RIPK2 Inhibition Blocks NOD2-Mediated IL-1β Production by Macrophages In Vitro but Exacerbates Crohn’s Disease-like Ileitis in SHIP–/– Mice
Bibliographic record
Abstract
Crohn’s disease is a chronic, idiopathic inflammatory bowel disease characterized by patchy, transmural inflammation that is influenced by genetic, environmental, and microbial factors. The NOD2 pathway mediates NFκB activation and pro-inflammatory cytokine production. In the SHIP–/– murine model of Crohn’s disease-like ileitis, macrophage-derived IL-1β production drives intestinal inflammation. SHIP reduces NOD2 signaling by preventing downstream interaction between RIPK2 and XIAP, leading us to hypothesize that blocking RIPK2 in SHIP–/– mice would ameliorate intestinal inflammation. We examined the effects of RIPK2 inhibition on pro-inflammatory cytokine production in SHIP+/+ and SHIP–/– macrophages and in mice, using the RIPK2 inhibitor, GSK2983559. We found that GSK2983559 blocked RIPK2 activation in SHIP+/+ and SHIP–/– bone marrow-derived macrophages (BMDMs), and reduced Il1b transcription and IL-1β production in (MDP+LPS)-stimulated SHIP–/– BMDMs. Despite the reduction of IL-1β production in BMDMs, in vivo treatment with GSK2983559 worsened intestinal inflammation and increased IL-1β concentrations in the ileal tissues of SHIP–/– mice. GSK2983559 only modestly reduced IL-1β in (MDP+LPS)-stimulated SHIP–/– peritoneal macrophages, and did not suppress pro-inflammatory cytokine production in response to TLR ligands in peritoneal macrophages from either SHIP+/+ or SHIP–/– mice. Taken together, our data suggest that although RIPK2 inhibition can block IL-1β production by (MDP+LPS)-stimulated macrophages in vitro, it is not an effective anti-inflammatory strategy in vivo, highlighting the limitations of targeting RIPK2 to treat intestinal inflammation in the context of SHIP deficiency.
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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 | 0.000 |
| 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) | 0.000 | 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".