Periodontitis and brain magnetic resonance imaging markers of Alzheimer's disease and cognitive aging.

INTRODUCTION: We examined the association of clinical, microbiological, and host response features of periodontitis with MRI markers of atrophy/cerebrovascular disease in the Washington Heights Inwood Columbia Aging Project (WHICAP) Ancillary Study of Oral Health. METHODS: We analyzed 468 participants with clinical periodontal data, microbial plaque and serum samples, and brain MRIs. We tested the association of periodontitis features with MRI features, after adjusting for multiple risk factors for Alzheimer's disease/Alzheimer's disease-related dementia (AD/ADRD). RESULTS: In fully adjusted models, having more teeth was associated with lower odds for infarcts, lower white matter hyperintensity (WMH) volume, higher entorhinal cortex volume, and higher cortical thickness. Higher extent of periodontitis was associated with lower entorhinal cortex volume and lower cortical thickness. Differential associations emerged between colonization by specific bacteria/serum antibacterial IgG responses and MRI outcomes. DISCUSSION: In an elderly cohort, clinical, microbiological, and serological features of periodontitis were associated with MRI findings related to ADRD risk. Further investigation of causal associations is warranted.

Oral and gut microbial profiling in periodontitis and Parkinson's disease.

Objectives: We tested the hypothesis that Parkinson's disease (PA) alters the periodontitis-associated oral microbiome. Method: Patients with periodontitis with Parkinson's disease (PA+P) and without PA (P) and systemically and periodontally healthy individuals (HC) were enrolled. Clinical, periodontal and neurological parameters were recorded. The severity of PA motor functions was measured. Unstimulated saliva samples and stool samples were collected. Next-generation sequencing of 16S ribosomal RNA (V1-V3 regions) was performed. Results: PA patients had mild-to-moderate motor dysfunction and comparable plaque scores as those without, indicating that oral hygiene was efficient in the PA+P group. In saliva, there were statistically significant differences in beta diversity between HC and PA+P (p = 0.001), HC and P (p = 0.001), and P and PA+P (p = 0.028). The microbial profiles of saliva and fecal samples were distinct. Mycoplasma faucium, Tannerella forsythia, Parvimonas micra, and Saccharibacteria (TM7) were increased in P; Prevotella pallens, Prevotella melaninogenica, Neisseria multispecies were more abundant in PA+P group, Ruthenibacterium lactatiformans, Dialister succinatiphilus, Butyrivibrio crossotus and Alloprevotella tannerae were detected in fecal samples in P groups compared to healthy controls. Conclusions: No significant differences were detected between Parkinson's and non-Parkinson's gut microbiomes, suggesting that Parkinson's disease modifies the oral microbiome in periodontitis subjects independent of the gut microbiome.

Dietary nitrate intake and net nitrite-generating capacity of the oral microbiome interact to enhance cardiometabolic health: Results from the Oral Infections Glucose Intolerance and Insulin Resistance Study (ORIGINS).

Background: We investigated the association between dietary nitrate intake and early clinical cardiometabolic risk biomarkers, and explored whether the oral microbiome modifies the association between dietary nitrate intake and cardiometabolic biomarkers. Methods: Cross-sectional data from 668 (mean [SD] age 31 [9] years, 73% women) participants was analyzed. Dietary nitrate intakes and alternative healthy eating index (AHEI) scores were calculated from food frequency questionnaire responses and a validated US food database. Subgingival 16S rRNA microbial genes (Illumina, MiSeq) were sequenced, and PICRUSt2 estimated metagenomic content. The Microbiome Induced Nitric oxide Enrichment Score (MINES) was calculated as a microbial gene abundance ratio representing enhanced net capacity for NO generation. Cardiometabolic risk biomarkers included systolic and diastolic blood pressure, HbA1c, glucose, insulin, and insulin resistance (HOMA-IR), and were regressed on nitrate intake tertiles in adjusted multivariable linear models. Results: Mean nitrate intake was 190[171] mg/day. Higher nitrate intake was associated with lower insulin, and HOMA-IR but particularly among participants with low abundance of oral nitrite enriching bacteria. For example, among participants with a low MINES, mean insulin[95%CI] levels in high vs. low dietary nitrate consumers were 5.8[5.3,6.5] vs. 6.8[6.2,7.5] (p=0.004) while respective insulin levels were 6.0[5.4,6.6] vs. 5.9[5.3,6.5] (p=0.76) among partcipants with high MINES (interaction p=0.02). Conclusion: Higher dietary nitrate intake was only associated with lower insulin and insulin resistance among individuals with reduced capacity for oral microbe-induced nitrite enrichment. These findings have implications for future precision medicine-oriented approaches that might consider assessing the oral microbiome prior to enrollment into dietary interventions or making dietary recommendations.