MP092APABETALONE, A BROMODOMAIN AND EXTRATERMINAL PROTEIN INHIBITOR, DECREASES KEY FACTORS IN VASCULAR CALCIFICATION IN VITRO AND IN CLINICAL TRIALS
Bibliographic record
Abstract
INTRODUCTION AND AIMS: Apabetalone, an orally active bromodomain and extraterminal (BET) protein inhibitor, reduced incidence of major adverse cardiac events (MACE) in patients with CVD and improved eGFR in a subpopulation with chronic kidney disease (CKD) in phase 2 trials. In CKD patients, vascular calcification (VC) increases CVD risk & is a predictor of all-cause mortality. The process of VC involves differentiation of vascular smooth muscle cells (VSMCs) into osteoblast-like cells resulting in altered gene expression, loss of contractility & extracellular mineralization. Here we report clinical effects of apabetalone on circulating levels of factors involved in VC, including alkaline phosphatase (ALP), an enzyme regulating pyrophosphate levels & contributing to calcium deposition. Circulating ALP is derived primarily from liver, & elevated ALP is associated with mortality in CKD or patients on dialysis. In vitro, cell systems demonstrate effects of apabetalone on expression of VC markers, differentiation of coronary artery VSMCs & pathological process of extracellular calcium deposition. METHODS: Effects of apabetalone on expression of osteogenic markers were investigated in primary human hepatocytes (PHH), human macrophages (U937), and primary human VSMCs. Extracellular calcium deposition induced by osteogenic culture conditions was measured in VSMCs. Proteomic assessment of plasma from a phase 1 trial in CKD patients receiving a single 100 mg oral dose of apabetalone was conducted using Ingenuity® Pathway Analysis. Proteins associated with VC were also assessed in plasma of CVD patients receiving apabetalone in 3 month (ASSERT) and 6 month (SUSTAIN & ASSURE) phase 2 trials. RESULTS: Factors involved in the process of VC are derived from multiple cell types. In PHH cells from multiple donors, ALP was downregulated 60-80% by apabetalone. Apabetalone also reduced expression of osteopontin, another established marker of VC, in PHH, VSMCs & U937 macrophages. Differentiation of primary VSMCs with osteogenic conditions induced expression of ALP, osteoprotegerin, RUNX2 & WNT5A, which was suppressed by apabetalone. Further, apabetalone dose dependently countered calcium deposition in VSMCs. Clinical trials support translational mechanisms investigated in vitro. Proteomic analysis of plasma from stage 4 CKD patients (n=8) demonstrated significant activation of pathways driving calcification including “BMP-2 signaling” and “RANK signaling in osteoclasts” versus age, gender & BMI matched individuals (n=8). Both pathways were downregulated by apabetalone 12 hours after a single dose. Apabetalone also significantly reduced circulating levels of proteins associated with VC in phase 2 trials in CVD patients, including ALP, osteopontin & osteoprotegerin. CONCLUSIONS: Apabetalone mediates reduction of factors & pathways associated with VC. Simultaneous effects on multiple contributing elements from a variety of cell types suggest apabetalone may decrease pathologic calcification in CKD & contribute to a reduction in MACE in patients with high CVD risk. The potential of apabetalone to reduce CVD in CKD patients is currently being explored in a subpopulation of the phase 3 BETonMACE cardiovascular outcomes trial in patients with established CVD and diabetes mellitus.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".