Faculty Bibliography

BACKGROUND: Concordance with the Dietary Approaches to Stop Hypertension (DASH) diet has been shown to reduce blood pressure (BP) in short-term intervention studies, but long-term effects are unclear. We evaluated the association of DASH diet concordance with BP trajectories and incidence of hypertension, in 2187 men and women (mean age 52.5 years at baseline) participating in the Framingham Offspring cohort. METHOD: Diet and BP were assessed from 1991 to 2008, with a median follow-up time of 13.4 years. DASH scores (ranging from 0 for worst to 10 for best concordance with DASH diet) were calculated by summing 10 food components that comprise the DASH diet pattern, including fruits and vegetables, low-fat dairy products, lean meat, and plant-based protein. Mixed-effect and Cox regression models were applied, to assess the association of DASH diet concordance with BP longitudinal change and with incidence of hypertension, respectively. All analyses were adjusted for age, sex, smoking status, history of diabetes, BMI, and physical activity. RESULT: Overall, SBP increased by 0.34 mmHg and DBP by 0.10 mmHg annually, in the Framingham Offspring cohort. Every unit increase in the DASH score resulted in a modest increase in SBP of 0.054 mmHg/year (P = 0.028). No associations were observed between DASH diet concordance and DBP or incidence of hypertension. CONCLUSION: Long-term concordance with the DASH diet was not associated with a decreasing BP trajectory over time, or with decreased incidence of hypertension, in this population of middle-aged adults.

PURPOSE: The insulin-signaling pathway plays a pivotal role in cancer biology; however, evidence of genetic alterations in human studies is limited. This case-control study nested within the Framingham Heart Study (FHS) examined the association between inherited genetic variation in the insulin receptor (INSR) gene and obesity-related cancer risk. METHODS: The study sample consisted of 1,475 controls and 396 cases from the second familial generation of the FHS. Participants who provided consent were genotyped. Nineteen single-nucleotide polymorphisms (SNPs) in the INSR gene were investigated in relation to risk of obesity-related cancers combined and breast, prostate and colorectal cancers. Generalized estimation equation models controlling for familial correlations and include age, sex, smoking and body mass index as covariates, assuming additive models, were used. RESULTS: Three SNPs, rs2059807, s8109559 and rs919275, were significantly associated with obesity-related cancers (p value < 0.02) with the most significantly associated SNP being rs2059807 (p value = 0.008). Carriers of two copies of SNP rs2059807 risk allele T were significantly less prevalent among subjects with obesity-related cancers [f(TT)cases = 14 vs. f(TT)controls = 18 %; OR 1.23]. In exploratory analyses evaluating site-specific cancers, the INSR rs2059807 association with these cancers was consistent with that observed for the main outcome (ORs colorectal cancer = 1.5, breast cancer = 1.29, prostate = 1.06). There was no statistically significant interaction between the INSR-SNP and blood glucose in relation to obesity-related cancer. CONCLUSIONS: The INSR gene is implicated in obesity-related cancer risk, as 3 of 19 SNPs were nominally associated, after false discovery rate (FDR) correction, with the main outcome. Risk allele homozygotes (rs2059807) were less prevalent among subjects with obesity-related cancer. These results should be replicated in other populations to confirm the findings.

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.

BACKGROUND: High body mass index (BMI) is consistently linked to increased risk of colorectal cancer for men, whereas the association is less clear for women. As risk estimates from observational studies may be biased and/or confounded, we conducted a Mendelian randomization study to estimate the causal association between BMI and colorectal cancer. METHODS: We used data from 10,226 colorectal cancer cases and 10,286 controls of European ancestry. The Mendelian randomization analysis used a weighted genetic risk score, derived from 77 genome-wide association study-identified variants associated with higher BMI, as an instrumental variable (IV). We compared the IV odds ratio (IV-OR) with the OR obtained using a conventional covariate-adjusted analysis. RESULTS: Individuals carrying greater numbers of BMI-increasing alleles had higher colorectal cancer risk [per weighted allele OR, 1.31; 95% confidence interval (CI), 1.10-1.57]. Our IV estimation results support the hypothesis that genetically influenced BMI is directly associated with risk for colorectal cancer (IV-OR per 5 kg/m(2), 1.50; 95% CI, 1.13-2.01). In the sex-specific IV analyses higher BMI was associated with higher risk of colorectal cancer among women (IV-OR per 5 kg/m(2), 1.82; 95% CI, 1.26-2.61). For men, genetically influenced BMI was not associated with colorectal cancer (IV-OR per 5 kg/m(2), 1.18; 95% CI, 0.73-1.92). CONCLUSIONS: High BMI was associated with increased colorectal cancer risk for women. Whether abdominal obesity, rather than overall obesity, is a more important risk factor for men requires further investigation. IMPACT: Overall, conventional epidemiologic and Mendelian randomization studies suggest a strong association between obesity and the risk of colorectal cancer. Cancer Epidemiol Biomarkers Prev; 24(7); 1024-31. (c)2015 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.

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.

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.

BACKGROUND: Cross-sectional studies have shown associations between arsenic exposure and prevalence of high BP; however, studies examining the relationship of arsenic exposure with longitudinal changes in blood pressure are lacking. METHOD: We evaluated associations of arsenic exposure in relation to longitudinal change in blood pressure in 10,853 participants in the Health Effects of Arsenic Longitudinal Study (HEALS). Arsenic was measured in well water and in urine samples at baseline and in urine samples every two years after baseline. Mixed effect models were used to estimate the association of baseline well and urinary creatinine-adjusted arsenic with blood pressure annual change during follow-up (median, 6.7 years). RESULT: In the HEALS population, the median water arsenic concentration at baseline was 62 microg/L. Individuals in the highest quartile of baseline water arsenic or urinary creatinine-adjusted arsenic had a greater annual increase in SBP compared with those in the reference group (beta=0.48 mmHg/year; 95% CI: 0.35-0.61, and beta=0.43 mmHg/year; 95% CI: 0.29-0.56) for water arsenic and urinary creatinine-adjusted arsenic, respectively) in fully adjusted models. Likewise, individuals in the highest quartile of baseline arsenic exposure had a greater annual increase in DBP (beta=0.39 mmHg/year; 95% CI: 0.30, 0.49, and beta=0.45 mmHg/year; 95% CI: 0.36, 0.55) for water arsenic and urinary creatinine-adjusted arsenic, respectively) compared with those in the lowest quartile. CONCLUSION: Our findings suggest that long-term arsenic exposure may accelerate age-related increases in blood pressure. These findings may help explain associations between arsenic exposure and cardiovascular disease.

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.