Browsing by Author "Jacobs, Eric 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.