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Record W4417016097 · doi:10.1182/blood-2025-1155

Innate immune dysregulation in monocytes in sickle cell disease

2025· article· en· W4417016097 on OpenAlexaff
Sarah Hinderstein, Gemma Vidal‐Pedrola, Subhasis Mohanty, Irene Matos, Judith Carbonella, Cecelia Calhoun, Lakshmanan Krishnamurti, Albert C. Shaw, İnci Yıldırım

Bibliographic record

VenueBlood · 2025
Typearticle
Languageen
FieldMedicine
TopicHemoglobinopathies and Related Disorders
Canadian institutionsInstitute of Infection and Immunity
Fundersnot available
KeywordsCD14CytokineInnate immune systemPeripheral blood mononuclear cellMonocyteImmune systemLipoteichoic acidReceptor

Abstract

fetched live from OpenAlex

Abstract Background : Sickle cell disease (SCD) is the most common genetic hematological disorder affecting ~100,000 people in the United States, resulting from a single base pair mutation resulting in a glutamic acid to valine substitution at position 6 in the beta-globin protein. Individuals with SCD have higher morbidity and mortality due to infectious diseases. A significant portion of patients with SCD, ~65% in some series, show impaired vaccine response and remain under-protected against vaccine-preventable infections. Chronic hemolysis associated with SCD results in splenic infarction and functional asplenia, but also overwhelms mechanisms to sequester heme and other damage-associated molecular patterns (DAMPs) released from erythrocytes that activate innate immune pattern recognition receptors such as Toll-like Receptors (TLRs). We aimed to investigate TLR function in monocytes and assess the effects of TLR 2/6, TLR4, and TLR7/8 agonists, lipoteichoic acid (LTA), lipopolysaccharide (LPS), and Resiquimod (R848) respectively, on cytokine production in monocytes from patients with and without SCD. Methods : Peripheral blood mononuclear cells (PBMC) were isolated from pediatric and young adult patients with SCD (n=17) and age and race-matched healthy participants (n=10), cryopreserved, and thawed before stimulation. We used flow cytometry to identify monocyte subsets and cytokine production by monocytes after stimulation with LTA, R848, or LPS. Monocyte subsets were classified as classical (CD14++CD16-), intermediate (CD14++CD16+), and non-classical (CD14dimCD16+). Cytokine production was evaluated in these populations using intracellular cytokine staining to detect TNF-a, IL-1b, IL-6, IL-8, and MCP-1. Statistical significance was compared using Mann-Whitney tests with a significance cutoff value of p=0.05. Results : SCD participants had total white blood cell counts and monocyte percentages within the normal range for their age. The median WBC count was 9.0x103 cell/µL, IQR 7.3x103 cell/µL-10.3x103 cells/µL, and the median monocyte percentage was 10%, IQR 8%-12.25%. SCD patients had a lower proportion of classical (CD14++CD16-) monocytes compared to healthy controls in the unstimulated group (p=0.0004), and in LTA (p=0.002), LPS (p=0.008), and R848 (p=0.03) groups after a 6-hour stimulation. There was a statistically significant increase in non-classical (CD14dimCD16+) monocytes in SCD patients in the unstimulated (p=0.02) group, and in the LTA (p=0.005) and R848 (p=0.04) groups following a 6-hour stimulation. After stimulation with LTA, there was a significant decrease in the percentage of classical monocytes producing IL-6 (p=0.02) in SCD patients compared to healthy controls and an increase in the percentage of classical monocytes producing IL-8 (p=0.006) in SCD patients compared to healthy controls. Following LPS stimulation, there was a significant increase in the percentage of classical monocytes producing IL-8 in SCD patients compared to healthy controls (p=0.002). After stimulation with R848, there was a significant increase in the percentage of classical monocytes producing IL-6 (p=0.04), IL-1b (p=0.0001), and IL-8 (p=<0.000001) compared to healthy controls. Conclusion: Monocytes from SCD patients show trends toward increased inflammatory responses, especially following TLR7/8 stimulation, compared to monocytes from age and race-matched healthy controls. This suggests alterations in TLR function in individuals with SCD, resulting in dysregulated innate immunity that may contribute to impaired responses to infection or vaccination.

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 score0.001
Threshold uncertainty score0.005

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 head0.004
GPT teacher head0.226
Teacher spread0.222 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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