Apabetalone Downregulates Fibrotic, Inflammatory and Calcific Processes in Renal Mesangial Cells: Mechanism for Reduced Cardiac Events in CKD Patients
Bibliographic record
Abstract
Background: Major adverse cardiac events (MACE) are prevalent in patients with chronic kidney disease (CKD). Apabetalone inhibits BET proteins, which regulate expression of genes involved in fibrosis, inflammation & calcification. In the phase 3 BETonMACE trial, apabetalone reduced MACE in patients with CKD (eGFR<60) implying favorable effects on the kidney-heart axis. Here we examine apabetalone's impact on pathways of nephropathy in human renal mesangial cells (HRMCs). Methods: HRMCs were stimulated with TGF-β1 or LPS ± 1-25μM apabetalone. Gene expression was measured by real-time PCR & RNA-seq. Smooth muscle actin (a-SMA) was examined by immunofluorescence & alkaline phosphatase (TNALP) activity in biochemical assays. RNA-seq from TGF-β1 stimulated HRMC was evaluated by GO and Ingenuity Pathway Analysis (IPA). Results: In HRMCs, apabetalone suppressed TGF-b1 induced pro-fibrotic gene expression including (a) a-SMA, a fibrotic marker, by 90% p<0.001 & de novo a-SMA protein production (b) fibronectin, an extracellular matrix (ECM) component, by 44% p<0.001 (c) NOX4, promoting reactive oxygen species (ROS) production, by 82% p<0.001 (d) TNALP, promoting calcification, by 96% & TNALP activity by 96% p<0.001. Apabetalone opposed LPS induced inflammatory gene expression: IL6 by 94%, IL1B by 95% & PTGS2 (COX2) by 94% p<0.001. In GO, ECM gene sets were in the top 20 affected by apabetalone, indicating reduced fibrosis. IPA predicted inhibition of NfkB-RelA and NFkB complex to suppress inflammation, and activation of glucose utilization & tolerance of ROS production pathways, such as Oxidative Phosphorylation (z-score 5.7 p<0.01 at 25μM; z-score 3.5 p>0.05 at 5μM) and NRF2-Mediated Oxidative Stress Response (z score 2.3 p<0.001 at 25μM; z-score 1.6 p<0.001 at 5μM). Conclusions: Apabetalone downregulates responses to TGF-β1 or LPS that promote fibrosis, inflammation & calcification in HRMCs. Changes in energy metabolism pathways predict apabetalone enables HRMC to cope with elevated glucose. Our results provide mechanistic insight into reduced MACE in CKD patients receiving apabetalone in the BETonMACE trial, & predict efficacy in the upcoming phase 3 BETonMACE2 trial. Funding: Commercial Support - Resverlogix Corp.
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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) | 0.003 | 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".