Citations

AbstractBackgroundBody mass index (BMI) and diabetes are established risk factors for colorectal cancer (CRC), likely through perturbations in metabolic traits (e.g. insulin resistance and glucose homeostasis). Identification of interactions between variation in genes and these metabolic risk factors may identify novel biologic insights into CRC etiology.MethodsTo improve statistical power and interpretation for gene‐environment interaction (G × E) testing, we tested genetic variants that regulate expression of a gene together for interaction with BMI (kg/m2) and diabetes on CRC risk among 26 017 cases and 20 692 controls. Each variant was weighted based on PrediXcan analysis of gene expression data from colon tissue generated in the Genotype‐Tissue Expression Project for all genes with heritability ≥1%. We used a mixed‐effects model to jointly measure the G × E interaction in a gene by partitioning the interactions into the predicted gene expression levels (fixed effects), and residual G × E effects (random effects). G × BMI analyses were stratified by sex as BMI‐CRC associations differ by sex. We used false discovery rates to account for multiple comparisons and reported all results with FDR <0.2.ResultsAmong 4839 genes tested, genetically predicted expressions of FOXA1 (P = 3.15 × 10−5), PSMC5 (P = 4.51 × 10−4) and CD33 (P = 2.71 × 10−4) modified the association of BMI on CRC risk for men; KIAA0753 (P = 2.29 × 10−5) and SCN1B (P = 2.76 × 10−4) modified the association of BMI on CRC risk for women; and PTPN2 modified the association between diabetes and CRC risk in both sexes (P = 2.31 × 10−5).ConclusionsAggregating G × E interactions and incorporating functional information, we discovered novel genes that may interact with BMI and diabetes on CRC risk.

Abstract Background: Results from epidemiologic studies examining polyunsaturated fatty acids (PUFA) and colorectal cancer risk are inconsistent. Mendelian randomization may strengthen causal inference from observational studies. Given their shared metabolic pathway, examining the combined effects of aspirin/NSAID use with PUFAs could help elucidate an association between PUFAs and colorectal cancer risk. Methods: Information was leveraged from genome-wide association studies (GWAS) regarding PUFA-associated SNPs to create weighted genetic scores (wGS) representing genetically predicted circulating blood PUFAs for 11,016 non-Hispanic white colorectal cancer cases and 13,732 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). Associations per SD increase in the wGS were estimated using unconditional logistic regression. Interactions between PUFA wGSs and aspirin/NSAID use on colorectal cancer risk were also examined. Results: Modest colorectal cancer risk reductions were observed per SD increase in circulating linoleic acid [ORLA = 0.96; 95% confidence interval (CI) = 0.93–0.98; P = 5.2 × 10−4] and α-linolenic acid (ORALA = 0.95; 95% CI = 0.92–0.97; P = 5.4 × 10−5), whereas modest increased risks were observed for arachidonic (ORAA = 1.06; 95% CI = 1.03–1.08; P = 3.3 × 10−5), eicosapentaenoic (OREPA = 1.04; 95% CI = 1.01–1.07; P = 2.5 × 10−3), and docosapentaenoic acids (ORDPA = 1.03; 95% CI = 1.01–1.06; P = 1.2 × 10−2). Each of these effects was stronger among aspirin/NSAID nonusers in the stratified analyses. Conclusions: Our study suggests that higher circulating shorter-chain PUFAs (i.e., LA and ALA) were associated with reduced colorectal cancer risk, whereas longer-chain PUFAs (i.e., AA, EPA, and DPA) were associated with an increased colorectal cancer risk. Impact: The interaction of PUFAs with aspirin/NSAID use indicates a shared colorectal cancer inflammatory pathway. Future research should continue to improve PUFA genetic instruments to elucidate the independent effects of PUFAs on colorectal cancer.

Abstract Genome-wide association studies of colorectal cancer (CRC) have identified over 50 susceptibility loci. These variants represent only a small fraction of total heritability for CRC. Gene-environment (GxE) interaction studies may help identify novel loci and biological interactions that give insight to the pathogenesis of CRC. Previous genome-wide GxE studies with dietary factors have identified interactions between loci and processed meat consumption and alcohol; however, limited statistical power remains a primary concern. Set-based SNP testing has the potential to increase statistical power to detect GxE interactions by aggregating functionally relevant SNPs. In this large pooled analysis using 14 case-control and nested case-control studies, we incorporated functional information from the transcriptome prediction tool, PrediXcan, into a novel set-based approach for testing GxE interactions. We used variant weights from the PrediXcan models of tissue-specific gene expression in the transverse colon as a priori variant information for a set-based GxE approach. We restricted our analysis to variants in the PrediXcan transverse colon gene models (n = 4,842). This discovery phase included 10,360 CRC and advanced adenoma cases, and 11,183 controls of European ancestry from the Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO) and the Colon Cancer Family Registry. All 14 studies were analyzed together in a pooled data set using the Mixed Effects Score Tests for interactions. We tested for gene interactions with sex- and study- specific quartiles of dietary intake of red meat (servings/day), processed meat (servings/day), vegetables (servings/day), fruits (servings/day), and fiber (g/day). We detected two genes with suggestive interactions (false discovery rate (FDR) &lt; 0.2) with intake of red meat and risk of CRC: Superoxide Dismutase 2 (SOD2) and Ubiquitin Conjugating Enzyme E2 H (UBE2H). No interactions at FDR &lt; 0.2 were observed for processed meat, vegetables, fruits, or fiber. The SOD2 gene, which encodes an enzyme important in apoptotic signaling and clearing of reactive oxygen species, may regulate response to colonic exposure to heme iron or increased bile acid from high-fat content in red meat. UBE2H is part of the ubiquitin-proteasome system that has a role in Wnt signaling, which can be mediated by heme iron in red meat and is commonly found dysregulated in cancer. These findings highlight the efficacy of integrating functional information and set-based testing for novel discovery of genes interacting with known dietary risk factors of CRC. We plan to replicate these findings in additional studies. Citation Format: Paneen S. Petersen, Yu-Ru Su, Sonja I. Berndt, Stephanie A. Bien, Hermann Brenner, Graham Casey, Andrew T. Chan, Jenny Chang-Claude, Jane C. Figueiredo, Steven J. Gallinger, Robert W. Haile, Tabitha A. Harrison, Michael Hoffmeister, Mark A. Jenkins, Amit D. Joshi, Sébastien Küry, Loic Le Marchand, Yi Lin, Noralane M. Lindor, Polly A. Newcomb, John D. Potter, Robert Schoen, Martha L. Slattery, Stephen N. Thibodeau, Emily White, Li Hsu, Ulrike Peters, CCFR, GECCO. Interactions between genetic predictors of gene expression and dietary factors associated with risk of colorectal cancer [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 5268.

Abstract Background Regular use of aspirin and other non-steroidal anti-inflammatory drugs (NSAIDs) is associated with lower risk of colorectal cancer (CRC). Genome-wide interaction analysis (GxE) has identified a few variants that may modify the effects of NSAIDs on CRC risk. However, limited statistical power remains a concern. Restricting analyses by using functional genomic information to aggregate variants into biologically relevant sets can reduce the number of tests, thereby increasing statistical power. We tested the interactions between variant models of gene expression and NSAIDs use on CRC risk. Methods Functional weights of each variant were estimated using PrediXcan based on jointly measured transcriptomes and genomes data of transverse colon tissues from the Genotype-Tissue Expression (GTEx) Project for all genes with sufficient heritability (≥1%). A mixed-effects model was used to assess the GxE effects in a gene among 9,917 incident CRC cases and 10,533 controls from 17 (nested) case-control studies from the Colon Cancer Family Registry (CCFR) and Genetics and Epidemiology of Colorectal Cancer Consortium (GECCO). GxE analysis was done by modeling the interaction between predicted gene expression and NSAID use (fixed effects), and residual variant-specific GxE effects that are not accounted for (random effects). Regular user of aspirin and/or non-aspirin NSAIDs was compared to non-regular users. False discovery rate (FDR) was used to account for multiple comparison and FDR≤0.2 was considered genome-wide significant. Secondary analysis was performed on significant genes and duration of use among users. Results Regular use of aspirin was higher among controls (30.3%) compared to cases (24.3%). Among the 4,842 genes tested, SORD significantly modified the effect of regular use of aspirin on CRC risk (p-interaction = 1.45×10-5; FDR=0.07). The SORD gene encodes sorbitol dehydrogenase (SORD), which oxidizes sorbitol to fructose in the polyol pathway. Decreased SORD concentrations were previously observed to dramatically increase in colorectal adenoma cells when compared to normal mucosa cells, suggesting the involvement of dysregulated polyol metabolisms in colorectal tumorigenesis. However, the duration of aspirin use was not statistically significantly associated with SORD gene expression on CRC risk (p=0.149) among 5,560 aspirin users. No significant interactions were observed between genetically determined colon gene expression levels and any NSAID use or non-aspirin NSAID use at FDR&lt;0.2. Conclusions Incorporating functional information, we discovered a novel gene that may interact with aspirin use to confer CRC risk. These findings provide preliminary support for new biological insights that could help understand the chemopreventive mechanisms of aspirin on CRC. We aim to replicate these findings in additional studies. Citation Format: Xiaoliang Wang, Yu-Ru Su, Andrew T. Chan, Stephanie Bien, Sonja I. Bernt, Hermann Brenner, Graham Casey, Jenny Chang-Claude, Steven J. Gallinger, Robert W. Haile, Tabitha A. Harrison, Michael Hoffmeister, Mark A. Jenkins, Amit Joshi, Yi Lin, Noralane M. Lindor, Loic Le Marchand, Hongmei Nan, Polly A. Newcomb, John D. Potter, Martha L. Slattery, Steve N. Thibodeau, Emily White, Li Hsu, Ulrike Peters. Functionally informed genome-wide interaction analysis of nonsteroidal anti-inflammatory drugs on colorectal cancer risk [abstract]. In: Proceedings of the American Association for Cancer Research Annual Meeting 2018; 2018 Apr 14-18; Chicago, IL. Philadelphia (PA): AACR; Cancer Res 2018;78(13 Suppl):Abstract nr 2965.

Abstract Background Previous genome-wide association studies (GWAS) have identified 42 loci (P < 5 × 10−8) associated with risk of colorectal cancer (CRC). Expanded consortium efforts facilitating the discovery of additional susceptibility loci may capture unexplained familial risk. Methods We conducted a GWAS in European descent CRC cases and control subjects using a discovery–replication design, followed by examination of novel findings in a multiethnic sample (cumulative n = 163 315). In the discovery stage (36 948 case subjects/30 864 control subjects), we identified genetic variants with a minor allele frequency of 1% or greater associated with risk of CRC using logistic regression followed by a fixed-effects inverse variance weighted meta-analysis. All novel independent variants reaching genome-wide statistical significance (two-sided P < 5 × 10−8) were tested for replication in separate European ancestry samples (12 952 case subjects/48 383 control subjects). Next, we examined the generalizability of discovered variants in East Asians, African Americans, and Hispanics (12 085 case subjects/22 083 control subjects). Finally, we examined the contributions of novel risk variants to familial relative risk and examined the prediction capabilities of a polygenic risk score. All statistical tests were two-sided. Results The discovery GWAS identified 11 variants associated with CRC at P < 5 × 10−8, of which nine (at 4q22.2/5p15.33/5p13.1/6p21.31/6p12.1/10q11.23/12q24.21/16q24.1/20q13.13) independently replicated at a P value of less than .05. Multiethnic follow-up supported the generalizability of discovery findings. These results demonstrated a 14.7% increase in familial relative risk explained by common risk alleles from 10.3% (95% confidence interval [CI] = 7.9% to 13.7%; known variants) to 11.9% (95% CI = 9.2% to 15.5%; known and novel variants). A polygenic risk score identified 4.3% of the population at an odds ratio for developing CRC of at least 2.0. Conclusions This study provides insight into the architecture of common genetic variation contributing to CRC etiology and improves risk prediction for individualized screening.

Telomeres cap chromosome ends, protecting them from degradation, double‐strand breaks, and end‐to‐end fusions. Telomeres are maintained by telomerase, a reverse transcriptase encoded by TERT, and an RNA template encoded by TERC. Loci in the TERT and adjoining CLPTM1L region are associated with risk of multiple cancers. We therefore investigated associations between variants in 22 telomere structure and maintenance gene regions and colorectal, breast, prostate, ovarian, and lung cancer risk. We performed subset‐based meta‐analyses of 204,993 directly‐measured and imputed SNPs among 61,851 cancer cases and 74,457 controls of European descent. Independent associations for SNP minor alleles were identified using sequential conditional analysis (with gene‐level p value cutoffs ≤3.08 × 10−5). Of the thirteen independent SNPs observed to be associated with cancer risk, novel findings were observed for seven loci. Across the DCLRE1B region, rs974494 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Across the TERC region, rs75316749 was positively associated with colorectal, breast, ovarian, and lung cancers. Across the DCLRE1B region, rs974404 and rs12144215 were inversely associated with prostate and lung cancers, and colorectal, breast, and prostate cancers, respectively. Near POT1, rs116895242 was inversely associated with colorectal, ovarian, and lung cancers, and RTEL1 rs34978822 was inversely associated with prostate and lung cancers. The complex association patterns in telomere‐related genes across cancer types may provide insight into mechanisms through which telomere dysfunction in different tissues influences cancer risk.

Abstract Background: The CpG island methylator phenotype (CIMP) represents a subset of colorectal cancers characterized by widespread aberrant DNA hypermethylation at select CpG islands. The risk factors and environmental exposures contributing to etiologic heterogeneity between CIMP and non-CIMP tumors are not known. Methods: We measured the CIMP status of 3,119 primary population-based colorectal cancer tumors from the multinational Colon Cancer Family Registry. Etiologic heterogeneity was assessed by a case–case study comparing risk factor frequency of colorectal cancer cases with CIMP and non-CIMP tumors using logistic regression to estimate the case–case odds ratio (ccOR). Results: We found associations between tumor CIMP status and MSI-H (ccOR = 7.6), BRAF V600E mutation (ccOR = 59.8), proximal tumor site (ccOR = 9; all P &lt; 0.0001), female sex [ccOR = 1.8; 95% confidence interval (CI), 1.5–2.1], older age (ccOR = 4.0 comparing over 70 years vs. under 50; 95% CI, 3.0–5.5), and family history of CRC (ccOR = 0.6; 95% CI, 0.5–0.7). While use of NSAIDs varied by tumor CIMP status for both males and females (P = 0.0001 and P = 0.02, respectively), use of multivitamin or calcium supplements did not. Only for female colorectal cancer was CIMP status associated with increased pack-years of smoking (Ptrend &lt; 0.001) and body mass index (BMI; Ptrend = 0.03). Conclusions: The frequency of several colorectal cancer risk factors varied by CIMP status, and the associations of smoking and obesity with tumor subtype were evident only for females. Impact: Differences in the associations of a unique DNA methylation–based subgroup of colorectal cancer with important lifestyle and environmental exposures increase understanding of the molecular pathologic epidemiology of this heavily methylated subset of colorectal cancer. Cancer Epidemiol Biomarkers Prev; 24(3); 512–9. ©2015 AACR.

Abstract A recent genome-wide association study found that genetic variants on chromosomes 3, 6, 7, 10, 11, 19 and X were associated with prostate cancer risk. We evaluated the most significant single-nucleotide polymorphisms (SNP) in these loci using a worldwide consortium of 13 groups (PRACTICAL). Blood DNA from 7,370 prostate cancer cases and 5,742 male controls was analyzed by genotyping assays. Odds ratios (OR) associated with each genotype were estimated using unconditional logistic regression. Six of the seven SNPs showed clear evidence of association with prostate cancer (P = 0.0007-P = 10−17). For each of these six SNPs, the estimated per-allele OR was similar to those previously reported and ranged from 1.12 to 1.29. One SNP on 3p12 (rs2660753) showed a weaker association than previously reported [per-allele OR, 1.08 (95% confidence interval, 1.00-1.16; P = 0.06) versus 1.18 (95% confidence interval, 1.06-1.31)]. The combined risks associated with each pair of SNPs were consistent with a multiplicative risk model. Under this model, and in combination with previously reported SNPs on 8q and 17q, these loci explain 16% of the familial risk of the disease, and men in the top 10% of the risk distribution have a 2.1-fold increased risk relative to general population rates. This study provides strong confirmation of these susceptibility loci in multiple populations and shows that they make an important contribution to prostate cancer risk prediction. (Cancer Epidemiol Biomarkers Prev 2008;17(8):2052–61)