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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    A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk
    Aglago, EK ; Kim, A ; Lin, Y ; Qu, C ; Evangelou, M ; Ren, Y ; Morrison, J ; Albanes, D ; Arndt, V ; Barry, EL ; Baurley, JW ; Berndt, S ; Bien, SA ; Bishop, DT ; Bouras, E ; Brenner, H ; Buchanan, DD ; Budiarto, A ; Carreras-Torres, R ; Casey, G ; Cenggoro, TW ; Chen, AT ; Chang-Claude, J ; Chen, X ; Conti, D ; Devall, M ; Diez-Obrero, V ; Dimou, N ; Drew, D ; Figueiredo, JC ; Gallinger, S ; Giles, GG ; Gruber, SB ; Gsur, A ; Gunter, MJ ; Hampel, H ; Harlid, S ; Hidaka, A ; Harrison, TA ; Hoffmeister, M ; Huyghe, JR ; Jenkins, MA ; Jordahl, K ; Joshi, AD ; Kawaguchi, ES ; Keku, TO ; Kundaje, A ; Larsson, SC ; Le Marchand, L ; Lewinger, JP ; Li, L ; Lynch, BM ; Mahesworo, B ; Mandic, M ; Obon-Santacana, M ; Morento, V ; Murphy, N ; Men, H ; Nassir, R ; Newcomb, PA ; Ogino, S ; Ose, J ; Pai, RK ; Palmer, JR ; Papadimitriou, N ; Pardamean, B ; Peoples, AR ; Platz, EA ; Potter, JD ; Prentice, RL ; Rennert, G ; Ruiz-Narvaez, E ; Sakoda, LC ; Scacheri, PC ; Schmit, SL ; Schoen, RE ; Shcherbina, A ; Slattery, ML ; Stern, MC ; Su, Y-R ; Tangen, CM ; Thibodeau, SN ; Thomas, DC ; Tian, Y ; Ulrich, CM ; van Duijnhoven, FJB ; Van Guelpen, B ; Visvanathan, K ; Vodicka, P ; Wang, J ; White, E ; Wolk, A ; Woods, MO ; Wu, AH ; Zemlianskaia, N ; Hsu, L ; Gauderman, WJ ; Peters, U ; Tsilidis, KK ; Campbell, PT (AMER ASSOC CANCER RESEARCH, 2023-08-01)
    UNLABELLED: Colorectal cancer risk can be impacted by genetic, environmental, and lifestyle factors, including diet and obesity. Gene-environment interactions (G × E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G × E interactions between body mass index (BMI) and common SNPs for colorectal cancer risk using data from 36,415 colorectal cancer cases and 48,451 controls from three international colorectal cancer consortia (CCFR, CORECT, and GECCO). The G × E tests included the conventional logistic regression using multiplicative terms (one degree of freedom, 1DF test), the two-step EDGE method, and the joint 3DF test, each of which is powerful for detecting G × E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant G×BMI interaction located within the Formin 1/Gremlin 1 (FMN1/GREM1) gene region (rs58349661). This SNP was also identified by the 3DF test, with a suggestive statistical significance in the 1DF test. Among participants with the CC genotype of rs58349661, overweight and obesity categories were associated with higher colorectal cancer risk, whereas null associations were observed across BMI categories in those with the TT genotype. Using data from three large international consortia, this study discovered a locus in the FMN1/GREM1 gene region that interacts with BMI on the association with colorectal cancer risk. Further studies should examine the potential mechanisms through which this locus modifies the etiologic link between obesity and colorectal cancer. SIGNIFICANCE: This gene-environment interaction analysis revealed a genetic locus in FMN1/GREM1 that interacts with body mass index in colorectal cancer risk, suggesting potential implications for precision prevention strategies.
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    A likelihood ratio approach for utilizing case-control data in the clinical classification of rare sequence variants: Application to BRCA1 and BRCA2
    Zanti, M ; O'Mahony, DG ; Parsons, MT ; Li, H ; Dennis, J ; Aittomäkkiki, K ; Andrulis, IL ; Anton-Culver, H ; Aronson, KJ ; Augustinsson, A ; Becher, H ; Bojesen, SE ; Bolla, MK ; Brenner, H ; Brown, MA ; Buys, SS ; Canzian, F ; Caputo, SM ; Castelao, JE ; Chang-Claude, J ; Czene, K ; Daly, MB ; De Nicolo, A ; Devilee, P ; Dörk, T ; Dunning, AM ; Dwek, M ; Eccles, DM ; Engel, C ; Gareth Evans, D ; Fasching, PA ; Gago-Dominguez, M ; García-Closas, M ; García-Sáenz, JA ; Gentry-Maharaj, A ; Geurts-Giele, WRR ; Giles, GG ; Glendon, G ; Goldberg, MS ; Gómez Garcia, EB ; Göendert, M ; Guénel, P ; Hahnen, E ; Haiman, CA ; Hall, P ; Hamann, U ; Harkness, EF ; Hogervorst, FBL ; Hollestelle, A ; Hoppe, R ; Hopper, JL ; Houdayer, C ; Houlston, RS ; Howell, A ; Jakimovska, M ; Jakubowska, A ; Jernström, H ; John, EM ; Kaaks, R ; Kitahara, CM ; Koutros, S ; Kraft, P ; Kristensen, VN ; Lacey, JV ; Lambrechts, D ; Léoné, M ; Lindblom, A ; Lubiski, J ; Lush, M ; Mannermaa, A ; Manoochehri, M ; Manoukian, S ; Margolin, S ; Martinez, ME ; Menon, U ; Milne, RL ; Monteiro, AN ; Murphy, RA ; Neuhausen, SL ; Nevanlinna, H ; Newman, WG ; Offit, K ; Park, SK ; James, P ; Peterlongo, P ; Peto, J ; Plaseska-Karanfilska, D ; Punie, K ; Radice, P ; Rashid, MU ; Rennert, G ; Romero, A ; Rosenberg, EH ; Saloustros, E ; Sandler, DP ; Schmidt, MK ; Schmutzler, RK ; Shu, XO ; Simard, J ; Southey, MC ; Cutting, G (Hindawi Limited, 2023-01-01)
    A large number of variants identified through clinical genetic testing in disease susceptibility genes are of uncertain significance (VUS). Following the recommendations of the American College of Medical Genetics and Genomics (ACMG) and Association for Molecular Pathology (AMP), the frequency in case-control datasets (PS4 criterion) can inform their interpretation. We present a novel case-control likelihood ratio-based method that incorporates gene-specific age-related penetrance. We demonstrate the utility of this method in the analysis of simulated and real datasets. In the analysis of simulated data, the likelihood ratio method was more powerful compared to other methods. Likelihood ratios were calculated for a case-control dataset of BRCA1 and BRCA2 variants from the Breast Cancer Association Consortium (BCAC) and compared with logistic regression results. A larger number of variants reached evidence in favor of pathogenicity, and a substantial number of variants had evidence against pathogenicity—findings that would not have been reached using other case-control analysis methods. Our novel method provides greater power to classify rare variants compared with classical case-control methods. As an initiative from the ENIGMA Analytical Working Group, we provide user-friendly scripts and preformatted Excel calculators for implementation of the method for rare variants in BRCA1, BRCA2, and other high-risk genes with known penetrance.
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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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    Elucidating the Risk of Colorectal Cancer for Variants in Hereditary Colorectal Cancer Genes
    Mahmood, K ; Thomas, M ; Qu, C ; Hsu, L ; Buchanan, DD ; Peters, U (W B SAUNDERS CO-ELSEVIER INC, 2023-10)
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    Probing the diabetes and colorectal cancer relationship using gene - environment interaction analyses
    Dimou, N ; Kim, AE ; Flanagan, O ; Murphy, N ; Diez-Obrero, V ; Shcherbina, A ; Aglago, EK ; Bouras, E ; Campbell, PT ; Casey, G ; Gallinger, S ; Gruber, SB ; Jenkins, MA ; Lin, Y ; Moreno, V ; Ruiz-Narvaez, E ; Stern, MC ; Tian, Y ; Tsilidis, KK ; Arndt, V ; Barry, EL ; Baurley, JW ; Berndt, SI ; Bezieau, S ; Bien, SA ; Bishop, DT ; Brenner, H ; Budiarto, A ; Carreras-Torres, R ; Cenggoro, TW ; Chan, AT ; Chang-Claude, J ; Chanock, SJ ; Chen, X ; Conti, DV ; Dampier, CH ; Devall, M ; Drew, DA ; Figueiredo, JC ; Giles, GG ; Gsur, A ; Harrison, TA ; Hidaka, A ; Hoffmeister, M ; Huyghe, JR ; Jordahl, K ; Kawaguchi, E ; Keku, TO ; Larsson, SC ; Le Marchand, L ; Lewinger, JP ; Li, L ; Mahesworo, B ; Morrison, J ; Newcomb, PA ; Newton, CC ; Obon-Santacana, M ; Ose, J ; Pai, RK ; Palmer, JR ; Papadimitriou, N ; Pardamean, B ; Peoples, AR ; Pharoah, PDP ; Platz, EA ; Potter, JD ; Rennert, G ; Scacheri, PC ; Schoen, RE ; Su, Y-R ; Tangen, CM ; Thibodeau, SN ; Thomas, DC ; Ulrich, CM ; Um, CY ; van Duijnhoven, FJB ; Visvanathan, K ; Vodicka, P ; Vodickova, L ; White, E ; Wolk, A ; Woods, MO ; Qu, C ; Kundaje, A ; Hsu, L ; Gauderman, WJ ; Gunter, MJ ; Peters, U (SPRINGERNATURE, 2023-08-24)
    BACKGROUND: Diabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis. METHODS: We used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test). RESULTS: Based on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 - ORAA: 1.62, 95% CI: 1.34-1.96; ORAG: 1.41, 95% CI: 1.30-1.54; ORGG: 1.22, 95% CI: 1.13-1.31; p-value3-d.f.: 5.46 × 10-11) and 13q14.13 (rs9526201, LRCH1 - ORGG: 2.11, 95% CI: 1.56-2.83; ORGA: 1.52, 95% CI: 1.38-1.68; ORAA: 1.13, 95% CI: 1.06-1.21; p-value2-d.f.: 7.84 × 10-09). DISCUSSION: These results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship.
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    Trajectories of body mass index from early adulthood to late midlife and incidence of total knee arthroplasty for osteoarthritis: findings from a prospective cohort study
    Hussain, SM ; Ackerman, IN ; Wang, Y ; English, DR ; Wluka, AE ; Giles, GG ; Cicuttini, FM (ELSEVIER SCI LTD, 2023-03)
    OBJECTIVE: To examine the association between body mass index (BMI) trajectories from early adulthood to late midlife and risk of total knee arthroplasty (TKA) for osteoarthritis. METHODS: 24,368 participants from the Melbourne Collaborative Cohort Study with weight collected during 1990-1994, 1995-1998, and 2003-2007, recalled weight at age 18-21 years, and height measured during 1990-1994 were included. Incident TKA from 2003 to 2007 to December 2018 was determined by linking cohort records to the National Joint Replacement Registry. RESULTS: Using group-based trajectory modelling, six distinct trajectories (TR) of BMI from early adulthood (age 18-21 years) to late midlife (approximately 62 years) were identified: lower normal to normal BMI (TR1; 19.7% population), normal BMI to borderline overweight (TR2; 36.7%), normal BMI to overweight (TR3; 26.8%), overweight to borderline obese (TR4; 3.5%), normal BMI to class 1 obesity (TR5; 10.1%), overweight to class 2 obesity (TR6; 3.2%). Over 12.4 years, 1,328 (5.4%) had TKA. The hazard ratios for TKA increased in all TR compared to TR1 [from TR2: 2.03 (95% CI 1.64-2.52) to TR6: 8.59 (6.44-11.46)]. 28.4% of TKA could be prevented if individuals followed the trajectory one lower, an average weight reduction of 8-12 kg from early adulthood to late midlife, saving $AUS 373 million/year. Most reduction would occur in TR2 (population attributable fraction 37.9%, 95% CI 26.7-47.3%) and TR3 (26.8%, 20.0-31.2%). CONCLUSIONS: Prevention of weight gain from young adulthood to late midlife in order to reduce overweight/obesity has the potential to significantly reduce the cost and burden of TKA.
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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.