Faculty Bibliography

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.

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.

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.

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.

BACKGROUND & AIMS/OBJECTIVE: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 (AUC) values, adjusting for study, age, and endoscopy findings 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 AUC value of 0.63 (95% CI, 0.62-0.64) for men and 0.62 (95% CI, 0.61-0.63) for women; AUC 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.

BACKGROUND:Higher sugar consumption may increase cancer risk by promoting insulin-glucose dysregulation, oxidative stress, hormonal imbalances, and excess adiposity. This prospective study investigates the association between dietary sugars(fructose and sucrose) and sugary foods and beverages in relation to combined and site-specific (breast, prostate, colorectal) adiposity-associated cancers. METHODS:The analytic sample consisted of 3,184 adults, aged 26-84y, from the Framingham Offspring cohort. Diet data was first collected between 1991-1995 using a food frequency questionnaire. Intakes of fructose, sucrose, sugary foods and sugary beverages (fruit juice and sugar-sweetened beverages) were derived. Participants were followed up until 2013 to ascertain cancer incidence; 565 doctor-diagnosed adiposity-related cancers, including 124 breast, 157 prostate and 68 colorectal cancers occurred. Multivariable-adjusted Cox proportional hazards models were used to evaluate associations. Tests for interaction with BMI and waist circumference were conducted. RESULTS:No associations were observed between fructose, sucrose, sugary food consumption and combined incidence of adiposity-related cancers or the examined site-specific cancers. While total consumption of sugary beverages was not associated with site-specific cancer risk, higher intakes of fruit juice were associated with 58% increased prostate cancer risk(HR:1.58;95%CI:1.04-2.41) in multivariable-adjusted models. In exploratory stratified analyses, higher sugary beverage intakes increased overall adiposity-related cancer risk by 59% in participants with excessive central adiposity(HR:1.59;95%CI:1.01-2.50)(p-trend=0.057). CONCLUSIONS:In this cohort of American adults, higher sugary beverage consumption was associated with increased cancer risk among participants with central adiposity. IMPACT/CONCLUSIONS:These analyses suggest that avoiding sugary beverages represents a simple dietary modification that may be used as an effective cancer control strategy.

BACKGROUND:Dysbiosis of the oral microbiome can lead to local oral disease and potentially to cancers of the head, neck, and digestive tract. However, little is known regarding exogenous factors contributing to such microbial imbalance. RESULTS:We examined the impact of alcohol consumption on the oral microbiome in a cross-sectional study of 1044 US adults. Bacterial 16S rRNA genes from oral wash samples were amplified, sequenced, and assigned to bacterial taxa. We tested the association of alcohol drinking level (non-drinker, moderate drinker, or heavy drinker) and type (liquor, beer, or wine) with overall microbial composition and individual taxon abundance. The diversity of oral microbiota and overall bacterial profiles differed between heavy drinkers and non-drinkers (α-diversity richness p = 0.0059 and β-diversity unweighted UniFrac p = 0.0036), and abundance of commensal order Lactobacillales tends to be decreased with higher alcohol consumption (fold changes = 0.89 and 0.94 for heavy and moderate drinkers, p trend = 0.005 [q = 0.064]). Additionally, certain genera were enriched in subjects with higher alcohol consumption, including Actinomyces, Leptotrichia, Cardiobacterium, and Neisseria; some of these genera contain oral pathogens, while Neisseria can synthesize the human carcinogen acetaldehyde from ethanol. Wine drinkers may differ from non-drinkers in microbial diversity and profiles (α-diversity richness p = 0.048 and β-diversity unweighted UniFrac p = 0.059) after controlling for drinking amount, while liquor and beer drinkers did not. All significant differences between drinkers and non-drinkers remained after exclusion of current smokers. CONCLUSIONS:Our results, from a large human study of alcohol consumption and the oral microbiome, indicate that alcohol consumption, and heavy drinking in particular, may influence the oral microbiome composition. These findings may have implications for better understanding the potential role that oral bacteria play in alcohol-related diseases.

Importance/UNASSIGNED:Case-control studies show a possible relationship between oral bacteria and head and neck squamous cell cancer (HNSCC). Prospective studies are needed to examine the temporal relationship between oral microbiome and subsequent risk of HNSCC. Objective/UNASSIGNED:To prospectively examine associations between the oral microbiome and incident HNSCC. Design, Setting, and Participants/UNASSIGNED:This nested case-control study was carried out in 2 prospective cohort studies: the American Cancer Society Cancer Prevention Study II Nutrition Cohort (CPS-II) and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). Among 122 004 participants, 129 incident patient cases of HNSCC were identified during an average 3.9 years of follow-up. Two controls per patient case (n = 254) were selected through incidence density sampling, matched on age, sex, race/ethnicity, and time since mouthwash collection. All participants provided mouthwash samples and were cancer-free at baseline. Exposures/UNASSIGNED:Oral microbiome composition and specific bacterial abundances were determined through bacterial 16S rRNA gene sequencing. Overall oral microbiome composition and specific taxa abundances were compared for the case group and the control group, using PERMANOVA and negative binomial generalized linear models, respectively, controlling for age, sex, race, cohort, smoking, alcohol, and oral human papillomavirus-16 status. Taxa with a 2-sided false discovery rate (FDR)-adjusted P-value (q-value) <.10 were considered significant. Main Outcomes and Measures/UNASSIGNED:Incident HNSCC. Results/UNASSIGNED:The study included 58 patient cases from CPS-II (mean [SD] age, 71.0 [6.4] years; 16 [27.6%] women) and 71 patient cases from PLCO (mean [SD] age, 62.7 [4.8] years; 13 [18.3%] women). Two controls per patient case (n = 254) were selected through incidence density sampling, matched on age, sex, race/ethnicity, and time since mouthwash collection. Head and neck squamous cell cancer cases and controls were similar with respect to age, sex, and race. Patients in the case group were more often current tobacco smokers, tended to have greater alcohol consumption (among drinkers), and to be positive for oral carriage of papillomavirus-16. Overall microbiome composition was not associated with risk of HNSCC. Greater abundance of genera Corynebacterium (fold change [FC], 0.58; 95% confidence interval [CI], 0.41-0.80; q = .06) and Kingella (FC, 0.63; 95% CI, 0.46-0.86; q = .08) were associated with decreased risk of HNSCC, potentially owing to carcinogen metabolism capacity. These findings were consistent for both cohorts and by cohort follow-up time. The observed relationships tended to be stronger for larynx cancer and for individuals with a history of tobacco use. Conclusions and Relevance/UNASSIGNED:This study demonstrates that greater oral abundance of commensal Corynebacterium and Kingella is associated with decreased risk of HNSCC, with potential implications for cancer prevention.

BACKGROUND:The United Arab Emirates (UAE) is faced with a rapidly increasing burden of non-communicable diseases including obesity, diabetes, and cardiovascular disease. The UAE Healthy Future study is a prospective cohort designed to identify associations between risk factors and these diseases amongst Emiratis. The study will enroll 20,000 UAE nationals aged ≥18 years. Environmental and genetic risk factors will be characterized and participants will be followed for future disease events. As this was the first time a prospective cohort study was being planned in the UAE, a pilot study was conducted in 2015 with the primary aim of establishing the feasibility of conducting the study. Other objectives were to evaluate the implementation of the main study protocols, and to build adequate capacity to conduct advanced clinical laboratory analyses. METHODS:Seven hundred sixty nine UAE nationals aged ≥18 years were invited to participate voluntarily in the pilot study. Participants signed an informed consent, completed a detailed questionnaire, provided random blood, urine, and mouthwash samples and were assessed for a series of clinical measures. All specimens were transported to the New York University Abu Dhabi laboratories where samples were processed and analyzed for routine chemistry and hematology. Plasma, serum, and a small whole blood sample for DNA extraction were aliquoted and stored at -80 °C for future analyses. RESULTS:Overall, 517 Emirati men and women agreed to participate (68% response rate). Of the total participants, 495 (95.0%), 430 (82.2%), and 492 (94.4%), completed the questionnaire, physical measurements, and provided biological samples, respectively. CONCLUSIONS:The pilot study demonstrated the feasibility of recruitment and completion of the study protocols for the first large-scale cohort study designed to identify emerging risk factors for the major non-communicable diseases in the region.