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Increased Tenascin-C expression contributes to cardiac dysfunction and fibrosis in Duchenne muscular dystrophy

2022· article· en· W4306291466 on OpenAlexaff
A Kiss, P L Szabo, Janine Ebner, Karlheinz Hilber, Dietmar Abraham, Sarah Costantino, Francesco Paneni, Anish Nikhanj, Niharika Kashyap, G Y Ouadit, Bruno K. Podesser

Bibliographic record

VenueEuropean Heart Journal · 2022
Typearticle
Languageen
FieldBiochemistry, Genetics and Molecular Biology
TopicMuscle Physiology and Disorders
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsMedicineTenascin CEjection fractionFibrosisCardiac fibrosisDuchenne muscular dystrophyInternal medicineInterquartile rangeCardiologyMyocardial fibrosisCardiac function curveMuscular dystrophyCardiomyopathyHeart failureDystrophinEndocrinologyImmunohistochemistry

Abstract

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Abstract Introduction and aims Cardiac fibrosis is characterized by the net accumulation of extracellular matrix (ECM) proteins in the cardiac interstitium and contributes to cardiac contractile dysfunction. In Duchenne muscular dystrophy (DMD), cardiomyopathy develops as a result of a dystrophin deficiency causing fibrofatty replacement of the myocardium, however the underlying mechanisms are not fully understood. There is a growing collection of evidence that ECM proteins, including Tenascin C (TN-C), plays a maladaptive role in left ventricular (LV) remodelling and cardiac fibrosis in ischemic heart disease. The aims of our study were 1) to assess TN-C levels, fibrosis and cardiac dysfunction in DMD patients, and 2) to clarify the role of TN-C in cardiovascular dysfunction and fibrosis using male mdx (n=10) and mdx TN-C KO mice (n=8). Results In male patients with DMD (n=18) and age matched controls (n=12) undergoing cardiac MRI, we detected greater myocardial fibrosis than in control hearts. In addition, we observed an elevation of TN-C plasma levels [median concentration (3.55); interquartile range (0.61–7.43) ng/mL] in DMD patients, and its expression negatively correlated to LV ejection fraction (EF) [median LVEF (45); interquartile range (37.5–51.5) %]. Male wt, mdx and mdx TN-C KO age-matched (10 months) mice were used. Transthoracic echocardiography was performed and fibrosis was assessed on cardiac tissue sections. Wire myography was used to assess vascular endothelial function. To explore the signalling pathways contributing to cardiac fibrosis, human cardiac fibroblasts (hCFs) were treated with recombinant human TN-C or TGF-β and gene expression and epigenetic regulation of NF-kB/p65 were assessed. Mdx mice showed significantly increased cardiac fibrosis which was accompanied with markedly elevated TN-C level in cardiac tissue and plasma compared to wt animals (p<0.05, respectively). Moreover, TN-C level in plasma correlated positively with the degree of cardiac dilation in dystrophic mice. In addition, vascular endothelial function was notably impaired in mdx mice. In contrast, we observed preserved vascular function in mdx- TN-C KO mice, this was accompanied by a significant reduction in cardiac fibrosis in compared to age-matched mdx mice (p<0.05, respectively). hCFs treated with TN-C or TGF-β showed increased collagen and α-SMA expressions which could be prevented by application of siRNA against TN-C. In addition, both TN-C and TGF-β caused p65/NF-κB promoter demethylation and subsequently triggered pro-inflammatory and pro-fibrotic signalling, which could be reversed by applying p38 MAPK inhibitor in hCFs. Conclusion TN-C is a critical component of cardiac fibrosis and cardiac dysfunction in DMD. The activation of NF-κB p65 signalling pathway may play a role in TN-C induced fibrosis. Thus, TN-C may be a mediator and potential target for therapy in DMD-associated cardiovascular complications. Funding Acknowledgement Type of funding sources: Foundation. Main funding source(s): Österreichische MuskelforschungFWF - Austrian Science Found P 35878

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 score0.001
Threshold uncertainty score0.005

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 integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.008
GPT teacher head0.225
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 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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Citations2
Published2022
Admission routes1
Has abstractyes

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