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    Genetic risk impacts the association of menopausal hormone therapy with colorectal cancer risk
    Tian, Y ; Lin, Y ; Qu, C ; Arndt, V ; Baurley, JW ; Berndt, SI ; Bien, SA ; Bishop, DT ; Brenner, H ; Buchanan, DD ; Budiarto, A ; Campbell, PT ; Carreras-Torres, R ; Casey, G ; Chan, AT ; Chen, R ; Chen, X ; Conti, DV ; Diez-Obrero, V ; Dimou, N ; Drew, DA ; Figueiredo, JC ; Gallinger, S ; Giles, GG ; Gruber, SB ; Gunter, MJ ; Harlid, S ; Harrison, TA ; Hidaka, A ; Hoffmeister, M ; Huyghe, JR ; Jenkins, MA ; Jordahl, KM ; Joshi, AD ; Keku, TO ; Kawaguchi, E ; Kim, AE ; Kundaje, A ; Larsson, SC ; Marchand, LL ; Lewinger, JP ; Li, L ; Moreno, V ; Morrison, J ; Murphy, N ; Nan, H ; Nassir, R ; Newcomb, PA ; Obon-Santacana, M ; Ogino, S ; Ose, J ; Pardamean, B ; Pellatt, AJ ; Peoples, AR ; Platz, EA ; Potter, JD ; Prentice, RL ; Rennert, G ; Ruiz-Narvaez, EA ; Sakoda, LC ; Schoen, RE ; Shcherbina, A ; Stern, MC ; Su, Y-R ; Thibodeau, SN ; Thomas, DC ; Tsilidis, KK ; van Duijnhoven, FJB ; Van Guelpen, B ; Visvanathan, K ; White, E ; Wolk, A ; Woods, MO ; Wu, AH ; Peters, U ; Gauderman, WJ ; Hsu, L ; Chang-Claude, J (SPRINGERNATURE, 2024-06-01)
    BACKGROUND: Menopausal hormone therapy (MHT), a common treatment to relieve symptoms of menopause, is associated with a lower risk of colorectal cancer (CRC). To inform CRC risk prediction and MHT risk-benefit assessment, we aimed to evaluate the joint association of a polygenic risk score (PRS) for CRC and MHT on CRC risk. METHODS: We used data from 28,486 postmenopausal women (11,519 cases and 16,967 controls) of European descent. A PRS based on 141 CRC-associated genetic variants was modeled as a categorical variable in quartiles. Multiplicative interaction between PRS and MHT use was evaluated using logistic regression. Additive interaction was measured using the relative excess risk due to interaction (RERI). 30-year cumulative risks of CRC for 50-year-old women according to MHT use and PRS were calculated. RESULTS: The reduction in odds ratios by MHT use was larger in women within the highest quartile of PRS compared to that in women within the lowest quartile of PRS (p-value = 2.7 × 10-8). At the highest quartile of PRS, the 30-year CRC risk was statistically significantly lower for women taking any MHT than for women not taking any MHT, 3.7% (3.3%-4.0%) vs 6.1% (5.7%-6.5%) (difference 2.4%, P-value = 1.83 × 10-14); these differences were also statistically significant but smaller in magnitude in the lowest PRS quartile, 1.6% (1.4%-1.8%) vs 2.2% (1.9%-2.4%) (difference 0.6%, P-value = 1.01 × 10-3), indicating 4 times greater reduction in absolute risk associated with any MHT use in the highest compared to the lowest quartile of genetic CRC risk. CONCLUSIONS: MHT use has a greater impact on the reduction of CRC risk for women at higher genetic risk. These findings have implications for the development of risk prediction models for CRC and potentially for the consideration of genetic information in the risk-benefit assessment of MHT use.
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    Breast and bowel cancers diagnosed in people 'too young to have cancer': A blueprint for research using family and twin studies
    Hopper, JL ; Li, S ; MacInnis, RJ ; Dowty, JG ; Nguyen, TL ; Bui, M ; Dite, GS ; Esser, VFC ; Ye, Z ; Makalic, E ; Schmidt, DF ; Goudey, B ; Alpen, K ; Kapuscinski, M ; Win, AK ; Dugue, P-A ; Milne, RL ; Jayasekara, H ; Brooks, JD ; Malta, S ; Calais-Ferreira, L ; Campbell, AC ; Young, JT ; Nguyen-Dumont, T ; Sung, J ; Giles, GG ; Buchanan, D ; Winship, I ; Terry, MB ; Southey, MC ; Jenkins, MA (WILEY, 2024-03-19)
    Young breast and bowel cancers (e.g., those diagnosed before age 40 or 50 years) have far greater morbidity and mortality in terms of years of life lost, and are increasing in incidence, but have been less studied. For breast and bowel cancers, the familial relative risks, and therefore the familial variances in age-specific log(incidence), are much greater at younger ages, but little of these familial variances has been explained. Studies of families and twins can address questions not easily answered by studies of unrelated individuals alone. We describe existing and emerging family and twin data that can provide special opportunities for discovery. We present designs and statistical analyses, including novel ideas such as the VALID (Variance in Age-specific Log Incidence Decomposition) model for causes of variation in risk, the DEPTH (DEPendency of association on the number of Top Hits) and other approaches to analyse genome-wide association study data, and the within-pair, ICE FALCON (Inference about Causation from Examining FAmiliaL CONfounding) and ICE CRISTAL (Inference about Causation from Examining Changes in Regression coefficients and Innovative STatistical AnaLysis) approaches to causation and familial confounding. Example applications to breast and colorectal cancer are presented. Motivated by the availability of the resources of the Breast and Colon Cancer Family Registries, we also present some ideas for future studies that could be applied to, and compared with, cancers diagnosed at older ages and address the challenges posed by young breast and bowel cancers.
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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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    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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    Validation of a Genetic-Enhanced Risk Prediction Model for Colorectal Cancer in a Large Community-Based Cohort.
    Su, Y-R ; Sakoda, LC ; Jeon, J ; Thomas, M ; Lin, Y ; Schneider, JL ; Udaltsova, N ; Lee, JK ; Lansdorp-Vogelaar, I ; Peterse, EFP ; Zauber, AG ; Zheng, J ; Zheng, Y ; Hauser, E ; Baron, JA ; Barry, EL ; Bishop, DT ; Brenner, H ; Buchanan, DD ; Burnett-Hartman, A ; Campbell, PT ; Casey, G ; Castellví-Bel, S ; Chan, AT ; Chang-Claude, J ; Figueiredo, JC ; Gallinger, SJ ; Giles, GG ; Gruber, SB ; Gsur, A ; Gunter, MJ ; Hampe, J ; Hampel, H ; Harrison, TA ; Hoffmeister, M ; Hua, X ; Huyghe, JR ; Jenkins, MA ; Keku, TO ; Marchand, LL ; Li, L ; Lindblom, A ; Moreno, V ; Newcomb, PA ; Pharoah, PDP ; Platz, EA ; Potter, JD ; Qu, C ; Rennert, G ; Schoen, RE ; Slattery, ML ; Song, M ; van Duijnhoven, FJB ; Van Guelpen, B ; Vodicka, P ; Wolk, A ; Woods, MO ; Wu, AH ; Hayes, RB ; Peters, U ; Corley, DA ; Hsu, L (American Association for Cancer Research (AACR), 2023-03-06)
    BACKGROUND: Polygenic risk scores (PRS) which summarize individuals' genetic risk profile may enhance targeted colorectal cancer screening. A critical step towards clinical implementation is rigorous external validations in large community-based cohorts. This study externally validated a PRS-enhanced colorectal cancer risk model comprising 140 known colorectal cancer loci to provide a comprehensive assessment on prediction performance. METHODS: The model was developed using 20,338 individuals and externally validated in a community-based cohort (n = 85,221). We validated predicted 5-year absolute colorectal cancer risk, including calibration using expected-to-observed case ratios (E/O) and calibration plots, and discriminatory accuracy using time-dependent AUC. The PRS-related improvement in AUC, sensitivity and specificity were assessed in individuals of age 45 to 74 years (screening-eligible age group) and 40 to 49 years with no endoscopy history (younger-age group). RESULTS: In European-ancestral individuals, the predicted 5-year risk calibrated well [E/O = 1.01; 95% confidence interval (CI), 0.91-1.13] and had high discriminatory accuracy (AUC = 0.73; 95% CI, 0.71-0.76). Adding the PRS to a model with age, sex, family and endoscopy history improved the 5-year AUC by 0.06 (P < 0.001) and 0.14 (P = 0.05) in the screening-eligible age and younger-age groups, respectively. Using a risk-threshold of 5-year SEER colorectal cancer incidence rate at age 50 years, adding the PRS had a similar sensitivity but improved the specificity by 11% (P < 0.001) in the screening-eligible age group. In the younger-age group it improved the sensitivity by 27% (P = 0.04) with similar specificity. CONCLUSIONS: The proposed PRS-enhanced model provides a well-calibrated 5-year colorectal cancer risk prediction and improves discriminatory accuracy in the external cohort. IMPACT: The proposed model has potential utility in risk-stratified colorectal cancer prevention.
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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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    Genome-Wide Interaction Analysis of Genetic Variants With Menopausal Hormone Therapy for Colorectal Cancer Risk
    Tian, Y ; Kim, AE ; Bien, SA ; Lin, Y ; Qu, C ; Harrison, TA ; Carreras-Torres, R ; Diez-Obrero, V ; Dimou, N ; Drew, DA ; Hidaka, A ; Huyghe, JR ; Jordahl, KM ; Morrison, J ; Murphy, N ; Obon-Santacana, M ; Ulrich, CM ; Ose, J ; Peoples, AR ; Ruiz-Narvaez, EA ; Shcherbina, A ; Stern, MC ; Su, Y-R ; van Duijnhoven, FJB ; Arndt, V ; Baurley, JW ; Berndt, S ; Bishop, DT ; Brenner, H ; Buchanan, DD ; Chan, AT ; Figueiredo, JC ; Gallinger, S ; Gruber, SB ; Harlid, S ; Hoffmeister, M ; Jenkins, MA ; Joshi, AD ; Keku, TO ; Larsson, SC ; Le Marchand, L ; Li, L ; Giles, GG ; Milne, RL ; Nan, H ; Nassir, R ; Ogino, S ; Budiarto, A ; Platz, EA ; Potter, JD ; Prentice, RL ; Rennert, G ; Sakoda, LC ; Schoen, RE ; Slattery, ML ; Thibodeau, SN ; Van Guelpen, B ; Visvanathan, K ; White, E ; Wolk, A ; Woods, MO ; Wu, AH ; Campbell, PT ; Casey, G ; Conti, D ; Gunter, MJ ; Kundaje, A ; Lewinger, JP ; Moreno, V ; Newcomb, PA ; Pardamean, B ; Thomas, DC ; Tsilidis, KK ; Peters, U ; Gauderman, WJ ; Hsu, L ; Chang-Claude, J (OXFORD UNIV PRESS INC, 2022-08-08)
    BACKGROUND: The use of menopausal hormone therapy (MHT) may interact with genetic variants to influence colorectal cancer (CRC) risk. METHODS: We conducted a genome-wide, gene-environment interaction between single nucleotide polymorphisms and the use of any MHT, estrogen only, and combined estrogen-progestogen therapy with CRC risk, among 28 486 postmenopausal women (11 519 CRC patients and 16 967 participants without CRC) from 38 studies, using logistic regression, 2-step method, and 2- or 3-degree-of-freedom joint test. A set-based score test was applied for rare genetic variants. RESULTS: The use of any MHT, estrogen only and estrogen-progestogen were associated with a reduced CRC risk (odds ratio [OR] = 0.71, 95% confidence interval [CI] = 0.64 to 0.78; OR = 0.65, 95% CI = 0.53 to 0.79; and OR = 0.73, 95% CI = 0.59 to 0.90, respectively). The 2-step method identified a statistically significant interaction between a GRIN2B variant rs117868593 and MHT use, whereby MHT-associated CRC risk was statistically significantly reduced in women with the GG genotype (OR = 0.68, 95% CI = 0.64 to 0.72) but not within strata of GC or CC genotypes. A statistically significant interaction between a DCBLD1 intronic variant at 6q22.1 (rs10782186) and MHT use was identified by the 2-degree-of-freedom joint test. The MHT-associated CRC risk was reduced with increasing number of rs10782186-C alleles, showing odds ratios of 0.78 (95% CI = 0.70 to 0.87) for TT, 0.68 (95% CI = 0.63 to 0.73) for TC, and 0.66 (95% CI = 0.60 to 0.74) for CC genotypes. In addition, 5 genes in rare variant analysis showed suggestive interactions with MHT (2-sided P < 1.2 × 10-4). CONCLUSION: Genetic variants that modify the association between MHT and CRC risk were identified, offering new insights into pathways of CRC carcinogenesis and potential mechanisms involved.
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    Body mass index and molecular subtypes of colorectal cancer
    Murphy, N ; Newton, CC ; Song, M ; Papadimitriou, N ; Hoffmeister, M ; Phipps, A ; Harrison, TA ; Newcomb, PA ; Aglago, EK ; Berndt, S ; Brenner, H ; Buchanan, DD ; Cao, Y ; Chan, AT ; Chen, X ; Cheng, I ; Chang-Claude, J ; Dimou, N ; Drew, D ; Farris, AB ; French, AJ ; Gallinger, S ; Georgeson, P ; Giannakis, M ; Giles, GG ; Gruber, SB ; Harlid, S ; Hsu, L ; Huang, W-Y ; Jenkins, MA ; Laskar, RS ; Le Marchand, L ; Limburg, P ; Lin, Y ; Mandic, M ; Nowak, JA ; Obon-Santacana, M ; Ogino, S ; Qu, C ; Sakoda, LC ; Schoen, RE ; Southey, MC ; Stadler, ZK ; Steinfelder, RS ; Sun, W ; Thibodeau, SN ; Toland, AE ; Trinh, QM ; Tsilidis, KK ; Ugai, T ; Van Guelpen, B ; Wang, X ; Woods, MO ; Zaidi, SH ; Gunter, MJ ; Peters, U ; Campbell, PT (OXFORD UNIV PRESS INC, 2023-02)
    BACKGROUND: Obesity is an established risk factor for colorectal cancer (CRC), but the evidence for the association is inconsistent across molecular subtypes of the disease. METHODS: We pooled data on body mass index (BMI), tumor microsatellite instability status, CpG island methylator phenotype status, BRAF and KRAS mutations, and Jass classification types for 11 872 CRC cases and 11 013 controls from 11 observational studies. We used multinomial logistic regression to estimate odds ratios (OR) and 95% confidence intervals (CI) adjusted for covariables. RESULTS: Higher BMI was associated with increased CRC risk (OR per 5 kg/m2 = 1.18, 95% CI = 1.15 to 1.22). The positive association was stronger for men than women but similar across tumor subtypes defined by individual molecular markers. In analyses by Jass type, higher BMI was associated with elevated CRC risk for types 1-4 cases but not for type 5 CRC cases (considered familial-like/Lynch syndrome microsatellite instability-H, CpG island methylator phenotype-low or negative, BRAF-wild type, KRAS-wild type, OR = 1.04, 95% CI = 0.90 to 1.20). This pattern of associations for BMI and Jass types was consistent by sex and design of contributing studies (cohort or case-control). CONCLUSIONS: In contrast to previous reports with fewer study participants, we found limited evidence of heterogeneity for the association between BMI and CRC risk according to molecular subtype, suggesting that obesity influences nearly all major pathways involved in colorectal carcinogenesis. The null association observed for the Jass type 5 suggests that BMI is not a risk factor for the development of CRC for individuals with Lynch syndrome.