ArticlePloS one2015
Gene Expression in Experimental Aortic Coarctation and Repair: Candidate Genes for Therapeutic Intervention?
Article in PloS one, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It is linked to trial NCT03262753 (LOVE-COARCT Study), which is not on this map. Cited by 6 papers.
What it found
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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.
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.
LOVE-COARCT Study: Long-term Outcomes and Vascular Evaluation After Coarctation of the Aorta Treatment
Who cites it
6 citing papers in PubMed, 11 citations in OpenAlex.
- Transcriptome analysis of the aortic coarctation area.Journal of molecular and cellular cardiology plus · 2024Article
- Aortic Remodeling Kinetics in Response to Coarctation-Induced Mechanical Perturbations.Biomedicines · 2023Article
- A workflow for viewing biomedical computational fluid dynamics results and corresponding data within virtual and augmented reality environments.Frontiers in medical technology · 2023Article
- Human genotyping and an experimental model reveal NPR-C as a possible contributor to morbidity in coarctation of the aorta.Physiological genomics · 2019Article
- Treating a 20 mm Hg gradient alleviates myocardial hypertrophy in experimental aortic coarctation.The Journal of surgical research · 2017Article
- Rare coding variants associated with blood pressure variation in 15 914 individuals of African ancestry.Journal of hypertension · 2017Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
6 authors at 2 institutions in 1 country.
Funding
Abstract
Coarctation of the aorta (CoA) is a constriction of the proximal descending thoracic aorta and is one of the most common congenital cardiovascular defects. Treatments for CoA improve life expectancy, but morbidity persists, particularly due to the development of chronic hypertension (HTN). Identifying the mechanisms of morbidity is difficult in humans due to confounding variables such as age at repair, follow-up duration, coarctation severity and concurrent anomalies. We previously developed an experimental model that replicates aortic pathology in humans with CoA without these confounding variables, and mimics correction at various times using dissolvable suture. Here we present the most comprehensive description of differentially expressed genes (DEGs) to date from the pathology of CoA, which were obtained using this model. Aortic samples (n=4/group) from the ascending aorta that experiences elevated blood pressure (BP) from induction of CoA, and restoration of normal BP after its correction, were analyzed by gene expression microarray, and enriched genes were converted to human orthologues. 51 DEGs with >6 fold-change (FC) were used to determine enriched Gene Ontology terms, altered pathways, and association with National Library of Medicine Medical Subject Headers (MeSH) IDs for HTN, cardiovascular disease (CVD) and CoA. The results generated 18 pathways, 4 of which (cell cycle, immune system, hemostasis and metabolism) were shared with MeSH ID's for HTN and CVD, and individual genes were associated with the CoA MeSH ID. A thorough literature search further uncovered association with contractile, cytoskeletal and regulatory proteins related to excitation-contraction coupling and metabolism that may explain the structural and functional changes observed in our experimental model, and ultimately help to unravel the mechanisms responsible for persistent morbidity after treatment for CoA.
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Registered trials
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.