The Potential of Docosahexaenoic Acid (DHA) in SARS-CoV-2 Management: DHA Reduces ACE2 Levels in Endothelial Cells
Bibliographic record
Abstract
Angiotensin-converting enzyme 2 (ACE2) is a transmembrane protein located on the surface of endothelial cells that promotes vasodilation by promoting the hydrolysis of angiotensin II. However, ACE2 also serves as the cellular receptor for SARS-CoV-2. Infection by SARS-CoV-2 can promote endothelial dysfunction which in turn is associated with greater infection severity. Long chain omega-3 fatty acids (n3 PUFA) like eicosapentaenoic acid (EPA) and docosahexaenoic acid (DHA) are reported to prevent endothelial dysfunction. Thus, we hypothesize that treatment with n3 PUFA may suppress the actions of SARS-CoV-2 on endothelial cells, potentially through endothelial ACE2. The objective of the study was therefore to investigate whether changes in ACE2 levels occur as part of the endothelial response to n3 PUFA treatment. Male fa/fa Zucker rats were randomised into 4 PUFA-based diet groups: α-linoleic acid (ALA), EPA, DHA, and linoleic acid (LA), for 8 weeks. EA.hy926 cells were cultured to sub-confluent and quiescent states and treated with various doses of DHA, EPA, and ALA for 8 or 24 h. ACE2 levels in tissues and cells were quantified by Western blotting. In contrast to ALA and EPA, DHA treatment significantly reduced ACE2 levels in rat heart, aorta, and kidney but not lungs after 8 weeks of diet intervention. EPA only showed this reduction compared to ALA in kidney. Interestingly, when applied to human endothelial cells in culture, DHA decreased ACE2 levels of growing EA.hy926 cells even at relatively low doses, but no significant effect was observed in quiescent cells. EPA also had an effect, but only at an extremely high dose. DHA reduced ACE2 levels in key organs and human endothelial cells, which should produce beneficial effects by lowering the susceptibility of cells to SARS-CoV-2. St Boniface Hospital Foundation - Research Without Borders and University of Manitoba - GETS
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".