Michael J LaMonte1, Robert J Genco2, Michael J Buck3, Daniel I McSkimming4, Lu Li5, Kathleen M Hovey6, Christopher A Andrews7, Wei Zheng5, Yijun Sun5, Amy E Millen6, Maria Tsompana3, Hailey R Banack6, Jean Wactawski-Wende6. 1. Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, 270 Farber Hall, 3435 Main Street, Buffalo, NY, 14214, USA. mlamonte@buffalo.edu. 2. Department of Oral Biology, School of Dental Medicine, UB Microbiome Center, University at Buffalo, Buffalo, NY, USA. 3. Department of Biochemistry, School of Medicine and Biomedical Sciences, NY State Center of Excellence in Bioinformatics and Life Sciences, University at Buffalo, Buffalo, NY, USA. 4. Genome, Environment, and Microbiome Center of Excellence, University at Buffalo, Buffalo, NY, USA. 5. Department of Microbiology and Immunology and Department of Computer and Engineering Science, NY State Center of Excellence in Bioinformatics and Life Sciences, University at Buffalo, Buffalo, NY, USA. 6. Department of Epidemiology and Environmental Health, School of Public Health and Health Professions, University at Buffalo, 270 Farber Hall, 3435 Main Street, Buffalo, NY, 14214, USA. 7. Department of Ophthalmology, School of Medicine, University of Michigan, Ann Arbor, MI, USA.
Abstract
BACKGROUND: The extent to which the composition and diversity of the oral microbiome varies with age is not clearly understood. METHODS: The 16S rRNA gene of subgingival plaque in 1219 women, aged 53-81 years, was sequenced and its taxonomy annotated against the Human Oral Microbiome Database (v.14.5). Composition of the subgingival microbiome was described in terms of centered log(2)-ratio (CLR) transformed OTU values, relative abundance, and prevalence. Correlations between microbiota abundance and age were evelauted using Pearson Product Moment correlations. P-values were corrected for multiple testing using the Bonferroni method. RESULTS: Of the 267 species identified overall, Veillonella dispar was the most abundant bacteria when described by CLR OTU (mean 8.3) or relative abundance (mean 8.9%); whereas Streptococcus oralis, Veillonella dispar and Veillonella parvula were most prevalent (100%, all) when described as being present at any amount. Linear correlations between age and several CLR OTUs (Pearson r = - 0.18 to 0.18), of which 82 (31%) achieved statistical significance (P < 0.05). The correlations lost significance following Bonferroni correction. Twelve species that differed across age groups (each corrected P < 0.05); 5 (42%) were higher in women ages 50-59 compared to ≥70 (corrected P < 0.05), and 7 (48%) were higher in women 70 years and older. CONCLUSIONS: We identified associations between several bacterial species and age across the age range of postmenopausal women studied. Understanding the functions of these bacteria could identify intervention targets to enhance oral health in later life.
BACKGROUND: The extent to which the composition and diversity of the oral microbiome varies with age is not clearly understood. METHODS: The 16S rRNA gene of subgingival plaque in 1219 women, aged 53-81 years, was sequenced and its taxonomy annotated against the Human Oral Microbiome Database (v.14.5). Composition of the subgingival microbiome was described in terms of centered log(2)-ratio (CLR) transformed OTU values, relative abundance, and prevalence. Correlations between microbiota abundance and age were evelauted using Pearson Product Moment correlations. P-values were corrected for multiple testing using the Bonferroni method. RESULTS: Of the 267 species identified overall, Veillonella dispar was the most abundant bacteria when described by CLR OTU (mean 8.3) or relative abundance (mean 8.9%); whereas Streptococcus oralis, Veillonella dispar and Veillonella parvula were most prevalent (100%, all) when described as being present at any amount. Linear correlations between age and several CLR OTUs (Pearson r = - 0.18 to 0.18), of which 82 (31%) achieved statistical significance (P < 0.05). The correlations lost significance following Bonferroni correction. Twelve species that differed across age groups (each corrected P < 0.05); 5 (42%) were higher in women ages 50-59 compared to ≥70 (corrected P < 0.05), and 7 (48%) were higher in women 70 years and older. CONCLUSIONS: We identified associations between several bacterial species and age across the age range of postmenopausal women studied. Understanding the functions of these bacteria could identify intervention targets to enhance oral health in later life.
Entities:
Keywords:
Aging; Epidemiology; Oral Microbiome; Women
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