Sex‐Specific Associations Between Systemic Inflammation and Brain Health in Aging: Evidence from a Multi‐Ethnic Canadian Cohort
Bibliographic record
Abstract
BACKGROUND: Females tend to exhibit greater reductions in brain volume and cognition with age compared to males. Furthermore, females are twice as likely as males to be diagnosed with Alzheimer's disease, and often experience a more severe disease course. Emerging evidence suggests that inflammation resulting from estradiol depletion during the menopause transition may play a key role in these age-related sex disparities. However, research examining sex-specific inflammatory pathways and their role in dementia remain limited. This study aimed to address this gap by examining whether sex moderates the influence of inflammation on brain and cognitive outcomes in a multi-ethnic Canadian cohort. METHOD: Cross-sectional data were collected from N=137 (mean age=65.8±6.7, 97 females (71%)) cognitively unimpaired older adults participating in the Canadian Multiethnic Research on Aging (CAMERA) study at Sunnybrook Research Institute in Toronto, Canada. Inflammation was measured with plasma-derived C-reactive protein (CRP). Markers of brain health included whole-brain gray matter volume (GMV) derived from FreeSurfer (v.8), and whole-atlas fractional anisotropy (FA) derived from UKF tractography-based white matter analysis. Cognition was measured with experimental and neuropsychological tests, including domain-specific scores for processing speed, executive function, and episodic memory. Linear regression analyses examined whether sex moderated the effect of inflammation on brain and cognitive outcomes. Covariates included age and years of education, as well as total intracranial volume for GMV analysis, and total white matter hyperintensity volume for FA analysis. RESULT: =0.06, pFDR=0.01) in females than males. Sex did not moderate the relationship between CRP and cognition (pFDR>0.05). CONCLUSION: Inflammation may have a stronger negative impact on gray matter volume and white matter microstructural integrity in females compared to males, potentially contributing to sex differences in neurodegeneration and dementia risk. Future research should investigate the underlying biological mechanisms driving these associations to inform the development of sex-specific interventions targeting inflammation-related neurodegenerative processes.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".