Browsing by Author "Gallinger, Steven J."

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    Association of Body Mass Index With Colorectal Cancer Risk by Genome-Wide Variants
    (Oxford University Press, 2021) Campbell, Peter T.; Lin, Yi; Bien, Stephanie A.; Figueiredo, Jane C.; Harrison, Tabitha A.; Guinter, Mark A.; Berndt, Sonja I.; Brenner, Hermann; Chan, Andrew T.; Chang-Claude, Jenny; Gallinger, Steven J.; Gapstur, Susan M.; Giles, Graham G.; Giovannucci, Edward; Gruber, Stephen B.; Gunter, Marc; Hoffmeister, Michael; Jacobs, Eric J.; Jenkins, Mark A.; Marchand, Loic Le; Li, Li; McLaughlin, John R.; Murphy, Neil; Milne, Roger L.; Newcomb, Polly A.; Newton, Christina; Ogino, Shuji; Potter, John D.; Rennert, Gad; Rennert, Hedy S.; Robinson, Jennifer; Sakoda, Lori C.; Slattery, Martha L.; Song, Yiqing; White, Emily; Woods, Michael O.; Casey, Graham; Hsu, Li; Peters, Ulrike; Epidemiology, School of Public Health
    Background: Body mass index (BMI) is a complex phenotype that may interact with genetic variants to influence colorectal cancer risk. Methods: We tested multiplicative statistical interactions between BMI (per 5 kg/m2) and approximately 2.7 million single nucleotide polymorphisms with colorectal cancer risk among 14 059 colorectal cancer case (53.2% women) and 14 416 control (53.8% women) participants. All analyses were stratified by sex a priori. Statistical methods included 2-step (ie, Cocktail method) and single-step (ie, case-control logistic regression and a joint 2-degree of freedom test) procedures. All statistical tests were two-sided. Results: Each 5 kg/m2 increase in BMI was associated with higher risks of colorectal cancer, less so for women (odds ratio [OR] = 1.14, 95% confidence intervals [CI] = 1.11 to 1.18; P = 9.75 × 10-17) than for men (OR = 1.26, 95% CI = 1.20 to 1.32; P = 2.13 × 10-24). The 2-step Cocktail method identified an interaction for women, but not men, between BMI and a SMAD7 intronic variant at 18q21.1 (rs4939827; Pobserved = .0009; Pthreshold = .005). A joint 2-degree of freedom test was consistent with this finding for women (joint P = 2.43 × 10-10). Each 5 kg/m2 increase in BMI was more strongly associated with colorectal cancer risk for women with the rs4939827-CC genotype (OR = 1.24, 95% CI = 1.16 to 1.32; P = 2.60 × 10-10) than for women with the CT (OR = 1.14, 95% CI = 1.09 to 1.19; P = 1.04 × 10-8) or TT (OR = 1.07, 95% CI = 1.01 to 1.14; P = .02) genotypes. Conclusion: These results provide novel insights on a potential mechanism through which a SMAD7 variant, previously identified as a susceptibility locus for colorectal cancer, and BMI may influence colorectal cancer risk for women.
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    Exploratory genome-wide interaction analysis of non-steroidal anti-inflammatory drugs and predicted gene expression on colorectal cancer risk
    (American Association for Cancer Research, 2020-09) Wang, Xiaoliang; Su, Yu-Ru; Petersen, Paneen S.; Bien, Stephanie; Schmit, Stephanie L.; Drew, David A.; Albanes, Demetrius; Berndt, Sonja I.; Brenner, Hermann; Campbell, Peter T.; Casey, Graham; Chang-Claude, Jenny; Gallinger, Steven J.; Gruber, Stephen B.; Haile, Robert W.; Harrison, Tabitha A.; Hoffmeister, Michael; Jacobs, Eric J.; Jenkins, Mark A.; Joshi, Amit D.; Li, Li; Lin, Yi; Lindor, Noralane M.; Le Marchand, Loïc; Martin, Vicente; Milne, Roger; Maclnnis, Robert; Moreno, Victor; Nan, Hongmei; Newcomb, Polly A.; Potter, John D.; Rennert, Gad; Rennert, Hedy; Slattery, Martha L.; Thibodeau, Steve N.; Weinstein, Stephanie J.; Woods, Michael O.; Chan, Andrew T.; White, Emily; Hsu, Li; Peters, Ulrike; Global Health, School of Public Health
    Background: Regular use of nonsteroidal anti-inflammatory drugs (NSAID) is associated with lower risk of colorectal cancer. Genome-wide interaction analysis on single variants (G × E) has identified several SNPs that may interact with NSAIDs to confer colorectal cancer risk, but variations in gene expression levels may also modify the effect of NSAID use. Therefore, we tested interactions between NSAID use and predicted gene expression levels in relation to colorectal cancer risk. Methods: Genetically predicted gene expressions were tested for interaction with NSAID use on colorectal cancer risk among 19,258 colorectal cancer cases and 18,597 controls from 21 observational studies. A Mixed Score Test for Interactions (MiSTi) approach was used to jointly assess G × E effects which are modeled via fixed interaction effects of the weighted burden within each gene set (burden) and residual G × E effects (variance). A false discovery rate (FDR) at 0.2 was applied to correct for multiple testing. Results: Among the 4,840 genes tested, genetically predicted expression levels of four genes modified the effect of any NSAID use on colorectal cancer risk, including DPP10 (PG×E = 1.96 × 10-4), KRT16 (PG×E = 2.3 × 10-4), CD14 (PG×E = 9.38 × 10-4), and CYP27A1 (PG×E = 1.44 × 10-3). There was a significant interaction between expression level of RP11-89N17 and regular use of aspirin only on colorectal cancer risk (PG×E = 3.23 × 10-5). No interactions were observed between predicted gene expression and nonaspirin NSAID use at FDR < 0.2. Conclusions: By incorporating functional information, we discovered several novel genes that interacted with NSAID use.
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    Genetically predicted circulating concentrations of micronutrients and risk of colorectal cancer among individuals of European descent: a Mendelian randomization study
    (Elsevier, 2021) Tsilidis, Konstantinos K.; Papadimitriou, Nikos; Dimou, Niki; Gill, Dipender; Lewis, Sarah J.; Martin, Richard M.; Murphy, Neil; Markozannes, Georgios; Zuber, Verena; Cross, Amanda J.; Burrows, Kimberley; Lopez, David S.; Key, Timothy J.; Travis, Ruth C.; Perez-Cornago, Aurora; Hunter, David J.; van Duijnhoven, Fränzel J. B.; Albanes, Demetrius; Arndt, Volker; Berndt, Sonja I.; Bézieau, Stéphane; Bishop, D. Timothy; Boehm, Juergen; Brenner, Hermann; Burnett-Hartman, Andrea; Campbell, Peter T.; Casey, Graham; Castellví-Bel, Sergi; Chan, Andrew T.; Chang-Claude, Jenny; de la Chapelle, Albert; Figueiredo, Jane C.; Gallinger, Steven J.; Giles, Graham G.; Goodman, Phyllis J.; Gsur, Andrea; Hampe, Jochen; Hampel, Heather; Hoffmeister, Michael; Jenkins, Mark A.; Keku, Temitope O.; Kweon, Sun-Seog; Larsson, Susanna C.; Le Marchand, Loic; Li, Christopher I.; Li, Li; Lindblom, Annika; Martín, Vicente; Milne, Roger L.; Moreno, Victor; Nan, Hongmei; Nassir, Rami; Newcomb, Polly A.; Offit, Kenneth; Pharoah, Paul D. P.; Platz, Elizabeth A.; Potter, John D.; Qi, Lihong; Rennert, Gad; Sakoda, Lori C.; Schafmayer, Clemens; Slattery, Martha L.; Snetselaar, Linda; Schenk, Jeanette; Thibodeau, Stephen N.; Ulrich, Cornelia M.; Van Guelpen, Bethany; Harlid, Sophia; Visvanathan, Kala; Vodickova, Ludmila; Wang, Hansong; White, Emily; Wolk, Alicja; Woods, Michael O.; Wu, Anna H.; Zheng, Wei; Bueno-de-Mesquita, Bas; Boutron-Ruault, Marie-Christine; Hughes, David J.; Jakszyn, Paula; Kühn, Tilman; Palli, Domenico; Riboli, Elio; Giovannucci, Edward L.; Banbury, Barbara L.; Gruber, Stephen B.; Peters, Ulrike; Gunter, Marc J.; Epidemiology, School of Public Health
    Background: The literature on associations of circulating concentrations of minerals and vitamins with risk of colorectal cancer is limited and inconsistent. Evidence from randomized controlled trials (RCTs) to support the efficacy of dietary modification or nutrient supplementation for colorectal cancer prevention is also limited. Objectives: To complement observational and RCT findings, we investigated associations of genetically predicted concentrations of 11 micronutrients (β-carotene, calcium, copper, folate, iron, magnesium, phosphorus, selenium, vitamin B-6, vitamin B-12, and zinc) with colorectal cancer risk using Mendelian randomization (MR). Methods: Two-sample MR was conducted using 58,221 individuals with colorectal cancer and 67,694 controls from the Genetics and Epidemiology of Colorectal Cancer Consortium, Colorectal Cancer Transdisciplinary Study, and Colon Cancer Family Registry. Inverse variance-weighted MR analyses were performed with sensitivity analyses to assess the impact of potential violations of MR assumptions. Results: Nominally significant associations were noted for genetically predicted iron concentration and higher risk of colon cancer [ORs per SD (ORSD): 1.08; 95% CI: 1.00, 1.17; P value = 0.05] and similarly for proximal colon cancer, and for vitamin B-12 concentration and higher risk of colorectal cancer (ORSD: 1.12; 95% CI: 1.03, 1.21; P value = 0.01) and similarly for colon cancer. A nominally significant association was also noted for genetically predicted selenium concentration and lower risk of colon cancer (ORSD: 0.98; 95% CI: 0.96, 1.00; P value = 0.05) and similarly for distal colon cancer. These associations were robust to sensitivity analyses. Nominally significant inverse associations were observed for zinc and risk of colorectal and distal colon cancers, but sensitivity analyses could not be performed. None of these findings survived correction for multiple testing. Genetically predicted concentrations of β-carotene, calcium, copper, folate, magnesium, phosphorus, and vitamin B-6 were not associated with disease risk. Conclusions: These results suggest possible causal associations of circulating iron and vitamin B-12 (positively) and selenium (inversely) with risk of colon cancer.
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    Interactions between folate intake and genetic predictors of gene expression levels associated with colorectal cancer risk
    (Springer, 2022-11-07) Haas, Cameron B.; Su, Yu-Ru; Petersen, Paneen; Wang, Xiaoliang; Bien, Stephanie A.; Lin, Yi; Albanes, Demetrius; Weinstein, Stephanie J.; Jenkins, Mark A.; Figueiredo, Jane C.; Newcomb, Polly A.; Casey, Graham; Marchand, Loic Le; Campbell, Peter T.; Moreno, Victor; Potter, John D.; Sakoda, Lori C.; Slattery, Martha L.; Chan, Andrew T.; Li, Li; Giles, Graham G.; Milne, Roger L.; Gruber, Stephen B.; Rennert, Gad; Woods, Michael O.; Gallinger, Steven J.; Berndt, Sonja; Hayes, Richard B.; Huang, Wen-Yi; Wolk, Alicja; White, Emily; Nan, Hongmei; Nassir, Rami; Lindor, Noralane M.; Lewinger, Juan P.; Kim, Andre E.; Conti, David; Gauderman, W. James; Buchanan, Daniel D.; Peters, Ulrike; Hsu , Li; Epidemiology, Richard M. Fairbanks School of Public Health
    Observational studies have shown higher folate consumption to be associated with lower risk of colorectal cancer (CRC). Understanding whether and how genetic risk factors interact with folate could further elucidate the underlying mechanism. Aggregating functionally relevant genetic variants in set-based variant testing has higher power to detect gene-environment (G × E) interactions and may provide information on the underlying biological pathway. We investigated interactions between folate consumption and predicted gene expression on colorectal cancer risk across the genome. We used variant weights from the PrediXcan models of colon tissue-specific gene expression as a priori variant information for a set-based G × E approach. We harmonized total folate intake (mcg/day) based on dietary intake and supplemental use across cohort and case-control studies and calculated sex and study specific quantiles. Analyses were performed using a mixed effects score tests for interactions between folate and genetically predicted expression of 4839 genes with available genetically predicted expression. We pooled results across 23 studies for a total of 13,498 cases with colorectal tumors and 13,918 controls of European ancestry. We used a false discovery rate of 0.2 to identify genes with suggestive evidence of an interaction. We found suggestive evidence of interaction with folate intake on CRC risk for genes including glutathione S-Transferase Alpha 1 (GSTA1; p = 4.3E-4), Tonsuko Like, DNA Repair Protein (TONSL; p = 4.3E-4), and Aspartylglucosaminidase (AGA: p = 4.5E-4). We identified three genes involved in preventing or repairing DNA damage that may interact with folate consumption to alter CRC risk. Glutathione is an antioxidant, preventing cellular damage and is a downstream metabolite of homocysteine and metabolized by GSTA1. TONSL is part of a complex that functions in the recovery of double strand breaks and AGA plays a role in lysosomal breakdown of glycoprotein.