Oral Microbiome and Cognition Among Black Cancer Caregivers
Bibliographic record
Abstract
BACKGROUND: Despite known links between oral health and dementia and the growing understanding of the role of the human microbiome in health, few studies have explored the relationship between the oral microbiome and cognition. Additionally, there is a notable absence of research on how the oral microbiome is associated with cognitive function in Black adult caregivers of cancer patients despite their elevated risk for both oral disease and cognitive impairment. OBJECTIVES: This study aimed to characterize the oral microbiome of Black caregivers of people living with cancer and explore the association of the oral microbiome with cognitive performance. METHODS: Thirty-one self-identified Black or African American caregivers of cancer patients in the greater metropolitan Atlanta area participated in the study. They provided oral microbiome samples. Cognitive performance was assessed using the Montreal Cognitive Assessment (MoCA), depressive symptoms with the Center for Epidemiological Studies-Depression Scale, and individual race-related stress with the Index of Race-Related Stress-Brief. Salivary microbiome diversity was analyzed using alpha and beta diversity metrics, and taxa associated with cognition were identified through differential abundance testing, adjusting for potential confounders. RESULTS: The mean age of participants was 54.8 years. MoCA scores ranged from 18 to 30, with a mean of 25. Participants were categorized into normal cognition (MoCA ≥ 26, n = 12) and low cognition (MoCA < 26, n = 16) groups. Education level and individual race-related stress were associated with cognition group and were controlled for in the oral microbiome analysis. Alpha and beta diversity analyses showed no significant overall differences between cognition groups. Differential abundance testing suggested 48 taxa were associated with cognition status, many of which are known to be associated with periodontal disease and cognition. DISCUSSION: This study revealed associations between cognition status and specific oral bacteria, many of which are known to be associated with periodontal disease and cognitive impairment. These findings underscore the complex relationship between oral health and cognitive function, suggesting a need for further research to develop oral microbiome profiles capable of identifying individuals at risk for cognitive decline and guiding targeted interventions for promoting overall well-being and cognitive health.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".