Faculty Bibliography

INTRODUCTION/BACKGROUND:Self-reported tobacco use in the United Arab Emirates is among the highest in the region. Use of tobacco products other than cigarettes is widespread, but little is known about specific behavior use patterns. There have been no studies that have biochemically verified smoking status. METHODS:The UAE Healthy Future Study (UAEHFS) seeks to understand the causes of non-communicable diseases through a 20,000-person cohort study. During the study pilot, 517 Emirati nationals were recruited to complete a questionnaire, provide clinical measurements and biological samples. Complete smoking data were available for 428 participants. Validation of smoking status via cotinine testing was conducted based on complete questionnaire data and matching urine samples for 399 participants, using a cut-off of 200ng/ml to indicate active smoking status. RESULTS:Self-reported tobacco use was 36% among men and 3% among women in the sample. However, biochemical verification of smoking status revealed that 42% men and 9% of women were positive for cotinine indicating possible recent tobacco use. Dual and poly-use of tobacco products was fairly common with 32% and 6% of the sample reporting respectively. CONCLUSIONS:This is the first study in the region to biochemically verify tobacco use self-report data. Tobacco use in this study population was found to be higher than previously thought, especially among women. Misclassification of smoking status was more common than expected. Poly-tobacco use was also very common. Additional studies are needed to understand tobacco use behaviors and the extent to which people may be exposed to passive tobacco smoke. IMPLICATIONS/CONCLUSIONS:This study is the first in the region to biochemically verify self-reported smoking status.

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.

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.

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.

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.

Population-based epidemiologic studies can provide important insight regarding the role of the microbiome in human health and disease. Buccal cells samples using commercial mouthwash have been obtained in large prospective cohorts for the purpose of studying human genomic DNA. We aimed to better understand if these mouthwash samples are also a valid resource for the study of the oral microbiome. We collected one saliva sample and one Scope mouthwash sample from 10 healthy subjects. Bacterial 16S rRNA genes from both types of samples were amplified, sequenced, and assigned to bacterial taxa. We comprehensively compared these paired samples for bacterial community composition and individual taxonomic abundance. We found that mouthwash samples yielded similar amount of bacterial DNA as saliva samples (p from Student's t-test for paired samples = 0.92). Additionally, the paired samples had similar within sample diversity (p from = 0.33 for richness, and p = 0.51 for Shannon index), and clustered as pairs for diversity when analyzed by unsupervised hierarchical cluster analysis. No significant difference was found in the paired samples with respect to the taxonomic abundance of major bacterial phyla, Bacteroidetes, Firmicutes, Proteobacteria, Fusobacteria, and Actinobacteria (FDR adjusted q values from Wilcoxin signed-rank test = 0.15, 0.15, 0.87, 1.00 and 0.15, respectively), and all identified genera, including genus Streptococcus (q = 0.21), Prevotella (q = 0.25), Neisseria (q = 0.37), Veillonella (q = 0.73), Fusobacterium (q = 0.19), and Porphyromonas (q = 0.60). These results show that mouthwash samples perform similarly to saliva samples for analysis of the oral microbiome. Mouthwash samples collected originally for analysis of human DNA are also a resource suitable for human microbiome research.

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.

When some individuals are screen-detected before the beginning of the study, but otherwise would have been diagnosed symptomatically during the study, this results in different case-ascertainment probabilities among screened and unscreened participants, referred to here as lead-time-biased case-ascertainment (LTBCA). In fact, this issue can arise even in risk-factor studies nested within a randomized screening trial; even though the screening intervention is randomly allocated to trial arms, there is no randomization to potential risk-factors and uptake of screening can differ by risk-factor strata. Under the assumptions that neither screening nor the risk factor affects underlying incidence and no other forms of bias operate, we simulate and compare the underlying cumulative incidence and that observed in the study due to LTBCA. The example used will be constructed from the randomized Prostate, Lung, Colorectal, and Ovarian cancer screening trial. The derived mathematical model is applied to simulating two nested studies to evaluate the potential for screening bias in observational lung cancer studies. Because of differential screening under plausible assumptions about preclinical incidence and duration, the simulations presented here show that LTBCA due to chest x-ray screening can significantly increase the estimated risk of lung cancer due to smoking by 1% and 50%. Traditional adjustment methods cannot account for this bias, as the influence screening has on observational study estimates involves events outside of the study observation window (enrollment and follow-up) that change eligibility for potential participants, thus biasing case ascertainment.

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.

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.