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Abstract 15469: Activation of Sting Pathway Promotes Epigenetic Induction of Smooth Muscle Cell Phenotypic Alterations in Aortic Wall

2022· article· en· W4380836596 on OpenAlexaff
Abhijit Chakraborty, Yanming Li, Chen Zhang, Li Yang, Kimberly R. Rebello, Lin Zhang, Kaifu Chen, Hernán Vásquez, Joseph S. Coselli, Scott A. LeMaire, Ying H. Shen

Bibliographic record

VenueCirculation · 2022
Typearticle
Languageen
FieldMedicine
TopicAortic aneurysm repair treatments
Canadian institutionsKimberly-Clark (Canada)
Fundersnot available
KeywordsEpigeneticsChromatinBiologyChromatin remodelingCell biologyPhenotypic switchingProinflammatory cytokineChromatin immunoprecipitationPhenotypeMedicineCancer researchGene expressionImmunologyGeneInflammationGeneticsPromoter

Abstract

fetched live from OpenAlex

Introduction: Smooth muscle cell phenotypic alteration is a prominent feature of aortic aneurysms and dissections (AAD) that causes the loss of functional, contractile, smooth muscle cells (SMCs) and subsequent aortic dysfunction. However, SMC phenotypic alteration in AAD and the underlying mechanism is poorly understood. Hypothesis: Stress on the aorta induces a phenotypic switch in SMCs from a contractile role to a pro-inflammatory role that promotes cell dysfunction and death. Methods: We performed single-cell RNA and ATAC sequencing (scRNA-seq, scATAC-seq) of ascending aortic tissues from patients with sporadic ascending AAD and organ donor controls, alongside murine aortic tissues from a sporadic AAD model and wild-type mice. The role of the STING pathway in SMC phenotypic alterations was studied in human aortic SMCs. Chromatin immunoprecipitation assays were used to study epigenetic regulation Results: Significant SMC transformation from a contractile phenotype to a pro-inflammatory, pro-fibroblast, and pro-death phenotype was seen in scRNA-seq of aortic tissues from AAD patients and a sporadic AAD murine tissue. Our sc-ATACseq indicated that SMC transformation was partially controlled by chromatin remodeling of these genes, and IRF3 was identified as a key transcriptional factor for the reduction of chromatin accessibility of contractile genes, but induction of chromatin accessibility of inflammatory genes. In cultured SMCs, cytosolic DNA, through STING-TBK1 signaling, activated IRF3, which directly bound cis-elements of contractile genes, and recruited EZH2 to induce repressive H3K27me3 modification, leading to SMC gene suppression. Activated IRF3 also induced inflammatory gene expression. SMC-Sting deficiency prevented proinflammatory phenotypic switch in the sporadic AAD mouse model and restored contractile phenotype. Conclusion: We highlight an epigenetic pathway responsible for SMC dysfunction that induced SMC gene suppression and SMC phenotype changes and identified STING-TBK-IRF3-EZH2 as key signaling that suppresses SMC genes. To the best of our knowledge, this is the first study reporting that the STING pathway contributes to AAD development by SMC transition from a contractile to an inflammatory phenotype.

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 score0.007
Threshold uncertainty score0.025

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)0.0070.002

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 head0.260
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 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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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