Melbourne School of Population and Global Health - Research Publications

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    Modifiable lifestyle risk factors and survival after diagnosis with multiple myeloma
    Cheah, S ; Bassett, JK ; Bruinsma, FJ ; Hopper, J ; Jayasekara, H ; Joshua, D ; Macinnis, RJ ; Prince, HM ; Southey, MC ; Vajdic, CM ; van Leeuwen, MT ; Doo, NW ; Harrison, SJ ; English, DR ; Giles, GG ; Milne, RL (TAYLOR & FRANCIS LTD, 2023-10-03)
    BACKGROUND: While remaining incurable, median overall survival for MM now exceeds 5 years. Yet few studies have investigated how modifiable lifestyle factors influence survival. We investigate whether adiposity, diet, alcohol, or smoking are associated with MM-related fatality. RESEARCH DESIGN AND METHODS: We recruited 760 incident cases of MM via cancer registries in two Australian states during 2010-2016. Participants returned questionnaires on health and lifestyle. Follow-up ended in 2020. Flexible parametric survival models were used to estimate hazard ratios (HR) and 95% confidence intervals (CI) for lifestyle exposures and risk of all-cause and MM-specific fatality. RESULTS: Higher pre-diagnosis Alternative Healthy Eating Index (AHEI) scores were associated with reduced MM-specific fatality (per 10-unit score, HR = 0.84, 95%CI = 0.70-0.99). Pre-diagnosis alcohol consumption was inversely associated with MM-specific fatality, compared with nondrinkers (0.1-20 g per day, HR = 0.59, 95%CI = 0.39-0.90; >20 g per day, HR = 0.67, 95%CI = 0.40-1.13). Tobacco smoking was associated with increased all-cause fatality compared with never smoking (former smokers: HR = 1.44, 95%CI = 1.10-1.88; current smokers: HR = 1.30, 95%CI = 0.80-2.10). There was no association between pre-enrollment body mass index (BMI) and MM-specific or all-cause fatality. CONCLUSIONS: Our findings support established recommendations for healthy diets and against smoking. Higher quality diet, as measured by the AHEI, may improve survival post diagnosis with MM.
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    Physical activity, sedentary time and breast cancer risk: a Mendelian randomisation study
    Dixon-Suen, SC ; Lewis, SJ ; Martin, RM ; English, DR ; Boyle, T ; Giles, GG ; Michailidou, K ; Bolla, MK ; Wang, Q ; Dennis, J ; Lush, M ; Ahearn, TU ; Ambrosone, CB ; Andrulis, IL ; Anton-Culver, H ; Arndt, V ; Aronson, KJ ; Augustinsson, A ; Auvinen, P ; Beane Freeman, LE ; Becher, H ; Beckmann, MW ; Behrens, S ; Bermisheva, M ; Blomqvist, C ; Bogdanova, N ; Bojesen, SE ; Bonanni, B ; Brenner, H ; Bruening, T ; Buys, SS ; Camp, NJ ; Campa, D ; Canzian, F ; Castelao, JE ; Cessna, MH ; Chang-Claude, J ; Chanock, SJ ; Clarke, CL ; Conroy, DM ; Couch, FJ ; Cox, A ; Cross, SS ; Czene, K ; Daly, MB ; Devilee, P ; Doerk, T ; Dwek, M ; Eccles, DM ; Eliassen, AH ; Engel, C ; Eriksson, M ; Evans, DG ; Fasching, PA ; Fletcher, O ; Flyger, H ; Fritschi, L ; Gabrielson, M ; Gago-Dominguez, M ; Garcia-Closas, M ; Garcia-Saenz, JA ; Goldberg, MS ; Guenel, P ; Guendert, M ; Hahnen, E ; Haiman, CA ; Haeberle, L ; Hakansson, N ; Hall, P ; Hamann, U ; Hart, SN ; Harvie, M ; Hillemanns, P ; Hollestelle, A ; Hooning, MJ ; Hoppe, R ; Hopper, J ; Howell, A ; Hunter, DJ ; Jakubowska, A ; Janni, W ; John, EM ; Jung, A ; Kaaks, R ; Keeman, R ; Kitahara, CM ; Koutros, S ; Kraft, P ; Kristensen, VN ; Kubelka-Sabit, K ; Kurian, AW ; Lacey, J ; Lambrechts, D ; Le Marchand, L ; Lindblom, A ; Loibl, S ; Lubinski, J ; Mannermaa, A ; Manoochehri, M ; Margolin, S ; Martinez, ME ; Mavroudis, D ; Menon, U ; Mulligan, AM ; Murphy, RA ; Nevanlinna, H ; Nevelsteen, I ; Newman, WG ; Offit, K ; Olshan, AF ; Olsson, H ; Orr, N ; Patel, A ; Peto, J ; Plaseska-Karanfilska, D ; Presneau, N ; Rack, B ; Radice, P ; Rees-Punia, E ; Rennert, G ; Rennert, HS ; Romero, A ; Saloustros, E ; Sandler, DP ; Schmidt, MK ; Schmutzler, RK ; Schwentner, L ; Scott, C ; Shah, M ; Shu, X-O ; Simard, J ; Southey, MC ; Stone, J ; Surowy, H ; Swerdlow, AJ ; Tamimi, RM ; Tapper, WJ ; Taylor, JA ; Terry, MB ; Tollenaar, RAEM ; Troester, MA ; Truong, T ; Untch, M ; Vachon, CM ; Joseph, V ; Wappenschmidt, B ; Weinberg, CR ; Wolk, A ; Yannoukakos, D ; Zheng, W ; Ziogas, A ; Dunning, AM ; Pharoah, PDP ; Easton, DF ; Milne, RL ; Lynch, BM (BMJ PUBLISHING GROUP, 2022-10)
    OBJECTIVES: Physical inactivity and sedentary behaviour are associated with higher breast cancer risk in observational studies, but ascribing causality is difficult. Mendelian randomisation (MR) assesses causality by simulating randomised trial groups using genotype. We assessed whether lifelong physical activity or sedentary time, assessed using genotype, may be causally associated with breast cancer risk overall, pre/post-menopause, and by case-groups defined by tumour characteristics. METHODS: We performed two-sample inverse-variance-weighted MR using individual-level Breast Cancer Association Consortium case-control data from 130 957 European-ancestry women (69 838 invasive cases), and published UK Biobank data (n=91 105-377 234). Genetic instruments were single nucleotide polymorphisms (SNPs) associated in UK Biobank with wrist-worn accelerometer-measured overall physical activity (nsnps=5) or sedentary time (nsnps=6), or accelerometer-measured (nsnps=1) or self-reported (nsnps=5) vigorous physical activity. RESULTS: Greater genetically-predicted overall activity was associated with lower breast cancer overall risk (OR=0.59; 95% confidence interval (CI) 0.42 to 0.83 per-standard deviation (SD;~8 milligravities acceleration)) and for most case-groups. Genetically-predicted vigorous activity was associated with lower risk of pre/perimenopausal breast cancer (OR=0.62; 95% CI 0.45 to 0.87,≥3 vs. 0 self-reported days/week), with consistent estimates for most case-groups. Greater genetically-predicted sedentary time was associated with higher hormone-receptor-negative tumour risk (OR=1.77; 95% CI 1.07 to 2.92 per-SD (~7% time spent sedentary)), with elevated estimates for most case-groups. Results were robust to sensitivity analyses examining pleiotropy (including weighted-median-MR, MR-Egger). CONCLUSION: Our study provides strong evidence that greater overall physical activity, greater vigorous activity, and lower sedentary time are likely to reduce breast cancer risk. More widespread adoption of active lifestyles may reduce the burden from the most common cancer in women.
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    Does genetic predisposition modify the effect of lifestyle-related factors on DNA methylation?
    Yu, C ; Hodge, AM ; Wong, EM ; Joo, JE ; Makalic, E ; Schmidt, DF ; Buchanan, DD ; Severi, G ; Hopper, JL ; English, DR ; Giles, GG ; Milne, RL ; Southey, MC ; Dugue, P-A (TAYLOR & FRANCIS INC, 2022-12-02)
    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.
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    Methylation scores for smoking, alcohol consumption and body mass index and risk of seven types of cancer
    Dugue, P-A ; Yu, C ; Hodge, AMM ; Wong, EM ; Joo, JEE ; Jung, C-H ; Schmidt, D ; Makalic, E ; Buchanan, DDD ; Severi, G ; English, DRR ; Hopper, JLL ; Milne, RLL ; Giles, GGG ; Southey, MCC (WILEY, 2023-08-01)
    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.
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    Alcohol and tobacco use and risk of multiple myeloma: A case‐control study
    Cheah, S ; Bassett, JK ; Bruinsma, FJ ; Cozen, W ; Hopper, JL ; Jayasekara, H ; Joshua, D ; MacInnis, RJ ; Prince, HM ; Vajdic, CM ; van Leeuwen, MT ; Doo, NW ; Harrison, SJ ; English, DR ; Giles, GG ; Milne, RL (Wiley, 2022-02)
    Abstract Multiple myeloma (MM) is the second most common hematological cancer and causes significant mortality and morbidity. Knowledge regarding modifiable risk factors for MM remains limited. This analysis of an Australian population‐based case–control family study investigates whether smoking or alcohol consumption is associated with risk of MM and related diseases. Incident cases (n = 789) of MM were recruited via cancer registries in Victoria and New South Wales. Controls (n = 1,113) were either family members of cases (n = 696) or controls recruited for a similarly designed study of renal cancers (n = 417). Adjusted odds ratios (OR) and 95% confidence intervals (CI) were estimated using unconditional multivariable logistic regression. Heavy intake (>20 g ethanol/day) of alcohol had a lower risk of MM compared with nondrinkers (OR = 0.68, 95% CI: 0.50–0.93), and there was an inverse dose–response relationship for average daily alcohol intake (OR per 10 g ethanol per day = 0.92, 95% CI: 0.86–0.99); there was no evidence of an interaction with sex. There was no evidence of an association with MM risk for smoking‐related exposures (p > 0.18). The associations between smoking and alcohol with MM are similar to those with non‐Hodgkin lymphoma. Further research into potential underlying mechanisms is warranted.
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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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    DNA methylation-based biological aging and cancer risk and survival: Pooled analysis of seven prospective studies
    Dugue, P-A ; Bassett, JK ; Joo, JE ; Jung, C-H ; Wong, EM ; Moreno-Betancur, M ; Schmidt, D ; Makalic, E ; Li, S ; Severi, G ; Hodge, AM ; Buchanan, DD ; English, DR ; Hopper, JL ; Southey, MC ; Giles, GG ; Milne, RL (WILEY, 2018-04-15)
    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.
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    Lifetime alcohol intake and risk of non-Hodgkin lymphoma: Findings from the Melbourne Collaborative Cohort Study
    Jayasekara, H ; Juneja, S ; Hodge, AM ; Room, R ; Milne, RL ; Hopper, JL ; English, DR ; Giles, GG ; MacInnis, RJ (WILEY, 2018-03-01)
    Cohort studies have reported inconsistent evidence regarding alcohol intake and risk of non-Hodgkin lymphoma (NHL), mostly based on alcohol intake assessed close to study enrolment. We examined this association using alcohol intake measured from age 20 onwards. We calculated usual alcohol intake for 10-year periods from age 20 using recalled frequency and quantity of beverage-specific consumption for 37,990 participants aged 40-69 years from the Melbourne Collaborative Cohort Study. Cox regression was performed to derive hazard ratios (HRs) and 95% confidence intervals (CIs) for the association between alcohol intake (g/day) and NHL risk. After a mean follow-up of 19.3 years, 538 NHL cases were diagnosed. Approximately 80% of participants were either lifetime abstainers or consumed below 20 g of ethanol/day. All categories of lifetime alcohol intake were associated with about 20% lower incidence of NHL compared with lifetime abstention, but there was no evidence of a trend by amount consumed (HR = 0.97 per 10 g/day increment in intake, 95% CI: 0.92-1.03; p value = 0.3). HRs for beer, wine and spirits were 0.91 (95% CI: 0.83-1.00; p value = 0.05), 1.03 (95% CI: 0.94-1.12; p value = 0.6), and 1.06 (95% CI: 0.83-1.37; p value = 0.6), respectively, per 10 g/day increment in lifetime intake. There were no significant differences in associations between NHL subtypes. In this low-drinking cohort, we did not detect a dose-dependent association between lifetime alcohol intake and NHL risk.
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    Associations of alcohol intake, smoking, physical activity and obesity with survival following colorectal cancer diagnosis by stage, anatomic site and tumor molecular subtype
    Jayasekara, H ; English, DR ; Haydon, A ; Hodge, AM ; Lynch, BM ; Rosty, C ; Williamson, EJ ; Clendenning, M ; Southey, MC ; Jenkins, MA ; Room, R ; Hopper, JL ; Milne, RL ; Buchanan, DD ; Giles, GG ; MacInnis, RJ (WILEY, 2018-01-15)
    The influence of lifestyle factors on survival following a diagnosis of colorectal cancer (CRC) is not well established. We examined associations between lifestyle factors measured before diagnosis and CRC survival. The Melbourne Collaborative Cohort Study collected data on alcohol intake, cigarette smoking and physical activity, and body measurements at baseline (1990-1994) and wave 2 (2003-2007). We included participants diagnosed to 31 August 2015 with incident stages I-III CRC within 10-years post exposure assessment. Information on tumor characteristics and vital status was obtained. Tumor DNA was tested for microsatellite instability (MSI) and somatic mutations in oncogenes BRAF (V600E) and KRAS. We estimated hazard ratios (HRs) for associations between lifestyle factors and overall and CRC-specific mortality using Cox regression. Of 724 eligible CRC cases, 339 died (170 from CRC) during follow-up (average 9.0 years). Exercise (non-occupational/leisure-time) was associated with higher CRC-specific survival for stage II (HR = 0.25, 95% CI: 0.10-0.60) but not stages I/III disease (p for interaction = 0.01), and possibly for colon and KRAS wild-type tumors. Waist circumference was inversely associated with CRC-specific survival (HR = 1.25 per 10 cm increment, 95% CI: 1.08-1.44), independent of stage, anatomic site and tumor molecular status. Cigarette smoking was associated with lower overall survival, with suggestive evidence of worse survival for BRAF mutated CRC, but not with CRC-specific survival. Alcohol intake was not associated with survival. Survival did not differ by MSI status. We have identified pre-diagnostic predictors of survival following CRC that may have clinical and public health relevance.
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    Genome-Wide Measures of Peripheral Blood Dna Methylation and Prostate Cancer Risk in a Prospective Nested Case-Control Study
    FitzGerald, LM ; Naeem, H ; Makalic, E ; Schmidt, DF ; Dowty, JG ; Joo, JE ; Jung, C-H ; Bassett, JK ; Dugue, P-A ; Chung, J ; Lonie, A ; Milne, RL ; Wong, EM ; Hopper, JL ; English, DR ; Severi, G ; Baglietto, L ; Pedersen, J ; Giles, GG ; Southey, MC (WILEY, 2017-04-01)