Higher ACE2 expression in the brains of individuals with Alzheimer’s disease
Bibliographic record
Abstract
Background The emergence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major cause of death, particularly in the elderly. The geriatric population in which cognitive decline due to Alzheimer’s disease (AD) is frequent is disproportionately affected by the pandemic. In addition, central nervous system (CNS) manifestations have been reported in a significant subset of SARS-CoV-2 infected patients. Method Since the principal entry receptor utilized by SARS-COV-2 is Angiotensin-Converting Enzyme 2 (ACE2), we examined whether ACE2 protein and mRNA levels were altered postmortem in parietal cortex samples from two different AD cohorts, totalling 142 cases. Results Both immunoblot and RT-qPCR analysis revealed higher concentrations of ACE2 protein and mRNA in persons with a neuropathological diagnosis of AD, compared to age-matched controls. Brain levels of ACE2 were inversely correlated with antemortem cognitive scores. We found that ACE2 protein was highly enriched in microvessels of mice compared to brain parenchyma, but not in humans. Detachment of ACE2 from brain cell membranes was strongly associated with pericytes loss. No significant change of ACE2 protein was detected in the parietal cortex from the 3xTg-AD mouse model of AD neuropathology. Conclusion Our data suggest that cognitive impairment is associated with higher levels of ACE2 in the brain, which might contribute the higher risk of CNS SARS-CoV-2 infection in cognitively impaired individuals and AD patients.
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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 | 0.000 |
| 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) | 0.002 | 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".