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Record W4402403088 · doi:10.1101/2024.09.08.611829

β2-Adrenergic Biased Agonist Nebivolol Inhibits the Development of Th17 and the Response of Memory Th17 Cells in an NF-κB-Dependent Manner

2024· preprint· en· W4402403088 on OpenAlexafffund
Mehri Hajiaghayi, Fatemeh Gholizadeh, Eric Han, Samuel R. Little, Niloufar Rahbari, Isabella Ardila, Carolina Naranjo, Kasra Tehranimeh, Steve C. C. Shih, Peter J. Darlington

Bibliographic record

VenuebioRxiv (Cold Spring Harbor Laboratory) · 2024
Typepreprint
Languageen
FieldNeuroscience
TopicStress Responses and Cortisol
Canadian institutionsMcGill UniversityConcordia University
FundersNatural Sciences and Engineering Research Council of Canada
KeywordsNebivololFlow cytometryCREBAdrenergic receptorCell biologyReceptorPeripheral blood mononuclear cellBiologyChemistryMolecular biologyEndocrinologyTranscription factorGeneIn vitroBiochemistry

Abstract

fetched live from OpenAlex

Abstract Introduction Adrenergic receptors regulate metabolic, cardiovascular and immunological functions in response to the sympathetic nervous system. The effect of β2-adrenergic receptor (AR) as a high-expression receptor on different subpopulations of T cells is complex and varies depending on the type of ligand and context. While traditional β2-AR agonists generally suppress T cells, they potentially enhance IL-17A production by Th17 cells. The effects of pharmacological drugs that count as biased agonists of AR like nebivolol are not completely understood. We investigated the impact of nebivolol on human memory CD4+ T (Th1, Th2, Th17) cells and polarized naïve Th17 cells highlighting its potential for IL-17A suppression via a non-canonical β2AR cell-signaling pathway. Methods The effects of nebivolol were tested on healthy human peripheral blood mononuclear cells, purified memory Th cells, and polarized naïve Th17 cells activated with antiCD3/antiCD28/antiCD2 ImmunoCult reagent. IFN-γ, IL-4, and IL-17A which are primarily derived from Th1, Th2, and Th17 cells respectively, were quantified by ELISA and flow cytometry. IL-10 was measured by ELISA. Gene expression of RORC, ADRB1, ADRB2, and ADRB3 was evaluated by qPCR. The ADRB2 gene was knocked out in memory Th cells using CRISPR/Cas9. Protein expression of phosphorylated-serine133-CREB and phosphorylated-NF-κB p65 was assessed by Western blot. Proliferation was assessed by fluorescent dye loading and flow cytometry. Results Nebivolol treatment decreased IL-17A and IFN-γ secretion by activated-memory Th cells and elevated IL-4 levels. Nebivolol reduced the proportion of IL-17A+ Th cells and downregulated RORC expression. Unlike the β2-AR agonist terbutaline, nebivolol inhibited the shift of naïve CD4+ T cells towards the Th17 phenotype. IL-10 and proliferation index remained unchanged. Nebivolol-treated β2-knockout memory Th cells showed significant inhibition of β2AR-mediated signaling, evidenced by the absence of IL-17A suppression compared to controls. Phosphorylation of the NF-κB p65 subunit was inhibited by nebivolol, but CREB phosphorylation was not changed, suggesting a selective transcriptional control. Conclusions The findings demonstrate that nebivolol acts through a β2-AR-mediated signaling pathway, as a distinctive anti-inflammatory agent capable of selectively shifting Th17 cells and suppressing phosphorylation of NF-κB. This highlights nebivolol’s potential for therapeutic interventions in chronic autoimmune conditions with elevated IL-17A levels.

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 imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.009

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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.

Opus teacher head0.025
GPT teacher head0.244
Teacher spread0.219 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

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".

Quick stats

Citations0
Published2024
Admission routes2
Has abstractyes

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