Oral Microbial Dysbiosis Associated with Alzheimer’s Dementia in Puerto Ricans: A Preliminary Report
Bibliographic record
Abstract
Abstract Background New studies have linked epidemiological and pathophysiological relationships between oral microbiota and Alzheimer’s disease (AD), a neurodegenerative disease more prevalent in the Puerto Rican population. Dysbiosis of the oral microbiome induces periodontal disease, which increases systemic chronic inflammation, an important component in the multifactorial pathogenesis of AD. This project aims to characterize the oral microbiota’s composition and diversity in AD patients compared to healthy controls, and explore the potential role of oral dysbiosis in dementia. Method A total of 52 participants were recruited (28 with Alzheimer’s Disease and 24 healthy controls), IRB #2290033626. Evaluations included a complete medical history and physical exam, and psychologic assessments with the Montreal Cognitive Assessment (MOCA) and Clinical Dementia Rating (CDR). Blood samples were collected for genotyping of the APOE gene. Oral samples were collected for genomic DNA extractions and microbiome characterization using 16S rRNA genes (V4 region) via Illumina MiSeq. Result A statistically significant difference in bacterial composition was found in beta‐diversity between AD group and Controls (p‐value = 0.027). Among cognitive stages by CDR (p‐value = 0.04), a significant difference in beta‐diversity is also seen between participants with “no dementia”, “mild dementia”, and severe dementia”, which also correlates with distinctive richness at the genus‐level. LEFSe and Correlation analysis showed an increased abundance of oral genus Haemophilus in controls as compared to AD, and in increase in Corynebacterium in AD patients. Additionally, there is an increase in the proinflammatory bacteria Prevotella and a decrease in anti‐inflammatory bacteria Proteobateria also occurs in AD participants with abundance correlating with grades of cognitive impairment. Conclusion This research underscores the intricate interplay between oral microbiota dysbiosis, periodontal disease, chronic inflammation, and Alzheimer’s Disease (AD). Our preliminary findings suggest a potential association between alterations in oral microbiota composition and the presence and severity of AD. Further investigation, including periodontal assessments and analysis of chronic inflammatory markers, is warranted to elucidate the mechanistic links and potential therapeutic avenues in managing AD within the Puerto Rican population.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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 source (direct Gemma or distilled Codex), 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".