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Record 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 on 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

Bibliographic record

VenueBlood · 2015
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsUniversity of Victoria
Fundersnot available
KeywordsInflammationTLR4Innate immune systemPattern recognition receptorMonocyteImmunologyThalassemiaToll-like receptorHemeBiologyImmune systemMedicineInternal medicineBiochemistry

Abstract

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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.

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: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.001
Threshold uncertainty score0.004

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.251
Teacher spread0.227 · 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 designObservational
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".

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Citations0
Published2015
Admission routes1
Has abstractyes

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