Mapping sex differences in brain and cognition in relation to <i>APOE4</i> and amyloid burden: A longitudinal normative modelling study
Bibliographic record
Abstract
Abstract Sex differences in Alzheimer’s disease (AD) risk and progression are increasingly recognized, with females exhibiting higher global prevalence rates. Yet it remains unclear how genetic and biomarker indicators of Alzheimer’s risk, such as the apolipoprotein E-ɛ4 ( APOE4 ) allele and amyloid burden, relate to sex differences in brain and cognitive health during the preclinical stage. Using established normative models trained on ~58,000 healthy participants, we computed regional z-scores from T1-weighted MRI scans in 372 cognitively normal participants from the Insight 46 cohort. Scans were acquired at two timepoints, approximately three years apart, beginning at age 70. Regions with z-scores below −1.96 were classified as brain-structure outliers and summarized as total outlier count (tOC). We used linear mixed-effects models to examine how sex, age, and AD risk ( APOE4 status and amyloid burden) relate to tOC and cognitive outcomes measured by Preclinical Alzheimer Cognitive Composite (PACC) scores. Both cross-sectional associations and longitudinal changes in tOC and PACC scores were examined, and we tested whether the effects of APOE4 status and amyloid burden on brain and cognitive measures differed by sex. Cross-sectional analyses showed that males had greater tOC than females at younger ages. At timepoint 1, spatial maps showed more regions with outliers in males, though high outlier proportions were limited to occipital areas. By timepoint 2, group differences became more spatially distinct, with males and females showing deviations in different regions. Longitudinally, older males exhibited steeper increases in tOC over time compared to females. Females showed higher PACC scores overall, while no sex differences were observed in cognitive change over time. Greater tOC and amyloid burden were both associated with poorer cognitive outcomes, with the strongest association observed in female APOE4 carriers. However, we found no evidence that AD risk influenced age-related changes in tOC or cognition over time. These findings highlight the complex interplay between sex, age, and AD risk in shaping brain structure and cognition in later life. Some of the observed patterns may reflect emerging vulnerability not yet captured by short-term longitudinal change, underscoring the importance of continued observation. In conclusion, normative modelling provides a valuable approach for detecting subtle variation in brain and cognitive aging across risk groups.
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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 | 0.004 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".