Integrated stress response associated with dark microglia promotes microglial lipogenesis and contributes to neurodegeneration
Bibliographic record
Abstract
Abstract Microglia, the brain’s primary resident immune cells, are a heterogeneous population and can assume phenotypes with diverse functional outcomes on brain homeostasis. In Alzheimer’s disease (AD), where microglia are a leading causal cell type, microglia subsets with protective functions have been well characterized. Yet, the identity of microglia subsets that drive neurodegeneration remains unresolved. Here, we identify a neurodegenerative microglia phenotype that is characterized by a conserved stress signaling pathway, the integrated stress response (ISR). Using mouse models to activate or inhibit ISR in microglia, we show that ISR underlies the ultrastructurally distinct “dark” microglia subset linked to pathological synapse loss. Inducing microglial ISR in murine AD models exacerbates neurodegenerative pathologies, such as Tau pathology and synaptic terminal loss. Conversely, inhibiting microglial ISR in AD models ameliorates these pathologies. Mechanistically, we present evidence that ISR promotes the secretion of toxic long-chain lipids that impair neuron and oligodendrocyte homeostasis in vitro. Accordingly, small molecule-based inhibition of lipid synthesis in AD models ameliorates synaptic terminal loss. Our results demonstrate that activation of ISR within microglia represents a novel pathway contributing to neurodegeneration and suggest that this may be sustained, at least in part, by the secretion of long-chain lipids from ISR-activated microglia.
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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".