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Record W4402903820 · doi:10.1126/sciimmunol.adj8094

Twin study identifies early immunological and metabolic dysregulation of CD8 <sup>+</sup> T cells in multiple sclerosis

2024· article· en· W4402903820 on OpenAlexaff
Vladyslav Kavaka, Luisa Mutschler, Clara de la Rosa del Val, Klara Eglseer, A.M. Martı́nez, Andrea Flierl‐Hecht, Birgit Ertl‐Wagner, Daniel Keeser, Matin Mortazavi, Klaus Seelos, Hanna Zimmermann, Jürgen Haas, Brigitte Wildemann, Tania Kümpfel, Klaus Dornmair, Thomas Korn, Reinhard Hohlfeld, Martin Kerschensteiner, Lisa Ann Gerdes, Eduardo Beltrán

Bibliographic record

VenueScience Immunology · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicT-cell and B-cell Immunology
Canadian institutionsSickKids FoundationHospital for Sick ChildrenUniversity of Toronto
Fundersnot available
KeywordsMultiple sclerosisNeuroinflammationCD8ImmunologyProinflammatory cytokineSubclinical infectionBiologyT cellPhenotypeCellCytotoxic T cellImmune systemInflammationGeneticsVirology

Abstract

fetched live from OpenAlex

Multiple sclerosis (MS) is an inflammatory neurological disease of the central nervous system with a subclinical phase preceding frank neuroinflammation. CD8 + T cells are abundant within MS lesions, but their potential role in disease pathology remains unclear. Using high-throughput single-cell RNA sequencing and single-cell T cell receptor analysis, we compared CD8 + T cell clones from the blood and cerebrospinal fluid (CSF) of monozygotic twin pairs in which the cotwin had either no or subclinical neuroinflammation (SCNI). We identified peripheral MS-associated immunological and metabolic alterations indicative of an enhanced migratory, proinflammatory, and activated CD8 + T cell phenotype, which was also evident in cotwins with SCNI and in an independent validation cohort of people with MS. Together, our in-depth single-cell analysis indicates a disease-driving proinflammatory role of infiltrating CD8 + T cells and identifies potential immunological and metabolic therapeutic targets in both prodromal and definitive stages of the disease.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
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 score0.202
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0000.005
Scholarly communication0.0000.001
Open science0.0010.001
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 head0.026
GPT teacher head0.243
Teacher spread0.217 · 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

Citations20
Published2024
Admission routes1
Has abstractyes

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