Examining Cognitive Decline Across Black and White Participants in the Harvard Aging Brain Study
Bibliographic record
Abstract
BACKGROUND: Black Americans are approximately twice as likely to develop dementia as compared to White Americans and the magnitude of this disparity is often attributed to a variety of factors that include psychosocial and vascular risk factors. However, less is known about the potential contribution of Alzheimer's disease pathological differences. OBJECTIVE: To examine potential differences incross-sectional and longitudinal cognitive performance in black and white participants who were clinically normal at baseline. METHODS: 296 participants (48 African-American/black participants) underwent MRI and amyloid PET at baseline. Linear mixed models were used to examine the main effects of race, years of education, reading ability, Framingham Heart Study cardiovascular risk score (FHS-CVD), white matter hyperintensities (WMH), and amyloid (Aβ) burden on the Preclinical Alzheimer Cognitive Composite-5 (PACC5). RESULTS: Lower levels of educationalattainment and reading ability were found for blacks compared to whites. By contrast, no differences in FHS-CVD, WMH, or Aβ were found by racial group. Baseline differences in PACC5 score were attenuated after adjusting for educationalfactors, vascular factors, and Aβ, but remained lower for blacks compared to whites (β= -0.24, p = 0.014). Further, blacks demonstrated a faster rate of PACC5 decline longitudinally compared to whites (β = -0.055, p = 0.025) after adjusting for covariates. CONCLUSION: Accounting for educationalfactors, vascular factors, and Aβ burden diminished, but did not eliminate, racial differences in PACC5 performance longitudinally. Understanding potential differences in longitudinal cognitive outcomes by race may be important for upcoming secondary prevention 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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".