ArticleCirculation. Arrhythmia and electrophysiology2022
GENESIS: Gene-Specific Machine Learning Models for Variants of Uncertain Significance Found in Catecholaminergic Polymorphic Ventricular Tachycardia and Long QT Syndrome-Associated Genes.
Article in Circulation. Arrhythmia and electrophysiology, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.
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Who cites it
22 citing papers in PubMed, 33 citations in OpenAlex.
- Explainable machine learning-driven identification of heart failure biomarkers: a multi-model feature selection approach with SHAP-based interpretability.Scientific reports · 2026Article
- Structural Evaluation ofCirculation. Genomic and precision medicine · 2026Article
- Artificial intelligence in pediatric arrhythmias: current landscape, unique challenges, and translational perspectives.Frontiers in pediatrics · 2026Review
- Current perspectives and challenges of using artificial intelligence in immunodeficiencies.The Journal of allergy and clinical immunology · 2025Review
- Leveraging artificial intelligence for risk stratification of inherited cardiomyopathies in under-resourced settings.Heart rhythm O2 · 2025Article
- Machine learning and multi-omics integration: advancing cardiovascular translational research and clinical practice.Journal of translational medicine · 2025Review
- Single-cell multi-omics analysis reveals the mechanism of action of a novel antioxidant polyphenol nanoparticle loaded with STAT3 agonist in mediating cardiomyocyte ferroptosis to ameliorate age-related heart failure.Journal of nanobiotechnology · 2025Article
- An augmented transformer model trained on protein family specific variant data leads to improved prediction of variants of uncertain significance.Human genetics · 2025Article
- Meta-EA: a gene-specific combination of available computational tools for predicting missense variant effects.Nature communications · 2025Article
- Beyond the Beat, Next-Generation Sequencing Discovery of NovelCardiology research and practice · 2025Article
- The Genetic Basis of Sudden Cardiac Death: From Diagnosis to Emerging Genetic Therapies.Annual review of medicine · 2025Review
- Artificial Intelligence in Diagnosis of Long QT Syndrome: A Review of Current State, Challenges, and Future Perspectives.Mayo Clinic proceedings. Digital health · 2024Review
- The Clinical Findings, Pathogenic Variants, and Gene Therapy Qualifications Found in a Leber Congenital Amaurosis Phenotypic Spectrum Patient Cohort.International journal of molecular sciences · 2024Article
- Evaluating pro-arrhythmogenic effects of the T634S-hERG mutation: insights from a simulation study.Interface focus · 2023Article
- Article
- A rare case with fetal autoimmune heart block and KNCH2 variant-induced long QT syndrome: a controversial opinion on prenatal management strategy.BMC cardiovascular disorders · 2023Article
- Continuous Bayesian variant interpretation accounts for incomplete penetrance among Mendelian cardiac channelopathies.Genetics in medicine : official journal of the American College of Medical Genetics · 2023Article
- Molecular autopsy: Twenty years of post-mortem diagnosis in sudden cardiac death.Frontiers in medicine · 2023Review
- Genetics of congenital arrhythmia syndromes: the challenge of variant interpretation.Current opinion in genetics & development · 2022Review
- Mutation-Specific Differences in Kv7.1 (International journal of molecular sciences · 2022Review
Corrections and comments
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Authors and funding
9 authors at 5 institutions in 4 countries.
Funding
Abstract
backgroundCardiac channelopathies such as catecholaminergic polymorphic tachycardia and long QT syndrome predispose patients to fatal arrhythmias and sudden cardiac death. As genetic testing has become common in clinical practice, variants of uncertain significance (VUS) in genes associated with catecholaminergic polymorphic ventricular tachycardia and long QT syndrome are frequently found. The objective of this study was to predict pathogenicity of catecholaminergic polymorphic ventricular tachycardia-associated
methodsThe GENe-specific EnSemble grId Search framework was developed to identify high-performing machine learning models for
resultsThe GENe-specific EnSemble grId Search models outperformed alternative methods, with area under the receiver operating characteristics up to 0.87, average precisions up to 0.83, and calibration slopes as close to 1.0 (perfect) as 1.04. Blinded voltage-clamp analysis of HEK293T cells expressing 2 predicted pathogenic variants in
conclusionsGene-specific machine learning models may have a role in post-genetic testing diagnostic analyses by providing high performance prediction of variant pathogenicity.
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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.