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. Author manuscript; available in PMC: 2015 May 1.
Published in final edited form as: Hum Genet. 2013 Nov 2;133(5):509–521. doi: 10.1007/s00439-013-1387-z

A genome-wide association study of prostate cancer in West African men

Michael B Cook 1,*, Zhaoming Wang 1,2,*, Edward D Yeboah 3,4,*, Yao Tettey 3,4, Richard B Biritwum 3,4, Andrew A Adjei 3,4, Evelyn Tay 3,4, Ann Truelove 5, Shelley Niwa 5, Charles C Chung 1, Annand P Chokkalingam 6, Lisa W Chu 7, Meredith Yeager 1,2, Amy Hutchinson 1,2, Kai Yu 1, Kristin A Rand 8, Christopher A Haiman 8; African Ancestry Prostate Cancer GWAS Consortium, Robert N Hoover 1, Ann W Hsing 6,9,#, Stephen J Chanock 1,#
PMCID: PMC3988225  NIHMSID: NIHMS537226  PMID: 24185611

Abstract

Background

Age-adjusted mortality rates for prostate cancer are higher for African American men compared with those of European ancestry. Recent data suggest that West African men also have elevated risk for prostate cancer relative to European men. Genetic susceptibility to prostate cancer could account for part of this difference.

Methods

We conducted a genome-wide association study (GWAS) of prostate cancer in West African men in the Ghana Prostate Study. Association testing was performed using multivariable logistic regression adjusted for age and genetic ancestry for 474 prostate cancer cases and 458 population-based controls on the Illumina HumanOmni-5 Quad BeadChip.

Results

The most promising association was at 10p14 within an intron of a long non-coding RNA (lncRNA RP11-543F8.2) 360 kb centromeric of GATA3 (p=1.29E−7). In sub-analyses, SNPs at 5q31.3 were associated with high Gleason score (≥7) cancers, the strongest of which was a missense SNP in PCDHA1 (rs34575154, p=3.66E−8), and SNPs at Xq28 (rs985081, p=8.66E−9) and 6q21 (rs2185710, p=5.95E−8) were associated with low Gleason score (<7) cancers. We sought to validate our findings in silico in the African Ancestry Prostate Cancer GWAS Consortium, but only one SNP, at 10p14, replicated at p<0.05. Of the 90 prostate cancer loci reported from studies of men of European, Asian or African American ancestry, we were able to test 81 in the Ghana Prostate Study, and 10 of these replicated at p<0.05.

Conclusion

Further genetic studies of prostate cancer in West African men are needed to confirm our promising susceptibility loci.

Keywords: prostate cancer, Africa, GWAS, case-control

Introduction

In the United States, age-adjusted incidence rates of prostate cancer in African-Americans are two-fold higher than those observed in men of European ancestry (Li et al. 2012). Although age-adjusted estimates of prostate cancer from African cancer registries suggest lower rates for African men (Center et al. 2012; Chu et al. 2011), international comparisons are complicated by population screening, overdiagnosis (Welch and Black 2010), and incomplete cancer registration (Parkin et al. 2010). Despite their challenges, mortality statistics (Ferlay et al. 2010) can provide a stable and robust cancer statistic (Welch and Black 2010), particularly for international comparisons. Age-adjusted mortality rates of prostate cancer show a pattern distinct from that of incidence (Center et al. 2012; Rebbeck et al. 2013), with equal or higher rates in Africa—and specifically, the West African region—compared with North America or Western Europe. Since West Africa is the principal ancestral origin of a substantial proportion of African-American men (Bryc et al. 2010; Torres et al. 2012), one may hypothesize that genetic susceptibility loci that vary in allele frequency by ancestral population could account for part of the observed differences in prostate cancer rates within the United States (US).

Recent genome-wide association studies (GWAS) have shown that genetic variants associated with prostate cancer—such as those at 8q24 (Amundadottir et al. 2006; Freedman et al. 2006; Haiman et al. 2007) and 17q21 (Haiman et al. 2011b)—are more common among African Americans compared with men of European ancestry. Whether the differences in susceptibility allele frequencies can partially explain differences in incidence across regions can best be answered by discovery of a larger fraction of the set of common variants associated with risk. To date, approximately 90 independent prostate cancer loci have been identified through GWAS, primarily in men of European background. Based on empiric analyses of existing data sets, it is estimated that these loci represent perhaps less than the total number of common variants, which could be even higher in men of African ancestry (Park et al. 2010). To investigate genetic susceptibility to prostate cancer in West Africa, we conducted a GWAS in the Ghana Prostate Study, a collaboration involving the US National Cancer Institute (NCI) and the University of Ghana.

Methods

Study Participants

Participants for analysis were recruited through the Ghana Prostate Study—a population-based component, and a clinical component. The population-based component was a probability sample designed using the 2000 Ghana Population and Housing Census data in an attempt to recruit approximately 1,000 men aged 50–74 years in the Greater Accra region (~3 million people) (Chokkalingam et al. 2012), which successfully recruited 1,037 healthy men between 2004 and 2006 with a response percentage of 98.8% (Chokkalingam et al. 2012). Consented individuals underwent an in-person interview, and within seven days had a digital rectal examination (DRE) and provided an over-night fasting blood sample for prostate specific antigen (PSA) testing, biomarker assays, and genetic analysis. Subjects who had a positive screen by PSA (>2.5 ng/ml) or DRE underwent a transrectal ultrasound-guided biopsy. A total of 73 histologically-confirmed prostate cancer cases were identified through the population-based screening component of the Ghana Prostate Study and are included in the case population analyzed herein. From the remaining 964 screen-negative individuals, 836 had at least 20 ug DNA extracted and available for analysis, and 500 of these were matched to cases for analysis by age (in 5 year categories).

In the Ghana Prostate Study, we recruited 676 prostate cancer cases at Korle Bu Teaching Hospital in Accra, Ghana between 2008 and 2012. All consented cases were interviewed and provided an overnight fasting blood sample. At the time of selection for this analysis we had recruited 582 prostate cancer cases, from which we selected 427 for analysis. Combined with the 73 cases diagnosed through the population-based component of the study, this yielded 500 available prostate cancer cases for analysis. Five technical replicates for each of three individuals served as quality control (QC) samples.

This Ghana Prostate Study was approved by institutional review boards in Ghana and at the National Cancer Institute.

Genotyping and Quality Control

DNA samples for this project were extracted from buffy coat samples using the Qiagen method according to the manufacturer’s instructions. Pre-genotyping quality control metrics excluded six case samples and two controls. 494 prostate cancer cases, 498 screen-negative controls, plus 15 distinct quality control samples were genotyped on the Illumina HumanOmni5-Quad BeadChip (Clarke et al. 2012).

The initial overall completion rate of genotype calls was 97.38%. After excluding 57,489 loci with no genotype call, the overall completion rate increased to 98.70%. A total of 70,872 loci were excluded due to low completion rates (<90%) and 1,393,418 single nucleotide polymorphisms (SNP) monomorphic in men from Ghana were further excluded. We advanced 2,837,019 SNPs for association analysis. For the quality control samples, which included three distinct samples each with five technical replicates, the concordance rate exceeded 99.99%. Twenty-seven (7 cases, 20 controls) samples were excluded due to low completion rate (lower than 94%) or extreme mean heterozygosity (lower than 13.5% or greater than 16.5%). A further five cases were excluded for having less than 80% African ancestry using the HapMap build 26 data (CEU, JPT+CHB, YRI) as the continental reference populations in a STRUCTURE analysis (Engelhardt and Stephens 2010). Principal components analysis (PCA) identified 16 individuals (five cases, 11 controls) with significant deviation of eigenvectors and thus, they were excluded (Reich et al. 2008). Finally, unexpected relatedness (1st–2nd degree), assessed using the GLU qc.ibds module (http://code.google.com/p/glu-genetics/) with an IBD0 threshold of 0.70, was detected for 11 pairs of full-sibling and one monozygotic twin; one individual randomly chosen from each related group was retained while two cases and nine controls were excluded. Note that one nuclear family involved three individuals and accounted for three related pairs, so, a total of 11 individuals were removed. In addition, one case sample was excluded due to incomplete phenotype with missing age. The final analytic data set included 474 prostate cancer cases and 458 screen-negative controls.

Statistical Analysis

Association tests for prostate cancer susceptibility were performed using multivariable unconditional logistic regression analyses (1 degree-of-freedom) adjusted for age and two eigenvectors (p<0.01 based on the null model) identified in PCA analysis. In addition, we stratified the analysis by Gleason score (≤6, ≥7). Follow-up analyses were conducted in the African Ancestry Prostate Cancer GWAS Consortium using a total 5,096 cases and 4,972 controls (Haiman et al. 2011a; Haiman et al. 2011b). Additional resources used for the analyses were dbSNP (Sherry et al. 2001), 1000 Genomes Project (Clarke et al. 2012), GENCODE (Harrow et al. 2012), HaploReg (Ward and Kellis 2012), RegulomeDB (Boyle et al. 2012), and Haploview 4.2 (Barrett et al. 2005).

Results

The results of the scan are shown in Table 1, which displays the 30 most promising SNPs associated with prostate cancer in the Ghana Prostate Study. Notable is a new locus marked by rs7918885 at 10p14 for prostate cancer risk (p value of 1.29E−7). Figure 1 depicts the eight correlated markers typed as part of our study, which are approximately 360 kb 5’ of GATA3; notably they localize to an intronic region of lncRNA gene RP11-543F8.2. Assessment of the correlated variants in 1000 Genomes Project data, restricted to the West African populations, did not reveal notable variants in the coding or splicing regions of the lncRNA RP11-543F8.2 (Supplementary Figure 1). Bioinformatic analyses of the eight correlated SNPs using the ENCODE resources point towards motif changes, DNase I hypersensitivity sites, and NHEK enhancer histone marks, but there was no overall significant enrichment for such elements (2012). Visual inspection of a quantile-quantile plot of the observed versus expected p values (Supplementary Figure 2), as well as the inflation factor of 1.01, indicated an absence of any systemic bias (e.g., residual population stratification). The results of the initial scan also suggested promising signals at 5q31.3, 3p26.1, and 8p23.2. Twenty-nine of our top 30 SNPs were analyzed in the African Ancestry Prostate Cancer GWAS Consortium; 12 SNPs were directly typed and 17 SNPs imputed using 1000 Genomes Project data (Clarke et al. 2012) (Supplementary Table 1). Only one of the 29 tested SNPs were statistically significant (p < 0.05) in the African American dataset, and that was rs2993385 located at 10p14.

Table 1.

The 30 most significant SNP associations with prostate cancer in the Ghana Prostate Study GWAS

rs Number Cytoband Location1 Alleles
(referent |
effect)		 Effect Allele
Frequency
(control |
case)		 Per Effect Allele
OR (95%CI)		 P value In gene(s) or nearest gene(s) if distance specified2
rs7918885 10p14 8474595 T | G 0.145 | 0.076 0.40 (0.28, 0.57) 1.29E-07 358kb 5' of GATA3, RP11-543F8.2 (intron)
rs10905371 10p14 8480044 A | G 0.142 | 0.074 0.41 (0.29, 0.58) 2.77E-07 363kb 5' of GATA3, RP11-543F8.2 (intron)
rs7896254 10p14 8486161 G | A 0.100 | 0.044 0.33 (0.21, 0.51) 3.27E-07 369kb 5' of GATA3, RP11-543F8.2 (intron)
rs10905374 10p14 8481486 G | A 0.145 | 0.077 0.42 (0.29, 0.59) 4.43E-07 364kb 5' of GATA3, RP11-543F8.2 (intron)
rs7096374 10p14 8484113 C | T 0.143 | 0.076 0.42 (0.30, 0.59) 5.16E-07 368kb 5' of GATA3, RP11-543F8.2 (intron)
rs61749035 5q31.3 140718750 G | T 0.037 | 0.077 3.22 (2.00, 5.19) 7.50E-07 PCDHGA1 (intron), PCDHGA2 (missense)
rs114246623 3p26.1 6935066 G | A 0.015 | 0.078 4.93 (2.53, 9.59) 7.70E-07 GRM7-AS2 (AC066606.1) (intron)
rs147739031 8p23.2 3247408 A | G 0.005 | 0.039 11.48 (3.78, 34.90) 9.96E-07 CSMD1 (intron)
rs115850745 6p21.32 32655508 A | G 0.371 | 0.265 0.56 (0.44, 0.71) 1.05E-06 19kb 3' of AL662789.1, 21kb 3' of HLA-DQB1
rs10961884 9p22.3 15111573 T | C 0.023 | 0.086 3.96 (2.23, 7.02) 1.11E-06 32kb 5' of U6.1033, 59kb 3' of TTC39B
rs115899206 6p21.2 40084864 A | G 0.015 | 0.052 4.91 (2.49, 9.68) 1.59E-06 154kb 3' of RP11-552E20.1, 183kb 3' of MOCS1
rs12477565 2q14.2 121081260 G | T 0.420 | 0.514 1.68 (1.35, 2.08) 2.25E-06 AC012363.13 (intron), 22kb 5' of INHBB
rs12251624 10p14 8479257 T | C 0.159 | 0.091 0.46 (0.33, 0.64) 2.62E-06 362kb 5' of GATA3, RP11-543F8.2 (intron)
rs7090925 10p14 8479868 A | G 0.159 | 0.091 0.46 (0.33, 0.64) 2.62E-06 363kb 5' of GATA3, RP11-543F8.2 (intron)
rs17097185 5q31.3 140711097 C | G 0.039 | 0.077 3.02 (1.88, 4.84) 2.70E-06 PCDHGA1 (missense)
rs114799364 1p36.13 18900554 C | T 0.073 | 0.038 0.33 (0.20, 0.53) 2.72E-06 57kb 5' of PAX7
rs4151685 5q31.3 140213805 A | C 0.044 | 0.089 2.80 (1.79, 4.38) 3.52E-06 PCDHA1, PCDHA2, PCDHA3, PCDHA4, PCDHA5, PCDHA6 (intron for all)
rs34575154 5q31.3 140166953 A | G 0.044 | 0.089 2.80 (1.79, 4.38) 3.56E-06 PCDHA1 (missense)
rs370971 20q13.12 42371095 G | A 0.428 | 0.518 1.65 (1.33, 2.04) 4.92E-06 15kb 3' of GTSF1L
rs6878145 5q31.3 140718552 A | G 0.039 | 0.076 2.94 (1.83, 4.73) 4.94E-06 PCDHGA1 (intron), PCDHGA2 (missense)
rs2993385 10p14 8462439 T | C 0.178 | 0.110 0.50 (0.37, 0.68) 5.94E-06 345kb 5' of GATA3, RP11-543F8.2 (intron)
rs1329536 6p12.3 47663326 C | T 0.051 | 0.096 2.54 (1.68, 3.84) 6.20E-06 GPR111 (UTR-3)
rs116776862 5q31.3 140177075 G | A 0.045 | 0.089 2.67 (1.72, 4.14) 6.86E-06 PCDHA1 (intron)
rs13432692 2p25.2 6085200 C | T 0.541 | 0.443 0.63 (0.51, 0.77) 7.02E-06 LOC150622 (AC073479.1) (intron)
rs75404762 13q12.3 30562130 T | C 0.015 | 0.043 4.49 (2.27, 8.90) 7.04E-06 38kb 5' of LOC440131 (RP11-90M5.1)
rs73146440 7q11.22 67865802 A | G 0.038 | 0.012 0.19 (0.09, 0.41) 7.53E-06 113kb 5' of RP5-945F2.3, 1.1Mb 5' of STAG3L4
rs285198 20q13.12 42364734 G | A 0.431 | 0.519 1.64 (1.32, 2.03) 7.87E-06 9.1kb 3' of GTSF1L, 19.4kb 3' of MYBL2
rs12057381 1p32.2 57769516 G | A 0.132 | 0.068 0.45 (0.31, 0.64) 8.44E-06 DAB1 (intron)
rs116679801 5q31.3 140711954 C | G 0.037 | 0.071 3.00 (1.83, 4.91) 8.49E-06 PCDHGA1 (missense)
rs2056150 2p24.3 14603290 G | A 0.321 | 0.405 1.70 (1.34, 2.15) 1.03E-05 62kb 5' of NCRNA00276, 170kb 5' of FAM84A
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1

Location is per GRCh37.p5.

2

Gene information curated from Haploreg, dbSNP, Ensembl, and GENCODE.

Figure 1. Association results, recombination plot and linkage disequilibrium structure for the 198.9kb region of 10p14.

Figure 1

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Association results from a trend test in –log10Pvalues (y axis, left) of the SNPs are shown according to their chromosomal positions (x axis). The r2 values were computed from rs7918885 to all of the other plotted SNPs to differentially size data points according to their level of linkage disequilibrium. SNPs that are highly correlated with rs7918885 (n=6) were colored red. Linkage disequilibrium structure based on controls (n=458) was visualized by snp.plotter software. The line graph shows likelihood ratio statistics (y axis, right) for recombination hotspot by SequenceLDhot software and 3 different colors represent 3 tests of 100 controls without resampling. Physical locations are based on NCBI Build 37 of the human genome. Gene annotation was based on ENCODE/GENCODE version 12 from the UCSC Genome Browser.

Results from a sub-analysis, stratified by Gleason score (<7, 136 cases; ≥7, 317 cases), are shown in Table 2. In the Gleason score ≥7 stratum, the 5q31.3 locus reached genome-wide statistical significance (5E−8) with the lowest p value being 3.66E−8 for rs34575154, a missense SNP in PCDHA1. In addition, SNPs at 22q13.31, 7q31.31 and 2q14.2 had p values less than E−7. In the Gleason score <7 stratum, seven loci were observed to have p values less than E−7, and two SNPs were below genome-wide statistical significance: rs985081 at Xq28 (p=8.66E−9) and rs2185710 at 6q21 (p=5.95E−8). We analyzed these SNPs stratified by Gleason score in the African Ancestry Prostate Cancer GWAS Consortium yet none of them replicated at p<0.05, although there was evidence for between-study heterogeneity of effect for several of these SNPs within the African American data (Haiman et al. 2011a; Haiman et al. 2011b).

Table 2.

The most promising SNP associations with prostate cancer stratified by Gleason score in the Ghana Prostate Study GWAS, with estimates also from the African Ancestry Prostate Cancer GWAS Consortium

Ghana Prostate Study African Ancestry Prostate Cancer GWAS Consortium
Gleason rs Number Cytoband Location Alleles
(referent |
effect)		 Effect Allele
Frequency
(control | case)		 Per Effect Allele
OR (95%CI)		 P value In gene(s) or nearest gene(s) if distance
specified		 Effect Allele
Frequency
(control | case)		 Per Effect Allele
OR (95%CI)		 P value P Het
Greater than or even to 7 rs34575154 5q31.3 140166953 A | G 0.044 | 0.098 3.79 (2.31, 6.20) 3.66E-08 PCDHA1 (missense) 0.048 | 0.050 1.05 (0.87, 1.27) 0.582 0.025
rs4151685 5q31.3 140213805 A | C 0.044 | 0.098 3.77 (2.30, 6.16) 4.02E-08 PCDHA1 (intron); PCDHA@ 0.045 | 0.047 1.06 (0.87, 1.28) 0.586 0.028
rs116776862 5q31.3 140177075 G | A 0.045 | 0.098 3.53 (2.18, 5.73) 9.07E-08 PCDHA1 (intron); PCDHA@ 0.048 | 0.050 1.04 (0.86, 1.26)* 0.675 0.028
rs7706544 5q31.3 140070148 C | T 0.051 | 0.104 3.34 (2.09, 5.34) 1.94E-07 HARS (intron) 0.052 | 0.054 1.04 (0.87, 1.25) 0.665 0.053
rs115338764 5q31.3 140041187 G | A 0.051 | 0.104 3.34 (2.09, 5.34) 1.98E-07 IK (intron) 0.051 | 0.054 1.04 (0.87, 1.25)* 0.660 0.053
rs61749035 5q31.3 140718750 G | T 0.037 | 0.084 3.82 (2.26, 6.47) 2.07E-07 PCDHGA2 (missense); PCDHA@ 0.045 | 0.047 1.10 (0.91, 1.34)* 0.339 0.022
rs6889768 5q31.3 139929877 T | G 0.039 | 0.085 3.70 (2.20, 6.24) 3.81E-07 SRA1 (3'UTR) 0.035 | 0.041 1.18 (0.95, 1.46) 0.134 0.196
rs6008813 22q13.31 46812585 G | A 0.389 | 0.490 1.90 (1.47, 2.44) 4.34E-07 CELSR1 (intron) 0.371 | 0.387 1.06 (0.97, 1.16)* 0.183 0.889
kgp22385671 5q31.3 140208753 A | G 0.044 | 0.092 3.59 (2.16, 5.97) 4.47E-07 PCDHA1 (intron); PCDHA@ 0.048 | 0.049 1.04 (0.86, 1.26)* 0.654 0.029
rs113425597 5q31.3 140187201 G | C 0.044 | 0.091 3.55 (2.13, 5.91) 6.36E-07 PCDHA1 (synonymous); PCDHA@ 0.048 | 0.050 1.04 (0.86, 1.26)* 0.675 0.028
rs12537079 7q31.31 117704706 T | G 0.146 | 0.071 0.35 (0.23, 0.53) 6.95E-07 61kb 5' of AC003084.2; 119kb 5' of NAA38 0.204 | 0.195 0.97 (0.87, 1.07) 0.540 0.818
rs6880234 5q31.3 140215956 C | G 0.044 | 0.092 3.53 (2.12, 5.88) 7.49E-07 PCDHA7 (missense); PCDHA@ 0.046 | 0.047 1.05 (0.87, 1.28)* 0.603 0.027
rs12477565 2q14.2 121081260 G | T 0.420 | 0.528 1.85 (1.44, 2.38) 8.18E-07 AC012363.13; 22kb 5' of INHBB 0.514 | 0.526 1.06 (0.97, 1.16)* 0.222 0.571
rs17097185 5q31.3 140711097 C | G 0.039 | 0.084 3.55 (2.10, 5.98) 8.41E-07 PCDHGA1 (missense) 0.045 | 0.047 1.10 (0.90, 1.33)* 0.342 0.022
rs17119623 5q31.3 139961837 T | C 0.050 | 0.101 3.17 (1.97, 5.10) 1.19E-06 APBB3; 13kb 5' of SLC35A4 0.047 | 0.049 1.04 (0.86, 1.26) 0.661 0.292
rs6878145 5q31.3 140718552 A | G 0.039 | 0.082 3.43 (2.03, 5.80) 1.93E-06 PCDHGA2 (missense); PCDHA@ 0.045 | 0.047 1.10 (0.91, 1.34)* 0.339 0.022
rs7715021 5q31.3 139941943 C | G 0.051 | 0.098 3.10 (1.92, 5.01) 2.09E-06 APBB3 (missense) 0.050 | 0.053 1.07 (0.89, 1.28)* 0.487 0.313
Less than 7 rs985081 Xq28 148538099 T | C 0.025 | 0.141 3.08 (2.01, 4.73) 8.66E-09 22kb 3' of IDS 0.070 | 0.082 1.08 (0.98, 1.20) 0.112 0.192
rs2185710 6q21 113377048 A | G 0.166 | 0.295 2.77 (1.89, 4.05) 5.95E-08 84kb 3' of U6 0.334 | 0.348 1.05 (0.97, 1.14)* 0.229 0.573
rs66504230 6q14.3 86871444 T | C 0.090 | 0.186 3.15 (2.01, 4.95) 1.77E-07 169kb 5' of U4 0.113 | 0.106 0.94 (0.84, 1.06)* 0.344 0.030
rs114918764 4q26 117370706 C | T 0.002 | 0.045 34.07 (6.45, 179.92) 3.65E-07 40kb 3' of RP11-55L3.1; 150kb 5' of MIR1973 0.002 | 0.002 0.93 (0.23, 3.70)* 0.915 0.280
rs73043340 3p22.3 33126972 C | T 0.007 | 0.042 12.04 (3.98, 36.46) 3.76E-07 GLB1 (intron) 0.085 | 0.085 0.98 (0.86, 1.13)* 0.819 0.455
rs62477096 7q31.33 124936442 A | G 0.178 | 0.283 2.45 (1.70, 3.53) 6.63E-07 RP11-3B12.2; 366kb 3' of POT1 0.196 | 0.194 0.99 (0.90, 1.09)* 0.814 0.619
rs6965492 7q31.33 124944982 G | T 0.179 | 0.286 2.49 (1.72, 3.61) 6.92E-07 RP11-3B12.2; 375kb 3' of POT1 0.191 | 0.190 1.00 (0.91, 1.09) 0.947 0.484
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*

Imputed using 1000 Genomes Project data

Lastly, in our prostate cancer GWAS of African men we were able to assess 81 of the previously reported 90 prostate cancer susceptibility loci (Table 3), and observed that 10 of these SNPs were statistically significant (p<0.05), including SNPs within “Region 1” (rs7017300, rs10090154) and “Region 2” (rs13254738, rs16901979) of the 8q24 region (Haiman et al. 2007), as well as rs7210100 from the 17q21 region which was initially reported by the African Ancestry Prostate Cancer GWAS Consortium (Haiman et al. 2011b). Other SNPs previously associated with prostate cancer, mostly in populations of European ancestry, did not replicate in our African population.

Table 3.

The association of previously reported prostate cancer susceptibility SNPs from European and Asian populations in relation to prostate cancer in African men.

SNP Cytoband Location1 Nearest Gene2 Study PMID(s) Study Population Ancestry Ghana SNP Location Reference |
Effect Alleles		 Case | Control
Effect Allele
Frequencies		 P value Per Allele
OR (95%CI)
rs1218582 1q21.3 154834183 KCNN3 (intron) 23535732 European rs1218582 154834183 G | A 0.31 | 0.33 0.12 0.84 (0.67, 1.05)
rs4245739 1q32.1 204518842 MDM4 (3'-URT) 23535732 European rs4245739 204518842 C | A 0.78 | 0.77 0.82 0.97 (0.76, 1.25)
rs10187424 2p11.2 85794297 VAMP8 (intronic); 5.6kb 3' of GGCX 21743467 European, Asian rs10187424 85794297 T | C 0.66 | 0.72 0.17 0.86 (0.68, 1.07)
rs721048 2p15 63131731 EHBP1 (intron) 18264098 European rs7210483 63131731 G | A 0.00 | 0.00 0.90 0.79 (0.02, 38.16)
rs1465618 2p21 43553949 THADA (intron) 19767753 European, Asian rs1465618 43553949 T | C 0.95 | 0.94 0.13 1.43 (0.90, 2.28)
rs11902236 2p25.1 10117868 GRHL1 (intron) 23535732 European rs11902236 10117868 C | T 0.65 | 0.69 0.31 0.89 (0.72, 1.11)
rs12621278 2q31.1 173311553 ITGA6 (intron) 19767753 European, African American, Asian - - - - - -
rs2292884 2q37.3 238443226 MLPH (missense) 21743057 European - - - - - -
rs3771570 2q37.3 242382864 FARP2 (intron) 23535732 European rs3771570 242382864 C | T 0.01 | 0.00 0.030 5.39 (1.17, 24.77)
rs7629490 3p11.2 87241497 34kb 3' of MIR4795 21743057 European rs7629490 87241497 C | T 0.17 | 0.21 0.12 0.81 (0.62, 1.06)
rs2055109 3p11.2 87467332 142kb 3' of POU1F1 22366784 Asian - - - - - -
rs2660753 3p12.1 87110674 70kb 3' of VGLL3 18264097 European - - - - - -
rs9284813 3p12.1 87152169 112kb 5' of VGLL3 20676098 Asian rs9284813 87152169 A | G 0.46 | 0.43 0.39 1.09 (0.89, 1.35)
rs17181170 3p12.1 87173324 102kb 3' of MIR4795 19767753 European, Asian rs17181170 87173324 G | A 0.12 | 0.16 0.031 0.72 (0.54, 0.97)
rs7611694 3q13.2 113275624 SIDT1 (intron) 23535732 European rs7611694 113275624 A | C 0.34 | 0.37 0.29 0.89 (0.71, 1.11)
rs10934853 3q21.3 128038373 EEFSEC (intron) 19767754 European rs10934853 128038373 C | A 0.82 | 0.80 0.53 1.09 (0.83, 1.42)
rs6763931 3q23 141102833 ZBTB38 (intron) 21743467 European rs6763931 141102833 G | A 0.91 | 0.90 0.019 1.53 (1.07, 2.18)
rs10936632 3q26.2 170130102 RP11-469J4.3; 6.5kb 5' of CLDN11 21743467 European rs109366323 170130102 C | A 0.15 | 0.18 0.051 0.75 (0.57, 1.00)
rs1894292 4q13.3 74349158 AFM (intron) 23535732 European rs1894292 74349158 G | A 0.26 | 0.27 0.76 0.96 (0.76, 1.22)
rs12500426 4q22.3 95514609 PDLIM5 (intron) 19767753 European rs12500426 95514609 A | C 0.61 | 0.62 0.90 0.99 (0.80, 1.22)
rs17021918 4q22.3 95562877 PDLIM5 (intron) 19767753 European rs17021918 95562877 C | T 0.21 | 0.21 0.71 1.05 (0.81, 1.36)
rs7679673 4q24 106061534 AC004069.2; 5.5kb 5' of TET2 19767753 European rs7679673 106061534 C | A 0.60 | 0.63 0.010 0.75 (0.60, 0.93)
rs2121875 5p12 44365545 FGF10 intronic 21743467 European rs2121875 44365545 C | A 0.20 | 0.20 0.79 0.97 (0.74, 1.25)
rs2242652 5p15.33 1280028 TERT (intron) 21743467 European rs22426523 1280028 G | A 0.12 | 0.13 0.34 0.85 (0.61, 1.19)
rs12653946 5p15.33 1895829 CTD-2194D22.4; 13kb 3' of IRX4 20676098 Asian rs12653946 1895829 C | T 0.40 | 0.42 0.25 0.88 (0.72, 1.09)
rs6869841 5q35.1 172939426 28kb 3' of CTB-164N12.1 23535732 European rs6869841 172939426 C | T 0.37 | 0.36 0.36 1.11 (0.89, 1.38)
rs3096702 6p21.32 32192331 486bp 5' of NOTCH4 23535732 European rs3096702 32192331 A | G 0.87 | 0.87 0.72 1.06 (0.77, 1.45)
rs130067 6p21.33 31118511 CCHCR1 (missense) 21743467 European - - - - - -
rs2273669 6q21 109285189 ARMC2 (intron) 23535732 European rs2273669 109285189 A | G 0.37 | 0.35 0.22 1.15 (0.92, 1.42)
rs339331 6q22.1 117210052 RFX6 (intron) 20676098 Asian rs339331 117210052 T | C 0.17 | 0.23 0.002 0.67 (0.52, 0.87)
rs1933488 6q25.2 153441079 RGS17 (intron) 23535732 European rs1933488 153441079 A | G 0.43 | 0.44 0.78 0.97 (0.78, 1.20)
rs651164 6q25.3 160581374 1.6kb 3' of SLC22A1 19767753; 21743057 European, Asian; European rs651164 160581374 A | G 0.76 | 0.74 0.42 1.12 (0.85, 1.49)
rs9364554 6q25.3 160833664 SLC22A3 (intron) 18264097 European rs9364554 160833664 C | T 0.01 | 0.01 0.45 1.49 (0.53, 4.18)
rs10486567 7p15.2 27976563 JAZF1 (intron) 18264096 European rs10486567 27976563 G | A 0.25 | 0.26 0.27 0.88 (0.69, 1.11)
rs12155172 7p15.3 20994491 AC006481.1 23535732 European rs12155172 20994491 A | G 0.88 | 0.88 0.85 0.97 (0.70, 1.34)
rs6465657 7q21.3 97816327 LMTK2 (intron) 18264097 European rs6465657 97816327 C | T 0.01 | 0.02 0.18 0.54 (0.22, 1.33)
rs1512268 8p21.2 23526463 9.7kb 3' of NKX3-1 19767753 European, African American, Asian - - - - - -
rs11135910 8p21.2 25892142 EBF2 (intron) 23535732 European rs11135910 25892142 C | T 0.09 | 0.09 0.91 1.02 (0.70, 1.49)
rs13252298 8q24.21 128095156 689bp 5' of RP11-255B23.2 19767752 European rs13252298 128095156 A | G 0.01 | 0.01 0.70 1.27 (0.39, 4.14)
rs7841060 8q24.21 128096477 2kb 5' of RP11-255B23.2 19767755 European rs7841060 128096477 T | G 0.34 | 0.37 0.85 0.98 (0.79, 1.21)
rs16901979 8q24.21 128124916 30kb 5' of RP11-255B23.2; 303kb 5' of POU5F1B 17401366 European rs169019793 128124916 C | A 0.56 | 0.50 0.022 1.27 (1.04, 1.57)
rs188140481 8q24.21 128191672 6.2kb 3' of RP11-255B23.4 23104005 European - - - - - -
rs16902094 8q24.21 128320346 RP11-382A18.1 19767754 European rs16902094 128320346 A | G 0.10 | 0.11 0.65 0.92 (0.66, 1.30)
rs620861 8q24.21 128335673 RP11-382A18.1; 92kb 5' of POU5F1B 19767752; 19767755 European; European rs620861 128335673 G | A 0.33 | 0.33 0.91 0.99 (0.79, 1.23)
rs6983267 8q24.21 128413305 RP11-382A18.1; 15kb 5' of POU5F1B 17401363; 18264097; 18264096; 19767752 European and African American; European; European; European rs6983267 128413305 G | T 0.02 | 0.02 0.51 1.28 (0.62, 2.63)
rs6999921 8q24.21 128440928 RP11-382A18.1 21743057 European rs6999921 128440928 A | G 0.13 | 0.09 0.060 1.38 (0.99, 1.93)
rs1447293 8q24.21 128472320 RP11-382A18.1 (intron) 21743057 European rs1447293 128472320 C | T 0.08 | 0.06 0.053 1.51 (1.00, 2.29)
rs10090154 8q24.21 128532137 38kb 5' of RP11-382A18.1; 38kb 3' of LOC727677 19767752 European rs100901543 128532137 T | C 0.80 | 0.85 0.005 0.67 (0.51, 0.89)
rs7837688 8q24.21 128539360 45kb 5' of RP11-382A18.1 20676098 Asian rs7837688 128539360 T | G 0.94 | 0.96 0.063 0.64 (0.40, 1.02)
rs817826 9q31.2 110156300 26kb 3' of RP11-363D24.1; 62kb 5' of RAD23B 23023329 Asian rs817826 110156300 C | T 0.68 | 0.65 0.47 1.09 (0.87, 1.36)
rs10993994 10q11.23 51549496 TIMM23B; 55bp 5' of MSMB 18264097; 18264096 European; European rs10993994 51549496 T | C 0.33 | 0.34 0.94 1.01 (0.81, 1.26)
rs3850699 10q24.32 104414221 TRIM8 (intron) 23535732 European rs3850699 104414221 A | G 0.41 | 0.44 0.45 0.92 (0.74, 1.14)
rs2252004 10q26.12 122844709 94kb 5' of RP11-159H3.2; 176kb 5' of WDR11 22366784 Asian rs2252004 122844709 C | A 0.65 | 0.63 0.52 1.07 (0.87, 1.33)
rs10749408 10q26.12 122967526 22kb 3' of RP11-159H3.2; 270kb 3' of FGFR2 22130093 European rs107494083 122967526 C | T 0.81 | 0.83 0.39 0.89 (0.68, 1.16)
rs11199874 10q26.12 123032519 87kb 3' of RP11-159H3.2; 205kb 3' of FGFR2 22130093 European rs111998743 123032519 G | A 0.11 | 0.12 0.30 0.84 (0.61, 1.17)
rs4962416 10q26.13 126696872 CTBP2 (intron) 18264096 European rs4962416 126696872 T | C 0.16 | 0.13 0.055 1.33 (0.99, 1.79)
rs7127900 11p15.5 2233574 32kb 3' of AC132217.2; 39kb 5' of MIR4686 19767753 European rs7127900 2233574 A | G 0.55 | 0.57 0.50 0.93 (0.75, 1.15)
rs1938781 11q12.1 58915110 FAM111A (intron) 22366784 Asian rs1938781 58915110 A | G 0.35 | 0.32 0.086 1.22 (0.97, 1.53)
rs10896438 11q13.3 68906570 8.1kb 5' of RP11-554A11.3; 48kb 5' of TPCN2 21531787 European rs10896438 68906570 T | G 0.20 | 0.23 0.96 0.99 (0.77, 1.29)
rs12793759 11q13.3 68974555 87kb 5' of MYEOV 21531787 European rs127937593 68974555 G | A 0.09 | 0.08 0.21 1.26 (0.87, 1.82)
rs10896449 11q13.3 68994667 67kb 5' of MYEOV 18264096; 21531787 European; European rs10896449 68994667 A | G 0.79 | 0.74 0.007 1.40 (1.10, 1.79)
rs7940107 11q13.3 69027770 34kb 5' of MYEOV 21743057 European rs7940107 69027770 G | A 0.34 | 0.36 0.69 0.96 (0.77, 1.19)
rs11568818 11q22.2 102401661 176bp 5' of MMP7 23535732 European rs11568818 102401661 T | C 0.45 | 0.44 0.89 1.02 (0.83, 1.25)
rs10875943 12q13.12 49676010 8.9kb 5' of TUBA1C 21743467 European rs108759433 49676010 T | C 0.75 | 0.71 0.11 1.21 (0.96, 1.53)
rs902774 12q13.13 53273904 17kb 3' of KRT8 21743057 European rs902774 53273904 G | A 0.09 | 0.08 0.087 1.39 (0.95, 2.02)
rs1270884 12q24.21 114685571 6kb 5' of RP11-139B1.1 23535732 European rs1270884 114685571 A | G 0.87 | 0.87 0.80 0.96 (0.71, 1.30)
rs9600079 13q22.1 73728139 14kb 3' of U7.97; 76kb 5' of KLF5 20676098 Asian rs9600079 73728139 G | T 0.54 | 0.62 0.002 0.71 (0.58, 0.88)
rs8008270 14q22.1 53372330 FERMT2 (intron) 23535732 European rs8008270 53372330 T | C 0.70 | 0.67 0.093 1.21 (0.97, 1.51)
rs7141529 14q24.1 69126744 RAD51B 23535732 European rs7141529 69126744 T | C 0.58 | 0.55 0.59 1.06 (0.85, 1.32)
rs1994198 15q21.1 46653167 9.2kb 5' of SNORD11.1; 670kb 5' of SQRDL 22130093 European rs1994198 46653167 C | T 0.31 | 0.31 0.88 1.02 (0.81, 1.27)
rs684232 17p13.3 618965 VPS53 23535732 European rs684232 618965 T | C 0.74 | 0.76 0.76 0.96 (0.76, 1.22)
rs11649743 17q12 36074979 HNF1B (intron) 18758462 European rs11649743 36074979 G | A 0.04 | 0.04 0.71 1.12 (0.63, 1.98)
rs4430796 17q12 36098040 HNF1B (intron) 17603485 European rs4430796 36098040 G | A 0.30 | 0.28 0.15 1.18 (0.94, 1.48)
rs7501939 17q12 36101156 HNF1B (intron) 19767753; 18264097; 17603485; 19318570 European, Asian; European; European; European rs7501939 36101156 T | C 0.40 | 0.38 0.64 1.05 (0.85, 1.29)
rs138213197 17q21.3 46805705 HOXB13 (missense) 23104005 European - - - - - -
rs11650494 17q21.32 47345186 9.2kb 3' of RP1-62O9.3 23535732 European rs11650494 47345186 G | A 0.29 | 0.27 0.37 1.11 (0.88, 1.41)
rs7210100 17q21.33 47436749 ZNF652 (intron) 21602798 African American rs7210100 47436749 G | A 0.08 | 0.05 0.008 1.78 (1.16, 2.72)
rs1859962 17q24.3 69108753 186kb 3' of U7.34; 933kb 5' of KCNJ2 17603485 European rs1859962 69108753 G | T 0.76 | 0.78 0.40 0.90 (0.71, 1.15)
rs7241993 18q23 76773973 11kb 3' of SALL3 23535732 European rs7241993 76773973 C | T 0.58 | 0.58 0.85 1.02 (0.83, 1.26)
rs8102476 19q13.2 38735613 6.3kb 3' of PPP1R14A 19767754 European rs8102476 38735613 C | T 0.16 | 0.16 0.51 0.91 (0.69, 1.20)
rs11672691 19q13.2 41985587 35kb 3' of C19orf69 23065704 European rs11672691 41985587 A | G 0.06 | 0.06 0.92 0.98 (0.64, 1.49)
rs2735839 19q13.33 51364623 602bp 5' of KLK3 18264097 European rs2735839 51364623 A | G 0.67 | 0.67 0.64 1.05 (0.85, 1.30)
rs103294 19q13.42 54797848 2kb 3' of LILRA3 23023329 Asian rs103294 54797848 C | T 0.08 | 0.06 0.20 1.31 (0.87, 1.96)
rs2427345 20q13.33 61015611 9kb 3' of RP5-908M14.5 23535732 European rs2427345 61015611 C | T 0.56 | 0.55 0.81 1.03 (0.83, 1.27)
rs6062509 20q13.33 62362563 ZGPAT (intron) 23535732 European rs6062509 62362563 G | T 0.94 | 0.95 0.79 0.94 (0.60, 1.48)
rs5759167 22q13.2 43500212 6.5kb 5' of BIK 21390317 European rs5759167 43500212 G | T 0.17 | 0.19 0.53 0.92 (0.70, 1.20)
rs742134 22q13.2 43518275 BIK (intron) 21743057 European rs742134 43518275 A | G 0.85 | 0.81 0.055 1.32 (0.99, 1.76)
rs5945572 Xp11.22 51229683 3.2kb 3' of NUDT11 18264098 European rs59455723 51229683 A | G 0.88 | 0.90 0.31 0.88 (0.68, 1.13)
rs2405942 Xp22.2 9814135 SHROOM2 (intron) 23535732 European - - - - - -
rs5919432 Xq12 67021550 77kb 5' of AR 21743467 European rs59194323 67021550 C | T 0.14 | 0.14 0.56 1.08 (0.84, 1.39)
Open in a new tab
1

Location is per GRCh37.p5.

2

Gene information curated from Haploreg, dbSNP, Ensembl, and GENCODE.

3

Imputed using 1000 Genomes Project data. Table includes SNPs with published p values <5x10-8 for overall, advanced or aggressive prostate cancer. Loci detected in European populations only were pruned using 1000 Genomes Project data with pairwise r2 > 0.3 and the SNP with lower p value preferably chosen to be listed in the table.

Discussion

In this GWAS of prostate cancer in West African men, there is evidence for an association between a possible new locus at 10p14 and prostate cancer. In an additional sub-analysis, we observed SNPs at 5q31.3 associated with high Gleason score (≥7) prostate cancers, and of SNPs at Xq28 and 6q21 in relation to low Gleason score (<7) prostate cancers; however, these observations require further confirmation because of the small sample size reported herein. Because of the noted racial disparities in prostate cancer incidence between men of European and African descent, this unique analysis may provide insight into prostate cancer pathogenesis, particularly for African populations. Lastly, of the 90 prostate cancer loci reported from studies of men of European, Asian or African American ancestry, we were able to test 81 in the Ghana Prostate Study, and 10 of these replicated at p<0.05, differences that may be partly ascribed to distinct genomic architecture (including different patterns of underlying linkage disequilibrium), heterogeneous prostate cancer populations, and uncharacterized gene-environment interactions.

The strongest associated SNP, rs7918885, localizes to 10p14 and is approximately 360 kb 5’ of GATA3 within an intron of the lncRNA gene RP11-543F8.2. An assessment of highly correlated SNPs using the 1000 Genomes Project data did not reveal splice or exonic variants of RP11-543F8.2. In the NHGRI catalog of GWAS SNPs, the closest SNP associated with any cancer resides 227kb away (Chung and Chanock 2011; Hindorff et al. 2009). The locus is marked by rs10795668 in a colorectal GWAS but its underlying biology is still unknown (Tomlinson et al. 2008). We also note that there is minimal linkage disequilibrium between that rs10795668 and rs7918885 (r2=0.001 in scan control set); moreover, there are several recombination-hot spots between the two markers.

Although we detected a promising association between the 10p14 SNPs and prostate cancer in this study of West African men, the highest p value did not quite reach the genome-wide threshold of 5×10−8. It is possible that the signal we have detected at 10p14 is due to chance, but more likely insufficient power to detect a low effect SNP (Donnelly 2008; Kraft and Hunter 2009). We had 64% power to detect rs7918885 under 5E-8 and based on the observed allele frequencies and odds ratio.

We did attempt to replicate the findings presented herein using a large meta-analytic dataset comprised of African Americans—the African Ancestry Prostate Cancer GWAS Consortium—, but only one SNP (rs2993385 at 10p14) replicated at p<0.05. There are three primary, non-mutually exclusive reasons why genetic signals may not be observed in the ancestrally-related, but distinct, African American population. The first reason is that the genomic architecture of African American men is distinct from that of African men. A recent analysis estimated that the African American population has continuously received gene flow from European populations over 14 generations (Jin et al. 2012) that has resulted in the African American population having mean ancestral percentages of 75% West African, 20% European, and 5% Native American (Bryc et al. 2010; Tishkoff et al. 2009; Zakharia et al. 2009). Individuals who self-identify as African American are highly variable in degree of West African admixture (Bryc et al. 2010; Henn et al. 2010; Jin et al. 2012; Tishkoff et al. 2009). There are also large differences in allele frequencies (Adeyemo and Rotimi 2010; Ntzani et al. 2012), private SNPs (Campbell and Tishkoff 2008; Conrad et al. 2006), patterns of homozygosity (Pemberton et al. 2012), and LD structure (Campbell and Tishkoff 2008; Conrad et al. 2006) between African and African American populations. In addition, African ancestry of African Americans is most similar to the non-Bantu Niger-Kordofanian population of West Africa (Bryc et al. 2010; Tishkoff et al. 2009), tribes of which overlap with the geographical location of the Ghana Prostate Study.

The second reason is screening. In the United States the use of DRE and PSA screening has been widespread and has resulted in over-diagnosis (Welch and Black 2010) and a concurrent change in Gleason score distribution. SEER data indicates that, of the black men diagnosed with prostate cancer during 2003–2008, 1% were reported with Gleason 2-4, 48% with Gleason 5-6, and 51% with Gleason 7-10. Respective percentages for the 474 Ghanaian cases in the study were 1%, 29% and 70%. The greater proportion of advanced grades may be expected given that only 70 cases in the final analysis were detected through the population screening component of our study; a majority of the remaining 404 were symptomatic cases who presented at the clinic; the prevalence of PSA screening in Ghana, during the study period, was low (4% vs. >50% in US). Thus the majority of our case population is comprised of symptomatic disease rather than screen-detected cancers, which is especially important for this malignancy given it is expected to develop in 80% of men by age 80 years (Franks 1954; Haas et al. 2008; Sakr et al. 1993).

The third reason could be related to uncharacterized gene-environment interactions (Hemminki et al. 2006; Perez-Losada et al. 2011). In support of a strong environmental component is the fact prostate cancer mortality rates in the US are geographically variable both between and within racial groups 1, yet neither migration patterns (Tolnay 2003) nor genetic diversity (Zakharia et al. 2009) of the African American population can account for such patterns and trends.

Differences in population genetics, environments, and disease spectra can account for differences in observed associations with complex diseases across ancestrally diverse groups (Ioannidis 2007; Ntzani et al. 2012). For example, the African Ancestry Prostate Cancer GWAS Consortium replicated approximately half of the 49 SNPs previously associated and validated in populations of European ancestry (Haiman et al. 2011a). Other studies of European sub-populations (Gaj et al. 2012; Vijai et al. 2011), Asian populations (Liu et al. 2012; Takata et al. 2010) and populations of African descent (Chang et al. 2005; Xu et al. 2011) have reported similar results. Conversely, prostate cancer risk loci discrete to specific non-Caucasian populations have also been described (Akamatsu et al. 2012; Batra et al. 2011; Haiman et al. 2011b; Takata et al. 2010; Wang et al. 2012). In addition, functional studies support the idea that some of these differences by ancestry may have a biological grounding (Grisanzio et al. 2012). In summary, we present evidence for a promising novel prostate cancer locus at 10p14 in a West African population in our initial GWAS. Further studies of prostate cancer in West African men are required for validation of this locus as well as those associated with low or high Gleason score prostate cancers. Further efforts are required to recruit greater numbers of cases in high quality epidemiologic studies to investigate the underlying genetics—and in turn gene-environment interactions—of a complex disease such as prostate cancer.

Supplementary Material

439_2013_1387_MOESM1_ESM

Acknowledgements

The authors thank Ms. Vicky Okyne for her expert help in coordinating the study; consultants/resident urologists, pathologists, nurses, and interviewers of Korle-Bu Hospital and University of Ghana Medical School for their assistance with subject enrollment, screening, and clinical examination; the study participants for their contribution toward a better understanding of prostate disease; A. DeMarzo and G. Netto of Johns Hopkins University for pathology review; Ms. Violet Devairakkam, Ms. Norma Kim, and Mr. John Heinrich of Research Triangle Institute (RTI) for their expert study management; Prof. Rosalind A. Eeles and her team for cross-checking published prostate cancer loci specified in Table 3; and members of the African Ancestry Prostate Cancer GWAS Consortium for looking-up our most promising associations from our African GWAS. This research was supported by the Intramural Research Program of the National Cancer Institute, National Institutes of Health.

FUNDING

Intramural Program of the National Cancer Institute, National Institutes of Health, Department of Health and Human Services including Contract No. HHSN261200800001E.

Footnotes

There are no financial disclosures from any of the authors.

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