Evidence map›Paper›PMID 40066353›Full record

ReviewFrontiers in cardiovascular medicine2025

Modeling thoracic aortic genetic variants in the zebrafish: useful for predicting clinical pathogenicity?

Andrew Prendergast, Mary B Sheppard, Jakub K Famulski, Stefania Nicoli, Sandip Mukherjee, Patrick Sips, John A Elefteriades

Abstract readReview
In one paragraph

Review in Frontiers in cardiovascular medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Andrew PrendergastYale Zebrafish Research Core, Department of Comparative Medicine, Yale University School of Medicine, New Haven, CT, United States.
Mary B SheppardDepartment of Family and Community Medicine, Saha Aortic Center, Saha Cardiovascular Research Center, University of Kentucky College of Medicine, Lexington, KY, United States.
Jakub K FamulskiDepartment of Biology, University of Kentucky, Lexington, KY, United States.
Stefania NicoliYale Zebrafish Research Core, Department of Comparative Medicine, Yale University School of Medicine, New Haven, CT, United States.
Sandip MukherjeeAortic Institute at Yale-New Haven, Yale University School of Medicine, New Haven, CT, United States.
Patrick SipsDepartment of Biomolecular Medicine, Ghent University, Ghent, Belgium.
John A ElefteriadesAortic Institute at Yale-New Haven, Yale University School of Medicine, New Haven, CT, United States.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Thoracic aortic aneurysm and dissection (TAAD) significantly impact cardiovascular morbidity and mortality. A large subset of TAAD cases, particularly those with an earlier onset, is linked to heritable genetic defects. Despite progress in characterizing genes associated with both syndromic and non-syndromic heritable TAAD, the causative gene remains unknown in most cases. Another important bottleneck in the correct and timely diagnosis of TAAD is the large proportion of variants of unknown significance (VUS) that are routinely encountered upon medical genetic testing. Reliable functional modeling data is required to accurately identify new causal genes and to determine the pathogenicity of VUS. To address this gap, our collaborative effort-comprising teams from Yale University, University of Kentucky, and Ghent University-explores a novel approach: modeling TAAD in zebrafish. Leveraging the unique advantages of this animal model promises to allow for accelerated variant pathogenicity assessment, ultimately enhancing patient care. In this review, we critically explore the currently available zebrafish-based approaches that can be used for testing pathogenicity of genes and variants related to TAAD, and we offer an outlook on the implementation of these strategies for clinical applications.

Indexed as

cardiovascular imagingCRISPRgenetic variant testingthoracic aortic diseasezebrafish modeling

Identifiers

PMID40066353
PMCPMC11892108

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.