Inflammation in Alzheimer’s Disease: Do Sex and APOE Matter?
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Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) disproportionately affects females with steeper cognitive decline and more neuropathology compared to males, which is exacerbated in females carrying the APOEɛ4 allele. The risk of developing AD is also higher in female APOEɛ4 carriers in earlier age groups (aged 65-75), and the progression from cognitively normal to mild cognitive impairment (MCI) and to AD may be influenced by sex. Inflammation is observed in AD and is related to aging, stress, and neuroplasticity, and although studies are scarce, sex differences are noted in inflammation. OBJECTIVE: The objective of this study was to investigate underlying physiological inflammatory mechanisms that may help explain why there are sex differences in AD and APOEɛ4 carriers. METHODS: We investigated, using the ADNI database, the effect of sex and APOE genotype (non-carriers or carriers of 1 and 2 APOEɛ4 alleles) and sex and diagnosis (cognitively normal (CN), MCI, AD) on CSF (N = 279) and plasma (N = 527) markers of stress and inflammation. RESULTS: We found CSF IL-16 and IL-8 levels differed by sex and APOE genotype, as IL-16 was higher in female APOEɛ4 carriers compared to non-carriers, while the opposite pattern was observed in males with IL-8. Furthermore, females had on average higher levels of plasma CRP and ICAM1 but lower levels of CSF ICAM1, IL-8, IL-16, and IgA than males. Carrying APOEɛ4 alleles and diagnosis (MCI and AD) decreased plasma CRP in both sexes. CONCLUSION: Sex and APOE genotype differences in CSF and plasma inflammatory biomarkers support that the underlying physiological changes during aging differ by sex and tissue origin.
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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 | 0.000 | 0.000 |
| 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) | 0.001 | 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 it