The Intersection between COVID-19, the Gene Family of ACE2 and Alzheimer’s Disease
Bibliographic record
Abstract
We reviewed factors that might influence COVID-19 outcomes (eg, neurological symptoms), including the link to Alzheimer’s disease. Since the virus triggers COVID-19 infection through binding to ACE2, we focused on the ACE2 gene family, including ACE. Both ACE2 and ACE are involved in the renin–angiotensin system (RAS). In general, ACE causes inflammation and vasoconstriction, while ACE2 leads to anti-inflammation activity and vasodilation. The disturbed balance between these counter-regulatory pathways could influence susceptibility to COVID-19. Notably, dysregulation of the RAS-equilibrium contributes to Alzheimer’s disease. Differences in the incidence and symptoms of COVID-19 in diverse populations could be attributed to variability in the human genome. For example, ACE and ACE2 variations could modify the outcome of COVID-19 in different populations. It would be important to conduct genome-wide studies to detect variants influencing COVID-19 presentation, with a special focus on variants affecting immune-related pathways and expression of RAS-related genes.
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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 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".