Abstract 626: Apabetalone (Rvx-208), a Selective Bet Protein Inhibitor, Reduces Expression of Acute Phase Response Markers <i>in vitro</i> and in Patients With Cardiovascular Disease and Chronic Kidney Disease
Bibliographic record
Abstract
Apabetalone is an inhibitor of the epigenetic readers bromodomain and extraterminal (BET) proteins, currently in a phase 3 outcomes trial in patients with cardiovascular disease (CVD) and diabetes mellitus. A post hoc analysis of phase 2b trials demonstrated a 55% relative risk reduction in major adverse cardiac events in CVD patients. Elevated inflammatory markers correlate with CVD. Inflammation also accompanies chronic kidney disease (CKD) and CKD patients are at risk of CVD. Previous research has shown that apabetalone modulates pathways that contribute to chronic inflammation, including the acute phase response (APR). Here, pathway analysis of gene microarrays showed downregulation of APR by apabetalone in primary human hepatocytes (PHH). Real-time PCR and ELISA analysis of RVX-208 treated PHHs confirmed that APR genes that correlate with CVD are suppressed by 20 to 95%, including CRP, ceruloplasmin (CP), serum amyloid P (SAP), PAI-1, alpha 2-macroglobulin (A2M), complement C2, C3 and C5, MBL2, serum amyloid A and interleukin 18. Apabetalone decreased IL-6-induced expression of CP, SAP and A2M, with most striking effects on CRP (-75%). Apabetalone also decreased LPS-induced expression of SAP in a mouse endotoxemia model. To assess effects of apabetalone on inflammatory mediators in CVD patients, SOMAscan™ 1.3K proteomic analysis was performed on plasma from phase 2b ASSERT (12 weeks; n=25) and ASSURE (26 weeks; n=47) clinical trials. This approach identified APR as the top downregulated pathway by apabetalone in both trials. APR biomarkers are elevated in CKD patients where they correlate with disease progression. To gain insight into the pharmacodynamics of the APR response to apabetalone, stage 4 CKD patients (n=8) received a single dose of the drug followed by plasma proteomics at several time points. At 12h post dose, APR was significantly downregulated by apabetalone. Of note, CRP was decreased in CKD patients after 12h of treatment (-7%, p=0.04) versus baseline, as well as in ASSERT (-43%, p=0.01) and ASSURE (-21%, p=0.02) trials versus placebo. Downregulation of the APR pathway by apabetalone may lead to reduced chronic inflammation in CVD and CKD patients and contribute to the reduction in MACE in patients with high residual CVD risk.
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".