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Related Concept Videos

Genome-wide Association Studies-GWAS01:11

Genome-wide Association Studies-GWAS

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Genome-wide association studies or GWAS are used to identify whether common SNPs are associated with certain diseases. Suppose specific SNPs are more frequently observed in individuals with a particular disease than those without the disease. In that case, those SNPs are said to be associated with the disease. Chi-square analysis is performed to check the probability of the allele likely to be associated with the disease.
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A single nucleotide polymorphism or SNP is a single nucleotide variation at a specific genomic position in a large population. It is the most prevalent type of sequence variation found in the human genome. Point mutations that occur in more than 1% of the population qualify as SNPs. These are present once every 1000 nucleotides on an average in the human genome. Replacement of a purine with another purine (A/G) or a pyrimidine with another pyrimidine (C/T) is known as a transition. In contrast,...
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Identification and Classification of Position-specific GABAA Receptor Subunit Missense Variants for Their Role In Hippocampal Pyramidal Neurons
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SPARC: a structural pathogenicity algorithm for risk classification of hERG variants.

Frank C Chatelain1,2, Barbara Ribeiro de Oliveira2,3, Guillaume Grataloup1

  • 1Université Côte d'Azur, INSERM, CNRS, Institut de Pharmacologie Moléculaire et Cellulaire, Valbonne, France.

Europace : European Pacing, Arrhythmias, and Cardiac Electrophysiology : Journal of the Working Groups on Cardiac Pacing, Arrhythmias, and Cardiac Cellular Electrophysiology of the European Society of Cardiology
|December 24, 2025
PubMed
Summary
This summary is machine-generated.

A new computational tool, SPARC, predicts the pathogenicity of cardiac hERG gene variants. This method aids in classifying uncertain variants, improving diagnosis of inherited heart conditions like Long QT syndrome.

Keywords:
ArrhythmiaHigh throughput phenotypingStructural pathogenicity scoreUCSF ChimeraVariant of uncertain significancehERG channel

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Area of Science:

  • Genetics and Molecular Biology
  • Cardiology
  • Bioinformatics

Background:

  • Inherited mutations in KCNH2 gene cause arrhythmogenic syndromes.
  • Clinical interpretation of hERG gene variants, especially variants of uncertain significance (VUS), is challenging.

Purpose of the Study:

  • To develop and validate a computational pipeline (SPARC) for predicting hERG variant pathogenicity.
  • To integrate structural metrics into a composite score for variant classification.

Main Methods:

  • Developed a semi-automated in silico pipeline (SPARC) using five structural metrics.
  • Applied SPARC to 1727 hERG variants from ClinVar and a French cohort.
  • Validated predictions using high-throughput automated patch clamp on a subset of variants.

Main Results:

  • SPARC identified 260 variants as high risk (SPS ≥ 3.25).
  • Functional validation confirmed SPARC's predictions, including for several VUS.
  • SPARC demonstrated superior performance compared to AlphaMissense and Revel.

Conclusions:

  • Comprehensive structural scoring reliably stratifies hERG variant pathogenicity.
  • SPARC is a scalable, cost-effective tool for pre-screening and prioritizing variants for experimental validation.
  • This approach aids clinical interpretation of genetic variants in arrhythmogenic syndromes.