Browsing by Author "Lindor, Noralane M."

Now showing 1 - 2 of 2
  • Thumbnail Image
    Item
    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.
  • Thumbnail Image
    Item
    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.