Author Manuscript Published OnlineFirst on June 1, 2015; DOI: 10.1158/2159-8290.CD-15-0315 Author manuscripts have been peer reviewed and accepted for publication but have not yet been edited.
A large multi-ethnic genome-wide association study of prostate cancer identifies novel risk variants and substantial ethnic differences
Thomas J. Hoffmann,1,2 Stephen K. Van Den Eeden,3,4 Lori C. Sakoda,3 Eric Jorgenson,3 Laurel A. Habel,3 Rebecca E. Graff,1 Michael N. Passarelli,1 Clinton L. Cario,1 Nima C. Emami,1 Chun R. Chao,5 Nirupa R. Ghai,5 Jun Shan,3 Dilrini K. Ranatunga,3 Charles P. Quesenberry,3 David Aaronson,6 Joseph Presti,6 Wang Zhaoming,7 Sonja I. Berndt,7 Stephen J. Chanock,7 Shannon K. McDonnell,8 Amy J French,9 Daniel J Schaid,8 Stephen N. Thibodeau,9 Qiyuan Li,10 Matthew L. Freedman,11 Kathryn L. Penney,12 Lorelei A. Mucci,12 Christopher A. Haiman,13 Brian E. Henderson,13 Daniela Seminara,14 Mark N. Kvale,2 Pui-Yan Kwok,2 Catherine Schaefer,3 Neil Risch,1,2,3 and John S. Witte1,2,4,15
1
Department of Epidemiology and Biostatistics, University of California San Francisco, San
Francisco, CA 94158, USA 2
Institute for Human Genetics, University of California San Francisco, San Francisco, CA, 94143
USA 3
Division of Research, Kaiser Permanente, Northern California, Oakland, CA 94612, USA
4
Department of Urology, University of California San Francisco, San Francisco, CA 94158, USA
5
Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena CA
91101, USA 6
Department of Urology, Kaiser Oakland Medical Center, Northern California, Oakland, CA
94612, USA
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7
Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics,
Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda MD, USA. 8Department
of Health Science Research, Mayo Clinic, Rochester MN
9Department
of Laboratory Medicine and Pathology, Mayo Clinic, Rochester MN
10Medical
College, Xiamen University, Xiamen China 361102
11Department
of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical
School, Boston, MA 02115 and Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA and The Eli and Edythe L. Broad Institute, Cambridge, MA 12Department
of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA and
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 13Department
of Preventive Medicine, Keck School of Medicine and Norris Comprehensive
Cancer Center, University of Southern California, Los Angeles, CA 14National 15
Cancer Institute, National Institutes of Health, Bethesda, MD
UCSF Helen Diller Family Comprehensive Cancer Center, University of California San
Francisco, San Francisco, CA 94158, USA
Corresponding Authors: John S. Witte, University of California San Francisco, 1450 3rd St, San Francisco, CA 94158, USA, Tel: 415-502-6882, Fax: 415-476-1356 ([email protected]) or Stephen Van Den Eeden, Division of Research, Kaiser Permanente, Northern California, Oakland, CA 94612, Tel: 510-891-3718
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([email protected])
Running title: GWAS of Prostate Cancer Keywords: Prostate cancer, genome-wide association study Abbreviations list: PCa, prostate cancer; KP, Kaiser Permanente; RPGEH, Research Program on Genes, Environment, and Health; MEC, Multiethnic Cohort; PSA, prostate specific antigen; LD, linkage disequilibrium; BMI, body mass index; DHSs, DNaseI hypersensitivity sites; CGEMs, Cancer Genemics Markers of Susceptibility Project; CMHS, California Men's Health Study; GERA, Genetic Epidemiology Research on Aging; KPNCCR, Kaiser Permanente Northern California Cancer Registry; KPSCCR, Kaiser Permanente Southern California Cancer Registry; SEER, Surveillance, Epidemiology, and End Results; EUR, European-optimized array; EAS, East Asian-optimized array; LAT, Latino-optimized array; AFR, African-Americanoptimized array; QC, quality control; MAF, minor allele frequency; HWE, Hardy-Weinberg Equilibrium; PCs, Principal components; H&E, hemetoxylin and eosin; PHS, Physician's Health Study; HPFS, Healthy Professionals Follow-up study; BPC3, Breast and Prostate Cancer Cohort Consortium; TCGA, The Cancer Genome Atlas; FE, fixed effects; RE, random effects; CI, confidence interval
Notes: Grant support: This work was supported by National Institutes of Health grants: CA127298, CA088164 and CA112355 (JSW); AG046616 and DC013300 (TJH); R01 GM107427 (MLF); CA136578, CA141298, and CA131945 (KLP, LAM); CA151254 and CA157881 (SNT). This work was also 3
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supported by the UCSF Goldberg-Benioff Program in Cancer Translational Biology (JSW), Prostate Cancer Foundation Young Investigator Awards (KLP, LAM), Department Of Defense grant W81XWH-11-1-0261 (SNT), the MEC and the genotyping in AAPC were supported by NIH grants CA63464, CA54281, CA1326792, CA148085 and HG004726, funds from the California Cancer Research Program, grant number 99-86883, and from The Community Benefit Program, Kaiser Permanente Northern California. Support for participant enrollment, survey completion, and biospecimen collection for the RPGEH was provided by the Robert Wood Johnson Foundation, the Wayne and Gladys Valley Foundation, the Ellison Medical Foundation, and Kaiser Permanente national and regional community benefit programs. Genotyping of the GERA cohort was funded by a grant from the National Institute on Aging, National Institute of Mental Health, and the National Institute of Health Common Fund (RC2 AG036607 to CAS and NJR). PEGASUS was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Reprints requests and fees payment: John S. Witte, University of California San Francisco, 1450 3rd St, San Francisco, CA 94158, USA, Tel: 415-502-6882, Fax: 415-476-1356 ([email protected]) Conflict of Interest: No potential conflicts of interest were disclosed.
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Abstract A genome-wide association study of prostate cancer in Kaiser Permanente health plan members (7,783 cases, 38,595 controls; 80.3% non-Hispanic white, 4.9% African-American, 7.0% East Asian, 7.8% Latino) revealed a new independent risk indel rs4646284 at the previouslyidentified locus 6q25.3 that replicated in PEGASUS (N=7,539) and MEC (N=4,679) (p=1.0x1019
, OR=1.18). Across the 6q25.3 locus, rs4646284 exhibited the strongest association with
expression of SLC22A1 (p=1.3x10-23) and SLC22A3 (p=3.2x10-52). At the known 19q13.33 locus rs2659124 (p=1.3x10-13, OR=1.18) nominally replicated in PEGASUS. A risk score of 105 known risk SNPs was strongly associated with prostate cancer (p1.0). Only four of the variants with ORs0.3, so all were used. In the East Asian race/ethnicity group, rs116041037 and rs7210100 had r2=0.87, and rs1016343 and rs6983562 has r2=0.55; the latter SNP was removed in both circumstances when computing the risk score. To estimate the variance explained by these risk scores, we report Nagelgerke's pseudo-r2 estimate (57).
GWAS Array Heritability We estimated the additive array heritability using GCTA v1.24 (58). Array heritability estimates can be more sensitive to artifacts than GWAS results (58). Thus, to limit any potential batch effects, we limited this analysis to the homogeneous group of 30,598 non-Hispanic white men (3,605 cases and 26,993 controls) genotyped with the EUR array with Axiom v1 reagent kit. We also employed a stronger set of filters than used in the GWAS (58). Specifically, in addition to the filters noted above, we excluded SNPs with: HWE p0.05. We used only the autosomes, as is commonly done for estimating heritability. Finally, we LD-filtered the SNPs such that no two SNPs had a pairwise r2>0.8. This resulted in 26,226 individuals (3,143 cases and 23,083 controls), 402,748 genotyped SNPs, and 2,184,083 imputed SNPs with rinfo2≥0.3 and
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MAF≥0.01 used in the analysis. We assumed a population prevalence of PCa=0.12 in the liability threshold model.
We further partitioned the genome into several sets using a joint variance components fit in GCTA (59). We first tested the previously-known hits vs. the rest of the genome, and then partitioned into the functional categories, prioritized similarly to (33): coding, UTR, promoter, DHS, intron, and intergenic. SNPs that happened to fall in overlapping regions were assigned to the highest priority category. The coding, UTR, and intron regions were determined from the UCSC Genome Browser known gene database (60). Unlike (33), who defined the promoters as +/-2Kb of a transcription start site, we defined the promoters from the Eukaryotic Promoter Database new v003 (34). The DHSs were determined from (33). For this partitioning, we defined enrichment for each category as the percentage of heritability explained divided by the percentage of genome. CIs and p-values were determined by 108 bootstrap iterations.
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Acknowledgements We are grateful to the Kaiser Permanente Northern California members who have generously agreed to participate in the Kaiser Permanente Research Program on Genes, Environment, and Health, the ProHealth Study and the California Men's Health Study. We would like to thank Peter Kraft, David Hunter, Sara Lindstrom, and Constance Chen for the contribution of PHS and HPFS genetic data through the BPC3.
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Tables
Table 1. Descriptive factors for KP study population used in genome-wide association study of prostate cancer.
Cases N Total Race/ethnicity: non-Hispanic white African-American Asian Latino Age: Age < 50 50 ≤ Age < 60 60 ≤Age < 70 70 ≤ Age PSA* Mean (SD) Median (MAD) Interquartile Range Gleason: ≤5 6 7 8 9 10
%
7783
Controls N
%
38595
6406 601 288 488
82.3% 7.7% 3.7% 6.3%
30866 1650 2938 3141
80.0% 4.3% 7.6% 8.1%
86 1224 3604 2869
1.1% 15.7% 46.3% 36.9%
4619 7536 12240 14200
12.0% 19.5% 31.7% 36.8%
11.6 6.4 4.8-9.7
(53.4) (3.0)
2.5 1.5 0.8-2.8
(5.5) (1.2)
167 3067 1641 292 174 27
2.3% 53.8% 33.1% 5.8% 3.5% 0.5%
-------------
-------------
* PSA is given as the latest measure before diagnosis for cases, and the latest measure available to us from electronic medical records for controls. MAD, median absolute deviation.
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Table 2. Prostate cancer genome-wide association study results for new risk indel rs4646284 at 6q25.3 and for risk SNP rs2659124 at 19q13.33. These variants were detected in the KP study population and tested for replication in the PEGASUS and MEC cohorts. (a) Single variant and conditional analyses for 6q25.3 indel rs4646284 and the previous prostate cancer risk SNPs rs9364554 and rs651164. (b) Single variant and conditional analyses for 19q13.33 SNP rs2659124 detected here and the previous prostate cancer risk SNP rs2735839. Meta-analysis is given for the fixed effects (FE) and random effects (RE) analysis. Chromosome positions are given in b37. The risk allele frequency (RAF) is the pooled frequency across both cases and controls.
(a) No Conditioning Variant
OR (95% CI)
p
OR (95% CI)
p
r2info
KP NH white KP Latino KP Asian KP Af-Amer KP Meta FE KP Meta RE MEC PEGASUS Overall Meta FE Overall Meta RE
1.17 (1.12, 1.23) 1.13 (0.94, 1.36) 1.03 (0.84, 1.27) 1.18 (1.02, 1.37) 1.17 (1.12, 1.22) 1.17 (1.12, 1.22) 1.13 (1.03, 1.25) 1.27 (1.17, 1.37) 1.18 (1.14, 1.22) 1.18 (1.13, 1.23)
6.7x10-11 0.20 0.76 0.029 5.5x10-12 5.5x10-12 0.0094 1.4x10-8 1.0x10-19 9.8x10-17
1.16 (1.10, 1.23) 1.06 (0.85, 1.31) 0.91 (0.68, 1.23) 1.21 (1.03, 1.42) 1.15 (1.09, 1.21) 1.15 (1.07, 1.22) 1.13 (1.03, 1.25) 1.20 (1.09, 1.32) 1.16 (1.11, 1.21) 1.16 (1.11, 1.21)
3.3x10-7 0.61 0.56 0.020 8.5x10-8 7.7x10-5 0.014 0.00024 5.4x10-12 5.4x10-12
0.91 0.89 0.89 0.85 0.81 0.80 -
C
KP NH white KP Latino KP Asian KP Af-Amer KP Meta FE KP Meta RE MEC PEGASUS Overall Meta FE Overall Meta RE
0.279 0.227 0.319 0.079 0.074 0.293 -
1.10 (1.05, 1.15) 1.16 (0.97, 1.29) 1.06 (0.87, 1.29) 1.14 (0.89, 1.47) 1.10 (1.06, 1.15) 1.10 (1.06, 1.15) 1.21 (1.02, 1.41) 1.22 (1.13, 1.31) 1.14 (1.10, 1.18) 1.15 (1.09, 1.20)
6.6x10-5 0.1 0.59 0.3 1.1x10-5 1.1x10-5 0.024 9.3x10-8 6.3x10-12 6.1x10-8
1.05 (1.00, 1.10) 1.13 (0.93, 1.36) 1.05 (0.86, 1.28) 1.11 (0.85, 1.43) 1.06 (1.01, 1.11) 1.06 (1.01, 1.11) 1.19 (1.00, 1.40) 1.16 (1.07, 1.25) 1.09 (1.05, 1.13) 1.10 (1.05, 1.15)
0.070 0.21 0.63 0.45 0.019 0.019 0.041 0.00022 1.9x10-5 0.00014
1.00 1.00 1.00 1.00 1.00 1.00 -
G
KP NH white KP Latino KP Asian KP Af-Amer KP Meta FE KP Meta RE MEC PEGASUS
0.308 0.380 0.515 0.264 0.307 0.306
0.94 (0.90, 0.98) 0.88 (0.75, 1.04) 0.91 (0.76, 1.10) 1.02 (0.88, 1.18) 0.94 (0.90, 0.98) 0.94 (0.90, 0.98) 0.98 (0.90, 1.08) 0.91 (0.84, 0.97)
0.0088 0.12 0.35 0.82 0.0037 0.0037 0.73 0.0065
1.01 (0.96, 1.06) 0.91 (0.76, 1.09) 0.85 (0.65, 1.11) 1.08 (0.93, 1.28) 1.00 (0.96, 1.05) 1.00 (0.93, 1.07) 1.03 (0.93, 1.13) 0.99 (0.92, 1.07)
0.79 0.29 0.24 0.30 0.96 0.90 0.60 0.82
1.00 1.00 1.00 1.00 1.00 1.00
Ref. Allele T
Previous SNP: rs9364554
T
Previous SNP: rs651164
A
Indel: rs4646284
Conditioning on other 6q25.3 SNPs
Risk AF 0.298 0.250 0.324 0.365 0.361 0.278 -
Risk Allele TG (indel)
Group
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Overall Meta FE Overall Meta RE
-
0.94 (0.91, 0.97) 0.94 (0.91, 0.97)
0.00019 0.00019
1.00 (0.97, 1.04) 1.00 (0.97, 1.04)
0.89 0.89
-
Pairwise correlations of these three SNPs in European, Latino, East Asian and AfricanAmericans, respectively (KP data): r2rs4646284,rs9364554
= 0.15, 0.090, 0.00028, 0.017;
r2rs4646284,rs651164
= 0.19, 0.19, 0.53, 0.10;
r2rs4646284,rs9364559
= 0.00047, 0.0088, 0.0018, 0.0010.
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(b) No Conditioning SNP Risk SNP: rs2659124
Previous SNP: rs2735839
Risk Allele T
Ref. Allele A
T
C
Conditioning on other 19q13.33 SNPs
OR (95% CI)
p-value
OR (95% CI)
p-value
r2info
KP NH white KP Latino KP Asian KP Af-Amer KP Meta FE KP Meta RE MEC PEGASUS Overall Meta FE Overall Meta RE
Risk AF 0.854 0.809 0.587 0.847 0.839 0.868 -
1.22 (1.14, 1.30) 1.31 (1.07, 1.61) 1.15 (0.95, 1.40) 1.28 (1.05, 1.57) 1.22 (1.15, 1.29) 1.22 (1.15, 1.29) 1.06 (0.94, 1.20) 1.16 (1.05, 1.28) 1.18 (1.13, 1.24) 1.18 (1.12, 1.24)
2.2x10-9 0.0099 0.15 0.013 1.9x10-12 1.9x10-12 0.33 0.0027 1.3x10-13 3.0x10-10
1.13 (1.04, 1.23) 1.36 (1.00, 1.86) 1.03 (0.62, 1.71) 1.29 (1.05, 1.59) 1.16 (1.07, 1.25) 1.16 (1.07, 1.25) 1.09 (0.97, 1.23) 1.15 (1.01, 1.31) 1.14 (1.08, 1.21) 1.14 (1.08, 1.21)
0.0043 0.053 0.91 0.014 9.2x10-5 9.2x10-5 0.16 0.031 4.3x10-6 4.3x10-6
0.99 0.99 0.98 0.95 0.89 1.00 -
KP NH white KP Latino KP Asian KP Af-Amer KP Meta FE KP Meta RE MEC PEGASUS Overall Meta FE Overall Meta RE
0.150 0.214 0.419 0.302 0.311 0.140 -
1.20 (1.13, 1.28) 1.21 (1.00, 1.47) 1.15 (0.95, 1.40) 1.02 (0.88, 1.18) 1.17 (1.11, 1.24) 1.16 (1.07, 1.25) 0.93 (0.85, 1.02) 0.90 (0.82. 0.99) 0.88 (0.85, 0.92) 0.89 (0.84, 0.93)
1.6x10-8 0.052 0.15 0.70 5.7x10-9 0.00012 0.11 0.038 2.0x10-10 3.5x10-6
1.11 (1.02, 1.23) 0.97 (0.72, 1.30) 1.13 (0.68, 1.88) 0.98 (0.84, 1.14) 1.07 (1.00, 1.15) 1.07 (1.00, 1.15) 0.91 (0.83, 1.00) 0.99 (0.88, 1.13) 1.01 (0.96, 1.06) 1.00 (0.92, 1.09)
0.016 0.83 0.63 0.75 0.056 0.056 0.058 0.92 0.76 0.99
1.00 1.00 1.00 1.00 1.00 0.99 -
Study Group
Pairwise correlations of these two SNPs in European, Latino, East Asian and African-Americans, respectively (KP data): r2rs2659124, rs2735839 = 0.50, 0.58, 0.85, 0.055.
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Table 3. Array heritability enrichment of the coding, UTR, promoter, DHS, intron, and intergenic partitions for non-Hispanic whites using the imputed data. Results are from fitting each partition separately (univariate), and then subsequent results are from the joint multivariate fit, Kaiser Permanente Study Population.
Univariate
Multivariate fit
Region
hg2
hg2 (SE)
Coding
0.029 (0.014) 0.013 (0.014)
3.9%
18,608
0.85%
4.6 (0.0, 13.5)
0.45
UTR
0.048 (0.019) 0.016 (0.020)
4.7%
27,778
1.27%
3.7 (0.0, 12.2)
0.56
Promoter 0.001 (0.003) 0.001 (0.003)
0.2%
3.347
0.15%
1.3 (0.0, 10.8)
0.94
(SE)
% hg2
# SNPs
% Genome Enrichment (95% CI) Enrichment P
DHS
0.299 (0.049) 0.243 (0.065)
70.9%
361,426
16.56%
4.3 (2.0, 5.6)
0.0039
Intron
0.193 (0.045) 0.039 (0.055)
11.5%
699,518
32.04%
0.4 (0.0, 1.2)
0.14
8.7% 1,072,335
49.12%
0.2 (0.0, 0.8)
0.0058
0.334 (0.060) 0.342 (0.060) 100.0% 2,183,012
100.00%
1.0
Intergenic 0.199 (0.051) 0.030 (0.060) Total
-
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Figure Legends
Figure 1. Results from a genome-wide association study (GWAS) of prostate cancer in Kaiser Permanente population (8,399 cases and 38,745 controls), highlighting key chromosomal regions. P-values are for variant associations with prostate cancer from trans-ethnic fixed-effects meta-analysis of four race/ethnicity GWAS (non-Hispanic white, Latino, African-American, East Asian), each adjusted for age and ancestry principal components. Horizontal dashed lines indicated genome-wide statistical significance (p
A large multi-ethnic genome-wide association study of prostate cancer identifies novel risk variants and substantial ethnic differences
Thomas J. Hoffmann,1,2 Stephen K. Van Den Eeden,3,4 Lori C. Sakoda,3 Eric Jorgenson,3 Laurel A. Habel,3 Rebecca E. Graff,1 Michael N. Passarelli,1 Clinton L. Cario,1 Nima C. Emami,1 Chun R. Chao,5 Nirupa R. Ghai,5 Jun Shan,3 Dilrini K. Ranatunga,3 Charles P. Quesenberry,3 David Aaronson,6 Joseph Presti,6 Wang Zhaoming,7 Sonja I. Berndt,7 Stephen J. Chanock,7 Shannon K. McDonnell,8 Amy J French,9 Daniel J Schaid,8 Stephen N. Thibodeau,9 Qiyuan Li,10 Matthew L. Freedman,11 Kathryn L. Penney,12 Lorelei A. Mucci,12 Christopher A. Haiman,13 Brian E. Henderson,13 Daniela Seminara,14 Mark N. Kvale,2 Pui-Yan Kwok,2 Catherine Schaefer,3 Neil Risch,1,2,3 and John S. Witte1,2,4,15
1
Department of Epidemiology and Biostatistics, University of California San Francisco, San
Francisco, CA 94158, USA 2
Institute for Human Genetics, University of California San Francisco, San Francisco, CA, 94143
USA 3
Division of Research, Kaiser Permanente, Northern California, Oakland, CA 94612, USA
4
Department of Urology, University of California San Francisco, San Francisco, CA 94158, USA
5
Department of Research and Evaluation, Kaiser Permanente Southern California, Pasadena CA
91101, USA 6
Department of Urology, Kaiser Oakland Medical Center, Northern California, Oakland, CA
94612, USA
1
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7
Laboratory of Translational Genomics, Division of Cancer Epidemiology and Genetics,
Department of Health and Human Services, National Cancer Institute, National Institutes of Health, Bethesda MD, USA. 8Department
of Health Science Research, Mayo Clinic, Rochester MN
9Department
of Laboratory Medicine and Pathology, Mayo Clinic, Rochester MN
10Medical
College, Xiamen University, Xiamen China 361102
11Department
of Medical Oncology, Dana-Farber Cancer Institute and Harvard Medical
School, Boston, MA 02115 and Center for Functional Cancer Epigenetics, Dana-Farber Cancer Institute, Boston, MA and The Eli and Edythe L. Broad Institute, Cambridge, MA 12Department
of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA and
Channing Division of Network Medicine, Department of Medicine, Brigham and Women's Hospital and Harvard Medical School, Boston, MA 13Department
of Preventive Medicine, Keck School of Medicine and Norris Comprehensive
Cancer Center, University of Southern California, Los Angeles, CA 14National 15
Cancer Institute, National Institutes of Health, Bethesda, MD
UCSF Helen Diller Family Comprehensive Cancer Center, University of California San
Francisco, San Francisco, CA 94158, USA
Corresponding Authors: John S. Witte, University of California San Francisco, 1450 3rd St, San Francisco, CA 94158, USA, Tel: 415-502-6882, Fax: 415-476-1356 ([email protected]) or Stephen Van Den Eeden, Division of Research, Kaiser Permanente, Northern California, Oakland, CA 94612, Tel: 510-891-3718
2
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([email protected])
Running title: GWAS of Prostate Cancer Keywords: Prostate cancer, genome-wide association study Abbreviations list: PCa, prostate cancer; KP, Kaiser Permanente; RPGEH, Research Program on Genes, Environment, and Health; MEC, Multiethnic Cohort; PSA, prostate specific antigen; LD, linkage disequilibrium; BMI, body mass index; DHSs, DNaseI hypersensitivity sites; CGEMs, Cancer Genemics Markers of Susceptibility Project; CMHS, California Men's Health Study; GERA, Genetic Epidemiology Research on Aging; KPNCCR, Kaiser Permanente Northern California Cancer Registry; KPSCCR, Kaiser Permanente Southern California Cancer Registry; SEER, Surveillance, Epidemiology, and End Results; EUR, European-optimized array; EAS, East Asian-optimized array; LAT, Latino-optimized array; AFR, African-Americanoptimized array; QC, quality control; MAF, minor allele frequency; HWE, Hardy-Weinberg Equilibrium; PCs, Principal components; H&E, hemetoxylin and eosin; PHS, Physician's Health Study; HPFS, Healthy Professionals Follow-up study; BPC3, Breast and Prostate Cancer Cohort Consortium; TCGA, The Cancer Genome Atlas; FE, fixed effects; RE, random effects; CI, confidence interval
Notes: Grant support: This work was supported by National Institutes of Health grants: CA127298, CA088164 and CA112355 (JSW); AG046616 and DC013300 (TJH); R01 GM107427 (MLF); CA136578, CA141298, and CA131945 (KLP, LAM); CA151254 and CA157881 (SNT). This work was also 3
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supported by the UCSF Goldberg-Benioff Program in Cancer Translational Biology (JSW), Prostate Cancer Foundation Young Investigator Awards (KLP, LAM), Department Of Defense grant W81XWH-11-1-0261 (SNT), the MEC and the genotyping in AAPC were supported by NIH grants CA63464, CA54281, CA1326792, CA148085 and HG004726, funds from the California Cancer Research Program, grant number 99-86883, and from The Community Benefit Program, Kaiser Permanente Northern California. Support for participant enrollment, survey completion, and biospecimen collection for the RPGEH was provided by the Robert Wood Johnson Foundation, the Wayne and Gladys Valley Foundation, the Ellison Medical Foundation, and Kaiser Permanente national and regional community benefit programs. Genotyping of the GERA cohort was funded by a grant from the National Institute on Aging, National Institute of Mental Health, and the National Institute of Health Common Fund (RC2 AG036607 to CAS and NJR). PEGASUS was supported by the Intramural Research Program, Division of Cancer Epidemiology and Genetics, National Cancer Institute, National Institutes of Health. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. Reprints requests and fees payment: John S. Witte, University of California San Francisco, 1450 3rd St, San Francisco, CA 94158, USA, Tel: 415-502-6882, Fax: 415-476-1356 ([email protected]) Conflict of Interest: No potential conflicts of interest were disclosed.
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Abstract A genome-wide association study of prostate cancer in Kaiser Permanente health plan members (7,783 cases, 38,595 controls; 80.3% non-Hispanic white, 4.9% African-American, 7.0% East Asian, 7.8% Latino) revealed a new independent risk indel rs4646284 at the previouslyidentified locus 6q25.3 that replicated in PEGASUS (N=7,539) and MEC (N=4,679) (p=1.0x1019
, OR=1.18). Across the 6q25.3 locus, rs4646284 exhibited the strongest association with
expression of SLC22A1 (p=1.3x10-23) and SLC22A3 (p=3.2x10-52). At the known 19q13.33 locus rs2659124 (p=1.3x10-13, OR=1.18) nominally replicated in PEGASUS. A risk score of 105 known risk SNPs was strongly associated with prostate cancer (p1.0). Only four of the variants with ORs0.3, so all were used. In the East Asian race/ethnicity group, rs116041037 and rs7210100 had r2=0.87, and rs1016343 and rs6983562 has r2=0.55; the latter SNP was removed in both circumstances when computing the risk score. To estimate the variance explained by these risk scores, we report Nagelgerke's pseudo-r2 estimate (57).
GWAS Array Heritability We estimated the additive array heritability using GCTA v1.24 (58). Array heritability estimates can be more sensitive to artifacts than GWAS results (58). Thus, to limit any potential batch effects, we limited this analysis to the homogeneous group of 30,598 non-Hispanic white men (3,605 cases and 26,993 controls) genotyped with the EUR array with Axiom v1 reagent kit. We also employed a stronger set of filters than used in the GWAS (58). Specifically, in addition to the filters noted above, we excluded SNPs with: HWE p0.05. We used only the autosomes, as is commonly done for estimating heritability. Finally, we LD-filtered the SNPs such that no two SNPs had a pairwise r2>0.8. This resulted in 26,226 individuals (3,143 cases and 23,083 controls), 402,748 genotyped SNPs, and 2,184,083 imputed SNPs with rinfo2≥0.3 and
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MAF≥0.01 used in the analysis. We assumed a population prevalence of PCa=0.12 in the liability threshold model.
We further partitioned the genome into several sets using a joint variance components fit in GCTA (59). We first tested the previously-known hits vs. the rest of the genome, and then partitioned into the functional categories, prioritized similarly to (33): coding, UTR, promoter, DHS, intron, and intergenic. SNPs that happened to fall in overlapping regions were assigned to the highest priority category. The coding, UTR, and intron regions were determined from the UCSC Genome Browser known gene database (60). Unlike (33), who defined the promoters as +/-2Kb of a transcription start site, we defined the promoters from the Eukaryotic Promoter Database new v003 (34). The DHSs were determined from (33). For this partitioning, we defined enrichment for each category as the percentage of heritability explained divided by the percentage of genome. CIs and p-values were determined by 108 bootstrap iterations.
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Acknowledgements We are grateful to the Kaiser Permanente Northern California members who have generously agreed to participate in the Kaiser Permanente Research Program on Genes, Environment, and Health, the ProHealth Study and the California Men's Health Study. We would like to thank Peter Kraft, David Hunter, Sara Lindstrom, and Constance Chen for the contribution of PHS and HPFS genetic data through the BPC3.
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Tables
Table 1. Descriptive factors for KP study population used in genome-wide association study of prostate cancer.
Cases N Total Race/ethnicity: non-Hispanic white African-American Asian Latino Age: Age < 50 50 ≤ Age < 60 60 ≤Age < 70 70 ≤ Age PSA* Mean (SD) Median (MAD) Interquartile Range Gleason: ≤5 6 7 8 9 10
%
7783
Controls N
%
38595
6406 601 288 488
82.3% 7.7% 3.7% 6.3%
30866 1650 2938 3141
80.0% 4.3% 7.6% 8.1%
86 1224 3604 2869
1.1% 15.7% 46.3% 36.9%
4619 7536 12240 14200
12.0% 19.5% 31.7% 36.8%
11.6 6.4 4.8-9.7
(53.4) (3.0)
2.5 1.5 0.8-2.8
(5.5) (1.2)
167 3067 1641 292 174 27
2.3% 53.8% 33.1% 5.8% 3.5% 0.5%
-------------
-------------
* PSA is given as the latest measure before diagnosis for cases, and the latest measure available to us from electronic medical records for controls. MAD, median absolute deviation.
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Table 2. Prostate cancer genome-wide association study results for new risk indel rs4646284 at 6q25.3 and for risk SNP rs2659124 at 19q13.33. These variants were detected in the KP study population and tested for replication in the PEGASUS and MEC cohorts. (a) Single variant and conditional analyses for 6q25.3 indel rs4646284 and the previous prostate cancer risk SNPs rs9364554 and rs651164. (b) Single variant and conditional analyses for 19q13.33 SNP rs2659124 detected here and the previous prostate cancer risk SNP rs2735839. Meta-analysis is given for the fixed effects (FE) and random effects (RE) analysis. Chromosome positions are given in b37. The risk allele frequency (RAF) is the pooled frequency across both cases and controls.
(a) No Conditioning Variant
OR (95% CI)
p
OR (95% CI)
p
r2info
KP NH white KP Latino KP Asian KP Af-Amer KP Meta FE KP Meta RE MEC PEGASUS Overall Meta FE Overall Meta RE
1.17 (1.12, 1.23) 1.13 (0.94, 1.36) 1.03 (0.84, 1.27) 1.18 (1.02, 1.37) 1.17 (1.12, 1.22) 1.17 (1.12, 1.22) 1.13 (1.03, 1.25) 1.27 (1.17, 1.37) 1.18 (1.14, 1.22) 1.18 (1.13, 1.23)
6.7x10-11 0.20 0.76 0.029 5.5x10-12 5.5x10-12 0.0094 1.4x10-8 1.0x10-19 9.8x10-17
1.16 (1.10, 1.23) 1.06 (0.85, 1.31) 0.91 (0.68, 1.23) 1.21 (1.03, 1.42) 1.15 (1.09, 1.21) 1.15 (1.07, 1.22) 1.13 (1.03, 1.25) 1.20 (1.09, 1.32) 1.16 (1.11, 1.21) 1.16 (1.11, 1.21)
3.3x10-7 0.61 0.56 0.020 8.5x10-8 7.7x10-5 0.014 0.00024 5.4x10-12 5.4x10-12
0.91 0.89 0.89 0.85 0.81 0.80 -
C
KP NH white KP Latino KP Asian KP Af-Amer KP Meta FE KP Meta RE MEC PEGASUS Overall Meta FE Overall Meta RE
0.279 0.227 0.319 0.079 0.074 0.293 -
1.10 (1.05, 1.15) 1.16 (0.97, 1.29) 1.06 (0.87, 1.29) 1.14 (0.89, 1.47) 1.10 (1.06, 1.15) 1.10 (1.06, 1.15) 1.21 (1.02, 1.41) 1.22 (1.13, 1.31) 1.14 (1.10, 1.18) 1.15 (1.09, 1.20)
6.6x10-5 0.1 0.59 0.3 1.1x10-5 1.1x10-5 0.024 9.3x10-8 6.3x10-12 6.1x10-8
1.05 (1.00, 1.10) 1.13 (0.93, 1.36) 1.05 (0.86, 1.28) 1.11 (0.85, 1.43) 1.06 (1.01, 1.11) 1.06 (1.01, 1.11) 1.19 (1.00, 1.40) 1.16 (1.07, 1.25) 1.09 (1.05, 1.13) 1.10 (1.05, 1.15)
0.070 0.21 0.63 0.45 0.019 0.019 0.041 0.00022 1.9x10-5 0.00014
1.00 1.00 1.00 1.00 1.00 1.00 -
G
KP NH white KP Latino KP Asian KP Af-Amer KP Meta FE KP Meta RE MEC PEGASUS
0.308 0.380 0.515 0.264 0.307 0.306
0.94 (0.90, 0.98) 0.88 (0.75, 1.04) 0.91 (0.76, 1.10) 1.02 (0.88, 1.18) 0.94 (0.90, 0.98) 0.94 (0.90, 0.98) 0.98 (0.90, 1.08) 0.91 (0.84, 0.97)
0.0088 0.12 0.35 0.82 0.0037 0.0037 0.73 0.0065
1.01 (0.96, 1.06) 0.91 (0.76, 1.09) 0.85 (0.65, 1.11) 1.08 (0.93, 1.28) 1.00 (0.96, 1.05) 1.00 (0.93, 1.07) 1.03 (0.93, 1.13) 0.99 (0.92, 1.07)
0.79 0.29 0.24 0.30 0.96 0.90 0.60 0.82
1.00 1.00 1.00 1.00 1.00 1.00
Ref. Allele T
Previous SNP: rs9364554
T
Previous SNP: rs651164
A
Indel: rs4646284
Conditioning on other 6q25.3 SNPs
Risk AF 0.298 0.250 0.324 0.365 0.361 0.278 -
Risk Allele TG (indel)
Group
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Overall Meta FE Overall Meta RE
-
0.94 (0.91, 0.97) 0.94 (0.91, 0.97)
0.00019 0.00019
1.00 (0.97, 1.04) 1.00 (0.97, 1.04)
0.89 0.89
-
Pairwise correlations of these three SNPs in European, Latino, East Asian and AfricanAmericans, respectively (KP data): r2rs4646284,rs9364554
= 0.15, 0.090, 0.00028, 0.017;
r2rs4646284,rs651164
= 0.19, 0.19, 0.53, 0.10;
r2rs4646284,rs9364559
= 0.00047, 0.0088, 0.0018, 0.0010.
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(b) No Conditioning SNP Risk SNP: rs2659124
Previous SNP: rs2735839
Risk Allele T
Ref. Allele A
T
C
Conditioning on other 19q13.33 SNPs
OR (95% CI)
p-value
OR (95% CI)
p-value
r2info
KP NH white KP Latino KP Asian KP Af-Amer KP Meta FE KP Meta RE MEC PEGASUS Overall Meta FE Overall Meta RE
Risk AF 0.854 0.809 0.587 0.847 0.839 0.868 -
1.22 (1.14, 1.30) 1.31 (1.07, 1.61) 1.15 (0.95, 1.40) 1.28 (1.05, 1.57) 1.22 (1.15, 1.29) 1.22 (1.15, 1.29) 1.06 (0.94, 1.20) 1.16 (1.05, 1.28) 1.18 (1.13, 1.24) 1.18 (1.12, 1.24)
2.2x10-9 0.0099 0.15 0.013 1.9x10-12 1.9x10-12 0.33 0.0027 1.3x10-13 3.0x10-10
1.13 (1.04, 1.23) 1.36 (1.00, 1.86) 1.03 (0.62, 1.71) 1.29 (1.05, 1.59) 1.16 (1.07, 1.25) 1.16 (1.07, 1.25) 1.09 (0.97, 1.23) 1.15 (1.01, 1.31) 1.14 (1.08, 1.21) 1.14 (1.08, 1.21)
0.0043 0.053 0.91 0.014 9.2x10-5 9.2x10-5 0.16 0.031 4.3x10-6 4.3x10-6
0.99 0.99 0.98 0.95 0.89 1.00 -
KP NH white KP Latino KP Asian KP Af-Amer KP Meta FE KP Meta RE MEC PEGASUS Overall Meta FE Overall Meta RE
0.150 0.214 0.419 0.302 0.311 0.140 -
1.20 (1.13, 1.28) 1.21 (1.00, 1.47) 1.15 (0.95, 1.40) 1.02 (0.88, 1.18) 1.17 (1.11, 1.24) 1.16 (1.07, 1.25) 0.93 (0.85, 1.02) 0.90 (0.82. 0.99) 0.88 (0.85, 0.92) 0.89 (0.84, 0.93)
1.6x10-8 0.052 0.15 0.70 5.7x10-9 0.00012 0.11 0.038 2.0x10-10 3.5x10-6
1.11 (1.02, 1.23) 0.97 (0.72, 1.30) 1.13 (0.68, 1.88) 0.98 (0.84, 1.14) 1.07 (1.00, 1.15) 1.07 (1.00, 1.15) 0.91 (0.83, 1.00) 0.99 (0.88, 1.13) 1.01 (0.96, 1.06) 1.00 (0.92, 1.09)
0.016 0.83 0.63 0.75 0.056 0.056 0.058 0.92 0.76 0.99
1.00 1.00 1.00 1.00 1.00 0.99 -
Study Group
Pairwise correlations of these two SNPs in European, Latino, East Asian and African-Americans, respectively (KP data): r2rs2659124, rs2735839 = 0.50, 0.58, 0.85, 0.055.
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Table 3. Array heritability enrichment of the coding, UTR, promoter, DHS, intron, and intergenic partitions for non-Hispanic whites using the imputed data. Results are from fitting each partition separately (univariate), and then subsequent results are from the joint multivariate fit, Kaiser Permanente Study Population.
Univariate
Multivariate fit
Region
hg2
hg2 (SE)
Coding
0.029 (0.014) 0.013 (0.014)
3.9%
18,608
0.85%
4.6 (0.0, 13.5)
0.45
UTR
0.048 (0.019) 0.016 (0.020)
4.7%
27,778
1.27%
3.7 (0.0, 12.2)
0.56
Promoter 0.001 (0.003) 0.001 (0.003)
0.2%
3.347
0.15%
1.3 (0.0, 10.8)
0.94
(SE)
% hg2
# SNPs
% Genome Enrichment (95% CI) Enrichment P
DHS
0.299 (0.049) 0.243 (0.065)
70.9%
361,426
16.56%
4.3 (2.0, 5.6)
0.0039
Intron
0.193 (0.045) 0.039 (0.055)
11.5%
699,518
32.04%
0.4 (0.0, 1.2)
0.14
8.7% 1,072,335
49.12%
0.2 (0.0, 0.8)
0.0058
0.334 (0.060) 0.342 (0.060) 100.0% 2,183,012
100.00%
1.0
Intergenic 0.199 (0.051) 0.030 (0.060) Total
-
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Figure Legends
Figure 1. Results from a genome-wide association study (GWAS) of prostate cancer in Kaiser Permanente population (8,399 cases and 38,745 controls), highlighting key chromosomal regions. P-values are for variant associations with prostate cancer from trans-ethnic fixed-effects meta-analysis of four race/ethnicity GWAS (non-Hispanic white, Latino, African-American, East Asian), each adjusted for age and ancestry principal components. Horizontal dashed lines indicated genome-wide statistical significance (p
