High CSF cortisol levels are associated with frontal lobe and hippocampal atrophy across patients on the Alzheimer’s disease spectrum
Bibliographic record
Abstract
Abstract Background Multiple studies have linked high cerebrospinal fluid (CSF) cortisol levels, a frequently used biomarker of stress, with the Alzheimer’s disease (AD) pathophysiology. However, the relationship between CSF cortisol levels and AD‐related brain atrophy is not fully understood. Thus, this study sought to determine the association between CSF cortisol levels and neuroimaging biomarkers of brain structure indexed by magnetic resonance imaging (MRI) in patients across the AD spectrum. Methods Participants with baseline measures of CSF cortisol and structural (high‐resolution T1‐weighted) MRI (n = 300) were selected from the Alzheimer’s Disease Neuroimaging Initiative (ADNI) database. The MRI scans were processed with FreeSurfer (v. 7.1.1), and the statistical analyses were performed using R (v. 4.1.1; R Core Team, 2021). We performed a region‐of‐interest (ROI) analysis using a generalized linear model (GLM), to assess the association between CSF cortisol levels and (1) volume of hippocampus, amygdala, subcortical and cortical segmentation, (2) cortical thickness and (3) surface area of cortical structures (Fig. 1). The ROI analysis was corrected by Bonferroni (p < 0.0005). Results CSF cortisol levels did not correlate with left hippocampal volume (p = 0.2; Fig. 2A) and mean global brain thickness (p = 0.002; Fig. 2C). However, we found a negative correlation with the volume of left fimbria (r = ‐0.20, p = 0.0003; Fig. 2B) and right superior frontal thickness (r = ‐0.21, p = 0.0003; Fig. 2D). In the regression model, only right superior frontal thickness showed significant association with CSF cortisol levels after adjusting for age (corrected R2 = 0.11, p < 0.0001). The other regions and parameters analyzed did not present significant correlations with CSF cortisol levels. Conclusions This cross‐sectional study found an association between elevated CSF cortisol levels and atrophy of left fimbria and right superior frontal in patients on the AD spectrum. Our findings suggest a particular vulnerability to cortisol in selected regions. To the best of our knowledge, this is the first study to assess the associations between CSF cortisol levels and ROIs from hippocampus and amygdala segmentation. Our results have potential implications for understating AD‐related brain atrophy and developing innovative therapeutic strategies.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".