Early-life stress lastingly impacts microglial transcriptome and function under basal and immune-challenged conditions
Bibliographic record
Abstract
Early-life stress (ELS) leads to increased vulnerability to psychiatric disorders including depression later in life. Neuroinflammatory processes have been implicated in ELS-induced negative health outcomes, but how ELS impacts microglia, the main tissue-resident macrophages of the central nervous system, is unknown. Here, we determined the effects of ELS-induced by limited bedding and nesting material during the first week of life (postnatal days [P]2-9) on microglial (i) morphology; (ii) hippocampal gene expression; and (iii) synaptosome phagocytic capacity in male pups (P9) and adult (P200) mice. The hippocampus of ELS-exposed adult mice displayed altered proportions of morphological subtypes of microglia, as well as microglial transcriptomic changes related to the tumor necrosis factor response and protein ubiquitination. ELS exposure leads to distinct gene expression profiles during microglial development from P9 to P200 and in response to an LPS challenge at P200. Functionally, synaptosomes from ELS-exposed mice were phagocytosed less by age-matched microglia. At P200, but not P9, ELS microglia showed reduced synaptosome phagocytic capacity when compared to control microglia. Lastly, we confirmed the ELS-induced increased expression of the phagocytosis-related gene GAS6 that we observed in mice, in the dentate gyrus of individuals with a history of child abuse using in situ hybridization. These findings reveal persistent effects of ELS on microglial function and suggest that altered microglial phagocytic capacity is a key contributor to ELS-induced phenotypes.
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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) | 0.001 | 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".