Ivig Negatively Regulates LPS-Induced Monocytes Activation Through a Microrna-146a Related Mechanism
Notice bibliographique
Résumé
Abstract Abstract 3274 Background: Cells from the monocytic lineage are known to play a central role in the immune defense against pathogens. In the adaptive immune response, they act as antigen presenting cells to trigger T and B cell responses. Monocytic cells also participate in innate immunity following recognition of pathogen-associated molecular patterns (PAMPs) such as bacterial lipopolysaccharides (LPS), which leads to their activation and release of very potent inflammatory mediators. The innate immune response thus needs to be tightly regulated to control not only its onset, but also its termination in order to avoid excessive inflammation. Recent studies have shown that the differentiation and functions of monocytic cells involve small RNA species, named microRNAs (miRNAs). MiRNAs are 21–23 nucleotide long single strand RNAs, which mainly cause gene silencing by degradation of target mRNAs or by inhibition of translation. Among them, miR-146a has captivated interest as it plays an important role in the negative regulation of acute inflammatory responses during activation of the innate immune system. In fact, it has been shown that miR-146a expression is gradually increased in THP-1 monocytic cells following stimulation with LPS or cytokines (e.g. IL-1β and TNF-α) via a NF-κB dependent pathway. MiR-146a inhibits the expression of IRAK1 and TRAF6 leading to the subsequent suppression of NF-κB activity. Consequently, the expression of NF-κB target genes such as IL-1β, TNF-α and PU.1 is suppressed. Therefore, miR146a controls NF-κB signaling via a negative feedback regulation loop and thus can be considered as an anti-inflammatory mediator. IVIg is a therapeutic preparation of polyclonal human IgG isolated from the plasma of thousands of healthy donors. IVIg is well known for its anti-inflammatory effects on a variety of immune cells and processes. More precisely, it has been shown to abrogate the capacity of monocyte-derived dendritic cells to secrete pro-inflammatory cytokines while increasing the expression of anti-inflammatory cytokines such as IL-10. We thus hypothesize that at least some of the anti-inflammatory effects of IVIg on monocytic cells could be triggered through the modulation of miR-146a expression. Objectives: To evaluate the involvement of miR-146a in the anti-inflammatory effects of IVIg following LPS stimulation of human monocytes. Methods: Human monocytes were obtained from the blood of healthy volunteers and treated with LPS (1 mg/mL) or IVIg (15 mg/mL) alone or alternatively, pretreated with LPS followed by addition of IVIg. Pre-treatment with LPS was done during for 4 h prior to addition of IVIg for 3, 6, 12 and 24 hours. Cells were then recovered and separated in two parts. The first part was used to extract the small RNA fraction of total RNA for miRNA analysis and the second part was used for protein isolation. The miR-146a level was measured by real time PCR while NF-kB and IRF4 protein levels were evaluated by western blotting. Finally, the expression of the transcription factor PU.1 was evaluated by flow cytometry. Results: Our preliminary data revealed that addition of IVIg to LPS-pretreated human monocytes resulted in a significant upregulation of miR-146a expression associated with a significant reduction in NF-κB expression. Furthermore, the expression of the PU.1/IRF4 transcriptional activator complex involved in the stimulation of inflammatory cytokine production was modulated. Indeed, we found that the expression PU.1 was reduced in IVIg-treated cells whereas IRF4 expression was increased, thus promoting the IRF4-mediated cytokine production inhibitory pathway. Conclusion: Our preliminary data suggest that in human monocytes, the anti-inflammatory effects of IVIg may involve miR-146a negative feedback loop regulation of NF-κB activity. Disclosures: No relevant conflicts of interest to declare.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,002 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».