Faculty Bibliography

Objective/UNASSIGNED:'Environmental' factors associated with colorectal cancer (CRC) risk include modifiable and non-modifiable variables. Whether those with different non-modifiable baseline risks will benefit similarly from reducing their modifiable CRC risks remains unclear. Design/UNASSIGNED:Using 7945 cases and 8893 controls from 11 population-based studies, we combined 17 risk factors to characterise the overall environmental predisposition to CRC (environmental risk score (E-score)). We estimated the absolute risks (ARs) of CRC of 10 and 30 years across E-score using incidence-rate data from the Surveillance, Epidemiology, and End Results programme. We then combined the modifiable risk factors and estimated ARs across the modifiable risk score, stratified by non-modifiable risk profile based on genetic predisposition, family history and height. Results/UNASSIGNED:, 1.33; 95% CI 1.30 to 1.37). Across E-scores, 30-year ARs of CRC increased from 2.5% in the lowest quartile (Q1) to 5.9% in the highest (Q4) quartile for men, and from 2.1% to 4.5% for women. The modifiable risk score had a stronger association in those with high non-modifiable risk (relative excess risk due to interaction=1.2, 95% CI 0.5 to 1.9). For those in Q4 of non-modifiable risk, a decrease in modifiable risk reduced 30-year ARs from 8.9% to 3.4% for men and from 6.0% to 3.2% for women, a level lower or comparable to the average population risk. Conclusions/UNASSIGNED:Changes in modifiable risk factors may result in a substantial decline in CRC risk in both sexes. Those with high inherited risk may reap greater benefit from lifestyle modifications. Our results suggested comprehensive evaluation of environmental factors may facilitate CRC risk stratification.

Increasing evidence indicates that gut microbiota may influence colorectal cancer risk. Diet, particularly fibre intake, may modify gut microbiota composition, which may affect cancer risk. We investigated the relationship between dietary fibre intake and gut microbiota in adults. Using 16S rRNA gene sequencing, we assessed gut microbiota in faecal samples from 151 adults in two independent study populations: National Cancer Institute (NCI), n 75, and New York University (NYU), n 76. We calculated energy-adjusted fibre intake based on FFQ. For each study population with adjustment for age, sex, race, BMI and smoking, we evaluated the relationship between fibre intake and gut microbiota community composition and taxon abundance. Total fibre intake was significantly associated with overall microbial community composition in NYU (P=0·008) but not in NCI (P=0·81). In a meta-analysis of both study populations, higher fibre intake tended to be associated with genera of class Clostridia, including higher abundance of SMB53 (fold change (FC)=1·04, P=0·04), Lachnospira (FC=1·03, P=0·05) and Faecalibacterium (FC=1·03, P=0·06), and lower abundance of Actinomyces (FC=0·95, P=0·002), Odoribacter (FC=0·95, P=0·03) and Oscillospira (FC=0·96, P=0·06). A species-level meta-analysis showed that higher fibre intake was marginally associated with greater abundance of Faecalibacterium prausnitzii (FC=1·03, P=0·07) and lower abundance of Eubacterium dolichum (FC=0·96, P=0·04) and Bacteroides uniformis (FC=0·97, P=0·05). Thus, dietary fibre intake may impact gut microbiota composition, particularly class Clostridia, and may favour putatively beneficial bacteria such as F. prausnitzii. These findings warrant further understanding of diet-microbiota relationships for future development of colorectal cancer prevention strategies.

BACKGROUND:Several studies have examined association between human papillomaviruses (HPVs) and esophageal cancer, but results have been inconsistent. This is the first prospective study to investigate associations between alpha, beta and gamma HPV detection in the oral cavity and risk of esophageal cancer. METHODS:We conducted a nested case-control study among 96,650 cancer-free participants in the American Cancer Society Cancer Prevention Cohort and the Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. Incident esophageal cancer cases (n=125) were identified during an average 3.9 years of follow-up. Three controls per case (n=372) were selected and matched on age, sex, race/ethnicity and time since mouthwash collection. Alpha, beta and gamma HPV DNA in oral samples was detected using a next-generation sequencing assay. Conditional logistic regression models were used to estimate odds ratios (OR) and 95% confidence intervals (CI), adjusting for smoking and alcohol consumption. Statistical significance was evaluated using permutation test. RESULTS:Prevalence of oral alpha, beta, and gamma HPV was 18.4%, 64.8%, and 42.4% in cases and 14.3%, 55.1%, and 33.6% in controls, respectively. Oral HPV16 detection was not associated with esophageal cancer (OR=0.54, 95%CI 0.1-4.84) and none of the esophageal squamous cell carcinoma cases (n=28) were HPV16 positive. Some oral HPV types were more common in cases than controls; however, none of the associations were statistically significant. CONCLUSION/CONCLUSIONS:Although HPVs in oral cavity are very common, this study showed no evidence of association between oral HPVs and esophageal cancer. IMPACT/CONCLUSIONS:Oral HPVs may not contribute to risk of esophageal cancer.

Exposure to ambient fine particulate matter (PM_2.5) is a major global health concern. Quantitative estimates of attributable mortality are based on disease-specific hazard ratio models that incorporate risk information from multiple PM_2.5 sources (outdoor and indoor air pollution from use of solid fuels and secondhand and active smoking), requiring assumptions about equivalent exposure and toxicity. We relax these contentious assumptions by constructing a PM_2.5-mortality hazard ratio function based only on cohort studies of outdoor air pollution that covers the global exposure range. We modeled the shape of the association between PM_2.5 and nonaccidental mortality using data from 41 cohorts from 16 countries-the Global Exposure Mortality Model (GEMM). We then constructed GEMMs for five specific causes of death examined by the global burden of disease (GBD). The GEMM predicts 8.9 million [95% confidence interval (CI): 7.5-10.3] deaths in 2015, a figure 30% larger than that predicted by the sum of deaths among the five specific causes (6.9; 95% CI: 4.9-8.5) and 120% larger than the risk function used in the GBD (4.0; 95% CI: 3.3-4.8). Differences between the GEMM and GBD risk functions are larger for a 20% reduction in concentrations, with the GEMM predicting 220% higher excess deaths. These results suggest that PM_2.5 exposure may be related to additional causes of death than the five considered by the GBD and that incorporation of risk information from other, nonoutdoor, particle sources leads to underestimation of disease burden, especially at higher concentrations.

OBJECTIVE:Recent mechanistic and epidemiological evidence implicates air pollution as a potential risk factor for diabetes; however, mortality risks have not been evaluated in a large US cohort assessing exposures to multiple pollutants with detailed consideration of personal risk factors for diabetes. RESEARCH DESIGN AND METHODS/METHODS:. Associations between the air pollutants and the risk of diabetes mortality (N = 3598) were evaluated using multivariate Cox proportional hazards models adjusted for both individual-level and census-level contextual covariates. RESULTS:(HR = 1.09; 95% CI: 1.01-1.18 per 10 ppb). The strength of the relationship was robust to alternate exposure assessments and model specifications. We also observed significant effect modification, with elevated mortality risks observed among those with higher BMI and lower levels of fruit consumption. CONCLUSIONS:, is related to increased risk of diabetes mortality in the U.S, with attenuation of adverse effects by lower BMI and higher fruit consumption, suggesting that air pollution is involved in the etiology and/or control of diabetes.

Cigarette smoking alters the oral microbiome; however, the effect of alternative tobacco products remains unclear. Middle Eastern tobacco products like dokha and shisha, are becoming globally widespread. We tested for the first time in a Middle Eastern population the hypothesis that different tobacco products impact the oral microbiome. The oral microbiome of 330 subjects from the United Arab Emirates Healthy Future Study was assessed by amplifying the bacterial 16S rRNA gene from mouthwash samples. Tobacco consumption was assessed using a structured questionnaire and further validated by urine cotinine levels. Oral microbiome overall structure and specific taxon abundances were compared, using PERMANOVA and DESeq analyses respectively. Our results show that overall microbial composition differs between smokers and nonsmokers (p = 0.0001). Use of cigarettes (p = 0.001) and dokha (p = 0.042) were associated with overall microbiome structure, while shisha use was not (p = 0.62). The abundance of multiple genera were significantly altered (enriched/depleted) in cigarette smokers; however, only Actinobacillus, Porphyromonas, Lautropia and Bifidobacterium abundances were significantly changed in dokha users whereas no genera were significantly altered in shisha smokers. For the first time, we show that smoking dokha is associated to oral microbiome dysbiosis, suggesting that it could have similar effects as smoking cigarettes on oral health.

Background: The oral microbiota play a central role in oral health, and possibly in carcinogenesis. Research suggests that coffee and tea consumption may have beneficial health effects. We examined the associations of these common beverages with the oral ecosystem in a large cross-sectional study.Methods: We assessed oral microbiota in mouthwash samples from 938 participants in two U.S. cohorts using 16S rRNA gene sequencing. Coffee and tea intake were assessed from food frequency questionnaires. We examined associations of coffee and tea intake with overall oral microbiota diversity and composition using linear regression and permutational MANOVA, respectively, and with taxon abundance using negative binomial generalized linear models; all models adjusted for age, sex, cohort, body mass index, smoking, ethanol intake, and energy intake.Results: Higher tea intake was associated with greater oral microbiota richness (P = 0.05) and diversity (P = 0.006), and shifts in overall community composition (P = 0.002); coffee was not associated with these microbiome parameters. Tea intake was associated with altered abundance of several oral taxa; these included Fusobacteriales, Clostridiales, and Shuttleworthia satelles (higher with increasing tea) and Bifidobacteriaceae, Bergeyella, Lactobacillales, and Kingella oralis (lower with increasing tea). Higher coffee intake was only associated with greater abundance of Granulicatella and Synergistetes.Conclusions: In the largest study to date of tea and coffee consumption in relation to the oral microbiota, the microbiota of tea drinkers differed in several ways from nondrinkers.Impact: Tea-driven changes to the oral microbiome may contribute to previously observed associations between tea and oral and systemic diseases, including cancers. Cancer Epidemiol Biomarkers Prev; 27(7); 814-21. ©2018 AACR.

Case-control studies suggest that higher whole grain and lower refined grain intakes are associated with reduced cancer risk, but longitudinal evidence is limited. The objective of this prospective cohort study is to evaluate associations between whole and refined grains and their food sources in relation to adiposity-related cancer risk. Participants were adults from the Framingham Offspring cohort (N = 3,184; ≥18 yr). Diet, measured using a food frequency questionnaire, medical and lifestyle data were collected at exam 5 (1991-95). Between 1991 and 2013, 565 adiposity-related cancers were ascertained using pathology reports. Cox proportional hazards models were used to estimate adjusted hazard ratios and 95% confidence intervals for associations of whole and refined grains with risk of adiposity-related cancers combined and with risk of breast and prostate cancers in exploratory site-specific analyses. Null associations between whole and refined grains and combined incidence of adiposity-related cancers were observed in multivariable-adjusted models (HR: 0.94; 95% CI: 0.71-1.23 and HR: 0.98; 95% CI: 0.70-1.38, respectively). In exploratory analyses, higher intakes of whole grains (oz eq/day) and whole grain food sources (servings/day) were associated with 39% and 47% lower breast cancer risk (HR: 0.61; 95% CI: 0.38-0.98 and HR: 0.53; 95% CI: 0.33-0.86, respectively). In conclusion, whole and refined grains were not associated with adiposity-related cancer risk. Whole grains may protect against breast cancer, but findings require confirmation within a larger sample and in other ethnic groups.

Animal models suggest that gut microbiota contribute to obesity; however, a consistent taxonomic signature of obesity has yet to be identified in humans. We examined whether a taxonomic signature of obesity is present across two independent study populations. We assessed gut microbiome from stool for 599 adults, by 16S rRNA gene sequencing. We compared gut microbiome diversity, overall composition, and individual taxon abundance for obese (BMI ≥ 30 kg/m²), overweight (25 ≤ BMI < 30), and healthy-weight participants (18.5 ≤ BMI < 25). We found that gut species richness was reduced (p = 0.04), and overall composition altered (p = 0.04), in obese (but not overweight) compared to healthy-weight participants. Obesity was characterized by increased abundance of class Bacilli and its families Streptococcaceae and Lactobacillaceae, and decreased abundance of several groups within class Clostridia, including Christensenellaceae, Clostridiaceae, and Dehalobacteriaceae (q < 0.05). These findings were consistent across two independent study populations. When random forest models were trained on one population and tested on the other as well as a previously published dataset, accuracy of obesity prediction was good (~70%). Our large study identified a strong and consistent taxonomic signature of obesity. Though our study is cross-sectional and causality cannot be determined, identification of microbes associated with obesity can potentially provide targets for obesity prevention and treatment.

Temporal variation in microbiome measurements can reduce power. Quantification of this variation is essential for designing chronic disease studies. We analyzed 16S rRNA profiles in paired specimens separated by six months from three studies. We evaluated temporal stability by calculating intraclass correlation coefficients (ICCs). Sample sizes to detect microbiome differences between equal numbers of cases and controls for a nested case-control design were calculated based on estimated ICCs. Across body sites, 12 phylum-level ICCs were greater than 0.5. Similarly, 11 alpha-diversity ICCs were greater than 0.5. Fecal beta diversity estimates had ICCs over 0.5. For a single collection with most microbiome metrics, detecting an odds ratio (OR) of 2.0 would require 300-500 cases when matching one case to one control at P = 0.05. Two or three sequential specimens reduce the number of required subjects by 40%-50% for low-ICC metrics. Relative abundances of major phyla and alpha diversity metrics have low temporal stability. Thus, detecting associations of moderate effect size with these metrics will require large sample sizes. As beta-diversity for feces is reasonably stable over time, smaller sample sizes can detect associations with community composition. Sequential pre-diagnostic specimens from thousands of prospectively ascertained cases are required to detect modest disease associations with particular microbiome metrics.