Tests for Gene-Environment Interactions and Joint Effects with Exposure Misclassification

The number of methods for genome-wide testing of gene-environment interactions (GEI) continues to increase with the hope of discovering new genetic risk factors and obtaining insight into the disease-gene-environment relationship. The relative performance of these methods based on family-wise type 1 error rate and power depends on underlying disease-gene-environment associations, estimates of which may be biased in the presence of exposure misclassification. This simulation study expands on a previously published simulation study of methods for detecting GEI by evaluating the impact of exposure misclassification. We consider seven single step and modular screening methods for identifying GEI at a genome-wide level and seven joint tests for genetic association and GEI, for which the goal is to discover new genetic susceptibility loci by leveraging GEI when present. In terms of statistical power, modular methods that screen based on the marginal disease-gene relationship are more robust to exposure misclassification. Joints tests that include main/marginal effects of a gene display a similar robustness, confirming results from earlier studies. Our results offer an increased understanding of the strengths and limitations of methods for genome-wide search for GEI and joint tests in presence of exposure misclassification. KEY WORDS: case-control; genome-wide association; gene discovery, gene-environment independence; modular methods; multiple testing; screening test; weighted hypothesis test. Abbreviations: CC, case-control; CC(EXP), CC in the exposed subgroup; CO, case-only; CT, cocktail; DF, degree of freedom; D-G, disease-gene; EB, empirical Bayes; EB(EXP), EB in the exposed subgroup; EDGxE, joint marginal/association screening; FWER, family-wise error rate; G-E, gene-environment; GEI, gene-environment interaction; GEWIS, Gene Environment Wide Interaction Study; H2, hybrid two-step; LR, likelihood ratio; MA, marginal; OR, odds ratio; SE, sensitivity; SP, specificity; TS, two-step gene-environment screening

Heterozygote advantage at HLA class I and II loci and reduced risk of colorectal cancer

Objective: Reduced diversity at Human Leukocyte Antigen (HLA) loci may adversely affect the host's ability to recognize tumor neoantigens and subsequently increase disease burden. We hypothesized that increased heterozygosity at HLA loci is associated with a reduced risk of developing colorectal cancer (CRC). Methods: We imputed HLA class I and II four-digit alleles using genotype data from a population-based study of 5,406 cases and 4,635 controls from the Molecular Epidemiology of Colorectal Cancer Study (MECC). Heterozygosity at each HLA locus and the number of heterozygous genotypes at HLA class -I (A, B, and C) and HLA class -II loci (DQB1, DRB1, and DPB1) were quantified. Logistic regression analysis was used to estimate the risk of CRC associated with HLA heterozygosity. Individuals with homozygous genotypes for all loci served as the reference category, and the analyses were adjusted for sex, age, genotyping platform, and ancestry. Further, we investigated associations between HLA diversity and tumor-associated T cell repertoire features, as measured by tumor infiltrating lymphocytes (TILs; N=2,839) and immunosequencing (N=2,357). Results: Individuals with all heterozygous genotypes at all three class I genes had a reduced odds of CRC (OR: 0.74; 95% CI: 0.56-0.97, p= 0.031). A similar association was observed for class II loci, with an OR of 0.75 (95% CI: 0.60-0.95, p= 0.016). For class-I and class-II combined, individuals with all heterozygous genotypes had significantly lower odds of developing CRC (OR: 0.66, 95% CI: 0.49-0.87, p= 0.004) than those with 0 or one heterozygous genotype. HLA class I and/or II diversity was associated with higher T cell receptor (TCR) abundance and lower TCR clonality, but results were not statistically significant. Conclusion: Our findings support a heterozygote advantage for the HLA class-I and -II loci, indicating an important role for HLA genetic variability in the etiology of CRC

Lymphocytic infiltration in stage II microsatellite stable colorectal tumors: A retrospective prognosis biomarker analysis

Background: Identifying stage II patients with colorectal cancer (CRC) at higher risk of progression is a clinical priority in order to optimize the advantages of adjuvant chemotherapy while avoiding unnecessary toxicity. Recently, the intensity and the quality of the host immune response in the tumor microenvironment have been reported to have an important role in tumorigenesis and an inverse association with tumor progression. This association is well established in microsatellite instable CRC. In this work, we aim to assess the usefulness of measures of T-cell infiltration as prognostic biomarkers in 640 stage II, CRC tumors, 582 of them confirmed microsatellite stable. Methods and findings: We measured both the quantity and clonality index of T cells by means of T-cell receptor (TCR) immunosequencing in a discovery dataset (95 patients with colon cancer diagnosed at stage II and microsatellite stable, median age 67, 30% women) and replicated the results in 3 additional series of stage II patients from 2 countries. Series 1 and 2 were recruited in Barcelona, Spain and included 112 fresh frozen (FF, median age 69, 44% women) and 163 formalin-fixed paraffin-embedded (FFPE, median age 67, 39% women) samples, respectively. Series 3 included 270 FFPE samples from patients recruited in Haifa, Northern Israel, as part of a large case-control study of CRC (median age 73, 46% women). Median follow-up time was 81.1 months. Cox regression models were fitted to evaluate the prognostic value of T-cell abundance and Simpson clonality of TCR variants adjusting by sex, age, tumor location, and stage (IIA and IIB). In the discovery dataset, higher TCR abundance was associated with better prognosis (hazard ratio [HR] for ≥Q1 = 0.25, 95% CI 0.10-0.63, P = 0.003). A functional analysis of gene expression on these tumors revealed enrichment in pathways related to immune response. Higher values of clonality index (lower diversity) were not associated with worse disease-free survival, though the HR for ≥Q3 was 2.32 (95% CI 0.90-5.97, P = 0.08). These results were replicated in an independent FF dataset (TCR abundance: HR = 0.30, 95% CI 0.12-0.72, P = 0.007; clonality: HR = 3.32, 95% CI 1.38-7.94, P = 0.007). Also, the association with prognosis was tested in 2 independent FFPE datasets. The same association was observed with TCR abundance (HR = 0.41, 95% CI 0.18-0.93, P = 0.03 and HR = 0.56, 95% CI 0.31-1, P = 0.042, respectively, for each FFPE dataset). However, the clonality index was associated with prognosis only in the FFPE dataset from Israel (HR = 2.45, 95% CI 1.39-4.32, P = 0.002). Finally, a combined analysis combining all microsatellite stable (MSS) samples demonstrated a clear prognosis value both for TCR abundance (HR = 0.39, 95% CI 0.26-0.57, P = 1.3e-06) and the clonality index (HR = 2.13, 95% CI 1.44-3.15, P = 0.0002). These associations were also observed when variables were considered continuous in the models (HR per log2 of TCR abundance = 0.85, 95% CI 0.78-0.93, P = 0.0002; HR per log2 or clonality index = 1.16, 95% CI 1.03-1.31, P = 0.016). Limitations: This is a retrospective study, and samples had been preserved with different methods. Validation series lack complete information about microsatellite instability (MSI) status and pathology assessment. The Molecular Epidemiology of Colorectal Cancer (MECC) study had information about overall survival instead of progression-free survival. Conclusion: Results from this study demonstrate that tumor lymphocytes, assessed by TCR repertoire quantification based on a sequencing method, are an independent prognostic factor in microsatellite stable stage II CRC

Tumor immune infiltration estimated from gene expression profiles predicts colorectal cancer relapse

A substantial fraction of patients with stage I-III colorectal adenocarcinoma (CRC) experience disease relapse after surgery with curative intent. However, biomarkers for predicting the likelihood of CRC relapse have not been fully explored. Therefore, we assessed the association between tumor infiltration by a broad array of innate and adaptive immune cell types and CRC relapse risk. We implemented a discovery-validation design including a discovery dataset from Moffitt Cancer Center (MCC; Tampa, FL) and three independent validation datasets: (1) GSE41258 (2) the Molecular Epidemiology of Colorectal Cancer (MECC) study, and (3) GSE39582. Infiltration by 22 immune cell types was inferred from tumor gene expression data, and the association between immune infiltration by each cell type and relapse-free survival was assessed using Cox proportional hazards regression. Within each of the four independent cohorts, CD4+ memory activated T cell (HR: 0.93, 95% CI: 0.90-0.96; FDR = 0.0001) infiltration was associated with longer time to disease relapse, independent of stage, microsatellite instability, and adjuvant therapy. Based on our meta-analysis across the four datasets, 10 innate and adaptive immune cell types associated with disease relapse of which 2 were internally validated using multiplex immunofluorescence. Moreover, immune cell type infiltration was a better predictors of disease relapse than Consensus Molecular Subtype (CMS) and other expression-based biomarkers (Immune-AICMCC:238.1-238.9; CMS-AICMCC: 241.0). These data suggest that transcriptome-derived immune profiles are prognostic indicators of CRC relapse and quantification of both innate and adaptive immune cell types may serve as candidate biomarkers for predicting prognosis and guiding frequency and modality of disease surveillance

Genome-wide association study of colorectal cancer identifies six new susceptibility loci

El document inclou una pàgina final amb una correcció (corrigendum). Aquesta, per si sola, té el següent DOI: 10.1038/ncomms9739 i es va publicar al mateix vol. 6.Genetic susceptibility to colorectal cancer is caused by rare pathogenic mutations and common genetic variants that contribute to familial risk. Here we report the results of a two-stage association study with 18,299 cases of colorectal cancer and 19,656 controls, with follow-up of the most statistically significant genetic loci in 4,725 cases and 9,969 controls from two Asian consortia. We describe six new susceptibility loci reaching a genome-wide threshold of P<5.0E-08. These findings provide additional insight into the underlying biological mechanisms of colorectal cancer and demonstrate the scientific value of large consortia-based genetic epidemiology studies

Exploratory genome-wide interaction analysis of non-steroidal 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

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. Geneenvironment interactions (G x E) can provide biological insights into the effects of obesity on colorectal cancer risk. Here, we assessed potential genome-wide G x 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 x 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 x E interactions under specific conditions. BMI was associated with higher colorectal cancer risk. The two-step approach revealed a statistically significant GxBMI 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

Cumulative Burden of Colorectal Cancer-Associated Genetic Variants Is More Strongly Associated With Early-Onset vs Late-Onset Cancer.

BACKGROUND & AIMS: Early-onset colorectal cancer (CRC, in persons younger than 50 years old) is increasing in incidence; yet, in the absence of a family history of CRC, this population lacks harmonized recommendations for prevention. We aimed to determine whether a polygenic risk score (PRS) developed from 95 CRC-associated common genetic risk variants was associated with risk for early-onset CRC. METHODS: We studied risk for CRC associated with a weighted PRS in 12,197 participants younger than 50 years old vs 95,865 participants 50 years or older. PRS was calculated based on single nucleotide polymorphisms associated with CRC in a large-scale genome-wide association study as of January 2019. Participants were pooled from 3 large consortia that provided clinical and genotyping data: the Colon Cancer Family Registry, the Colorectal Transdisciplinary Study, and the Genetics and Epidemiology of Colorectal Cancer Consortium and were all of genetically defined European descent. Findings were replicated in an independent cohort of 72,573 participants. RESULTS: Overall associations with CRC per standard deviation of PRS were significant for early-onset cancer, and were stronger compared with late-onset cancer (P for interaction = .01); when we compared the highest PRS quartile with the lowest, risk increased 3.7-fold for early-onset CRC (95% CI 3.28-4.24) vs 2.9-fold for late-onset CRC (95% CI 2.80-3.04). This association was strongest for participants without a first-degree family history of CRC (P for interaction = 5.61 × 10-5). When we compared the highest with the lowest quartiles in this group, risk increased 4.3-fold for early-onset CRC (95% CI 3.61-5.01) vs 2.9-fold for late-onset CRC (95% CI 2.70-3.00). Sensitivity analyses were consistent with these findings. CONCLUSIONS: In an analysis of associations with CRC per standard deviation of PRS, we found the cumulative burden of CRC-associated common genetic variants to associate with early-onset cancer, and to be more strongly associated with early-onset than late-onset cancer, particularly in the absence of CRC family history. Analyses of PRS, along with environmental and lifestyle risk factors, might identify younger individuals who would benefit from preventive measures

Combining Asian and European genome-wide association studies of colorectal cancer improves risk prediction across racial and ethnic populations

Polygenic risk scores (PRS) have great potential to guide precision colorectal cancer (CRC) prevention by identifying those at higher risk to undertake targeted screening. However, current PRS using European ancestry data have sub-optimal performance in non-European ancestry populations, limiting their utility among these populations. Towards addressing this deficiency, we expand PRS development for CRC by incorporating Asian ancestry data (21,731 cases; 47,444 controls) into European ancestry training datasets (78,473 cases; 107,143 controls). The AUC estimates (95% CI) of PRS are 0.63(0.62-0.64), 0.59(0.57-0.61), 0.62(0.60-0.63), and 0.65(0.63-0.66) in independent datasets including 1681-3651 cases and 8696-115,105 controls of Asian, Black/African American, Latinx/Hispanic, and non-Hispanic White, respectively. They are significantly better than the European-centric PRS in all four major US racial and ethnic groups (p-values < 0.05). Further inclusion of non-European ancestry populations, especially Black/African American and Latinx/Hispanic, is needed to improve the risk prediction and enhance equity in applying PRS in clinical practice