Antiphospholipid antibodies promote leukocyte–endothelial cell adhesion and thrombosis in mice by antagonizing eNOS via β2GPI and apoER2
Bibliographic record
Abstract
In antiphospholipid syndrome (APS), antiphospholipid antibodies (aPL) binding to β2 glycoprotein I (β2GPI) induce endothelial cell-leukocyte adhesion and thrombus formation via unknown mechanisms. Here we show that in mice both of these processes are caused by the inhibition of eNOS. In studies of cultured human, bovine, and mouse endothelial cells, the promotion of monocyte adhesion by aPL entailed decreased bioavailable NO, and aPL fully antagonized eNOS activation by diverse agonists. Similarly, NO-dependent, acetylcholine-induced increases in carotid vascular conductance were impaired in aPL-treated mice. The inhibition of eNOS was caused by antibody recognition of domain I of β2GPI and β2GPI dimerization, and it was due to attenuated eNOS S1179 phosphorylation mediated by protein phosphatase 2A (PP2A). Furthermore, LDL receptor family member antagonism with receptor-associated protein (RAP) prevented aPL inhibition of eNOS in cell culture, and ApoER2-/- mice were protected from aPL inhibition of eNOS in vivo. Moreover, both aPL-induced increases in leukocyte-endothelial cell adhesion and thrombus formation were absent in eNOS-/- and in ApoER2-/- mice. Thus, aPL-induced leukocyte-endothelial cell adhesion and thrombosis are caused by eNOS antagonism, which is due to impaired S1179 phosphorylation mediated by β2GPI, apoER2, and PP2A. Our results suggest that novel therapies for APS can now be developed targeting these mechanisms.
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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) | 0.001 | 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 | 0.001 | 0.001 |
| 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".