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Record W4393405818 · doi:10.1073/pnas.2400675121

The IRG1–itaconate axis protects from cholesterol-induced inflammation and atherosclerosis

2024· article· en· W4393405818 on OpenAlexfundno aff
Yannick Cyr, Fazli Bozal, José Gabriel Barcia Durán, Alexandra Newman, Letizia Amadori, Panagiotis Smyrnis, Morgane Gourvest, Dayasagar Das, Michael Gildea, Ravneet Kaur, Tracy Zhang, Kristin M. Wang, Richard Von Itter, P. Martin Schlegel, Samantha Dupuis, Bernard F. Sanchez, Ann Marie Schmidt, Edward A. Fisher, Coen van Solingen, Chiara Giannarelli, Kathryn J. Moore

Bibliographic record

VenueProceedings of the National Academy of Sciences · 2024
Typearticle
Languageen
FieldImmunology and Microbiology
TopicAtherosclerosis and Cardiovascular Diseases
Canadian institutionsnot available
FundersNational Institute of Allergy and Infectious DiseasesNational Heart, Lung, and Blood InstituteCanadian Institutes of Health ResearchYork UniversityChan Zuckerberg InitiativeNYU Grossman School of MedicineNational Institute of General Medical SciencesAmerican Heart AssociationClinical Trials Fund, Canadian Institutes of Health Research
KeywordsInflammationProinflammatory cytokineFoam cellInflammasomeImmune systemMacrophagePeripheral blood mononuclear cellLipid metabolismBiologyImmunologyMedicineEndocrinologyBiochemistryIn vitro

Abstract

fetched live from OpenAlex

Atherosclerosis is fueled by a failure to resolve lipid-driven inflammation within the vasculature that drives plaque formation. Therapeutic approaches to reverse atherosclerotic inflammation are needed to address the rising global burden of cardiovascular disease (CVD). Recently, metabolites have gained attention for their immunomodulatory properties, including itaconate, which is generated from the tricarboxylic acid-intermediate cis-aconitate by the enzyme Immune Responsive Gene 1 (IRG1/ACOD1). Here, we tested the therapeutic potential of the IRG1–itaconate axis for human atherosclerosis. Using single-cell RNA sequencing (scRNA-seq), we found that IRG1 is up-regulated in human coronary atherosclerotic lesions compared to patient-matched healthy vasculature, and in mouse models of atherosclerosis, where it is primarily expressed by plaque monocytes, macrophages, and neutrophils. Global or hematopoietic Irg1 -deficiency in mice increases atherosclerosis burden, plaque macrophage and lipid content, and expression of the proatherosclerotic cytokine interleukin (IL)-1β. Mechanistically, absence of Irg1 increased macrophage lipid accumulation, and accelerated inflammation via increased neutrophil extracellular trap (NET) formation and NET-priming of the NLRP3-inflammasome in macrophages, resulting in increased IL-1β release. Conversely, supplementation of the Irg1 –itaconate axis using 4-octyl itaconate (4-OI) beneficially remodeled advanced plaques and reduced lesional IL-1β levels in mice. To investigate the effects of 4-OI in humans, we leveraged an ex vivo systems-immunology approach for CVD drug discovery. Using CyTOF and scRNA-seq of peripheral blood mononuclear cells treated with plasma from CVD patients, we showed that 4-OI attenuates proinflammatory phospho-signaling and mediates anti-inflammatory rewiring of macrophage populations. Our data highlight the relevance of pursuing IRG1–itaconate axis supplementation as a therapeutic approach for atherosclerosis in humans.

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 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 score0.243
Threshold uncertainty score0.297

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.032
GPT teacher head0.264
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.

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".

Quick stats

Citations67
Published2024
Admission routes1
Has abstractyes

Explore more

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