# Gene therapy for long QT syndrome type 2

> **NIH NIH R01** · RHODE ISLAND HOSPITAL · 2024 · $814,039

## Abstract

Abstract
There are >500 pathologic variants within 17 genes causing congenital long QT syndrome, which
leads to polymorphic ventricular tachycardia (pVT) and sudden cardiac death (SCD). About 30%
of the mutations are concentrated in the KCNH2 gene resulting in loss-of-function of the rapidly
activating delayed rectifier potassium current IKr causing prolongation of the action potential
duration and QT interval (LQT2). We developed a transgenic rabbit model for LQT2 that
recapitulate the human phenotype. This application is aimed at developing gene therapy for LQT2
using our rabbit model and an AAV9-mediated mosaic gene expression of hERG. Aim 1 to rescue
the phenotype of LQT2G by delivering AAV9-encoded shRNA that will abolish expression of both
the human pore mutant transgene and endogenous rERG with an shRNA-resistant hERG
(hERG*) under the control of the CMV promoter at doses of 6E13vg/kg and 2E14vg/kg as
compared to vehicle control. The Aim also proposes to study the cellular phenotype of the treated
rabbits as compared to vehicle control. Aim 2 proposes to monitor ant test the two groups for
spontaneous and inducible arrhythmias. This application outlines the roadmap for gene therapy
of all variants causing human LQT2 syndrome and has the potential to revolutionize the therapy
of this syndrome.

## Key facts

- **NIH application ID:** 10876607
- **Project number:** 1R01HL166165-01A1
- **Recipient organization:** RHODE ISLAND HOSPITAL
- **Principal Investigator:** GIDEON KOREN
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $814,039
- **Award type:** 1
- **Project period:** 2024-04-01 → 2028-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10876607

## Citation

> US National Institutes of Health, RePORTER application 10876607, Gene therapy for long QT syndrome type 2 (1R01HL166165-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10876607. Licensed CC0.

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