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Objectives: To study the levels of systemic markers for inflammation with parameters of periodontal diseases in older people., Design: A cross-sectional study was conducted in a cohort that is being followed prospectively on the effects of aging and body composition on morbidity., Setting: University of Pittsburgh, Pittsburgh, and University of Tennessee, Memphis., Participants: One thousand one hundred thirty-one participants (mean age+/-standard deviation 72.7+/-2.8); 66% white and 50% male., Measurements: Periodontal examination, including probing depth and attachment loss, was performed. Periodontal disease extent was divided into 0% of sites with probing depth of 6 mm or more, 1% to 10% of sites with probing depth of 6 mm or more and more than 10% of sites with probing depth of 6 mm or more. Subgingival plaque samples were collected from four molar teeth, and the levels of periodontal pathogens were determined using the benzoyl-DL-arginine-naphthylamide (BANA) test. Plasma interleukin-6 (IL-6), C-reactive protein (CRP), plasminogen activator inhibitor type-1 (PAI-1), and tumor necrosis factor alpha (TNF-alpha) levels were measured in all participants. Assessments of risk factors associated with elevated levels of markers of systemic inflammation were also determined. Multiple regression analysis was employed to analyze the data., Results: IL-6 levels were significantly higher in participants with more-extensive periodontal disease than in other participants. Periodontal disease extent was significantly associated with higher TNF-alpha plasma levels, controlling for established risk factors for elevated TNF-alpha levels. Participants with BANA-positive species had significantly higher CRP plasma levels when controlling for risk factors for elevated CRP levels., Conclusion: Periodontal disease and infection may be modifiable risk indicators for elevated levels of systemic inflammatory markers in older people.

Introduction: Periodontal disease is a chronic, inflammatory bacterial dysbiosis that is associated with both Alzheimer’s disease (AD) and Down syndrome. Methods: A total of 48 elderly cognitively normal subjects were evaluated for differences in subgingival periodontal bacteria (assayed by 16S rRNA sequencing) between cerebrospinal fluid (CSF) biomarker groups of amyloid and neurofibrillary pathology. A dysbiotic index (DI) was defined at the genus level as the abundance ratio of known periodontal bacteria to healthy bacteria. Analysis of variance/analysis of covariance (ANOVA/ANCOVA), linear discriminant effect-size analyses (LEfSe) were used to determine the bacterial genera and species differences between the CSF biomarker groups. Results: At genera and species levels, higher subgingival periodontal dysbiosis was associated with reduced CSF amyloid beta (Aβ)42 (P = 0.02 and 0.01) but not with P-tau. Discussion: We show a selective relationship between periodontal disease bacterial dysbiosis and CSF biomarkers of amyloidosis, but not for tau. Further modeling is needed to establish the direct link between oral bacteria and Aβ. [ABSTRACT FROM AUTHOR]

Introduction: The impaired host defense system in HIV infection impacts the oral and gastrointestinal microbiota and associated opportunistic infections. Antiretroviral treatment is predicted to partially restore host defenses and decrease the oral manifestation of HIV/AIDS. Well-designed longitudinal studies are needed to better understand the interactions of soluble host defense proteins with bacteria and virus in HIV/AIDS. “Crosstalk” was designed as a longitudinal study of host responses along the gastrointestinal (GI) tract and interactions between defense molecules and bacteria in HIV infection and subsequent therapy. Purpose: The clinical core formed the infrastructure for the study of the interactions between the proteome, microbiome and innate immune system. The core recruited and retained study subjects, scheduled visits, obtained demographic and medical data, assessed oral health status, collected samples, and guided analysis of the hypotheses. This manuscript presents a well-designed clinical core that may serve as a model for studies that combine clinical and laboratory data. Methods: Crosstalk was a case-control longitudinal clinical study an initial planned enrollment of 170 subjects. HIV+ antiretroviral naïve subjects were followed for 9 visits over 96 weeks and HIV uninfected subjects for 3 visits over 24 weeks. Clinical prevalence of oral mucosal lesions, dental caries and periodontal disease were assessed. Results: During the study, 116 subjects (47 HIV+, 69 HIV-) were enrolled. Cohorts of HIV+ and HIV- were demographically similar except for a larger proportion of women in the HIV- group. The most prevalent oral mucosal lesions were oral candidiasis and hairy leukoplakia in the HIV+ group. Discussion: The clinical core was essential to enable the links between clinical and laboratory data. The study aims to determine specific differences between oral and GI tissues that account for unique patterns of opportunistic infections and to delineate the differences in their susceptibility to infection by HIV and their responses post-HAART. [ABSTRACT FROM AUTHOR]

Individual bacteria and shifts in the composition of the microbiome have been associated with human diseases including cancer. To investigate changes in the microbiome associated with oral cancers, we profiled cancers and anatomically matched contralateral normal tissue from the same patient by sequencing 16S rDNA hypervariable region amplicons. In cancer samples from both a discovery and a subsequent confirmation cohort, abundance of Firmicutes (especially Streptococcus) and Actinobacteria (especially Rothia) was significantly decreased relative to contralateral normal samples from the same patient. Significant decreases in abundance of these phyla were observed for pre-cancers, but not when comparing samples from contralateral sites (tongue and floor of mouth) from healthy individuals. Weighted UniFrac principal coordinates analysis based on 12 taxa separated most cancers from other samples with greatest separation of node positive cases. These studies begin to develop a framework for exploiting the oral microbiome for monitoring oral cancer development, progression and recurrence. [ABSTRACT FROM AUTHOR]

The purpose of this study was to provide a univariate and multivariate analysis of genomic microbial data and salivary mass-spectrometry proteomic profiles for dental caries outcomes. In order to determine potential useful biomarkers for dental caries, a multivariate classification analysis was employed to build predictive models capable of classifying microbial and salivary sample profiles with generalization performance. We used high-throughput methodologies including multiplexed microbial arrays and SELDI-TOF-MS profiling to characterize the oral flora and salivary proteome in 204 children aged 1-8 years (n = 118 caries-free, n = 86 caries-active). The population received little dental care and was deemed at high risk for childhood caries. Findings of the study indicate that models incorporating both microbial and proteomic data are superior to models of only microbial or salivary data alone. Comparison of results for the combined and independent data suggests that the combination of proteomic and microbial sources is beneficial for the classification accuracy and that combined data lead to improved predictive models for caries-active and caries-free patients. The best predictive model had a 6% test error, >92% sensitivity, and >95% specificity. These findings suggest that further characterization of the oral microflora and the salivary proteome associated with health and caries may provide clinically useful biomarkers to better predict future caries experience. [ABSTRACT FROM AUTHOR]

Unlabelled: Despite significant advances in surgical procedures and treatment, long-term prognosis for patients with oral cancer remains poor, with survival rates among the lowest of major cancers. Better methods are desperately needed to identify potential malignancies early when treatments are more effective.Objective: To develop robust classification models from cytology-on-a-chip measurements that mirror diagnostic performance of gold standard approach involving tissue biopsy.Materials and Methods: Measurements were recorded from 714 prospectively recruited patients with suspicious lesions across 6 diagnostic categories (each confirmed by tissue biopsy -histopathology) using a powerful new 'cytology-on-a-chip' approach capable of executing high content analysis at a single cell level. Over 200 cellular features related to biomarker expression, nuclear parameters and cellular morphology were recorded per cell. By cataloging an average of 2000 cells per patient, these efforts resulted in nearly 13 million indexed objects.Results: Binary "low-risk"/"high-risk" models yielded AUC values of 0.88 and 0.84 for training and validation models, respectively, with an accompanying difference in sensitivity+specificity of 6.2%. In terms of accuracy, this model accurately predicted the correct diagnosis approximately 70% of the time, compared to the 69% initial agreement rate of the pool of expert pathologists. Key parameters identified in these models included cell circularity, Ki67 and EGFR expression, nuclear-cytoplasmic ratio, nuclear area, and cell area.Conclusions: This chip-based approach yields objective data that can be leveraged for diagnosis and management of patients with PMOL as well as uncovering new molecular-level insights behind cytological differences across the OED spectrum. [ABSTRACT FROM AUTHOR]