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Induction of Nrg1 and ErbB4 Is Specific to Virus Induced Injury of the Myocardium and May be Detected during Pathogenesis of Viral Myocarditis as Blood‐Based Biomarkers for Diagnosis

2020· article· en· W3016675504 on OpenAlexaff
Paul Hanson, Al Rohet Hossain, Gurpreet K. Singhera, Bruce M. McManus

Bibliographic record

VenueThe FASEB Journal · 2020
Typearticle
Languageen
FieldMedicine
TopicViral Infections and Immunology Research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMyocarditisViral MyocarditisPathogenesisMedicineInflammationPathologyImmunologyInternal medicine

Abstract

fetched live from OpenAlex

Background Myocarditis, inflammation of the myocardium, globally affects >3 million people annually. Heterogeneous histological findings and clinical presentation ranging from flu‐like illness to acute cardiogenic shock make diagnosis exceedingly difficult. The current gold standard for diagnosis requires histological examination of invasive endomyocardial biopsies, which provides a sensitivity of <30% in independently published studies. Although etiologies are diverse, viruses are the most prominent causes of myocarditis. Our studies demonstrated that the coxsackievirus B3 (CVB3), a common pathogen associated with viral myocarditis, manipulates the expression of Neuregulin 1 (Nrg1) and its ligand, receptor tyrosine‐protein kinase, ErbB4. Moreover, previous studies in other viruses have demonstrated preferential expression of the higher affinity Nrg1 β versus the less potent Nrg1 α isoform. The goal of this research is to determine the specificity of Nrg1 and ErbB4 induction to viral myocarditis as compared to other forms of acute myocardial injury, particularly myocardial infarction (m.i.). Additionally, we aim to analyze expression, tissue and isoform specificity of Nrg1 and ErbB4 in blood and heart tissue during the pathogenesis of viral myocarditis towards developing a non‐invasive blood‐based diagnostic assay via novel biomarkers. Methods 4‐week old male A/J mice were sham or CVB3 infected. Blood and tissue were harvested at time points corresponding to the acute, sub‐acute and chronic phases of disease. Specimens were analyzed for mRNA and protein expression and sub‐cellular localization using RT‐qPCR, Western blotting and confocal microscopy, respectively. Expression of Nrg1 and ErbB4 in viral myocarditis models was compared to murine myocardial infarction models via confocal microscopy. Results Upregulation (p<0.05) of Nrg1 and ErbB4 protein fragments were observed in murine heart tissue at different phases of viral pathogenesis as compared to m.i. and non‐infected controls. The observed upregulation was specific to the heart and not observed in the infected pancreas or lung. In addition, ~35 kDa and ~26 kDa fragments of Nrg1 and ErbB4 respectively were detected in the plasma of infected mice, while absent in the non‐infected controls. Confocal microscopy revealed that Nrg1 localized to the nuclear periphery while a diffuse increase in cellular ErbB4 expression was observed during infection. mRNA levels of Nrg1 β were significantly upregulated (~3‐fold) at the acute phase (6–7 dpi) of viral myocarditis, while the differences in expression of Nrg1 α were not significant. Conclusion Tissue specific upregulation and fragments detected in the plasma of both ErbB4 and Nrg1, with preferential expression of Nrg1 β , were observed as a result of CVB3 infection. Moreover, upregulation was not observed in an ischemic model of acute myocardial injury, indicating a viral specific process. These composite observations support the concept that these biomarkers may ultimately yield a non‐invasive blood‐based diagnostic assay for viral myocarditis. Support or Funding Information This research is supported by the Myocarditis Foundation and the Michael Smith Foundation for Health Research.

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 score0.006

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)0.0020.000

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 head0.039
GPT teacher head0.291
Teacher spread0.252 · 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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Citations0
Published2020
Admission routes1
Has abstractyes

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