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Enregistrement W2979831829 · doi:10.1182/blood.v126.23.950.950

Iron Level and Monocyte Morphology Predict TLR4 Expression and Reactive Oxygen Species Production Which Influences Chronic Inflammation in β-Thalassemia

2015· article· en· W2979831829 sur OpenAlexaff
Patrick B. Walter, Paul Harmatz, Annie Higa, Vivian Ng, Marcels Weyhmiller, Patricia Evans, John B. Porter, Nancy Sweeters, Jackson Price, David W. Killilea, Lynne Neumayr, Ashutosh Lal, Elliott Vichinsky

Notice bibliographique

RevueBlood · 2015
Typearticle
Langueen
DomaineMedicine
ThématiqueHemoglobinopathies and Related Disorders
Établissements canadiensUniversity of Victoria
Organismes subventionnairesnon disponible
Mots-clésInflammationTLR4Innate immune systemPattern recognition receptorMonocyteImmunologyThalassemiaToll-like receptorHemeBiologyImmune systemMedicineInternal medicineBiochemistry

Résumé

récupéré en direct d'OpenAlex

Abstract Introduction: β-thalassemia major requires a lifetime of transfusion and chelation therapy and despite improved chelation therapies, patients endure organ iron overload and increased hemolysis leading to organ injury and release of damage associated bio-markers. The structure of these markers are recognized by pattern recognition receptors (PRR) of the innate immune system as damage associated molecular patterns (DAMPs), which trigger inflammation and increased reactive oxygen species (ROS). The specificity of this recognition depends on PRRs, such as toll-like receptor 4 (TLR4), to provide the first line of defense against pathogens and DAMPS to initiate inflammation. Therefore, chronic organ iron loading is implicated in the chronic inflammation and morbidity of β-thalassemia major; however, the mechanism of how monocytes respond to iron loading in β-thalassemia remains largely unknown. This study investigated how chronic iron and heme overload affected innate immune cell morphology and expression of TLR4 and ROS by modeling THP-1 cellscompared to β-thalassemia monocytes. Methods: Cultured THP-1 monocytic cells were exposed to increasing concentrations of ferric citrate (0-250 μM) or heme (0-50 μM) for 24 hours or to chronic exposures of 40 μM ferric citrate for up to 3 weeks. Anti-human TLR4 phycoerythrin conjugated antibodies (TLR4-PE) were used to quantify TLR4 expression and 2,7-dichlorodihydrofluorescein diacetate (DCFH-DA) was used to measure ROS. Flow cytometry was done using a BD FACSCalibur. Peripheral-blood samples were obtained from 13 consenting β-thalassemia patients as part of the Novartis sponsored study investigating the effects of combined chelation therapy (CICL670AUS42T). Samples were also obtained from ethnically and age matched healthy controls. Peripheral-blood monocytes and THP-1 cells were gated on the parameters of forward and side scatter to stratify cells based on size and granularity, separating cells into two populations: larger more granular (LG) and smaller less granular (SG) cells. Results are reported as the MFI ratios of LG versus SG cells for TLR4-PE or DCFH-DA as a functional measure of the difference in TLR4 or ROS expression between these populations. Results: In vitro, LG THP-1 cells expressed 4-fold more TLR4 and 10-fold more ROS than SG cells (p < 0.001). Treatment of THP-1 cells with increasing concentrations of iron or heme for 1 day or 3 weeks, increased the ROS and TLR4 heterogeneity between LG and SG monocytes. The LG versus SG ratio of ROS production significantly correlated to the concentration of ferric citrate or heme added to the culture media (r = 0.64, p = 0.019 and r = 0.58 and p = 0.048, respectively). The mean ratio for iron but not heme treated THP-1 cells was significantly greater than for untreated cells (p = 0.008 and p = 0.406, respectively). Mean LG versus SG ratios of TLR4-PE MFI were 5.20 ± 1.56 for ferric citrate, 4.11 ± 0.90 for heme, and 3.78 ± 1.41 for untreated cells. We observed a similar TLR4 morphological heterogenic pattern in peripheral-blood monocytes from iron overloaded β-thalassemia patients. β-thalassemia LG monocytes had significantly greater TLR4 MFI than SG monocytes (LG mean = 11.91 ± 1.17, SG mean = 6.56 ± 1.02, p < 0.001). Long-term treatment of THP-1 monocytic cells for 3 weeks with 40 μM ferric citrate also resulted in the same phenomena regarding TLR4. No difference was observed in ROS production for control LG cells and SG cells; however, THP-1 cells treated for 3 weeks with 40uM ferric citrate revealed populations of LG cells that expressed 3 fold more ROS than SG cells. Conclusion: THP-1 monocytic cells and β-thalassemic peripheral-blood monocytes exhibit a morphological heterogeneity where LG cells express more TLR4 and in vitro, produce more ROS than SG cells. As TLR4 is one of the receptors for the initiation of inflammation, LG cells are likely greater contributors to the chronic inflammation experienced by β-thalassemia patients. Thus, we hypothesize that iron overload may give rise to monocytes that are larger and more granular and express more TLR4 and ROS. Disclosures Walter: Novartis: Research Funding. Porter:Shire: Consultancy, Honoraria; Novartis: Consultancy, Honoraria, Research Funding; Celgene: Consultancy.

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 enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,001
Score d'incertitude au seuil0,004

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,025
Tête enseignante GPT0,251
Écart entre enseignants0,227 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeObservationnel
Domainenon disponible
GenreEmpirique

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2015
Routes d'admission1
Résumé présentoui

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