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Ezh2 Shapes T Cell Plasticity to Drive Atherosclerosis

2025· article· en· W4407235444 on OpenAlexaff
Cecilia Assunta Bonfiglio, Michael Lacy, Vasiliki Triantafyllidou, Floriana Maria Farina, Aleksandar Janjic, Katrin Nitz, Yuting Wu, Venetia Bazioti, Irem Avcilar-Kücükgöze, Yonara Freire Soares Marques, Markus Joppich, Mahadia Kumkum, Anuroop Venkateswaran Venkatasubramani, Axel Imhof, Wolfgang Enard, Lars Mäegdefessel, Menno P.J. de Winther, Christian Weber, Donato Santovito, Esther Lutgens, Dorothee Atzler

Bibliographic record

VenueCirculation · 2025
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAtherosclerosis and Cardiovascular Diseases
Canadian institutionsInstitute of Infection and Immunity
FundersAmsterdam Cardiovascular Sciences, Amsterdam University Medical CentersNational Institutes of HealthBerlin Institute of HealthBundesministerium für Bildung und ForschungZonMwFondation LeducqDeutsche ForschungsgemeinschaftAmsterdam University Medical CentersDeutsches Zentrum für Herz-Kreislaufforschung
KeywordsEZH2CCL5T cellImmune systemCD8ChemokineCancer researchInflammationBiologyImmunologyCell biologyEpigeneticsIL-2 receptor

Abstract

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BACKGROUND: The activation and polarization of T cells play a crucial role in atherosclerosis and dictate athero-inflammation. The epigenetic enzyme EZH2 (enhancer of zeste homolog 2) mediates the H3K27me3 (trimethylation of histone H3 lysine 27) and is pivotal in controlling T cell responses. METHODS: To detail the role of T cell EZH2 in atherosclerosis, we used human carotid endarterectomy specimens to reveal plaque expression and geography of EZH2. Atherosclerosis-prone Apoe (apolipoprotein E)–deficient mice with CD (cluster of differentiation) 4 + or CD8 + T cell–specific Ezh2 deletion (Ezh2 cd4 -knockout [KO], Ezh2 cd8 -KO) were analyzed to unravel the role of T cell Ezh2 in atherosclerosis and T cell–associated immune status. RESULTS: EZH2 expression is elevated in advanced human atherosclerotic plaques and primarily expressed in the T cell nucleus, suggesting the importance of canonical EZH2 function in atherosclerosis. Ezh2 cd4 -KO, but not Ezh2 cd8 -KO, mice showed reduced atherosclerosis with fewer advanced plaques, which contained less collagen and macrophages, indicating that Ezh2 in CD4 + T cells drives atherosclerosis. In-depth analysis of CD4 + T cells of Ezh2 cd4 -KO mice revealed that absence of Ezh2 results in a type 2 immune response with increased Il-4 (interleukin 4) gene and protein expression in the aorta and lymphoid organs. In vitro, Ezh2 -deficient T cells polarized macrophages toward an anti-inflammatory phenotype. Single-cell RNA-sequencing of splenic T cells revealed that Ezh2 deficiency reduced naive, Ccl5 + (C-C motif chemokine ligand 5) and regulatory T cell populations and increased the frequencies of memory T cells and invariant natural killer T (iNKT) cells. Flow cytometric analysis identified a shift toward Th2 (type 2 T helper) effector CD4 + T cells in Ezh2 cd4 -KO mice and confirmed a profound increase in splenic iNKT cells with increased expression of Plzf (promyelocytic leukemia zinc finger), which is the characteristic marker of the iNKT2 subset. Likewise, Zbtb16 ([zinc finger and BTB domain containing 16], the Plzf-encoding gene) transcripts were elevated in the aorta of Ezh2 cd4 -KO mice, suggesting an accumulation of iNKT2 cells in the plaque. H3K27me3–chromatin immunoprecipitation followed by quantitative polymerase chain reaction showed that T cell–Ezh2 regulates the transcription of the Il-4 and Zbtb16 genes. CONCLUSIONS: Our study uncovers the importance of T cell EZH2 in human and mouse atherosclerosis. Inhibition of Ezh2 in CD4 + T cells drives type 2 immune responses, resulting in an accumulation of iNKT2 and Th2 cells, memory T cells and anti-inflammatory macrophages that limit the progression of atherosclerosis.

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 score0.002
Threshold uncertainty score0.008

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 integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.001

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 head0.011
GPT teacher head0.220
Teacher spread0.209 · 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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Citations19
Published2025
Admission routes1
Has abstractyes

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