Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa.

Prostate cancer is the most frequently diagnosed cancer in males in developed countries. To identify common prostate cancer susceptibility alleles, we genotyped 211,155 SNPs on a custom Illumina array (iCOGS) in blood DNA from 25,074 prostate cancer cases and 24,272 controls from the international PRACTICAL Consortium. Twenty-three new prostate cancer susceptibility loci were identified at genome-wide significance (P < 5 × 10−8). More than 70 prostate cancer susceptibility loci, explaining ~30% of the familial risk for this disease, have now been identified. On the basis of combined risks conferred by the new and previously known risk loci, the top 1% of the risk distribution has a 4.7-fold higher risk than the average of the population being profiled. These results will facilitate population risk stratification for clinical studies.

Genome-wide association studies (GWAS) have identified 76 variants associated with prostate cancer risk predominantly in populations of European ancestry. To identify additional susceptibility loci for this common cancer, we conducted a meta-analysis of >10 million SNPs in 43,303prostate cancer cases and 43,737 controls from studies in populations of European, African, Japanese and Latino ancestry. Twenty-three novel susceptibility loci were revealed at P<5×10-8; 15 variants were identified among men of European ancestry, 7 from multiethnic analyses and one was associated with early-onset prostate cancer. These 23 variants, in combination with the known prostate cancer risk variants, explain 33% of the familial risk of the disease in European ancestry populations. These findings provide new regions for investigation into the pathogenesis of prostate cancer and demonstrate the utility of combining ancestrally diverse populations to discover risk loci for disease.

Prostate cancer is a highly heritable disease with large disparities in incidence rates across ancestry populations. We conducted a multiancestry meta-analysis of prostate cancer genome-wide association studies (107,247 cases and 127,006 controls) and identified 86 new genetic risk variants independently associated with prostate cancer risk, bringing the total to 269 known risk variants. The top genetic risk score (GRS) decile was associated with odds ratios that ranged from 5.06 [95% confidence interval (CI) 4.84–5.29] for men of European ancestry to 3.74 [95% CI 3.36–4.17] for men of African ancestry. Men of African ancestry were estimated to have a mean GRS that was 2.18-times higher [95% CI 2.14–2.22], and men of East Asian ancestry 0.73-times lower [95% CI 0.71–0.76], than men of European ancestry. These findings support the role of germline variation contributing to population differences in prostate cancer risk, with the GRS offering an approach for personalized risk prediction.

Prostate cancer (PrCa) is the most frequently diagnosed male cancer in developed countries. To identify common PrCa susceptibility alleles, we have previously conducted a genome-wide association study in which 541, 129 SNPs were genotyped in 1,854 PrCa cases with clinically detected disease and 1,894 controls. We have now evaluated promising associations in a second stage, in which we genotyped 43,671 SNPs in 3,650 PrCa cases and 3,940 controls, and a third stage, involving an additional 16,229 cases and 14,821 controls from 21 studies. In addition to previously identified loci, we identified a further seven new prostate cancer susceptibility loci on chromosomes 2, 4, 8, 11, and 22 (P=1.6×10 −8 to P=2.7×10 −33 ).Genome-wide association studies (GWAS) provide a powerful approach to identify common disease alleles. We previously conducted a GWAS 1 , based on genotyping of 541, 129 SNPs in 1,854 clinically detected PrCa cases and 1,894 controls (see Figure 1, stage 1). Follow-up genotyping of SNPs exhibiting strong evidence of association (P<10 −6 ), in a further 3,268 cases and 3,366 controls, allowed us to identify SNPs at 7 susceptibility loci associated with the disease at genome-wide levels of significance 1 . Other studies have identified an additional 8 loci [2][3][4][5][6][7][8][9] . These loci, however, explain only a small fraction of the familial risk of PrCa. Moreover, the strength of the associations that have been detected are generally small (perallele odds ratios, OR, 1.1-1.2), and the power of the existing studies to detect many of the susceptibility alleles has been limited. It is highly likely, therefore, that other PrCa predisposition loci exist, and that such loci should be detectable by studies with larger sample sizes.In an attempt to identify further susceptibility loci, we conducted a more extensive follow-up of SNPs showing evidence of association in stage 1 of our GWAS. We designed a panel of 47,120 SNPs, aiming to include all SNPs with a significant association in stage 1 at P-trend (1df)<.05 or P(2df)<.01 (see Online Methods). These SNPs were genotyped using the Illumina iSELECT platform in 3,894 PrCa cases and 4,055 controls from the United Kingdom (UK) and Australia ( Figure 1, stage 2). After quality control (QC) exclusions (as described in Online Methods), we utilised data from 43,671 SNPs in 3,650 PrCa cases and 3,940 controls. NIH-PA Author ManuscriptNIH-PA Author Manuscript NIH-PA Author ManuscriptGenotype frequencies in cases and controls were compared using a 1 degree of freedom (df) Cochran-Armitage trend test (for QQ plots see Supplementary Figure 1). There was little evidence of inflation in the test statistics in the UK samples (estimated inflation factor λ=1.08), but there was more marked inflation in those from Australia (λ=1.23; λ=1.19 for stage 2 overall), suggestive of some population substructure. The Australian samples were selected from three studies (MCCS, RFPCS and EOPCS; see Supplementary Note for cohort descriptions), and further analysis revealed that ...