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.

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.

Modeling the longitudinal transitions of electronic cigarettes and conventional cigarettes with time-dependent covariates among adolescents.

E-cigarettes may help combustible cigarette smokers switch to a less harmful alternative, or may increase the risk of subsequent initiation of cigarettes among non-smokers. Among youth, it is not clear whether both pathways occur equally, or whether one direction is more likely than the other. We used data from a prospective cohort study of youth in Southern California followed twice annually from Fall 2013 (9th grade) to Fall 2015 (11th grade) (N = 1977). A polytomous logistic regression model was used to simultaneously estimate transition rates for initiation of and abstention from e-cigarettes and cigarettes. Use of e-cigarettes was positively associated with initiation of cigarettes (OR = 7.57; 95%CI:[5.32, 10.8]) and negatively associated with cigarette abstention (OR = 0.58; 95%CI:[0.33, 0.99]) in adjusted models; cigarette use was positively associated with e-cigarette initiation (OR = 2.54; 95%CI:[1.45, 4.47]) and negatively associated with e-cigarette abstention (OR = 0.31; 95%CI:[0.17,0.57]). Uni-directional transition from e-cigarettes only to cigarettes only occurred less frequently than expected under independence (OR = 0.33; 95% CI [0.20, 0.55]), whereas simultaneously initiating both products (OR = 9.79; 95%CI:[7.22, 13.3]) and simultaneously abstaining (OR = 2.84; 95%CI:[1.50, 5.37]) were more frequent than expected. E-cigarettes were more strongly associated with subsequent cigarette initiation than the reverse, though both models indicated that use of either product seems to encourage use of the other. Models also indicated that use of either e-cigarettes or cigarettes resulted in reduced abstention of the other product. Findings suggest that prevention efforts for that continue to focus on both e-cigarettes and cigarettes are needed.

Radiation Treatment, ATM, BRCA1/2, and CHEK2*1100delC Pathogenic Variants and Risk of Contralateral Breast Cancer.

Whether radiation therapy (RT) affects contralateral breast cancer (CBC) risk in women with pathogenic germline variants in moderate- to high-penetrance breast cancer-associated genes is unknown. In a population-based case-control study, we examined the association between RT; variants in ATM, BRCA1/2, or CHEK2*1100delC; and CBC risk. We analyzed 708 cases of women with CBC and 1399 controls with unilateral breast cancer, all diagnosed with first invasive breast cancer between 1985 and 2000 and aged younger than 55 years at diagnosis and screened for variants in breast cancer-associated genes. Rate ratios (RR) and 95% confidence intervals (CIs) were estimated using multivariable conditional logistic regression. RT did not modify the association between known pathogenic variants and CBC risk (eg, BRCA1/2 pathogenic variant carriers without RT: RR = 3.52, 95% CI = 1.76 to 7.01; BRCA1/2 pathogenic variant carriers with RT: RR = 4.46, 95% CI = 2.96 to 6.71), suggesting that modifying RT plans for young women with breast cancer is unwarranted. Rare ATM missense variants, not currently identified as pathogenic, were associated with increased risk of RT-associated CBC (carriers of ATM rare missense variants of uncertain significance without RT: RR = 0.38, 95% CI = 0.09 to 1.55; carriers of ATM rare missense variants of uncertain significance with RT: RR = 2.98, 95% CI = 1.31 to 6.80). Further mechanistic studies will aid clinical decision-making related to RT.

Association of a Pathway-Specific Genetic Risk Score With Risk of Radiation-Associated Contralateral Breast Cancer.

Importance: Radiation therapy for breast cancer is associated with increased risk of a second primary contralateral breast cancer, but the genetic factors modifying this association are not well understood. Objective: To determine whether a genetic risk score comprising single nucleotide polymorphisms in the nonhomologous end-joining DNA repair pathway is associated with radiation-associated contralateral breast cancer. Design, Setting, and Participants: This case-control study included a case group of women with contralateral breast cancer that was diagnosed at least 1 year after a first primary breast cancer who were individually matched to a control group of women with unilateral breast cancer. Inclusion criteria were receiving a first invasive breast cancer diagnosis prior to age 55 years between 1985 and 2008. Women were recruited through 8 population-based cancer registries in the United States, Canada, and Denmark as part of the Women's Environment, Cancer, and Radiation Epidemiology Studies I (November 2000 to August 2004) and II (March 2010 to December 2012). Data analysis was conducted from July 2017 to August 2019. Exposures: Stray radiation dose to the contralateral breast during radiation therapy for the first breast cancer. A novel genetic risk score comprised of genetic variants in the nonhomologous end-joining DNA repair pathway was considered the potential effect modifier, dichotomized as high risk if the score was above the median of 74 and low risk if the score was at or below the median. Main Outcomes and Measures: The main outcome was risk of contralateral breast cancer associated with stray radiation dose stratified by genetic risk score, age, and latency. Results: A total of 5953 women were approached for study participation, and 3732 women (62.7%) agreed to participate. The median (range) age at first diagnosis was 46 (23-54) years. After 5 years of latency or more, among women who received the first diagnosis when they were younger than 40 years, exposure to 1.0 Gy (to convert to rad, multiply by 100) or more of stray radiation was associated with a 2-fold increased risk of contralateral breast cancer compared with women who were not exposed (rate ratio, 2.0 [95% CI, 1.1-3.6]). The risk was higher among women with a genetic risk score above the median (rate ratio, 3.0 [95% CI, 1.1-8.1]), and there was no association among women with a genetic risk score below the median (rate ratio, 1.3 [95% CI, 0.5-3.7]). Among younger women with a high genetic risk score, the attributable increased risk for contralateral breast cancer associated with stray radiation dose was 28%. Conclusions and Relevance: This study found an increased risk of contralateral breast cancer that was attributable to stray radiation exposure among women with a high genetic risk score and who received a first breast cancer diagnosis when they were younger than 40 years after 5 years or more of latency. This genetic risk score may help guide treatment and surveillance for women with breast cancer.

Metabolic signature of healthy lifestyle and its relation with risk of hepatocellular carcinoma in a large European cohort.

Background: Studies using metabolomic data have identified metabolites from several compound classes that are associated with disease-related lifestyle factors. Objective: In this study, we identified metabolic signatures reflecting lifestyle patterns and related them to the risk of hepatocellular carcinoma (HCC) in the European Prospective Investigation into Cancer and Nutrition (EPIC) cohort. Design: Within a nested case-control study of 147 incident HCC cases and 147 matched controls, partial least squares (PLS) analysis related 7 modified healthy lifestyle index (HLI) variables (diet, BMI, physical activity, lifetime alcohol, smoking, diabetes, and hepatitis) to 132 targeted serum-measured metabolites and a liver function score. The association between the resulting PLS scores and HCC risk was examined in multivariable conditional logistic regression models, where ORs and 95% CIs were computed. Results: The lifestyle component's PLS score was negatively associated with lifetime alcohol, BMI, smoking, and diabetes, and positively associated with physical activity. Its metabolic counterpart was positively related to the metabolites sphingomyelin (SM) (OH) C14:1, C16:1, and C22:2, and negatively related to glutamate, hexoses, and the diacyl-phosphatidylcholine PC aaC32:1. The lifestyle and metabolomics components were inversely associated with HCC risk, with the ORs for a 1-SD increase in scores equal to 0.53 (95% CI: 0.38, 0.74) and 0.28 (0.18, 0.43), and the associated AUCs equal to 0.64 (0.57, 0.70) and 0.74 (0.69, 0.80), respectively. Conclusions: This study identified a metabolic signature reflecting a healthy lifestyle pattern which was inversely associated with HCC risk. The metabolic profile displayed a stronger association with HCC than did the modified HLI derived from questionnaire data. Measuring a specific panel of metabolites may identify strata of the population at higher risk for HCC and can add substantial discrimination compared with questionnaire data. This trial was registered at clinicaltrials.gov as NCT03356535.

Breast Cancer Family History and Contralateral Breast Cancer Risk in Young Women: An Update From the Women's Environmental Cancer and Radiation Epidemiology Study.

Purpose The Women's Environmental Cancer and Radiation Epidemiology (WECARE) study demonstrated the importance of breast cancer family history on contralateral breast cancer (CBC) risk, even for noncarriers of deleterious BRCA1/2 mutations. With the completion of WECARE II, updated risk estimates are reported. Additional analyses that exclude women negative for deleterious mutations in ATM, CHEK2*1100delC, and PALB2 were performed. Patients and Methods The WECARE Study is a population-based case-control study that compared 1,521 CBC cases with 2,212 individually matched unilateral breast cancer (UBC) controls. Participants were younger than age 55 years when diagnosed with a first invasive breast cancer between 1985 and 2008. Women were interviewed about breast cancer risk factors, including family history. A subset of women was screened for deleterious mutations in BRCA1/2, ATM, CHEK2*1100delC, and PALB2. Rate ratios (RRs) were estimated using multivariable conditional logistic regression. Cumulative absolute risks (ARs) were estimated by combining RRs from the WECARE Study and population-based SEER*Stat cancer incidence data. Results Women with any first-degree relative with breast cancer had a 10-year AR of 8.1% for CBC (95% CI, 6.7% to 9.8%). Risks also were increased if the relative was diagnosed at an age younger than 40 years (10-year AR, 13.5%; 95% CI, 8.8% to 20.8%) or with CBC (10-year AR, 14.1%; 95% CI, 9.5% to 20.7%). These risks are comparable with those seen in BRCA1/2 deleterious mutation carriers (10-year AR, 18.4%; 95% CI, 16.0% to 21.3%). In the subset of women who tested negative for deleterious mutations in BRCA1/2, ATM, CHEK2*1100delC, and PALB2, estimates were unchanged. Adjustment for known breast cancer single-nucleotide polymorphisms did not affect estimates. Conclusion Breast cancer family history confers a high CBC risk, even after excluding women with deleterious mutations. Clinicians are urged to use detailed family histories to guide treatment and future screening decisions for young women with breast cancer.

Are Metabolic Signatures Mediating the Relationship between Lifestyle Factors and Hepatocellular Carcinoma Risk? Results from a Nested Case-Control Study in EPIC.

Background: The "meeting-in-the-middle" (MITM) is a principle to identify exposure biomarkers that are also predictors of disease. The MITM statistical framework was applied in a nested case-control study of hepatocellular carcinoma (HCC) within European Prospective Investigation into Cancer and Nutrition (EPIC), where healthy lifestyle index (HLI) variables were related to targeted serum metabolites.Methods: Lifestyle and targeted metabolomic data were available from 147 incident HCC cases and 147 matched controls. Partial least squares analysis related 7 lifestyle variables from a modified HLI to a set of 132 serum-measured metabolites and a liver function score. Mediation analysis evaluated whether metabolic profiles mediated the relationship between each lifestyle exposure and HCC risk.Results: Exposure-related metabolic signatures were identified. Particularly, the body mass index (BMI)-associated metabolic component was positively related to glutamic acid, tyrosine, PC aaC38:3, and liver function score and negatively to lysoPC aC17:0 and aC18:2. The lifetime alcohol-specific signature had negative loadings on sphingomyelins (SM C16:1, C18:1, SM(OH) C14:1, C16:1 and C22:2). Both exposures were associated with increased HCC with total effects (TE) = 1.23 (95% confidence interval = 0.93-1.62) and 1.40 (1.14-1.72), respectively, for BMI and alcohol consumption. Both metabolic signatures mediated the association between BMI and lifetime alcohol consumption and HCC with natural indirect effects, respectively, equal to 1.56 (1.24-1.96) and 1.09 (1.03-1.15), accounting for a proportion mediated of 100% and 24%.Conclusions: In a refined MITM framework, relevant metabolic signatures were identified as mediators in the relationship between lifestyle exposures and HCC risk.Impact: The understanding of the biological basis for the relationship between modifiable exposures and cancer would pave avenues for clinical and public health interventions on metabolic mediators. Cancer Epidemiol Biomarkers Prev; 27(5); 531-40. ©2018 AACR.

Determining Risk of Colorectal Cancer and Starting Age of Screening Based on Lifestyle, Environmental, and Genetic Factors.

BACKGROUND & AIMS: Guidelines for initiating colorectal cancer (CRC) screening are based on family history but do not consider lifestyle, environmental, or genetic risk factors. We developed models to determine risk of CRC, based on lifestyle and environmental factors and genetic variants, and to identify an optimal age to begin screening. METHODS: We collected data from 9748 CRC cases and 10,590 controls in the Genetics and Epidemiology of Colorectal Cancer Consortium and the Colorectal Transdisciplinary study, from 1992 through 2005. Half of the participants were used to develop the risk determination model and the other half were used to evaluate the discriminatory accuracy (validation set). Models of CRC risk were created based on family history, 19 lifestyle and environmental factors (E-score), and 63 CRC-associated single-nucleotide polymorphisms identified in genome-wide association studies (G-score). We evaluated the discriminatory accuracy of the models by calculating area under the receiver operating characteristic curve values, adjusting for study, age, and endoscopy history for the validation set. We used the models to project the 10-year absolute risk of CRC for a given risk profile and recommend ages to begin screening in comparison to CRC risk for an average individual at 50 years of age, using external population incidence rates for non-Hispanic whites from the Surveillance, Epidemiology, and End Results program registry. RESULTS: In our models, E-score and G-score each determined risk of CRC with greater accuracy than family history. A model that combined both scores and family history estimated CRC risk with an area under the receiver operating characteristic curve value of 0.63 (95% confidence interval, 0.62-0.64) for men and 0.62 (95% confidence interval, 0.61-0.63) for women; area under the receiver operating characteristic curve values based on only family history ranged from 0.53 to 0.54 and those based only E-score or G-score ranged from 0.59 to 0.60. Although screening is recommended to begin at age 50 years for individuals with no family history of CRC, starting ages calculated based on combined E-score and G-score differed by 12 years for men and 14 for women, for individuals with the highest vs the lowest 10% of risk. CONCLUSIONS: We used data from 2 large international consortia to develop CRC risk calculation models that included genetic and environmental factors along with family history. These determine risk of CRC and starting ages for screening with greater accuracy than the family history only model, which is based on the current screening guideline. These scoring systems might serve as a first step toward developing individualized CRC prevention strategies.

Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases.

Recently, many new approaches, study designs, and statistical and analytical methods have emerged for studying gene-environment interactions (G×Es) in large-scale studies of human populations. There are opportunities in this field, particularly with respect to the incorporation of -omics and next-generation sequencing data and continual improvement in measures of environmental exposures implicated in complex disease outcomes. In a workshop called "Current Challenges and New Opportunities for Gene-Environment Interaction Studies of Complex Diseases," held October 17-18, 2014, by the National Institute of Environmental Health Sciences and the National Cancer Institute in conjunction with the annual American Society of Human Genetics meeting, participants explored new approaches and tools that have been developed in recent years for G×E discovery. This paper highlights current and critical issues and themes in G×E research that need additional consideration, including the improved data analytical methods, environmental exposure assessment, and incorporation of functional data and annotations.

Opportunities and Challenges for Environmental Exposure Assessment in Population-Based Studies.

A growing number and increasing diversity of factors are available for epidemiological studies. These measures provide new avenues for discovery and prevention, yet they also raise many challenges for adoption in epidemiological investigations. Here, we evaluate 1) designs to investigate diseases that consider heterogeneous and multidimensional indicators of exposure and behavior, 2) the implementation of numerous methods to capture indicators of exposure, and 3) the analytical methods required for discovery and validation. We find that case-control studies have provided insights into genetic susceptibility but are insufficient for characterizing complex effects of environmental factors on disease development. Prospective and two-phase designs are required but must balance extended data collection with follow-up of study participants. We discuss innovations in assessments including the microbiome; mass spectrometry and metabolomics; behavioral assessment; dietary, physical activity, and occupational exposure assessment; air pollution monitoring; and global positioning and individual sensors. We claim the the availability of extensive correlated data raises new challenges in disentangling specific exposures that influence cancer risk from among extensive and often correlated exposures. In conclusion, new high-dimensional exposure assessments offer many new opportunities for environmental assessment in cancer development. Cancer Epidemiol Biomarkers Prev; 26(9); 1370-80. ©2017 AACR.

Association of Common Genetic Variants With Contralateral Breast Cancer Risk in the WECARE Study.

Background: Women with unilateral breast cancer (UBC) are at risk of developing a subsequent contralateral breast cancer (CBC). Common variants are associated with breast cancer risk. Whether these influence CBC risk is unknown. Methods: Participants were breast cancer cases from the population-based Women's Environmental Cancer and Radiation Epidemiology (WECARE) Study. Sixty-seven established breast cancer risk loci were genotyped directly or by imputation in 1459 case subjects with CBC and 2126 UBC control subjects. An unweighted polygenic risk score (PRS) was created by summing the number of risk alleles for each directly genotyped single nucleotide polymorphism (SNP), or for imputed loci, the imputed dosage. A weighted PRS was calculated similarly, but where each SNP's contribution was weighted by the published per-allele log odds ratio. Unweighted and weighted polygenic risk scores and CBC risk were modeled using conditional logistic regression. Cumulative CBC risk was estimated and benchmarked using Surveillance, Epidemiology, and End Results population incidence rates. Results: Both unweighted and weighted PRS were statistically significantly associated with CBC risk. The adjusted risk ratio of CBC in women in the upper quartile of unweighted PRS compared with the lowest quartile was 1.63 (95% confidence interval [CI] = 1.33 to 2.00). The estimated 10-year cumulative risk for women in the upper quartile of the unweighted PRS was 7.4% (95% CI = 6.0% to 9.1%). For women in the upper quartile of the weighted PRS, the risk ratio for CBC was 1.75 (95% CI = 1.41 to 2.18) compared with women in the lowest quartile. There was no statistically significant heterogeneity by age, treatment (radiation therapy dose, tamoxifen, chemotherapy), estrogen receptor status of the first primary, histology of the first primary, length of at-risk period for CBC, or breast cancer family history. Conclusions: Common genomic variants associated with the development of first primary breast cancer are also associated with the development of CBC; the risk is strongest among those who carry more risk alleles.

Estimating the Effect of Targeted Screening Strategies: An Application to Colonoscopy and Colorectal Cancer.

Screening behavior depends on previous screening history and family members' behaviors, which can act as both confounders and intermediate variables on a causal pathway from screening to disease risk. Conventional analyses that adjust for these variables can lead to incorrect inferences about the causal effect of screening if high-risk individuals are more likely to be screened. Analyzing the data in a manner that treats screening as randomized conditional on covariates allows causal parameters to be estimated; inverse probability weighting based on propensity of exposure scores is one such method considered here. I simulated family data under plausible models for the underlying disease process and for screening behavior to assess the performance of alternative methods of analysis and whether a targeted screening approach based on individuals' risk factors would lead to a greater reduction in cancer incidence in the population than a uniform screening policy. Simulation results indicate that there can be a substantial underestimation of the effect of screening on subsequent cancer risk when using conventional analysis approaches, which is avoided by using inverse probability weighting. A large case-control study of colonoscopy and colorectal cancer from Germany shows a strong protective effect of screening, but inverse probability weighting makes this effect even stronger. Targeted screening approaches based on either fixed risk factors or family history yield somewhat greater reductions in cancer incidence with fewer screens needed to prevent one cancer than population-wide approaches, but the differences may not be large enough to justify the additional effort required. See video abstract at, http://links.lww.com/EDE/B207.

GWASeq: targeted re-sequencing follow up to GWAS.

BACKGROUND: For the last decade the conceptual framework of the Genome-Wide Association Study (GWAS) has dominated the investigation of human disease and other complex traits. While GWAS have been successful in identifying a large number of variants associated with various phenotypes, the overall amount of heritability explained by these variants remains small. This raises the question of how best to follow up on a GWAS, localize causal variants accounting for GWAS hits, and as a consequence explain more of the so-called "missing" heritability. Advances in high throughput sequencing technologies now allow for the efficient and cost-effective collection of vast amounts of fine-scale genomic data to complement GWAS. RESULTS: We investigate these issues using a colon cancer dataset. After QC, our data consisted of 1993 cases, 899 controls. Using marginal tests of associations, we identify 10 variants distributed among six targeted regions that are significantly associated with colorectal cancer, with eight of the variants being novel to this study. Additionally, we perform so-called 'SNP-set' tests of association and identify two sets of variants that implicate both common and rare variants in the etiology of colorectal cancer. CONCLUSIONS: Here we present a large-scale targeted re-sequencing resource focusing on genomic regions implicated in colorectal cancer susceptibility previously identified in several GWAS, which aims to 1) provide fine-scale targeted sequencing data for fine-mapping and 2) provide data resources to address methodological questions regarding the design of sequencing-based follow-up studies to GWAS. Additionally, we show that this strategy successfully identifies novel variants associated with colorectal cancer susceptibility and can implicate both common and rare variants.

The Influence of Screening for Precancerous Lesions on Family-Based Genetic Association Tests: An Example of Colorectal Polyps and Cancer.

Unintended consequences of secondary prevention include potential introduction of bias into epidemiologic studies estimating genotype-disease associations. To better understand such bias, we simulated a family-based study of colorectal cancer (CRC), which can be prevented by resecting screen-detected polyps. We simulated genes related to CRC development through risk of polyps (G1), risk of CRC but not polyps (G2), and progression from polyp to CRC (G3). Then, we examined 4 analytical strategies for studying diseases subject to secondary prevention, comparing the following: 1) CRC cases with all controls, without adjusting for polyp history; 2) CRC cases with controls, adjusting for polyp history; 3) CRC cases with only polyp-free controls; and 4) cases with either CRC or polyps with controls having neither. Strategy 1 yielded estimates of association between CRC and each G that were not substantially biased. Strategies 2-4 yielded biased estimates varying in direction according to analysis strategy and gene type. Type I errors were correct, but strategy 1 provided greater power for estimating associations with G2 and G3. We also applied each strategy to case-control data from the Colon Cancer Family Registry (1997-2007). Generally, the best analytical option balancing bias and power is to compare all CRC cases with all controls, ignoring polyps.

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

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.

A model to determine colorectal cancer risk using common genetic susceptibility loci.

BACKGROUND & AIMS: Risk for colorectal cancer (CRC) can be greatly reduced through screening. To aid in the development of screening strategies, we refined models designed to determine risk of CRC by incorporating information from common genetic susceptibility loci. METHODS: By using data collected from more than 12,000 participants in 6 studies performed from 1990 through 2011 in the United States and Germany, we developed risk determination models based on sex, age, family history, genetic risk score (number of risk alleles carried at 27 validated common CRC susceptibility loci), and history of endoscopic examinations. The model was validated using data collected from approximately 1800 participants in the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial, conducted from 1993 through 2001 in the United States. RESULTS: We identified a CRC genetic risk score that independently predicted which patients in the training set would develop CRC. Compared with determination of risk based only on family history, adding the genetic risk score increased the discriminatory accuracy from 0.51 to 0.59 (P = .0028) for men and from 0.52 to 0.56 (P = .14) for women. We calculated age- and sex-specific 10-year CRC absolute risk estimates based on the number of risk alleles, family history, and history of endoscopic examinations. A model that included a genetic risk score better determined the recommended starting age for screening in subjects with and without family histories of CRC. The starting age for high-risk men (family history of CRC and genetic risk score, 90%) was 42 years, and for low-risk men (no family history of CRC and genetic risk score, 10%) was 52 years. For men with no family history and a high genetic risk score (90%), the starting age would be 47 years; this is an intermediate value that is 5 years earlier than it would be for men with a genetic risk score of 10%. Similar trends were observed in women. CONCLUSIONS: By incorporating information on CRC risk alleles, we created a model to determine the risk for CRC more accurately. This model might be used to develop screening and prevention strategies.