Audrey Renson1, Heidi E Jones2, Francesco Beghini3, Nicola Segata3, Christine P Zolnik4, Mykhaylo Usyk5, Thomas U Moody6, Lorna Thorpe7, Robert Burk8, Levi Waldron9, Jennifer B Dowd10. 1. Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York, NY; Department of Epidemiology, Gillings School of Global Public Health, University of North Carolina, Chapel Hill, NC. Electronic address: arenson@ad.unc.edu. 2. Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York, NY. 3. Department of Cellular, Computational and Integrative Biology, University of Trento, Trento, Italy. 4. Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY; Department of Biology, Long Island University, Brooklyn, NY. 5. Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY. 6. Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY; Immunology Program, Sloan Kettering Institute, Memorial Sloan Kettering Cancer Center, New York, NY. 7. Department of Population Health, NYU School of Medicine, New York, NY. 8. Department of Pediatrics, Albert Einstein College of Medicine, Bronx, NY; Departments of Microbiology and Immunology, Epidemiology and Population Health, and Obstetrics, Gynecology and Women's Health, Albert Einstein College of Medicine, Bronx, NY. 9. Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York, NY; Institute for Implementation Science in Population Health, City University of New York, New York, NY. 10. Department of Epidemiology and Biostatistics, Graduate School of Public Health and Health Policy, City University of New York, New York, NY; Department of Global Health and Social Medicine, King's College London, London, UK.
Abstract
PURPOSE: Variations in the oral microbiome are potentially implicated in social inequalities in oral disease, cancers, and metabolic disease. We describe sociodemographic variation of oral microbiomes in a diverse sample. METHODS: We performed 16S rRNA sequencing on mouthwash specimens in a subsample (n = 282) of the 2013-2014 population-based New York City Health and Nutrition Examination Study. We examined differential abundance of 216 operational taxonomic units, and alpha and beta diversity by age, sex, income, education, nativity, and race/ethnicity. For comparison, we examined differential abundance by diet, smoking status, and oral health behaviors. RESULTS: Sixty-nine operational taxonomic units were differentially abundant by any sociodemographic variable (false discovery rate < 0.01), including 27 by race/ethnicity, 21 by family income, 19 by education, 3 by sex. We found 49 differentially abundant by smoking status, 23 by diet, 12 by oral health behaviors. Genera differing for multiple sociodemographic characteristics included Lactobacillus, Prevotella, Porphyromonas, Fusobacterium. CONCLUSIONS: We identified oral microbiome variation consistent with health inequalities, more taxa differing by race/ethnicity than diet, and more by SES variables than oral health behaviors. Investigation is warranted into possible mediating effects of the oral microbiome in social disparities in oral and metabolic diseases and cancers.
PURPOSE: Variations in the oral microbiome are potentially implicated in social inequalities in oral disease, cancers, and metabolic disease. We describe sociodemographic variation of oral microbiomes in a diverse sample. METHODS: We performed 16S rRNA sequencing on mouthwash specimens in a subsample (n = 282) of the 2013-2014 population-based New York City Health and Nutrition Examination Study. We examined differential abundance of 216 operational taxonomic units, and alpha and beta diversity by age, sex, income, education, nativity, and race/ethnicity. For comparison, we examined differential abundance by diet, smoking status, and oral health behaviors. RESULTS: Sixty-nine operational taxonomic units were differentially abundant by any sociodemographic variable (false discovery rate < 0.01), including 27 by race/ethnicity, 21 by family income, 19 by education, 3 by sex. We found 49 differentially abundant by smoking status, 23 by diet, 12 by oral health behaviors. Genera differing for multiple sociodemographic characteristics included Lactobacillus, Prevotella, Porphyromonas, Fusobacterium. CONCLUSIONS: We identified oral microbiome variation consistent with health inequalities, more taxa differing by race/ethnicity than diet, and more by SES variables than oral health behaviors. Investigation is warranted into possible mediating effects of the oral microbiome in social disparities in oral and metabolic diseases and cancers.
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