Improving reporting standards for polygenic scores in risk prediction studies.

Polygenic risk scores (PRSs), which often aggregate results from genome-wide association studies, can bridge the gap between initial discovery efforts and clinical applications for the estimation of disease risk using genetics. However, there is notable heterogeneity in the application and reporting of these risk scores, which hinders the translation of PRSs into clinical care. Here, in a collaboration between the Clinical Genome Resource (ClinGen) Complex Disease Working Group and the Polygenic Score (PGS) Catalog, we present the Polygenic Risk Score Reporting Standards (PRS-RS), in which we update the Genetic Risk Prediction Studies (GRIPS) Statement to reflect the present state of the field. Drawing on the input of experts in epidemiology, statistics, disease-specific applications, implementation and policy, this comprehensive reporting framework defines the minimal information that is needed to interpret and evaluate PRSs, especially with respect to downstream clinical applications. Items span detailed descriptions of study populations, statistical methods for the development and validation of PRSs and considerations for the potential limitations of these scores. In addition, we emphasize the need for data availability and transparency, and we encourage researchers to deposit and share PRSs through the PGS Catalog to facilitate reproducibility and comparative benchmarking. By providing these criteria in a structured format that builds on existing standards and ontologies, the use of this framework in publishing PRSs will facilitate translation into clinical care and progress towards defining best practice.

Novel breast cancer susceptibility loci under linkage peaks identified in African ancestry consortia.

BACKGROUND: Expansion of genome-wide association studies across population groups is needed to improve our understanding of shared and unique genetic contributions to breast cancer. We performed association and replication studies guided by a priori linkage findings from African ancestry (AA) relative pairs. METHODS: We performed fixed-effect inverse-variance weighted meta-analysis under three significant AA breast cancer linkage peaks (3q26-27, 12q22-23, and 16q21-22) in 9241 AA cases and 10 193 AA controls. We examined associations with overall breast cancer as well as estrogen receptor (ER)-positive and negative subtypes (193,132 SNPs). We replicated associations in the African-ancestry Breast Cancer Genetic Consortium (AABCG). RESULTS: In AA women, we identified two associations on chr12q for overall breast cancer (rs1420647, OR = 1.15, p = 2.50×10-6; rs12322371, OR = 1.14, p = 3.15×10-6), and one for ER-negative breast cancer (rs77006600, OR = 1.67, p = 3.51×10-6). On chr3, we identified two associations with ER-negative disease (rs184090918, OR = 3.70, p = 1.23×10-5; rs76959804, OR = 3.57, p = 1.77×10-5) and on chr16q we identified an association with ER-negative disease (rs34147411, OR = 1.62, p = 8.82×10-6). In the replication study, the chr3 associations were significant and effect sizes were larger (rs184090918, OR: 6.66, 95% CI: 1.43, 31.01; rs76959804, OR: 5.24, 95% CI: 1.70, 16.16). CONCLUSION: The two chr3 SNPs are upstream to open chromatin ENSR00000710716, a regulatory feature that is actively regulated in mammary tissues, providing evidence that variants in this chr3 region may have a regulatory role in our target organ. Our study provides support for breast cancer variant discovery using prioritization based on linkage evidence.

Author Correction: The evolutionary history of lethal metastatic prostate cancer.

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

Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction.

Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20-29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%-5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%-95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%-1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20-29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age.

Genetic predisposition to mosaic Y chromosome loss in blood.

Mosaic loss of chromosome Y (LOY) in circulating white blood cells is the most common form of clonal mosaicism1-5, yet our knowledge of the causes and consequences of this is limited. Here, using a computational approach, we estimate that 20% of the male population represented in the UK Biobank study (n = 205,011) has detectable LOY. We identify 156 autosomal genetic determinants of LOY, which we replicate in 757,114 men of European and Japanese ancestry. These loci highlight genes that are involved in cell-cycle regulation and cancer susceptibility, as well as somatic drivers of tumour growth and targets of cancer therapy. We demonstrate that genetic susceptibility to LOY is associated with non-haematological effects on health in both men and women, which supports the hypothesis that clonal haematopoiesis is a biomarker of genomic instability in other tissues. Single-cell RNA sequencing identifies dysregulated expression of autosomal genes in leukocytes with LOY and provides insights into why clonal expansion of these cells may occur. Collectively, these data highlight the value of studying clonal mosaicism to uncover fundamental mechanisms that underlie cancer and other ageing-related diseases.

Protein-truncating and rare missense variants in ATM and CHEK2 and associations with cancer in UK Biobank whole-exome sequence data.

BACKGROUND: Deleterious germline variants in ATM and CHEK2 have been associated with a moderately increased risk of breast cancer. Risks for other cancers remain unclear. METHODS: Cancer associations for coding variants in ATM and CHEK2 were evaluated using whole-exome sequence data from UK Biobank linked to cancer registration data (348 488 participants), and analysed both as a retrospective case-control and a prospective cohort study. Odds ratios, hazard ratios, and combined relative risks (RRs) were estimated by cancer type and gene. Separate analyses were performed for protein-truncating variants (PTVs) and rare missense variants (rMSVs; allele frequency <0.1%). RESULTS: PTVs in ATM were associated with increased risks of nine cancers at p<0.001 (pancreas, oesophagus, lung, melanoma, breast, ovary, prostate, bladder, lymphoid leukaemia (LL)), and three at p<0.05 (colon, diffuse non-Hodgkin's lymphoma (DNHL), rectosigmoid junction). Carriers of rMSVs had increased risks of four cancers (p<0.05: stomach, pancreas, prostate, Hodgkin's disease (HD)). RRs were highest for breast, prostate, and any cancer where rMSVs lay in the FAT or PIK domains, and had a Combined Annotation Dependent Depletion score in the highest quintile.PTVs in CHEK2 were associated with three cancers at p<0.001 (breast, prostate, HD) and six at p<0.05 (oesophagus, melanoma, ovary, kidney, DNHL, myeloid leukaemia). Carriers of rMSVs had increased risks of five cancers (p<0.001: breast, prostate, LL; p<0.05: melanoma, multiple myeloma). CONCLUSION: PTVs in ATM and CHEK2 are associated with a wide range of cancers, with the highest RR for pancreatic cancer in ATM PTV carriers. These findings can inform genetic counselling of carriers.

Validation of the BOADICEA model in a prospective cohort of BRCA1/2 pathogenic variant carriers.

BACKGROUND: No validation has been conducted for the BOADICEA multifactorial breast cancer risk prediction model specifically in BRCA1/2 pathogenic variant (PV) carriers to date. Here, we evaluated the performance of BOADICEA in predicting 5-year breast cancer risks in a prospective cohort of BRCA1/2 PV carriers ascertained through clinical genetic centres. METHODS: We evaluated the model calibration and discriminatory ability in the prospective TRANsIBCCS cohort study comprising 1614 BRCA1 and 1365 BRCA2 PV carriers (209 incident cases). Study participants had lifestyle, reproductive, hormonal, anthropometric risk factor information, a polygenic risk score based on 313 SNPs and family history information. RESULTS: The full multifactorial model considering family history together with all other risk factors was well calibrated overall (E/O=1.07, 95% CI: 0.92 to 1.24) and in quintiles of predicted risk. Discrimination was maximised when all risk factors were considered (Harrell's C-index=0.70, 95% CI: 0.67 to 0.74; area under the curve=0.79, 95% CI: 0.76 to 0.82). The model performance was similar when evaluated separately in BRCA1 or BRCA2 PV carriers. The full model identified 5.8%, 12.9% and 24.0% of BRCA1/2 PV carriers with 5-year breast cancer risks of <1.65%, <3% and <5%, respectively, risk thresholds commonly used for different management and risk-reduction options. CONCLUSION: BOADICEA may be used to aid personalised cancer risk management and decision-making for BRCA1 and BRCA2 PV carriers. It is implemented in the free-access CanRisk tool (https://www.canrisk.org/).

Genome-wide association study and functional follow-up identify 14q12 as a candidate risk locus for cervical cancer.

Cervical cancer is among the leading causes of cancer-related death in females worldwide. Infection by human papillomavirus (HPV) is an established risk factor for cancer development. However, genetic factors contributing to disease risk remain largely unknown. We report on a genome-wide association study (GWAS) on 375 German cervical cancer patients and 866 healthy controls, followed by a replication study comprising 658 patients with invasive cervical cancer, 1361 with cervical dysplasia and 841 healthy controls. Functional validation was performed for the top GWAS variant on chromosome 14q12 (rs225902, close to PRKD1). After bioinformatic annotation and in silico predictions, we performed transcript analysis in a cervical tissue series of 317 samples and demonstrate rs225902 as an expression quantitative trait locus (eQTL) for FOXG1 and two tightly co-regulated long non-coding RNAs at this genomic region, CTD-2251F13 (lnc-PRKD1-1) and CTD-2503I6 (lnc-FOXG1-6). We also show allele-specific effects of the 14q12 variants via luciferase assays. We propose a combined effect of genotype, HPV status and gene expression at this locus on cervical cancer progression. Taken together, this work uncovers a potential candidate locus with regulatory functions and contributes to the understanding of genetic susceptibility to cervical cancer.

Polygenic risk scores for prediction of breast cancer risk in women of African ancestry: a cross-ancestry approach.

Polygenic risk scores (PRSs) are useful for predicting breast cancer risk, but the prediction accuracy of existing PRSs in women of African ancestry (AA) remains relatively low. We aim to develop optimal PRSs for the prediction of overall and estrogen receptor (ER) subtype-specific breast cancer risk in AA women. The AA dataset comprised 9235 cases and 10 184 controls from four genome-wide association study (GWAS) consortia and a GWAS study in Ghana. We randomly divided samples into training and validation sets. We built PRSs using individual-level AA data by a forward stepwise logistic regression and then developed joint PRSs that combined (1) the PRSs built in the AA training dataset and (2) a 313-variant PRS previously developed in women of European ancestry. PRSs were evaluated in the AA validation set. For overall breast cancer, the odds ratio per standard deviation of the joint PRS in the validation set was 1.34 [95% confidence interval (CI): 1.27-1.42] with the area under receiver operating characteristic curve (AUC) of 0.581. Compared with women with average risk (40th-60th PRS percentile), women in the top decile of the PRS had a 1.98-fold increased risk (95% CI: 1.63-2.39). For PRSs of ER-positive and ER-negative breast cancer, the AUCs were 0.608 and 0.576, respectively. Compared with existing methods, the proposed joint PRSs can improve prediction of breast cancer risk in AA women.

Estimation of age of onset and progression of breast cancer by absolute risk dependent on polygenic risk score and other risk factors.

BACKGROUND: Genetic, lifestyle, reproductive, and anthropometric factors are associated with the risk of developing breast cancer. However, it is not yet known whether polygenic risk score (PRS) and absolute risk based on a combination of risk factors are associated with the risk of progression of breast cancer. This study aims to estimate the distribution of sojourn time (pre-clinical screen-detectable period) and mammographic sensitivity by absolute breast cancer risk derived from polygenic profile and the other risk factors. METHODS: The authors used data from a population-based case-control study. Six categories of 10-year absolute risk based on different combinations of risk factors were derived using the Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm. Women were classified into low, medium, and high-risk groups. The authors constructed a continuous-time multistate model. To calculate the sojourn time, they simulated the trajectories of subjects through the disease states. RESULTS: There was little difference in sojourn time with a large overlap in the 95% confidence interval (CI) between the risk groups across the six risk categories and PRS studied. However, the age of entry into the screen-detectable state varied by risk category, with the mean age of entry of 53.4 years (95% CI, 52.2-54.1) and 57.0 years (95% CI, 55.1-57.7) in the high-risk and low-risk women, respectively. CONCLUSION: In risk-stratified breast screening, the age at the start of screening, but not necessarily the frequency of screening, should be tailored to a woman's risk level. The optimal risk-stratified screening strategy that would improve the benefit-to-harm balance and the cost-effectiveness of the screening programs needs to be studied.

Validation of the BOADICEA model for epithelial tubo-ovarian cancer risk prediction in UK Biobank.

BACKGROUND: The clinical validity of the multifactorial BOADICEA model for epithelial tubo-ovarian cancer (EOC) risk prediction has not been assessed in a large sample size or over a longer term. METHODS: We evaluated the model discrimination and calibration in the UK Biobank cohort comprising 199,429 women (733 incident EOCs) of European ancestry without previous cancer history. We predicted 10-year EOC risk incorporating data on questionnaire-based risk factors (QRFs), family history, a 36-SNP polygenic risk score and pathogenic variants (PV) in six EOC susceptibility genes (BRCA1, BRCA2, RAD51C, RAD51D, BRIP1 and PALB2). RESULTS: Discriminative ability was maximised under the multifactorial model that included all risk factors (AUC = 0.68, 95% CI: 0.66-0.70). This model was well calibrated in deciles of predicted risk with calibration slope=0.99 (95% CI: 0.98-1.01). Discriminative ability was similar in women younger or older than 60 years. The AUC was higher when analyses were restricted to PV carriers (0.76, 95% CI: 0.69-0.82). Using relative risk (RR) thresholds, the full model classified 97.7%, 1.7%, 0.4% and 0.2% women in the RR < 2.0, 2.0 ≤ RR < 2.9, 2.9 ≤ RR < 6.0 and RR ≥ 6.0 categories, respectively, identifying 9.1 of incident EOC among those with RR ≥ 2.0. DISCUSSION: BOADICEA, implemented in CanRisk ( www.canrisk.org ), provides valid 10-year EOC risks and can facilitate clinical decision-making in EOC risk management.

Disentangling the relationships of body mass index and circulating sex hormone concentrations in mammographic density using Mendelian randomization.

PURPOSE: Mammographic density phenotypes, adjusted for age and body mass index (BMI), are strong predictors of breast cancer risk. BMI is associated with mammographic density measures, but the role of circulating sex hormone concentrations is less clear. We investigated the relationship between BMI, circulating sex hormone concentrations, and mammographic density phenotypes using Mendelian randomization (MR). METHODS: We applied two-sample MR approaches to assess the association between genetically predicted circulating concentrations of sex hormones [estradiol, testosterone, sex hormone-binding globulin (SHBG)], BMI, and mammographic density phenotypes (dense and non-dense area). We created instrumental variables from large European ancestry-based genome-wide association studies and applied estimates to mammographic density phenotypes in up to 14,000 women of European ancestry. We performed analyses overall and by menopausal status. RESULTS: Genetically predicted BMI was positively associated with non-dense area (IVW: ß = 1.79; 95% CI = 1.58, 2.00; p = 9.57 × 10-63) and inversely associated with dense area (IVW: ß = - 0.37; 95% CI = - 0.51,- 0.23; p = 4.7 × 10-7). We observed weak evidence for an association of circulating sex hormone concentrations with mammographic density phenotypes, specifically inverse associations between genetically predicted testosterone concentration and dense area (ß = - 0.22; 95% CI = - 0.38, - 0.053; p = 0.009) and between genetically predicted estradiol concentration and non-dense area (ß = - 3.32; 95% CI = - 5.83, - 0.82; p = 0.009), although results were not consistent across a range of MR approaches. CONCLUSION: Our findings support a positive causal association between BMI and mammographic non-dense area and an inverse association between BMI and dense area. Evidence was weaker and inconsistent for a causal effect of circulating sex hormone concentrations on mammographic density phenotypes. Based on our findings, associations between circulating sex hormone concentrations and mammographic density phenotypes are weak at best.

Systematic Minigene-Based Splicing Analysis and Tentative Clinical Classification of 52 CHEK2 Splice-Site Variants.

BACKGROUND: Disrupted pre-mRNA splicing is a frequent deleterious mechanism in hereditary cancer. We aimed to functionally analyze candidate spliceogenic variants of the breast cancer susceptibility gene CHEK2 by splicing reporter minigenes. METHODS: A total of 128 CHEK2 splice-site variants identified in the Breast Cancer After Diagnostic Gene Sequencing (BRIDGES) project (https://cordis.europa.eu/project/id/634935) were analyzed with MaxEntScan and subsetted to 52 variants predicted to impact splicing. Three CHEK2 minigenes, which span all 15 exons, were constructed and validated. The 52 selected variants were then genetically engineered into the minigenes and assayed in MCF-7 (human breast adenocarcinoma) cells. RESULTS: Of 52 variants, 46 (88.5%) impaired splicing. Some of them led to complex splicing patterns with up to 11 different transcripts. Thirty-four variants induced splicing anomalies without any trace or negligible amounts of the full-length transcript. A total of 89 different transcripts were annotated, which derived from different events: single- or multi-exon skipping, alternative site-usage, mutually exclusive exon inclusion, intron retention or combinations of the abovementioned events. Fifty-nine transcripts were predicted to introduce premature termination codons, 7 kept the original open-reading frame, 5 removed the translation start codon, 6 affected the 5'UTR (Untranslated Region), and 2 included missense variations. Analysis of variant c.684-2A > G revealed the activation of a non-canonical TG-acceptor site and exon 6 sequences critical for its recognition. CONCLUSIONS: Incorporation of minigene read-outs into an ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular Pathology)-based classification scheme allowed us to classify 32 CHEK2 variants (27 pathogenic/likely pathogenic and 5 likely benign). However, 20 variants (38%) remained of uncertain significance, reflecting in part the complex splicing patterns of this gene.

Proactive breast cancer risk assessment in primary care: a review based on the principles of screening.

In the UK, the National Institute for Health and Care Excellence (NICE) recommends that women at moderate or high risk of breast cancer be offered risk-reducing medication and enhanced breast screening/surveillance. In June 2022, NICE withdrew a statement recommending assessment of risk in primary care only when women present with concerns. This shift to the proactive assessment of risk substantially changes the role of primary care, in effect paving the way for a primary care-based screening programme to identify those at moderate or high risk of breast cancer. In this article, we review the literature surrounding proactive breast cancer risk assessment within primary care against the consolidated framework for screening. We find that risk assessment for women under 50 years currently satisfies many of the standard principles for screening. Most notably, there are large numbers of women at moderate or high risk currently unidentified, risk models exist that can identify those women with reasonable accuracy, and management options offer the opportunity to reduce breast cancer incidence and mortality in that group. However, there remain a number of uncertainties and research gaps, particularly around the programme/system requirements, that need to be addressed before these benefits can be realised.

Evaluation of SNPs associated with mammographic density in European women with mammographic density in Asian women from South-East Asia.

PURPOSE: Mammographic density (MD), after accounting for age and body mass index (BMI), is a strong heritable risk factor for breast cancer. Genome-wide association studies (GWAS) have identified 64 SNPs in 55 independent loci associated with MD in women of European ancestry. Their associations with MD in Asian women, however, are largely unknown. METHOD: Using linear regression adjusting for age, BMI, and ancestry-informative principal components, we evaluated the associations of previously reported MD-associated SNPs with MD in a multi-ethnic cohort of Asian ancestry. Area and volumetric mammographic densities were determined using STRATUS (N = 2450) and Volpara™ (N = 2257). We also assessed the associations of these SNPs with breast cancer risk in an Asian population of 14,570 cases and 80,870 controls. RESULTS: Of the 61 SNPs available in our data, 21 were associated with MD at a nominal threshold of P value < 0.05, all in consistent directions with those reported in European ancestry populations. Of the remaining 40 variants with a P-value of association > 0.05, 29 variants showed consistent directions of association as those previously reported. We found that nine of the 21 MD-associated SNPs in this study were also associated with breast cancer risk in Asian women (P < 0.05), seven of which showed a direction of associations that was consistent with that reported for MD. CONCLUSION: Our study confirms the associations of 21 SNPs (19/55 or 34.5% out of all known MD loci identified in women of European ancestry) with area and/or volumetric densities in Asian women, and further supports the evidence of a shared genetic basis through common genetic variants for MD and breast cancer risk.

Minigene-based splicing analysis and ACMG/AMP-based tentative classification of 56 ATM variants.

The ataxia telangiectasia-mutated (ATM) protein is a major coordinator of the DNA damage response pathway. ATM loss-of-function variants are associated with 2-fold increased breast cancer risk. We aimed at identifying and classifying spliceogenic ATM variants detected in subjects of the large-scale sequencing project BRIDGES. A total of 381 variants at the intron-exon boundaries were identified, 128 of which were predicted to be spliceogenic. After further filtering, we ended up selecting 56 variants for splicing analysis. Four functional minigenes (mgATM) spanning exons 4-9, 11-17, 25-29, and 49-52 were constructed in the splicing plasmid pSAD. Selected variants were genetically engineered into the four constructs and assayed in MCF-7/HeLa cells. Forty-eight variants (85.7%) impaired splicing, 32 of which did not show any trace of the full-length (FL) transcript. A total of 43 transcripts were identified where the most prevalent event was exon/multi-exon skipping. Twenty-seven transcripts were predicted to truncate the ATM protein. A tentative ACMG/AMP (American College of Medical Genetics and Genomics/Association for Molecular Pathology)-based classification scheme that integrates mgATM data allowed us to classify 29 ATM variants as pathogenic/likely pathogenic and seven variants as likely benign. Interestingly, the likely pathogenic variant c.1898+2T>G generated 13% of the minigene FL-transcript due to the use of a noncanonical GG-5'-splice-site (0.014% of human donor sites). Circumstantial evidence in three ATM variants (leakiness uncovered by our mgATM analysis together with clinical data) provides some support for a dosage-sensitive expression model in which variants producing ≥30% of FL-transcripts would be predicted benign, while variants producing ≤13% of FL-transcripts might be pathogenic. © 2022 The Authors. The Journal of Pathology published by John Wiley & Sons Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Splicing predictions, minigene analyses, and ACMG-AMP clinical classification of 42 germline PALB2 splice-site variants.

PALB2 loss-of-function variants confer high risk of developing breast cancer. Here we present a systematic functional analysis of PALB2 splice-site variants detected in approximately 113,000 women in the large-scale sequencing project Breast Cancer After Diagnostic Gene Sequencing (BRIDGES; https://bridges-research.eu/). Eighty-two PALB2 variants at the intron-exon boundaries were analyzed with MaxEntScan. Forty-two variants were selected for the subsequent splicing functional assays. For this purpose, three splicing reporter minigenes comprising exons 1-12 were constructed. The 42 potential spliceogenic variants were introduced into the minigenes by site-directed mutagenesis and assayed in MCF-7/MDA-MB-231 cells. Splicing anomalies were observed in 35 variants, 23 of which showed no traces or minimal amounts of the expected full-length transcripts of each minigene. More than 30 different variant-induced transcripts were characterized, 23 of which were predicted to truncate the PALB2 protein. The pathogenicity of all variants was interpreted according to an in-house adaptation of the American College of Medical Genetics and Genomics and the Association for Molecular Pathology (ACMG-AMP) variant classification scheme. Up to 23 variants were classified as pathogenic/likely pathogenic. Remarkably, three ±1,2 variants (c.49-2A>T, c.108+2T>C, and c.211+1G>A) were classified as variants of unknown significance, as they produced significant amounts of either in-frame transcripts of unknown impact on the PALB2 protein function or the minigene full-length transcripts. In conclusion, we have significantly contributed to the ongoing effort of identifying spliceogenic variants in the clinically relevant PALB2 cancer susceptibility gene. Moreover, we suggest some approaches to classify the findings in accordance with the ACMG-AMP rationale. © 2021 The Authors. The Journal of Pathology published by John Wiley & Sons, Ltd on behalf of The Pathological Society of Great Britain and Ireland.

Polymorphisms in genes of melatonin biosynthesis and signaling support the light-at-night hypothesis for breast cancer.

Light-at-night triggers the decline of pineal gland melatonin biosynthesis and secretion and is an IARC-classified probable breast-cancer risk factor. We applied a large-scale molecular epidemiology approach to shed light on the putative role of melatonin in breast cancer. We investigated associations between breast-cancer risk and polymorphisms at genes of melatonin biosynthesis/signaling using a study population of 44,405 women from the Breast Cancer Association Consortium (22,992 cases, 21,413 population-based controls). Genotype data of 97 candidate single nucleotide polymorphisms (SNPs) at 18 defined gene regions were investigated for breast-cancer risk effects. We calculated adjusted odds ratios (ORs) and 95% confidence intervals (CI) by logistic regression for the main-effect analysis as well as stratified analyses by estrogen- and progesterone-receptor (ER, PR) status. SNP-SNP interactions were analyzed via a two-step procedure based on logic regression. The Bayesian false-discovery probability (BFDP) was used for all analyses to account for multiple testing. Noteworthy associations (BFDP < 0.8) included 10 linked SNPs in tryptophan hydroxylase 2 (TPH2) (e.g. rs1386492: OR = 1.07, 95% CI 1.02-1.12), and a SNP in the mitogen-activated protein kinase 8 (MAPK8) (rs10857561: OR = 1.11, 95% CI 1.04-1.18). The SNP-SNP interaction analysis revealed noteworthy interaction terms with TPH2- and MAPK-related SNPs (e.g. rs1386483R ∧ rs1473473D ∧ rs3729931D: OR = 1.20, 95% CI 1.09-1.32). In line with the light-at-night hypothesis that links shift work with elevated breast-cancer risks our results point to SNPs in TPH2 and MAPK-genes that may impact the intricate network of circadian regulation.

Prospective validation of the BOADICEA multifactorial breast cancer risk prediction model in a large prospective cohort study.

BACKGROUND: The multifactorial Breast and Ovarian Analysis of Disease Incidence and Carrier Estimation Algorithm (BOADICEA) breast cancer risk prediction model has been recently extended to consider all established breast cancer risk factors. We assessed the clinical validity of the model in a large independent prospective cohort. METHODS: We validated BOADICEA (V.6) in the Swedish KARolinska Mammography Project for Risk Prediction of Breast Cancer (KARMA) cohort including 66 415 women of European ancestry (median age 54 years, IQR 45-63; 816 incident breast cancers) without previous cancer diagnosis. We calculated 5-year risks on the basis of questionnaire-based risk factors, pedigree-structured first-degree family history, mammographic density (BI-RADS), a validated breast cancer polygenic risk score (PRS) based on 313-SNPs, and pathogenic variant status in 8 breast cancer susceptibility genes: BRCA1, BRCA2, PALB2, CHEK2, ATM, RAD51C, RAD51D and BARD1. Calibration was assessed by comparing observed and expected risks in deciles of predicted risk and the calibration slope. The discriminatory ability was assessed using the area under the curve (AUC). RESULTS: Among the individual model components, the PRS contributed most to breast cancer risk stratification. BOADICEA was well calibrated in predicting the risks for low-risk and high-risk women when all, or subsets of risk factors are included in the risk prediction. Discrimination was maximised when all risk factors are considered (AUC=0.70, 95% CI: 0.66 to 0.73; expected-to-observed ratio=0.88, 95% CI: 0.75 to 1.04; calibration slope=0.97, 95% CI: 0.95 to 0.99). The full multifactorial model classified 3.6% women as high risk (5-year risk ≥3%) and 11.1% as very low risk (5-year risk <0.33%). CONCLUSION: The multifactorial BOADICEA model provides valid breast cancer risk predictions and a basis for personalised decision-making on disease prevention and screening.

Comprehensive epithelial tubo-ovarian cancer risk prediction model incorporating genetic and epidemiological risk factors.

BACKGROUND: Epithelial tubo-ovarian cancer (EOC) has high mortality partly due to late diagnosis. Prevention is available but may be associated with adverse effects. A multifactorial risk model based on known genetic and epidemiological risk factors (RFs) for EOC can help identify women at higher risk who could benefit from targeted screening and prevention. METHODS: We developed a multifactorial EOC risk model for women of European ancestry incorporating the effects of pathogenic variants (PVs) in BRCA1, BRCA2, RAD51C, RAD51D and BRIP1, a Polygenic Risk Score (PRS) of arbitrary size, the effects of RFs and explicit family history (FH) using a synthetic model approach. The PRS, PV and RFs were assumed to act multiplicatively. RESULTS: Based on a currently available PRS for EOC that explains 5% of the EOC polygenic variance, the estimated lifetime risks under the multifactorial model in the general population vary from 0.5% to 4.6% for the first to 99th percentiles of the EOC risk distribution. The corresponding range for women with an affected first-degree relative is 1.9%-10.3%. Based on the combined risk distribution, 33% of RAD51D PV carriers are expected to have a lifetime EOC risk of less than 10%. RFs provided the widest distribution, followed by the PRS. In an independent partial model validation, absolute and relative 5-year risks were well calibrated in quintiles of predicted risk. CONCLUSION: This multifactorial risk model can facilitate stratification, in particular among women with FH of cancer and/or moderate-risk and high-risk PVs. The model is available via the CanRisk Tool (www.canrisk.org).