Social stress up-regulates inflammatory gene expression in the leukocyte transcriptome via β-adrenergic induction of myelopoiesis
Bibliographic record
Abstract
Across a variety of adverse life circumstances, such as social isolation and low socioeconomic status, mammalian immune cells have been found to show a conserved transcriptional response to adversity (CTRA) involving increased expression of proinflammatory genes. The present study examines whether such effects might stem in part from the selective up-regulation of a subpopulation of immature proinflammatory monocytes (Ly-6c(high) in mice, CD16(-) in humans) within the circulating leukocyte pool. Transcriptome representation analyses showed relative expansion of the immature proinflammatory monocyte transcriptome in peripheral blood mononuclear cells from people subject to chronic social stress (low socioeconomic status) and mice subject to repeated social defeat. Cellular dissection of the mouse peripheral blood mononuclear cell transcriptome confirmed these results, and promoter-based bioinformatic analyses indicated increased activity of transcription factors involved in early myeloid lineage differentiation and proinflammatory effector function (PU.1, NF-κB, EGR1, MZF1, NRF2). Analysis of bone marrow hematopoiesis confirmed increased myelopoietic output of Ly-6c(high) monocytes and Ly-6c(intermediate) granulocytes in mice subject to repeated social defeat, and these effects were blocked by pharmacologic antagonists of β-adrenoreceptors and the myelopoietic growth factor GM-CSF. These results suggest that sympathetic nervous system-induced up-regulation of myelopoiesis mediates the proinflammatory component of the leukocyte CTRA dynamic and may contribute to the increased risk of inflammation-related disease associated with adverse social conditions.
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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".