Prostate cancer risk regions at 8q24 and 17q24 are differentially associated with somatic TMPRSS2:ERG fusion status.

Molecular and epidemiological differences have been described between TMPRSS2:ERG fusion-positive and fusion-negative prostate cancer (PrCa). Assuming two molecularly distinct subtypes, we have examined 27 common PrCa risk variants, previously identified in genome-wide association studies, for subtype specific associations in a total of 1221 TMPRSS2:ERG phenotyped PrCa cases. In meta-analyses of a discovery set of 552 cases with TMPRSS2:ERG data and 7650 unaffected men from five centers we have found support for the hypothesis that several common risk variants are associated with one particular subtype rather than with PrCa in general. Risk variants were analyzed in case-case comparisons (296 TMPRSS2:ERG fusion-positive versus 256 fusion-negative cases) and an independent set of 669 cases with TMPRSS2:ERG data was established to replicate the top five candidates. Significant differences (P < 0.00185) between the two subtypes were observed for rs16901979 (8q24) and rs1859962 (17q24), which were enriched in TMPRSS2:ERG fusion-negative (OR = 0.53, P = 0.0007) and TMPRSS2:ERG fusion-positive PrCa (OR = 1.30, P = 0.0016), respectively. Expression quantitative trait locus analysis was performed to investigate mechanistic links between risk variants, fusion status and target gene mRNA levels. For rs1859962 at 17q24, genotype dependent expression was observed for the candidate target gene SOX9 in TMPRSS2:ERG fusion-positive PrCa, which was not evident in TMPRSS2:ERG negative tumors. The present study established evidence for the first two common PrCa risk variants differentially associated with TMPRSS2:ERG fusion status. TMPRSS2:ERG phenotyping of larger studies is required to determine comprehensive sets of variants with subtype-specific roles in PrCa.

Height, selected genetic markers and prostate cancer risk: results from the PRACTICAL consortium.

This corrects the article DOI: 10.1038/bjc.2017.231.

Gene and pathway level analyses of germline DNA-repair gene variants and prostate cancer susceptibility using the iCOGS-genotyping array.

This corrects the article DOI: 10.1038/bjc.2016.50.

Alcohol consumption and prostate cancer incidence and progression: A Mendelian randomisation study.

Prostate cancer is the most common cancer in men in developed countries, and is a target for risk reduction strategies. The effects of alcohol consumption on prostate cancer incidence and survival remain unclear, potentially due to methodological limitations of observational studies. In this study, we investigated the associations of genetic variants in alcohol-metabolising genes with prostate cancer incidence and survival. We analysed data from 23,868 men with prostate cancer and 23,051 controls from 25 studies within the international PRACTICAL Consortium. Study-specific associations of 68 single nucleotide polymorphisms (SNPs) in 8 alcohol-metabolising genes (Alcohol Dehydrogenases (ADHs) and Aldehyde Dehydrogenases (ALDHs)) with prostate cancer diagnosis and prostate cancer-specific mortality, by grade, were assessed using logistic and Cox regression models, respectively. The data across the 25 studies were meta-analysed using fixed-effect and random-effects models. We found little evidence that variants in alcohol metabolising genes were associated with prostate cancer diagnosis. Four variants in two genes exceeded the multiple testing threshold for associations with prostate cancer mortality in fixed-effect meta-analyses. SNPs within ALDH1A2 associated with prostate cancer mortality were rs1441817 (fixed effects hazard ratio, HRfixed = 0.78; 95% confidence interval (95%CI):0.66,0.91; p values = 0.002); rs12910509, HRfixed = 0.76; 95%CI:0.64,0.91; p values = 0.003); and rs8041922 (HRfixed = 0.76; 95%CI:0.64,0.91; p values = 0.002). These SNPs were in linkage disequilibrium with each other. In ALDH1B1, rs10973794 (HRfixed = 1.43; 95%CI:1.14,1.79; p values = 0.002) was associated with prostate cancer mortality in men with low-grade prostate cancer. These results suggest that alcohol consumption is unlikely to affect prostate cancer incidence, but it may influence disease progression.

Integration of multiethnic fine-mapping and genomic annotation to prioritize candidate functional SNPs at prostate cancer susceptibility regions.

Interpretation of biological mechanisms underlying genetic risk associations for prostate cancer is complicated by the relatively large number of risk variants (n = 100) and the thousands of surrogate SNPs in linkage disequilibrium. Here, we combined three distinct approaches: multiethnic fine-mapping, putative functional annotation (based upon epigenetic data and genome-encoded features), and expression quantitative trait loci (eQTL) analyses, in an attempt to reduce this complexity. We examined 67 risk regions using genotyping and imputation-based fine-mapping in populations of European (cases/controls: 8600/6946), African (cases/controls: 5327/5136), Japanese (cases/controls: 2563/4391) and Latino (cases/controls: 1034/1046) ancestry. Markers at 55 regions passed a region-specific significance threshold (P-value cutoff range: 3.9 × 10(-4)-5.6 × 10(-3)) and in 30 regions we identified markers that were more significantly associated with risk than the previously reported variants in the multiethnic sample. Novel secondary signals (P < 5.0 × 10(-6)) were also detected in two regions (rs13062436/3q21 and rs17181170/3p12). Among 666 variants in the 55 regions with P-values within one order of magnitude of the most-associated marker, 193 variants (29%) in 48 regions overlapped with epigenetic or other putative functional marks. In 11 of the 55 regions, cis-eQTLs were detected with nearby genes. For 12 of the 55 regions (22%), the most significant region-specific, prostate-cancer associated variant represented the strongest candidate functional variant based on our annotations; the number of regions increased to 20 (36%) and 27 (49%) when examining the 2 and 3 most significantly associated variants in each region, respectively. These results have prioritized subsets of candidate variants for downstream functional evaluation.

Fine-mapping the HOXB region detects common variants tagging a rare coding allele: evidence for synthetic association in prostate cancer.

The HOXB13 gene has been implicated in prostate cancer (PrCa) susceptibility. We performed a high resolution fine-mapping analysis to comprehensively evaluate the association between common genetic variation across the HOXB genetic locus at 17q21 and PrCa risk. This involved genotyping 700 SNPs using a custom Illumina iSelect array (iCOGS) followed by imputation of 3195 SNPs in 20,440 PrCa cases and 21,469 controls in The PRACTICAL consortium. We identified a cluster of highly correlated common variants situated within or closely upstream of HOXB13 that were significantly associated with PrCa risk, described by rs117576373 (OR 1.30, P = 2.62×10(-14)). Additional genotyping, conditional regression and haplotype analyses indicated that the newly identified common variants tag a rare, partially correlated coding variant in the HOXB13 gene (G84E, rs138213197), which has been identified recently as a moderate penetrance PrCa susceptibility allele. The potential for GWAS associations detected through common SNPs to be driven by rare causal variants with higher relative risks has long been proposed; however, to our knowledge this is the first experimental evidence for this phenomenon of synthetic association contributing to cancer susceptibility.

Assessing the role of insulin-like growth factors and binding proteins in prostate cancer using Mendelian randomization: Genetic variants as instruments for circulating levels.

Circulating insulin-like growth factors (IGFs) and their binding proteins (IGFBPs) are associated with prostate cancer. Using genetic variants as instruments for IGF peptides, we investigated whether these associations are likely to be causal. We identified from the literature 56 single nucleotide polymorphisms (SNPs) in the IGF axis previously associated with biomarker levels (8 from a genome-wide association study [GWAS] and 48 in reported candidate genes). In ∼700 men without prostate cancer and two replication cohorts (N ∼ 900 and ∼9,000), we examined the properties of these SNPS as instrumental variables (IVs) for IGF-I, IGF-II, IGFBP-2 and IGFBP-3. Those confirmed as strong IVs were tested for association with prostate cancer risk, low (< 7) vs. high (≥ 7) Gleason grade, localised vs. advanced stage, and mortality, in 22,936 controls and 22,992 cases. IV analysis was used in an attempt to estimate the causal effect of circulating IGF peptides on prostate cancer. Published SNPs in the IGFBP1/IGFBP3 gene region, particularly rs11977526, were strong instruments for IGF-II and IGFBP-3, less so for IGF-I. Rs11977526 was associated with high (vs. low) Gleason grade (OR per IGF-II/IGFBP-3 level-raising allele 1.05; 95% CI: 1.00, 1.10). Using rs11977526 as an IV we estimated the causal effect of a one SD increase in IGF-II (∼265 ng/mL) on risk of high vs. low grade disease as 1.14 (95% CI: 1.00, 1.31). Because of the potential for pleiotropy of the genetic instruments, these findings can only causally implicate the IGF pathway in general, not any one specific biomarker.

Gene and pathway level analyses of germline DNA-repair gene variants and prostate cancer susceptibility using the iCOGS-genotyping array.

BACKGROUND: Germline mutations within DNA-repair genes are implicated in susceptibility to multiple forms of cancer. For prostate cancer (PrCa), rare mutations in BRCA2 and BRCA1 give rise to moderately elevated risk, whereas two of B100 common, low-penetrance PrCa susceptibility variants identified so far by genome-wide association studies implicate RAD51B and RAD23B. METHODS: Genotype data from the iCOGS array were imputed to the 1000 genomes phase 3 reference panel for 21 780 PrCa cases and 21 727 controls from the Prostate Cancer Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium. We subsequently performed single variant, gene and pathway-level analyses using 81 303 SNPs within 20 Kb of a panel of 179 DNA-repair genes. RESULTS: Single SNP analyses identified only the previously reported association with RAD51B. Gene-level analyses using the SKAT-C test from the SNP-set (Sequence) Kernel Association Test (SKAT) identified a significant association with PrCa for MSH5. Pathway-level analyses suggested a possible role for the translesion synthesis pathway in PrCa risk and Homologous recombination/Fanconi Anaemia pathway for PrCa aggressiveness, even though after adjustment for multiple testing these did not remain significant. CONCLUSIONS: MSH5 is a novel candidate gene warranting additional follow-up as a prospective PrCa-risk locus. MSH5 has previously been reported as a pleiotropic susceptibility locus for lung, colorectal and serous ovarian cancers.

Polyunsaturated fatty acids and prostate cancer risk: a Mendelian randomisation analysis from the PRACTICAL consortium.

BACKGROUND: Prostate cancer is a common cancer worldwide with no established modifiable lifestyle factors to guide prevention. The associations between polyunsaturated fatty acids (PUFAs) and prostate cancer risk have been inconsistent. Using Mendelian randomisation, we evaluated associations between PUFAs and prostate cancer risk. METHODS: We used individual-level data from a consortium of 22 721 cases and 23 034 controls of European ancestry. Externally-weighted PUFA-specific polygenic risk scores (wPRSs), with explanatory variation ranging from 0.65 to 33.07%, were constructed and used to evaluate associations with prostate cancer risk per one standard deviation (s.d.) increase in genetically-predicted plasma PUFA levels using multivariable-adjusted unconditional logistic regression. RESULTS: No overall association was observed between the genetically-predicted PUFAs evaluated in this study and prostate cancer risk. However, risk reductions were observed for short-chain PUFAs, linoleic (ORLA=0.95, 95%CI=0.92, 0.98) and α-linolenic acids (ORALA=0.96, 95%CI=0.93, 0.98), among men <62 years; whereas increased risk was found among men ⩾62 years for LA (ORLA=1.04, 95%CI=1.01, 1.07). For long-chain PUFAs (i.e., arachidonic, eicosapentaenoic, and docosapentaenoic acids), increased risks were observed among men <62 years (ORAA=1.05, 95%CI=1.02, 1.08; OREPA=1.04, 95%CI=1.01, 1.06; ORDPA=1.05, 95%CI=1.02, 1.08). CONCLUSION: Results from this study suggest that circulating ω-3 and ω-6 PUFAs may have a different role in the aetiology of early- and late-onset prostate cancer.

Pubertal development and prostate cancer risk: Mendelian randomization study in a population-based cohort.

BACKGROUND: Epidemiological studies have observed a positive association between an earlier age at sexual development and prostate cancer, but markers of sexual maturation in boys are imprecise and observational estimates are likely to suffer from a degree of uncontrolled confounding. To obtain causal estimates, we examined the role of pubertal development in prostate cancer using genetic polymorphisms associated with Tanner stage in adolescent boys in a Mendelian randomization (MR) approach. METHODS: We derived a weighted genetic risk score for pubertal development, combining 13 SNPs associated with male Tanner stage. A higher score indicated a later puberty onset. We examined the association of this score with prostate cancer risk, stage and grade in the UK-based ProtecT case-control study (n = 2,927), and used the PRACTICAL consortium (n = 43,737) as a replication sample. RESULTS: In ProtecT, the puberty genetic score was inversely associated with prostate cancer grade (odds ratio (OR) of high- vs. low-grade cancer, per tertile of the score: 0.76; 95 % CI, 0.64-0.89). In an instrumental variable estimation of the causal OR, later physical development in adolescence (equivalent to a difference of one Tanner stage between pubertal boys of the same age) was associated with a 77 % (95 % CI, 43-91 %) reduced odds of high Gleason prostate cancer. In PRACTICAL, the puberty genetic score was associated with prostate cancer stage (OR of advanced vs. localized cancer, per tertile: 0.95; 95 % CI, 0.91-1.00) and prostate cancer-specific mortality (hazard ratio amongst cases, per tertile: 0.94; 95 % CI, 0.90-0.98), but not with disease grade. CONCLUSIONS: Older age at sexual maturation is causally linked to a reduced risk of later prostate cancer, especially aggressive disease.

Fine-mapping identifies multiple prostate cancer risk loci at 5p15, one of which associates with TERT expression.

Associations between single nucleotide polymorphisms (SNPs) at 5p15 and multiple cancer types have been reported. We have previously shown evidence for a strong association between prostate cancer (PrCa) risk and rs2242652 at 5p15, intronic in the telomerase reverse transcriptase (TERT) gene that encodes TERT. To comprehensively evaluate the association between genetic variation across this region and PrCa, we performed a fine-mapping analysis by genotyping 134 SNPs using a custom Illumina iSelect array or Sequenom MassArray iPlex, followed by imputation of 1094 SNPs in 22 301 PrCa cases and 22 320 controls in The PRACTICAL consortium. Multiple stepwise logistic regression analysis identified four signals in the promoter or intronic regions of TERT that independently associated with PrCa risk. Gene expression analysis of normal prostate tissue showed evidence that SNPs within one of these regions also associated with TERT expression, providing a potential mechanism for predisposition to disease.

The effects of height and BMI on prostate cancer incidence and mortality: a Mendelian randomization study in 20,848 cases and 20,214 controls from the PRACTICAL consortium.

BACKGROUND: Epidemiological studies suggest a potential role for obesity and determinants of adult stature in prostate cancer risk and mortality, but the relationships described in the literature are complex. To address uncertainty over the causal nature of previous observational findings, we investigated associations of height- and adiposity-related genetic variants with prostate cancer risk and mortality. METHODS: We conducted a case-control study based on 20,848 prostate cancers and 20,214 controls of European ancestry from 22 studies in the PRACTICAL consortium. We constructed genetic risk scores that summed each man's number of height and BMI increasing alleles across multiple single nucleotide polymorphisms robustly associated with each phenotype from published genome-wide association studies. RESULTS: The genetic risk scores explained 6.31 and 1.46% of the variability in height and BMI, respectively. There was only weak evidence that genetic variants previously associated with increased BMI were associated with a lower prostate cancer risk (odds ratio per standard deviation increase in BMI genetic score 0.98; 95% CI 0.96, 1.00; p = 0.07). Genetic variants associated with increased height were not associated with prostate cancer incidence (OR 0.99; 95% CI 0.97, 1.01; p = 0.23), but were associated with an increase (OR 1.13; 95 % CI 1.08, 1.20) in prostate cancer mortality among low-grade disease (p heterogeneity, low vs. high grade <0.001). Genetic variants associated with increased BMI were associated with an increase (OR 1.08; 95 % CI 1.03, 1.14) in all-cause mortality among men with low-grade disease (p heterogeneity = 0.03). CONCLUSIONS: We found little evidence of a substantial effect of genetically elevated height or BMI on prostate cancer risk, suggesting that previously reported observational associations may reflect common environmental determinants of height or BMI and prostate cancer risk. Genetically elevated height and BMI were associated with increased mortality (prostate cancer-specific and all-cause, respectively) in men with low-grade disease, a potentially informative but novel finding that requires replication.

Genome-wide association study identifies new prostate cancer susceptibility loci.

Prostate cancer (PrCa) is the most common non-skin cancer diagnosed among males in developed countries and the second leading cause of cancer mortality, yet little is known regarding its etiology and factors that influence clinical outcome. Genome-wide association studies (GWAS) of PrCa have identified at least 30 distinct loci associated with small differences in risk. We conducted a GWAS in 2782 advanced PrCa cases (Gleason grade ≥ 8 or tumor stage C/D) and 4458 controls with 571 243 single nucleotide polymorphisms (SNPs). Based on in silico replication of 4679 SNPs (Stage 1, P < 0.02) in two published GWAS with 7358 PrCa cases and 6732 controls, we identified a new susceptibility locus associated with overall PrCa risk at 2q37.3 (rs2292884, P= 4.3 × 10(-8)). We also confirmed a locus suggested by an earlier GWAS at 12q13 (rs902774, P= 8.6 × 10(-9)). The estimated per-allele odds ratios for these loci (1.14 for rs2292884 and 1.17 for rs902774) did not differ between advanced and non-advanced PrCa (case-only test for heterogeneity P= 0.72 and P= 0.61, respectively). Further studies will be needed to assess whether these or other loci are differentially associated with PrCa subtypes.

Common genetic variants associated with disease from genome-wide association studies are mutually exclusive in prostate cancer and rheumatoid arthritis.

UNLABELLED: WHAT'S KNOWN ON THE SUBJECT? AND WHAT DOES THE STUDY ADD?: The link between inflammation and cancer has long been reported and inflammation is thought to play a role in the pathogenesis of many cancers, including prostate cancer (PrCa). Over the last 5 years, genome-wide association studies (GWAS) have reported numerous susceptibility loci that predispose individuals to many different traits. The present study aims to ascertain if there are common genetic risk profiles that might predispose individuals to both PrCa and the autoimmune inflammatory condition, rheumatoid arthritis. These results could have potential public heath impact in terms of screening and chemoprevention. OBJECTIVES: To investigate if potential common pathways exist for the pathogenesis of autoimmune disease and prostate cancer (PrCa). To ascertain if the single nucleotide polymorphisms (SNPs) reported by genome-wide association studies (GWAS) as being associated with susceptibility to PrCa are also associated with susceptibility to the autoimmune disease rheumatoid arthritis (RA). MATERIALS AND METHODS: The original Wellcome Trust Case Control Consortium (WTCCC) UK RA GWAS study was expanded to include a total of 3221 cases and 5272 controls. In all, 37 germline autosomal SNPs at genome-wide significance associated with PrCa risk were identified from a UK/Australian PrCa GWAS. Allele frequencies were compared for these 37 SNPs between RA cases and controls using a chi-squared trend test and corrected for multiple testing (Bonferroni). RESULTS: In all, 33 SNPs were able to be analysed in the RA dataset. Proxies could not be located for the SNPs in 3q26, 5p15 and for two SNPs in 17q12. After applying a Bonferroni correction for the number of SNPs tested, the SNP mapping to CCHCR1 (rs130067) retained statistically significant evidence for association (P = 6 × 10(-4) ; odds ratio [OR] = 1.15, 95% CI: 1.06-1.24); this has also been associated with psoriasis. However, further analyses showed that the association of this allele was due to confounding by RA-associated HLA-DRB1 alleles. CONCLUSIONS: There is currently no evidence that SNPs associated with PrCa at genome-wide significance are associated with the development of RA. Studies like this are important in determining if common genetic risk profiles might predispose individuals to many diseases, which could have implications for public health in terms of screening and chemoprevention.

Clinical implications of family history of prostate cancer and genetic risk single nucleotide polymorphism (SNP) profiles in an active surveillance cohort.

OBJECTIVES: To explore the potential prognostic role of family history (FH) of prostate cancer and prostate cancer risk single nucleotide polymorphisms (SNPs) in patients undergoing active surveillance (AS) for prostate cancer. This is the first study to date, which has investigated the potential prognostic role of SNP profiles in an AS cohort PATIENTS AND METHODS: FH data were collected from patients in the Royal Marsden Hospital AS study. In all, 39 prostate cancer-risk SNPs identified from published genome wide association studies (GWAS) were genotyped using the Sequenom Platform and TaqMan™ assays from available DNA. The cumulative genetic-risk scores for each patient were then calculated using the weighted effect estimated from previous GWAS (log-additive model). FH status and the genetic-risk scores were assessed against adverse outcomes in AS, time to treatment and adverse histology on repeat biopsy, using univariable and multivariable Cox regression models to address time to treatment; and binary logistic regression to address biopsy upgrade. RESULTS: Of 471 patients, 55 (13.6%) had adverse histology on repeat biopsies and 145 (30.8%) had deferred treatment. On univariate analysis, there was no significant relationship between FH of prostate cancer in any degree of relation, and adverse histology or time to treatment. For risk score analyses, 386 patients' DNA was studied; and there was also no relationship found between the calculated genetic risk scores and adverse histology or time to treatment (P = 0.573 and P = 0.965, respectively). The retrospective study design and the few events were the main limitation of the study. CONCLUSIONS: There is currently insufficient data to support the use of FH status or prostate cancer SNP profile risk scores as prognostic factors in AS and these should not be used to influence management decisions. As more genetic variants are discovered this may change and should be reassessed in multicentre AS cohorts.

A risk prediction algorithm based on family history and common genetic variants: application to prostate cancer with potential clinical impact.

Genome wide association studies have identified several single nucleotide polymorphisms (SNPs) that are independently associated with small increments in risk of prostate cancer, opening up the possibility for using such variants in risk prediction. Using segregation analysis of population-based samples of 4,390 families of prostate cancer patients from the UK and Australia, and assuming all familial aggregation has genetic causes, we previously found that the best model for the genetic susceptibility to prostate cancer was a mixed model of inheritance that included both a recessive major gene component and a polygenic component (P) that represents the effect of a large number of genetic variants each of small effect, where . Based on published studies of 26 SNPs that are currently known to be associated with prostate cancer, we have extended our model to incorporate these SNPs by decomposing the polygenic component into two parts: a polygenic component due to the known susceptibility SNPs, , and the residual polygenic component due to the postulated but as yet unknown genetic variants, . The resulting algorithm can be used for predicting the probability of developing prostate cancer in the future based on both SNP profiles and explicit family history information. This approach can be applied to other diseases for which population-based family data and established risk variants exist.

Identification of new genetic risk factors for prostate cancer.

There is evidence that a substantial part of genetic predisposition to prostate cancer (PCa) may be due to lower penetrance genes which are found by genome-wide association studies. We have recently conducted such a study and seven new regions of the genome linked to PCa risk have been identified. Three of these loci contain candidate susceptibility genes: MSMB, LMTK2 and KLK2/3. The MSMB and KLK2/3 genes may be useful for PCa screening, and the LMTK2 gene might provide a potential therapeutic target. Together with results from other groups, there are now 23 germline genetic variants which have been reported. These results have the potential to be developed into a genetic test. However, we consider that marketing of tests to the public is premature, as PCa risk can not be evaluated fully at this stage and the appropriate screening protocols need to be developed. Follow-up validation studies, as well as studies to explore the psychological implications of genetic profile testing, will be vital prior to roll out into healthcare.

Association analyses of more than 140,000 men identify 63 new prostate cancer susceptibility loci.

Genome-wide association studies (GWAS) and fine-mapping efforts to date have identified more than 100 prostate cancer (PrCa)-susceptibility loci. We meta-analyzed genotype data from a custom high-density array of 46,939 PrCa cases and 27,910 controls of European ancestry with previously genotyped data of 32,255 PrCa cases and 33,202 controls of European ancestry. Our analysis identified 62 novel loci associated (P < 5.0 × 10-8) with PrCa and one locus significantly associated with early-onset PrCa (≤55 years). Our findings include missense variants rs1800057 (odds ratio (OR) = 1.16; P = 8.2 × 10-9; G>C, p.Pro1054Arg) in ATM and rs2066827 (OR = 1.06; P = 2.3 × 10-9; T>G, p.Val109Gly) in CDKN1B. The combination of all loci captured 28.4% of the PrCa familial relative risk, and a polygenic risk score conferred an elevated PrCa risk for men in the ninetieth to ninety-ninth percentiles (relative risk = 2.69; 95% confidence interval (CI): 2.55-2.82) and first percentile (relative risk = 5.71; 95% CI: 5.04-6.48) risk stratum compared with the population average. These findings improve risk prediction, enhance fine-mapping, and provide insight into the underlying biology of PrCa1.

Polygenic hazard score to guide screening for aggressive prostate cancer: development and validation in large scale cohorts.

OBJECTIVES: To develop and validate a genetic tool to predict age of onset of aggressive prostate cancer (PCa) and to guide decisions of who to screen and at what age. DESIGN: Analysis of genotype, PCa status, and age to select single nucleotide polymorphisms (SNPs) associated with diagnosis. These polymorphisms were incorporated into a survival analysis to estimate their effects on age at diagnosis of aggressive PCa (that is, not eligible for surveillance according to National Comprehensive Cancer Network guidelines; any of Gleason score ≥7, stage T3-T4, PSA (prostate specific antigen) concentration ≥10 ng/L, nodal metastasis, distant metastasis). The resulting polygenic hazard score is an assessment of individual genetic risk. The final model was applied to an independent dataset containing genotype and PSA screening data. The hazard score was calculated for these men to test prediction of survival free from PCa. SETTING: Multiple institutions that were members of international PRACTICAL consortium. PARTICIPANTS: All consortium participants of European ancestry with known age, PCa status, and quality assured custom (iCOGS) array genotype data. The development dataset comprised 31 747 men; the validation dataset comprised 6411 men. MAIN OUTCOME MEASURES: Prediction with hazard score of age of onset of aggressive cancer in validation set. RESULTS: In the independent validation set, the hazard score calculated from 54 single nucleotide polymorphisms was a highly significant predictor of age at diagnosis of aggressive cancer (z=11.2, P<10-16). When men in the validation set with high scores (>98th centile) were compared with those with average scores (30th-70th centile), the hazard ratio for aggressive cancer was 2.9 (95% confidence interval 2.4 to 3.4). Inclusion of family history in a combined model did not improve prediction of onset of aggressive PCa (P=0.59), and polygenic hazard score performance remained high when family history was accounted for. Additionally, the positive predictive value of PSA screening for aggressive PCa was increased with increasing polygenic hazard score. CONCLUSIONS: Polygenic hazard scores can be used for personalised genetic risk estimates that can predict for age at onset of aggressive PCa.

Reducing GWAS Complexity.

Genome-wide association studies (GWAS) have revealed numerous genomic 'hits' associated with complex phenotypes. In most cases these hits, along with surrogate genetic variation as measure by numerous single nucleotide polymorphisms (SNPs) that are in linkage disequilibrium, are not in coding genes making assignment of functionality or causality intractable. Here we propose that fine-mapping along with the matching of risk SNPs at chromatin biofeatures lessen this complexity by reducing the number of candidate functional/causal SNPs. For example, we show here that only on average 2 SNPs per prostate cancer risk locus are likely candidates for functionality/causality; we further propose that this manageable number should be taken forward in mechanistic studies. The candidate SNPs can be looked up for each prostate cancer risk region in 2 recent publications in 2015 (1,2) from our groups.