Methylation scores for smoking, alcohol consumption and body mass index and risk of seven types of cancer

Methylation marks of exposure to health risk factors may be useful markers of cancer risk as they might better capture current and past exposures than questionnaires, and reflect different individual responses to exposure. We used data from seven case-control studies nested within the Melbourne Collaborative Cohort Study of blood DNA methylation and risk of colorectal, gastric, kidney, lung, prostate and urothelial cancer, and B-cell lymphoma (N cases = 3123). Methylation scores (MS) for smoking, body mass index (BMI), and alcohol consumption were calculated based on published data as weighted averages of methylation values. Rate ratios (RR) and 95% confidence intervals for association with cancer risk were estimated using conditional logistic regression and expressed per SD increase of the MS, with and without adjustment for health-related confounders. The contribution of MS to discriminate cases from controls was evaluated using the area under the curve (AUC). After confounder adjustment, we observed: large associations (RR = 1.5-1.7) with lung cancer risk for smoking MS; moderate associations (RR = 1.2-1.3) with urothelial cancer risk for smoking MS and with mature B-cell neoplasm risk for BMI and alcohol MS; moderate to small associations (RR = 1.1-1.2) for BMI and alcohol MS with several cancer types and cancer overall. Generally small AUC increases were observed after inclusion of several MS in the same model (colorectal, gastric, kidney, urothelial cancers: +3%; lung cancer: +7%; B-cell neoplasms: +8%). Methylation scores for smoking, BMI and alcohol consumption show independent associations with cancer risk, and may provide some improvements in risk prediction.

Heritable methylation marks associated with prostate cancer risk

DNA methylation marks that are inherited from parents to offspring are known to play a role in cancer risk and could explain part of the familial risk for cancer. We therefore conducted a genome-wide search for heritable methylation marks associated with prostate cancer risk. Peripheral blood DNA methylation was measured for 133 of the 469 members of 25 multiple-case prostate cancer families, using the EPIC array. We used these families to systematically search the genome for methylation marks with Mendelian patterns of inheritance, then we tested the 1,000 most heritable marks for association with prostate cancer risk. After correcting for multiple testing, 41 heritable methylation marks were associated with prostate cancer risk. Separate analyses, based on 869 incident cases and 869 controls from a prospective cohort study, showed that 9 of these marks near the metastable epiallele VTRNA2-1 were also nominally associated with aggressive prostate cancer risk in the population.

Epigenome-wide association study of short-term temperature fluctuations based on within-sibship analyses in Australian females

BACKGROUND

Temperature fluctuations can affect human health independent of the effect of mean temperature. However, no study has evaluated whether short-term temperature fluctuations could affect DNA methylation.

METHODS

Peripheral blood DNA methylation for 479 female siblings of 130 families were analysed. Gridded daily temperatures data were obtained, linked to each participant's home address, and used to calculate nine different metrics of short-term temperature fluctuations: temperature variabilities (TVs) within the day of blood draw and preceding one to seven days (TV 0-1 to TV 0-7), diurnal temperature range (DTR), and temperature change between neighbouring days (TCN). Within-sibship design was used to perform epigenome-wide association analyses, adjusting for daily mean temperatures, and other important covariates (e.g., smoking, alcohol use, cell-type proportions). Differentially methylated regions (DMRs) were further identified. Multiple-testing comparisons with a significant threshold of 0.01 for cytosine-guanine dinucleotides (CpGs) and 0.05 for DMRs were applied.

RESULTS

Among 479 participants (mean age ± SD, 56.4 ± 7.9 years), we identified significant changes in methylation levels in 14 CpGs and 70 DMRs associated with temperature fluctuations. Almost all identified CpGs were associated with exposure to temperature fluctuations within three days. Differentially methylated signals were mapped to 68 genes that were linked to human diseases such as cancer (e.g., colorectal carcinoma, breast carcinoma, and metastatic neoplasms) and mental disorder (e.g., schizophrenia, mental depression, and bipolar disorder). The top three most significantly enriched gene ontology terms were Response to bacterium (TV 0-3), followed by Hydrolase activity, acting on ester bonds (TCN), and Oxidoreductase activity (TV 0-3).

CONCLUSIONS

Short-term temperature fluctuations were associated with differentially methylated signals across the human genome, which provides evidence on the potential biological mechanisms underlying the health impact of temperature fluctuations. Future studies are needed to further clarify the roles of DNA methylation in diseases associated with temperature fluctuations.

Wildfire-related PM2.5 and DNA methylation: An Australian twin and family study

BACKGROUND

Wildfire-related fine particulate matter (PM_2.5) has many adverse health impacts, but its impacts on human epigenome are unknown. We aimed to evaluate the associations between long-term exposure to wildfire-related PM_2.5 and blood DNA methylation, and whether the associations differ from those with non-wildfire-related PM_2.5.

METHODS

We studied 479 Australian women comprising 132 twin pairs and 215 of their sisters. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on 3-year (year of blood collection and previous two years) average wildfire-related and non-wildfire-related PM_2.5 at 0.01°×0.01° spatial resolution were created by combining information from satellite observations, chemical transport models, and ground-based observations. Exposure data were linked to each participant's home address, assuming the address did not change during the exposure window. For DNA methylation of each cytosine-guanine dinucleotide (CpG), and for global DNA methylation represented by the average of all measured CpGs or CpGs in repetitive elements, we evaluated their associations with wildfire- or non-wildfire-related PM_2.5 using a within-sibship analysis controlling for factors shared between siblings and other important covariates. Differentially methylated regions (DMRs) were defined by comb-p and DMRcate.

RESULTS

The 3-year average wildfire-related PM_2.5 (range: 0.3 to 7.6 µg/m³_, mean: 1.6 µg/m³) was negatively, but not significantly (p-values greater than 0.05) associated with all seven global DNA methylation measures. There were 26 CpGs and 33 DMRs associated with wildfire-related PM_2.5 (Bonferroni adjusted p-value < 0.05) mapped to 47 genes enriched for pathways related to inflammatory regulation and platelet activation. These genes have been related to many human diseases or phenotypes e.g., cancer, mental disorders, diabetes, obesity, asthma, blood pressure. These CpGs, DMRs and enriched pathways did not overlap with the 1 CpG and 7 DMRs associated with non-wildfire-related PM_2.5.

CONCLUSIONS

Long-term exposure to wildfire-related PM_2.5 was associated with various blood DNA methylation signatures in Australian women, and these were distinct from those associated with non-wildfire-related PM_2.5.

Does genetic predisposition modify the effect of lifestyle-related factors on DNA methylation?

Lifestyle-related phenotypes have been shown to be heritable and associated with DNA methylation. We aimed to investigate whether genetic predisposition to tobacco smoking, alcohol consumption, and higher body mass index (BMI) moderates the effect of these phenotypes on blood DNA methylation. We calculated polygenic scores (PGS) to quantify genetic predisposition to these phenotypes using training (N = 7,431) and validation (N = 4,307) samples. Using paired genetic-methylation data (N = 4,307), gene-environment interactions (i.e., PGS × lifestyle) were assessed using linear mixed-effects models with outcomes: 1) methylation at sites found to be strongly associated with smoking (1,061 CpGs), alcohol consumption (459 CpGs), and BMI (85 CpGs) and 2) two epigenetic ageing measures, PhenoAge and GrimAge. In the validation sample, PGS explained ~1.4% (P = 1 × 10-14), ~0.6% (P = 2 × 10-7), and ~8.7% (P = 7 × 10-87) of variance in smoking initiation, alcohol consumption, and BMI, respectively. Nominally significant interaction effects (P < 0.05) were found at 61, 14, and 7 CpGs for smoking, alcohol consumption, and BMI, respectively. There was strong evidence that all lifestyle-related phenotypes were positively associated with PhenoAge and GrimAge, except for alcohol consumption with PhenoAge. There was weak evidence that the association of smoking with GrimAge was attenuated in participants genetically predisposed to smoking (interaction term: -0.022, standard error [SE] = 0.012, P = 0.058) and that the association of alcohol consumption with PhenoAge was attenuated in those genetically predisposed to drink alcohol (interaction term: -0.030, SE = 0.015, P = 0.041). In conclusion, genetic susceptibility to unhealthy lifestyles did not strongly modify the association between observed lifestyle behaviour and blood DNA methylation. Potential associations were observed for epigenetic ageing measures, which should be replicated in additional studies.

Early life affects late-life health through determining DNA methylation across the lifespan: A twin study

Background

Previous findings for the genetic and environmental contributions to DNA methylation variation were for limited age ranges only. We investigated the lifespan contributions and their implications for human health for the first time.

Methods

1,720 monozygotic twin (MZ) pairs and 1,107 dizygotic twin (DZ) pairs aged 0-92 years were included. Familial correlations (i.e., correlations between twins) for 353,681 methylation sites were estimated and modelled as a function of twin pair cohabitation history.

Findings

The methylome average familial correlation was around zero at birth (MZ pair: -0.01; DZ pair: -0.04), increased with the time of twins living together during childhood at rates of 0.16 (95%CI: 0.12-0.20) for MZ pairs and 0.13 (95%CI: 0.07-0.20) for DZ pairs per decade, and decreased with the time of living apart during adulthood at rates of 0.026 (95%CI: 0.019-0.033) for MZ pairs and 0.027 (95%CI: 0.011-0.043) for DZ pairs per decade. Neither the increasing nor decreasing rate differed by zygosity (both P>0.1), consistent with cohabitation environment shared by twins, rather than genetic factors, influencing the methylation familial correlation changes. Familial correlations for 6.6% (23,386/353,681) sites changed with twin pair cohabitation history. These sites were enriched for high heritability, proximal promoters, and epigenetic/genetic associations with various early-life factors and late-life health conditions.

Interpretation

Early life strongly influences DNA methylation variation across the lifespan, and the effects are stronger for heritable sites and sites biologically relevant to the regulation of gene expression. Early life could affect late-life health through influencing DNA methylation.

Funding

Victorian Cancer Agency, Cancer Australia, Cure Cancer Foundation.

Association of FOXO3 Blood DNA Methylation with Cancer Risk, Cancer Survival, and Mortality

Genetic variants in FOXO3 are associated with longevity. Here, we assessed whether blood DNA methylation at FOXO3 was associated with cancer risk, survival, and mortality. We used data from eight prospective case–control studies of breast (n = 409 cases), colorectal (n = 835), gastric (n = 170), kidney (n = 143), lung (n = 332), prostate (n = 869), and urothelial (n = 428) cancer and B-cell lymphoma (n = 438). Case–control pairs were matched on age, sex, country of birth, and smoking (lung cancer study). Conditional logistic regression was used to assess associations between cancer risk and methylation at 45 CpGs of FOXO3 included on the HumanMethylation450 assay. Mixed-effects Cox models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for associations with cancer survival (total n = 2286 deaths). Additionally, using data from 1088 older participants, we assessed associations of FOXO3 methylation with overall and cause-specific mortality (n = 354 deaths). Methylation at a CpG in the first exon region of FOXO3 (6:108882981) was associated with gastric cancer survival (HR = 2.39, 95% CI: 1.60–3.56, p = 1.9 × 10⁻⁵). Methylation at three CpGs in TSS1500 and gene body was associated with lung cancer survival (p < 6.1 × 10⁻⁵). We found no evidence of associations of FOXO3 methylation with cancer risk and mortality. Our findings may contribute to understanding the implication of FOXO3 in longevity.

Repeatability of methylation measures using a QIAseq targeted methyl panel and comparison with the Illumina HumanMethylation450 assay

OBJECTIVE

In previous studies using Illumina Infinium methylation arrays, we have identified DNA methylation marks associated with cancer predisposition and progression. In the present study, we have sought to find appropriate technology to both technically validate our data and expand our understanding of DNA methylation in these genomic regions. Here, we aimed to assess the repeatability of methylation measures made using QIAseq targeted methyl panel and to compare them with those obtained from the Illumina HumanMethylation450 (HM450K) assay. We included in the analysis high molecular weight DNA extracted from whole blood (WB) and DNA extracted from formalin-fixed paraffin-embedded tissues (FFPE).

RESULTS

The repeatability of QIAseq-methylation measures was assessed at 40 CpGs, using the Intraclass Correlation Coefficient (ICC). The mean ICCs and 95% confidence intervals (CI) were 0.72 (0.62-0.81), 0.59 (0.47-0.71) and 0.80 (0.73-0.88) for WB, FFPE and both sample types combined, respectively. For technical replicates measured using QIAseq and HM450K, the mean ICCs (95% CI) were 0.53 (0.39-0.68), 0.43 (0.31-0.56) and 0.70 (0.59-0.80), respectively. Bland-Altman plots indicated good agreement between QIAseq and HM450K measurements. These results demonstrate that the QIAseq targeted methyl panel produces reliable and reproducible methylation measurements across the 40 CpGs that were examined.

Ambient temperature and genome-wide DNA methylation: A twin and family study in Australia

Little is known about the association between ambient temperature and DNA methylation, which is a potential biological process through which ambient temperature affects health. This study aimed to evaluate the association between ambient temperature and DNA methylation across human genome. We included 479 Australian women, including 132 twin pairs and 215 sisters of these twins. Blood-derived DNA methylation was measured using the HumanMethylation450 BeadChip array. Data on average ambient temperature during eight different exposure windows [lag0d (the blood draw day), lag0-7d (the current day and previous seven days prior to blood draw), lag0-14d, lag0-21d, lag0-28d, lag0-90d, lag0-180d, and lag0-365d)] was linked to each participant's home address. For each cytosine-guanine dinucleotide (CpG), we evaluated the association between its methylation level and temperature using generalized estimating equations (GEE), adjusting for important covariates. We used comb-p and DMRcate to identify differentially methylated regions (DMRs). We identified 31 CpGs at which blood DNA methylation were significantly associated with ambient temperature with false discovery rate [FDR] < 0.05. There were 82 significant DMRs identified by both comb-p (Sidak p-value < 0.01) and DMRcate (FDR < 0.01). Most of these CpGs and DMRs only showed association with temperature during one specific exposure window. These CpGs and DMRs were mapped to 85 genes. These related genes have been related to many human chronic diseases or phenotypes (e.g., diabetes, arthritis, breast cancer, depression, asthma, body height) in previous studies. The signals of short-term windows (lag0d and lag0-21d) showed enrichment in biological processes related to cell adhesion. In conclusion, short-, medium-, and long-term exposures to ambient temperature were all associated with blood DNA methylation, but the target genomic loci varied by exposure window. These differential methylation signals may serve as potential biomarkers to understand the health impacts of temperature.

Smoking Methylation Marks for Prediction of Urothelial Cancer Risk

BACKGROUND

Self-reported information may not accurately capture smoking exposure. We aimed to evaluate whether smoking-associated DNA methylation markers improve urothelial cell carcinoma (UCC) risk prediction.

METHODS

Conditional logistic regression was used to assess associations between blood-based methylation and UCC risk using two matched case-control samples: 404 pairs from the Melbourne Collaborative Cohort Study (MCCS) and 440 pairs from the Women's Health Initiative (WHI) cohort. Results were pooled using fixed-effects meta-analysis. We developed methylation-based predictors of UCC and evaluated their prediction accuracy on two replication data sets using the area under the curve (AUC).

RESULTS

The meta-analysis identified associations (P < 4.7 × 10^-5) for 29 of 1,061 smoking-associated methylation sites, but these were substantially attenuated after adjustment for self-reported smoking. Nominally significant associations (P < 0.05) were found for 387 (36%) and 86 (8%) of smoking-associated markers without/with adjustment for self-reported smoking, respectively, with same direction of association as with smoking for 387 (100%) and 79 (92%) markers. A Lasso-based predictor was associated with UCC risk in one replication data set in MCCS [N = 134; odds ratio per SD (OR) = 1.37; 95% CI, 1.00-1.90] after confounder adjustment; AUC = 0.66, compared with AUC = 0.64 without methylation information. Limited evidence of replication was found in the second testing data set in WHI (N = 440; OR = 1.09; 95% CI, 0.91-1.30).

CONCLUSIONS

Combination of smoking-associated methylation marks may provide some improvement to UCC risk prediction. Our findings need further evaluation using larger data sets.

IMPACT

DNA methylation may be associated with UCC risk beyond traditional smoking assessment and could contribute to some improvements in stratification of UCC risk in the general population.

Residential surrounding greenness and DNA methylation: An epigenome-wide association study

BACKGROUND

DNA methylation is a potential biological mechanism through which residential greenness affects health, but little is known about its association with greenness and whether the association could be modified by genetic background. We aimed to evaluate the association between surrounding greenness and genome-wide DNA methylation and potential gene-greenness interaction effects on DNA methylation.

METHODS

We measured blood-derived DNA methylation using the HumanMethylation450 BeadChip array (Illumina) for 479 Australian women, including 66 monozygotic, 66 dizygotic twin pairs, and 215 sisters of these twins. Surrounding greenness was represented by Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) within 300, 500, 1000 or 2000 m surrounding participants' home addresses. For each cytosine-guanine dinucleotide (CpG), the associations between its methylation level and NDVI or EVI were evaluated by generalized estimating equations, after adjusting for age, education, marital status, area-level socioeconomic status, smoking behavior, cell-type proportions, and familial clustering. We used comb-p and DMRcate to identify significant differentially methylated regions (DMRs). For each significant CpG, we evaluated the interaction effects of greenness and single-nucleotide polymorphisms (SNPs) within ±1 Mb window on its methylation level.

RESULTS

We found associations between surrounding greenness and blood DNA methylation for one CpG (cg04720477, mapped to the promoter region of CNP gene) with false discovery rate [FDR] < 0.05, and for another 9 CpGs with 0.05 ≤ FDR < 0.10. For two of these CpGs, we found 33 SNPs significantly (FDR < 0.05) modified the greenness-methylation association. There were 35 significant DMRs related to surrounding greenness that were identified by both comb-p (Sidak p-value < 0.01) and DMRcate (FDR < 0.01). Those CpGs and DMRs were mapped to genes related to many human diseases, such as mental health disorders and neoplasms as well as nutritional and metabolic diseases.

CONCLUSIONS

Surrounding greenness was associated with blood DNA methylation of many loci across human genome, and this association could be modified by genetic variations.

870Methylation marks of prenatal exposure to maternal smoking and risk of cancer in adulthood

Background

Prenatal exposure to maternal smoking is detrimental to child health but its association with risk of cancer has seldom been investigated. Maternal smoking induces widespread and long-lasting DNA methylation changes, which we study here for association with risk of cancer in adulthood.

Methods

Eight prospective case-control studies nested within the Melbourne Collaborative Cohort Study were used to assess associations between maternal-smoking-associated methylation marks in blood and risk of several cancers: breast (N = 406 cases), colorectal (N = 814), gastric (N = 166), kidney (N = 139), lung (N = 327), prostate (N = 847) and urothelial cancer (N = 404) and B-cell lymphoma (N = 426). We used conditional logistic regression models to estimate odds ratios (OR) and 95% confidence intervals (CI) for associations between cancer and five methylation scores calculated as weighted averages for 568, 19, 15, 28, and 17 CpG sites. Models were adjusted for confounders, including personal smoking history (smoking status, pack-years, age at starting and quitting), and methylation scores for personal smoking.

Results

All methylation scores for maternal smoking were strongly positively associated with risk of urothelial cancer. Risk estimates were only slightly attenuated after adjustment for smoking history, other potential confounders and methylation scores for personal smoking. Potential inverse associations were observed with risk of lung cancer and B-cell lymphoma.

Conclusions

We found that methylation marks of prenatal exposure to maternal smoking are associated with increased risk of urothelial cancer.

Key messages

Our study demonstrates the potential for using DNA methylation to investigate the impact of early-life, unmeasured exposures on later-life cancer risk.

Surrounding Greenness and Biological Aging Based on DNA Methylation: A Twin and Family Study in Australia

BACKGROUND

High surrounding greenness has many health benefits and might contribute to slower biological aging. However, very few studies have evaluated this from the perspective of epigenetics.

OBJECTIVES

We aimed to evaluate the association between surrounding greenness and biological aging based on DNA methylation.

METHODS

We derived Horvath's DNA methylation age (DNAmAge), Hannum's DNAmAge, PhenoAge, and GrimAge based on DNA methylation measured in peripheral blood samples from 479 Australian women in 130 families. Measures of DNAmAge acceleration (DNAmAgeAC) were derived from the residuals after regressing each DNAmAge metric on chronological age. Greenness was represented by satellite-derived Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) metrics within 300-, 500-, 1,000-, and 2,000-m buffers surrounding participant addresses. Greenness-DNAmAgeAC associations were estimated using a within-sibship design fitted by linear mixed effect models, adjusting for familial clustering and important covariates.

RESULTS

Greenness metrics were associated with significantly lower DNAmAgeAC based on GrimAge acceleration, suggesting slower biological aging with higher greenness based on both NDVI and EVI in 300-2,000m buffer areas. For example, each interquartile range increase in NDVI within 1,000m was associated with a 0.59 (95% CI: 0.18, 1.01)-year decrease in GrimAge acceleration. Greenness was also inversely associated with three of the eight components of GrimAge, specifically, DNA methylation-based surrogates of serum cystatin-C, serum growth differentiation factor 15, and smoking pack years. Associations between greenness and biological aging measured by Horvath's and Hannum's DNAmAgeAC were less consistent, and depended on neighborhood socioeconomic status. No significant associations were estimated for PhenoAge acceleration.

DISCUSSION

Higher surrounding greenness was associated with slower biological aging, as indicated by GrimAge age acceleration, in Australian women. Associations were also evident for three individual components of GrimAge, but were inconsistent for other measures of biological aging. Additional studies are needed to confirm our results. https://doi.org/10.1289/EHP8793.

Characterization of a RAD51C-silenced high-grade serous ovarian cancer model during development of PARP inhibitor resistance

Acquired PARP inhibitor (PARPi) resistance in BRCA1- or BRCA2-mutant ovarian cancer often results from secondary mutations that restore expression of functional protein. RAD51C is a less commonly studied ovarian cancer susceptibility gene whose promoter is sometimes methylated, leading to homologous recombination (HR) deficiency and PARPi sensitivity. For this study, the PARPi-sensitive patient-derived ovarian cancer xenograft PH039, which lacks HR gene mutations but harbors RAD51C promoter methylation, was selected for PARPi resistance by cyclical niraparib treatment in vivo. PH039 acquired PARPi resistance by the third treatment cycle and grew through subsequent treatment with either niraparib or rucaparib. Transcriptional profiling throughout the course of resistance development showed widespread pathway level changes along with a marked increase in RAD51C mRNA, which reflected loss of RAD51C promoter methylation. Analysis of ovarian cancer samples from the ARIEL2 Part 1 clinical trial of rucaparib monotherapy likewise indicated an association between loss of RAD51C methylation prior to on-study biopsy and limited response. Interestingly, the PARPi resistant PH039 model remained platinum sensitive. Collectively, these results not only indicate that PARPi treatment pressure can reverse RAD51C methylation and restore RAD51C expression, but also provide a model for studying the clinical observation that PARPi and platinum sensitivity are sometimes dissociated.

Methylation marks of prenatal exposure to maternal smoking and risk of cancer in adulthood

BACKGROUND

Prenatal exposure to maternal smoking is detrimental to child health but its association with risk of cancer has seldom been investigated. Maternal smoking induces widespread and long-lasting DNA methylation changes, which we study here for association with risk of cancer in adulthood.

METHODS

Eight prospective case-control studies nested within the Melbourne Collaborative Cohort Study were used to assess associations between maternal-smoking-associated methylation marks in blood and risk of several cancers: breast (n = 406 cases), colorectal (n = 814), gastric (n = 166), kidney (n = 139), lung (n = 327), prostate (n = 847) and urothelial (n = 404) cancer and B-cell lymphoma (n = 426). We used conditional logistic regression models to estimate odds ratios (ORs) and 95% confidence intervals (CIs) for associations between cancer and five methylation scores calculated as weighted averages for 568, 19, 15, 28 and 17 CpG sites. Models were adjusted for confounders, including personal smoking history (smoking status, pack-years, age at starting and quitting) and methylation scores for personal smoking.

RESULTS

All methylation scores for maternal smoking were strongly positively associated with risk of urothelial cancer. Risk estimates were only slightly attenuated after adjustment for smoking history, other potential confounders and methylation scores for personal smoking. Potential negative associations were observed with risk of lung cancer and B-cell lymphoma. No associations were observed for other cancers.

CONCLUSIONS

We found that methylation marks of prenatal exposure to maternal smoking are associated with increased risk of urothelial cancer. Our study demonstrates the potential for using DNA methylation to investigate the impact of early-life, unmeasured exposures on later-life cancer risk.

DNA Methylation Signatures and the Contribution of Age-Associated Methylomic Drift to Carcinogenesis in Early-Onset Colorectal Cancer

Simple Summary

The role of DNA methylation in the carcinogenesis of colorectal cancer (CRC) diagnosed <50 years of age (early-onset CRC or EOCRC) is currently unknown. In this study, we investigated the genome-wide DNA methylation of 97 tumour and 54 normal colonic mucosa samples from people with EOCRC with the aim of identifying unique DNA methylation signatures and determining the role of ageing-related DNA methylation drift and age-acceleration in EOCRC aetiology. We found extensive DNA methylation alterations associated with EOCRC carcinogenesis, including a unique signature comprising 234 loci compared with CRCs from people >50 years of age. CpGs that undergo ageing-related methylation drift were significantly altered in EOCRC, and accelerated ageing was also evident in normal mucosa from people with EOCRC. Our study is the first study to identify unique DNA methylation changes in EOCRC, contributing novel information that may aid future efforts towards EOCRC prevention.

Abstract

We investigated aberrant DNA methylation (DNAm) changes and the contribution of ageing-associated methylomic drift and age acceleration to early-onset colorectal cancer (EOCRC) carcinogenesis. Genome-wide DNAm profiling using the Infinium HM450K on 97 EOCRC tumour and 54 normal colonic mucosa samples was compared with: (1) intermediate-onset CRC (IOCRC; diagnosed between 50–70 years; 343 tumour and 35 normal); and (2) late-onset CRC (LOCRC; >70 years; 318 tumour and 40 normal). CpGs associated with age-related methylation drift were identified using a public dataset of 231 normal mucosa samples from people without CRC. DNAm-age was estimated using epiTOC2. Common to all three age-of-onset groups, 88,385 (20% of all CpGs) CpGs were differentially methylated between tumour and normal mucosa. We identified 234 differentially methylated genes that were unique to the EOCRC group; 13 of these DMRs/genes were replicated in EOCRC compared with LOCRCs from TCGA. In normal mucosa from people without CRC, we identified 28,154 CpGs that undergo ageing-related DNAm drift, and of those, 65% were aberrantly methylated in EOCRC tumours. Based on the mitotic-based DNAm clock epiTOC2, we identified age acceleration in normal mucosa of people with EOCRC compared with normal mucosa from the IOCRC, LOCRC groups (p = 3.7 × 10⁻¹⁶) and young people without CRC (p = 5.8 × 10⁻⁶). EOCRC acquires unique DNAm alterations at 234 loci. CpGs associated with ageing-associated drift were widely affected in EOCRC without needing the decades-long accrual of DNAm drift as commonly seen in intermediate- and late-onset CRCs. Accelerated ageing in normal mucosa from people with EOCRC potentially underlies the earlier age of diagnosis in CRC carcinogenesis.

Epigenetic Drift Association with Cancer Risk and Survival, and Modification by Sex

Simple Summary

Ageing is the strongest cancer risk factor, and men and women exhibit different risk profiles in terms of incidence and survival. DNA methylation is known to strongly vary by age and sex. Epigenetic drift refers to age-related DNA methylation changes and the tendency for increasing discordance between epigenomes over time, but it remains unknown to what extent the epigenetic drift contributes to cancer risk and survival. The aims of this study were to identify age-associated, sex-associated and sexually dimorphic age-associated (age-by-sex-associated) DNA methylation markers and investigate whether age- and age-by-sex-associated markers are associated with cancer risk and survival. Our study, which used a total of 2754 matched case–control pairs with DNA methylation in pre-diagnostic blood, is the first large study to examine the association between sex-specific epigenetic drift and cancer development and progression. The results may be useful for cancer early diagnosis and prediction of prognosis.

Abstract

To investigate age- and sex-specific DNA methylation alterations related to cancer risk and survival, we used matched case–control studies of colorectal (n = 835), gastric (n = 170), kidney (n = 143), lung (n = 332), prostate (n = 869) and urothelial (n = 428) cancers, and mature B-cell lymphoma (n = 438). Linear mixed-effects models were conducted to identify age-, sex- and age-by-sex-associated methylation markers using a discovery (controls)-replication (cases) strategy. Replication was further examined using summary statistics from Generation Scotland (GS). Associations between replicated markers and risk of and survival from cancer were assessed using conditional logistic regression and Cox models (hazard ratios (HR)), respectively. We found 32,659, 23,141 and 48 CpGs with replicated associations for age, sex and age-by-sex, respectively. The replication rates for these CpGs using GS summary data were 94%, 86% and 91%, respectively. Significant associations for cancer risk and survival were identified at some individual age-related CpGs. Opposite to previous findings using epigenetic clocks, there was a strong negative trend in the association between epigenetic drift and risk of colorectal cancer. Methylation at two CpGs overlapping TMEM49 and ARX genes was associated with survival of overall (HR = 0.91, p = 7.7 × 10⁻⁴) and colorectal (HR = 1.52, p = 1.8 × 10⁻⁴) cancer, respectively, with significant age-by-sex interaction. Our results may provide markers for cancer early detection and prognosis prediction.

Association of variably methylated tumour DNA regions with overall survival for invasive lobular breast cancer

Background

Tumour DNA methylation profiling has shown potential to refine disease subtyping and improve the diagnosis and prognosis prediction of breast cancer. However, limited data exist regarding invasive lobular breast cancer (ILBC). Here, we investigated the genome-wide variability of DNA methylation levels across ILBC tumours and assessed the association between methylation levels at the variably methylated regions and overall survival in women with ILBC.

Methods

Tumour-enriched DNA was prepared by macrodissecting formalin-fixed paraffin embedded (FFPE) tumour tissue from 130 ILBCs diagnosed in the participants of the Melbourne Collaborative Cohort Study (MCCS). Genome-wide tumour DNA methylation was measured using the HumanMethylation 450K (HM450K) BeadChip array. Variably methylated regions (VMRs) were identified using the DMRcate package in R. Cox proportional hazards regression models were used to assess the association between methylation levels at the ten most significant VMRs and overall survival. Gene set enrichment analyses were undertaken using the web-based tool Metaspace. Replication of the VMR and survival analysis findings was examined using data retrieved from The Cancer Genome Atlas (TCGA) for 168 ILBC cases. We also examined the correlation between methylation and gene expression for the ten VMRs of interest using TCGA data.

Results

We identified 2771 VMRs (P < 10⁻⁸) in ILBC tumours. The ten most variably methylated clusters were predominantly located in the promoter region of the genes: ISM1, APC, TMEM101, ASCL2, NKX6, HIST3H2A/HIST3H2BB, HCG4P3, HES5, CELF2 and EFCAB4B. Higher methylation level at several of these VMRs showed an association with reduced overall survival in the MCCS. In TCGA, all associations were in the same direction, however stronger than in the MCCS. The pooled analysis of the MCCS and TCGA data showed that methylation at four of the ten genes was associated with reduced overall survival, independently of age and tumour stage; APC: Hazard Ratio (95% Confidence interval) per one-unit M-value increase: 1.18 (1.02–1.36), TMEM101: 1.23 (1.02–1.48), HCG4P3: 1.37 (1.05–1.79) and CELF2: 1.21 (1.02–1.43). A negative correlation was observed between methylation and gene expression for CELF2 (R = − 0.25, P = 0.001), but not for TMEM101 and APC.

Conclusions

Our study identified regions showing greatest variability across the ILBC tumour genome and found methylation at several genes to potentially serve as a biomarker of survival for women with ILBC.

Biological Aging Measures Based on Blood DNA Methylation and Risk of Cancer: A Prospective Study

Background

We previously investigated the association between 5 "first-generation" measures of epigenetic aging and cancer risk in the Melbourne Collaborative Cohort Study. This study assessed cancer risk associations for 3 recently developed methylation-based biomarkers of aging: PhenoAge, GrimAge, and predicted telomere length.

Methods

We estimated rate ratios (RRs) for the association between these 3 age-adjusted measures and risk of colorectal (N = 813), gastric (N = 165), kidney (N = 139), lung (N = 327), mature B-cell (N = 423), prostate (N = 846), and urothelial (N = 404) cancer using conditional logistic regression models. We also assessed associations by time since blood draw and by cancer subtype, and we investigated potential nonlinearity.

Results

We observed relatively strong associations of age-adjusted PhenoAge with risk of colorectal, kidney, lung, mature B-cell, and urothelial cancers (RR per SD was approximately 1.2-1.3). Similar findings were obtained for age-adjusted GrimAge, but the association with lung cancer risk was much larger (RR per SD = 1.82, 95% confidence interval [CI] = 1.44 to 2.30), after adjustment for smoking status, pack-years, starting age, time since quitting, and other cancer risk factors. Most associations appeared linear, larger than for the first-generation measures, and were virtually unchanged after adjustment for a large set of sociodemographic, lifestyle, and anthropometric variables. For cancer overall, the comprehensively adjusted rate ratio per SD was 1.13 (95% CI = 1.07 to 1.19) for PhenoAge and 1.12 (95% CI = 1.05 to 1.20) for GrimAge and appeared larger within 5 years of blood draw (RR = 1.29, 95% CI = 1.15 to 1.44 and 1.19, 95% CI = 1.06 to 1.33, respectively).

Conclusions

The methylation-based measures PhenoAge and GrimAge may provide insights into the relationship between biological aging and cancer and be useful to predict cancer risk, particularly for lung cancer.

Genetic and environmental causes of variation in epigenetic aging across the lifespan

Background

DNA methylation-based biological age (DNAm age) is an important biomarker for adult health. Studies in specific age ranges have found widely varying results about its genetic and environmental causes of variation. However, these studies are not able to provide a comprehensive view of the causes of variation over the lifespan.

Results

In order to investigate the genetic and environmental causes of DNAm age variation across the lifespan, we pooled genome-wide DNA methylation data for 4217 people aged 0–92 years from 1871 families. DNAm age was calculated using the Horvath epigenetic clock. We estimated familial correlations in DNAm age for monozygotic (MZ) twin, dizygotic (DZ) twin, sibling, parent–offspring, and spouse pairs by cohabitation status. Genetic and environmental variance components models were fitted and compared. We found that twin pair correlations were − 0.12 to 0.18 around birth, not different from zero (all P > 0.29). For all pairs of relatives, their correlations increased with time spent living together (all P < 0.02) at different rates (MZ > DZ and siblings > parent–offspring; P < 0.001) and decreased with time spent living apart (P = 0.02) at similar rates. These correlation patterns were best explained by cohabitation-dependent shared environmental factors, the effects of which were 1.41 (95% confidence interval [CI] 1.16 to 1.66) times greater for MZ pairs than for DZ and sibling pairs, and the latter were 2.03 (95% CI 1.13 to 9.47) times greater than for parent–offspring pairs. Genetic factors explained 13% (95% CI − 10 to 35%) of variation (P = 0.27). Similar results were found for another two epigenetic clocks, suggesting that our observations are robust to how DNAm age is measured. In addition, results for the other clocks were consistent with there also being a role for prenatal environmental factors in determining their variation.

Conclusions

Variation in DNAm age is mostly caused by environmental factors, including those shared to different extents by relatives while living together and whose effects persist into old age. The equal environment assumption of the classic twin study might not hold for epigenetic aging.

DNA Methylation in Peripheral Blood and Risk of Gastric Cancer: A Prospective Nested Case-control Study

DNA methylation in peripheral blood is a potential biomarker of gastric cancer risk which could be used for early detection. We conducted a prospective case-control study nested within the Melbourne Collaborative Cohort Study. Genomic DNA was prepared from blood samples collected a median of 12 years before diagnosis for cases (N = 168). Controls (N = 163) were matched to cases on sex, year of birth, country of birth, and blood sample type using incidence density sampling. Genome-wide DNA methylation was measured using the Infinium HumanMethylation450K Beadchip. Global measures of DNA methylation were defined as the median methylation M value, calculated for each of 13 CpG subsets representing genomic function, mean methylation and location, and reliability of measurement. Conditional logistic regression was conducted to assess associations between these global measures of methylation and gastric cancer risk, adjusting for Helicobacter pylori and other potential confounders. We tested nonlinear associations using quintiles of the global measure distribution. A genome-wide association study of DNA methylation and gastric cancer risk was also conducted (N = 484,989 CpGs) using conditional logistic regression, adjusting for potential confounders. Differentially methylated regions (DMR) were investigated using the R package DMRcate We found no evidence of associations with gastric cancer risk for individual CpGs or DMRs (P > 7.6 × 10^-6). No evidence of association was observed with global measures of methylation (OR 1.07 per SD of overall median methylation; 95% confidence interval, 0.80-1.44; P = 0.65). We found no evidence that blood DNA methylation is prospectively associated with gastric cancer risk.Prevention Relevance: We studied DNA methylation in blood to try and predict who was at risk of gastric cancer before symptoms developed, by which stage survival is poor. We did not find any such markers, but the importance of early diagnosis in gastric cancer remains, and the search for markers continues.

Smoking and blood DNA methylation: an epigenome-wide association study and assessment of reversibility

We conducted a genome-wide association study of blood DNA methylation and smoking, attempted replication of previously discovered associations, and assessed the reversibility of smoking-associated methylation changes. DNA methylation was measured in baseline peripheral blood samples for 5,044 participants in the Melbourne Collaborative Cohort Study. For 1,032 participants, these measures were repeated using blood samples collected at follow-up, a median of 11 years later. A cross-sectional analysis of the association between smoking and DNA methylation and a longitudinal analysis of changes in smoking status and changes in DNA methylation were conducted. We used our cross-sectional analysis to replicate previously reported associations for current (N = 3,327) and former (N = 172) smoking. A comprehensive smoking index accounting for the biological half-life of smoking compounds and several aspects of smoking history was constructed to assess the reversibility of smoking-induced methylation changes. This measure of lifetime exposure to smoking allowed us to detect more associations than comparing current with never smokers. We identified 4,496 cross-sectional associations at P < 10-7, including 3,296 annotated to 1,326 genes that were not previously implicated in smoking-associated DNA methylation changes at this significance threshold. We replicated the majority of previously reported associations (P < 10-7) for current and former smokers. In our data, we observed for former smokers a substantial degree of return to the methylation levels of never smokers, compared with current smokers (median: 74%, IQR = 63-86%), corresponding to small values (median: 2.75, IQR = 1.5-5.25) for the half-life parameter of the comprehensive smoking index. Longitudinal analyses identified 368 sites at which methylation changed upon smoking cessation. Our study demonstrates the usefulness of the comprehensive smoking index to detect associations between smoking and DNA methylation at CpGs across the genome, replicates the vast majority of previously reported associations, and quantifies the reversibility of smoking-induced methylation changes.

Integrating DNA methylation measures to improve clinical risk assessment: are we there yet? The case of BRCA1 methylation marks to improve clinical risk assessment of breast cancer

Current risk prediction models estimate the probability of developing breast cancer over a defined period based on information such as family history, non-genetic breast cancer risk factors, genetic information from high and moderate risk breast cancer susceptibility genes and, over the past several years, polygenic risk scores (PRS) from more than 300 common variants. The inclusion of additional data such as PRS improves risk stratification, but it is anticipated that the inclusion of epigenetic marks could further improve model performance accuracy. Here, we present the case for including information on DNA methylation marks to improve the accuracy of these risk prediction models, and consider how this approach contrasts genetic information, as identifying DNA methylation marks associated with breast cancer risk differs inherently according to the source of DNA, approaches to the measurement of DNA methylation, and the timing of measurement. We highlight several DNA-methylation-specific challenges that should be considered when incorporating information on DNA methylation marks into risk prediction models, using BRCA1, a highly penetrant breast cancer susceptibility gene, as an example. Only after careful consideration of study design and DNA methylation measurement will prospective performance of the incorporation of information regarding DNA methylation marks into risk prediction models be valid.

Genome-wide association study of peripheral blood DNA methylation and conventional mammographic density measures

Age- and body mass index (BMI)-adjusted mammographic density is one of the strongest breast cancer risk factors. DNA methylation is a molecular mechanism that could underlie inter-individual variation in mammographic density. We aimed to investigate the association between breast cancer risk-predicting mammographic density measures and blood DNA methylation. For 436 women from the Australian Mammographic Density Twins and Sisters Study and 591 women from the Melbourne Collaborative Cohort Study, mammographic density (dense area, nondense area and percentage dense area) defined by the conventional brightness threshold was measured using the CUMULUS software, and peripheral blood DNA methylation was measured using the HumanMethylation450 (HM450) BeadChip assay. Associations between DNA methylation at >400,000 sites and mammographic density measures adjusted for age and BMI were assessed within each cohort and pooled using fixed-effect meta-analysis. Associations with methylation at genetic loci known to be associated with mammographic density were also examined. We found no genome-wide significant (p < 10^-7 ) association for any mammographic density measure from the meta-analysis, or from the cohort-specific analyses. None of the 299 methylation sites located at genetic loci associated with mammographic density was associated with any mammographic density measure after adjusting for multiple testing (all p > 0.05/299 = 1.7 × 10^-4 ). In summary, our study did not find evidence for associations between blood DNA methylation, as measured by the HM450 assay, and conventional mammographic density measures that predict breast cancer risk.

Causes of blood methylomic variation for middle-aged women measured by the HumanMethylation450 array

To address the limitations in current classic twin/family research on the genetic and/or environmental causes of human methylomic variation, we measured blood DNA methylation for 479 women (mean age 56 years) including 66 monozygotic (MZ), 66 dizygotic (DZ) twin pairs and 215 sisters of twins, and 11 random technical duplicates using the HumanMethylation450 array. For each methylation site, we estimated the correlation for pairs of duplicates, MZ twins, DZ twins, and siblings, fitted variance component models by assuming the variation is explained by genetic factors, by shared and individual environmental factors, and by independent measurement error, and assessed the best fitting model. We found that the average (standard deviation) correlations for duplicate, MZ, DZ, and sibling pairs were 0.10 (0.35), 0.07 (0.21), -0.01 (0.14) and -0.04 (0.07). At the genome-wide significance level of 10^-7, 93.3% of sites had no familial correlation, and 5.6%, 0.1%, and 0.2% of sites were correlated for MZ, DZ, and sibling pairs. For 86.4%, 6.9%, and 7.1% of sites, the best fitting model included measurement error only, a genetic component, and at least one environmental component. For the 13.6% of sites influenced by genetic and/or environmental factors, the average proportion of variance explained by environmental factors was greater than that explained by genetic factors (0.41 vs. 0.37, P value <10^-15). Our results are consistent with, for middle-aged woman, blood methylomic variation measured by the HumanMethylation450 array being largely explained by measurement error, and more influenced by environmental factors than by genetic factors.

Genome-wide DNA methylation assessment of 'BRCA1-like' early-onset breast cancer: Data from the Australian Breast Cancer Family Registry

Breast cancers arising in women carrying a germline mutation in BRCA1 are typically high-grade, early-onset and have distinct morphological features (BRCA1-like). However, the majority of early-onset breast cancers of this morphological type are not associated with germline BRCA1 mutations or constitutional BRCA1 promoter methylation. We aimed to assess DNA methylation across the genome for associations with the "BRCA1-like" morphology. Genome-wide methylation in blood-derived DNA was measured using the Infinium HumanMethylation450K BeadChip assay for women under the age of 40 years participating in the Australian Breast Cancer Family Study (ABCFS) diagnosed with: i) BRCA1-like breast cancer (n = 30); and ii) breast cancer without BRCA1-like morphological features (non BRCA1-like; n = 30), and age-matched unaffected women (controls; n = 30). Corresponding tumour-derived DNA from 43 of the affected women was also assessed. Methylation of blood-derived DNA was found to be elevated across 17 consecutive marks in the BRCA1 promoter region and decreased at several other genomic regions (including TWIST2 and CTBP1) for 7 women (23%) diagnosed with BRCA1-like breast cancer compared with women in the other groups. Corresponding tumour-derived DNA available from 5 of these 7 women had elevated methylation within the BRCA1 and SPHK2 promoter region and decreased methylation within the ADAP1, IGF2BP3 and SPATA13 promoter region when compared with the other breast tumours. These methylation marks could be biomarkers of risk for BRCA1-like breast cancer, and could be responsible in part for their distinctive morphological features and biology. As such, they may assist with prevention and targeted therapies for this cancer subtype.

Inference about causation between body mass index and DNA methylation in blood from a twin family study

BACKGROUND

Several studies have reported DNA methylation in blood to be associated with body mass index (BMI), but few have investigated causal aspects of the association. We used a twin family design to assess this association at two life points and applied a novel analytical approach to appraise the evidence for causality.

METHODS

The methylation profile of DNA from peripheral blood was measured for 479 Australian women from 130 twin families. Linear regression was used to estimate the associations of DNA methylation at ~410,000 cytosine-guanine dinucleotides (CpGs), and of the average DNA methylation at ~20,000 genes, with current BMI, BMI at age 18-21 years, and the change between the two (BMI change). A novel regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess causation.

RESULTS

At a 5% false discovery rate, nine, six and 12 CpGs at 24 loci were associated with current BMI, BMI at age 18-21 years and BMI change, respectively. The average DNA methylation of the BHLHE40 and SOCS3 loci was associated with current BMI, and of the PHGDH locus with BMI change. From the ICE FALCON analyses with BMI as the predictor and DNA methylation as the outcome, a woman's DNA methylation level was associated with her co-twin's BMI, and the association disappeared after conditioning on her own BMI, consistent with BMI causing DNA methylation. To the contrary, using DNA methylation as the predictor and BMI as the outcome, a woman's BMI was not associated with her co-twin's DNA methylation level, consistent with DNA methylation not causing BMI.

CONCLUSION

For middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with current BMI, BMI at age 18-21 years and BMI change. Our study suggests that BMI has a causal effect on peripheral blood DNA methylation.

Obtaining high quality transcriptome data from formalin-fixed, paraffin-embedded diagnostic prostate tumor specimens

Prognostic genomic biomarkers that can be measured at diagnosis to aid choice of treatment options are unavailable for most common cancers. This is due in part to the poor quality and quantity of available diagnostic specimens for discovery research and to limitations in genomic technologies. Recent technical advances now enable high-density molecular analyses using suboptimal biological specimens. Here we describe the optimization of a transcriptome-specific protocol for use with formalin-fixed, paraffin-embedded (FFPE) diagnostic prostate cancer (PrCa) specimens. We applied the Ion AmpliSeq Transcriptome Human Gene Expression Kit (AmpliSeq Kit) to RNA samples extracted from 36 tumor-enriched and 16 adjacent normal tissues (ADJ_NT) from 37 FFPE PrCa specimens over a series of eight pilot studies, incorporating protocol modifications from Pilots 2 to 5. Data quality were measured by (1) the total number of mapped reads; (2) the percentage of reads that mapped to AmpliSeq target regions (OnTarget%); (3) the percentage of genes on the AmpliSeq panel with a read count ≥10 (TargetsDetected%); and (4) comparing the gene read-count distribution of the prostate tissue samples with the median gene read-count distribution of cell line-derived RNA samples. Modifications incorporated into Pilot study 5 provided gene expression data equivalent to cell line-derived RNA samples. These modifications included the use of freshly cut slides for macrodissection; increased tissue section thickness (8 µm); RNA extraction using the RecoverAll Total Nucleic Acid Isolation Kit for FFPE (ThermoFisher); 18 target amplification cycles; and processing six samples per Ion PI chip. This protocol will facilitate the discovery of prognostic biomarkers for cancer by allowing researchers to exploit previously underutilized diagnostic FFPE specimens.

Genome-wide average DNA methylation is determined in utero

BACKGROUND

Investigating the genetic and environmental causes of variation in genome-wide average DNA methylation (GWAM), a global methylation measure from the HumanMethylation450 array, might give a better understanding of genetic and environmental influences on methylation.

METHODS

We measured GWAM for 2299 individuals aged 0 to 90 years from seven twin and/or family studies. We estimated familial correlations, modelled correlations with cohabitation history and fitted variance components models for GWAM.

RESULTS

The correlation in GWAM for twin pairs was ∼0.8 at birth, decreased with age during adolescence and was constant at ∼0.4 throughout adulthood, with no evidence that twin pair correlations differed by zygosity. Non-twin first-degree relatives were correlated, from 0.17 [95% confidence interval (CI): 0.05-0.30] to 0.28 (95% CI: 0.08-0.48), except for middle-aged siblings (0.01, 95% CI: -0.10-0.12), and the correlation increased with time living together and decreased with time living apart. Spouse pairs were correlated in all studies, from 0.23 (95% CI: 0.3-0.43) to 0.31 (95% CI: 0.05-0.52), and the correlation increased with time living together. The variance explained by environmental factors shared by twins alone was 90% (95% CI: 74-95%) at birth, decreased in early life and plateaued at 28% (95% CI: 17-39%) in middle age and beyond. There was a cohabitation-related environmental component of variance.

CONCLUSIONS

GWAM is determined in utero by prenatal environmental factors, the effects of which persist throughout life. The variation of GWAM is also influenced by environmental factors shared by family members, as well as by individual-specific environmental factors.

Association of DNA Methylation-Based Biological Age With Health Risk Factors and Overall and Cause-Specific Mortality

Measures of biological age based on blood DNA methylation, referred to as age acceleration (AA), have been developed. We examined whether AA was associated with health risk factors and overall and cause-specific mortality. At baseline (1990-1994), blood samples were drawn from 2,818 participants in the Melbourne Collaborative Cohort Study (Melbourne, Victoria, Australia). DNA methylation was determined using the Infinium HumanMethylation450 BeadChip array (Illumina Inc., San Diego, California). Mixed-effects models were used to examine the association of AA with health risk factors. Cox models were used to assess the association of AA with mortality. A total of 831 deaths were observed during a median 10.7 years of follow-up. Associations of AA were observed with male sex, Greek nationality (country of birth), smoking, obesity, diabetes, lower education, and meat intake. AA measures were associated with increased mortality, and this was only partly accounted for by known determinants of health (hazard ratios were attenuated by 20%-40%). Weak evidence of heterogeneity in the association was observed by sex (P = 0.06) and cause of death (P = 0.07) but not by other factors. DNA-methylation-based AA measures are associated with several major health risk factors, but these do not fully explain the association between AA and mortality. Future research should investigate what genetic and environmental factors determine AA.

Heritable DNA methylation marks associated with susceptibility to breast cancer

Mendelian-like inheritance of germline DNA methylation in cancer susceptibility genes has been previously reported. We aimed to scan the genome for heritable methylation marks associated with breast cancer susceptibility by studying 25 Australian multiple-case breast cancer families. Here we report genome-wide DNA methylation measured in 210 peripheral blood DNA samples provided by family members using the Infinium HumanMethylation450. We develop and apply a new statistical method to identify heritable methylation marks based on complex segregation analysis. We estimate carrier probabilities for the 1000 most heritable methylation marks based on family structure, and we use Cox proportional hazards survival analysis to identify 24 methylation marks with corresponding carrier probabilities significantly associated with breast cancer. We replicate an association with breast cancer risk for four of the 24 marks using an independent nested case-control study. Here, we report a novel approach for identifying heritable DNA methylation marks associated with breast cancer risk.

Causal effect of smoking on DNA methylation in peripheral blood: a twin and family study

Background

Smoking has been reported to be associated with peripheral blood DNA methylation, but the causal aspects of the association have rarely been investigated. We aimed to investigate the association and underlying causation between smoking and blood methylation.

Methods

The methylation profile of DNA from the peripheral blood, collected as dried blood spots stored on Guthrie cards, was measured for 479 Australian women including 66 monozygotic twin pairs, 66 dizygotic twin pairs, and 215 sisters of twins from 130 twin families using the Infinium HumanMethylation450K BeadChip array. Linear regression was used to estimate associations between methylation at ~ 410,000 cytosine-guanine dinucleotides (CpGs) and smoking status. A regression-based methodology for twins, Inference about Causation through Examination of Familial Confounding (ICE FALCON), was used to assess putative causation.

Results

At a 5% false discovery rate, 39 CpGs located at 27 loci, including previously reported AHRR, F2RL3, 2q37.1 and 6p21.33, were found to be differentially methylated across never, former and current smokers. For all 39 CpG sites, current smokers had the lowest methylation level. Our study provides the first replication for two previously reported CpG sites, cg06226150 (SLC2A4RG) and cg21733098 (12q24.32). From the ICE FALCON analysis with smoking status as the predictor and methylation score as the outcome, a woman’s methylation score was associated with her co-twin’s smoking status, and the association attenuated towards the null conditioning on her own smoking status, consistent with smoking status causing changes in methylation. To the contrary, using methylation score as the predictor and smoking status as the outcome, a woman’s smoking status was not associated with her co-twin’s methylation score, consistent with changes in methylation not causing smoking status.

Conclusions

For middle-aged women, peripheral blood DNA methylation at several genomic locations is associated with smoking. Our study suggests that smoking has a causal effect on peripheral blood DNA methylation, but not vice versa.

Electronic supplementary material

The online version of this article (10.1186/s13148-018-0452-9) contains supplementary material, which is available to authorized users.

The utility of DNA extracted from saliva for genome-wide molecular research platforms

OBJECTIVE

The study aimed to investigate the suitability of DNA extracted from saliva for high throughput molecular genotyping and DNA methylation platforms by comparing its performance with that of DNA extracted from blood. The genome-wide methylation profile, using the Infinium HumanMethylation450 Beadchip array^® (Illumina, San Diego, CA), was measured for 20 DNA samples. Common genetic variation was measured, using the Infinium HumanCore Beadchip^® (Illumina, San Diego, CA) for 4 samples (matching samples from 2 people).

RESULTS

DNA from blood and saliva returned genotyping call rates and reproducibility frequencies of > 99%. High-quality DNA methylation data was obtained from both saliva and blood DNA, with average detection p-values for each sample ranging from 0.001 to 0.006. Slightly higher global DNA methylation levels were observed in whole blood DNA than saliva DNA. Correlations between individuals for each sample type were generally greater than correlations between two sample types from the same individual (Pearson's correlation, r = 0.9696 in 10 pairs of matched blood and saliva derived DNA, r = 0.9702 between saliva samples, and r = 0.9769 between blood derived DNA). Saliva yields DNA of sufficient quantity and quality to compare favourably with blood as a source of DNA for genetic and epigenetic research purposes.

DNA methylation-based biological aging and cancer risk and survival: Pooled analysis of seven prospective studies

The association between aging and cancer is complex. Recent studies have developed measures of biological aging based on DNA methylation and called them "age acceleration." We aimed to assess the associations of age acceleration with risk of and survival from seven common cancers. Seven case-control studies of DNA methylation and colorectal, gastric, kidney, lung, prostate and urothelial cancer and B-cell lymphoma nested in the Melbourne Collaborative Cohort Study were conducted. Cancer cases, vital status and cause of death were ascertained through linkage with cancer and death registries. Conditional logistic regression and Cox models were used to estimate odds ratios (OR) and hazard ratios (HR) and 95% confidence intervals (CI) for associations of five age acceleration measures derived from the Human Methylation 450 K Beadchip assay with cancer risk (N = 3,216 cases) and survival (N = 1,726 deaths), respectively. Epigenetic aging was associated with increased cancer risk, ranging from 4% to 9% per five-year age acceleration for the 5 measures considered. Heterogeneity by study was observed, with stronger associations for risk of kidney cancer and B-cell lymphoma. An associated increased risk of death following cancer diagnosis ranged from 2% to 6% per five-year age acceleration, with no evidence of heterogeneity by cancer site. Cancer risk and mortality were increased by 15-30% for the fourth versus first quartile of age acceleration. DNA methylation-based measures of biological aging are associated with increased cancer risk and shorter cancer survival, independently of major health risk factors.

Novel associations between blood DNA methylation and body mass index in middle-aged and older adults

BACKGROUND/OBJECTIVES

There is increasing evidence of a relationship between blood DNA methylation and body mass index (BMI). We aimed to assess associations of BMI with individual methylation measures (CpGs) through a cross-sectional genome-wide DNA methylation association study and a longitudinal analysis of repeated measurements over time.

SUBJECTS/METHODS

Using the Illumina Infinium HumanMethylation450 BeadChip, DNA methylation measures were determined in baseline peripheral blood samples from 5361 adults recruited to the Melbourne Collaborative Cohort Study (MCCS) and selected for nested case-control studies, 2586 because they were subsequently diagnosed with cancer (cases) and 2775 as controls. For a subset of 1088 controls, these measures were repeated using blood samples collected at wave 2 follow-up, a median of 11 years later; weight was measured at both time points. Associations between BMI and blood DNA methylation were assessed using linear mixed-effects regression models adjusted for batch effects and potential confounders. These were applied to cases and controls separately, with results combined through fixed-effects meta-analysis.

RESULTS

Cross-sectional analysis identified 310 CpGs associated with BMI with P<1.0 × 10^-7, 225 of which had not been reported previously. Of these 225 novel associations, 172 were replicated (P<0.05) using the Atherosclerosis Risk in Communities (ARIC) study. We also replicated using MCCS data (P<0.05) 335 of 392 associations previously reported with P<1.0 × 10^-7, including 60 that had not been replicated before. Associations between change in BMI and change in methylation were observed for 34 of the 310 strongest signals in our cross-sectional analysis, including 7 that had not been replicated using the ARIC study.

CONCLUSIONS

Together, these findings suggest that BMI is associated with blood DNA methylation at a large number of CpGs across the genome, several of which are located in or near genes involved in ATP-binding cassette transportation, tumour necrosis factor signalling, insulin resistance and lipid metabolism.

Genome-Wide Measures of Peripheral Blood Dna Methylation and Prostate Cancer Risk in a Prospective Nested Case-Control Study

BACKGROUND

Global measures of peripheral blood DNA methylation have been associated with risk of some malignancies, including breast, bladder, and gastric cancer. Here, we examined genome-wide measures of peripheral blood DNA methylation in prostate cancer and its non-aggressive and aggressive disease forms.

METHODS

We used a matched, case-control study of 687 incident prostate cancer samples, nested within a larger prospective cohort study. DNA methylation was measured in pre-diagnostic, peripheral blood samples using the Illumina Infinium HM450K BeadChip. Genome-wide measures of DNA methylation were computed as the median M-value of all CpG sites and according to CpG site location and regulatory function. We used conditional logistic regression to test for associations between genome-wide measures of DNA methylation and risk of prostate cancer and its subtypes, and by time between blood draw and diagnosis.

RESULTS

We observed no associations between the genome-wide measure of DNA methylation based on all CpG sites and risk of prostate cancer or aggressive disease. Risk of non-aggressive disease was associated with higher methylation of CpG islands (OR = 0.80; 95%CI = 0.68-0.94), promoter regions (OR = 0.79; 95%CI = 0.66-0.93), and high density CpG regions (OR = 0.80; 95%CI = 0.68-0.94). Additionally, higher methylation of all CpGs (OR = 0.66; 95%CI = 0.48-0.89), CpG shores (OR = 0.62; 95%CI = 0.45-0.84), and regulatory regions (OR = 0.68; 95% CI = 0.51-0.91) was associated with a reduced risk of overall prostate cancer within 5 years of blood draw but not thereafter.

CONCLUSIONS

A reduced risk of overall prostate cancer within 5 years of blood draw and non-aggressive prostate cancer was associated with higher genome-wide methylation of peripheral blood DNA. While these data have no immediate clinical utility, with further work they may provide insight into the early events of prostate carcinogenesis. Prostate 77:471-478, 2017. © 2017 Wiley Periodicals, Inc.

DNA methylation changes measured in pre-diagnostic peripheral blood samples are associated with smoking and lung cancer risk

DNA methylation changes are associated with cigarette smoking. We used the Illumina Infinium HumanMethylation450 array to determine whether methylation in DNA from pre-diagnostic, peripheral blood samples is associated with lung cancer risk. We used a case-control study nested within the EPIC-Italy cohort and a study within the MCCS cohort as discovery sets (a total of 552 case-control pairs). We validated the top signals in 429 case-control pairs from another 3 studies. We identified six CpGs for which hypomethylation was associated with lung cancer risk: cg05575921 in the AHRR gene (p-valuepooled  = 4 × 10-17 ), cg03636183 in the F2RL3 gene (p-valuepooled  = 2 × 10 - 13 ), cg21566642 and cg05951221 in 2q37.1 (p-valuepooled  = 7 × 10-16 and 1 × 10-11 respectively), cg06126421 in 6p21.33 (p-valuepooled  = 2 × 10-15 ) and cg23387569 in 12q14.1 (p-valuepooled  = 5 × 10-7 ). For cg05951221 and cg23387569 the strength of association was virtually identical in never and current smokers. For all these CpGs except for cg23387569, the methylation levels were different across smoking categories in controls (p-valuesheterogeneity  ≤ 1.8 x10 - 7 ), were lowest for current smokers and increased with time since quitting for former smokers. We observed a gain in discrimination between cases and controls measured by the area under the ROC curve of at least 8% (p-values ≥ 0.003) in former smokers by adding methylation at the 6 CpGs into risk prediction models including smoking status and number of pack-years. Our findings provide convincing evidence that smoking and possibly other factors lead to DNA methylation changes measurable in peripheral blood that may improve prediction of lung cancer risk.

Methylation of Breast Cancer Predisposition Genes in Early-Onset Breast Cancer: Australian Breast Cancer Family Registry

DNA methylation can mimic the effects of both germline and somatic mutations for cancer predisposition genes such as BRCA1 and p16^INK4a. Constitutional DNA methylation of the BRCA1 promoter has been well described and is associated with an increased risk of early-onset breast cancers that have BRCA1-mutation associated histological features. The role of methylation in the context of other breast cancer predisposition genes has been less well studied and often with conflicting or ambiguous outcomes. We examined the role of methylation in known breast cancer susceptibility genes in breast cancer predisposition and tumor development. We applied the Infinium HumanMethylation450 Beadchip (HM450K) array to blood and tumor-derived DNA from 43 women diagnosed with breast cancer before the age of 40 years and measured the methylation profiles across promoter regions of BRCA1, BRCA2, ATM, PALB2, CDH1, TP53, FANCM, CHEK2, MLH1, MSH2, MSH6 and PMS2. Prior genetic testing had demonstrated that these women did not carry a germline mutation in BRCA1, ATM, CHEK2, PALB2, TP53, BRCA2, CDH1 or FANCM. In addition to the BRCA1 promoter region, this work identified regions with variable methylation at multiple breast cancer susceptibility genes including PALB2 and MLH1. Methylation at the region of MLH1 in these breast cancers was not associated with microsatellite instability. This work informs future studies of the role of methylation in breast cancer susceptibility gene silencing.

Global measures of peripheral blood-derived DNA methylation as a risk factor in the development of mature B-cell neoplasms

AIM

To examine whether peripheral blood methylation is associated with risk of developing mature B-cell neoplasms (MBCNs).

MATERIALS & METHODS

We conducted a case-control study nested within a large prospective cohort. Peripheral blood was collected from healthy participants. Cases of MBCN were identified by linkage to cancer registries. Methylation was measured using the Infinium(®) HumanMethylation450.

RESULTS

During a median of 10.6-year follow-up, 438 MBCN cases were evaluated. Global hypomethylation was associated with increased risk of MBCN (odds ratio: 2.27, [95% CI: 1.59-3.25]). Within high CpG promoter regions, hypermethylation was associated with increased risk (odds ratio: 1.76 [95% CI: 1.25-2.48]). Promoter hypermethylation was observed in HOXA9 and CDH1 genes.

CONCLUSION

Aberrant global DNA methylation is detectable in peripheral blood collected years before diagnosis and is associated with increased risk of MBCN, suggesting changes to DNA methylation are an early event in MBCN development.

Tools for translational epigenetic studies involving formalin-fixed paraffin-embedded human tissue: applying the Infinium HumanMethyation450 Beadchip assay to large population-based studies

BACKGROUND

Large population-based translational epigenetic studies are emerging due to recent technological advances that have made molecular analyses possible. For example, the Infinium HumanMethylation450 Beadchip (HM450K) has enabled studies of genome-wide methylation on a scale not previously possible. However, application of the HM450K to DNA extracted from formalin-fixed paraffin-embedded (FFPE) tumour material has been more challenging than application to high quality DNA extracted from blood. To facilitate the application of this assay consistently across a large number of FFPE tumour-enriched DNA samples we have devised a modification to the HM450K protocol for FFPE that includes an additional quality control (QC) checkpoint.

RESULTS

QC checkpoint 3 was designed to assess the presence of DNA after bisulfite conversion and restoration, just prior to application of the HM450K assay. DNA was extracted from 474 archival FFPE breast tumour material. Five samples did not have a detectable amount of DNA with an additional 42 failing to progress past QC checkpoint 3. Genome-wide methylation was measured for the remaining 428 tumour-enriched DNA. Of these, only 4 samples failed our stringent HM450K data criteria thus representing a 99% success rate. Using prior knowledge about methylation marks associated with breast cancer we further explored the quality of the data. Twenty probes in the BRCA1 promoter region showed increased methylation in triple-negative breast cancers compared to Luminal A, Luminal B and HER2-positive breast cancer subtypes. Validation of this observation in published data from The Cancer Genome Atlas (TCGA) Network (obtained from DNA extracted from fresh frozen tumour samples) confirms the quality of the data obtained from the improved protocol.

CONCLUSIONS

The modified protocol is suitable for the analysis of FFPE tumour-enriched DNA and can be systematically applied to hundreds of samples. This protocol will have utility in population-based translational epigenetic studies and is applicable to a wide variety of translated studies interested in analysis of methylation and its role in the predisposition to disease and disease progression.

The use of DNA from archival dried blood spots with the Infinium HumanMethylation450 array

BACKGROUND

Dried blood (Guthrie card) spots provide an efficient way to collect and store blood specimens. DNA from this source has been utilised for a number of molecular analyses including genome-wide association studies, but only few studies have tested the feasibility of using it for epigenetic applications, particularly at a genome-wide level.

RESULTS

In this study, we demonstrate the successful use of DNA isolated from archived dried blood spots for the Infinium HumanMethylation450 Beadchip, along with DNA from matched frozen buffy coats. We obtained high quality and reproducible genome-wide DNA methylation profiles using both sample types. We also report high correlations (r > 0.9907) between DNA obtained from matched dried blood spots and frozen buffy coats, sufficient to distinguish between unrelated individuals.

CONCLUSIONS

We, thus, demonstrate that DNA from archived dried blood spots is suitable for genome-wide DNA methylation profiling.

Constitutional methylation of the BRCA1 promoter is specifically associated with BRCA1 mutation-associated pathology in early-onset breast cancer

Women carrying germline mutations in BRCA1 are at a substantially elevated risk of breast cancer and their tumors typically have distinctive morphologic features. We hypothesized that constitutional methylation of the BRCA1 promoter region could give rise to such breast cancers in women. We selected 255 women diagnosed with breast cancer before the age of 40 years for whom BRCA1 germline mutations had not been identified. Of them, 52 had five or more of nine BRCA1 mutation-associated morphologic features (group 1), 39 had four (group 2), and 164 had three or less (group 3). The prevalence of detectable BRCA1 promoter methylation in peripheral blood DNA decreased from 31% to 10% to 5% across groups 1-3, respectively (P = 0.000002), and was significantly greater than the 4% frequency in unaffected controls (P = 0.004). Peripheral blood methylation was associated with a 3.5-fold (95% CI, 1.4-10.5) increased risk of having early onset breast cancer. Methylation was consistently mosaic in the peripheral blood where the estimated allelic frequency of BRCA1 promoter methylation ranged from 0.1% to 17%. Group 1 women, but not group 3 women, with detectable methylation of peripheral blood DNA had high levels of BRCA1 promoter methylation of their tumor DNA, indicating that constitutional BRCA1 methylation strongly predisposes toward the development of BRCA1 methylated tumors that then have features resembling BRCA1 mutated tumors. Screening peripheral blood for BRCA1 promoter methylation might thus predict early-onset breast cancers. This raises the possibility of chemoprevention or other intervention to diminish the risk of developing breast cancer in these women.

BRCA1 promoter methylation in peripheral blood DNA of mutation negative familial breast cancer patients with a BRCA1 tumour phenotype

Introduction

Individuals with germline mutations in the BRCA1 gene have an elevated risk of developing breast cancer, and often display characteristic clinicopathological features. We hypothesised that inactivation of BRCA1 by promoter methylation could occur as a germline or an early somatic event that predisposes to breast cancer with the phenotype normally associated with BRCA1 germline mutation.

Methods

We examined seven cases from breast-ovarian cancer families with tumours that showed BRCA1-like pathology but did not have detectable BRCA1 or BRCA2 germline mutations present. Methylation levels were tested by several quantitative techniques including MethyLight, methylation-sensitive high resolution melting (MS-HRM) and a newly developed digital MS-HRM assay.

Results

In one patient, methylation of 10% of the BRCA1 alleles was detected in the peripheral blood DNA, consistent with 20% of cells having one methylated allele. Buccal mucosa DNA from this individual displayed approximately 5% BRCA1 methylation. In two other patients, methylation of BRCA1 was detected in the peripheral blood at significantly lower but still readily detectable levels (approximately 1%). Tumour DNAs from these three patients were heavily methylated at BRCA1. The other patients had no detectable BRCA1 methylation in their peripheral blood. One of seven age-matched controls showed extremely low levels of methylation in their peripheral blood (approximately 0.1%).

Conclusion

These results demonstrate that in some cases of breast cancer, low-level promoter methylation of BRCA1 occurs in normal tissues of the body and is associated with the development of BRCA1-like breast cancer.

Is MSH2 a breast cancer susceptibility gene?

Mutations in the DNA mismatch repair gene MSH2 lead to increased replication error and microsatellite instability and account for a substantial proportion of hereditary non-polyposis colorectal cancer (Lynch syndrome). A recent international collaborative genome-wide linkage scan (GWS) for breast cancer susceptibility loci found some evidence for there being a breast cancer susceptibility gene in a genomic region on chromosome 2p close to MSH2. We sought to investigate the possibility that mutations in MSH2 might explain the multiple cases of breast cancer in some families that were included in the international GWS. DNA samples from the affected probands of 59 multiple-case breast cancer families, many of whom gave LOD scores >0.5 in the MSH2 region, were screened for large genomic alterations in MSH2 via the Multiplex Ligation-dependent Probe Amplification (MLPA) assay and for coding region mutations via exonic sequencing. Several of the families also contained cases of colorectal cancer in addition to breast cancer and had been included in the GWS that had identified a positive LOD score on chromosome 2p. Using MLPA, c.1236C > T was identified in one proband but this variant was not predicted to create an alternate acceptor/donor site within exon 7 MSH2 using in silico analyses. A c.1734T > C was identified in a second proband via exonic sequencing but testing of the variant in other family members did not support segregation of this variant with disease. Extensive screening of 59 multiple-case breast cancer families did not identify any coding region mutations or larger genomic alterations in MSH2 that might implicate MSH2 as a breast cancer susceptibility gene.

Prediction of BRCA1 and BRCA2 mutation status using post-irradiation assays of lymphoblastoid cell lines is compromised by inter-cell-line phenotypic variability

BACKGROUND AND PURPOSE

Assays to determine the pathogenicity of unclassified sequence variants in disease-associated genes include the analysis of lymphoblastoid cell lines (LCLs). We assessed the ability of several assays of LCLs to distinguish carriers of germline BRCA1 and BRCA2 gene mutations from mutation-negative controls to determine their utility for use in a diagnostic setting.

MATERIALS AND METHODS

Post-ionising radiation cell viability and micronucleus formation, and telomere length were assayed in LCLs carrying BRCA1 or BRCA2 mutations, and in unaffected mutation-negative controls.

RESULTS

Post-irradiation cell viability and micronucleus induction assays of LCLs from individuals carrying pathogenic BRCA1 mutations, unclassified BRCA1 sequence variants or wildtype BRCA1 sequence showed significant phenotypic heterogeneity within each group. Responses were not consistent with predicted functional consequences of known pathogenic or normal sequences. Telomere length was also highly heterogeneous within groups of LCLs carrying pathogenic BRCA1 or BRCA2 mutations, and normal BRCA1 sequences, and was not predictive of mutation status.

CONCLUSION

Given the significant degree of phenotypic heterogeneity of LCLs after gamma-irradiation, and the lack of association with BRCA1 or BRCA2 mutation status, we conclude that the assays evaluated in this study should not be used as a means of differentiating pathogenic and non-pathogenic sequence variants for clinical application. We suggest that a range of normal controls must be included in any functional assays of LCLs to ensure that any observed differences between samples reflect the genotype under investigation rather than generic inter-individual variation.

Molecular characterization and cancer risk associated with BRCA1 and BRCA2 splice site variants identified in multiple-case breast cancer families

Genetic screening of women from multiple-case breast cancer families and other research-based endeavors have identified an extensive collection of germline variations of BRCA1 and BRCA2 that can be classified as deleterious and have clinical relevance. For some variants, such as those in the conserved intronic splice site regions which are highly likely to alter splicing, it is not possible to classify them based on the identified DNA sequence variation alone. We studied 11 multiple-case breast cancer families carrying seven distinct splice site region genetic alterations in BRCA1 or BRCA2 (BRCA1, c.IVS6-2delA, c.IVS9-2A>C, c.IVS4-1G>T, c.IVS20+1G>A and BRCA2, c.IVS17-1G>C, c.IVS20+1G>A, c.IVS7-1G>A) and applied SpliceSiteFinder to predict possible changes in efficiency of splice donor and acceptor sites, characterized the transcripts, and estimated the average age-specific cumulative risk (penetrance) using a modified segregation analysis. SpliceSiteFinder predicted and we identified transcipts that illustrated that all variants caused exon skipping, and all but two led to frameshifts. The risks of breast cancer to age 70 yrs, averaged over all variants, over BRCA1 variants alone, and over BRCA2 variants alone, were 73% (95% confidence interval 47-93), 64% (95%CI 28-96) and 79% (95%CI 48-98) respectively (all P<0.0001). Therefore five of these seven consensus splice site variants of BRCA1 and BRCA2 produce a transcript similar to that of other previously described deleterious exonic variants and are associated with similar high lifetime risks.