Microglial sex dimorphism poses greater vulnerability to Alzheimer’s disease in females: A cross‐species study
Bibliographic record
Abstract
Abstract Background Understanding sex dimorphism in neurodevelopment and neurodegeneration is imperative for therapeutic strategy, clinical trial enrichment, and personalized medicine. However, the cellular underpinning of sex dimorphism in Alzheimer’s disease (AD) pathophysiology is still poorly understood. Here, we aimed to investigate the effect of sex on microglial activation and its effect on cognition using the major targets of AD clinical trials – amyloid ([18F]AZD4694), tau ([18F]MK6240), and neuroinflammation ([11C]PBR28) – through a multimodal PET study in humans and rats. Method A total of 108 participants (70 CN, 25 MCI, and 13 AD; 36 M, 72 F) with a high‐affinity binder for TSPO from the TRIAD cohort underwent 3 PET scans and MMSE for cognitive assessment. Static [18F]AZD4694, [18F]MK6240, and [11C]PBR28 SUVR images were generated. All PET images were normalized to the ADNI template, used cerebellar grey as a reference region. Furthermore, 29 rats (8 WT, 21 Tg; 13 M, 16 F) underwent a 60‐min dynamic [18F]AZD4694 and [11C]PBR28 PET scans. All PET images were normalized to the average template. [18F]AZD4694 and [11C]PBR28 BPND were quantified based on SRTM method using Pons and midbrain as a reference region, respectively. The sex effect on neuroinflammation is evaluated based on a linear regression model in humans and rats. Consequently, sex dimorphism induced neuroinflammation effect on cognition was assessed using MMSE. All the models were corrected for age, APOE, education, amyloid and tau status. Result In this study, females showed greater [11C]PBR28 binding in basal temporal regions in humans and parietotemporal cortex, hippocampus, and basal forebrain in rats. Consequently, greater neuroinflammation in females showed negative effects on MMSE but not in males, p = 0.033. Conclusion This study demonstrated the greater microglia activation in females compared to males. Considering the difference in the microglia reaction to amyloidosis in rodents compared to humans, the increased microglial activation effect on cognition was only assessed in humans. Here, microglial sex dimorphism showed deleterious effects on cognition only in females. This study highlights the difference in microglial reactivity leading to greater vulnerability to cognitive decline in females. As such, it is imperative to explore a sex‐specific therapeutic strategy for AD clinical trial.
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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) | 0.005 | 0.001 |
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".