Abstract 407: Apabetalone (RVX-208) Inhibits Key Pro-Atherogenic Mediators and Pathways in Diabetes and Inflammatory Conditions; <i>in vitro</i> and in Patients
Bibliographic record
Abstract
Apabetalone (RVX-208) is a small molecule bromodomain & extraterminal (BET) protein inhibitor that targets the second bromodomain (BD2) within BET proteins. In phase 2 trials, apabetalone treatment reduced relative risk of MACE events by 57% in patients with cardiovascular disease (CVD) and type II diabetes (T2DM). In both CVD and T2DM, elevated circulating glucose, inflammatory mediators, and cell surface adhesion molecules drive vascular inflammation (VI), resulting in the recruitment, adhesion, and infiltration of leukocytes to the atherosclerotic plaque. Continuous inflammation promotes cytokine production, immune cell infiltration, and plaque rupture, which accounts for 67% of fatal myocardial infarctions (MIs) and sudden cardiac deaths. Here we show in vitro that TNFα and high glucose treatment induced significant adhesion of THP-1 monocytes to endothelial cells, an outcome inhibited by apabetalone treatment. Apabetalone suppressed the transcription of critical drivers of pro-inflammatory signaling ( RELA ), immune cell activation and recruitment ( MCP-1 ), and plaque rupture ( IL-8 ) in endothelial cells. Ingenuity® Pathway Analysis (IPA®), GSEA, and GO analysis of human umbilical vein endothelial cell (HUVEC) gene expression data predicted that apabetalone would inhibit pro-atherogenic pathways, gene sets, and upstream regulators. These include cytokine and chemokine signalling, immune and inflammatory response, Toll-Like Receptor (TLR) signalling, and TNFα signalling. In addition, IPA® disease and biological function analysis predicted inhibition of immune cell recruitment and activation by apabetalone. These in vitro effects are consistent with plasma proteomic results (SOMAscan®) from apabetalone-treated CVD T2DM patients, which demonstrated inhibitory effects on TNFα signalling, acute phase response, intrinsic prothrombin activation, leukocyte extravasation signalling and coagulation. Amelioration of diabetes and inflammation driven atherogenesis by apabetalone treatment likely contributes to the reduction in MACE observed in phase 2. The ongoing phase 3 post-ACS clinical trial in T2DM patients, BETonMACE, is investigating the effect of apabetalone on MACE reduction and will report in 2019.
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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 | 0.000 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".