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Updated: Apr 21, 2026

Microarray-based Identification of Individual HERV Loci Expression: Application to Biomarker Discovery in Prostate Cancer
Published on: November 2, 2013
Polymorphisms influencing prostate-specific antigen concentration may bias genome-wide association studies on
Paul J Dluzniewski1, Jianfeng Xu2, Ingo Ruczinski3
1Department of Epidemiology, Johns Hopkins Bloomberg School of Public Health, Baltimore, Maryland.
Background:
Genome-wide association studies (GWAS) have produced weak (OR = 1.1-1.5) but significant associations between single nucleotide polymorphisms (SNPs) and prostate cancer. However, these associations may be explained by detection bias caused by SNPs influencing PSA concentration. Thus, in a simulation study, we quantified the extent of bias in the association between a SNP and prostate cancer when the SNP influences PSA concentration.
Methods:
We generated 2,000 replicate cohorts of 20,000 men using real-world estimates of prostate cancer risk, prevalence of carrying ≥1 minor allele, PSA concentration, and the influence of a SNP on PSA concentration. We modeled risk ratios (RR) of 1.00, 1.25, and 1.50 for the association between carrying ≥1 minor allele and prostate cancer. We calculated mean betas from the replicate cohorts and quantified bias under each scenario.
Results:
Assuming no association between a SNP and prostate cancer, the estimated mean bias in betas ranged from 0.02 to 0.10 for ln PSA being 0.05 to 0.20 ng/mL higher in minor allele carriers; the mean biased RRs ranged from 1.03 to 1.11. Assuming true RRs = 1.25 and 1.50, the biased RRs were as large as 1.39 and 1.67, respectively.
Conclusion:
Estimates of the association between SNPs and prostate cancer can be biased to the magnitude observed in published GWAS, possibly resulting in type I error. However, large associations (RR > 1.10) may not fully be explained by this bias.
Impact:
The influence of SNPs on PSA concentration should be considered when interpreting results from GWAS on prostate cancer.

