# Integrating KCNH2 Variant-Specific Features and Heterozygote Phenotypes to Estimate Long QT Penetrance

> **NIH NIH R01** · VANDERBILT UNIVERSITY MEDICAL CENTER · 2024 · $584,720

## Abstract

PROJECT SUMMARY/ABSTRACT
Sequencing an individual’s genome now costs less than many routine medical procedures. A resulting vision is
that everyone will have their genome sequenced early in life to enable individualized medical advice about
disease prevention and drug selection. A major concern with this vision, however, is proper interpretation of the
overwhelming volume of discovered novel and rare variants. In other contexts, a new diagnostic test can be
benchmarked and validated in studies that compare large populations with and without a disorder to determine
the predictive value of a positive result. In the genetic sequencing context, however, a positive test for most
variants cannot be applied to enough heterozygous individuals for a definitive association with disease.
Pathogenic variants in KCNH2 (a.k.a. hERG, a cardiac potassium channel gene critical for cardiomyocyte
repolarization) can cause sudden cardiac death in the young and can predispose carriers to drug-induced
arrhythmias. Genetic variants in KCNH2 are responsible for ~ 6% of autopsy-negative sudden unexplained
death in the young and ~ 1% of sudden infant death syndrome cases. Additionally, among heterozygous
carriers of variants in KCNH2, women are at greater overall risk of a severe event (including sudden cardiac
death) which is increased in the postpartum period. Since most disease-associated variants in KCNH2 are
rare, full exome sequencing has the potential to identify those individuals at greater risk early in life before any
phenotype manifests. However, even among heterozygous carriers of KCNH2 variants definitively associated
with disease, not all develop the same phenotype.
To address the challenge of variant interpretation, the American College of Medical Genetics and Genomics
suggests criteria to incorporate variant population, functional, computational, and segregation data using
several described heuristics. Our foundational hypothesis is that clinically meaningful knowledge is lost
in the compression of these variant-specific data to a dichotomous classification. To investigate this
hypothesis, we will generate in vitro data for all missense variants in KCNH2 prospectively, build a prediction
model of disease penetrance, and validate resulting predictions against the incidence of arrhythmias and
cardiac events for variants observed in the Electronic Medical Records and Genomics Network (eMERGE), a
Leducq Transatlantic Network, and the UK Biobank.

## Key facts

- **NIH application ID:** 10773047
- **Project number:** 5R01HL160863-03
- **Recipient organization:** VANDERBILT UNIVERSITY MEDICAL CENTER
- **Principal Investigator:** Brett M Kroncke
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $584,720
- **Award type:** 5
- **Project period:** 2022-02-01 → 2027-01-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10773047

## Citation

> US National Institutes of Health, RePORTER application 10773047, Integrating KCNH2 Variant-Specific Features and Heterozygote Phenotypes to Estimate Long QT Penetrance (5R01HL160863-03). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10773047. Licensed CC0.

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