Genome-wide interaction study of dietary intake of fibre, fruits, and vegetables with risk of colorectal cancer.

BACKGROUND: Consumption of fibre, fruits and vegetables have been linked with lower colorectal cancer (CRC) risk. A genome-wide gene-environment (G × E) analysis was performed to test whether genetic variants modify these associations. METHODS: A pooled sample of 45 studies including up to 69,734 participants (cases: 29,896; controls: 39,838) of European ancestry were included. To identify G × E interactions, we used the traditional 1--degree-of-freedom (DF) G × E test and to improve power a 2-step procedure and a 3DF joint test that investigates the association between a genetic variant and dietary exposure, CRC risk and G × E interaction simultaneously. FINDINGS: The 3-DF joint test revealed two significant loci with p-value <5 × 10-8. Rs4730274 close to the SLC26A3 gene showed an association with fibre (p-value: 2.4 × 10-3) and G × fibre interaction with CRC (OR per quartile of fibre increase = 0.87, 0.80, and 0.75 for CC, TC, and TT genotype, respectively; G × E p-value: 1.8 × 10-7). Rs1620977 in the NEGR1 gene showed an association with fruit intake (p-value: 1.0 × 10-8) and G × fruit interaction with CRC (OR per quartile of fruit increase = 0.75, 0.65, and 0.56 for AA, AG, and GG genotype, respectively; G × E -p-value: 0.029). INTERPRETATION: We identified 2 loci associated with fibre and fruit intake that also modify the association of these dietary factors with CRC risk. Potential mechanisms include chronic inflammatory intestinal disorders, and gut function. However, further studies are needed for mechanistic validation and replication of findings. FUNDING: National Institutes of Health, National Cancer Institute. Full funding details for the individual consortia are provided in acknowledgments.

Two genome-wide interaction loci modify the association of nonsteroidal anti-inflammatory drugs with colorectal cancer.

Regular, long-term aspirin use may act synergistically with genetic variants, particularly those in mechanistically relevant pathways, to confer a protective effect on colorectal cancer (CRC) risk. We leveraged pooled data from 52 clinical trial, cohort, and case-control studies that included 30,806 CRC cases and 41,861 controls of European ancestry to conduct a genome-wide interaction scan between regular aspirin/nonsteroidal anti-inflammatory drug (NSAID) use and imputed genetic variants. After adjusting for multiple comparisons, we identified statistically significant interactions between regular aspirin/NSAID use and variants in 6q24.1 (top hit rs72833769), which has evidence of influencing expression of TBC1D7 (a subunit of the TSC1-TSC2 complex, a key regulator of MTOR activity), and variants in 5p13.1 (top hit rs350047), which is associated with expression of PTGER4 (codes a cell surface receptor directly involved in the mode of action of aspirin). Genetic variants with functional impact may modulate the chemopreventive effect of regular aspirin use, and our study identifies putative previously unidentified targets for additional mechanistic interrogation.

Genetic risk impacts the association of menopausal hormone therapy with colorectal cancer risk.

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.

Genome-Wide Gene-Environment Interaction Analyses to Understand the Relationship between Red Meat and Processed Meat Intake and Colorectal Cancer Risk.

BACKGROUND: High red meat and/or processed meat consumption are established colorectal cancer risk factors. We conducted a genome-wide gene-environment (GxE) interaction analysis to identify genetic variants that may modify these associations. METHODS: A pooled sample of 29,842 colorectal cancer cases and 39,635 controls of European ancestry from 27 studies were included. Quantiles for red meat and processed meat intake were constructed from harmonized questionnaire data. Genotyping arrays were imputed to the Haplotype Reference Consortium. Two-step EDGE and joint tests of GxE interaction were utilized in our genome-wide scan. RESULTS: Meta-analyses confirmed positive associations between increased consumption of red meat and processed meat with colorectal cancer risk [per quartile red meat OR = 1.30; 95% confidence interval (CI) = 1.21-1.41; processed meat OR = 1.40; 95% CI = 1.20-1.63]. Two significant genome-wide GxE interactions for red meat consumption were found. Joint GxE tests revealed the rs4871179 SNP in chromosome 8 (downstream of HAS2); greater than median of consumption ORs = 1.38 (95% CI = 1.29-1.46), 1.20 (95% CI = 1.12-1.27), and 1.07 (95% CI = 0.95-1.19) for CC, CG, and GG, respectively. The two-step EDGE method identified the rs35352860 SNP in chromosome 18 (SMAD7 intron); greater than median of consumption ORs = 1.18 (95% CI = 1.11-1.24), 1.35 (95% CI = 1.26-1.44), and 1.46 (95% CI = 1.26-1.69) for CC, CT, and TT, respectively. CONCLUSIONS: We propose two novel biomarkers that support the role of meat consumption with an increased risk of colorectal cancer. IMPACT: The reported GxE interactions may explain the increased risk of colorectal cancer in certain population subgroups.

Genome-wide interaction analysis of folate for colorectal cancer risk.

BACKGROUND: Epidemiological and experimental evidence suggests that higher folate intake is associated with decreased colorectal cancer (CRC) risk; however, the mechanisms underlying this relationship are not fully understood. Genetic variation that may have a direct or indirect impact on folate metabolism can provide insights into folate's role in CRC. OBJECTIVES: Our aim was to perform a genome-wide interaction analysis to identify genetic variants that may modify the association of folate on CRC risk. METHODS: We applied traditional case-control logistic regression, joint 3-degree of freedom, and a 2-step weighted hypothesis approach to test the interactions of common variants (allele frequency >1%) across the genome and dietary folate, folic acid supplement use, and total folate in relation to risk of CRC in 30,550 cases and 42,336 controls from 51 studies from 3 genetic consortia (CCFR, CORECT, GECCO). RESULTS: Inverse associations of dietary, total folate, and folic acid supplement with CRC were found (odds ratio [OR]: 0.93; 95% confidence interval [CI]: 0.90, 0.96; and 0.91; 95% CI: 0.89, 0.94 per quartile higher intake, and 0.82 (95% CI: 0.78, 0.88) for users compared with nonusers, respectively). Interactions (P-interaction < 5×10-8) of folic acid supplement and variants in the 3p25.2 locus (in the region of Synapsin II [SYN2]/tissue inhibitor of metalloproteinase 4 [TIMP4]) were found using traditional interaction analysis, with variant rs150924902 (located upstream to SYN2) showing the strongest interaction. In stratified analyses by rs150924902 genotypes, folate supplementation was associated with decreased CRC risk among those carrying the TT genotype (OR: 0.82; 95% CI: 0.79, 0.86) but increased CRC risk among those carrying the TA genotype (OR: 1.63; 95% CI: 1.29, 2.05), suggesting a qualitative interaction (P-interaction = 1.4×10-8). No interactions were observed for dietary and total folate. CONCLUSIONS: Variation in 3p25.2 locus may modify the association of folate supplement with CRC risk. Experimental studies and studies incorporating other relevant omics data are warranted to validate this finding.

Probing the diabetes and colorectal cancer relationship using gene - environment interaction analyses.

BACKGROUND: Diabetes is an established risk factor for colorectal cancer. However, the mechanisms underlying this relationship still require investigation and it is not known if the association is modified by genetic variants. To address these questions, we undertook a genome-wide gene-environment interaction analysis. METHODS: We used data from 3 genetic consortia (CCFR, CORECT, GECCO; 31,318 colorectal cancer cases/41,499 controls) and undertook genome-wide gene-environment interaction analyses with colorectal cancer risk, including interaction tests of genetics(G)xdiabetes (1-degree of freedom; d.f.) and joint testing of Gxdiabetes, G-colorectal cancer association (2-d.f. joint test) and G-diabetes correlation (3-d.f. joint test). RESULTS: Based on the joint tests, we found that the association of diabetes with colorectal cancer risk is modified by loci on chromosomes 8q24.11 (rs3802177, SLC30A8 - ORAA: 1.62, 95% CI: 1.34-1.96; ORAG: 1.41, 95% CI: 1.30-1.54; ORGG: 1.22, 95% CI: 1.13-1.31; p-value3-d.f.: 5.46 × 10-11) and 13q14.13 (rs9526201, LRCH1 - ORGG: 2.11, 95% CI: 1.56-2.83; ORGA: 1.52, 95% CI: 1.38-1.68; ORAA: 1.13, 95% CI: 1.06-1.21; p-value2-d.f.: 7.84 × 10-09). DISCUSSION: These results suggest that variation in genes related to insulin signaling (SLC30A8) and immune function (LRCH1) may modify the association of diabetes with colorectal cancer risk and provide novel insights into the biology underlying the diabetes and colorectal cancer relationship.

A Genetic Locus within the FMN1/GREM1 Gene Region Interacts with Body Mass Index in Colorectal Cancer Risk.

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.

Genome-wide Interaction Study with Smoking for Colorectal Cancer Risk Identifies Novel Genetic Loci Related to Tumor Suppression, Inflammation, and Immune Response.

BACKGROUND: Tobacco smoking is an established risk factor for colorectal cancer. However, genetically defined population subgroups may have increased susceptibility to smoking-related effects on colorectal cancer. METHODS: A genome-wide interaction scan was performed including 33,756 colorectal cancer cases and 44,346 controls from three genetic consortia. RESULTS: Evidence of an interaction was observed between smoking status (ever vs. never smokers) and a locus on 3p12.1 (rs9880919, P = 4.58 × 10-8), with higher associated risk in subjects carrying the GG genotype [OR, 1.25; 95% confidence interval (CI), 1.20-1.30] compared with the other genotypes (OR <1.17 for GA and AA). Among ever smokers, we observed interactions between smoking intensity (increase in 10 cigarettes smoked per day) and two loci on 6p21.33 (rs4151657, P = 1.72 × 10-8) and 8q24.23 (rs7005722, P = 2.88 × 10-8). Subjects carrying the rs4151657 TT genotype showed higher risk (OR, 1.12; 95% CI, 1.09-1.16) compared with the other genotypes (OR <1.06 for TC and CC). Similarly, higher risk was observed among subjects carrying the rs7005722 AA genotype (OR, 1.17; 95% CI, 1.07-1.28) compared with the other genotypes (OR <1.13 for AC and CC). Functional annotation revealed that SNPs in 3p12.1 and 6p21.33 loci were located in regulatory regions, and were associated with expression levels of nearby genes. Genetic models predicting gene expression revealed that smoking parameters were associated with lower colorectal cancer risk with higher expression levels of CADM2 (3p12.1) and ATF6B (6p21.33). CONCLUSIONS: Our study identified novel genetic loci that may modulate the risk for colorectal cancer of smoking status and intensity, linked to tumor suppression and immune response. IMPACT: These findings can guide potential prevention treatments.

Interactions between folate intake and genetic predictors of gene expression levels associated with colorectal cancer risk.

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.

Genome-Wide Interaction Analysis of Genetic Variants With Menopausal Hormone Therapy for Colorectal Cancer Risk.

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.

Beyond GWAS of Colorectal Cancer: Evidence of Interaction with Alcohol Consumption and Putative Causal Variant for the 10q24.2 Region.

BACKGROUND: Currently known associations between common genetic variants and colorectal cancer explain less than half of its heritability of 25%. As alcohol consumption has a J-shape association with colorectal cancer risk, nondrinking and heavy drinking are both risk factors for colorectal cancer. METHODS: Individual-level data was pooled from the Colon Cancer Family Registry, Colorectal Transdisciplinary Study, and Genetics and Epidemiology of Colorectal Cancer Consortium to compare nondrinkers (≤1 g/day) and heavy drinkers (>28 g/day) with light-to-moderate drinkers (1-28 g/day) in GxE analyses. To improve power, we implemented joint 2df and 3df tests and a novel two-step method that modifies the weighted hypothesis testing framework. We prioritized putative causal variants by predicting allelic effects using support vector machine models. RESULTS: For nondrinking as compared with light-to-moderate drinking, the hybrid two-step approach identified 13 significant SNPs with pairwise r2 > 0.9 in the 10q24.2/COX15 region. When stratified by alcohol intake, the A allele of lead SNP rs2300985 has a dose-response increase in risk of colorectal cancer as compared with the G allele in light-to-moderate drinkers [OR for GA genotype = 1.11; 95% confidence interval (CI), 1.06-1.17; OR for AA genotype = 1.22; 95% CI, 1.14-1.31], but not in nondrinkers or heavy drinkers. Among the correlated candidate SNPs in the 10q24.2/COX15 region, rs1318920 was predicted to disrupt an HNF4 transcription factor binding motif. CONCLUSIONS: Our study suggests that the association with colorectal cancer in 10q24.2/COX15 observed in genome-wide association study is strongest in nondrinkers. We also identified rs1318920 as the putative causal regulatory variant for the region. IMPACT: The study identifies multifaceted evidence of a possible functional effect for rs1318920.

Tumor-associated antigen-specific T cells with nivolumab are safe and persist in vivo in relapsed/refractory Hodgkin lymphoma.

Hodgkin lymphoma (HL) Reed Sternberg cells express tumor-associated antigens (TAA) that are potential targets for cellular therapies. We recently demonstrated that TAA-specific T cells (TAA-Ts) targeting WT1, PRAME, and Survivin were safe and associated with prolonged time to progression in solid tumors. Hence, we evaluated whether TAA-Ts when given alone or with nivolumab were safe and could elicit antitumor effects in vivo in patients with relapsed/refractory (r/r) HL. Ten patients were infused with TAA-Ts (8 autologous and 2 allogeneic) for active HL (n = 8) or as adjuvant therapy after hematopoietic stem cell transplant (n = 2). Six patients received nivolumab priming before TAA-Ts and continued until disease progression or unacceptable toxicity. All 10 products recognized 1 or more TAAs and were polyfunctional. Patients were monitored for safety for 6 weeks after the TAA-Ts and for response until disease progression. The infusions were safe with no clear dose-limiting toxicities. Patients receiving TAA-Ts as adjuvant therapy remain in continued remission at 3+ years. Of the 8 patients with active disease, 1 patient had a complete response and 7 had stable disease at 3 months, 3 of whom remain with stable disease at 1 year. Antigen spreading and long-term persistence of TAA-Ts in vivo were observed in responding patients. Nivolumab priming impacted TAA-T recognition and persistence. In conclusion, treatment of patients with r/r HL with TAA-Ts alone or in combination with nivolumab was safe and produced promising results. This trial was registered at www.clinicaltrials.gov as #NCT022039303 and #NCT03843294.

Genetic Effects on Transcriptome Profiles in Colon Epithelium Provide Functional Insights for Genetic Risk Loci.

BACKGROUND & AIMS: The association of genetic variation with tissue-specific gene expression and alternative splicing guides functional characterization of complex trait-associated loci and may suggest novel genes implicated in disease. Here, our aims were as follows: (1) to generate reference profiles of colon mucosa gene expression and alternative splicing and compare them across colon subsites (ascending, transverse, and descending), (2) to identify expression and splicing quantitative trait loci (QTLs), (3) to find traits for which identified QTLs contribute to single-nucleotide polymorphism (SNP)-based heritability, (4) to propose candidate effector genes, and (5) to provide a web-based visualization resource. METHODS: We collected colonic mucosal biopsy specimens from 485 healthy adults and performed bulk RNA sequencing. We performed genome-wide SNP genotyping from blood leukocytes. Statistical approaches and bioinformatics software were used for QTL identification and downstream analyses. RESULTS: We provided a complete quantification of gene expression and alternative splicing across colon subsites and described their differences. We identified thousands of expression and splicing QTLs and defined their enrichment at genome-wide regulatory regions. We found that part of the SNP-based heritability of diseases affecting colon tissue, such as colorectal cancer and inflammatory bowel disease, but also of diseases affecting other tissues, such as psychiatric conditions, can be explained by the identified QTLs. We provided candidate effector genes for multiple phenotypes. Finally, we provided the Colon Transcriptome Explorer web application. CONCLUSIONS: We provide a large characterization of gene expression and splicing across colon subsites. Our findings provide greater etiologic insight into complex traits and diseases influenced by transcriptomic changes in colon tissue.

Genetic architectures of proximal and distal colorectal cancer are partly distinct.

OBJECTIVE: An understanding of the etiologic heterogeneity of colorectal cancer (CRC) is critical for improving precision prevention, including individualized screening recommendations and the discovery of novel drug targets and repurposable drug candidates for chemoprevention. Known differences in molecular characteristics and environmental risk factors among tumors arising in different locations of the colorectum suggest partly distinct mechanisms of carcinogenesis. The extent to which the contribution of inherited genetic risk factors for CRC differs by anatomical subsite of the primary tumor has not been examined. DESIGN: To identify new anatomical subsite-specific risk loci, we performed genome-wide association study (GWAS) meta-analyses including data of 48 214 CRC cases and 64 159 controls of European ancestry. We characterised effect heterogeneity at CRC risk loci using multinomial modelling. RESULTS: We identified 13 loci that reached genome-wide significance (p<5×10-8) and that were not reported by previous GWASs for overall CRC risk. Multiple lines of evidence support candidate genes at several of these loci. We detected substantial heterogeneity between anatomical subsites. Just over half (61) of 109 known and new risk variants showed no evidence for heterogeneity. In contrast, 22 variants showed association with distal CRC (including rectal cancer), but no evidence for association or an attenuated association with proximal CRC. For two loci, there was strong evidence for effects confined to proximal colon cancer. CONCLUSION: Genetic architectures of proximal and distal CRC are partly distinct. Studies of risk factors and mechanisms of carcinogenesis, and precision prevention strategies should take into consideration the anatomical subsite of the tumour.

Identifying Novel Susceptibility Genes for Colorectal Cancer Risk From a Transcriptome-Wide Association Study of 125,478 Subjects.

BACKGROUND AND AIMS: Susceptibility genes and the underlying mechanisms for the majority of risk loci identified by genome-wide association studies (GWAS) for colorectal cancer (CRC) risk remain largely unknown. We conducted a transcriptome-wide association study (TWAS) to identify putative susceptibility genes. METHODS: Gene-expression prediction models were built using transcriptome and genetic data from the 284 normal transverse colon tissues of European descendants from the Genotype-Tissue Expression (GTEx), and model performance was evaluated using data from The Cancer Genome Atlas (n = 355). We applied the gene-expression prediction models and GWAS data to evaluate associations of genetically predicted gene-expression with CRC risk in 58,131 CRC cases and 67,347 controls of European ancestry. Dual-luciferase reporter assays and knockdown experiments in CRC cells and tumor xenografts were conducted. RESULTS: We identified 25 genes associated with CRC risk at a Bonferroni-corrected threshold of P < 9.1 × 10-6, including genes in 4 novel loci, PYGL (14q22.1), RPL28 (19q13.42), CAPN12 (19q13.2), MYH7B (20q11.22), and MAP1L3CA (20q11.22). In 9 known GWAS-identified loci, we uncovered 9 genes that have not been reported previously, whereas 4 genes remained statistically significant after adjusting for the lead risk variant of the locus. Through colocalization analysis in GWAS loci, we additionally identified 12 putative susceptibility genes that were supported by TWAS analysis at P < .01. We showed that risk allele of the lead risk variant rs1741640 affected the promoter activity of CABLES2. Knockdown experiments confirmed that CABLES2 plays a vital role in colorectal carcinogenesis. CONCLUSIONS: Our study reveals new putative susceptibility genes and provides new insight into the biological mechanisms underlying CRC development.

Association of Body Mass Index With Colorectal Cancer Risk by Genome-Wide Variants.

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.

A general framework for functionally informed set-based analysis: Application to a large-scale colorectal cancer study.

Genome-wide association studies (GWAS) have successfully identified tens of thousands of genetic variants associated with various phenotypes, but together they explain only a fraction of heritability, suggesting many variants have yet to be discovered. Recently it has been recognized that incorporating functional information of genetic variants can improve power for identifying novel loci. For example, S-PrediXcan and TWAS tested the association of predicted gene expression with phenotypes based on GWAS summary statistics by leveraging the information on genetic regulation of gene expression and found many novel loci. However, as genetic variants may have effects on more than one gene and through different mechanisms, these methods likely only capture part of the total effects of these variants. In this paper, we propose a summary statistics-based mixed effects score test (sMiST) that tests for the total effect of both the effect of the mediator by imputing genetically predicted gene expression, like S-PrediXcan and TWAS, and the direct effects of individual variants. It allows for multiple functional annotations and multiple genetically predicted mediators. It can also perform conditional association analysis while adjusting for other genetic variants (e.g., known loci for the phenotype). Extensive simulation and real data analyses demonstrate that sMiST yields p-values that agree well with those obtained from individual level data but with substantively improved computational speed. Importantly, a broad application of sMiST to GWAS is possible, as only summary statistics of genetic variant associations are required. We apply sMiST to a large-scale GWAS of colorectal cancer using summary statistics from ∼120, 000 study participants and gene expression data from the Genotype-Tissue Expression (GTEx) project. We identify several novel and secondary independent genetic loci.

Exploratory Genome-Wide Interaction Analysis of Nonsteroidal Anti-inflammatory Drugs and Predicted Gene Expression on Colorectal Cancer Risk.

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. IMPACT: These findings provide preliminary support that could help understand the chemopreventive mechanisms of NSAIDs on colorectal cancer.

Functional informed genome-wide interaction analysis of body mass index, diabetes and colorectal cancer risk.

BACKGROUND: Body 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. METHODS: To 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. RESULTS: Among 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 ). CONCLUSIONS: Aggregating G × E interactions and incorporating functional information, we discovered novel genes that may interact with BMI and diabetes on CRC risk.

Modeling the effect of prolonged ethanol exposure on global gene expression and chromatin accessibility in normal 3D colon organoids.

In this study we aimed to explore the potential biological effect of ethanol exposure on healthy colon epithelial cells using normal human colon 3D organoid "mini-gut" cultures. In numerous published studies ethanol use has been shown to be an environmental risk factor for colorectal cancer (CRC) development; however, the influence of ethanol exposure on normal colon epithelial cell biology remains poorly understood. We investigated the potential molecular effects of ethanol exposure in normal colon 3D organoids in a small pilot study (n = 3) using RNA-seq and ATAC-seq. We identify 1965 differentially expressed genes and 2217 differentially accessible regions of chromatin in response to ethanol treatment. Further, by cross-referencing our results with previously published analysis in colorectal cancer cell lines, we have not only validated a number of reported differentially expressed genes, but also identified several novel candidates for future investigation. In summary, our data highlights the potential importance for the use of normal colon 3D organoid models as a novel tool for the investigation of the relationship between the effects of environmental risk factors associated with colorectal cancer and the molecular mechanisms through which they confer this risk.