Endogenous and Therapeutic 25-Hydroxycholesterols May Worsen Early SARS-CoV-2 Pathogenesis in Mice
Bibliographic record
Abstract
Abstract Oxysterols (i.e., oxidized cholesterol species) have complex roles in biology. 25-hydroxycholesterol (25HC), a product of activity of cholesterol-25-hydroxylase (CH25H) upon cholesterol, has recently been shown to be broadly antiviral, suggesting therapeutic potential against SARS-CoV-2. However, 25HC can also amplify inflammation and tissue injury and be converted by CYP7B1 to 7α,25HC, a lipid with chemoattractant activity via the G protein-coupled receptor, EBI2/GPR183. Here, using in vitro studies and two different murine models of SARS-CoV-2 infection, we investigate the effects of these two oxysterols on SARS-CoV-2 pneumonia. We show that while 25HC and enantiomeric-25HC are antiviral in vitro against human endemic coronavirus-229E, they did not inhibit SARS-CoV-2; nor did supplemental 25HC reduce pulmonary SARS-CoV-2 titers in the K18-human ACE2 mouse model in vivo . 25HC treatment also did not alter immune cell influx into the airway, airspace cytokines, lung pathology, weight loss, symptoms, or survival but was associated with increased airspace albumin, an indicator of microvascular injury, and increased plasma pro-inflammatory cytokines. Conversely, mice treated with the EBI2/GPR183 inhibitor NIBR189 displayed a modest increase in lung viral load only at late time points, but no change in weight loss. Consistent with these findings, although Ch25h was upregulated in the lungs of SARS-CoV-2-infected WT mice, lung viral titers and weight loss in Ch25h −/– and Gpr183 −/– mice infected with the beta variant were similar to control animals. Taken together, endogenous 25-hydroxycholesterols do not significantly regulate early SARS-CoV-2 replication or pathogenesis and supplemental 25HC may have pro-injury rather than therapeutic effects in SARS-CoV-2 pneumonia.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".