doi: 10.1002/pros.21208.

Prostate cancer risk-associated variants reported from genome-wide association studies: meta-analysis and their contribution to genetic Variation

Seong-Tae Kim  1 , Yu Cheng, Fang-Chi Hsu, Tao Jin, A Karim Kader, S Lilly Zheng, William B Isaacs, Jianfeng Xu, Jielin Sun
Affiliations

Prostate cancer risk-associated variants reported from genome-wide association studies: meta-analysis and their contribution to genetic Variation

Seong-Tae Kim et al. Prostate. .

Abstract

Background: Genome-wide association studies (GWAS) have led to the discovery of multiple single nucleotide polymorphisms (SNPs) that are associated with prostate cancer (PCa) risk. These SNPs may potentially be used for risk prediction. To date, there is not a stable estimate of their effect on PCa risk and their contribution to the genetic variation both of which are important for future risk prediction.

Methods: A literature review was conducted to identify SNPs associated with PCa risk with the following criteria: (1) GWAS in the Caucasian population; (2) SNPs with P-value <1.0×10(-6); and (3) one SNP from each independent LD block. A meta-analysis was performed to estimate combined odds ratio (OR) and its 95% confidence interval (CI) for the identified SNPs. The proportion of total genetic variance that is attributable by each of these SNPs was also estimated.

Results: Thirty PCa risk-associated SNPs were identified. These SNPs had OR estimates between 1.12 and 1.47 except for marker rs16901979 (OR=1.80). Significant heterogeneity in OR estimates was found among different studies for 13 SNPs. The proportion of total genetic variance attributed by each SNP ranged between 0.2% and 0.9%. These 30 SNPs explained ∼13.5% of the total genetic variance of PCa risk in the Caucasian population.

Conclusion: This study provides more stable OR estimates for PCa risk-associated SNPs, which is an important baseline for the effect of these SNPs in risk prediction. These SNPs explain a considerable proportion of genetic variance, however, the majority of genetic variance has yet to be explained.

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Figures

Figure 1
Figure 1
a Forest plots of selected PCa risk associated SNPs. Pooled is the result of meta-analysis. b Forest plots of selected PCa risk associated SNPs. Pooled is the result of meta-analysis.
Figure 1
Figure 1
a Forest plots of selected PCa risk associated SNPs. Pooled is the result of meta-analysis. b Forest plots of selected PCa risk associated SNPs. Pooled is the result of meta-analysis.
See this image and copyright information in PMC

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