Melbourne School of Population and Global Health - Research Publications

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    Genetic and Environmental Causes of Variation in an Automated Breast Cancer Risk Factor Based on Mammographic Textures
    Ye, Z ; Dite, GS ; Nguyen, TL ; Macinnis, RJ ; Schmidt, DF ; Makalic, E ; Al-Qershi, OM ; Nguyen-Dumont, T ; Goudey, B ; Stone, J ; Dowty, JG ; Giles, GG ; Southey, MC ; Hopper, JL ; Li, S (AMER ASSOC CANCER RESEARCH, 2024-02-06)
    BACKGROUND: Cirrus is an automated risk predictor for breast cancer that comprises texture-based mammographic features and is mostly independent of mammographic density. We investigated genetic and environmental variance of variation in Cirrus. METHODS: We measured Cirrus for 3,195 breast cancer-free participants, including 527 pairs of monozygotic (MZ) twins, 271 pairs of dizygotic (DZ) twins, and 1,599 siblings of twins. Multivariate normal models were used to estimate the variance and familial correlations of age-adjusted Cirrus as a function of age. The classic twin model was expanded to allow the shared environment effects to differ by zygosity. The SNP-based heritability was estimated for a subset of 2,356 participants. RESULTS: There was no evidence that the variance or familial correlations depended on age. The familial correlations were 0.52 (SE, 0.03) for MZ pairs and 0.16(SE, 0.03) for DZ and non-twin sister pairs combined. Shared environmental factors specific to MZ pairs accounted for 20% of the variance. Additive genetic factors accounted for 32% (SE = 5%) of the variance, consistent with the SNP-based heritability of 36% (SE = 16%). CONCLUSION: Cirrus is substantially familial due to genetic factors and an influence of shared environmental factors that was evident for MZ twin pairs only. The latter could be due to nongenetic factors operating in utero or in early life that are shared by MZ twins. IMPACT: Early-life factors, shared more by MZ pairs than DZ/non-twin sister pairs, could play a role in the variation in Cirrus, consistent with early life being recognized as a critical window of vulnerability to breast carcinogens.
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    Segregation analysis of 17,425 population-based breast cancer families: Evidence for genetic susceptibility and risk prediction
    Li, S ; MacInnis, RJ ; Lee, A ; Nguyen-Dumont, T ; Dorling, L ; Carvalho, S ; Dite, GS ; Shah, M ; Luccarini, C ; Wang, Q ; Milne, RL ; Jenkins, MA ; Giles, GG ; Dunning, AM ; Pharoah, PDP ; Southey, MC ; Easton, DF ; Hopper, JL ; Antoniou, AC (CELL PRESS, 2022-10-06)
    Rare pathogenic variants in known breast cancer-susceptibility genes and known common susceptibility variants do not fully explain the familial aggregation of breast cancer. To investigate plausible genetic models for the residual familial aggregation, we studied 17,425 families ascertained through population-based probands, 86% of whom were screened for pathogenic variants in BRCA1, BRCA2, PALB2, CHEK2, ATM, and TP53 via gene-panel sequencing. We conducted complex segregation analyses and fitted genetic models in which breast cancer incidence depended on the effects of known susceptibility genes and other unidentified major genes and a normally distributed polygenic component. The proportion of familial variance explained by the six genes was 46% at age 20-29 years and decreased steadily with age thereafter. After allowing for these genes, the best fitting model for the residual familial variance included a recessive risk component with a combined genotype frequency of 1.7% (95% CI: 0.3%-5.4%) and a penetrance to age 80 years of 69% (95% CI: 38%-95%) for homozygotes, which may reflect the combined effects of multiple variants acting in a recessive manner, and a polygenic variance of 1.27 (95% CI: 0.94%-1.65), which did not vary with age. The proportion of the residual familial variance explained by the recessive risk component was 40% at age 20-29 years and decreased with age thereafter. The model predicted age-specific familial relative risks consistent with those observed by large epidemiological studies. The findings have implications for strategies to identify new breast cancer-susceptibility genes and improve disease-risk prediction, especially at a young age.
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    Genetic Aspects of Mammographic Density Measures Associated with Breast Cancer Risk
    Li, S ; Nguyen, TL ; Tu, N-D ; Dowty, JG ; Dite, GS ; Ye, Z ; Trinh, HN ; Evans, CF ; Tan, M ; Sung, J ; Jenkins, MA ; Giles, GG ; Hopper, JL ; Southey, MC (MDPI, 2022-06)
    Cumulus, Altocumulus, and Cirrocumulus are measures of mammographic density defined at increasing pixel brightness thresholds, which, when converted to mammogram risk scores (MRSs), predict breast cancer risk. Twin and family studies suggest substantial variance in the MRSs could be explained by genetic factors. For 2559 women aged 30 to 80 years (mean 54 years), we measured the MRSs from digitized film mammograms and estimated the associations of the MRSs with a 313-SNP breast cancer polygenic risk score (PRS) and 202 individual SNPs associated with breast cancer risk. The PRS was weakly positively correlated (correlation coefficients ranged 0.05−0.08; all p < 0.04) with all the MRSs except the Cumulus-white MRS based on the “white but not bright area” (correlation coefficient = 0.04; p = 0.06). After adjusting for its association with the Altocumulus MRS, the PRS was not associated with the Cumulus MRS. There were MRS associations (Bonferroni-adjusted p < 0.04) with one SNP in the ATXN1 gene and nominally with some ESR1 SNPs. Less than 1% of the variance of the MRSs is explained by the genetic markers currently known to be associated with breast cancer risk. Discovering the genetic determinants of the bright, not white, regions of the mammogram could reveal substantial new genetic causes of breast cancer.
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    Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing
    Southey, MC ; Dowty, JG ; Riaz, M ; Steen, JA ; Renault, A-L ; Tucker, K ; Kirk, J ; James, P ; Winship, I ; Pachter, N ; Poplawski, N ; Grist, S ; Park, DJ ; Pope, BJ ; Mahmood, K ; Hammet, F ; Mahmoodi, M ; Tsimiklis, H ; Theys, D ; Rewse, A ; Willis, A ; Morrow, A ; Speechly, C ; Harris, R ; Sebra, R ; Schadt, E ; Lacaze, P ; McNeil, JJ ; Giles, GG ; Milne, RL ; Hopper, JL ; Nguyen-Dumont, T (NATURE PORTFOLIO, 2021-12-09)
    Population-based estimates of breast cancer risk for carriers of pathogenic variants identified by gene-panel testing are urgently required. Most prior research has been based on women selected for high-risk features and more data is needed to make inference about breast cancer risk for women unselected for family history, an important consideration of population screening. We tested 1464 women diagnosed with breast cancer and 862 age-matched controls participating in the Australian Breast Cancer Family Study (ABCFS), and 6549 healthy, older Australian women enroled in the ASPirin in Reducing Events in the Elderly (ASPREE) study for rare germline variants using a 24-gene-panel. Odds ratios (ORs) were estimated using unconditional logistic regression adjusted for age and other potential confounders. We identified pathogenic variants in 11.1% of the ABCFS cases, 3.7% of the ABCFS controls and 2.2% of the ASPREE (control) participants. The estimated breast cancer OR [95% confidence interval] was 5.3 [2.1-16.2] for BRCA1, 4.0 [1.9-9.1] for BRCA2, 3.4 [1.4-8.4] for ATM and 4.3 [1.0-17.0] for PALB2. Our findings provide a population-based perspective to gene-panel testing for breast cancer predisposition and opportunities to improve predictors for identifying women who carry pathogenic variants in breast cancer predisposition genes.
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    Genome-wide and transcriptome-wide association studies of mammographic density phenotypes reveal novel loci
    Chen, H ; Fan, S ; Stone, J ; Thompson, DJ ; Douglas, J ; Li, S ; Scott, C ; Bolla, MK ; Wang, Q ; Dennis, J ; Michailidou, K ; Li, C ; Peters, U ; Hopper, JL ; Southey, MC ; Nguyen-Dumont, T ; Nguyen, TL ; Fasching, PA ; Behrens, A ; Cadby, G ; Murphy, RA ; Aronson, K ; Howell, A ; Astley, S ; Couch, F ; Olson, J ; Milne, RL ; Giles, GG ; Haiman, CA ; Maskarinec, G ; Winham, S ; John, EM ; Kurian, A ; Eliassen, H ; Andrulis, I ; Evans, DG ; Newman, WG ; Hall, P ; Czene, K ; Swerdlow, A ; Jones, M ; Pollan, M ; Fernandez-Navarro, P ; McConnell, DS ; Kristensen, VN ; Rothstein, JH ; Wang, P ; Habel, LA ; Sieh, W ; Dunning, AM ; Pharoah, PDP ; Easton, DF ; Gierach, GL ; Tamimi, RM ; Vachon, CM ; Lindstrom, S (BMC, 2022-04-12)
    BACKGROUND: Mammographic density (MD) phenotypes, including percent density (PMD), area of dense tissue (DA), and area of non-dense tissue (NDA), are associated with breast cancer risk. Twin studies suggest that MD phenotypes are highly heritable. However, only a small proportion of their variance is explained by identified genetic variants. METHODS: We conducted a genome-wide association study, as well as a transcriptome-wide association study (TWAS), of age- and BMI-adjusted DA, NDA, and PMD in up to 27,900 European-ancestry women from the MODE/BCAC consortia. RESULTS: We identified 28 genome-wide significant loci for MD phenotypes, including nine novel signals (5q11.2, 5q14.1, 5q31.1, 5q33.3, 5q35.1, 7p11.2, 8q24.13, 12p11.2, 16q12.2). Further, 45% of all known breast cancer SNPs were associated with at least one MD phenotype at p < 0.05. TWAS further identified two novel genes (SHOX2 and CRISPLD2) whose genetically predicted expression was significantly associated with MD phenotypes. CONCLUSIONS: Our findings provided novel insight into the genetic background of MD phenotypes, and further demonstrated their shared genetic basis with breast cancer.
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    Population-based estimates of age-specific cumulative risk of breast cancer for pathogenic variants in ATM
    Renault, A-L ; Dowty, JG ; Steen, JA ; Li, S ; Winship, IM ; Giles, GG ; Hopper, JL ; Southey, MC ; Nguyen-Dumont, T (BMC, 2022-04-01)
    BACKGROUND: Multigene panel tests for breast cancer predisposition routinely include ATM as it is now a well-established breast cancer predisposition gene. METHODS: We included ATM in a multigene panel test applied to the Australian Breast Cancer Family Registry (ABCFR), a population-based case-control-family study of breast cancer, with the purpose of estimating the prevalence and penetrance of heterozygous ATM pathogenic variants from the family data, using segregation analysis. RESULTS: The estimated breast cancer hazard ratio for carriers of pathogenic ATM variants in the ABCFR was 1.32 (95% confidence interval 0.45-3.87; P = 0.6). The estimated cumulative risk of breast cancer to age 80 years for heterozygous ATM pathogenic variant carriers was estimated to be 13% (95% CI 4.6-30). CONCLUSIONS: Although ATM has been definitively identified as a breast cancer predisposition gene, further evidence, such as variant-specific penetrance estimates, are needed to inform risk management strategies for carriers of pathogenic variants to increase the clinical utility of population testing of this gene.
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    Familial Aspects of Mammographic Density Measures Associated with Breast Cancer Risk
    Nguyen, TL ; Li, S ; Dowty, JG ; Dite, GS ; Ye, Z ; Nguyen-Dumont, T ; Trinh, HN ; Evans, CF ; Tan, M ; Sung, J ; Jenkins, MA ; Giles, GG ; Southey, MC ; Hopper, JL (MDPI, 2022-03)
    Cumulus, Cumulus-percent, Altocumulus, Cirrocumulus, and Cumulus-white are mammogram risk scores (MRSs) for breast cancer based on mammographic density defined in effect by different levels of pixel brightness and adjusted for age and body mass index. We measured these MRS from digitized film mammograms for 593 monozygotic (MZ) and 326 dizygotic (DZ) female twin pairs and 1592 of their sisters. We estimated the correlations in relatives (r) and the proportion of variance due to genetic factors (heritability) using the software FISHER and predicted the familial risk ratio (FRR) associated with each MRS. The ρ estimates ranged from: 0.41 to 0.60 (standard error [SE] 0.02) for MZ pairs, 0.16 to 0.26 (SE 0.05) for DZ pairs, and 0.19 to 0.29 (SE 0.02) for sister pairs (including pairs of a twin and her non-twin sister), respectively. Heritability estimates were 39% to 69% under the classic twin model and 36% to 56% when allowing for shared non-genetic factors specific to MZ pairs. The FRRs were 1.08 to 1.17. These MRSs are substantially familial, due mostly to genetic factors that explain one-quarter to one-half as much of the familial aggregation of breast cancer that is explained by the current best polygenic risk score.
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    Identification of new breast cancer predisposition genes via whole exome sequencing
    Southey, MC ; Park, DJ ; Lesueur, F ; Odefrey, F ; Nguyen-Dumont, T ; Hammet, F ; Neuhausen, SL ; John, EM ; Andrulis, IL ; Chenevix-Trench, G ; Baglietto, L ; Le Calvez-Kelm, F ; Pertesi, M ; Lonie, A ; Pope, B ; Sinilnikova, O ; Tsimiklis, H ; Giles, GG ; Hopper, JL ; Tavtigian, SV ; Goldgar, DE (Springer Science and Business Media LLC, 2012-01)
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    Prospective Evaluation over 15 Years of Six Breast Cancer Risk Models
    Li, SX ; Milne, RL ; Nguyen-Dumont, T ; English, DR ; Giles, GG ; Southey, MC ; Antoniou, AC ; Lee, A ; Winship, I ; Hopper, JL ; Terry, MB ; MacInnis, RJ (MDPI, 2021-10)
    Prospective validation of risk models is needed to assess their clinical utility, particularly over the longer term. We evaluated the performance of six commonly used breast cancer risk models (IBIS, BOADICEA, BRCAPRO, BRCAPRO-BCRAT, BCRAT, and iCARE-lit). 15-year risk scores were estimated using lifestyle factors and family history measures from 7608 women in the Melbourne Collaborative Cohort Study who were aged 50-65 years and unaffected at commencement of follow-up two (conducted in 2003-2007), of whom 351 subsequently developed breast cancer. Risk discrimination was assessed using the C-statistic and calibration using the expected/observed number of incident cases across the spectrum of risk by age group (50-54, 55-59, 60-65 years) and family history of breast cancer. C-statistics were higher for BOADICEA (0.59, 95% confidence interval (CI) 0.56-0.62) and IBIS (0.57, 95% CI 0.54-0.61) than the other models (p-difference ≤ 0.04). No model except BOADICEA calibrated well across the spectrum of 15-year risk (p-value < 0.03). The performance of BOADICEA and IBIS was similar across age groups and for women with or without a family history. For middle-aged Australian women, BOADICEA and IBIS had the highest discriminatory accuracy of the six risk models, but apart from BOADICEA, no model was well-calibrated across the risk spectrum.
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    Repeatability of methylation measures using a QIAseq targeted methyl panel and comparison with the Illumina HumanMethylation450 assay
    Yu, C ; Dugue, P-A ; Dowty, JG ; Hammet, F ; Joo, JE ; Wong, EM ; Hosseinpour, M ; Giles, GG ; Hopper, JL ; Tu, N-D ; MacInnis, RJ ; Southey, MC (SPRINGERNATURE, 2021-10-24)
    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.