Reducing Vascular Calcification by Anti-IL-1β Monoclonal Antibody in a Mouse Model of Familial Hypercholesterolemia
Bibliographic record
Abstract
BACKGROUND: Given the link between cholesterol and activation of inflammation via interleukin 1β (IL-1β), we tested the effects of IL-1β inhibition on atherosclerotic calcification in mice. Patients with familial hypercholesterolemia develop extensive aortic calcification and calcific aortic stenosis. Although statins delay this process, low-density lipoprotein (LDL) cholesterol lowering alone is not enough to avert it. Data suggest that vascular inflammation initiated by hypercholesterolemia is followed by unchecked mineralization at sites of atherosclerotic plaques. The LDL-receptor (LDLR)-deficient (Ldlr(-/-)) and LDLR-attenuated Pcsk9(Tg) mice are available animal models for pharmacological testing. METHODS: A mouse monoclonal antibody (mAb) against IL-1β or placebo was administered subcutaneously in Ldlr(-/-) and Pcsk9(Tg) models fed a Western diet. Drug level, anthropometric, lipid, and glucose profiles were determined. Expressions of proprotein convertase subtilisin/kexin type 9 (PCSK9), serum amyloid A1, and cytokine were measured by enzyme-linked immunosorbent assay. Aortic calcification was determined by microcomputerized tomography (micro-CT) and X-ray densitometry, and aortic flow velocity was assessed by ultrasound. RESULTS: Circulating levels of IL-1β in Ldlr(-/-) mice were significantly greater (2-fold) than observed in Pcsk9(Tg) mice. Placebo- and mAb-treated mice did not differ in their growth, lipid, glucose profiles, and other cytokines. Calcifications were significantly diminished in mAb-treatment Ldlr(-/-) mice (a reduction of ∼ 75% by X-ray and ∼ 90% by micro-CT) and reduced insignificantly in mAb-treatment Pcsk9(Tg) mice, whereas aortic flow velocity was unchanged in both models. CONCLUSIONS: Herein, we demonstrate that aortic calcifications can be inhibited by an IL-1β mAb in LDLR-deficient mice. These results have a translational component to prevent vascular calcification in human and represent new evidence to rationalize targeting inflammation in cardiovascular 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".