Polygenic hazard score is associated with prostate cancer in multi-ethnic populations

Genetic models for cancer have been evaluated using almost exclusively European data, which could exacerbate health disparities. A polygenic hazard score (PHS1) is associated with age at prostate cancer diagnosis and improves screening accuracy in Europeans. Here, we evaluate performance of PHS2 (PHS1, adapted for OncoArray) in a multi-ethnic dataset of 80,491 men (49,916 cases, 30,575 controls). PHS2 is associated with age at diagnosis of any and aggressive (Gleason score ≥ 7, stage T3-T4, PSA ≥ 10 ng/mL, or nodal/distant metastasis) cancer and prostate-cancer-specific death. Associations with cancer are significant within European (n = 71,856), Asian (n = 2,382), and African (n = 6,253) genetic ancestries (p < 10-180). Comparing the 80th/20th PHS2 percentiles, hazard ratios for prostate cancer, aggressive cancer, and prostate-cancer-specific death are 5.32, 5.88, and 5.68, respectively. Within European, Asian, and African ancestries, hazard ratios for prostate cancer are: 5.54, 4.49, and 2.54, respectively. PHS2 risk-stratifies men for any, aggressive, and fatal prostate cancer in a multi-ethnic dataset.

Common genetic and clinical risk factors: Association with fatal prostate cancer in the Cohort of Swedish Men

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Background: Clinical variables (age, family history, and genetics) are commonly used for prostate cancer risk stratification. Recently, polygenic hazard scores (PHS46, PHS166) were validated as associated with age at prostate cancer diagnosis. While polygenic scores, including PHS, are associated with all prostate cancer and are not specific for fatal cancers, PHS46 was also associated with age at prostate cancer death. We evaluated if adding PHS to available clinical variables improves associations with prostate cancer death. Methods: Genotype and phenotype data were obtained from a nested case-control subset (n=3,279; 2,163 were diagnosed with prostate cancer, 278 died of prostate cancer) of the longitudinal, population-based Cohort of Swedish Men. PHS and clinical variables (family history, alcohol intake, smoking, heart disease, hypertension, diabetes history, and body mass index) were independently tested via univariable Cox proportional hazards models for association with age at prostate cancer death. Multivariable Cox models were constructed with clinical variables and PHS. Log-likelihood tests compared models. Results: Median age at last follow-up and at prostate cancer death were 78.0 (IQR: 72.3-84.1) and 81.4 (75.4-86.3) years, respectively. On univariable analysis, PHS46 (HR 3.41 [95% CI 2.78-4.17]), family history (HR 1.72 [1.46-2.03]), alcohol intake (HR 1.74 [1.40-2.15]), and diabetes (HR 0.53 [0.37-0.75]) were each associated with prostate cancer death. A multivariable clinical model including PHS46 improved associations for fatal disease ( p<10−15). On multivariable analysis, PHS46 (HR 2.45 [1.99-2.97]), family history (HR 1.73 [1.48-2.03]), alcohol intake (HR 1.45 [1.19-1.76]), and diabetes (HR 0.62 [0.42-0.90]) all remained associated with prostate cancer death. Similar results were found using the newer PHS166. Conclusions: PHS had the most robust association with fatal prostate cancer in a multivariable model with common clinical risk factors, including family history. Adding PHS to clinical variables may improve individualized prostate cancer risk stratification strategies.

Breast Cancer Risk Genes - Association Analysis in More than 113,000 Women

BACKGROUND

Genetic testing for breast cancer susceptibility is widely used, but for many genes, evidence of an association with breast cancer is weak, underlying risk estimates are imprecise, and reliable subtype-specific risk estimates are lacking.

METHODS

We used a panel of 34 putative susceptibility genes to perform sequencing on samples from 60,466 women with breast cancer and 53,461 controls. In separate analyses for protein-truncating variants and rare missense variants in these genes, we estimated odds ratios for breast cancer overall and tumor subtypes. We evaluated missense-variant associations according to domain and classification of pathogenicity.

RESULTS

Protein-truncating variants in 5 genes (ATM, BRCA1, BRCA2, CHEK2, and PALB2) were associated with a risk of breast cancer overall with a P value of less than 0.0001. Protein-truncating variants in 4 other genes (BARD1, RAD51C, RAD51D, and TP53) were associated with a risk of breast cancer overall with a P value of less than 0.05 and a Bayesian false-discovery probability of less than 0.05. For protein-truncating variants in 19 of the remaining 25 genes, the upper limit of the 95% confidence interval of the odds ratio for breast cancer overall was less than 2.0. For protein-truncating variants in ATM and CHEK2, odds ratios were higher for estrogen receptor (ER)-positive disease than for ER-negative disease; for protein-truncating variants in BARD1, BRCA1, BRCA2, PALB2, RAD51C, and RAD51D, odds ratios were higher for ER-negative disease than for ER-positive disease. Rare missense variants (in aggregate) in ATM, CHEK2, and TP53 were associated with a risk of breast cancer overall with a P value of less than 0.001. For BRCA1, BRCA2, and TP53, missense variants (in aggregate) that would be classified as pathogenic according to standard criteria were associated with a risk of breast cancer overall, with the risk being similar to that of protein-truncating variants.

CONCLUSIONS

The results of this study define the genes that are most clinically useful for inclusion on panels for the prediction of breast cancer risk, as well as provide estimates of the risks associated with protein-truncating variants, to guide genetic counseling. (Funded by European Union Horizon 2020 programs and others.).

Rare Germline Variants in ATM Predispose to Prostate Cancer: A PRACTICAL Consortium Study

BACKGROUND

Germline ATM mutations are suggested to contribute to predisposition to prostate cancer (PrCa). Previous studies have had inadequate power to estimate variant effect sizes.

OBJECTIVE

To precisely estimate the contribution of germline ATM mutations to PrCa risk.

DESIGN, SETTING, AND PARTICIPANTS

We analysed next-generation sequencing data from 13 PRACTICAL study groups comprising 5560 cases and 3353 controls of European ancestry.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Variant Call Format files were harmonised, annotated for rare ATM variants, and classified as tier 1 (likely pathogenic) or tier 2 (potentially deleterious). Associations with overall PrCa risk and clinical subtypes were estimated.

RESULTS AND LIMITATIONS

PrCa risk was higher in carriers of a tier 1 germline ATM variant, with an overall odds ratio (OR) of 4.4 (95% confidence interval [CI]: 2.0-9.5). There was also evidence that PrCa cases with younger age at diagnosis (<65 yr) had elevated tier 1 variant frequencies (p_difference = 0.04). Tier 2 variants were also associated with PrCa risk, with an OR of 1.4 (95% CI: 1.1-1.7).

CONCLUSIONS

Carriers of pathogenic ATM variants have an elevated risk of developing PrCa and are at an increased risk for earlier-onset disease presentation. These results provide information for counselling of men and their families.

PATIENT SUMMARY

In this study, we estimated that men who inherit a likely pathogenic mutation in the ATM gene had an approximately a fourfold risk of developing prostate cancer. In addition, they are likely to develop the disease earlier.

Trans-ancestry genome-wide association meta-analysis of prostate cancer identifies new susceptibility loci and informs genetic risk prediction

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.

Constitutional morphological features and risk of hip osteoarthritis: a case-control study using standard radiographs

OBJECTIVES

To evaluate the risk of association with hip osteoarthritis (OA) of 14 morphological features measured on standard antero-posterior pelvis radiographs.

METHODS

A case-control study of 566 symptomatic unilateral hip OA cases and 1108 controls without hip OA, using the Genetics of OA and Lifestyle database. Unaffected hips of cases were assumed to reflect pre-OA morphology of the contralateral affected hip. ORs with 95% CI adjusted for confounding factors were calculated using logistic regression. Hierarchical clustering on principal component method was used to identify clusters of morphological features. Proportional risk contribution (PRC) of these morphological features in the context of other risk factors of hip OA was estimated using receiver operating characteristic analysis.

RESULTS

All morphological features showed right-left symmetry in controls. Each feature was associated with hip OA after adjusting for age, gender and body mass index. Increased sourcil angle had the strongest association (OR: 6.93, 95% CI 5.16 to 9.32). Three clusters were identified. The PRC varied between individual features, as well as between clusters. It was 35% (95% CI 31% to 40%) for all 14 morphological features, compared to 21% (95% CI 19% to 24%) for all other well-established risk factors.

CONCLUSIONS

Constitutional morphological variation strongly associates with hip OA development and may explain much of its heritability. Relevant morphological measures can be assessed readily on standard radiographs to help predict risk of hip OA. Prospective studies are required to provide further support for causality.

The CHEK2 Variant C.349A>G Is Associated with Prostate Cancer Risk and Carriers Share a Common Ancestor

The identification of recurrent founder variants in cancer predisposing genes may have important implications for implementing cost-effective targeted genetic screening strategies. In this study, we evaluated the prevalence and relative risk of the CHEK2 recurrent variant c.349A>G in a series of 462 Portuguese patients with early-onset and/or familial/hereditary prostate cancer (PrCa), as well as in the large multicentre PRACTICAL case-control study comprising 55,162 prostate cancer cases and 36,147 controls. Additionally, we investigated the potential shared ancestry of the carriers by performing identity-by-descent, haplotype and age estimation analyses using high-density SNP data from 70 variant carriers belonging to 11 different populations included in the PRACTICAL consortium. The CHEK2 missense variant c.349A>G was found significantly associated with an increased risk for PrCa (OR 1.9; 95% CI: 1.1-3.2). A shared haplotype flanking the variant in all carriers was identified, strongly suggesting a common founder of European origin. Additionally, using two independent statistical algorithms, implemented by DMLE+2.3 and ESTIAGE, we were able to estimate the age of the variant between 2300 and 3125 years. By extending the haplotype analysis to 14 additional carrier families, a shared core haplotype was revealed among all carriers matching the conserved region previously identified in the high-density SNP analysis. These findings are consistent with CHEK2 c.349A>G being a founder variant associated with increased PrCa risk, suggesting its potential usefulness for cost-effective targeted genetic screening in PrCa families.

The effect of sample size on polygenic hazard models for prostate cancer

We determined the effect of sample size on performance of polygenic hazard score (PHS) models in prostate cancer. Age and genotypes were obtained for 40,861 men from the PRACTICAL consortium. The dataset included 201,590 SNPs per subject, and was split into training and testing sets. Established-SNP models considered 65 SNPs that had been previously associated with prostate cancer. Discovery-SNP models used stepwise selection to identify new SNPs. The performance of each PHS model was calculated for random sizes of the training set. The performance of a representative Established-SNP model was estimated for random sizes of the testing set. Mean HR98/50 (hazard ratio of top 2% to average in test set) of the Established-SNP model increased from 1.73 [95% CI: 1.69-1.77] to 2.41 [2.40-2.43] when the number of training samples was increased from 1 thousand to 30 thousand. Corresponding HR98/50 of the Discovery-SNP model increased from 1.05 [0.93-1.18] to 2.19 [2.16-2.23]. HR98/50 of a representative Established-SNP model using testing set sample sizes of 0.6 thousand and 6 thousand observations were 1.78 [1.70-1.85] and 1.73 [1.71-1.76], respectively. We estimate that a study population of 20 thousand men is required to develop Discovery-SNP PHS models while 10 thousand men should be sufficient for Established-SNP models.

African-specific improvement of a polygenic hazard score for age at diagnosis of prostate cancer

Polygenic hazard score (PHS) models are associated with age at diagnosis of prostate cancer. Our model developed in Europeans (PHS46) showed reduced performance in men with African genetic ancestry. We used a cross-validated search to identify single nucleotide polymorphisms (SNPs) that might improve performance in this population. Anonymized genotypic data were obtained from the PRACTICAL consortium for 6253 men with African genetic ancestry. Ten iterations of a 10-fold cross-validation search were conducted to select SNPs that would be included in the final PHS46+African model. The coefficients of PHS46+African were estimated in a Cox proportional hazards framework using age at diagnosis as the dependent variable and PHS46, and selected SNPs as predictors. The performance of PHS46 and PHS46+African was compared using the same cross-validated approach. Three SNPs (rs76229939, rs74421890 and rs5013678) were selected for inclusion in PHS46+African. All three SNPs are located on chromosome 8q24. PHS46+African showed substantial improvements in all performance metrics measured, including a 75% increase in the relative hazard of those in the upper 20% compared to the bottom 20% (2.47-4.34) and a 20% reduction in the relative hazard of those in the bottom 20% compared to the middle 40% (0.65-0.53). In conclusion, we identified three SNPs that substantially improved the association of PHS46 with age at diagnosis of prostate cancer in men with African genetic ancestry to levels comparable to Europeans.

Prognostic Accuracy of Fetal MRI in Predicting Postnatal Neurodevelopmental Outcome

BACKGROUND AND PURPOSE

The superior diagnostic accuracy of fetal MR imaging in detecting fetal brain abnormalities has been previously demonstrated; however, the ability of fetal MR imaging to prognosticate postnatal outcome is not well-studied. We performed a retrospective analysis to determine the prognostic accuracy of fetal MR imaging in predicting postnatal neurodevelopmental outcome.

MATERIALS AND METHODS

We identified all fetal MR imaging performed at the Children's Hospital of Eastern Ontario during a 10-year period and assessed agreement between prenatal prognosis and postnatal outcome. Prenatal prognosis was determined by a pediatric neurologist who reviewed the fetal MR imaging report and categorized each pregnancy as having a favorable, indeterminate, or poor prognosis. Assessment of postnatal neurodevelopmental outcome was made solely on the basis of the child's Gross Motor Function Classification System score and whether the child developed epilepsy. Postnatal outcome was categorized as favorable, intermediate, or poor. We also assessed the diagnostic accuracy of fetal MR imaging by comparing prenatal and postnatal imaging diagnoses.

RESULTS

We reviewed 145 fetal MR images: 114 were included in the assessment of diagnostic accuracy, and 104 were included in the assessment of prognostic accuracy. There was 93.0% agreement between prenatal and postnatal imaging diagnoses. Prognosis was favorable in 44.2%, indeterminate in 50.0%, and poor in 5.8% of pregnancies. There was 93.5% agreement between a favorable prenatal prognosis and a favorable postnatal outcome.

CONCLUSIONS

A favorable prenatal prognosis is highly predictive of a favorable postnatal outcome. Further studies are required to better understand the role of fetal MR imaging in prognosticating postnatal development, particularly in pregnancies with indeterminate and poor prognoses.

A Genetic Risk Score to Personalize Prostate Cancer Screening, Applied to Population Data

BACKGROUND

A polygenic hazard score (PHS), the weighted sum of 54 SNP genotypes, was previously validated for association with clinically significant prostate cancer and for improved prostate cancer screening accuracy. Here, we assess the potential impact of PHS-informed screening.

METHODS

United Kingdom population incidence data (Cancer Research United Kingdom) and data from the Cluster Randomized Trial of PSA Testing for Prostate Cancer were combined to estimate age-specific clinically significant prostate cancer incidence (Gleason score ≥7, stage T3-T4, PSA ≥10, or nodal/distant metastases). Using HRs estimated from the ProtecT prostate cancer trial, age-specific incidence rates were calculated for various PHS risk percentiles. Risk-equivalent age, when someone with a given PHS percentile has prostate cancer risk equivalent to an average 50-year-old man (50-year-standard risk), was derived from PHS and incidence data. Positive predictive value (PPV) of PSA testing for clinically significant prostate cancer was calculated using PHS-adjusted age groups.

RESULTS

The expected age at diagnosis of clinically significant prostate cancer differs by 19 years between the 1st and 99th PHS percentiles: men with PHS in the 1st and 99th percentiles reach the 50-year-standard risk level at ages 60 and 41, respectively. PPV of PSA was higher for men with higher PHS-adjusted age.

CONCLUSIONS

PHS provides individualized estimates of risk-equivalent age for clinically significant prostate cancer. Screening initiation could be adjusted by a man's PHS.

IMPACT

Personalized genetic risk assessments could inform prostate cancer screening decisions.

European polygenic risk score for prediction of breast cancer shows similar performance in Asian women

Polygenic risk scores (PRS) have been shown to predict breast cancer risk in European women, but their utility in Asian women is unclear. Here we evaluate the best performing PRSs for European-ancestry women using data from 17,262 breast cancer cases and 17,695 controls of Asian ancestry from 13 case-control studies, and 10,255 Chinese women from a prospective cohort (413 incident breast cancers). Compared to women in the middle quintile of the risk distribution, women in the highest 1% of PRS distribution have a ~2.7-fold risk and women in the lowest 1% of PRS distribution has ~0.4-fold risk of developing breast cancer. There is no evidence of heterogeneity in PRS performance in Chinese, Malay and Indian women. A PRS developed for European-ancestry women is also predictive of breast cancer risk in Asian women and can help in developing risk-stratified screening programmes in Asia.

Prediction models for prostate cancer to be used in the primary care setting: a systematic review

OBJECTIVE

To identify risk prediction models for prostate cancer (PCa) that can be used in the primary care and community health settings.

DESIGN

Systematic review.

DATA SOURCES

MEDLINE and Embase databases combined from inception and up to the end of January 2019.

ELIGIBILITY

Studies were included based on satisfying all the following criteria: (i) presenting an evaluation of PCa risk at initial biopsy in patients with no history of PCa, (ii) studies not incorporating an invasive clinical assessment or expensive biomarker/genetic tests, (iii) inclusion of at least two variables with prostate-specific antigen (PSA) being one of them, and (iv) studies reporting a measure of predictive performance. The quality of the studies and risk of bias was assessed by using the Prediction model Risk Of Bias ASsessment Tool (PROBAST).

DATA EXTRACTION AND SYNTHESIS

Relevant information extracted for each model included: the year of publication, source of data, type of model, number of patients, country, age, PSA range, mean/median PSA, other variables included in the model, number of biopsy cores to assess outcomes, study endpoint(s), cancer detection, model validation and model performance.

RESULTS

An initial search yielded 109 potential studies, of which five met the set criteria. Four studies were cohort-based and one was a case-control study. PCa detection rate was between 20.6% and 55.8%. Area under the curve (AUC) was reported in four studies and ranged from 0.65 to 0.75. All models showed significant improvement in predicting PCa compared with being based on PSA alone. The difference in AUC between extended models and PSA alone was between 0.06 and 0.21.

CONCLUSION

Only a few PCa risk prediction models have the potential to be readily used in the primary healthcare or community health setting. Further studies are needed to investigate other potential variables that could be integrated into models to improve their clinical utility for PCa testing in a community setting.

Germline HOXB13 mutations p.G84E and p.R217C do not confer an increased breast cancer risk

In breast cancer, high levels of homeobox protein Hox-B13 (HOXB13) have been associated with disease progression of ER-positive breast cancer patients and resistance to tamoxifen treatment. Since HOXB13 p.G84E is a prostate cancer risk allele, we evaluated the association between HOXB13 germline mutations and breast cancer risk in a previous study consisting of 3,270 familial non-BRCA1/2 breast cancer cases and 2,327 controls from the Netherlands. Although both recurrent HOXB13 mutations p.G84E and p.R217C were not associated with breast cancer risk, the risk estimation for p.R217C was not very precise. To provide more conclusive evidence regarding the role of HOXB13 in breast cancer susceptibility, we here evaluated the association between HOXB13 mutations and increased breast cancer risk within 81 studies of the international Breast Cancer Association Consortium containing 68,521 invasive breast cancer patients and 54,865 controls. Both HOXB13 p.G84E and p.R217C did not associate with the development of breast cancer in European women, neither in the overall analysis (OR = 1.035, 95% CI = 0.859-1.246, P = 0.718 and OR = 0.798, 95% CI = 0.482-1.322, P = 0.381 respectively), nor in specific high-risk subgroups or breast cancer subtypes. Thus, although involved in breast cancer progression, HOXB13 is not a material breast cancer susceptibility gene.

SAT-047 Adoption of an Age Adjusted Testosterone Reference Range Reduces Referrals to Endocrine Clinic and New Prescriptions of Testosterone

Testosterone levels decline with age. However, until recently well defined harmonised age and/or obesity (BMI <30kg/m²) adjusted reference ranges did not exist.¹ There is also a lack of international consensus on whether an age adjusted reference range (RR) should be used to define the syndrome of hypogonadism in men. Our local referral guideline suggests referral to endocrinology is appropriate if morning testosterone is <9.4nmol/L similar to the Endocrine Society Clinical Practice Guideline.² In mid 2018 our laboratory adopted the published all men age adjusted RR¹. We sought to; i) investigate clinic referrals before and after adoption of the all men age adjusted RR and, ii) to model the impact on referrals and prescription of testosterone replacement therapy (TRT) had we adopted either the lower limit of either all men or non-obese age adjusted RR as our referral criteria. Despite similar numbers of testosterone levels being measured in the laboratory, referrals to endocrine clinic for investigation of male hypogonadism fell by 52% (n=101 vs 48) in the one year following the introduction of the new age adjusted RR, with a corresponding reduction in prescriptions for testosterone. Mean testosterone concentration (6.7±2.5 vs 6.4±3.9nmol/L [mean±SD], NS), and age (51±13.9 vs 50±17.9 years, NS) of individuals referred were similar before and after the change of RR. Of the 101 patients referred for investigation of hypogonadism prior to the new RR mean testosterone concentrations were 8.5±4.5, 7.3±4.1, 6.8±3.6, 6.7±2.1 & 6.6±1.6nmol/L, with 39, 71, 39, 40 & 17% of the 87 patients seen in clinic being prescribed TRT in age groups 19-39 (n=28), 40-49 (n=7), 50-59 (n=33), 60-69 (n=20) &70-79 (n=6) respectively, excluding those with a history of anabolic steroid use or Klinefelter’s syndrome. Mean BMI was 30.9±4.4kg/m², which was similar between age groups. Had the lower limit of normal of the all men testosterone RR been employed as our referral criteria in the preceding year, 23.8% (24/101) of referrals would not have met referral criteria, and 26.2% (n=11/42) of those receiving a prescription would potentially not have received a trial of TRT. In contrast, had the non-obese age adjusted RR had been adopted for all men 13.9% (14/101) of referrals would not have met referral criteria and, of those prescribed testosterone, 2.4% (n= 1/42) would not have received a trial of TRT. In conclusion, adoption of the all men age adjusted RR for testosterone has been associated with a significant fall in referrals for investigation of male hypogonadism. However, modelling of historical clinic data would suggest that some non-obese individuals miss out on a therapeutic trial of TRT, especially if the all men, rather than non-obese, age adjusted RR is adopted.

Reference: (1) Travison et al, J Clin Endocrinol Metab, 2017,102(4):1161-1173, (2) Bhasin S et al,. J Clin Endocrinol Metab. March 2018;103(5):1715-1744.

Evaluation of associations between genetically predicted circulating protein biomarkers and breast cancer risk

A small number of circulating proteins have been reported to be associated with breast cancer risk, with inconsistent results. Herein, we attempted to identify novel protein biomarkers for breast cancer via the integration of genomics and proteomics data. In the Breast Cancer Association Consortium (BCAC), with 122,977 cases and 105,974 controls of European descendants, we evaluated the associations of the genetically predicted concentrations of >1,400 circulating proteins with breast cancer risk. We used data from a large-scale protein quantitative trait loci (pQTL) analysis as our study instrument. Summary statistics for these pQTL variants related to breast cancer risk were obtained from the BCAC and used to estimate odds ratios (OR) for each protein using the inverse-variance weighted method. We identified 56 proteins significantly associated with breast cancer risk by instrumental analysis (false discovery rate <0.05). Of these, the concentrations of 32 were influenced by variants close to a breast cancer susceptibility locus (ABO, 9q34.2). Many of these proteins, such as insulin receptor, insulin-like growth factor receptor 1 and other membrane receptors (OR: 0.82-1.18, p values: 6.96 × 10-4 -3.28 × 10-8 ), are linked to insulin resistance and estrogen receptor signaling pathways. Proteins identified at other loci include those involved in biological processes such as alcohol and lipid metabolism, proteolysis, apoptosis, immune regulation and cell motility and proliferation. Consistent associations were observed for 22 proteins in the UK Biobank data (p < 0.05). The study identifies potential novel biomarkers for breast cancer, but further investigation is needed to replicate our findings.

Identification of novel breast cancer susceptibility loci in meta-analyses conducted among Asian and European descendants

Known risk variants explain only a small proportion of breast cancer heritability, particularly in Asian women. To search for additional genetic susceptibility loci for breast cancer, here we perform a meta-analysis of data from genome-wide association studies (GWAS) conducted in Asians (24,206 cases and 24,775 controls) and European descendants (122,977 cases and 105,974 controls). We identified 31 potential novel loci with the lead variant showing an association with breast cancer risk at P < 5 × 10-8. The associations for 10 of these loci were replicated in an independent sample of 16,787 cases and 16,680 controls of Asian women (P < 0.05). In addition, we replicated the associations for 78 of the 166 known risk variants at P < 0.05 in Asians. These findings improve our understanding of breast cancer genetics and etiology and extend previous findings from studies of European descendants to Asian women.

Genetically Predicted Levels of DNA Methylation Biomarkers and Breast Cancer Risk: Data From 228 951 Women of European Descent

BACKGROUND

DNA methylation plays a critical role in breast cancer development. Previous studies have identified DNA methylation marks in white blood cells as promising biomarkers for breast cancer. However, these studies were limited by low statistical power and potential biases. Using a new methodology, we investigated DNA methylation marks for their associations with breast cancer risk.

METHODS

Statistical models were built to predict levels of DNA methylation marks using genetic data and DNA methylation data from HumanMethylation450 BeadChip from the Framingham Heart Study (n = 1595). The prediction models were validated using data from the Women's Health Initiative (n = 883). We applied these models to genomewide association study (GWAS) data of 122 977 breast cancer patients and 105 974 controls to evaluate if the genetically predicted DNA methylation levels at CpG sites (CpGs) are associated with breast cancer risk. All statistical tests were two-sided.

RESULTS

Of the 62 938 CpG sites CpGs investigated, statistically significant associations with breast cancer risk were observed for 450 CpGs at a Bonferroni-corrected threshold of P less than 7.94 × 10-7, including 45 CpGs residing in 18 genomic regions, that have not previously been associated with breast cancer risk. Of the remaining 405 CpGs located within 500 kilobase flaking regions of 70 GWAS-identified breast cancer risk variants, the associations for 11 CpGs were independent of GWAS-identified variants. Integrative analyses of genetic, DNA methylation, and gene expression data found that 38 CpGs may affect breast cancer risk through regulating expression of 21 genes.

CONCLUSION

Our new methodology can identify novel DNA methylation biomarkers for breast cancer risk and can be applied to other diseases.

Fine-mapping of 150 breast cancer risk regions identifies 191 likely target genes

Genome-wide association studies have identified breast cancer risk variants in over 150 genomic regions, but the mechanisms underlying risk remain largely unknown. These regions were explored by combining association analysis with in silico genomic feature annotations. We defined 205 independent risk-associated signals with the set of credible causal variants in each one. In parallel, we used a Bayesian approach (PAINTOR) that combines genetic association, linkage disequilibrium and enriched genomic features to determine variants with high posterior probabilities of being causal. Potentially causal variants were significantly over-represented in active gene regulatory regions and transcription factor binding sites. We applied our INQUSIT pipeline for prioritizing genes as targets of those potentially causal variants, using gene expression (expression quantitative trait loci), chromatin interaction and functional annotations. Known cancer drivers, transcription factors and genes in the developmental, apoptosis, immune system and DNA integrity checkpoint gene ontology pathways were over-represented among the highest-confidence target genes.

Re-evaluating genetic variants identified in candidate gene studies of breast cancer risk using data from nearly 280,000 women of Asian and European ancestry

BACKGROUND

We previously conducted a systematic field synopsis of 1059 breast cancer candidate gene studies and investigated 279 genetic variants, 51 of which showed associations. The major limitation of this work was the small sample size, even pooling data from all 1059 studies. Thereafter, genome-wide association studies (GWAS) have accumulated data for hundreds of thousands of subjects. It's necessary to re-evaluate these variants in large GWAS datasets.

METHODS

Of these 279 variants, data were obtained for 228 from GWAS conducted within the Asian Breast Cancer Consortium (24,206 cases and 24,775 controls) and the Breast Cancer Association Consortium (122,977 cases and 105,974 controls of European ancestry). Meta-analyses were conducted to combine the results from these two datasets.

FINDINGS

Of those 228 variants, an association was observed for 12 variants in 10 genes at a Bonferroni-corrected threshold of P < 2·19 × 10-4. The associations for four variants reached P < 5 × 10-8 and have been reported by previous GWAS, including rs6435074 and rs6723097 (CASP8), rs17879961 (CHEK2) and rs2853669 (TERT). The remaining eight variants were rs676387 (HSD17B1), rs762551 (CYP1A2), rs1045485 (CASP8), rs9340799 (ESR1), rs7931342 (CHR11), rs1050450 (GPX1), rs13010627 (CASP10) and rs9344 (CCND1). Further investigating these 10 genes identified associations for two additional variants at P < 5 × 10-8, including rs4793090 (near HSD17B1), and rs9210 (near CYP1A2), which have not been identified by previous GWAS.

INTERPRETATION

Though most candidate gene variants were not associated with breast cancer risk, we found 14 variants showing an association. Our findings warrant further functional investigation of these variants. FUND: National Institutes of Health.

Circulating vitamin D concentrations and risk of breast and prostate cancer: a Mendelian randomization study

BACKGROUND

Observational studies have suggested an association between circulating vitamin D concentrations [25(OH)D] and risk of breast and prostate cancer, which was not supported by a recent Mendelian randomization (MR) analysis comprising 15 748 breast and 22 898 prostate-cancer cases. Demonstrating causality has proven challenging and one common limitation of MR studies is insufficient power.

METHODS

We aimed to determine whether circulating concentrations of vitamin D are causally associated with the risk of breast and prostate cancer, by using summary-level data from the largest ever genome-wide association studies conducted on vitamin D (N = 73 699), breast cancer (Ncase = 122 977) and prostate cancer (Ncase = 79 148). We constructed a stronger instrument using six common genetic variants (compared with the previous four variants) and applied several two-sample MR methods.

RESULTS

We found no evidence to support a causal association between 25(OH)D and risk of breast cancer [OR per 25 nmol/L increase, 1.02 (95% confidence interval: 0.97-1.08), P = 0.47], oestrogen receptor (ER)+ [1.00 (0.94-1.07), P = 0.99] or ER- [1.02 (0.90-1.16), P = 0.75] subsets, prostate cancer [1.00 (0.93-1.07), P = 0.99] or the advanced subtype [1.02 (0.90-1.16), P = 0.72] using the inverse-variance-weighted method. Sensitivity analyses did not reveal any sign of directional pleiotropy.

CONCLUSIONS

Despite its almost five-fold augmented sample size and substantially improved statistical power, our MR analysis does not support a causal effect of circulating 25(OH)D concentrations on breast- or prostate-cancer risk. However, we can still not exclude a modest or non-linear effect of vitamin D. Future studies may be designed to understand the effect of vitamin D in subpopulations with a profound deficiency.

Publisher Correction: Shared heritability and functional enrichment across six solid cancers

An amendment to this paper has been published and can be accessed via a link at the top of the paper.

Germline DNA Repair Gene Mutations in Young-onset Prostate Cancer Cases in the UK: Evidence for a More Extensive Genetic Panel

BACKGROUND

Rare germline mutations in DNA repair genes are associated with prostate cancer (PCa) predisposition and prognosis.

OBJECTIVE

To quantify the frequency of germline DNA repair gene mutations in UK PCa cases and controls, in order to more comprehensively evaluate the contribution of individual genes to overall PCa risk and likelihood of aggressive disease.

DESIGN, SETTING, AND PARTICIPANTS

We sequenced 167 DNA repair and eight PCa candidate genes in a UK-based cohort of 1281 young-onset PCa cases (diagnosed at ≤60yr) and 1160 selected controls.

OUTCOME MEASUREMENTS AND STATISTICAL ANALYSIS

Gene-level SKAT-O and gene-set adaptive combination of p values (ADA) analyses were performed separately for cases versus controls, and aggressive (Gleason score ≥8, n=201) versus nonaggressive (Gleason score ≤7, n=1048) cases.

RESULTS AND LIMITATIONS

We identified 233 unique protein truncating variants (PTVs) with minor allele frequency <0.5% in controls in 97 genes. The total proportion of PTV carriers was higher in cases than in controls (15% vs 12%, odds ratio [OR]=1.29, 95% confidence interval [CI] 1.01-1.64, p=0.036). Gene-level analyses selected NBN (pSKAT-O=2.4×10-4) for overall risk and XPC (pSKAT-O=1.6×10-4) for aggressive disease, both at candidate-level significance (p<3.1×10-4 and p<3.4×10-4, respectively). Gene-set analysis identified a subset of 20 genes associated with increased PCa risk (OR=3.2, 95% CI 2.1-4.8, pADA=4.1×10-3) and four genes that increased risk of aggressive disease (OR=11.2, 95% CI 4.6-27.7, pADA=5.6×10-3), three of which overlap the predisposition gene set.

CONCLUSIONS

The union of the gene-level and gene-set-level analyses identified 23 unique DNA repair genes associated with PCa predisposition or risk of aggressive disease. These findings will help facilitate the development of a PCa-specific sequencing panel with both predictive and prognostic potential.

PATIENT SUMMARY

This large sequencing study assessed the rate of inherited DNA repair gene mutations between prostate cancer patients and disease-free men. A panel of 23 genes was identified, which may improve risk prediction or treatment pathways in future clinical practice.

Two truncating variants in FANCC and breast cancer risk

Fanconi anemia (FA) is a genetically heterogeneous disorder with 22 disease-causing genes reported to date. In some FA genes, monoallelic mutations have been found to be associated with breast cancer risk, while the risk associations of others remain unknown. The gene for FA type C, FANCC, has been proposed as a breast cancer susceptibility gene based on epidemiological and sequencing studies. We used the Oncoarray project to genotype two truncating FANCC variants (p.R185X and p.R548X) in 64,760 breast cancer cases and 49,793 controls of European descent. FANCC mutations were observed in 25 cases (14 with p.R185X, 11 with p.R548X) and 26 controls (18 with p.R185X, 8 with p.R548X). There was no evidence of an association with the risk of breast cancer, neither overall (odds ratio 0.77, 95%CI 0.44-1.33, p = 0.4) nor by histology, hormone receptor status, age or family history. We conclude that the breast cancer risk association of these two FANCC variants, if any, is much smaller than for BRCA1, BRCA2 or PALB2 mutations. If this applies to all truncating variants in FANCC it would suggest there are differences between FA genes in their roles on breast cancer risk and demonstrates the merit of large consortia for clarifying risk associations of rare variants.