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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ItemA comprehensive gene-environment interaction analysis in Ovarian Cancer using genome-wide significant common variants(WILEY, 2019-05-01)As a follow-up to genome-wide association analysis of common variants associated with ovarian carcinoma (cancer), our study considers seven well-known ovarian cancer risk factors and their interactions with 28 genome-wide significant common genetic variants. The interaction analyses were based on data from 9971 ovarian cancer cases and 15,566 controls from 17 case-control studies. Likelihood ratio and Wald tests for multiplicative interaction and for relative excess risk due to additive interaction were used. The top multiplicative interaction was noted between oral contraceptive pill (OCP) use (ever vs. never) and rs13255292 (p value = 3.48 × 10-4 ). Among women with the TT genotype for this variant, the odds ratio for OCP use was 0.53 (95% CI = 0.46-0.60) compared to 0.71 (95%CI = 0.66-0.77) for women with the CC genotype. When stratified by duration of OCP use, women with 1-5 years of OCP use exhibited differential protective benefit across genotypes. However, no interaction on either the multiplicative or additive scale was found to be statistically significant after multiple testing correction. The results suggest that OCP use may offer increased benefit for women who are carriers of the T allele in rs13255292. On the other hand, for women carrying the C allele in this variant, longer (5+ years) use of OCP may reduce the impact of carrying the risk allele of this SNP. Replication of this finding is needed. The study presents a comprehensive analytic framework for conducting gene-environment analysis in ovarian cancer.
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ItemNovel mammogram-based measures improve breast cancer risk prediction beyond an established mammographic density measure(WILEY, 2021-05-01)Mammograms contain information that predicts breast cancer risk. We developed two novel mammogram-based breast cancer risk measures based on image brightness (Cirrocumulus) and texture (Cirrus). Their risk prediction when fitted together, and with an established measure of conventional mammographic density (Cumulus), is not known. We used three studies consisting of: 168 interval cases and 498 matched controls; 422 screen-detected cases and 1197 matched controls; and 354 younger-diagnosis cases and 944 controls frequency-matched for age at mammogram. We conducted conditional and unconditional logistic regression analyses of individually- and frequency-matched studies, respectively. We estimated measure-specific risk gradients as the change in odds per standard deviation of controls after adjusting for age and body mass index (OPERA) and calculated the area under the receiver operating characteristic curve (AUC). For interval, screen-detected and younger-diagnosis cancer risks, the best fitting models (OPERAs [95% confidence intervals]) involved: Cumulus (1.81 [1.41-2.31]) and Cirrus (1.72 [1.38-2.14]); Cirrus (1.49 [1.32-1.67]) and Cirrocumulus (1.16 [1.03 to 1.31]); and Cirrus (1.70 [1.48 to 1.94]) and Cirrocumulus (1.46 [1.27-1.68]), respectively. The AUCs were: 0.73 [0.68-0.77], 0.63 [0.60-0.66], and 0.72 [0.69-0.75], respectively. Combined, our new mammogram-based measures have twice the risk gradient for screen-detected and younger-diagnosis breast cancer (P ≤ 10-12 ), have at least the same discriminatory power as the current polygenic risk score, and are more correlated with causal factors than conventional mammographic density. Discovering more information about breast cancer risk from mammograms could help enable risk-based personalised breast screening.
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ItemNo Preview AvailableGenome-wide association analysis identifies three new breast cancer susceptibility loci(NATURE PUBLISHING GROUP, 2012-03)Breast cancer is the most common cancer among women. To date, 22 common breast cancer susceptibility loci have been identified accounting for ∼8% of the heritability of the disease. We attempted to replicate 72 promising associations from two independent genome-wide association studies (GWAS) in ∼70,000 cases and ∼68,000 controls from 41 case-control studies and 9 breast cancer GWAS. We identified three new breast cancer risk loci at 12p11 (rs10771399; P = 2.7 × 10(-35)), 12q24 (rs1292011; P = 4.3 × 10(-19)) and 21q21 (rs2823093; P = 1.1 × 10(-12)). rs10771399 was associated with similar relative risks for both estrogen receptor (ER)-negative and ER-positive breast cancer, whereas the other two loci were associated only with ER-positive disease. Two of the loci lie in regions that contain strong plausible candidate genes: PTHLH (12p11) has a crucial role in mammary gland development and the establishment of bone metastasis in breast cancer, and NRIP1 (21q21) encodes an ER cofactor and has a role in the regulation of breast cancer cell growth.
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ItemEvaluation of variation in the phosphoinositide-3-kinase catalytic subunit alpha oncogene and breast cancer risk(NATURE PUBLISHING GROUP, 2011-12-06)BACKGROUND: Somatic mutations in phosphoinositide-3-kinase catalytic subunit alpha (PIK3CA) are frequent in breast tumours and have been associated with oestrogen receptor (ER) expression, human epidermal growth factor receptor-2 overexpression, lymph node metastasis and poor survival. The goal of this study was to evaluate the association between inherited variation in this oncogene and risk of breast cancer. METHODS: A single-nucleotide polymorphism from the PIK3CA locus that was associated with breast cancer in a study of Caucasian breast cancer cases and controls from the Mayo Clinic (MCBCS) was genotyped in 5436 cases and 5280 controls from the Cancer Genetic Markers of Susceptibility (CGEMS) study and in 30 949 cases and 29 788 controls from the Breast Cancer Association Consortium (BCAC). RESULTS: Rs1607237 was significantly associated with a decreased risk of breast cancer in MCBCS, CGEMS and all studies of white Europeans combined (odds ratio (OR)=0.97, 95% confidence interval (CI) 0.95-0.99, P=4.6 × 10(-3)), but did not reach significance in the BCAC replication study alone (OR=0.98, 95% CI 0.96-1.01, P=0.139). CONCLUSION: Common germline variation in PIK3CA does not have a strong influence on the risk of breast cancer.
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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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ItemBreast Cancer Risk and 6q22.33: Combined Results from Breast Cancer Association Consortium and Consortium of Investigators on Modifiers of BRCA1/2(PUBLIC LIBRARY SCIENCE, 2012-06-29)Recently, a locus on chromosome 6q22.33 (rs2180341) was reported to be associated with increased breast cancer risk in the Ashkenazi Jewish (AJ) population, and this association was also observed in populations of non-AJ European ancestry. In the present study, we performed a large replication analysis of rs2180341 using data from 31,428 invasive breast cancer cases and 34,700 controls collected from 25 studies in the Breast Cancer Association Consortium (BCAC). In addition, we evaluated whether rs2180341 modifies breast cancer risk in 3,361 BRCA1 and 2,020 BRCA2 carriers from 11 centers in the Consortium of Investigators of Modifiers of BRCA1/2 (CIMBA). Based on the BCAC data from women of European ancestry, we found evidence for a weak association with breast cancer risk for rs2180341 (per-allele odds ratio (OR) = 1.03, 95% CI 1.00-1.06, p = 0.023). There was evidence for heterogeneity in the ORs among studies (I(2) = 49.3%; p = <0.004). In CIMBA, we observed an inverse association with the minor allele of rs2180341 and breast cancer risk in BRCA1 mutation carriers (per-allele OR = 0.89, 95%CI 0.80-1.00, p = 0.048), indicating a potential protective effect of this allele. These data suggest that that 6q22.33 confers a weak effect on breast cancer risk.
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ItemAssessing interactions between the associations of common genetic susceptibility variants, reproductive history and body mass index with breast cancer risk in the breast cancer association consortium: a combined case-control study(BIOMED CENTRAL LTD, 2010)INTRODUCTION: Several common breast cancer genetic susceptibility variants have recently been identified. We aimed to determine how these variants combine with a subset of other known risk factors to influence breast cancer risk in white women of European ancestry using case-control studies participating in the Breast Cancer Association Consortium. METHODS: We evaluated two-way interactions between each of age at menarche, ever having had a live birth, number of live births, age at first birth and body mass index (BMI) and each of 12 single nucleotide polymorphisms (SNPs) (10q26-rs2981582 (FGFR2), 8q24-rs13281615, 11p15-rs3817198 (LSP1), 5q11-rs889312 (MAP3K1), 16q12-rs3803662 (TOX3), 2q35-rs13387042, 5p12-rs10941679 (MRPS30), 17q23-rs6504950 (COX11), 3p24-rs4973768 (SLC4A7), CASP8-rs17468277, TGFB1-rs1982073 and ESR1-rs3020314). Interactions were tested for by fitting logistic regression models including per-allele and linear trend main effects for SNPs and risk factors, respectively, and single-parameter interaction terms for linear departure from independent multiplicative effects. RESULTS: These analyses were applied to data for up to 26,349 invasive breast cancer cases and up to 32,208 controls from 21 case-control studies. No statistical evidence of interaction was observed beyond that expected by chance. Analyses were repeated using data from 11 population-based studies, and results were very similar. CONCLUSIONS: The relative risks for breast cancer associated with the common susceptibility variants identified to date do not appear to vary across women with different reproductive histories or body mass index (BMI). The assumption of multiplicative combined effects for these established genetic and other risk factors in risk prediction models appears justified.