Exposure-response of serum biomarkers to vamorolone, a dissociative corticosteroidal anti-inflammatory drug, in 4- to <7-year children
Bibliographic record
Abstract
OBJECTIVES: Corticosteroid agonists of the glucocorticoid receptor are a mainstay of therapeutics for pro-inflammatory conditions. Vamorolone is a novel partial agonist that is differentiated from the other members of the corticosteroid class by non-metabolism by 11β-hydroxysteroid dehydrogenases, antagonism of the mineralocorticoid receptor, and differential co-factor binding. Our objective was to define the pharmacodynamic response of serum proteins to vamorolone. METHODS: Clinical trial participants with Duchenne muscular dystrophy (4 to <7 yr; n = 39; mean [SD] age = 5.3 [1.0]) enrolled in a multiple ascending dose study of vamorolone were studied (24-fold dose range). Dose-response and exposure-response of 1,305 serum proteins were defined by intra-subject longitudinal changes (baseline vs. Day 14). RESULTS: Dose-response analysis identified 159 of 1,305 serum proteins as dose-responsive to vamorolone (12 % of proteins tested; 20 % increased, 80 % decreased). Two inflammatory networks showed drug-responsive suppression. One centered on extracellular serine proteases and lymphotoxins (PI3, KLK7, KLK8, KLK11, lymphotoxins A, B) converging on NFκB. The second centered on cytokines (CCL22/MDC, CCL21, CCL14, CXCL12) and IL23 signaling. In the IL23 network, acutely responsive anti-inflammatory proteins included increases of an inhibitor of IL17 signaling (IL17RC) and decreases of IL23 (IL12B:IL23A). A protein associated with resistance to environmental microbes, PTP1C, showed strong induction and is a novel candidate for aspects of corticosteroid efficacy. Two networks of cell-associated proteins were identified as drug responsive that may represent muscle tissue response (efficacy): connective tissue remodeling upstream of Notch signaling, and plasma membrane proteins impinging on AKT1 signaling. CONCLUSION: The serum proteome pharmacodynamics of the response to vamorolone was defined.
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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.000 |
| 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".