ReviewJournal of cellular and molecular medicine2023
Role of non-coding variants in cardiovascular disease.
Review in Journal of cellular and molecular medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 11 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.
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Who cites it
11 citing papers in PubMed, 19 citations in OpenAlex.
- Multi-trait GWAS reveals divergent local and polygenic architecture of cardiovascular traits across African and European ancestries in the UK Biobank.Communications biology · 2026Article
- Genomic structural equation modeling reveals shared genetic structure of cardiac function and structure-function association studies of CLCNKA mutations.Scientific reports · 2026Article
- Global Evaluation of Congenital Heart Disease-Associated Non-Coding Variants.Research square · 2026Article
- The ChickenGTEx portal: a pan-tissue catalogue of regulatory variants shaping transcriptomic and phenotypic diversity.Nucleic acids research · 2026Article
- The Utility of Genome-Wide Association Studies in Inherited Arrhythmias and Cardiomyopathies.Genes · 2025Review
- Functional Validation of Noncoding Variants Associated With Nonsyndromic Orofacial Cleft.Human mutation · 2025Review
- Cardiomyopathies: The Role of Non-Coding RNAs.Non-coding RNA · 2024Review
- Decoding Non-coding Variants: Recent Approaches to Studying Their Role in Gene Regulation and Human Diseases.Frontiers in bioscience (Scholar edition) · 2024Review
- Prioritizing cardiovascular disease-associated variants altering NKX2-5 and TBX5 binding through an integrative computational approach.The Journal of biological chemistry · 2023Article
- LDLR and PCSK9 3´UTR variants and their putative effects on microRNA molecular interactions in familial hypercholesterolemia: a computational approach.Molecular biology reports · 2023Article
- Role of non-coding variants in cardiovascular disease.Journal of cellular and molecular medicine · 2023Review
Corrections and comments
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Authors and funding
9 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Cardiovascular diseases (CVDs) constitute one of the significant causes of death worldwide. Different pathological states are linked to CVDs, which despite interventions and treatments, still have poor prognoses. The genetic component, as a beneficial tool in the risk stratification of CVD development, plays a role in the pathogenesis of this group of diseases. The emergence of genome-wide association studies (GWAS) have led to the identification of non-coding parts associated with cardiovascular traits and disorders. Variants located in functional non-coding regions, including promoters/enhancers, introns, miRNAs and 5'/3' UTRs, account for 90% of all identified single-nucleotide polymorphisms associated with CVDs. Here, for the first time, we conducted a comprehensive review on the reported non-coding variants for different CVDs, including hypercholesterolemia, cardiomyopathies, congenital heart diseases, thoracic aortic aneurysms/dissections and coronary artery diseases. Additionally, we present the most commonly reported genes involved in each CVD. In total, 1469 non-coding variants constitute most reports on familial hypercholesterolemia, hypertrophic cardiomyopathy and dilated cardiomyopathy. The application and identification of non-coding variants are beneficial for the genetic diagnosis and better therapeutic management of CVDs.
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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.