Bruton Tyrosine Kinase Inhibition Decreases Inflammation and Differentially Impacts Phagocytosis and Cellular Metabolism in Mouse- and Human-derived Myeloid Cells
Bibliographic record
Abstract
Bruton tyrosine kinase (BTK) is a kinase expressed by various immune cells and is often activated under proinflammatory states. Although the majority of BTK-related research has historically focused on B cells, understanding the role of BTK in non-B cell populations is critical given myeloid cells also express BTK at comparable levels. In this study, we investigated and compared how BTK inhibition in human and murine myeloid cells alters cell phenotype and function. All experiments were performed using two BTK inhibitors (evobrutinib and tolebrutinib) that are currently in late-stage clinical trials for the treatment of multiple sclerosis. Assays were performed to assess the impact of BTK inhibition on cytokine and microRNA expression, phagocytic capacity, and cellular metabolism. In all cells, both evobrutinib and tolebrutinib significantly decreased phosphorylated BTK and LPS-induced cytokine release. BTK inhibition also significantly decreased the oxygen consumption rate and extracellular acidification rate in myeloid cells, and significantly decreased phagocytosis in murine-derived cells, but not human macrophages. To further elucidate the mechanism, we also investigated the expression of microRNAs known to impact the function of myeloid cells. BTK inhibition resulted in an altered microRNA expression profile (i.e., decreased miR-155-5p and increased miR-223-3p), which is consistent with a decreased proinflammatory myeloid cell phenotype. In summary, these results provide further insights into the mechanism of action of BTK inhibitors in the context of immune-related diseases, while also highlighting important species-specific and cell-specific differences that should be considered when interpreting and comparing results between preclinical and human studies.
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 machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 source (direct Gemma or distilled Codex), 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".