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Association of Coffee and Tea Intake with the Oral Microbiome: Results from a Large Cross-Sectional Study Published OnlineFirst April 27, 2018; DOI: 10.1158/1055-9965.EPI-18-0184 Research Article Cancer Epidemiology, Biomarkers Association of Coffee and Tea Intake with the Oral & Prevention Microbiome: Results from a Large Cross-Sectional Study Brandilyn A. Peters1, Marjorie L. McCullough2, Mark P. Purdue3, Neal D. Freedman3, Caroline Y. Um2, Susan M. Gapstur2, Richard B. Hayes1,4, and Jiyoung Ahn1,4 Abstract Background: The oral microbiota play a central role in oral shifts in overall community composition (P ¼ 0.002); coffee health, and possibly in carcinogenesis. Research suggests that was not associated with these microbiome parameters. Tea coffee and tea consumption may have beneficial health effects. intake was associated with altered abundance of several We examined the associations of these common beverages with oral taxa; these included Fusobacteriales, Clostridiales, the oral ecosystem in a large cross-sectional study. and Shuttleworthia satelles (higher with increasing tea) and Methods: We assessed oral microbiota in mouthwash samples Bifidobacteriaceae, Bergeyella, Lactobacillales, and Kingella from 938 participants in two U.S. cohorts using 16S rRNA gene oralis (lower with increasing tea). Higher coffee intake was sequencing. Coffee and tea intake were assessed from food fre- only associated with greater abundance of Granulicatella and quency questionnaires. We examined associations of coffee and Synergistetes. tea intake with overall oral microbiota diversity and composition Conclusions: In the largest study to date of tea and coffee using linear regression and permutational MANOVA, respective- consumption in relation to the oral microbiota, the microbiota of ly, and with taxon abundance using negative binomial general- tea drinkers differed in several ways from nondrinkers. ized linear models; all models adjusted for age, sex, cohort, body Impact: Tea-driven changes to the oral microbiome may con- mass index, smoking, ethanol intake, and energy intake. tribute to previously observed associations between tea and oral Results: Higher tea intake was associated with greater oral and systemic diseases, including cancers. Cancer Epidemiol Biomarkers microbiota richness (P ¼ 0.05) and diversity (P ¼ 0.006), and Prev; 27(7); 814–21. Ó2018 AACR. Introduction food metabolic pathways (7); at the same time, dietary exposures lead to ecological adaptation and selection of the microbial The oral microbiome, comprising more than 600 bacterial community (7). species (1), plays a central role in the maintenance of oral health Coffee and tea are commonly consumed beverages among (2). Consequently, dysbiosis of microbiota in dental plaques can Americans (8, 9), and both have received attention for purported cause the oral diseases of periodontitis and caries (3). Addition- health benefits. Reports from large cohort studies indicate a robust ally, oral dysbiosis has been associated with systemic cancers, inverse association of coffee consumption with total mortality including head and neck cancer (4), pancreatic cancer (5), and and cause-specific mortality from cancer (10–12). Similar find- esophageal cancer (6). While the importance of the oral micro- ings have been reported for tea consumption (13–15), though biome in human health is becoming increasingly clear, little is effects may differ for green versus black tea (14). Coffee and tea known regarding factors that influence oral microbiome compo- have also been inversely associated with head and neck cancer risk sition. The human oral microbiota comes into direct contact (16–18), while tea may also prevent dental caries, periodontitis, with orally ingested dietary factors, undoubtedly contributing to and tooth loss (19–21). Both coffee and tea are complex mixtures containing many biologically active compounds, including caf- feine and polyphenols, which may have antioxidant, antimuta- 1Division of Epidemiology, Department of Population Health, NYU School of genic, antiproliferative, and/or anti-inflammatory effects Medicine, New York, New York. 2Epidemiology Research Program, American (22–24); a wide variety of mechanisms may contribute to disease Cancer Society, Atlanta, Georgia. 3Division of Cancer Epidemiology and protection at different systemic sites. 4 Genetics, National Cancer Institute, Bethesda, Maryland. NYU Perlmutter Some evidence suggests that coffee and tea drinking may affect Cancer Center, New York, New York. the oral microbiome (25–27), which could be a further mecha- Note: Supplementary data for this article are available at Cancer Epidemiology, nism for the effects of these beverages on oral and/or systemic Biomarkers & Prevention Online (http://cebp.aacrjournals.org/). health, including their chemopreventive properties. However, the Corresponding Author: Jiyoung Ahn, NYU School of Medicine, 650 First associations of coffee and tea drinking with oral microbiome Avenue, New York, NY 10016. Phone: 212-263-3390; Fax: 301-496-6829; E-mail: composition have not been comprehensively examined in a large [email protected] study. We evaluated these associations in a large cross-sectional doi: 10.1158/1055-9965.EPI-18-0184 analysis of American adults from two well-characterized cohort Ó2018 American Association for Cancer Research. studies, the American Cancer Society (ACS) Cancer Prevention 814 Cancer Epidemiol Biomarkers Prev; 27(7) July 2018 Downloaded from cebp.aacrjournals.org on September 29, 2021. © 2018 American Association for Cancer Research. Published OnlineFirst April 27, 2018; DOI: 10.1158/1055-9965.EPI-18-0184 Coffee, Tea, and the Oral Microbiome Study II (CPS-II) and the National Cancer Institute (NCI) Prostate, Microbiome assay Lung, Colorectal, and Ovarian Cancer Screening Trial (PLCO). Bacterial genomic DNA was extracted from oral wash samples Oral microbiota were assessed via 16S rRNA gene sequencing of using the Mo Bio PowerSoil DNA Isolation Kit. As reported microbial DNA from oral wash samples, and oral microbiome previously (32), 16S rRNA gene sequencing on the extracted DNA diversity and composition were evaluated in relation to frequency was performed. 16S rRNA gene amplicon libraries were generated of coffee and tea intake. using primers incorporating FLX Titanium adapters and a sample barcode sequence, allowing unidirectional sequencing covering variable regions V3 to V4 (Primers: 347F- 50GGAGGCAGCA- Materials and Methods 0 0 0 GTAAGGAAT-3 and 803R- 5 CTACCGGGGTATCTAATCC-3 ). Study population Five nanograms genomic DNA was used as the template in 25 Participants were drawn from the NCI PLCO cohort (28) and mL PCR reaction buffer for 16S rRNA gene amplicon preparation. the ACS CPS-II cohort (29), which are described in detail in the Cycling conditions were one cycle of 94C for 3 minutes, followed above-cited references. Both cohorts included U.S. adult men and by 25 cycles of 94C for 15 seconds, 52C for 45 seconds and 72C women, collected demographic, medical and lifestyle informa- for 1 minute followed by a final extension of 72C for 8 minutes. tion, and followed participants prospectively for cancer incidence. The generated amplicons were then purified using Agencourt Oral wash samples were collected from a subset of each cohort. AMPure XP kit (Beckman Coulter). Purified amplicons were All subjects included in the present cross-sectional analysis quantified by fluorometry using the Quant-iT PicoGreen dsDNA were originally selected from the CPS-II and PLCO cohorts as Assay Kit (Invitrogen). Equimolar amounts (107 molecules/mL) of cases or controls for collaborative nested case–control studies of purified amplicons were pooled for sequencing. Pyrosequencing the oral microbiome in relation to head/neck cancer (4) and (Roche 454 GS FLX Titanium) was carried out according to the pancreatic cancer (5). Participants are organized into 4 study manufacturer's instructions. groups: CPS-IIa, CPS-II participants in the head and neck study; CPS-IIb, CPS-II participants in the pancreas study; PLCOa, PLCO Sequence data processing participants in the head and neck study; and PLCOb, PLCO Sequence reads were demultiplexed, and poor-quality reads participants in the pancreas study. Cases were participants who excluded, using default parameters in QIIME (33). Quality- developed one of these two types of cancers at any point after filtered reads were clustered into operational taxonomic units collection of the oral wash samples. Age and sex-matched controls (OTU) against the Human Oral Microbiome Database (HOMD) were selected by incidence density sampling among cohort reference sequence collection (version 14.5; ref. 34), and assigned members who provided an oral wash sample and had no cancer HOMD taxonomy, using QIIME script pick_closed_reference_otus. prior to selection. py (33). The final dataset for this analysis of n ¼ 938 participants From the original 1,215 participants selected for inclusion in contained 9,921,097 reads [mean Æ SD ¼ 10,577 Æ 2,819; range the case–control studies (CPS-II n ¼ 543 and PLCO n ¼ 672), we ¼ (3,084–33,784)] and 681 OTUs. We generated a phylogenetic excluded participants missing smoking status or food frequency tree from aligned HOMD reference sequences using FastTree (35). questionnaire (FFQ) data, participants for whom sequencing Quality control data showing good reproducibility between repli- failed, participants with implausible daily energy intakes based cates have been published previously for this dataset (36). on FFQ responses (<500 or >4,000 kcal/day), and one participant with low library depth (1,516 sequence reads), leaving
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