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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.

ObjectiveEarly-onset colorectal cancer (CRC) is increasing in the USA despite rapid declines in older ages. Similar patterns are reported in Australia and Canada, but a comprehensive global analysis of contemporary data is lacking.DesignWe extracted long-term data from Cancer Incidence in Five Continents and supplemental sources to report on worldwide CRC incidence rates and trends by age (20–49 years and ≥50 years) through diagnosis year 2012 or beyond (Australia, Finland, New Zealand, Norway, Sweden, USA).ResultsDuring 2008–2012, age-standardised CRC incidence rates in adults <50 ranged from 3.5 per 100 000 (95% CI 3.2 to 3.9) in India (Chennai) to 12.9 (95% CI 12.6 to 13.3) in Korea. During the most recent decade of available data, incidence in adults <50 was stable in 14 of 36 countries; declined in Austria, Italy and Lithuania; and increased in 19 countries, nine of which had stable or declining trends in older adults (Australia, Canada, Denmark, Germany, New Zealand, Slovenia, Sweden, UK and USA). In Cyprus, Netherlands and Norway, inclines in incidence in young adults were twice as rapid as those in older adults (eg, Norway average annual per cent change (AAPC), 1.9 (95% CI 1.4 to 2.5) vs 0.5 (95% CI 0.3 to 0.7)). Among most high-income countries with long-term data, the uptick in early-onset disease began in the mid-1990s. The steepest increases in young adults were in Korea (AAPC, 4.2 (95% CI 3.4 to 5.0)) and New Zealand (AAPC, 4.0 (95% CI 2.1 to 6.0)).ConclusionCRC incidence increased exclusively in young adults in nine high-income countries spanning three continents, potentially signalling changes in early-life exposures that influence large bowel carcinogenesis.

ObjectiveA 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.DesignWe 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.ResultsCarriage 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.ConclusionsThis study provides supportive evidence that oral microbiota may play a role in the aetiology of pancreatic cancer.

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.

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/m 2 ), 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.

Investigation of microbe-metabolite relationships in the gut is needed to understand and potentially reduce colorectal cancer (CRC) risk. Microbiota and metabolomics profiling were performed on lyophilized feces from 42 CRC cases and 89 matched controls. Multivariable logistic regression was used to identify statistically independent associations with CRC. First principal coordinate-component pair (PCo1-PC1) and false discovery rate (0.05)-corrected P-values were calculated for 116,000 Pearson correlations between 530 metabolites and 220 microbes in a sex*case/control meta-analysis. Overall microbe-metabolite PCo1-PC1 was more strongly correlated in cases than in controls (Rho 0.606 vs 0.201, P = 0.01). CRC was independently associated with lower levels of Clostridia, Lachnospiraceae, p-aminobenzoate and conjugated linoleate, and with higher levels of Fusobacterium, Porphyromonas, p-hydroxy-benzaldehyde, and palmitoyl-sphingomyelin. Through postulated effects on cell shedding (palmitoyl-sphingomyelin), inflammation (conjugated linoleate), and innate immunity (p-aminobenzoate), metabolites mediated the CRC association with Fusobacterium and Porphyromonas by 29% and 34%, respectively. Overall, palmitoyl-sphingomyelin correlated directly with abundances of Enterobacteriaceae (Gammaproteobacteria), three Actinobacteria and five Firmicutes. Only Parabacteroides correlated inversely with palmitoyl-sphingomyelin. Other lipids correlated inversely with Alcaligenaceae (Betaproteobacteria). Six Bonferroni-significant correlations were found, including low indolepropionate and threnoylvaline with Actinobacteria and high erythronate and an uncharacterized metabolite with Enterobacteriaceae. Feces from CRC cases had very strong microbe-metabolite correlations that were predominated by Enterobacteriaceae and Actinobacteria. Metabolites mediated a direct CRC association with Fusobacterium and Porphyromonas, but not an inverse association with Clostridia and Lachnospiraceae. This study identifies complex microbe-metabolite networks that may provide insights on neoplasia and targets for intervention.

Background The oral fungal microbiome (mycobiome) is not well characterized, particularly in relation to oral diseases such as periodontal disease. We aimed to describe and compare the oral mycobiome of subjects with and without periodontal disease. Results We characterized the oral mycobiome in 30 adult subjects (15 with periodontal disease, 15 with good oral health) by sequencing the taxonomically informative pan-fungal internal transcribed spacer (ITS) gene in DNA extracted from oral wash samples. We observed at least 81 genera and 154 fungal species across all samples. Candida and Aspergillus were the most frequently observed genera (isolated from 100% of participants), followed by Penicillium (97%), Schizophyllum (93%), Rhodotorula (90%), and Gibberella (83%). Candida and Aspergillus were also the most highly abundant genera in the samples (median relative abundance = 21% and 44%, respectively). Aspergillus niger was the most highly abundant species in the samples (median relative abundance = 44%). We did not observe significant differences in overall oral mycobiome diversity or composition between participants with periodontal disease and participants with good oral health, nor did we observe significant differences in phylum through species level taxon relative abundance or carriage between the two groups. Genus Candida , previously associated with periodontal disease in culture-based studies, had higher median relative abundance in participants with periodontal disease (33.2%) compared to participants with oral health (2.2%), though the difference was not significant ( p  = 0.52). Additionally, within the periodontal disease group, median relative abundance of Candida increased with increasing number of permanent teeth lost (1–2 teeth lost: 3.2%; 3–4 teeth lost: 16.6%; ≥5 teeth lost: 73.9%; p  = 0.11), though sample size was small for this analysis. Conclusions In this first study comprehensively characterizing the oral mycobiome of adults with periodontal disease or good oral health, we observed trends of higher Candida abundance in participants with periodontal disease, and participants with greater tooth loss. Small sample size may have limited the power to detect significant associations. Larger studies including subgingival samples may further establish the core oral mycobiome in health, and relate it to periodontal disease.

Outdoor fine particulate matter (≤ 2.5 μm; PM2.5) has been identified as a global health threat, but the number of large U.S. prospective cohort studies with individual participant data remains limited, especially at lower recent exposures. We aimed to test the relationship between long-term exposure PM2.5 and death risk from all nonaccidental causes, cardiovascular (CVD), and respiratory diseases in 517,041 men and women enrolled in the National Institutes of Health-AARP cohort. Individual participant data were linked with residence PM2.5 exposure estimates across the continental United States for a 2000-2009 follow-up period when matching census tract-level PM2.5 exposure data were available. Participants enrolled ranged from 50 to 71 years of age, residing in six U.S. states and two cities. Cox proportional hazard models yielded hazard ratio (HR) estimates per 10 μg/m3 of PM2.5 exposure. PM2.5 exposure was significantly associated with total mortality (HR = 1.03; 95% CI: 1.00, 1.05) and CVD mortality (HR = 1.10; 95% CI: 1.05, 1.15), but the association with respiratory mortality was not statistically significant (HR = 1.05; 95% CI: 0.98, 1.13). A significant association was found with respiratory mortality only among never smokers (HR = 1.27; 95% CI: 1.03, 1.56). Associations with 10-μg/m3 PM2.5 exposures in yearly participant residential annual mean, or in metropolitan area-wide mean, were consistent with baseline exposure model results. Associations with PM2.5 were similar when adjusted for ozone exposures. Analyses of California residents alone also yielded statistically significant PM2.5 mortality HRs for total and CVD mortality. Long-term exposure to PM2.5 air pollution was associated with an increased risk of total and CVD mortality, providing an independent test of the PM2.5-mortality relationship in a new large U.S. prospective cohort experiencing lower post-2000 PM2.5 exposure levels. Thurston GD, Ahn J, Cromar KR, Shao Y, Reynolds HR, Jerrett M, Lim CC, Shanley R, Park Y, Hayes RB. 2016. Ambient particulate matter air pollution exposure and mortality in the NIH-AARP Diet and Health cohort. Environ Health Perspect 124:484-490; http://dx.doi.org/10.1289/ehp.1509676.

Oral microbiome dysbiosis is associated with oral disease and potentially with systemic diseases; however, the determinants of these microbial imbalances are largely unknown. In a study of 1204 US adults, we assessed the relationship of cigarette smoking with the oral microbiome. 16S rRNA gene sequencing was performed on DNA from oral wash samples, sequences were clustered into operational taxonomic units (OTUs) using QIIME and metagenomic content was inferred using PICRUSt. Overall oral microbiome composition differed between current and non-current (former and never) smokers ( P <0.001). Current smokers had lower relative abundance of the phylum Proteobacteria (4.6%) compared with never smokers (11.7%) (false discovery rate q =5.2 × 10 −7 ), with no difference between former and never smokers; the depletion of Proteobacteria in current smokers was also observed at class, genus and OTU levels. Taxa not belonging to Proteobacteria were also associated with smoking: the genera Capnocytophaga , Peptostreptococcus and Leptotrichia were depleted, while Atopobium and Streptococcus were enriched, in current compared with never smokers. Functional analysis from inferred metagenomes showed that bacterial genera depleted by smoking were related to carbohydrate and energy metabolism, and to xenobiotic metabolism. Our findings demonstrate that smoking alters the oral microbiome, potentially leading to shifts in functional pathways with implications for smoking-related diseases.

BACKGROUND:Long-term exposure to ambient particulate matter (PM) air pollution is associated with increased cardiovascular disease (CVD); however, the impact of PM on clinical risk factors for CVD in healthy subjects is unclear. We examined the relationship of PM with levels of circulating lipids and blood pressure in the Third National Health and Nutrition Examination Survey (NHANES III), a large nationally representative US survey. METHODS:This study was based on 11,623 adult participants of NHANES III (1988–1994; median age 41.0). Serum lipids and blood pressure were measured during the NHANES III examination. Average exposure for 1988–1994 to particulate matter <10 μm in aerodynamic diameter (PM10) at the residences of participants was estimated based on measurements from US Environmental Protection Agency monitors. Multivariate linear regression was used to estimate the associations of PM10 with lipids and blood pressure. RESULTS:An interquartile range width increase in PM10 exposure (11.1 μg/m) in the study population was associated with 2.42% greater serum triglycerides (95% confidence interval1.09, 3.76); multivariate adjusted means of triglycerides according to increasing quartiles of PM10 were 137.6, 142.5, 142.6, and 148.9 mg/dl, respectively. An interquartile range width increase in PM10 was associated with 1.43% greater total cholesterol (95% confidence interval1.21, 1.66). These relationships with triglycerides and total cholesterol did not differ by age or region. Associations of PM10 with blood pressure were modest. CONCLUSIONS:Findings from this large, diverse study indicate that greater long-term PM10 exposure is associated with elevated serum triglycerides and total cholesterol, potentially mediating air pollution-related effects on CVD.