Fenebrutinib, a Bruton’s tyrosine kinase inhibitor, blocks distinct human microglial signaling pathways
Bibliographic record
Abstract
Abstract Background Bruton’s tyrosine kinase (BTK) is an intracellular signaling enzyme that regulates B-lymphocyte and myeloid cell functions. Due to its involvement in both innate and adaptive immune compartments, BTK inhibitors have emerged as a therapeutic option in autoimmune disorders such as multiple sclerosis (MS). Brain-penetrant, small-molecule BTK inhibitors may also address compartmentalized neuroinflammation, which is proposed to underlie MS disease progression. BTK is expressed by microglia, which are the resident innate immune cells of the brain; however, the precise roles of microglial BTK and impact of BTK inhibitors on microglial functions are still being elucidated. Research on the effects of BTK inhibitors has been limited to rodent disease models. This is the first study reporting effects in human microglia. Methods Here we characterize the pharmacological and functional properties of fenebrutinib, a potent, highly selective, noncovalent, reversible, brain-penetrant BTK inhibitor, in human microglia and complex human brain cell systems, including brain organoids. Results We find that fenebrutinib blocks the deleterious effects of microglial Fc gamma receptor (FcγR) activation, including cytokine and chemokine release, microglial clustering and neurite damage in diverse human brain cell systems. Gene expression analyses identified pathways linked to inflammation, matrix metalloproteinase production and cholesterol metabolism that were modulated by fenebrutinib treatment. In contrast, fenebrutinib had no significant impact on human microglial pathways linked to Toll-like receptor 4 (TLR4) and NACHT, LRR and PYD domains-containing protein 3 (NLRP3) signaling or myelin phagocytosis. Conclusions Our study enhances the understanding of BTK functions in human microglial signaling that are relevant to MS pathogenesis and suggests that fenebrutinib could attenuate detrimental microglial activity associated with FcγR activation in people with MS.
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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 | 0.000 |
| 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".