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. Utilizing 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=1,595). The prediction models were validated using data from the Women's Health Initiative (N=883). We applied these models to genome-wide association study (GWAS) data of 122,977 breast cancer cases and 105,974 controls to evaluate if the genetically predicted DNA methylation levels at 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<7.94 × 10-7, including 45 CpGs residing in 18 genomic regions which 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.Includes CRUK, FP7 and RU

The admixture maximum likelihood test to test for association between rare variants and disease phenotypes.

BACKGROUND: The development of genotyping arrays containing hundreds of thousands of rare variants across the genome and advances in high-throughput sequencing technologies have made feasible empirical genetic association studies to search for rare disease susceptibility alleles. As single variant testing is underpowered to detect associations, the development of statistical methods to combine analysis across variants - so-called "burden tests" - is an area of active research interest. We previously developed a method, the admixture maximum likelihood test, to test multiple, common variants for association with a trait of interest. We have extended this method, called the rare admixture maximum likelihood test (RAML), for the analysis of rare variants. In this paper we compare the performance of RAML with six other burden tests designed to test for association of rare variants. RESULTS: We used simulation testing over a range of scenarios to test the power of RAML compared to the other rare variant association testing methods. These scenarios modelled differences in effect variability, the average direction of effect and the proportion of associated variants. We evaluated the power for all the different scenarios. RAML tended to have the greatest power for most scenarios where the proportion of associated variants was small, whereas SKAT-O performed a little better for the scenarios with a higher proportion of associated variants. CONCLUSIONS: The RAML method makes no assumptions about the proportion of variants that are associated with the phenotype of interest or the magnitude and direction of their effect. The method is flexible and can be applied to both dichotomous and quantitative traits and allows for the inclusion of covariates in the underlying regression model. The RAML method performed well compared to the other methods over a wide range of scenarios. Generally power was moderate in most of the scenarios, underlying the need for large sample sizes in any form of association testing.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Risk Analysis of Prostate Cancer in PRACTICAL Consortium--Response.

D.F. Easton was recipient of the CR-UK grant C1287/A10118. R.A. Eeles was recipient of the CR-UK grant C5047/A10692.This is the author accepted manuscript. The final version is available from the American Association for Cancer Research via http://dx.doi.org/10.1158/1055-9965.EPI-15-100

Cancer incidence in relatives of British Fanconi Anaemia patients.

BACKGROUND: Fanconi anemia (FA) is an autosomal recessive DNA repair disorder with affected individuals having a high risk of developing acute myeloid leukaemia and certain solid tumours. Thirteen complementation groups have been identified and the genes for all of these are known (FANCA, B, C, D1/BRCA2, D2, E, F, G, I, J/BRIP1, L, M and N/PALB2). Previous studies of cancer incidence in relatives of Fanconi anemia cases have produced conflicting results. A study of British FA families was therefore carried out to investigate this question, since increases in cancer risk in FA heterozygotes would have implications for counselling FA family members, and possibly also for the implementation of preventative screening measures in FA heterozygotes. METHODS: Thirty-six families took part and data was collected on 575 individuals (276 males, 299 females), representing 18,136 person years. In this cohort, 25 males and 30 females were reported with cancer under the age of 85 years, and 36 cancers (65%) could be confirmed from death certificates, cancer registries or clinical records. RESULTS: A total of 55 cancers were reported in the FA families compared to an estimated incidence of 56.95 in a comparable general population cohort, and the relative risk of cancer was 0.97 (95% C.I. = 0.71-1.23, p = 0.62) for FA family members. Analysis of relative risk for individual cancer types in each carrier probability group did not reveal any significant differences with the possible exception of prostate cancer (RR = 3.089 (95% C.I. = 1.09 - 8.78; Chi2 = 4.767, p = 0.029). CONCLUSION: This study has not shown a significant difference in overall cancer risk in FA families.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Protein-Coding Variants Implicate Novel Genes Related to Lipid Homeostasis Contributing to Body Fat Distribution

Body fat distribution is a heritable risk factor for a range of adverse health consequences, including hyperlipidemia and type 2 diabetes. To identify protein-coding variants associated with body fat distribution, assessed by waist-to-hip ratio adjusted for body mass index, we analyzed 246,328 431 predicted coding and splice site variants available on exome arrays in up to 344,369 individuals from five major ancestries for discovery and 132,177 independent European-ancestry individuals for validation. We identified 15 common (minor allele frequency, MAF ≥ 5%) and 9 low frequency or rare (MAF < 5%) coding variants that have not been reported previously. Pathway/gene set enrichment analyses of all associated variants highlight lipid particle, adiponectin level, abnormal white adipose tissue physiology, and bone development and morphology as processes affecting fat distribution and body shape. Furthermore, the cross-trait associations and the analyses of variant and gene function highlight a strong connection to lipids, cardiovascular traits, and type 2 diabetes. In functional follow-up analyses, specifically in Drosophila RNAi-knockdown crosses, we observed a significant increase in the total body triglyceride levels for two genes (DNAH10 and PLXND1). By examining variants often poorly tagged or entirely missed by genome-wide association studies, we implicate novel genes in fat distribution, stressing the importance of interrogating low-frequency and protein-coding variants

BRCA1 and BRCA2 mutation predictions using the BOADICEA and BRCAPRO models and penetrance estimation in high-risk French-Canadian families.

INTRODUCTION: Several genetic risk models for breast and ovarian cancer have been developed, but their applicability to specific populations has not been evaluated. We used data from French-Canadian families to evaluate the mutation predictions given by the BRCAPRO and BOADICEA models. We also used this data set to estimate the age-specific risks for breast and ovarian cancer in BRCA1 and BRCA2 mutation carriers. METHODS: A total of 195 families with multiple affected individuals with breast or ovarian cancer were recruited through the INHERIT (INterdisciplinary HEalth Research International Team on BReast CAncer susceptibility) BRCAs research program. Observed BRCA1 and BRCA2 mutation status was compared with predicted carrier probabilities under the BOADICEA and BRCAPRO models. The models were assessed using Brier scores, attributes diagrams and receiver operating characteristic curves. Log relative risks for breast and ovarian cancer in mutation carriers versus population risks were estimated by maximum likelihood, using a modified segregation analysis implemented in the computer program MENDEL. Twenty-five families were eligible for inclusion in the BRCA1 penetrance analysis and 27 families were eligible for the BRCA2 penetrance analysis. RESULTS: The BOADICEA model predicted accurately the number of BRCA1 and BRCA2 mutations for the various groups of families, and was found to discriminate well at the individual level between carriers and noncarriers. BRCAPRO over-predicted the number of mutations in almost all groups of families, in particular the number of BRCA1 mutations. It significantly overestimated the carrier frequency for high predicted probabilities. However, it discriminated well between carriers and noncarriers. Receiver operating characteristic (ROC) curves indicate similar sensitivity and specificity for BRCAPRO and BOADICEA. The estimated risks for breast and ovarian cancer in BRCA1 and BRCA2 mutation carriers were consistent with previously published estimates. CONCLUSION: The BOADICEA model predicts accurately the carrier probabilities in French-Canadian families and may be used for counselling in this population. None of the penetrance estimates was significantly different from previous estimates, suggesting that previous estimates may be appropriate for counselling in this population.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are

Incorporating truncating variants in PALB2, CHEK2, and ATM into the BOADICEA breast cancer risk model.

PURPOSE: The proliferation of gene panel testing precipitates the need for a breast cancer (BC) risk model that incorporates the effects of mutations in several genes and family history (FH). We extended the BOADICEA model to incorporate the effects of truncating variants in PALB2, CHEK2, and ATM. METHODS: The BC incidence was modeled via the explicit effects of truncating variants in BRCA1/2, PALB2, CHEK2, and ATM and other unobserved genetic effects using segregation analysis methods. RESULTS: The predicted average BC risk by age 80 for an ATM mutation carrier is 28%, 30% for CHEK2, 50% for PALB2, and 74% for BRCA1 and BRCA2. However, the BC risks are predicted to increase with FH burden. In families with mutations, predicted risks for mutation-negative members depend on both FH and the specific mutation. The reduction in BC risk after negative predictive testing is greatest when a BRCA1 mutation is identified in the family, but for women whose relatives carry a CHEK2 or ATM mutation, the risks decrease slightly. CONCLUSIONS: The model may be a valuable tool for counseling women who have undergone gene panel testing for providing consistent risks and harmonizing their clinical management. A Web application can be used to obtain BC risks in clinical practice (http://ccge.medschl.cam.ac.uk/boadicea/).Genet Med 18 12, 1190-1198.This work was funded by Cancer Research UK Grants C12292/A11174 and C1287/A10118. ACA is a Cancer Research UK Senior Cancer Research Fellow. This work was supported by the Governement of Canada through Genome Canada and the Canadian Institutes of Health Research, and the Ministère de l'enseignement supérieur, de la recherche, de la science et de la technologie du Québec through Génome Québec.This is the author accepted manuscript. The final version is available from Nature Publishing Group via http://dx.doi.org/10.1038/gim.2016.3

Genomic risk prediction of coronary artery disease in women with breast cancer: a prospective cohort study.

Funder: Wellcome TrustBackgroundAdvancements in cancer therapeutics have resulted in increases in cancer-related survival; however, there is a growing clinical dilemma. The current balancing of survival benefits and future cardiotoxic harms of oncotherapies has resulted in an increased burden of cardiovascular disease in breast cancer survivors. Risk stratification may help address this clinical dilemma. This study is the first to assess the association between a coronary artery disease-specific polygenic risk score and incident coronary artery events in female breast cancer survivors.MethodsWe utilized the Studies in Epidemiology and Research in Cancer Heredity prospective cohort involving 12,413 women with breast cancer with genotype information and without a baseline history of cardiovascular disease. Cause-specific hazard ratios for association of the polygenic risk score and incident coronary artery disease (CAD) were obtained using left-truncated Cox regression adjusting for age, genotype array, conventional risk factors such as smoking and body mass index, as well as other sociodemographic, lifestyle, and medical variables.ResultsOver a median follow-up of 10.3 years (IQR: 16.8) years, 750 incident fatal or non-fatal coronary artery events were recorded. A 1 standard deviation higher polygenic risk score was associated with an adjusted hazard ratio of 1.33 (95% CI 1.20, 1.47) for incident CAD.ConclusionsThis study provides evidence that a coronary artery disease-specific polygenic risk score can risk-stratify breast cancer survivors independently of other established cardiovascular risk factors

Parity and breast cancer risk among BRCA1 and BRCA2 mutation carriers.

INTRODUCTION: Increasing parity and age at first full-term pregnancy are established risk factors for breast cancer in the general population. However, their effects among BRCA1 and BRCA2 mutation carriers is still under debate. We used retrospective data on BRCA1 and BRCA2 mutation carriers from the UK to assess the effects of parity-related variables on breast cancer risk. METHODS: The data set included 457 mutation carriers who developed breast cancer (cases) and 332 healthy mutation carriers (controls), ascertained through families seen in genetic clinics. Hazard ratios were estimated by using a weighted cohort approach. RESULTS: Parous BRCA1 and BRCA2 mutation carriers were at a significantly lower risk of developing breast cancer (hazard ratio 0.54, 95% confidence interval 0.37 to 0.81; p = 0.002). The protective effect was observed only among carriers who were older than 40 years. Increasing age at first live birth was associated with an increased breast cancer risk among BRCA2 mutation carriers (p trend = 0.002) but not BRCA1 carriers. However, the analysis by age at first live birth was based on small numbers. CONCLUSION: The results suggest that the relative risks of breast cancer associated with parity among BRCA1 and BRCA2 mutation carriers may be similar to those in the general population and that reproductive history may be used to improve risk prediction in carriers.RIGHTS : This article is licensed under the BioMed Central licence at http://www.biomedcentral.com/about/license which is similar to the 'Creative Commons Attribution Licence'. In brief you may : copy, distribute, and display the work; make derivative works; or make commercial use of the work - under the following conditions: the original author must be given credit; for any reuse or distribution, it must be made clear to others what the license terms of this work are