Clinical and Bacterial Markers of Periodontitis and Their Association with Incident All-Cause and Alzheimer’s Disease Dementia in a Large National Survey
Bibliographic record
Abstract
Microbial agents including periodontal pathogens have recently appeared as important actors in Alzheimer’s disease (AD) pathology. We examined associations of clinical periodontal and bacterial parameters with incident all-cause and AD dementia as well as AD mortality among US middle-aged and older adults. Clinical [Attachment Loss (AL); probing pocket depth (PPD)] and bacterial [pathogen immunoglobulin G (IgG)] periodontal markers were investigated in relation to AD and all-cause dementia incidence and to AD mortality, using data from the third National Health and Nutrition Examination Surveys (NHANES III, 1988–1994) linked longitudinally with National Death Index and Medicare data through January 1, 2014, with up to 26 years of follow-up. Sex- and age-specific multivariable-adjusted Cox proportional hazards models were conducted. Among those ≥65 years, AD incidence and mortality were consistently associated with PPD, two factors and one cluster comprised of IgG titers against Porphyromonas gingivalis (P. gingivalis), Prevotella melaninogenica (P. melaninogenica) and Campylobacter rectus (C. rectus) among others. Specifically, AD incidence was linked to a composite of C. rectus and P. gingivalis titers (per SD, aHR = 1.22; 95% CI, 1.04–1.43, p = 0.012), while AD mortality risk was increased with another composite (per SD, aHR = 1.46; 95% CI, 1.09–1.96, p = 0.017) loading highly on IgG for P. gingivalis, Prevotella intermedia, Prevotella nigrescens, Fusobacterium nucleatum, C. rectus, Streptococcus intermedius, Capnocylophaga Ochracea, and P. melaninogenica. This study provides evidence for an association between periodontal pathogens and AD, which was stronger for older adults. Effectiveness of periodontal pathogen treatment on reducing sequelae of neurodegeneration should be tested in randomized controlled trials.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".