MétaCan
Menu
Back to cohort

1011 Metabolic reprogramming alters natural killer cell responses in chronic graft-versus-host disease

2024· article· en· W4404052762 on OpenAlexaff
Ao Mei, Madeline Lauener, Kirk R. Schultz, Subramaniam Malarkannan

Bibliographic record

VenueRegular and Young Investigator Award Abstracts · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicImmune Cell Function and Interaction
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsReprogrammingDiseaseHost (biology)Graft-versus-host diseaseCellBiologyImmunologyMedicineEcologyGeneticsInternal medicine

Abstract

fetched live from OpenAlex

<h3>Background</h3> Allogeneic hematopoietic stem cell transplantation (HSCT) has been developed as a major treatment option for leukemia and lymphoma patients. HSCT transfers pluripotent stem cells to reconstitute patients’ hematopoiesis with functional immune cells. Although the clinical practice of HSCT has been extensively studied and significantly improved over the last decades, the leading cause of late morbidity and mortality in patients remains chronic graft-versus-host disease (cGVHD). In published studies of cGVHD, natural killer (NK) cells have been recognized as one of the earliest immune cells reconstituted in post-HSCT patients. NK cells are known to suppress cGVHD with the potential, not limited to cytotoxicity, to restrain pathogenic cell types. Respectively, subsets of CD56<sup>bright</sup> NK cells, previously categorized as immature, are suggested to play a regulatory function in cGVHD patients. However, the knowledge gap pertains to the molecular mechanisms by which subsets of NK cells mediate the suppression of cGVHD in response to distinct environmental cues. <h3>Methods</h3> We performed single-cell RNA sequencing on NK cells isolated from the PBMC of patients who developed cGVHD (5 patients) or not (6 patients). With knowledge from previously published data, we performed <i>in vitro</i> assays on human NK cells collected from healthy donors to confirm the new findings from single-cell RNA sequencing. <h3>Results</h3> In our single-cell RNA sequencing results, we were able to identify distinct subsets of NK cells (figure 1A), which have significantly different percentages between the two groups of patients (figure 1B). Besides quantitative differences, transcriptomic differences were also observed among NK cells. More importantly, transcriptionally, we found NK cell subsets responded differently to IFN-α and IL-12/IL-18 between the two groups of patients (figure 1C). Respectively, NK cells from chronic GVHD patients have a considerate reduction of gene expression in response to IL-12/IL-18, with responses shifted toward IFN-α stimulation. In the previous publication, α-Ketoglutaric acid (aKG), one of the key intermediates in the TCA cycle, has been identified to be significantly increased in the plasma of chronic GVHD patients compared. By <i>in vitro</i> treatment of human NK cells with aKG, we confirmed that aKG alone can alter NK cell differentiation and responses to cytokines including IL-12/IL-18 and IFN-α via epigenetic modification. <h3>Conclusions</h3> Our study has revealed a novel mechanism of how the differentiation and function of human NK cells can be epigenetically reprogrammed by aKG, leading to different cGVHD progression. This finding has high translational relevance and can contribute to the treatment of cGVHD patients.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.815
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

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)0.0000.000

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 head0.014
GPT teacher head0.247
Teacher spread0.233 · 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 teacher head, not a consensus.

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 routes1
Has abstractyes

Explore more

Same venueRegular and Young Investigator Award AbstractsSame topicImmune Cell Function and InteractionFrench-language works237,207