Interleukin-15 enhances proinflammatory T-cell responses in patients with MS and EAE
Bibliographic record
Abstract
<h3>Objective</h3> We posit that interleukin-15 (IL-15) is a relevant contributor to MS pathobiology as this cytokine is elevated in the CNS and periphery of patients with MS. We aim to investigate (1) the impact of IL-15 on T lymphocytes from patients with MS and (2) the in vivo role of IL-15 using the experimental autoimmune encephalomyelitis (EAE) mouse model. <h3>Methods</h3> We compared the impact of IL-15 on T lymphocytes obtained from untreated patients with MS (relapsing-remitting, secondary progressive, and primary progressive) to cells from age/sex-matched healthy controls (HCs) using multiparametric flow cytometry and in vitro assays. We tested the effects of peripheral IL-15 administration after EAE disease onset in C57BL/6 mice. <h3>Results</h3> IL-15 triggered STAT5 signaling in an elevated proportion of T cells from patients with MS compared with HCs. This cytokine also enhanced the production of key proinflammatory cytokines (interferon γ, granulocyte-macrophage colony-stimulating factor [GM-CSF], IL-17, and tumor necrosis factor) by T cells from both MS and controls, but these effects were more robust for the production of IL-17 and GM-CSF in T-cell subsets from patients with MS. At the peak of EAE disease, the proportion of CD4<sup>+</sup> and CD8<sup>+</sup> T cells expressing CD122<sup>+</sup>, the key signaling IL-15 receptor chain, was enriched in the CNS compared with the spleen. Finally, peripheral administration of IL-15 into EAE mice after disease onset significantly aggravated clinical scores and increased the number of inflammatory CNS-infiltrating T cells long term after stopping IL-15 administration. <h3>Conclusions</h3> Our results underscore that IL-15 contributes to the amplification of T-cell inflammatory properties after disease onset in both MS and EAE.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 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".