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TYPE I INTERFERON AND MITOCHONDRIAL DYSFUNCTION ARE ASSOCIATED WITH DYSREGULATED CYTOTOXIC CD8+ T CELL RESPONSES IN JUVENILE SYSTEMIC LUPUS ERYTHEMATOSUS

2025· article· en· W4410715677 on OpenAlexvenueno aff
Ania Radziszewska, Hannah Peckham, Restuadi Restuadi, Melissa Kartawinata, Dale Moulding, Nina de Gruijter, George Robinson, Claire T. Deakin, Meredyth Wilkinson, Lucy R. Wedderburn, Elizabeth C. Jury, Elizabeth C. Rosser, Coziana Ciurtin

Bibliographic record

VenueThe Journal of Rheumatology · 2025
Typearticle
Languageen
FieldMedicine
TopicSystemic Lupus Erythematosus Research
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineCytotoxic T cellJuvenileCD8ImmunologyLupus erythematosusImmune systemAntibodyBiologyIn vitro

Abstract

fetched live from OpenAlex

PV001 / #50 Poster Topic: AS01 - Adaptive Immunity Background/Purpose Juvenile systemic lupus erythematosus (JSLE) is an autoimmune condition which causes significant morbidity in children and young adults. While many aspects of immune dysfunction have been studied extensively in adult-onset SLE, there is limited and contradictory evidence of how cytotoxic CD8+ T cells contribute to disease pathogenesis, and studies exploring cytotoxicity in JSLE are rare. Methods Detailed characterization of peripheral blood CD8+ T cells was undertaken in JSLE patients (n=44, median age 22 years and disease duration 9 years) and age/sex-matched healthy controls (HC, n=68, median age 20 years). Multiparameter flow cytometric immunophenotyping, RNA sequencing, serum metabolomic profiling, cell culture assays/functional in vitro studies, and mitochondrial morphology studies were performed. Results Frequencies of CD8+ T cells expressing the cytotoxic mediator perforin and effector cytokines interferon (IFN)-γ and tumor-necrosis-factor (TNF)-α were reduced in JSLE vs HC, irrespective of treatment or disease activity. Transcriptomic and serum metabolomic analysis identified that upregulated type I IFN signaling, mitochondrial dysfunction and metabolic disturbances underpinned these observations (see Figure). Mechanistic studies demonstrated that alteration in these pathways lead to a deficiency in effector memory (EM) JSLE CD8+ T cells, which are enriched for cytotoxic mediator-expressing cells, due to enhanced apoptosis of these cells selectively in JSLE vs HC. Figure. Transcriptomic analysis reveals upregulation of IFN-α responses and potential metabolic and mitochondrial disturbances in CD8+ T cells in JSLE. (a) Volcano plot showing differences in gene expression from RNA sequencing of CD8+ T cells from JSLE (n=26) vs HC (n=29). Blue and red points represent statistically significant differentially expressed genes below the FDR adjusted p-value threshold of 0.05. Blue and red arrows indicate number of statistically significant downregulated and upregulated genes, respectively. (b) Bar plot showing -log10p values and enrichment ratios (ER) of summary enriched pathway GO BP ontology terms in CD8+ T cells in JSLE vs HC using the 147 significantly upregulated and 91 significantly downregulated genes (FDR adjusted p<0.05). Statistical significance of enrichment was determined using a p-value cut-off of 0.01 and a minimum enrichment score of 1.5. Terms highlighted in red and blue represent pathways of potential interest, derived from upregulated (red) and downregulated (blue) genes in JSLE vs HC. (c) Word cloud representing all words taken from significantly enriched pathways in Metascape GO enrichment and GSEA analysis of DEGs in CD8+ T cells in JSLE vs HC. Text size indicates the frequency of the word. Conclusions Cytotoxic capacity of CD8+ T cells is diminished in JSLE due to a numerical deficiency in EM CD8+ T cells, which is linked to mitochondrial defects, dysregulated type I IFN signaling, and increased apoptosis. Future studies are needed to understand the therapeutic implications of these findings.

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 score0.005

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 head0.014
GPT teacher head0.265
Teacher spread0.250 · 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".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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