Abstract 14127: BET Protein Inhibitor Apabetalone Suppresses Inflammatory Hyperactivation of Monocytes From Patients With Cardiovascular Disease and Type 2 Diabetes
Bibliographic record
Abstract
Introduction: Hyperactivation of the monocyte inflammatory response is partly controlled by epigenetic mechanisms and contributes to atherosclerotic plaque formation in patients with cardiovascular disease (CVD) and type 2 diabetes mellitus (DM2). Hypothesis: Monocyte activation in DM2+CVD is regulated by bromodomain and extraterminal (BET) epigenetic readers and can be inhibited by apabetalone - a clinical stage BET inhibitor. Methods: CD14+ monocytes from 14 DM2+CVD patients and 12 matched control subjects were treated ex vivo with 25 μM apabetalone ± 25 U/mL interferon γ (IFNγ) for 4h or 24h. Expressed genes (180) were analyzed with the Nanostring™ Innate Immunity Panel. Secreted cytokines were immunoprofiled with a Milliplex® array (42). Bioinformatics were performed with Ingenuity® Pathway Analysis (IPA®) software. Results: Unstimulated DM2+CVD monocytes had higher IL1A , IL1B and IL8 cytokine gene expression and Toll-like receptor (TLR) 2 surface abundance than control monocytes, indicating proinflammatory activation. Ex vivo apabetalone treatment reduced IL1A and IL8 mRNA (p<0.001), as well as MCP-1, MCP-3, GRO-α, and IL-8 secretion (p<0.01), countering the pro-inflammatory activation of DM2+CVD monocytes. Further, DM2+CVD monocytes were hyperresponsive to ex vivo stimulation with IFNγ, upregulating genes within cytokine and NF-κB pathways ( TNF , CCL7 , CCL8 , MYD88 , RELA ) >30% more than controls (p<0.05). Apabetalone countered IFNγ hyperresponsiveness by reducing expression of overexpressed genes by up to 30% more in DM2+CVD monocytes versus controls (p<0.01). Ex vivo apabetalone treatment also countered IFNγ induced secretion of IL-1β and TNFα in DM2+CVD monocytes (p<0.01). Consistently, IPA® analysis of immune gene signatures post IFNγ stimulation in both cohorts predicted a more prominent reduction of Toll-like receptor and cytokine pathways by apabetalone in the diseased state. Conclusions: Monocytes isolated from DM2+CVD patients receiving standard of care therapies are in a hyperinflammatory state and hyperactivate upon IFNγ stimulation. Apabetalone treatment diminishes this proinflammatory phenotype, providing mechanistic insight into how BET protein inhibition may reduce CVD risk in DM2 patients.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".