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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    Deciphering colorectal cancer genetics through multi-omic analysis of 100,204 cases and 154,587 controls of European and east Asian ancestries
    Fernandez-Rozadilla, C ; Timofeeva, M ; Chen, Z ; Law, P ; Thomas, M ; Bien, S ; Diez-Obrero, V ; Li, L ; Fernandez-Tajes, J ; Palles, C ; Sherwood, K ; Harris, S ; Svinti, V ; McDonnell, K ; Farrington, S ; Studd, J ; Vaughan-Shaw, P ; Shu, X-O ; Long, J ; Cai, Q ; Guo, X ; Lu, Y ; Scacheri, P ; Studd, J ; Huyghe, J ; Harrison, T ; Shibata, D ; Haiman, C ; Devall, M ; Schumacher, F ; Melas, M ; Rennert, G ; Obon-Santacana, M ; Martin-Sanchez, V ; Moratalla-Navarro, F ; Oh, JH ; Kim, J ; Jee, SH ; Jung, KJ ; Kweon, S-S ; Shin, M-H ; Shin, A ; Ahn, Y-O ; Kim, D-H ; Oze, I ; Wen, W ; Matsuo, K ; Matsuda, K ; Tanikawa, C ; Ren, Z ; Gao, Y-T ; Jia, W-H ; Potter, J ; Jenkins, M ; Win, AK ; Pai, R ; Figueiredo, J ; Haile, R ; Gallinger, S ; Woods, M ; Newcomb, P ; Shibata, D ; Cheadle, J ; Kaplan, R ; Maughan, T ; Kerr, R ; Kerr, D ; Kirac, I ; Boehm, J ; Mecklin, L-P ; Jousilahti, P ; Knekt, P ; Aaltonen, L ; Rissanen, H ; Pukkala, E ; Eriksson, J ; Cajuso, T ; Hanninen, U ; Kondelin, J ; Palin, K ; Tanskanen, T ; Renkonen-Sinisalo, L ; Zanke, B ; Mannisto, S ; Albanes, D ; Weinstein, S ; Ruiz-Narvaez, E ; Palmer, J ; Buchanan, D ; Platz, E ; Visvanathan, K ; Ulrich, C ; Siegel, E ; Brezina, S ; Gsur, A ; Campbell, P ; Chang-Claude, J ; Hoffmeister, M ; Brenner, H ; Slattery, M ; Potter, J ; Tsilidis, K ; Schulze, M ; Gunter, M ; Murphy, N ; Castells, A ; Castellvi-Bel, S ; Moreira, L ; Arndt, V ; Shcherbina, A ; Stern, M ; Pardamean, B ; Bishop, T ; Giles, G ; Southey, M ; Idos, G ; McDonnell, K ; Abu-Ful, Z ; Greenson, J ; Shulman, K ; Lejbkowicz, F ; Offit, K ; Su, Y-R ; Steinfelder, R ; Keku, T ; van Guelpen, B ; Hudson, T ; Hampel, H ; Pearlman, R ; Berndt, S ; Hayes, R ; Martinez, ME ; Thomas, S ; Corley, D ; Pharoah, P ; Larsson, S ; Yen, Y ; Lenz, H-J ; White, E ; Li, L ; Doheny, K ; Pugh, E ; Shelford, T ; Chan, A ; Cruz-Correa, M ; Lindblom, A ; Shibata, D ; Joshi, A ; Schafmayer, C ; Scacheri, P ; Kundaje, A ; Nickerson, D ; Schoen, R ; Hampe, J ; Stadler, Z ; Vodicka, P ; Vodickova, L ; Vymetalkova, V ; Papadopoulos, N ; Edlund, C ; Gauderman, W ; Thomas, D ; Shibata, D ; Toland, A ; Markowitz, S ; Kim, A ; Gruber, S ; van Duijnhoven, F ; Feskens, E ; Sakoda, L ; Gago-Dominguez, M ; Wolk, A ; Naccarati, A ; Pardini, B ; FitzGerald, L ; Lee, SC ; Ogino, S ; Bien, S ; Kooperberg, C ; Li, C ; Lin, Y ; Prentice, R ; Qu, C ; Bezieau, S ; Tangen, C ; Mardis, E ; Yamaji, T ; Sawada, N ; Iwasaki, M ; Haiman, C ; Le Marchand, L ; Wu, A ; Qu, C ; McNeil, C ; Coetzee, G ; Hayward, C ; Deary, I ; Harris, S ; Theodoratou, E ; Reid, S ; Walker, M ; Ooi, LY ; Moreno, V ; Casey, G ; Gruber, S ; Tomlinson, I ; Zheng, W ; Dunlop, M ; Houlston, R ; Peters, U (NATURE PORTFOLIO, 2023-01)
    Colorectal cancer (CRC) is a leading cause of mortality worldwide. We conducted a genome-wide association study meta-analysis of 100,204 CRC cases and 154,587 controls of European and east Asian ancestry, identifying 205 independent risk associations, of which 50 were unreported. We performed integrative genomic, transcriptomic and methylomic analyses across large bowel mucosa and other tissues. Transcriptome- and methylome-wide association studies revealed an additional 53 risk associations. We identified 155 high-confidence effector genes functionally linked to CRC risk, many of which had no previously established role in CRC. These have multiple different functions and specifically indicate that variation in normal colorectal homeostasis, proliferation, cell adhesion, migration, immunity and microbial interactions determines CRC risk. Crosstissue analyses indicated that over a third of effector genes most probably act outside the colonic mucosa. Our findings provide insights into colorectal oncogenesis and highlight potential targets across tissues for new CRC treatment and chemoprevention strategies.
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    Causal relationships between breast cancer risk factors based on mammographic features
    Ye, Z ; Nguyen, TL ; Dite, GS ; Macinnis, RJ ; Schmidt, DF ; Makalic, E ; Al-Qershi, OM ; Bui, M ; Esser, VFC ; Dowty, JG ; Trinh, HN ; Evans, CF ; Tan, M ; Sung, J ; Jenkins, MA ; Giles, GG ; Southey, MC ; Hopper, JL ; Li, S (BMC, 2023-10-25)
    BACKGROUND: Mammogram risk scores based on texture and density defined by different brightness thresholds are associated with breast cancer risk differently and could reveal distinct information about breast cancer risk. We aimed to investigate causal relationships between these intercorrelated mammogram risk scores to determine their relevance to breast cancer aetiology. METHODS: We used digitised mammograms for 371 monozygotic twin pairs, aged 40-70 years without a prior diagnosis of breast cancer at the time of mammography, from the Australian Mammographic Density Twins and Sisters Study. We generated normalised, age-adjusted, and standardised risk scores based on textures using the Cirrus algorithm and on three spatially independent dense areas defined by increasing brightness threshold: light areas, bright areas, and brightest areas. Causal inference was made using the Inference about Causation from Examination of FAmilial CONfounding (ICE FALCON) method. RESULTS: The mammogram risk scores were correlated within twin pairs and with each other (r = 0.22-0.81; all P < 0.005). We estimated that 28-92% of the associations between the risk scores could be attributed to causal relationships between the scores, with the rest attributed to familial confounders shared by the scores. There was consistent evidence for positive causal effects: of Cirrus, light areas, and bright areas on the brightest areas (accounting for 34%, 55%, and 85% of the associations, respectively); and of light areas and bright areas on Cirrus (accounting for 37% and 28%, respectively). CONCLUSIONS: In a mammogram, the lighter (less dense) areas have a causal effect on the brightest (highly dense) areas, including through a causal pathway via textural features. These causal relationships help us gain insight into the relative aetiological importance of different mammographic features in breast cancer. For example our findings are consistent with the brightest areas being more aetiologically important than lighter areas for screen-detected breast cancer; conversely, light areas being more aetiologically important for interval breast cancer. Additionally, specific textural features capture aetiologically independent breast cancer risk information from dense areas. These findings highlight the utility of ICE FALCON and family data in decomposing the associations between intercorrelated disease biomarkers into distinct biological pathways.
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    Evaluation of European-based polygenic risk score for breast cancer in Ashkenazi Jewish women in Israel
    Levi, H ; Carmi, S ; Rosset, S ; Yerushalmi, R ; Zick, A ; Yablonski-Peretz, T ; Wang, Q ; Bolla, MK ; Dennis, J ; Michailidou, K ; Lush, M ; Ahearn, T ; Andrulis, IL ; Anton-Culver, H ; Antoniou, AC ; Arndt, V ; Augustinsson, A ; Auvinen, P ; Beane Freeman, L ; Beckmann, M ; Behrens, S ; Bermisheva, M ; Bodelon, C ; Bogdanova, N ; Bojesen, SE ; Brenner, H ; Byers, H ; Camp, N ; Castelao, J ; Chang-Claude, J ; Chirlaque, M-D ; Chung, W ; Clarke, C ; Collee, MJ ; Colonna, S ; Couch, F ; Cox, A ; Cross, SS ; Czene, K ; Daly, M ; Devilee, P ; Dork, T ; Dossus, L ; Eccles, DM ; Eliassen, AH ; Eriksson, M ; Evans, G ; Fasching, P ; Fletcher, O ; Flyger, H ; Fritschi, L ; Gabrielson, M ; Gago-Dominguez, M ; Garcia-Closas, M ; Garcia-Saenz, JA ; Genkinger, J ; Giles, GG ; Goldberg, M ; Guenel, P ; Hall, P ; Hamann, U ; He, W ; Hillemanns, P ; Hollestelle, A ; Hoppe, R ; Hopper, J ; Jakovchevska, S ; Jakubowska, A ; Jernstrom, H ; John, E ; Johnson, N ; Jones, M ; Vijai, J ; Kaaks, R ; Khusnutdinova, E ; Kitahara, C ; Koutros, S ; Kristensen, V ; Kurian, AW ; Lacey, J ; Lambrechts, D ; Le Marchand, L ; Lejbkowicz, F ; Lindblom, A ; Loibl, S ; Lori, A ; Lubinski, J ; Mannermaa, A ; Manoochehri, M ; Mavroudis, D ; Menon, U ; Mulligan, A ; Murphy, R ; Nevelsteen, I ; Newman, WG ; Obi, N ; O'Brien, K ; Offit, K ; Olshan, A ; Plaseska-Karanfilska, D ; Olson, J ; Panico, S ; Park-Simon, T-W ; Patel, A ; Peterlongo, P ; Rack, B ; Radice, P ; Rennert, G ; Rhenius, V ; Romero, A ; Saloustros, E ; Sandler, D ; Schmidt, MK ; Schwentner, L ; Shah, M ; Sharma, P ; Simard, J ; Southey, M ; Stone, J ; Tapper, WJ ; Taylor, J ; Teras, L ; Toland, AE ; Troester, M ; Truong, T ; van der Kolk, LE ; Weinberg, C ; Wendt, C ; Yang, XR ; Zheng, W ; Ziogas, A ; Dunning, AM ; Pharoah, P ; Easton, DF ; Ben-Sachar, S ; Elefant, N ; Shamir, R ; Elkon, R (BMJ PUBLISHING GROUP, 2023-12)
    BACKGROUND: Polygenic risk score (PRS), calculated based on genome-wide association studies (GWASs), can improve breast cancer (BC) risk assessment. To date, most BC GWASs have been performed in individuals of European (EUR) ancestry, and the generalisation of EUR-based PRS to other populations is a major challenge. In this study, we examined the performance of EUR-based BC PRS models in Ashkenazi Jewish (AJ) women. METHODS: We generated PRSs based on data on EUR women from the Breast Cancer Association Consortium (BCAC). We tested the performance of the PRSs in a cohort of 2161 AJ women from Israel (1437 cases and 724 controls) from BCAC (BCAC cohort from Israel (BCAC-IL)). In addition, we tested the performance of these EUR-based BC PRSs, as well as the established 313-SNP EUR BC PRS, in an independent cohort of 181 AJ women from Hadassah Medical Center (HMC) in Israel. RESULTS: In the BCAC-IL cohort, the highest OR per 1 SD was 1.56 (±0.09). The OR for AJ women at the top 10% of the PRS distribution compared with the middle quintile was 2.10 (±0.24). In the HMC cohort, the OR per 1 SD of the EUR-based PRS that performed best in the BCAC-IL cohort was 1.58±0.27. The OR per 1 SD of the commonly used 313-SNP BC PRS was 1.64 (±0.28). CONCLUSIONS: Extant EUR GWAS data can be used for generating PRSs that identify AJ women with markedly elevated risk of BC and therefore hold promise for improving BC risk assessment in AJ women.
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    Genome-wide Association Study of Bladder Cancer Reveals New Biological and Translational Insights
    Koutros, S ; Kiemeney, LA ; Choudhury, PP ; Milne, RL ; de Maturana, EL ; Ye, Y ; Joseph, V ; Florez-Vargas, O ; Dyrskjot, L ; Figueroa, J ; Dutta, D ; Giles, GG ; Hildebrandt, MAT ; Offit, K ; Kogevinas, M ; Weiderpass, E ; McCullough, ML ; Freedman, ND ; Albanes, D ; Kooperberg, C ; Cortessis, VK ; Karagas, MR ; Johnson, A ; Schwenn, MR ; Baris, D ; Furberg, H ; Bajorin, DF ; Cussenot, O ; Cancel-Tassin, G ; Benhamou, S ; Kraft, P ; Porru, S ; Carta, A ; Bishop, T ; Southey, MC ; Matullo, G ; Fletcher, T ; Kumar, R ; Taylor, JA ; Lamy, P ; Prip, F ; Kalisz, M ; Weinstein, SJ ; Hengstler, JG ; Selinski, S ; Harland, M ; Teo, M ; Kiltie, AE ; Tardon, A ; Serra, C ; Carrato, A ; Garcia-Closas, R ; Lloreta, J ; Schned, A ; Lenz, P ; Riboli, E ; Brennan, P ; Tjonneland, A ; Otto, T ; Ovsiannikov, D ; Volkert, F ; Vermeulen, SH ; Aben, KK ; Galesloot, TE ; Turman, C ; De Vivo, I ; Giovannucci, E ; Hunter, DJ ; Hohensee, C ; Hunt, R ; V. Patel, A ; Huang, W-Y ; Thorleifsson, G ; Gago-Dominguez, M ; Amiano, P ; Golka, K ; Stern, MC ; Yan, W ; Liu, J ; Alfred, S ; Katta, S ; Hutchinson, A ; Hicks, B ; Wheeler, WA ; Purdue, MP ; McGlynn, KA ; Kitahara, CM ; Haiman, CA ; Greene, MH ; Rafnar, T ; Chatterjee, N ; Chanock, SJ ; Wu, X ; Real, FX ; Silverman, DT ; Garcia-Closas, M ; Stefansson, K ; Prokunina-Olsson, L ; Malats, N ; Rothman, N (ELSEVIER, 2023-07)
    BACKGROUND: Genomic regions identified by genome-wide association studies (GWAS) for bladder cancer risk provide new insights into etiology. OBJECTIVE: To identify new susceptibility variants for bladder cancer in a meta-analysis of new and existing genome-wide genotype data. DESIGN, SETTING, AND PARTICIPANTS: Data from 32 studies that includes 13,790 bladder cancer cases and 343,502 controls of European ancestry were used for meta-analysis. OUTCOME MEASUREMENTS AND STATISTICAL ANALYSES: Log-additive associations of genetic variants were assessed using logistic regression models. A fixed-effects model was used for meta-analysis of the results. Stratified analyses were conducted to evaluate effect modification by sex and smoking status. A polygenic risk score (PRS) was generated on the basis of known and novel susceptibility variants and tested for interaction with smoking. RESULTS AND LIMITATIONS: Multiple novel bladder cancer susceptibility loci (6p.22.3, 7q36.3, 8q21.13, 9p21.3, 10q22.1, 19q13.33) as well as improved signals in three known regions (4p16.3, 5p15.33, 11p15.5) were identified, bringing the number of independent markers at genome-wide significance (p < 5 × 10-8) to 24. The 4p16.3 (FGFR3/TACC3) locus was associated with a stronger risk for women than for men (p-interaction = 0.002). Bladder cancer risk was increased by interactions between smoking status and genetic variants at 8p22 (NAT2; multiplicative p value for interaction [pM-I] = 0.004), 8q21.13 (PAG1; pM-I = 0.01), and 9p21.3 (LOC107987026/MTAP/CDKN2A; pM-I = 0.02). The PRS based on the 24 independent GWAS markers (odds ratio per standard deviation increase 1.49, 95% confidence interval 1.44-1.53), which also showed comparable results in two prospective cohorts (UK Biobank, PLCO trial), revealed an approximately fourfold difference in the lifetime risk of bladder cancer according to the PRS (e.g., 1st vs 10th decile) for both smokers and nonsmokers. CONCLUSIONS: We report novel loci associated with risk of bladder cancer that provide clues to its biological underpinnings. Using 24 independent markers, we constructed a PRS to stratify lifetime risk. The PRS combined with smoking history, and other established risk factors, has the potential to inform future screening efforts for bladder cancer. PATIENT SUMMARY: We identified new genetic markers that provide biological insights into the genetic causes of bladder cancer. These genetic risk factors combined with lifestyle risk factors, such as smoking, may inform future preventive and screening strategies for bladder cancer.
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    Variance of age-specific log incidence decomposition (VALID): a unifying model of measured and unmeasured genetic and non-genetic risks
    Hopper, JL ; Dowty, JG ; Nguyen, TL ; Li, S ; Dite, GS ; MacInnis, RJ ; Makalic, E ; Schmidt, DF ; Bui, M ; Stone, J ; Sung, J ; Jenkins, MA ; Giles, GG ; Southey, MC ; Mathews, JD (OXFORD UNIV PRESS, 2023-10-05)
    BACKGROUND: The extent to which known and unknown factors explain how much people of the same age differ in disease risk is fundamental to epidemiology. Risk factors can be correlated in relatives, so familial aspects of risk (genetic and non-genetic) must be considered. DEVELOPMENT: We present a unifying model (VALID) for variance in risk, with risk defined as log(incidence) or logit(cumulative incidence). Consider a normally distributed risk score with incidence increasing exponentially as the risk increases. VALID's building block is variance in risk, Δ2, where Δ = log(OPERA) is the difference in mean between cases and controls and OPERA is the odds ratio per standard deviation. A risk score correlated r between a pair of relatives generates a familial odds ratio of exp(rΔ2). Familial risk ratios, therefore, can be converted into variance components of risk, extending Fisher's classic decomposition of familial variation to binary traits. Under VALID, there is a natural upper limit to variance in risk caused by genetic factors, determined by the familial odds ratio for genetically identical twin pairs, but not to variation caused by non-genetic factors. APPLICATION: For female breast cancer, VALID quantified how much variance in risk is explained-at different ages-by known and unknown major genes and polygenes, non-genomic risk factors correlated in relatives, and known individual-specific factors. CONCLUSION: VALID has shown that, while substantial genetic risk factors have been discovered, much is unknown about genetic and familial aspects of breast cancer risk especially for young women, and little is known about individual-specific variance in risk.
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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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    Distinct Reproductive Risk Profiles for Intrinsic-Like Breast Cancer Subtypes: Pooled Analysis of Population-Based Studies
    Jung, AY ; Ahearn, TU ; Behrens, S ; Middha, P ; Bolla, MK ; Wang, Q ; Arndt, V ; Aronson, KJ ; Augustinsson, A ; Freeman, LEB ; Becher, H ; Brenner, H ; Canzian, F ; Carey, LA ; Consortium, C ; Czene, K ; Eliassen, AH ; Eriksson, M ; Evans, DG ; Figueroa, JD ; Fritschi, L ; Gabrielson, M ; Giles, GG ; Guenel, P ; Hadjisavvas, A ; Haiman, CA ; Hakansson, N ; Hall, P ; Hamann, U ; Hoppe, R ; Hopper, JL ; Howell, A ; Hunter, DJ ; Huesing, A ; Kaaks, R ; Kosma, V-M ; Koutros, S ; Kraft, P ; Lacey, J ; Le Marchand, L ; Lissowska, J ; Loizidou, MA ; Mannermaa, A ; Maurer, T ; Murphy, RA ; Olshan, AF ; Olsson, H ; Patel, A ; Perou, CM ; Rennert, G ; Shibli, R ; Shu, X-O ; Southey, MC ; Stone, J ; Tamimi, RM ; Teras, LR ; Troester, MA ; Truong, T ; Vachon, CM ; Wang, SS ; Wolk, A ; Wu, AH ; Yang, XR ; Zheng, W ; Dunning, AM ; Pharoah, PDP ; Easton, DF ; Milne, RL ; Chatterjee, N ; Schmidt, MK ; Garcia-Closas, M ; Chang-Claude, J (OXFORD UNIV PRESS INC, 2022-12)
    BACKGROUND: Reproductive factors have been shown to be differentially associated with risk of estrogen receptor (ER)-positive and ER-negative breast cancer. However, their associations with intrinsic-like subtypes are less clear. METHODS: Analyses included up to 23 353 cases and 71 072 controls pooled from 31 population-based case-control or cohort studies in the Breast Cancer Association Consortium across 16 countries on 4 continents. Polytomous logistic regression was used to estimate the association between reproductive factors and risk of breast cancer by intrinsic-like subtypes (luminal A-like, luminal B-like, luminal B-HER2-like, HER2-enriched-like, and triple-negative breast cancer) and by invasiveness. All statistical tests were 2-sided. RESULTS: Compared with nulliparous women, parous women had a lower risk of luminal A-like, luminal B-like, luminal B-HER2-like, and HER2-enriched-like disease. This association was apparent only after approximately 10 years since last birth and became stronger with increasing time (odds ratio [OR] = 0.59, 95% confidence interval [CI] = 0.49 to 0.71; and OR = 0.36, 95% CI = 0.28 to 0.46 for multiparous women with luminal A-like tumors 20 to less than 25 years after last birth and 45 to less than 50 years after last birth, respectively). In contrast, parous women had a higher risk of triple-negative breast cancer right after their last birth (for multiparous women: OR = 3.12, 95% CI = 2.02 to 4.83) that was attenuated with time but persisted for decades (OR = 1.03, 95% CI = 0.79 to 1.34, for multiparous women 25 to less than 30 years after last birth). Older age at first birth (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) and breastfeeding (Pheterogeneity < .001 for triple-negative compared with luminal A-like breast cancer) were associated with lower risk of triple-negative breast cancer but not with other disease subtypes. Younger age at menarche was associated with higher risk of all subtypes; older age at menopause was associated with higher risk of luminal A-like but not triple-negative breast cancer. Associations for in situ tumors were similar to luminal A-like. CONCLUSIONS: This large and comprehensive study demonstrates a distinct reproductive risk factor profile for triple-negative breast cancer compared with other subtypes, with implications for the understanding of disease etiology and risk prediction.
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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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    Adiposity and plasma concentrations of kynurenine pathway metabolites and traditional markers of inflammation.
    Wang, ME ; Hodge, AM ; Li, SX ; Southey, MC ; Giles, GG ; Dugué, P-A (Elsevier BV, 2023)
    AIM: The kynurenine pathway is increasingly recognised to play a role in inflammation and disease. We assessed the cross-sectional and longitudinal associations of adiposity measures (body mass index, waist-hip ratio, waist circumference and fat mass ratio) with plasma concentrations of kynurenine pathway metabolites and traditional markers of inflammation. METHODS: We used data from 970 Melbourne Collaborative Cohort Study participants who had plasma markers measured at baseline (median age 59 years) and follow-up (median age 70 years). Linear regression was used to assess cross-sectional and longitudinal associations between four adiposity measures and concentrations of i) nine kynurenine pathway metabolites; ii) two derived markers; iii) eight traditional inflammatory markers. RESULTS: Cross-sectionally, most kynurenine metabolites were strongly associated with adiposity measures at both time points; associations were generally stronger than for most inflammation markers except CRP (e.g. body mass index at baseline, quinolinic acid (per S.D. β = 0.30, 95%CI: 0.24-0.36, P = 10-21), kynurenine (β = 0.25, 95%CI: 0.19-0.31, P = 10-16) and CRP (β = 0.31, 95%CI: 0.25-0.37, P = 10-24), and remained largely unchanged after adjustment for confounders. Longitudinally, changes in adiposity measures over approximately a decade were positively associated with changes in kynurenine metabolite concentrations (in particular for 3-hydroxyanthranilic acid, kynurenine and quinolinic acid), and more strongly so than for other markers of inflammation, including CRP. CONCLUSIONS: In middle-aged and older adults, plasma concentrations of kynurenine metabolites are strongly associated with adiposity, both cross-sectionally and longitudinally. Our study demonstrates that kynurenine metabolites may be valuable markers to monitor the adverse consequences of obesity.