Higher Angiotensin I Converting Enzyme 2 (ACE2) levels in the brain of individuals with Alzheimer’s disease
Bibliographic record
Abstract
Abstract The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) is a major cause of death in the elderly. Cognitive decline due to Alzheimer’s disease (AD) is frequent in the geriatric population disproportionately affected by the COVID-19 pandemic. Interestingly, central nervous system (CNS) manifestations have been reported in SARS-CoV-2-infected patients. In this study, we investigated the levels of Angiotensin I Converting Enzyme 2 (ACE2), the main entry receptor of SARS-COV-2 in cells, in postmortem parietal cortex samples from two independent AD cohorts, totalling 142 persons. Higher concentrations of ACE2 protein and mRNA were found in individuals with a neuropathological diagnosis of AD compared to age-matched healthy control subjects. Brain levels of soluble ACE2 were inversely associated with cognitive scores (p = 0.02), markers of pericytes (PDGFRβ, p=0.02 and ANPEP, p = 0.007) and caveolin1 (p = 0.03), but positively correlated with soluble amyloid-β peptides (Aβ) concentrations (p = 0.01) and insoluble phospho- tau (S396/404, p = 0.002). No significant differences in ACE2 were observed in the 3xTgAD mouse model of tau and Aβ neuropathology. Results from immunofluorescence and Western blots showed that ACE2 protein is mainly localized in neurons in the human brain but predominantly in microvessels in the mouse brain. The present data show that an AD diagnosis is associated with higher levels of soluble ACE2 in the human brain, which might contribute to a higher risk of CNS SARS-CoV-2 infection.
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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) | 0.001 | 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 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".