Faculty Bibliography

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.

OBJECTIVE: A history of periodontal disease and the presence of circulating antibodies to selected oral pathogens have been associated with increased risk of pancreatic cancer; however, direct relationships of oral microbes with pancreatic cancer have not been evaluated in prospective studies. We examine the relationship of oral microbiota with subsequent risk of pancreatic cancer in a large nested case-control study. DESIGN: We selected 361 incident adenocarcinoma of pancreas and 371 matched controls from two prospective cohort studies, the American Cancer Society Cancer Prevention Study II and the National Cancer Institute Prostate, Lung, Colorectal and Ovarian Cancer Screening Trial. From pre-diagnostic oral wash samples, we characterised the composition of the oral microbiota using bacterial 16S ribosomal RNA (16S rRNA) gene sequencing. The associations between oral microbiota and risk of pancreatic cancer, controlling for the random effect of cohorts and other covariates, were examined using traditional and L1-penalised least absolute shrinkage and selection operator logistic regression. RESULTS: Carriage of oral pathogens, Porphyromonas gingivalis and Aggregatibacter actinomycetemcomitans, were associated with higher risk of pancreatic cancer (adjusted OR for presence vs absence=1.60 and 95% CI 1.15 to 2.22; OR=2.20 and 95% CI 1.16 to 4.18, respectively). Phylum Fusobacteria and its genus Leptotrichia were associated with decreased pancreatic cancer risk (OR per per cent increase of relative abundance=0.94 and 95% CI 0.89 to 0.99; OR=0.87 and 95% CI 0.79 to 0.95, respectively). Risks related to these phylotypes remained after exclusion of cases that developed within 2 years of sample collection, reducing the likelihood of reverse causation in this prospective study. CONCLUSIONS: This study provides supportive evidence that oral microbiota may play a role in the aetiology of pancreatic cancer.

BACKGROUND: Daily aspirin use has been recommended for secondary prevention of cardiovascular disease, but its use for primary prevention remains controversial. METHODS: We followed 440,277 men and women from the NIH-AARP Diet and Health Study (ages 50-71) and the Prostate, Lung, Colorectal, and Ovarian Cancer Screening Trial (ages 55-74) for mortality for 13 years on average. Frequency of aspirin use was ascertained through self-report, and cause of death by death certificates. We calculated multivariate hazard ratios (HRs) and 95% confidence intervals (CI) for mortality using Cox proportional hazards models for each cohort and combined by meta-analysis. RESULTS: We found a consistent U-shaped relationship between aspirin use and mortality in both studies, with differential risk patterns for cardiovascular mortality by disease history. Among individuals with a history of cardiovascular disease, daily aspirin use was associated with reduced cardiovascular mortality [HR=0.78 (95% CI 0.74-0.82)]. However, among those without a previous history, we observed no protection for daily aspirin users [HR=1.06 (1.02-1.11)], and elevated risk of cardiovascular mortality for those taking aspirin twice daily or more [HR=1.29 (1.19-1.39)]. Elevated risk persisted even among participants who lived beyond 5 years of follow-up and used aspirin without other nonsteroidal anti-inflammatory drugs [HR=1.31 (1.17-1.47)]. CONCLUSIONS: Results from these two large population-based U.S. cohorts confirm the utility of daily aspirin use for secondary prevention of cardiovascular mortality; however, our data suggest that caution should be exercised in more frequent use, particularly among individuals without a history of cardiovascular disease.

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.

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.

United States Veterans are at excess risk for type 2 diabetes, but population differentials in risk have not been characterized. We determined risk of type 2 diabetes in relation to prediabetes and dyslipidemic profiles in Veterans at the VA New York Harbor (VA NYHHS) during 2004-2014. Prediabetes was based on American Diabetes Association hemoglobin A1c (HbA1c) testing cut-points, one of several possible criteria used to define prediabetes. We evaluated transition to type 2 diabetes in 4,297 normoglycemic Veterans and 7,060 Veterans with prediabetes. Cox proportional hazards regression was used to relate HbA1c levels, lipid profiles, demographic, anthropometric and comorbid cardiovascular factors to incident diabetes (Hazard Ratio [HR] and 95% confidence intervals). Compared to normoglycemic Veterans (HbA1c: 5.0-5.6%; 31-38 mmol/mol), risks for diabetes were >2-fold in the moderate prediabetes risk group (HbA1c: 5.7-5.9%; 39-41 mmol/mol) (HR 2.37 [1.98-2.85]) and >5-fold in the high risk prediabetes group (HbA1c: 6.0-6.4%; 42-46 mmol/mol) (HR 5.59 [4.75-6.58]). Risks for diabetes were increased with elevated VLDL (≥40mg/dl; HR 1.31 [1.09-1.58]) and TG/HDL (≥1.5mg/dl; HR 1.34 [1.12-1.59]), and decreased with elevated HDL (≥35mg/dl; HR 0.80 [0.67-0.96]). Transition to diabetes in Veterans was related in age-stratified risk score analyses to HbA1c, VLDL, HDL and TG/HDL, BMI, hypertension and race, with 5-year risk differentials of 62% for the lowest (5-year risk, 13.5%) vs. the highest quartile (5-year risk, 21.9%) of the risk score. This investigation identified substantial differentials in risk of diabetes in Veterans, based on a readily-derived risk score suitable for risk stratification for type 2 diabetes prevention.