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Prostate-specific antigen (PSA) screening for prostate cancer remains controversial because it increases overdiagnosis and overtreatment of clinically insignificant tumors. Accounting for genetic determinants of constitutive, non-cancer-related PSA variation has potential to improve screening utility. We discovered 128 genome-wide significant associations (P-8) in a multi-ancestry meta-analysis of 95,768 men and developed a PSA polygenic score (PGSPSA) that explains 9.61% of constitutive PSA variation. We found that in men of European ancestry, using PGS-adjusted PSA would avoid 31% of negative prostate biopsies, but also result in 12% fewer biopsies in patients with prostate cancer, mostly with Gleason score P=6.2×10-14; AUC=0.755) than unadjusted PSA (OR=3.31,P=1.1×10-12; AUC=0.738) in 106 cases and 23,667 controls. Compared to a prostate cancer PGS alone (AUC=0.712), including genetically adjusted PSA improved detection of aggressive disease (AUC=0.786,P=7.2×10-4). Our findings highlight the potential utility of incorporating PGS for personalized biomarkers in prostate cancer screening.

Deciphering the genetic basis of prostate-specific antigen (PSA) levels may improve their utility to screen for prostate cancer (PCa). We thus conducted a transcriptome-wide association study (TWAS) of PSA levels using genome-wide summary statistics from 95,768 PCa-free men, the MetaXcan framework, and gene prediction models trained in Genotype-Tissue Expression (GTEx) project data. Tissue-specific analyses identified 41 statistically significant (p < 0.05/12,192 = 4.10e-6) associations in whole blood and 39 statistically significant (p < 0.05/13,844 = 3.61e-6) associations in prostate tissue, with 18 genes associated in both tissues. Cross-tissue analyses that combined associations across 45 tissues identified 155 genes that were statistically significantly (p < 0.05/22,249 = 2.25e-6) associated with PSA levels. Based on conditional analyses that assessed whether TWAS associations were attributable to a lead GWAS variant, we found 20 novel genes (11 single-tissue, 9 cross-tissue) that were associated with PSA levels in the TWAS. Of these novel genes, five showed evidence of colocalization (colocalization probability > 0.5):EXOSC9, CCNA2, HIST1H2BN, RP11-182L21.6, andRP11-327J17.2. Six of the 20 novel genes are not known to impact PCa risk. These findings yield new hypotheses for genetic factors underlying PSA levels that should be further explored toward improving our understanding of PSA biology.

Supplementary Table S1. Descriptive factors for KP study population, broken down by study. Supplementary Table S2. Genome-wide significant SNPs found in our cohort. Supplementary Table S3. Cis-eQTL expression of rs4646284. Supplementary Table S4. Results at the 105 loci previously found to be associated with prostate cancer. Supplementary Table S5. Risk score of and variance explained by the 105 previously reported hits. Supplementary Figure S1. Manhattan and Q-Q plots of each race/ethnicity and meta-analysis. Supplementary Figure S2. Local plots of novel replicated rs4646284 and suggestive rs2659124. Supplementary Figure S3. Cis-eQTL of SLC22A1 and SLC22A3. Supplementary Figure S4. Comparison of ORs of KP to previous reports by race/ethnicity. Supplementary Figure S5. KP AUC estimates.

Supplemental Table 1: Detailed characteristics of studies included in the ASSET meta-analysis of DNA damage repair and signaling genes. Supplemental Table 2: DNA repair gene, region, and final SNP selection data, using human reference genome assembly, GRCh38. Supplemental Table 3: List of all DNA repair genes and DNA repair pathways included in this study. Supplemental Table 4: Statistical associations (p-values) for cancer risk versus genetic variation within DNA repair pathways. Sensitivity analysis of Table 3, with RAD51B, MSH5, and BRCA2 gene removed from analysis. Statistically significant values are in bold (p < 0.05). Supplemental Table 5: Statistical associations (p-values) for cancer risk versus genetic variation within DNA repair pathways. Sensitivity analysis of Table 3, with 6 genes removed from the analysis -- all genes containing loci with individual SNP associations of p < 1 x 10-4. Statistically significant values are in bold (p < 0.05).

Figure S1-S6, Table S1-S10

Allele frequencies for 128 ancestry informative single nucleotide polymorphisms, with correlations (r values) between Structure model estimates and actual allele frequencies for our 24 African American (AA) patients, plus 146 other AA and 204 European American (EA) samples ; Individual patient admixture proportions from three ancestral populations ; Somatic transition and transversion rates and ratios in our data compared to the TCGA data ; Heatmap showing log2-ratios of tumor versus normal copy number in 100Kb segments across the genome ; Circos plots showing rearrangementsb and copy numberc in the 24 tumor samples, by ETS fusion status .

PDF - 99K, Detailed methods.

Individual patient Genomic Evaluators of Metastatic Prostate Cancer (GEMCaP) scores and test results, with and without copy-neutral losses.

Background: DNA damage is an established mediator of carcinogenesis, although genome-wide association studies (GWAS) have identified few significant loci. This cross-cancer site, pooled analysis was performed to increase the power to detect common variants of DNA repair genes associated with cancer susceptibility.Methods: We conducted a cross-cancer analysis of 60,297 single nucleotide polymorphisms, at 229 DNA repair gene regions, using data from the NCI Genetic Associations and Mechanisms in Oncology (GAME-ON) Network. Our analysis included data from 32 GWAS and 48,734 controls and 51,537 cases across five cancer sites (breast, colon, lung, ovary, and prostate). Because of the unavailability of individual data, data were analyzed at the aggregate level. Meta-analysis was performed using the Association analysis for SubSETs (ASSET) software. To test for genetic associations that might escape individual variant testing due to small effect sizes, pathway analysis of eight DNA repair pathways was performed using hierarchical modeling.Results: We identified three susceptibility DNA repair genes, RAD51B (P < 5.09 × 10−6), MSH5 (P < 5.09 × 10−6), and BRCA2 (P = 5.70 × 10−6). Hierarchical modeling identified several pleiotropic associations with cancer risk in the base excision repair, nucleotide excision repair, mismatch repair, and homologous recombination pathways.Conclusions: Only three susceptibility loci were identified, which had all been previously reported. In contrast, hierarchical modeling identified several pleiotropic cancer risk associations in key DNA repair pathways.Impact: Results suggest that many common variants in DNA repair genes are likely associated with cancer susceptibility through small effect sizes that do not meet stringent significance testing criteria. Cancer Epidemiol Biomarkers Prev; 25(1); 193–200. ©2015 AACR.

Prostate cancer is the most frequently diagnosed and second most fatal nonskin cancer among men in the United States. African American men are two times more likely to develop and die of prostate cancer compared with men of other ancestries. Previous whole genome or exome tumor-sequencing studies of prostate cancer have primarily focused on men of European ancestry. In this study, we sequenced and characterized somatic mutations in aggressive (Gleason ≥7, stage ≥T2b) prostate tumors from 24 African American patients. We describe the locations and prevalence of small somatic mutations (up to 50 bases in length), copy number aberrations, and structural rearrangements in the tumor genomes compared with patient-matched normal genomes. We observed several mutation patterns consistent with previous studies, such as large copy number aberrations in chromosome 8 and complex rearrangement chains. However, TMPRSS2-ERG gene fusions and PTEN losses occurred in only 21% and 8% of the African American patients, respectively, far less common than in patients of European ancestry. We also identified mutations that appeared specific to or more common in African American patients, including a novel CDC27-OAT gene fusion occurring in 17% of patients. The genomic aberrations reported in this study warrant further investigation of their biologic significant role in the incidence and clinical outcomes of prostate cancer in African Americans. Cancer Res; 76(7); 1860–8. ©2016 AACR.

Evaluation of prostate cancer prognosis after surgery is increasingly relying upon genomic analyses of tumor DNA. We assessed the ability of the biomarker panel Genomic Evaluators of Metastatic Prostate Cancer (GEMCaP) to predict biochemical recurrence in 33 European American and 28 African American prostate cancer cases using genome-wide copy number data from a previous study. “Biomarker positive” was defined as ≥20% of the 38 constituent copy number gain/loss GEMCaP loci affected in a given tumor; based on this threshold, the frequency of a positive biomarker was significantly lower in African Americans (n = 2; 7%) than European Americans (n = 11; 33%; P = 0.013). GEMCaP positivity was associated with risk of recurrence [hazard ratio (HR), 5.92; 95% confidence interval (CI), 2.32–15.11; P = 3 × 10−4] in the full sample and among European Americans (HR, 3.45; 95% CI, 1.13–10.51; P = 0.032) but was not estimable in African Americans due to the low rate of GEMCaP positivity. Overall, the GEMCaP recurrence positive predictive value (PPV) was 85%; in African Americans, PPV was 100%. When we expanded the definition of loss to include copy-neutral loss of heterozygosity (i.e., loss of one allele with concomitant duplication of the other), recurrence PPV was 83% for European American subjects. Under this definition, 5 African American subjects had a positive GEMCaP test value; 4 went on to develop biochemical recurrence (PPV = 80%). Our results suggest that the GEMCaP biomarker set could be an effective predictor for both European American and African American men diagnosed with localized prostate cancer who may benefit from immediate aggressive therapy after radical prostatectomy. Cancer Epidemiol Biomarkers Prev; 23(8); 1677–82. ©2014 AACR.

Supplementary Figure 1: Distribution of GEMCaP scores* in African American and European American prostate cancer cases. Supplementary Figure 2: Bland-Altman plot assessing the agreement between copy number estimates for the GEMCaP loci for four African American tumor samples profiled using both sequencing and SNP array technologies. Supplementary Table 1: Demographic and clinicopathologic characteristics of the study participants (n=62) by self-identified race-ethnicity. Supplementary Table 2: GEMCaP loci human genome build 19 base-pair locations. Supplementary Table 3: Comparison of copy number estimates from next generation sequencing and SNP array technologies for the GEMCaP loci from four African American prostate tumors. Supplementary Table 4: Evidence for CNAs in other studies of African American prostate tumors for the GEMCaP loci.

Genome-wide association study–identified prostate cancer risk variants explain only a relatively small fraction of its familial relative risk, and the genes responsible for many of these identified associations remain unknown. To discover novel prostate cancer genetic loci and possible causal genes at previously identified risk loci, we performed a transcriptome-wide association study in 79,194 cases and 61,112 controls of European ancestry. Using data from the Genotype-Tissue Expression Project, we established genetic models to predict gene expression across the transcriptome for both prostate models and cross-tissue models and evaluated model performance using two independent datasets. We identified significant associations for 137 genes at P < 2.61 × 10−6, a Bonferroni-corrected threshold, including nine genes that remained significant at P < 2.61 × 10−6 after adjusting for all known prostate cancer risk variants in nearby regions. Of the 128 remaining associated genes, 94 have not yet been reported as potential target genes at known loci. We silenced 14 genes and many showed a consistent effect on viability and colony-forming efficiency in three cell lines. Our study provides substantial new information to advance our understanding of prostate cancer genetics and biology.Significance:This study identifies novel prostate cancer genetic loci and possible causal genes, advancing our understanding of the molecular mechanisms that drive prostate cancer.

Supplemental Figure 1: Manhattan plot, illustrating p-values from 60,297 SNP associations, generated from each of the 10 studies used in the meta-analysis. Statistical significance threshold is denoted by the red line (p = 5.09 x 10-6).

Background: Prostate cancer incidence and mortality rates vary across populations, with African American men exhibiting the highest rates. To date, genome-wide association studies have identified 104 SNPs independently associated with prostate cancer in men of European ancestry.Methods: We investigated whether the ability to replicate findings for these 104 SNPs in African American, Asian, and Latino populations depends on variation in risk allele frequencies (RAF), strength of associations, and/or patterns of linkage disequilibrium (LD) at the associated loci. We extracted estimates of effect from the literature, and determined RAF and LD information across the populations from the 1000 Genomes Project.Results: Risk variants were largely replicated across populations. Relative to Europeans, 83% had smaller effect sizes among African Americans and 73% demonstrated smaller effect sizes among Latinos. Among Asians, however, 56% showed larger effect sizes than among Europeans. The largest difference in RAFs was observed between European and African ancestry populations, but this difference did not impact our ability to replicate. The extent of LD within 250 kb of risk loci in Asian ancestry populations was suggestively lower for variants that did not replicate (P = 0.013).Conclusions: Despite substantial overlap in prostate cancer risk SNPs across populations, the variation in prostate cancer incidence among different populations may still in part reflect unique underlying genetic architectures.Impact: Studying different ancestral populations is crucial for deciphering the genetic basis of prostate cancer. Cancer Epidemiol Biomarkers Prev; 24(6); 938–43. ©2015 AACR.

To identify rare variants associated with prostate cancer susceptibility and better characterize the mechanisms and cumulative disease risk associated with common risk variants, we conducted an integrated study of prostate cancer genetic etiology in two cohorts using custom genotyping microarrays, large imputation reference panels, and functional annotation approaches. Specifically, 11,984 men (6,196 prostate cancer cases and 5,788 controls) of European ancestry from Northern California Kaiser Permanente were genotyped and meta-analyzed with 196,269 men of European ancestry (7,917 prostate cancer cases and 188,352 controls) from the UK Biobank. Three novel loci, including two rare variants (European ancestry minor allele frequency < 0.01, at 3p21.31 and 8p12), were significant genome wide in a meta-analysis. Gene-based rare variant tests implicated a known prostate cancer gene (HOXB13), as well as a novel candidate gene (ILDR1), which encodes a receptor highly expressed in prostate tissue and is related to the B7/CD28 family of T-cell immune checkpoint markers. Haplotypic patterns of long-range linkage disequilibrium were observed for rare genetic variants at HOXB13 and other loci, reflecting their evolutionary history. In addition, a polygenic risk score (PRS) of 188 prostate cancer variants was strongly associated with risk (90th vs. 40th–60th percentile OR = 2.62, P = 2.55 × 10−191). Many of the 188 variants exhibited functional signatures of gene expression regulation or transcription factor binding, including a 6-fold difference in log-probability of androgen receptor binding at the variant rs2680708 (17q22). Rare variant and PRS associations, with concomitant functional interpretation of risk mechanisms, can help clarify the full genetic architecture of prostate cancer and other complex traits.Significance:This study maps the biological relationships between diverse risk factors for prostate cancer, integrating different functional datasets to interpret and model genome-wide data from over 200,000 men with and without prostate cancer.See related commentary by Lachance, p. 1637

Supplementary Tables 1-2; Supplementary Figures 1-3. Supplementary Table 1 describes the set of 104 SNPs across the different populations with information about risk allele frequency and strength of association with PrCa. Supplementary Table 2 summarizes the mean linkage disequilibrium calculated with all the pairs of SNPs (index SNPs/all other SNPs) in a window of 500 kb across the different populations for the 104 SNPs. Supplementary Figure 1 compares the log odd ratio between the European population (reference population) and the other populations at each single genetic variant. Supplementary Figure 2 compares the mean recombination rate between the European population (reference population) and the other populations at each single genetic variant. Supplementary Figure 3 compares the cumulative total heritability of liability attributable to each single genetic variant between the European population (reference population) and the other populations.

PDF - 159K, Supplementary Figure 1 - Distribution of GEMCaP scores in African American and European American prostate cancer cases. Supplementary Figure 2 - Bland-Altman plot assessing the agreement between copy number estimates for the GEMCaP loci for four African American tumor samples profiled using both sequencing and SNP array technologies. Supplementary Table 1 - Demographic and clinicopathologic characteristics of the study participants (n=62) by self-identified race-ethnicity. Supplementary Table 2 - GEMCaP loci human genome build 19 base-pair locations. Supplementary Table 3 - Comparison of copy number estimates from next generation sequencing and SNP array technologies for the GEMCaP loci from four African American prostate tumors. Supplementary Table 4 - Evidence for CNAs in other studies of African American prostate tumors for the GEMCaP loci.

Background: Genetic factors play an important role in prostate cancer (PCa) susceptibility.Objective: To discover common genetic variants contributing to the risk of PCa in men of African ancestry.Design, setting, and participants: We conducted a meta-analysis of ten genome-wide association studies consisting of 19378 cases and 61620 controls of African ancestry.Outcome measurements and statistical analysis: Common genotyped and imputed variants were tested for their association with PCa risk. Novel susceptibility loci were identified and incorporated into a multiancestry polygenic risk score (PRS). The PRS was evaluated for associations with PCa risk and disease aggressiveness.Results and limitations: Nine novel susceptibility loci for PCa were identified, of which seven were only found or substantially more common in men of African ancestry, including an African-specific stop-gain variant in the prostate-specific gene anoctamin 7 (ANO7). A multiancestry PRS of 278 risk variants conferred strong associations with PCa risk in African ancestry studies (odds ratios [ORs] >3 and >5 for men in the top PRS decile and percentile, respectively). More importantly, compared with men in the 40-60% PRS category, men in the top PRS decile had a significantly higher risk of aggressive PCa (OR = 1.23, 95% confidence interval = 1.10-1.38, p = 4.4 × 10-4).Conclusions: This study demonstrates the importance of large-scale genetic studies in men of African ancestry for a better understanding of PCa susceptibility in this high-risk population and suggests a potential clinical utility of PRS in differentiating between the risks of developing aggressive and nonaggressive disease in men of African ancestry.Patient summary: In this large genetic study in men of African ancestry, we discovered nine novel prostate cancer (PCa) risk variants. We also showed that a multiancestry polygenic risk score was effective in stratifying PCa risk, and was able to differentiate risk of aggressive and nonaggressive disease.

Obstructive heart defects (OHDs) share common structural lesions in arteries and cardiac valves, accounting for ~25% of all congenital heart defects. OHDs are highly heritable, resulting from interplay among maternal exposures, genetic susceptibilities, and epigenetic phenomena. A genome-wide association study was conducted in National Birth Defects Prevention Study participants (N

To identify new susceptibility loci to lung cancer among diverse populations, we performed cross-ancestry genome-wide association studies in European, East Asian and African populations and discovered five loci that have not been previously reported. We replicated 26 signals and identified 10 new lead associations from previously reported loci. Rare-variant associations tended to be specific to populations, but even common-variant associations influencing smoking behavior, such as those with CHRNA5 and CYP2A6, showed population specificity. Fine-mapping and expression quantitative trait locus colocalization nominated several candidate variants and susceptibility genes such as IRF4 and FUBP1. DNA damage assays of prioritized genes in lung fibroblasts indicated that a subset of these genes, including the pleiotropic gene IRF4, potentially exert effects by promoting endogenous DNA damage.

As genomic technologies rapidly develop, polygenic scores (PGS) are entering into a growing conversation on how to improve precision in public health and prevent chronic disease. However, although the integration of PGS into public health clinical services raises potential benefits, it also introduces potential harms. In particular, there is a high level of uncertainty about how to incorporate PGS into clinical settings in a manner that is equitable, just, and aligned with the long-term goals of most healthcare systems to support person-centered and value-based care. This paper argues that any conversation about whether and how to design and implement PGS clinical services requires dynamic engagement with local communities, patients, and families. These parties often face the consequences, both positive and negative, of such uncertainties and should therefore drive clinical translation. As a collaborative effort between hospital stakeholders, community partners, and researchers, this paper describes a community-empowered co-design process for addressing uncertainty and making programmatic decisions about the implementation of PGS into clinical services. We provide a framework for others interested in designing clinical programs that are responsive to, and inclusive and respectful of, local communities.

PURPOSE: We examined the demographic and clinicopathological parameters associated with the time to convert from active surveillance to treatment among men with prostate cancer. MATERIALS AND METHODS: A multi-institutional cohort of 7,279 patients managed with active surveillance had data and biospecimens collected for germline genetic analyses. RESULTS: Of 6,775 men included in the analysis, 2,260 (33.4%) converted to treatment at a median followup of 6.7 years. Earlier conversion was associated with higher Gleason grade groups (GG2 vs GG1 adjusted hazard ratio [aHR] 1.57, 95% CI 1.36–1.82; ≥GG3 vs GG1 aHR 1.77, 95% CI 1.29–2.43), serum prostate specific antigen concentrations (aHR per 5 ng/ml increment 1.18, 95% CI 1.11–1.25), tumor stages (cT2 vs cT1 aHR 1.58, 95% CI 1.41–1.77; ≥cT3 vs cT1 aHR 4.36, 95% CI 3.19–5.96) and number of cancerous biopsy cores (3 vs 1–2 cores aHR 1.59, 95% CI 1.37–1.84; ≥4 vs 1–2 cores aHR 3.29, 95% CI 2.94–3.69), and younger age (age continuous per 5-year increase aHR 0.96, 95% CI 0.93–0.99). Patients with high-volume GG1 tumors had a shorter interval to conversion than those with low-volume GG1 tumors and behaved like the higher-risk patients. We found no significant association between the time to conversion and self-reported race or genetic ancestry. CONCLUSIONS: A shorter time to conversion from active surveillance to treatment was associated with higher-risk clinicopathological tumor features. Furthermore, patients with high-volume GG1 tumors behaved similarly to those with intermediate and high-risk tumors. An exploratory analysis of self-reported race and genetic ancestry revealed no association with the time to conversion.