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.

No abstract

Genome‐wide association studies typically search for marginal associations between a single‐nucleotide polymorphism (SNP) and a disease trait while gene‐environment (G × E) interactions remain generally unexplored. More powerful methods beyond the simple case–control (CC) approach leverage either marginal effects or CC ascertainment to increase power. However, these potential gains depend on assumptions whose aptness is often unclear a priori. Here, we review G × E methods and use simulations to highlight performance as a function of main and interaction effects and the association of the two factors in the source population. Substantial variation in performance between methods leads to uncertainty as to which approach is most appropriate for any given analysis. We present a framework that (a) balances the robustness of a CC approach with the power of the case‐only (CO) approach; (b) incorporates main SNP effects; (c) allows for incorporation of prior information; and (d) allows the data to determine the most appropriate model. Our framework is based on Bayes model averaging, which provides a principled statistical method for incorporating model uncertainty. We average over inclusion of parameters corresponding to the main and G × E interaction effects and the G–E association in controls. The resulting method exploits the joint evidence for main and interaction effects while gaining power from a CO equivalent analysis. Through simulations, we demonstrate that our approach detects SNPs within a wide range of scenarios with increased power over current methods. We illustrate the approach on a gene‐environment scan in the USC Children's Health Study.

Prostate cancer (PCa) is a highly heritable disease with large disparities in incidence rates across racial and ethnic populations. The inadequate representation of diverse populations in current genome-wide association studies (GWAS) limits the translational potential of findings to the world’s populations and could result in biased risk prediction, further exacerbating health disparities. To improve our understanding of genetic risk of PCa, we conducted a multiethnic meta-analysis of PCa GWAS using 107,247 cases and 127,006 controls from the Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome (PRACTICAL) consortium, including 85,554 cases and 91,972 controls of European ancestry, 10,368 cases and 10,986 controls of African ancestry, 8,611 cases and 18,809 controls of Asian ancestry, and 2,714 cases and 5,239 controls of Hispanic ancestry. We identified 269 genetic risk variants independently associated with PCa risk, 86 of which were novel. To understand the aggregate effect of the 269 variants, we constructed a genetic risk score (GRS) using the multiethnic weights of the risk variants. Compared to men in the average 40-60% GRS category, the estimated OR for men in the top GRS decile (90-100%) was 5.06 [95% CI 4.84-5.29] for men of European ancestry, 3.74 [95% CI 3.36-4.17] for men of African ancestry, 4.47 [95% CI 3.52-5.68] for men of Asian ancestry, and 4.15 [95% CI 3.33-5.17] for men of Hispanic ancestry. Men of African ancestry were estimated to have a 2.18-times higher mean GRS [95% CI 2.14-2.22], and men of Asian ancestry 0.73-times lower [95% CI 0.71- 0.76], than men of European ancestry. Age significantly modified the GRS association with PCa risk, such that in men of European ancestry, the top decile GRS category was associated with an OR of 6.71 [95 % CI 5.99-7.52] for men ages 55 years or younger and 4.39 [95% CI 4.19-4.60] for men older than 55 years. Similarly, in men of African ancestry, the top decile GRS category was associated with an OR of 4.70 [95% CI 3.65-6.07] for men ages 55 years or younger and 3.37 [95% CI 2.99-3.80] for men older than 55 years. We found that 51% of aggressive cases of European ancestry and 45% of aggressive cases of African ancestry were within the top 20% of the GRS. The lifetime absolute risk of PCa for men in the top decile of the GRS reached 38% for both African Americans [95% CI 36-41%] and Whites [95% CI 37-39%], 31% [95% CI 27-36%] for Hispanics and 26% [95% CI 22-30%] for Asians. For comparison, we constructed a genome-wide GRS, including the 269 variants and variants associated with PCa with P<1.0 × 10-5. ORs calculated with genome-wide GRS were similar and had nearly identical discriminative ability as the 269 GRS in independent samples of 6,852 cases and 193,117 controls of European ancestry and 1,586 cases and 1,047 controls of African ancestry. These findings support the role of germline variation contributing to racial and ethnic disparities in PCa risk, with the GRS offering an approach for personalized risk prediction across populations. Citation Format: David V. Conti, Burcu F. Darst, Lilit Moss, Edward J. Saunders, Xin Sheng, Alisha Chou, Tokhir Dadaev, Sonja I. Berndt, Stephen K. Van Den Eeden, Stephen J. Chanock, Michael B. Cook, Hidewaki Nakagawa, John S. Witte, Rosalind A. Eeles, Zsofia Kote-Jarai, Christopher A. Haiman. Multiethnic GWAS meta-analysis identifies novel variants and informs genetic risk prediction for prostate cancer across populations [abstract]. In: Proceedings of the AACR Virtual Conference: Thirteenth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2020 Oct 2-4. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(12 Suppl):Abstract nr PO-146.

Prostate cancer (PCa) is a highly heritable disease with large disparities in incidence rates across racial and ethnic populations. The inadequate representation of diverse populations in current genome-wide association studies (GWAS) limits the translational potential of findings to the world's populations and could result in biased risk prediction, further exacerbating health disparities. To improve our understanding of genetic risk of PCa, we conducted the largest multiethnic PCa GWAS meta-analysis to date with 107,247 cases and 127,006 controls from the Prostate Cancer Association Group to Investigate Cancer-Associated Alterations in the Genome (PRACTICAL) consortium, including 85,554 cases and 91,972 controls of European ancestry, 10,368 cases and 10,986 controls of African ancestry, 8,611 cases and 18,809 controls of Asian ancestry, and 2,714 cases and 5,239 controls of Hispanic ethnicity. We identified 269 genetic risk variants independently associated with PCa risk, 86 of which were novel. Of the 183 previously reported prostate cancer risk variants, we identified stronger markers of risk for 62 variants using fine-mapping. To understand the aggregate effect of the 269 variants, we constructed a genetic risk score (GRS) using the multiethnic weights of the risk variants. Compared to men in the average 40-60% GRS category, the estimated OR for men in the top GRS decile (90-100%) was 5.06 [95% CI 4.84-5.29] for men of European ancestry, 3.74 [95% CI 3.36-4.17] for men of African ancestry, 4.47 [95% CI 3.52-5.68] for men of Asian ancestry, and 4.15 [95% CI 3.33-5.17] for Hispanic men. Men of African ancestry were estimated to have a 2.18-times higher mean GRS [95% CI 2.14-2.22], and men of Asian ancestry 0.73-times lower [95% CI 0.71-0.76], than men of European ancestry. Age significantly modified the GRS association with PCa risk, such that in men of European ancestry, the top decile GRS category was associated with an OR of 6.71 [95 % CI 5.99-7.52] for men ages 55 years or younger and 4.39 [95% CI 4.19-4.60] for men older than 55 years. Similarly, in men of African ancestry, the top GRS decile category was associated with an OR of 4.70 [95 % CI 3.65-6.07] for men ages 55 years or younger and 3.37 [95% CI 2.99-3.80] for men older than 55 years. We found that 51% of aggressive cases of European ancestry and 45% of aggressive cases of African ancestry were within the top 20% of the GRS. The lifetime absolute risk of PCa for men in the top decile of the GRS reached 38% for both African Americans [95% CI 36-41%] and Whites [95% CI 37-39%], 31% [95% CI 27-36%] for Hispanics and 26% [95% CI 22-30%] for Asians. For comparison, we constructed a genome-wide GRS, including the 269 variants and variants associated with PCa with P<1.0 × 10−5. ORs calculated with genome-wide GRS were similar and had nearly identical discriminative ability as the 269 GRS in independent samples of 6,852 cases and 193,117 controls of European ancestry and 1,586 cases and 1,047 controls of African ancestry. This suggests that a genome-wide GRS may not have improved ability to predict PCa risk compared to the 269 GRS. To understand the biological mechanisms impacted by genetic risk of PCa, we conducted integrative analyses of the GRS and serum metabolomics in 611 African ancestry men from the Multiethnic Cohort. We found that a higher GRS was associated with lower sphingolipid levels (beta=-0.08, P=3.1 × 10−4), lower androgenic steroids (beta=-0.06, P=0.003), and higher sarcosine levels (beta=0.11, P=0.002). Further, using a latent clustering approach, we found that these metabolites in conjunction with the GRS contributed to the clustering of men with low-risk, intermediate-risk, and high-risk of PCa. These findings support the role of germline variation contributing to racial and ethnic disparities in PCa risk, with the GRS offering an approach for personalized risk prediction across populations and informing the biological mechanisms underlying PCa risk. Citation Format: Burcu F. Darst, Lilit Moss, Edward J. Saunders, Nicholas Mancuso, Xin Sheng, Alisha Chou, Tokhir Dadaev, Sonja I. Berndt, Stephen K. Van Den Eeden, Stephen J. Chanock, Michael B. Cook, Tracy M. Layne, Demetrius Albanes, Hidewaki Nakagawa, John S. Witte, Practical Consortium, Rosalind A. Eeles, Zsofia Kote-Jarai, David V. Conti, Christopher A. Haiman. Multiethnic prostate cancer GWAS meta-analysis identifies novel variants, improves genetic risk prediction across populations, and informs biological mechanisms of prostate cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2021; 2021 Apr 10-15 and May 17-21. Philadelphia (PA): AACR; Cancer Res 2021;81(13_Suppl):Abstract nr NG03.