Acute IL-6 exposure triggers canonical IL6Ra signaling in hiPSC microglia, but not neural progenitor cells
Bibliographic record
Abstract
BACKGROUND: Prenatal exposure to elevated interleukin (IL)-6 levels is associated with increased risk for psychiatric disorders with a putative neurodevelopmental origin, such as schizophrenia (SZ), autism spectrum condition (ASC) and bipolar disorder (BD). Although rodent models provide causal evidence for this association, we lack a detailed understanding of the cellular and molecular mechanisms in human model systems. To close this gap, we characterized the response of human induced pluripotent stem cell (hiPSC-)derived microglia-like cells (MGL) and neural progenitor cells (NPCs) to IL-6 in monoculture. RESULTS: We observed that human forebrain NPCs did not respond to acute IL-6 exposure in monoculture at both protein and transcript levels due to the absence of IL6R expression and soluble (s)IL6Ra secretion. By contrast, acute IL-6 exposure resulted in STAT3 phosphorylation and increased IL6, JMJD3 and IL10 expression in MGL, confirming activation of canonical IL6Ra signaling. Bulk RNAseq identified 156 up-regulated genes (FDR < 0.05) in MGL following acute IL-6 exposure, including IRF8, REL, HSPA1A/B and OXTR, which significantly overlapped with an up-regulated gene set from human post-mortem brain tissue from individuals with schizophrenia. Acute IL-6 stimulation significantly increased MGL motility, consistent with gene ontology pathways highlighted from the RNAseq data and replicating rodent model indications that IRF8 regulates microglial motility. Finally, IL-6 induces MGLs to secrete CCL1, CXCL1, MIP-1α/β, IL-8, IL-13, IL-16, IL-18, MIF and Serpin-E1 after 3 h and 24 h. CONCLUSION: Our data provide evidence for cell specific effects of acute IL-6 exposure in a human model system, ultimately suggesting that microglia-NPC co-culture models are required to study how IL-6 influences human cortical neural progenitor cell development in vitro.
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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 | 0.000 | 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".