Peroxisomal defects in microglial cells induce a disease-associated microglial signature
Bibliographic record
Abstract
Microglial cells ensure essential roles in brain homeostasis. In pathological condition, microglia adopt a common signature, called disease-associated microglial (DAM) signature, characterized by the loss of homeostatic genes and the induction of disease-associated genes. In X-linked adrenoleukodystrophy (X-ALD), the most common peroxisomal disease, microglial defect has been shown to precede myelin degradation and may actively contribute to the neurodegenerative process. We previously established BV-2 microglial cell models bearing mutations in peroxisomal genes that recapitulate some of the hallmarks of the peroxisomal β-oxidation defects such as very long-chain fatty acid (VLCFA) accumulation. In these cell lines, we used RNA-sequencing and identified large-scale reprogramming for genes involved in lipid metabolism, immune response, cell signaling, lysosome and autophagy, as well as a DAM-like signature. We highlighted cholesterol accumulation in plasma membranes and observed autophagy patterns in the cell mutants. We confirmed the upregulation or downregulation at the protein level for a few selected genes that mostly corroborated our observations and clearly demonstrated increased expression and secretion of DAM proteins in the BV-2 mutant cells. In conclusion, the peroxisomal defects in microglial cells not only impact on VLCFA metabolism but also force microglial cells to adopt a pathological phenotype likely representing a key contributor to the pathogenesis of peroxisomal disorders.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| 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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".