Sex, racial, and <i>APOE</i> -ε4 allele differences in longitudinal white matter microstructure in multiple cohorts of aging and Alzheimer’s disease
Bibliographic record
Abstract
Structured Abstract INTRODUCTION The effects of sex, race, and Apolipoprotein E ( APOE ) – Alzheimer’s disease (AD) risk factors – on white matter integrity are not well characterized. METHODS Diffusion MRI data from nine well-established longitudinal cohorts of aging were free-water (FW)-corrected and harmonized. This dataset included 4,702 participants (age=73.06 ± 9.75) with 9,671 imaging sessions over time. FW and FW-corrected fractional anisotropy (FA FWcorr ) were used to assess differences in white matter microstructure by sex, race, and APOE- ε4 carrier status. RESULTS Sex differences in FA FWcorr in association and projection tracts, racial differences in FA FWcorr in projection tracts, and APOE- ε4 differences in FW limbic and occipital transcallosal tracts were most pronounced. DISCUSSION There are prominent differences in white matter microstructure by sex, race, and APOE- ε4 carrier status. This work adds to our understanding of disparities in AD. Additional work to understand the etiology of these differences is warranted. Highlights Sex, race, and APOE- ε4 carrier status relate to white matter microstructural integrity Females generally have lower FA FWcorr compared to males Non-Hispanic Black adults generally have lower FA FWcorr than non-Hispanic White adults APOE- ε4 carriers tended to have higher FW than non-carriers Research in Context Systematic Review The authors used PubMed and Google Scholar to review literature that used conventional and free-water (FW)-corrected microstructural metrics to evaluate sex, race, and APOE- ε4 differences in white matter microstructure. While studies have previously explored differences by sex and APOE- ε4 status, less is known about racial differences and no large-scale FW-corrected analysis has been performed. Interpretation Sex and race were more associated with FA FWcorr while APOE- ε4 status was associated with FW metrics. Association, projection, limbic, and occipital transcallosal tracts showed the greatest differences. Future Direction Future studies to determine the biological and social pathways that lead to sex, racial, and APOE- ε4 differences are warranted. Consent Statement All participants provided informed consent in their respective cohort studies.
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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 | 0.006 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".