Evidence map›Paper›PMID 42490151›Full record

ArticleJCI insight2026

Single-cell RNA sequencing reveals clonally expanded CD4+ tissue-resident memory T cells in histidyl-tRNA synthetase-induced myositis.

Decheng Li, Daniel P Reay, Iago Pinal-Fernandez, Maria Casal-Dominguez, Andrew L Mammen, Sarah L Gaffen, Timothy B Oriss, Dana P Ascherman

Abstract read
In one paragraph

Article in JCI insight, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

What it found

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2 · The registry

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3 · Its place in the literature

Who cites it

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4 · The record

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5 · Who and what money

Authors and funding

8 authors.

Decheng LiDivision of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Daniel P ReayDivision of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Iago Pinal-FernandezNational Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, Maryland, USA.
Maria Casal-DominguezNational Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, Maryland, USA.
Andrew L MammenNational Institute of Arthritis and Musculoskeletal and Skin Diseases, National Institutes of Health, Bethesda, Maryland, USA.
Sarah L GaffenDivision of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Timothy B OrissDivision of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.
Dana P AschermanDivision of Rheumatology and Clinical Immunology, Department of Medicine, University of Pittsburgh, Pittsburgh, Pennsylvania, USA.

Funding

Innate Immune Activation in Autoimmune MyopathyR01AR071369 · NIAMS · UNIVERSITY OF PITTSBURGH AT PITTSBURGH · PI ASCHERMAN, DANA P · 2017 to 2021
$1.9M
NIAMS NIH HHS R01 AR071369
6 · The paper itself

Abstract

The precise mechanisms underlying the pathogenesis of idiopathic inflammatory myopathy (IIM) remain undefined. However, there has been increasing recognition that tissue-resident memory T cells (TRMs) play an important role in the pathogenesis of systemic autoimmune disease. In IIM, TRM-associated transcriptional signatures have been reported but on a very limited basis. By using multimodal single-cell RNA-sequencing analysis in our established murine model of histidyl-tRNA synthetase-induced myositis, we identified a prominent population of CD4+ TRMs in inflamed skeletal muscle. Muscle CD4+ TRMs exhibited high expression of genes encoding Cd69, Cxcr6, Runx3, and Prdm1, alongside low expression of Klf2, Ccr7, Sell, S1pr1, and Tcf7 - a profile that is generally consistent with previous reports of TRM gene signature and that we validate through comparison with transcriptomic profiles of human muscle tissue. Detailed pathway analysis in our model indicates that muscle CD4+ TRMs contribute to innate immune regulatory pathways enriched for TNF and IFN-γ signaling. Furthermore, analysis of TCR clonotype distribution and CDR3 sequence similarity revealed pronounced clonal expansion of CD4+ TRMs relative to other T cell subsets - a pattern that remained stable from 2 to 6 weeks after immunization. Collectively, these results suggest a potential role for CD4+ TRMs in the pathogenesis of autoimmune myositis.

Indexed as

CD4-Positive T-LymphocytesHistidine-tRNA LigaseMemory T CellsMyositisAnimalsDisease Models, AnimalHumansImmunologic MemoryMaleMiceMice, Inbred C57BLMuscle, SkeletalSequence Analysis, RNASingle-Cell AnalysisSingle-Cell Gene Expression AnalysisHistidine-tRNA LigaseAutoimmunityImmunologyMuscleT cellsTranscriptomics

Identifiers

PMID42490151
PMCPMC13564085

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.