Faculty Bibliography

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.

BACKGROUND: Obesity is a recognised positive risk factor for colorectal adenoma and colorectal cancer. Obesity is associated with insulin resistance and compensatory hyperinsulinaemia, and circulating insulin and C-peptide, a biomarker of insulin levels, have been positively associated with colorectal cancer risk. However, whether a similar relationship exists for colorectal adenomas, an established colorectal cancer precursor, is unclear. METHODS: In a nested case-control study of 273 colorectal adenoma cases and 355 matched controls from the screening arm of the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial, serum C-peptide levels were measured by a chemiluminescent immunometric assay. Multivariable unconditional logistic regression models were used to calculate odds ratios (OR) and 95% confidence intervals (CI) for colorectal adenoma within quartiles of C-peptide. Further, to explore the temporal stability of C-peptide, repeat samples from the incident adenoma cases (n=50) and controls (n=30), over a 5-year period were assayed and the intra-class correlations (ICC) estimated. RESULTS: In a multivariable model that included established colorectal adenoma risk factors, C-peptide levels were not associated with colorectal adenoma (Q4 vs. Q1, OR 0.83, 95% CI: 0.52-1.31; P-trend 0.32); similar null associations were observed by gender, by adenoma subsite and for advanced adenomas. Among control participants, the ICC value over a 5-year period was 0.66. CONCLUSION: Our results suggest that higher C-peptide levels were not associated with colorectal adenoma incidence in this study population. Other biological pathways associated with obesity may be more relevant to the early stages of colorectal tumorigenesis.

IMPORTANCE: Use of aspirin and other nonsteroidal anti-inflammatory drugs (NSAIDs) is associated with lower risk of colorectal cancer. OBJECTIVE: To identify common genetic markers that may confer differential benefit from aspirin or NSAID chemoprevention, we tested gene x environment interactions between regular use of aspirin and/or NSAIDs and single-nucleotide polymorphisms (SNPs) in relation to risk of colorectal cancer. DESIGN, SETTING, AND PARTICIPANTS: Case-control study using data from 5 case-control and 5 cohort studies initiated between 1976 and 2003 across the United States, Canada, Australia, and Germany and including colorectal cancer cases (n=8634) and matched controls (n=8553) ascertained between 1976 and 2011. Participants were all of European descent. EXPOSURES: Genome-wide SNP data and information on regular use of aspirin and/or NSAIDs and other risk factors. MAIN OUTCOMES AND MEASURES: Colorectal cancer. RESULTS: Regular use of aspirin and/or NSAIDs was associated with lower risk of colorectal cancer (prevalence, 28% vs 38%; odds ratio [OR], 0.69 [95% CI, 0.64-0.74]; P = 6.2 x 10(-28)) compared with nonregular use. In the conventional logistic regression analysis, the SNP rs2965667 at chromosome 12p12.3 near the MGST1 gene showed a genome-wide significant interaction with aspirin and/or NSAID use (P = 4.6 x 10(-9) for interaction). Aspirin and/or NSAID use was associated with a lower risk of colorectal cancer among individuals with rs2965667-TT genotype (prevalence, 28% vs 38%; OR, 0.66 [95% CI, 0.61-0.70]; P = 7.7 x 10(-33)) but with a higher risk among those with rare (4%) TA or AA genotypes (prevalence, 35% vs 29%; OR, 1.89 [95% CI, 1.27-2.81]; P = .002). In case-only interaction analysis, the SNP rs16973225 at chromosome 15q25.2 near the IL16 gene showed a genome-wide significant interaction with use of aspirin and/or NSAIDs (P = 8.2 x 10(-9) for interaction). Regular use was associated with a lower risk of colorectal cancer among individuals with rs16973225-AA genotype (prevalence, 28% vs 38%; OR, 0.66 [95% CI, 0.62-0.71]; P = 1.9 x 10(-30)) but was not associated with risk of colorectal cancer among those with less common (9%) AC or CC genotypes (prevalence, 36% vs 39%; OR, 0.97 [95% CI, 0.78-1.20]; P = .76). CONCLUSIONS AND RELEVANCE: In this genome-wide investigation of gene x environment interactions, use of aspirin and/or NSAIDs was associated with lower risk of colorectal cancer, and this association differed according to genetic variation at 2 SNPs at chromosomes 12 and 15. Validation of these findings in additional populations may facilitate targeted colorectal cancer prevention strategies.

Low socioeconomic status has been reported to be associated with head and neck cancer risk. However, previous studies have been too small to examine the associations by cancer subsite, age, sex, global region and calendar time and to explain the association in terms of behavioral risk factors. Individual participant data of 23,964 cases with head and neck cancer and 31,954 controls from 31 studies in 27 countries pooled with random effects models. Overall, low education was associated with an increased risk of head and neck cancer (OR = 2.50; 95% CI = 2.02 - 3.09). Overall one-third of the increased risk was not explained by differences in the distribution of cigarette smoking and alcohol behaviors; and it remained elevated among never users of tobacco and nondrinkers (OR = 1.61; 95% CI = 1.13 - 2.31). More of the estimated education effect was not explained by cigarette smoking and alcohol behaviors: in women than in men, in older than younger groups, in the oropharynx than in other sites, in South/Central America than in Europe/North America and was strongest in countries with greater income inequality. Similar findings were observed for the estimated effect of low versus high household income. The lowest levels of income and educational attainment were associated with more than 2-fold increased risk of head and neck cancer, which is not entirely explained by differences in the distributions of behavioral risk factors for these cancers and which varies across cancer sites, sexes, countries and country income inequality levels.

BACKGROUND: Increasing incidence of head and neck cancer (HNC) in young adults has been reported. We aimed to compare the role of major risk factors and family history of cancer in HNC in young adults and older patients. METHODS: We pooled data from 25 case-control studies and conducted separate analyses for adults 45 years old ('older adults', 17 700 cases and 22 704 controls). Using logistic regression with studies treated as random effects, we estimated adjusted odds ratios (ORs) and 95% confidence intervals (CIs). RESULTS: The young group of cases had a higher proportion of oral tongue cancer (16.0% in women; 11.0% in men) and unspecified oral cavity / oropharynx cancer (16.2%; 11.1%) and a lower proportion of larynx cancer (12.1%; 16.6%) than older adult cases. The proportions of never smokers or never drinkers among female cases were higher than among male cases in both age groups. Positive associations with HNC and duration or pack-years of smoking and drinking were similar across age groups. However, the attributable fractions (AFs) for smoking and drinking were lower in young when compared with older adults (AFs for smoking in young women, older women, young men and older men, respectively, = 19.9% (95% CI = 9.8%, 27.9%), 48.9% (46.6%, 50.8%), 46.2% (38.5%, 52.5%), 64.3% (62.2%, 66.4%); AFs for drinking = 5.3% (-11.2%, 18.0%), 20.0% (14.5%, 25.0%), 21.5% (5.0%, 34.9%) and 50.4% (46.1%, 54.3%). A family history of early-onset cancer was associated with HNC risk in the young [OR = 2.27 (95% CI = 1.26, 4.10)], but not in the older adults [OR = 1.10 (0.91, 1.31)]. The attributable fraction for family history of early-onset cancer was 23.2% (8.60% to 31.4%) in young compared with 2.20% (-2.41%, 5.80%) in older adults. CONCLUSIONS: Differences in HNC aetiology according to age group may exist. The lower AF of cigarette smoking and alcohol drinking in young adults may be due to the reduced length of exposure due to the lower age. Other characteristics, such as those that are inherited, may play a more important role in HNC in young adults compared with older adults.

BACKGROUND:Many SNPs influence prostate cancer risk. To what extent genetic risk can be reduced by environmental factors is unknown. METHODS:We evaluated effect modification by environmental factors of the association between susceptibility SNPs and prostate cancer in 1,230 incident prostate cancer cases and 1,361 controls, all white and similar ages, nested in the Prostate, Lung, Colorectal, and Ovarian (PLCO) Cancer Trial. Genetic risk scores were calculated as number of risk alleles for 20 validated SNPs. We estimated the association between higher genetic risk (≥12 SNPs) and prostate cancer within environmental factor strata and tested for interaction. RESULTS:Men with ≥12 risk alleles had 1.98, 2.04, and 1.91 times the odds of total, advanced, and nonadvanced prostate cancer, respectively. These associations were attenuated with the use of selenium supplements, aspirin, ibuprofen, and higher vegetable intake. For selenium, the attenuation was most striking for advanced prostate cancer: compared with <12 alleles and no selenium, the OR for ≥12 alleles was 2.06 [95% confidence interval (CI), 1.67-2.55] in nonusers and 0.99 (0.38-2.58) in users (Pinteraction = 0.031). Aspirin had the most marked attenuation for nonadvanced prostate cancer: compared with <12 alleles and nonusers, the OR for ≥12 alleles was 2.25 (1.69-3.00) in nonusers and 1.70 (1.25-2.32) in users (Pinteraction = 0.009). This pattern was similar for ibuprofen (Pinteraction = 0.023) and vegetables (Pinteraction = 0.010). CONCLUSIONS:This study suggests that selenium supplements may reduce genetic risk of advanced prostate cancer, whereas aspirin, ibuprofen, and vegetables may reduce genetic risk of nonadvanced prostate cancer. IMPACT/CONCLUSIONS:The effect of genetic factors on prostate cancer risk may vary by lifestyle interventions.

BACKGROUND: Red meat intake has been associated with risk of colorectal cancer, potentially mediated through heterocyclic amines. The metabolic efficiency of N-acetyltransferase 2 (NAT2) required for the metabolic activation of such amines is influenced by genetic variation. The interaction between red meat intake, NAT2 genotype, and colorectal cancer has been inconsistently reported. METHODS: We used pooled individual-level data from the Colon Cancer Family Registry and the Genetics and Epidemiology of Colorectal Cancer Consortium. Red meat intake was collected by each study. We inferred NAT2 phenotype based on polymorphism at rs1495741, highly predictive of enzyme activity. Interaction was assessed using multiplicative interaction terms in multivariate-adjusted models. RESULTS: From 11 studies, 8,290 colorectal cancer cases and 9,115 controls were included. The highest quartile of red meat intake was associated with increased risk of colorectal cancer compared with the lowest quartile [OR, 1.41; 95% confidence interval (CI), 1.29-1.55]. However, a significant association was observed only for studies with retrospective diet data, not for studies with diet prospectively assessed before cancer diagnosis. Combining all studies, high red meat intake was similarly associated with colorectal cancer in those with a rapid/intermediate NAT2 genotype (OR, 1.38; 95% CI, 1.20-1.59) as with a slow genotype (OR, 1.43; 95% CI, 1.28-1.61; P interaction = 0.9). CONCLUSION: We found that high red meat intake was associated with increased risk of colorectal cancer only from retrospective case-control studies and not modified by NAT2 enzyme activity. IMPACT: Our results suggest no interaction between NAT2 genotype and red meat intake in mediating risk of colorectal cancer. Cancer Epidemiol Biomarkers Prev; 24(1); 198-205. (c)2014 AACR.

Height has an extremely polygenic pattern of inheritance. Genome-wide association studies (GWAS) have revealed hundreds of common variants that are associated with human height at genome-wide levels of significance. However, only a small fraction of phenotypic variation can be explained by the aggregate of these common variants. In a large study of African-American men and women (n = 14,419), we genotyped and analyzed 966,578 autosomal SNPs across the entire genome using a linear mixed model variance components approach implemented in the program GCTA (Yang et al Nat Genet 2010), and estimated an additive heritability of 44.7% (se: 3.7%) for this phenotype in a sample of evidently unrelated individuals. While this estimated value is similar to that given by Yang et al in their analyses, we remain concerned about two related issues: (1) whether in the complete absence of hidden relatedness, variance components methods have adequate power to estimate heritability when a very large number of SNPs are used in the analysis; and (2) whether estimation of heritability may be biased, in real studies, by low levels of residual hidden relatedness. We addressed the first question in a semi-analytic fashion by directly simulating the distribution of the score statistic for a test of zero heritability with and without low levels of relatedness. The second question was addressed by a very careful comparison of the behavior of estimated heritability for both observed (self-reported) height and simulated phenotypes compared to imputation R2 as a function of the number of SNPs used in the analysis. These simulations help to address the important question about whether today's GWAS SNPs will remain useful for imputing causal variants that are discovered using very large sample sizes in future studies of height, or whether the causal variants themselves will need to be genotyped de novo in order to build a prediction model that ultimately captures a large fraction of the variability of height, and by implication other complex phenotypes. Our overall conclusions are that when study sizes are quite large (5,000 or so) the additive heritability estimate for height is not apparently biased upwards using the linear mixed model; however there is evidence in our simulation that a very large number of causal variants (many thousands) each with very small effect on phenotypic variance will need to be discovered to fill the gap between the heritability explained by known versus unknown causal variants. We conclude that today's GWAS data will remain useful in the future for causal variant prediction, but that finding the causal variants that need to be predicted may be extremely laborious.

Increasing evidence suggests that the composition of the human gut microbiome is important in the etiology of human diseases; however, the personal factors that influence the gut microbiome composition are poorly characterized. Animal models point to sex hormone-related differentials in microbiome composition. In this study, we investigated the relationship of sex, body mass index (BMI) and dietary fiber intake with the gut microbiome in 82 humans. We sequenced fecal 16S rRNA genes by 454 FLX technology, then clustered and classified the reads to microbial genomes using the QIIME pipeline. Relationships of sex, BMI, and fiber intake with overall gut microbiome composition and specific taxon abundances were assessed by permutational MANOVA and multivariate logistic regression, respectively. We found that sex was associated with the gut microbiome composition overall (p=0.001). The gut microbiome in women was characterized by a lower abundance of Bacteroidetes (p=0.03). BMI (>25 kg/m2 vs. <25 kg/m2) was associated with the gut microbiome composition overall (p=0.05), and this relationship was strong in women (p=0.03) but not in men (p=0.29). Fiber from beans and from fruits and vegetables were associated, respectively, with greater abundance of Actinobacteria (p=0.006 and false discovery rate adjusted q=0.05) and Clostridia (p=0.009 and false discovery rate adjusted q=0.09). Our findings suggest that sex, BMI, and dietary fiber contribute to shaping the gut microbiome in humans. Better understanding of these relationships may have significant implications for gastrointestinal health and disease prevention.