Melbourne School of Population and Global Health - Research Publications

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    Cytomegalovirus, Epstein-Barr virus and risk of breast cancer before age 40 years: a case-control study
    Richardson, AK ; Cox, B ; McCredie, M ; Dite, GS ; Chang, JH ; Gertig, DM ; Southey, MC ; Giless, GG ; Hopper, JL (NATURE PUBLISHING GROUP, 2004-06-01)
    We investigated whether there is an association between cytomegalovirus (CMV) and Epstein-Barr virus (EBV) IgG levels and risk of breast cancer before age 40 years. CMV and EBV IgG levels were measured in stored plasma from 208 women with breast cancer and 169 controls who participated in the Australian Breast Cancer Family Study (ABCFS), a population-based case-control study. CMV and EBV IgG values were measured in units of optical density (OD). Cases and controls did not differ in seropositivity for CMV (59 and 57% respectively; P=0.8) or EBV (97 and 96% respectively; P=0.7). In seropositive women, mean IgG values were higher in cases than controls for CMV (1.20 vs 0.98 OD, P=0.005) but not for EBV (2.65 vs 2.57 OD, P=0.5). The adjusted odds ratios per OD unit were 1.46 (95% CI 1.06-2.03) for CMV IgG and 1.11 (0.93-1.33) for EBV IgG. The higher mean CMV IgG levels found in women with breast cancer could be the result of a more recent infection with CMV, and may mean that late exposure to CMV is a risk factor for breast cancer.
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    The AIB1 glutamine repeat polymorphism is not associated with risk of breast cancer before age 40 years in Australian women
    Montgomery, KG ; Chang, JH ; Gertig, DM ; Dite, GS ; McCredie, MR ; Giles, GG ; Southey, MC ; Hopper, JL ; Campbell, IG (BMC, 2005)
    INTRODUCTION: AIB1, located at 20q12, is a member of the steroid hormone coactivator family. It contains a glutamine repeat (CAG/CAA) polymorphism at its carboxyl-terminal region that may alter the transcriptional activation of the receptor and affect susceptibility to breast cancer through altered sensitivity to hormones. METHODS: We evaluated this repeat polymorphism in the context of early-onset disease by conducting a case-control study of 432 Australian women diagnosed with breast cancer before the age of 40 years and 393 population-based control individuals who were frequency matched for age. Genotyping was performed using a scanning laser fluorescence imager. RESULTS: There were no differences in genotype frequencies between cases and control individuals, or between cases categorized by family history or by BRCA1 and BRCA2 germline mutation status. There was no evidence that the presence of one or two alleles of 26 glutamine repeats or fewer was associated with breast cancer (odds ratio = 1.03, 95% confidence interval = 0.73-1.44), or that women with alleles greater than 29 repeats were at increased risk of breast cancer. Exclusion of women who carried a BRCA1 or BRCA2 mutation (24 cases) and non-Caucasian women (44 cases) did not alter the risk estimates or inferences. We present raw data, including that on mutation carriers, to allow pooling with other studies. CONCLUSION: There was no evidence that risk of breast cancer depends on AIB1 CAG/CAA polymorphism status, even if affected women carry a mutation in BRCA1 or BRCA2.
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    CYP17 genetic polymorphism, breast cancer, and breast cancer risk factors:: Australian Breast Cancer Family Study
    Chang, JH ; Gertig, DM ; Chen, XQ ; Dite, GS ; Jenkins, MA ; Milne, RL ; Southey, MC ; McCredie, MRE ; Giles, GG ; Chenevix-Trench, G ; Hopper, JL ; Spurdle, AB (BMC, 2005)
    INTRODUCTION: Because CYP17 can influence the degree of exposure of breast tissues to oestrogen, the interaction between polymorphisms in this gene and hormonal risk factors is of particular interest. We attempted to replicate the findings of studies assessing such interactions with the -34T-->C polymorphism. METHODS: Risk factor and CYP17 genotyping data were derived from a large Australian population-based case-control-family study of 1,284 breast cancer cases and 679 controls. Crude and adjusted odds ratio (OR) estimates and 95% confidence intervals (CIs) were calculated by unconditional logistic regression analyses. RESULTS: We found no associations between the CYP17 genotype and breast cancer overall. Premenopausal controls with A2/A2 genotype had a later age at menarche (P < 0.01). The only associations near statistical significance were that postmenopausal women with A1/A1 (wild-type) genotype had an increased risk of breast cancer if they had ever used hormone replacement therapy (OR 2.40, 95% CI 1.0 to 5.7; P = 0.05) and if they had menopause after age 47 years (OR 2.59, 95% CI 1.0 to 7.0; P = 0.06). We found no associations in common with any other studies, and no evidence for interactions. CONCLUSION: We observed no evidence of effect modification of reproductive risk factors by CYP17 genotype, although the experiment did not have sufficient statistical power to detect small main effects and modest effects in subgroups. Associations found only in subgroup analyses based on relatively small numbers require cautious interpretation without confirmation by other studies. This emphasizes the need for replication in multiple and large population-based studies to provide convincing evidence for gene-environment interactions.
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    Using Functional Data Analysis Models to Estimate Future Time Trends in Age-Specific Breast Cancer Mortality for the United States and England-Wales
    Erbas, B ; Akram, M ; Gertig, DM ; English, D ; Hopper, JL ; Kavanagh, AM ; Hyndman, R (JAPAN EPIDEMIOLOGICAL ASSOC, 2010-03)
    BACKGROUND: Mortality/incidence predictions are used for allocating public health resources and should accurately reflect age-related changes through time. We present a new forecasting model for estimating future trends in age-related breast cancer mortality for the United States and England-Wales. METHODS: We used functional data analysis techniques both to model breast cancer mortality-age relationships in the United States from 1950 through 2001 and England-Wales from 1950 through 2003 and to estimate 20-year predictions using a new forecasting method. RESULTS: In the United States, trends for women aged 45 to 54 years have continued to decline since 1980. In contrast, trends in women aged 60 to 84 years increased in the 1980s and declined in the 1990s. For England-Wales, trends for women aged 45 to 74 years slightly increased before 1980, but declined thereafter. The greatest age-related changes for both regions were during the 1990s. For both the United States and England-Wales, trends are expected to decline and then stabilize, with the greatest decline in women aged 60 to 70 years. Forecasts suggest relatively stable trends for women older than 75 years. CONCLUSIONS: Prediction of age-related changes in mortality/incidence can be used for planning and targeting programs for specific age groups. Currently, these models are being extended to incorporate other variables that may influence age-related changes in mortality/incidence trends. In their current form, these models will be most useful for modeling and projecting future trends of diseases for which there has been very little advancement in treatment and minimal cohort effects (eg. lethal cancers).
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    Fine-Scale Mapping of the 4q24 Locus Identifies Two Independent Loci Associated with Breast Cancer Risk
    Guo, X ; Long, J ; Zeng, C ; Michailidou, K ; Ghoussaini, M ; Bolla, MK ; Wang, Q ; Milne, RL ; Shu, X-O ; Cai, Q ; Beesley, J ; Kar, SP ; Andrulis, IL ; Anton-Culver, H ; Arndt, V ; Beckmann, MW ; Beeghly-Fadiel, A ; Benitez, J ; Blot, W ; Bogdanova, N ; Bojesen, SE ; Brauch, H ; Brenner, H ; Brinton, L ; Broeks, A ; Bruening, T ; Burwinkel, B ; Cai, H ; Canisius, S ; Chang-Claude, J ; Choi, J-Y ; Couch, FJ ; Cox, A ; Cross, SS ; Czene, K ; Darabi, H ; Devilee, P ; Droit, A ; Doerk, T ; Fasching, PA ; Fletcher, O ; Flyger, H ; Fostira, F ; Gaborieau, V ; Garcia-Closas, M ; Giles, GG ; Grip, M ; Guenel, P ; Haiman, CA ; Hamann, U ; Hartman, M ; Hollestelle, A ; Hopper, JL ; Hsiung, C-N ; Ito, H ; Jakubowska, A ; Johnson, N ; Kabisch, M ; Kang, D ; Khan, S ; Knight, JA ; Kosma, V-M ; Lambrechts, D ; Le Marchand, L ; Li, J ; Lindblom, A ; Lophatananon, A ; Lubinski, J ; Mannermaa, A ; Manoukian, S ; Margolin, S ; Marme, F ; Matsuo, K ; McLean, CA ; Meindl, A ; Muir, K ; Neuhausen, SL ; Nevanlinna, H ; Nord, S ; Olson, JE ; Orr, N ; Peterlongo, P ; Putti, TC ; Rudolph, A ; Sangrajrang, S ; Sawyer, EJ ; Schmidt, MK ; Schmutzler, RK ; Shen, C-Y ; Shi, J ; Shrubsole, MJ ; Southey, MC ; Swerdlow, A ; Teo, SH ; Thienpont, B ; Toland, AE ; Tollenaar, RAEM ; Tomlinson, IPM ; Truong, T ; Tseng, C-C ; van den Ouweland, A ; Wen, W ; Winqvist, R ; Wu, A ; Yip, CH ; Zamora, MP ; Zheng, Y ; Hall, P ; Pharoah, PDP ; Simard, J ; Chenevix-Trench, G ; Dunning, AM ; Easton, DF ; Zheng, W (AMER ASSOC CANCER RESEARCH, 2015-11)
    BACKGROUND: A recent association study identified a common variant (rs9790517) at 4q24 to be associated with breast cancer risk. Independent association signals and potential functional variants in this locus have not been explored. METHODS: We conducted a fine-mapping analysis in 55,540 breast cancer cases and 51,168 controls from the Breast Cancer Association Consortium. RESULTS: Conditional analyses identified two independent association signals among women of European ancestry, represented by rs9790517 [conditional P = 2.51 × 10(-4); OR, 1.04; 95% confidence interval (CI), 1.02-1.07] and rs77928427 (P = 1.86 × 10(-4); OR, 1.04; 95% CI, 1.02-1.07). Functional annotation using data from the Encyclopedia of DNA Elements (ENCODE) project revealed two putative functional variants, rs62331150 and rs73838678 in linkage disequilibrium (LD) with rs9790517 (r(2) ≥ 0.90) residing in the active promoter or enhancer, respectively, of the nearest gene, TET2. Both variants are located in DNase I hypersensitivity and transcription factor-binding sites. Using data from both The Cancer Genome Atlas (TCGA) and Molecular Taxonomy of Breast Cancer International Consortium (METABRIC), we showed that rs62331150 was associated with level of expression of TET2 in breast normal and tumor tissue. CONCLUSION: Our study identified two independent association signals at 4q24 in relation to breast cancer risk and suggested that observed association in this locus may be mediated through the regulation of TET2. IMPACT: Fine-mapping study with large sample size warranted for identification of independent loci for breast cancer risk.
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    SNP selection for genes of iron metabolism in a study of genetic modifiers of hemochromatosis
    Constantine, CC ; Gurrin, LC ; McLaren, CE ; Bahlo, M ; Anderson, GJ ; Vulpe, CD ; Forrest, SM ; Allen, KJ ; Gertig, DM (BMC, 2008-03-20)
    BACKGROUND: We report our experience of selecting tag SNPs in 35 genes involved in iron metabolism in a cohort study seeking to discover genetic modifiers of hereditary hemochromatosis. METHODS: We combined our own and publicly available resequencing data with HapMap to maximise our coverage to select 384 SNPs in candidate genes suitable for typing on the Illumina platform. RESULTS: Validation/design scores above 0.6 were not strongly correlated with SNP performance as estimated by Gentrain score. We contrasted results from two tag SNP selection algorithms, LDselect and Tagger. Varying r2 from 0.5 to 1.0 produced a near linear correlation with the number of tag SNPs required. We examined the pattern of linkage disequilibrium of three levels of resequencing coverage for the transferrin gene and found HapMap phase 1 tag SNPs capture 45% of the > or = 3% MAF SNPs found in SeattleSNPs where there is nearly complete resequencing. Resequencing can reveal adjacent SNPs (within 60 bp) which may affect assay performance. We report the number of SNPs present within the region of six of our larger candidate genes, for different versions of stock genotyping assays. CONCLUSION: A candidate gene approach should seek to maximise coverage, and this can be improved by adding to HapMap data any available sequencing data. Tag SNP software must be fast and flexible to data changes, since tag SNP selection involves iteration as investigators seek to satisfy the competing demands of coverage within and between populations, and typability on the technology platform chosen.
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    A comparison of different methods for including 'age at menopause' in analyses of the association between hormone replacement therapy use and breast cancer
    Simpson, Julie A. ; English, Dallas R. ; MacInnis, Robert J. ; Gertig, Dorata M. ; Hopper, John L. ; Giles, Graham G. ( 2007)
    Background and methodology: Late ‘age at menopause’ is a recognised risk factor for postmenopausal breast cancer and is also associated with decreased use of hormone replacement therapy (HRT). When investigating the association between HRT use and breast cancer risk it is therefore necessary to adjust for the potential confounder, ‘age at menopause’. ‘Age at menopause’, however, cannot be determined for women with a hysterectomy and ovarian conservation. Using data on 13 357 postmenopausal women in whom 396 cases of invasive breast cancer were diagnosed during 9 years of follow-up from the Melbourne Collaborative Cohort Study, we compared the estimates of relative risk of HRT use for breast cancer for three different methods of dealing with missing data: complete-case analysis single imputation and multiple imputation. Results: ‘Age at menopause’ was missing for 17% of the data. Both HRT use and ‘age at menopause’ were significant risk factors for breast cancer, although ‘age at menopause’ only marginally confounded the estimates of risk for HRT. Women with ‘age at menopause’ missing did not represent a random sample of the population. Complete-case analyses resulted in higher estimates of the risk associated with HRT use compared with the different methods of imputation. Discussion and conclusions: We recommend that analyses investigating the association between HRT and breast cancer should present the results in two ways: excluding women with ‘age at menopause’ missing and including the women using multiple imputation. For both methods, estimates of risk, with and without the adjustment of ‘age at menopause’, should be given.