Melbourne School of Population and Global Health - Research Publications
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ItemMethylation-based markers of aging and lifestyle-related factors and risk of breast cancer: a pooled analysis of four prospective studies(BMC, 2022-09-06)BACKGROUND: DNA methylation in blood may reflect adverse exposures accumulated over the lifetime and could therefore provide potential improvements in the prediction of cancer risk. A substantial body of research has shown associations between epigenetic aging and risk of disease, including cancer. Here we aimed to study epigenetic measures of aging and lifestyle-related factors in association with risk of breast cancer. METHODS: Using data from four prospective case-control studies nested in three cohorts of European ancestry participants, including a total of 1,655 breast cancer cases, we calculated three methylation-based measures of lifestyle factors (body mass index [BMI], tobacco smoking and alcohol consumption) and seven measures of epigenetic aging (Horvath-based, Hannum-based, PhenoAge and GrimAge). All measures were regression-adjusted for their respective risk factors and expressed per standard deviation (SD). Odds ratios (OR) and 95% confidence intervals (CI) were calculated using conditional or unconditional logistic regression and pooled using fixed-effects meta-analysis. Subgroup analyses were conducted by age at blood draw, time from blood sample to diagnosis, oestrogen receptor-positivity status and tumour stage. RESULTS: None of the measures of epigenetic aging were associated with risk of breast cancer in the pooled analysis: Horvath 'age acceleration' (AA): OR per SD = 1.02, 95%CI: 0.95-1.10; AA-Hannum: OR = 1.03, 95%CI:0.95-1.12; PhenoAge: OR = 1.01, 95%CI: 0.94-1.09 and GrimAge: OR = 1.03, 95%CI: 0.94-1.12, in models adjusting for white blood cell proportions, body mass index, smoking and alcohol consumption. The BMI-adjusted predictor of BMI was associated with breast cancer risk, OR per SD = 1.09, 95%CI: 1.01-1.17. The results for the alcohol and smoking methylation-based predictors were consistent with a null association. Risk did not appear to substantially vary by age at blood draw, time to diagnosis or tumour characteristics. CONCLUSION: We found no evidence that methylation-based measures of aging, smoking or alcohol consumption were associated with risk of breast cancer. A methylation-based marker of BMI was associated with risk and may provide insights into the underlying associations between BMI and breast cancer.
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ItemGenome-wide association study of peripheral blood DNA methylation and conventional mammographic density measures(WILEY, 2019-10-01)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.
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ItemNo Preview AvailableHeterogeneity of breast cancer associations with five susceptibility loci by clinical and pathological characteristics(PUBLIC LIBRARY SCIENCE, 2008-04)A three-stage genome-wide association study recently identified single nucleotide polymorphisms (SNPs) in five loci (fibroblast growth receptor 2 (FGFR2), trinucleotide repeat containing 9 (TNRC9), mitogen-activated protein kinase 3 K1 (MAP3K1), 8q24, and lymphocyte-specific protein 1 (LSP1)) associated with breast cancer risk. We investigated whether the associations between these SNPs and breast cancer risk varied by clinically important tumor characteristics in up to 23,039 invasive breast cancer cases and 26,273 controls from 20 studies. We also evaluated their influence on overall survival in 13,527 cases from 13 studies. All participants were of European or Asian origin. rs2981582 in FGFR2 was more strongly related to ER-positive (per-allele OR (95%CI) = 1.31 (1.27-1.36)) than ER-negative (1.08 (1.03-1.14)) disease (P for heterogeneity = 10(-13)). This SNP was also more strongly related to PR-positive, low grade and node positive tumors (P = 10(-5), 10(-8), 0.013, respectively). The association for rs13281615 in 8q24 was stronger for ER-positive, PR-positive, and low grade tumors (P = 0.001, 0.011 and 10(-4), respectively). The differences in the associations between SNPs in FGFR2 and 8q24 and risk by ER and grade remained significant after permutation adjustment for multiple comparisons and after adjustment for other tumor characteristics. Three SNPs (rs2981582, rs3803662, and rs889312) showed weak but significant associations with ER-negative disease, the strongest association being for rs3803662 in TNRC9 (1.14 (1.09-1.21)). rs13281615 in 8q24 was associated with an improvement in survival after diagnosis (per-allele HR = 0.90 (0.83-0.97). The association was attenuated and non-significant after adjusting for known prognostic factors. Our findings show that common genetic variants influence the pathological subtype of breast cancer and provide further support for the hypothesis that ER-positive and ER-negative disease are biologically distinct. Understanding the etiologic heterogeneity of breast cancer may ultimately result in improvements in prevention, early detection, and treatment.
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ItemMammographic density and risk of breast cancer by tumor characteristics: a case-control study(BMC, 2017-12-16)BACKGROUND: In a previous paper, we had assumed that the risk of screen-detected breast cancer mostly reflects inherent risk, and the risk of whether a breast cancer is interval versus screen-detected mostly reflects risk of masking. We found that inherent risk was predicted by body mass index (BMI) and dense area (DA) or percent dense area (PDA), but not by non-dense area (NDA). Masking, however, was best predicted by PDA but not BMI. In this study, we aimed to investigate if these associations vary by tumor characteristics and mode of detection. METHODS: We conducted a case-control study nested within the Melbourne Collaborative Cohort Study of 244 screen-detected cases matched to 700 controls and 148 interval cases matched to 446 controls. DA, NDA and PDA were measured using the Cumulus software. Tumor characteristics included size, grade, lymph node involvement, and ER, PR, and HER2 status. Conditional and unconditional logistic regression were applied as appropriate to estimate the Odds per Adjusted Standard Deviation (OPERA) adjusted for age and BMI, allowing the association with BMI to be a function of age at diagnosis. RESULTS: For screen-detected cancer, both DA and PDA were associated to an increased risk of tumors of large size (OPERA ~ 1.6) and positive lymph node involvement (OPERA ~ 1.8); no association was observed for BMI and NDA. For risk of interval versus screen-detected breast cancer, the association with risk for any of the three mammographic measures did not vary by tumor characteristics; an association was observed for BMI for positive lymph nodes (OPERA ~ 0.6). No associations were observed for tumor grade and ER, PR and HER2 status of tumor. CONCLUSIONS: Both DA and PDA were predictors of inherent risk of larger breast tumors and positive nodal status, whereas for each of the three mammographic density measures the association with risk of masking did not vary by tumor characteristics. This might raise the hypothesis that the risk of breast tumours with poorer prognosis, such as larger and node positive tumours, is intrinsically associated with increased mammographic density and not through delay of diagnosis due to masking.
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ItemEpigenome-wide association study for lifetime estrogen exposure identifies an epigenetic signature associated with breast cancer risk(BMC, 2019-04-30)BACKGROUND: It is well established that estrogens and other hormonal factors influence breast cancer susceptibility. We hypothesized that a woman's total lifetime estrogen exposure accumulates changes in DNA methylation, detectable in the blood, which could be used in risk assessment for breast cancer. METHODS: An estimated lifetime estrogen exposure (ELEE) model was defined using epidemiological data from EPIC-Italy (n = 31,864). An epigenome-wide association study (EWAS) of ELEE was performed using existing Illumina HumanMethylation450K Beadchip (HM450K) methylation data obtained from EPIC-Italy blood DNA samples (n = 216). A methylation index (MI) of ELEE based on 31 CpG sites was developed using HM450K data from EPIC-Italy and the Generations Study and evaluated for association with breast cancer risk in an independent dataset from the Generations Study (n = 440 incident breast cancer cases matched to 440 healthy controls) using targeted bisulfite sequencing. Lastly, a meta-analysis was conducted including three additional cohorts, consisting of 1187 case-control pairs. RESULTS: We observed an estimated 5% increase in breast cancer risk per 1-year longer ELEE (OR = 1.05, 95% CI 1.04-1.07, P = 3 × 10-12) in EPIC-Italy. The EWAS identified 694 CpG sites associated with ELEE (FDR Q < 0.05). We report a DNA methylation index (MI) associated with breast cancer risk that is validated in the Generations Study targeted bisulfite sequencing data (ORQ4_vs_Q1 = 1.77, 95% CI 1.07-2.93, P = 0.027) and in the meta-analysis (ORQ4_vs_Q1 = 1.43, 95% CI 1.05-2.00, P = 0.024); however, the correlation between the MI and ELEE was not validated across study cohorts. CONCLUSION: We have identified a blood DNA methylation signature associated with breast cancer risk in this study. Further investigation is required to confirm the interaction between estrogen exposure and DNA methylation in the blood.
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ItemInterval breast cancer risk associations with breast density, family history and breast tissue aging(WILEY, 2020-07-15)Interval breast cancers (those diagnosed between recommended mammography screens) generally have poorer outcomes and are more common among women with dense breasts. We aimed to develop a risk model for interval breast cancer. We conducted a nested case-control study within the Melbourne Collaborative Cohort Study involving 168 interval breast cancer patients and 498 matched control subjects. We measured breast density using the CUMULUS software. We recorded first-degree family history by questionnaire, measured body mass index (BMI) and calculated age-adjusted breast tissue aging, a novel measure of exposure to estrogen and progesterone based on the Pike model. We fitted conditional logistic regression to estimate odds ratio (OR) or odds ratio per adjusted standard deviation (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). The stronger risk associations were for unadjusted percent breast density (OPERA = 1.99; AUC = 0.66), more so after adjusting for age and BMI (OPERA = 2.26; AUC = 0.70), and for family history (OR = 2.70; AUC = 0.56). When the latter two factors and their multiplicative interactions with age-adjusted breast tissue aging (p = 0.01 and 0.02, respectively) were fitted, the AUC was 0.73 (95% CI 0.69-0.77), equivalent to a ninefold interquartile risk ratio. In summary, compared with using dense breasts alone, risk discrimination for interval breast cancers could be doubled by instead using breast density, BMI, family history and hormonal exposure. This would also give women with dense breasts, and their physicians, more information about the major consequence of having dense breasts-an increased risk of developing an interval breast cancer.
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ItemAnalysis of the breast cancer methylome using formalin-fixed paraffin-embedded tumour(SPRINGER, 2016-11)PURPOSE: Aberrant DNA methylation occurs frequently in breast carcinogenesis. Tools for translational epigenetic studies of breast cancer involving formalin-fixed paraffin-embedded (FFPE) human tissues have now been developed. Few studies have measured genome-wide methylation in DNA derived from paraffin-embedded tumour tissues and compared the DNA methylation in corresponding adjacent non-tumour ductal epithelium (ADJNT). These studies are technically challenging due to the spectrum of breast cancer pathologies, the variable suitability of DNA extracted from FFPE material and the difficulties in identifying ADJNT. We assessed the suitability of FFPE breast cancer material for genome-wide DNA methylation assessment of tumour and ADJNT. METHODS: Twenty-one archival breast tumour tissues with paired ADJNT obtained from separate blocks and at least 2 cm from the tumour were sourced from The Melbourne Collaborative Cohort Study (MCCS). DNA was prepared from macrodissected tissue samples and assessed for genome-wide methylation using the Infinium HumanMethylation450 Beadchip (HM450K) array. RESULTS: The 1000 most differentially methylated probes between tumour and ADJNT in this FFPE-derived dataset differentiated tumour and ADJNT in The Cancer Genome Atlas Network data (TCGA; derived from high molecular weight DNA using the same HM450K array). CONCLUSIONS: Large-scale studies of genome-wide DNA methylation using FFPE breast cancer specimens offer the opportunity to further refine the pathological classification of tumours, to include subtypes that are underrepresented in the TCGA data and provide the capacity to further explore intra-tumoural heterogeneity.
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ItemTools for translational epigenetic studies involving formalin-fixed paraffin-embedded human tissue: applying the Infinium HumanMethyation450 Beadchip assay to large population-based studies.(Springer Science and Business Media LLC, 2015-10-06)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.
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ItemMammographic density and risk of breast cancer by mode of detection and tumor size: a case-control study(BIOMED CENTRAL LTD, 2016-06-18)BACKGROUND: Risk of screen-detected breast cancer mostly reflects inherent risk, while risk of interval cancer reflects inherent risk and risk of masking (risk of the tumor not being detected due to increased dense tissue). Therefore the predictors of whether a breast cancer is interval or screen-detected include those that predict masking. Our aim was to investigate the associations between mammographic measures and (1) inherent risk, and (2) masking. METHODS: We conducted a case-control study nested within the Melbourne collaborative cohort study of 244 screen-detected cases (192 small tumors (<2 cm)) matched to 700 controls and 148 interval cases (76 small tumors) matched to 446 controls. Dense area (DA), percent dense area (PDA), and non-dense area (NDA) were measured using the Cumulus software. Conditional and unconditional logistic regression were applied as appropriate to estimate the odds per adjusted standard deviation (OPERA) adjusted for age and body mass index (BMI), allowing for the association with BMI to be a function of age at diagnosis. Tests of fit were performed using the Bayesian information criterion (BIC) and the area under the receiver operating characteristic curve. RESULTS: For screen-detected cancer, the association with BMI had a marginally significant dependence on age at diagnosis, and after adjustment both DA and PDA were associated with risk (OPERA approximately 1.2) and gave a similar fit. NDA was not associated with risk. For interval cancer, the BMI risk association was not dependent on age at diagnosis and the best fitting model was PDA alone (OPERA = 2.24, 95 % confidence interval 1.75, 2.86). Prediction of interval versus screen-detected cancer was best achieved by PDA alone (OPERA = 1.76, 95 % confidence interval 1.39, 2.22) with no association with BMI. When the analysis was restricted to small tumors to reduce the influence of tumor growth, we obtained similar results. CONCLUSIONS: Inherent breast cancer risk is predicted by BMI and DA or PDA, but not NDA. Masking is predicted by PDA, and not by BMI. Understanding risk and masking could help tailor mammographic screening.