# Using Electrocardiogram Genetics to Inform Arrhythmia Risk

> **NIH NIH R01** · MASSACHUSETTS GENERAL HOSPITAL · 2022 · $767,992

## Abstract

Project summary
Nearly one in three people will have an arrythmia during their lifetime and up to 10% may die of sudden cardiac
death. Arrhythmias and sudden cardiac death are heritable and often caused by problems of cardiac
conduction or repolarization. Nevertheless, the genetic causes are not well-defined. Moreover, interpretation of
genetic variation is limited by the frequent discovery of variants of uncertain clinical significance. Our
preliminary data suggest that using high-depth genomic sequencing data from large-scale biobanks with
routinely measured electrocardiogram intervals – indicators of arrhythmia and sudden cardiac death risk – has
the potential to address these challenges.
 Our overall goal is to minimize morbidity from cardiovascular disease. The specific objective of this
proposal is to utilize high-depth whole genome and exome sequencing data to identify, functionally
evaluate, and clinically characterize genetic variation that predisposes to arrhythmia risk and sudden
cardiac death. To do so, we will leverage a unique and massive repository of individuals with genomic
sequencing, electrocardiograms, and clinical data.
 The electrocardiogram is a widely utilized and inexpensive screening test. Standard electrocardiogram
intervals are reliable and reproducible measurements that are associated with a variety of cardiac conditions,
most notably arrhythmias and sudden cardiac death. Our overall hypothesis is that functional and clinically
relevant rare genetic variation underlies population-based electrocardiographic interval variability.
 In Aim 1, we will identify rare coding variation associated with electrocardiographic intervals. We will use
data from a unique resource of over 220,000 individuals with electrocardiograms and whole genome or exome
sequence data in the National Heart Lung and Blood Institute’s Trans-Omics for Precision Medicine Program,
UK Biobank, Geisinger MyCode/DiscovEHR cohort, and Mass General Brigham HealthCare Biobank. In Aim
2, we will validate and characterize the electrophysiological and structural impact of identified genes in stem
cell derived cardiomyocytes. In Aim 3 we will assess whether variants with large electrocardiographic trait
effect sizes are associated with arrhythmia risk using electronic health record data in nearly 400,000
sequenced individuals, and variant pathogenicity using ClinVar, a repository of clinical variant adjudications.
 Studying how rare genetic variants affect the electrocardiogram is an innovative approach for
understanding arrhythmia and sudden cardiac death risk. We anticipate that this paradigm will be broadly
applicable to other quantitative endophenotypes and heart diseases. We submit that our aims are consistent
with the NHLBI’s mission of understanding the causes of disease and enabling translation of basic discoveries
into clinical practice.

## Key facts

- **NIH application ID:** 10366259
- **Project number:** 1R01HL157635-01A1
- **Recipient organization:** MASSACHUSETTS GENERAL HOSPITAL
- **Principal Investigator:** Patrick Thomas Ellinor
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $767,992
- **Award type:** 1
- **Project period:** 2022-01-20 → 2025-12-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10366259

## Citation

> US National Institutes of Health, RePORTER application 10366259, Using Electrocardiogram Genetics to Inform Arrhythmia Risk (1R01HL157635-01A1). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10366259. Licensed CC0.

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