Efficacy of HDAC Inhibitors in Driving Peroxisomal β-Oxidation and Immune Responses in Human Macrophages: Implications for Neuroinflammatory Disorders
Bibliographic record
Abstract
Elevated levels of saturated very long-chain fatty acids (VLCFAs) in cell membranes and secreted lipoparticles have been associated with neurotoxicity and, therefore, require tight regulation. Excessive VLCFAs are imported into peroxisomes for degradation by β-oxidation. Impaired VLCFA catabolism due to primary or secondary peroxisomal alterations is featured in neurodegenerative and neuroinflammatory disorders such as X-linked adrenoleukodystrophy and multiple sclerosis (MS). Here, we identified that healthy human macrophages upregulate the peroxisomal genes involved in β-oxidation during myelin phagocytosis and pro-inflammatory activation, and that this response is impaired in peripheral macrophages and phagocytes in brain white matter lesions in MS patients. The pharmacological targeting of VLCFA metabolism and peroxisomes in innate immune cells could be favorable in the context of neuroinflammation and neurodegeneration. We previously identified the epigenetic histone deacetylase (HDAC) inhibitors entinostat and vorinostat to enhance VLCFA degradation and pro-regenerative macrophage polarization. However, adverse side effects currently limit their use in chronic neuroinflammation. Here, we focused on tefinostat, a monocyte/macrophage-selective HDAC inhibitor that has shown reduced toxicity in clinical trials. By using a gene expression analysis, peroxisomal β-oxidation assay, and live imaging of primary human macrophages, we assessed the efficacy of tefinostat in modulating VLCFA metabolism, phagocytosis, chemotaxis, and immune function. Our results revealed the significant stimulation of VLCFA degradation with the upregulation of genes involved in peroxisomal β-oxidation and interference with immune cell recruitment; however, tefinostat was less potent than the class I HDAC-selective inhibitor entinostat in promoting a regenerative macrophage phenotype. Further research is needed to fully explore the potential of class I HDAC inhibition and downstream targets in the context of neuroinflammation.
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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) | 0.001 | 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".