IL-1β Induces LDL Transcytosis by a Novel Pathway Involving LDLR and Rab27a
Bibliographic record
Abstract
BACKGROUND: In early atherosclerosis, circulating LDLs (low-density lipoproteins) traverse individual endothelial cells by an active process termed transcytosis. The CANTOS trial (Canakinumab Antiinflammatory Thrombosis Outcome Study) treated advanced atherosclerosis using a blocking antibody for IL-1β (interleukin-1β); this significantly reduced cardiovascular events. However, whether IL-1β regulates early disease, particularly LDL transcytosis, remains unknown. METHODS: We used total internal reflection fluorescence microscopy to quantify transcytosis by human coronary artery endothelial cells exposed to IL-1β. To investigate transcytosis in vivo, we injected wild-type and knockout mice with IL-1β and LDL to visualize acute LDL deposition in the aortic arch. RESULTS: Exposure to picomolar concentrations of IL-1β induced transcytosis of LDL but not of albumin by human coronary artery endothelial cells. Surprisingly, expression of the 2 known receptors for LDL transcytosis, ALK-1 (activin receptor-like kinase-1) and SR-BI (scavenger receptor BI), was unchanged or decreased. Instead, IL-1β increased the expression of the LDLR (LDL receptor); this was unexpected because LDLR is not required for LDL transcytosis. Overexpression of LDLR had no effect on basal LDL transcytosis. However, knockdown of LDLR abrogated the effect of IL-1β on transcytosis rates while the depletion of Cav-1 (caveolin-1) did not. Since LDLR was necessary but overexpression had no effect, we reasoned that another player must be involved. Using public RNA sequencing data to curate a list of Rab (Ras-associated binding) GTPases affected by IL-1β, we identified Rab27a. Overexpression of Rab27a alone had no effect on basal transcytosis, but its knockdown prevented induction by IL-1β. This was phenocopied by depletion of the Rab27a effector JFC1 (synaptotagmin-like protein 1). In vivo, IL-1β increased LDL transcytosis in the aortic arch of wild-type but not Ldlr −/− or Rab27a-deficient mice. The JFC1 inhibitor nexinhib20 also blocked IL-1β–induced LDL accumulation in the aorta. CONCLUSIONS: IL-1β induces LDL transcytosis by a distinct pathway requiring LDLR and Rab27a; this route differs from basal transcytosis. We speculate that induction of transcytosis by IL-1β may contribute to the acceleration of early disease.
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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 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".