Appraising the role of previously reported risk factors in epithelial ovarian cancer risk: A Mendelian randomization analysis

BACKGROUND

Various risk factors have been associated with epithelial ovarian cancer risk in observational epidemiological studies. However, the causal nature of the risk factors reported, and thus their suitability as effective intervention targets, is unclear given the susceptibility of conventional observational designs to residual confounding and reverse causation. Mendelian randomization (MR) uses genetic variants as proxies for risk factors to strengthen causal inference in observational studies. We used MR to evaluate the association of 12 previously reported risk factors (reproductive, anthropometric, clinical, lifestyle, and molecular factors) with risk of invasive epithelial ovarian cancer, invasive epithelial ovarian cancer histotypes, and low malignant potential tumours.

METHODS AND FINDINGS

Genetic instruments to proxy 12 risk factors were constructed by identifying single nucleotide polymorphisms (SNPs) that were robustly (P < 5 × 10-8) and independently associated with each respective risk factor in previously reported genome-wide association studies. These risk factors included genetic liability to 3 factors (endometriosis, polycystic ovary syndrome, type 2 diabetes) scaled to reflect a 50% higher odds liability to disease. We obtained summary statistics for the association of these SNPs with risk of overall and histotype-specific invasive epithelial ovarian cancer (22,406 cases; 40,941 controls) and low malignant potential tumours (3,103 cases; 40,941 controls) from the Ovarian Cancer Association Consortium (OCAC). The OCAC dataset comprises 63 genotyping project/case-control sets with participants of European ancestry recruited from 14 countries (US, Australia, Belarus, Germany, Belgium, Denmark, Finland, Norway, Canada, Poland, UK, Spain, Netherlands, and Sweden). SNPs were combined into multi-allelic inverse-variance-weighted fixed or random effects models to generate effect estimates and 95% confidence intervals (CIs). Three complementary sensitivity analyses were performed to examine violations of MR assumptions: MR-Egger regression and weighted median and mode estimators. A Bonferroni-corrected P value threshold was used to establish strong evidence (P < 0.0042) and suggestive evidence (0.0042 < P < 0.05) for associations. In MR analyses, there was strong or suggestive evidence that 2 of the 12 risk factors were associated with invasive epithelial ovarian cancer and 8 of the 12 were associated with 1 or more invasive epithelial ovarian cancer histotypes. There was strong evidence that genetic liability to endometriosis was associated with an increased risk of invasive epithelial ovarian cancer (odds ratio [OR] per 50% higher odds liability: 1.10, 95% CI 1.06-1.15; P = 6.94 × 10-7) and suggestive evidence that lifetime smoking exposure was associated with an increased risk of invasive epithelial ovarian cancer (OR per unit increase in smoking score: 1.36, 95% CI 1.04-1.78; P = 0.02). In analyses examining histotypes and low malignant potential tumours, the strongest associations found were between height and clear cell carcinoma (OR per SD increase: 1.36, 95% CI 1.15-1.61; P = 0.0003); age at natural menopause and endometrioid carcinoma (OR per year later onset: 1.09, 95% CI 1.02-1.16; P = 0.007); and genetic liability to polycystic ovary syndrome and endometrioid carcinoma (OR per 50% higher odds liability: 0.89, 95% CI 0.82-0.96; P = 0.002). There was little evidence for an association of genetic liability to type 2 diabetes, parity, or circulating levels of 25-hydroxyvitamin D and sex hormone binding globulin with ovarian cancer or its subtypes. The primary limitations of this analysis include the modest statistical power for analyses of risk factors in relation to some less common ovarian cancer histotypes (low grade serous, mucinous, and clear cell carcinomas), the inability to directly examine the association of some ovarian cancer risk factors that did not have robust genetic variants available to serve as proxies (e.g., oral contraceptive use, hormone replacement therapy), and the assumption of linear relationships between risk factors and ovarian cancer risk.

CONCLUSIONS

Our comprehensive examination of possible aetiological drivers of ovarian carcinogenesis using germline genetic variants to proxy risk factors supports a role for few of these factors in invasive epithelial ovarian cancer overall and suggests distinct aetiologies across histotypes. The identification of novel risk factors remains an important priority for the prevention of epithelial ovarian cancer.

Runs of homozygosity and testicular cancer risk

BACKGROUND

Testicular germ cell tumour (TGCT) is highly heritable but > 50% of the genetic risk remains unexplained. Epidemiological observation of greater relative risk to brothers of men with TGCT compared to sons has long alluded to recessively acting TGCT genetic susceptibility factors, but to date none have been reported. Runs of homozygosity (RoH) are a signature indicating underlying recessively acting alleles and have been associated with increased risk of other cancer types.

OBJECTIVE

To examine whether RoH are associated with TGCT risk.

METHODS

We performed a genome-wide RoH analysis using GWAS data from 3206 TGCT cases and 7422 controls uniformly genotyped using the OncoArray platform.

RESULTS

Global measures of homozygosity were not significantly different between cases and controls, and the frequency of individual consensus RoH was not significantly different between cases and controls, after correction for multiple testing. RoH at three regions, 11p13-11p14.3, 5q14.1-5q22.3 and 13q14.11-13q.14.13, were, however, nominally statistically significant at p < 0.01. Intriguingly, RoH200 at 11p13-11p14.3 encompasses Wilms tumour 1 (WT1), a recognized cancer susceptibility gene with roles in sex determination and developmental transcriptional regulation, processes repeatedly implicated in TGCT aetiology.

DISCUSSION AND CONCLUSION

Overall, our data do not support a major role in the risk of TGCT for recessively acting alleles acting through homozygosity, as measured by RoH in outbred populations of cases and controls.

Using prognosis to guide inclusion criteria, define standardised endpoints and stratify follow-up in active surveillance for prostate cancer

OBJECTIVES

To test whether using disease prognosis can inform a rational approach to active surveillance (AS) for early prostate cancer.

PATIENTS AND METHODS

We previously developed the Cambridge Prognostics Groups (CPG) classification, a five-tiered model that uses prostate-specific antigen (PSA), Grade Group and Stage to predict cancer survival outcomes. We applied the CPG model to a UK and a Swedish prostate cancer cohort to test differences in prostate cancer mortality (PCM) in men managed conservatively or by upfront treatment in CPG2 and 3 (which subdivides the intermediate-risk classification) vs CPG1 (low-risk). We then applied the CPG model to a contemporary UK AS cohort, which was optimally characterised at baseline for disease burden, to identify predictors of true prognostic progression. Results were re-tested in an external AS cohort from Spain.

RESULTS

In a UK cohort (n = 3659) the 10-year PCM was 2.3% in CPG1, 1.5%/3.5% in treated/untreated CPG2, and 1.9%/8.6% in treated/untreated CPG3. In the Swedish cohort (n = 27 942) the10-year PCM was 1.0% in CPG1, 2.2%/2.7% in treated/untreated CPG2, and 6.1%/12.5% in treated/untreated CPG3. We then tested using progression to CPG3 as a hard endpoint in a modern AS cohort (n = 133). During follow-up (median 3.5 years) only 6% (eight of 133) progressed to CPG3. Predictors of progression were a PSA density ≥0.15 ng/mL/mL and CPG2 at diagnosis. Progression occurred in 1%, 8% and 21% of men with neither factor, only one, or both, respectively. In an independent Spanish AS cohort (n = 143) the corresponding rates were 3%, 10% and 14%, respectively.

CONCLUSION

Using disease prognosis allows a rational approach to inclusion criteria, discontinuation triggers and risk-stratified management in AS.

The functional ALDH2 polymorphism is associated with breast cancer risk: A pooled analysis from the Breast Cancer Association Consortium

BACKGROUND

Epidemiological studies consistently indicate that alcohol consumption is an independent risk factor for female breast cancer (BC). Although the aldehyde dehydrogenase 2 (ALDH2) polymorphism (rs671: Glu>Lys) has a strong effect on acetaldehyde metabolism, the association of rs671 with BC risk and its interaction with alcohol intake have not been fully elucidated. We conducted a pooled analysis of 14 case-control studies, with individual data on Asian ancestry women participating in the Breast Cancer Association Consortium.

METHODS

We included 12,595 invasive BC cases and 12,884 controls for the analysis of rs671 and BC risk, and 2,849 invasive BC cases and 3,680 controls for the analysis of the gene-environment interaction between rs671 and alcohol intake for BC risk. The pooled odds ratios (OR) with 95% confidence intervals (CI) associated with rs671 and its interaction with alcohol intake for BC risk were estimated using logistic regression models.

RESULTS

The Lys/Lys genotype of rs671 was associated with increased BC risk (OR = 1.16, 95% CI 1.03-1.30, p = 0.014). According to tumor characteristics, the Lys/Lys genotype was associated with estrogen receptor (ER)-positive BC (OR = 1.19, 95% CI 1.05-1.36, p = 0.008), progesterone receptor (PR)-positive BC (OR = 1.19, 95% CI 1.03-1.36, p = 0.015), and human epidermal growth factor receptor 2 (HER2)-negative BC (OR = 1.25, 95% CI 1.05-1.48, p = 0.012). No evidence of a gene-environment interaction was observed between rs671 and alcohol intake (p = 0.537).

CONCLUSION

This study suggests that the Lys/Lys genotype confers susceptibility to BC risk among women of Asian ancestry, particularly for ER-positive, PR-positive, and HER2-negative tumor types.

Sex hormone binding globulin and risk of breast cancer: a Mendelian randomization study

BACKGROUND

There are observational data suggesting an inverse association between circulating concentrations of sex hormone binding globulin (SHBG) and risk of postmenopausal breast cancer. However, causality is uncertain and few studies have investigated this association by tumour receptor status. We aimed to investigate these associations under the causal framework of Mendelian randomization (MR).

METHODS

We used summary association estimates extracted from published genome-wide association study (GWAS) meta-analyses for SHBG and breast cancer, to perform two-sample MR analyses. Summary statistics were available for 122 977 overall breast cancer cases, of which 69 501 were estrogen receptor positive (ER+ve) and 21 468 were ER-ve, and 105 974 controls. To control for potential horizontal pleiotropy acting via body mass index (BMI), we performed multivariable inverse-variance weighted (IVW) MR as the main analysis, with the robustness of this approach further tested in sensitivity analyses.

RESULTS

The multivariable IVW MR analysis indicated a lower risk of overall (odds ratio [OR]: 0.94; 95% confidence interval [CI]: 0.90, 0.98; P: 0.006) and ER+ve (OR: 0.92; 95% CI: 0.87, 0.97; P: 0.003) breast cancer, and a higher risk of ER-ve disease (OR: 1.09; 95% CI: 1.00, 1.18; P: 0.047) per 25 nmol/L higher SHBG levels. Sensitivity analyses were consistent with the findings of the main analysis.

CONCLUSIONS

We corroborated the previous literature evidence coming from observational studies for a potentially causal inverse association between SHBG concentrations and risk of ER+ve breast cancer, but our findings also suggested a potential novel positive association with ER-ve disease that warrants further investigation, given the low prior probability of being true.

Association analyses identify 31 new risk loci for colorectal cancer susceptibility

Colorectal cancer (CRC) is a leading cause of cancer-related death worldwide, and has a strong heritable basis. We report a genome-wide association analysis of 34,627 CRC cases and 71,379 controls of European ancestry that identifies SNPs at 31 new CRC risk loci. We also identify eight independent risk SNPs at the new and previously reported European CRC loci, and a further nine CRC SNPs at loci previously only identified in Asian populations. We use in situ promoter capture Hi-C (CHi-C), gene expression, and in silico annotation methods to identify likely target genes of CRC SNPs. Whilst these new SNP associations implicate target genes that are enriched for known CRC pathways such as Wnt and BMP, they also highlight novel pathways with no prior links to colorectal tumourigenesis. These findings provide further insight into CRC susceptibility and enhance the prospects of applying genetic risk scores to personalised screening and prevention.

Consistent Biopsy Quality and Gleason Grading Within the Global Active Surveillance Global Action Plan 3 Initiative: A Prerequisite for Future Studies

Within the Movember Foundation's Global Action Plan Prostate Cancer Active Surveillance (GAP3) initiative, 25 centers across the globe collaborate to standardize active surveillance (AS) protocols for men with low-risk prostate cancer (PCa). A centralized PCa AS database, comprising data of more than 15000 patients worldwide, was created. Comparability of the histopathology between the different cohorts was assessed by a centralized pathology review of 445 biopsies from 15 GAP3 centers. Grade group 1 (Gleason score 6) in 85% and grade group ≥2 (Gleason score ≥7) in 15% showed 89% concordance at review with moderate agreement (κ=0.56). Average biopsy core length was similar among the analyzed cohorts. Recently established highly adverse pathologies, including cribriform and/or intraductal carcinoma, were observed in 3.6% of the reviewed biopsies. In conclusion, the centralized pathology review of 445 biopsies revealed comparable histopathology among the 15 GAP3 centers with a low frequency of high-risk features. This enables further data analyses-without correction-toward uniform global AS guidelines for men with low-risk PCa. PATIENT SUMMARY: Movember Foundation's Global Action Plan Prostate Cancer Active Surveillance (GAP3) initiative combines data from 15000 men with low-risk prostate cancer (PCa) across the globe to standardize active surveillance protocols. Histopathology review confirmed that the histopathology was consistent with low-risk PCa in most men and comparable between different centers.

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

In the version of this article initially published, the name of author Manuela Gago-Dominguez was misspelled as Manuela Gago Dominguez. The error has been corrected in the HTML and PDF version of the article.

Shared heritability and functional enrichment across six solid cancers

Quantifying the genetic correlation between cancers can provide important insights into the mechanisms driving cancer etiology. Using genome-wide association study summary statistics across six cancer types based on a total of 296,215 cases and 301,319 controls of European ancestry, here we estimate the pair-wise genetic correlations between breast, colorectal, head/neck, lung, ovary and prostate cancer, and between cancers and 38 other diseases. We observed statistically significant genetic correlations between lung and head/neck cancer (rg = 0.57, p = 4.6 × 10-8), breast and ovarian cancer (rg = 0.24, p = 7 × 10-5), breast and lung cancer (rg = 0.18, p =1.5 × 10-6) and breast and colorectal cancer (rg = 0.15, p = 1.1 × 10-4). We also found that multiple cancers are genetically correlated with non-cancer traits including smoking, psychiatric diseases and metabolic characteristics. Functional enrichment analysis revealed a significant excess contribution of conserved and regulatory regions to cancer heritability. Our comprehensive analysis of cross-cancer heritability suggests that solid tumors arising across tissues share in part a common germline genetic basis.

Author Correction: Genome-wide association study identifies susceptibility loci for B-cell childhood acute lymphoblastic leukemia

The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.

Author Correction: Germline variation at 8q24 and prostate cancer risk in men of European ancestry

The original version of this Article contained an error in the spelling of the author Manuela Gago-Dominguez, which was incorrectly given as Manuela G. Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.

Author Correction: Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma

The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article. Furthermore, in the original HTML version of this Article, the order of authors within the author list was incorrect. The PRACTICAL consortium was incorrectly listed after Richard S. Houlston and should have been listed after Nora Pashayan. This error has been corrected in the HTML version of the Article; the PDF version was correct at the time of publication.

Author Correction: Genome-wide association study of classical Hodgkin lymphoma identifies key regulators of disease susceptibility

The original version of this Article contained an error in the spelling of a member of the PRACTICAL Consortium, Manuela Gago-Dominguez, which was incorrectly given as Manuela Gago Dominguez. This has now been corrected in both the PDF and HTML versions of the Article.

Circulating Metabolic Biomarkers of Screen-Detected Prostate Cancer in the ProtecT Study

BACKGROUND

Whether associations between circulating metabolites and prostate cancer are causal is unknown. We report on the largest study of metabolites and prostate cancer (2,291 cases and 2,661 controls) and appraise causality for a subset of the prostate cancer-metabolite associations using two-sample Mendelian randomization (MR).

METHODS

The case-control portion of the study was conducted in nine UK centers with men ages 50-69 years who underwent prostate-specific antigen screening for prostate cancer within the Prostate Testing for Cancer and Treatment (ProtecT) trial. Two data sources were used to appraise causality: a genome-wide association study (GWAS) of metabolites in 24,925 participants and a GWAS of prostate cancer in 44,825 cases and 27,904 controls within the Association Group to Investigate Cancer Associated Alterations in the Genome (PRACTICAL) consortium.

RESULTS

Thirty-five metabolites were strongly associated with prostate cancer (P < 0.0014, multiple-testing threshold). These fell into four classes: (i) lipids and lipoprotein subclass characteristics (total cholesterol and ratios, cholesterol esters and ratios, free cholesterol and ratios, phospholipids and ratios, and triglyceride ratios); (ii) fatty acids and ratios; (iii) amino acids; (iv) and fluid balance. Fourteen top metabolites were proxied by genetic variables, but MR indicated these were not causal.

CONCLUSIONS

We identified 35 circulating metabolites associated with prostate cancer presence, but found no evidence of causality for those 14 testable with MR. Thus, the 14 MR-tested metabolites are unlikely to be mechanistically important in prostate cancer risk.

IMPACT

The metabolome provides a promising set of biomarkers that may aid prostate cancer classification.

AA9int: SNP interaction pattern search using non-hierarchical additive model set

Motivation

The use of single nucleotide polymorphism (SNP) interactions to predict complex diseases is getting more attention during the past decade, but related statistical methods are still immature. We previously proposed the SNP Interaction Pattern Identifier (SIPI) approach to evaluate 45 SNP interaction patterns/patterns. SIPI is statistically powerful but suffers from a large computation burden. For large-scale studies, it is necessary to use a powerful and computation-efficient method. The objective of this study is to develop an evidence-based mini-version of SIPI as the screening tool or solitary use and to evaluate the impact of inheritance mode and model structure on detecting SNP-SNP interactions.

Results

We tested two candidate approaches: the 'Five-Full' and 'AA9int' method. The Five-Full approach is composed of the five full interaction models considering three inheritance modes (additive, dominant and recessive). The AA9int approach is composed of nine interaction models by considering non-hierarchical model structure and the additive mode. Our simulation results show that AA9int has similar statistical power compared to SIPI and is superior to the Five-Full approach, and the impact of the non-hierarchical model structure is greater than that of the inheritance mode in detecting SNP-SNP interactions. In summary, it is recommended that AA9int is a powerful tool to be used either alone or as the screening stage of a two-stage approach (AA9int+SIPI) for detecting SNP-SNP interactions in large-scale studies.

Availability and implementation

The 'AA9int' and 'parAA9int' functions (standard and parallel computing version) are added in the SIPI R package, which is freely available at https://linhuiyi.github.io/LinHY_Software/.

Supplementary information

Supplementary data are available at Bioinformatics online.

Genome-wide association study implicates immune dysfunction in the development of Hodgkin lymphoma

To further our understanding of inherited susceptibility to Hodgkin lymphoma (HL), we performed a meta-analysis of 7 genome-wide association studies totaling 5325 HL cases and 22 423 control patients. We identify 5 new HL risk loci at 6p21.31 (rs649775; P = 2.11 × 10-10), 6q23.3 (rs1002658; P = 2.97 × 10-8), 11q23.1 (rs7111520; P = 1.44 × 10-11), 16p11.2 (rs6565176; P = 4.00 × 10-8), and 20q13.12 (rs2425752; P = 2.01 × 10-8). Integration of gene expression, histone modification, and in situ promoter capture Hi-C data at the 5 new and 13 known risk loci implicates dysfunction of the germinal center reaction, disrupted T-cell differentiation and function, and constitutive NF-κB activation as mechanisms of predisposition. These data provide further insights into the genetic susceptibility and biology of HL.

Germline variation at 8q24 and prostate cancer risk in men of European ancestry

Chromosome 8q24 is a susceptibility locus for multiple cancers, including prostate cancer. Here we combine genetic data across the 8q24 susceptibility region from 71,535 prostate cancer cases and 52,935 controls of European ancestry to define the overall contribution of germline variation at 8q24 to prostate cancer risk. We identify 12 independent risk signals for prostate cancer (p < 4.28 × 10-15), including three risk variants that have yet to be reported. From a polygenic risk score (PRS) model, derived to assess the cumulative effect of risk variants at 8q24, men in the top 1% of the PRS have a 4-fold (95%CI = 3.62-4.40) greater risk compared to the population average. These 12 variants account for ~25% of what can be currently explained of the familial risk of prostate cancer by known genetic risk factors. These findings highlight the overwhelming contribution of germline variation at 8q24 on prostate cancer risk which has implications for population risk stratification.

Identification of multiple risk loci and regulatory mechanisms influencing susceptibility to multiple myeloma

Genome-wide association studies (GWAS) have transformed our understanding of susceptibility to multiple myeloma (MM), but much of the heritability remains unexplained. We report a new GWAS, a meta-analysis with previous GWAS and a replication series, totalling 9974 MM cases and 247,556 controls of European ancestry. Collectively, these data provide evidence for six new MM risk loci, bringing the total number to 23. Integration of information from gene expression, epigenetic profiling and in situ Hi-C data for the 23 risk loci implicate disruption of developmental transcriptional regulators as a basis of MM susceptibility, compatible with altered B-cell differentiation as a key mechanism. Dysregulation of autophagy/apoptosis and cell cycle signalling feature as recurrently perturbed pathways. Our findings provide further insight into the biological basis of MM.

Large-scale Analysis Demonstrates Familial Testicular Cancer to have Polygenic Aetiology

Testicular germ cell tumour (TGCT) is the most common cancer in young men. Multiplex TGCT families have been well reported and analyses of population cancer registries have demonstrated a four- to eightfold risk to male relatives of TGCT patients. Early linkage analysis and recent large-scale germline exome analysis in TGCT cases demonstrate absence of major high-penetrance TGCT susceptibility gene(s). Serial genome-wide association study analyses in sporadic TGCT have in total reported 49 independent risk loci. To date, it has not been demonstrated whether familial TGCT arises due to enrichment of the same common variants underpinning susceptibility to sporadic TGCT or is due to shared environmental/lifestyle factors or disparate rare genetic TGCT susceptibility factors. Here we present polygenic risk score analysis of 37 TGCT susceptibility single-nucleotide polymorphisms in 236 familial and 3931 sporadic TGCT cases, and 12 368 controls, which demonstrates clear enrichment for TGCT susceptibility alleles in familial compared to sporadic cases (p=0.0001), with the majority of familial cases (84-100%) being attributable to polygenic enrichment. These analyses reveal TGCT as the first rare malignancy of early adulthood in which familial clustering is driven by the aggregate effects of polygenic variation in the absence of a major high-penetrance susceptibility gene.

PATIENT SUMMARY

To date, it has been unclear whether familial clusters of testicular germ cell tumour (TGCT) arise due to genetics or shared environmental or lifestyle factors. We present large-scale genetic analyses comparing 236 familial TGCT cases, 3931 isolated TGCT cases, and 12 368 controls. We show that familial TGCT is caused, at least in part, by presence of a higher dose of the same common genetic variants that cause susceptibility to TGCT in general.

Abstract 227: Germline variation at 8q24 and prostate cancer risk in men of European ancestry

We performed an in-depth and well-powered investigation of genetic variation across the cancer susceptibility region at chromosome 8q24 (127.6-129.0 Mb) to search for novel risk variants associated with prostate cancer (PCa) risk in the European ancestry population. We combined genotyped and imputed data from the PRACTICAL/ELLIPSE OncoArray and iCOGS consortia consisting of 71,535 PrCa cases and 52,935 controls of European ancestry. Variants with high imputation quality score (&gt;0.8) were retained for a total of 5,600 overlapping variants between the two datasets. Associations of genetic variants with PCa risk were evaluated using unconditional logistic regression with adjustment for country and ten principal components. The marginal risk estimates for the 5,600 variants that passed quality control were combined by a fixed effects meta-analysis. A meta-stepwise selection was performed on variants marginally associated with PCa risk from the meta results (P&lt;0.05). A polygenic risk score and the contribution to the familial relative risk of PCa were estimated for variants from the final model. Of the 5,600 variants at 8q24 retained for analysis, 1,268 (23%) were associated with PCa risk at P&lt;5x10-8 while 2,772 (49%) were marginally associated at P&lt;0.05. In the stepwise model, 12 variants remained statistically significantly associated with PCa risk with conditional meta p-values between 2.93x10-137 and 4.28x10-15. The independent stepwise signals were confirmed by Joint Analysis of Marginal (JAM) summary statistics, which defined the credible sets of variants driving those signals. Three of the variants (rs1914295, rs190257175, rs12549761) were weakly correlated (r2≤0.17) with any known PCa risk marker, and may define novel association signals. Men in the top 1% of the polygenic risk score distribution had a 3.97-fold relative risk (95%CI=3.87-4.07) compared to men with "average risk" (25th-75th percentiles). The 12 independent signals at 8q24 capture 11.54% (95%CI=9.86-13.65) of the familial relative risk of PCa, which is approximately one quarter of the total PCa familial relative risk explained by known genetic risk factors. Most of the independently associated signals have good evidence for biologic functionality; in particular, many reside within putative transcriptional enhancers and/or binding sites for AR and FOXA1 transcription factors in prostate cell lines. In summary, we defined 12 independent association signals among men of European ancestry, with three of the risk variants representing putative novel association signals. Whereas the individual associations of these variants with PCa risk are relatively modest (ORs&lt;2.0), their cumulative effects are substantial, and their contribution to the overall familial relative risk of PCa is substantially greater than any other known prostate cancer risk locus.

Citation Format: Marco Matejcic, Edward J. Saunders, Tokhir Dadaev, Mark Brook, Ali Amin Al Olama, Fredrick R. Schumacher, Sonja I. Berndt, Sara Benlloch, Kenneth Muir, Koveela Govindasami, Victoria L. Stevens, Susan M. Gapstur, Catherine M. Tangen, Jyotsna Batra, Judith Clements, APCB (Australian Prostate Cancer Bio Resource), Henrik Gronberg, Nora Pashayan, Johanna Schleutker, Demetrius Albanes, Alicja Wolk, Catharine West, Lorelei Mucci, Peter Kraft, Géraldine Cancel-Tassin, Stella Koutros, Karina Dalsgaard Sorensen, Lovise Maehle, Eli Marie Grindedal, Sara Strom, David E. Neal, Freddie C. Hamdy, Jenny L. Donovan, Ruth C. Travis, Robert J. Hamilton, Sue Ann Ingles, Barry Rosenstein, Yong-Jie Lu, Graham G. Giles, Adam S. Kibel, Ana Vega, Jeanette Bensen, Manolis Kogevinas, Fredrik Wiklund, Stephen Chanock, Douglas F. Easton, Rosalind A. Eeles, Zsofia Kote-Jarai, David V. Conti, Christopher A. Haiman. Germline variation at 8q24 and prostate cancer risk in men of European ancestry [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 227.

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.

Fine-mapping of prostate cancer susceptibility loci in a large meta-analysis identifies candidate causal variants

Prostate cancer is a polygenic disease with a large heritable component. A number of common, low-penetrance prostate cancer risk loci have been identified through GWAS. Here we apply the Bayesian multivariate variable selection algorithm JAM to fine-map 84 prostate cancer susceptibility loci, using summary data from a large European ancestry meta-analysis. We observe evidence for multiple independent signals at 12 regions and 99 risk signals overall. Only 15 original GWAS tag SNPs remain among the catalogue of candidate variants identified; the remainder are replaced by more likely candidates. Biological annotation of our credible set of variants indicates significant enrichment within promoter and enhancer elements, and transcription factor-binding sites, including AR, ERG and FOXA1. In 40 regions at least one variant is colocalised with an eQTL in prostate cancer tissue. The refined set of candidate variants substantially increase the proportion of familial relative risk explained by these known susceptibility regions, which highlights the importance of fine-mapping studies and has implications for clinical risk profiling.

Publisher Correction: Evidence that breast cancer risk at the 2q35 locus is mediated through IGFBP5 regulation

This corrects the article DOI: 10.1038/ncomms5999.