Seladelpar treatment reduces IL-31 and pruritus in patients with primary biliary cholangitis
Bibliographic record
Abstract
BACKGROUND AND AIMS: Pruritus is a debilitating symptom for many people living with primary biliary cholangitis (PBC). In studies with seladelpar, a selective peroxisome proliferator-activated receptor-delta agonist, patients with PBC experienced significant improvement in pruritus and reduction of serum bile acids. Interleukin-31 (IL-31) is a cytokine known to mediate pruritus, and blocking IL-31 signaling provides relief in pruritic skin diseases. This study examined the connection between seladelpar's antipruritic effects and IL-31 and bile acid levels in patients with PBC. APPROACH AND RESULTS: IL-31 levels were quantified in serum samples from the ENHANCE study of patients with PBC receiving daily oral doses of placebo (n = 55), seladelpar 5 mg (n = 53) or 10 mg (n = 53) for 3 months, and for healthy volunteers (n = 55). IL-31 levels were compared with pruritus using a numerical rating scale (NRS, 0-10) and with bile acid levels. Baseline IL-31 levels closely correlated with pruritus NRS ( r = 0.54, p < 0.0001), and total ( r = 0.54, p < 0.0001) and conjugated bile acids (up to 0.64, p < 0.0001). Decreases in IL-31 were observed with seladelpar 5 mg (-30%, p = 0.0003) and 10 mg (-52%, p < 0.0001) versus placebo (+31%). Patients with clinically meaningful improvement in pruritus (NRS ≥ 2 decrease) demonstrated greater dose-dependent reductions in IL-31 compared to those without pruritus improvement (NRS < 2 decrease). Strong correlations were observed for the changes between levels of IL-31 and total bile acids ( r = 0.63, p < 0.0001) in the seladelpar 10 mg group. CONCLUSIONS: Seladelpar decreased serum IL-31 and bile acids in patients with PBC. The reductions of IL-31 and bile acids correlated closely with each other and pruritus improvement, suggesting a mechanism to explain seladelpar's antipruritic effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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".