# Defining regulatory regions for cardiomyopathy genes

> **NIH NIH F30** · NORTHWESTERN UNIVERSITY · 2020 · $41,309

## Abstract

Project Summary/Abstract
Inherited cardiomyopathy is a genetically diverse disease marked by considerable phenotypic heterogeneity.
Mutations in more than 100 genes lead dilated, hypertrophic and other forms of cardiomyopathy. Within
individual families, most single mutations display a range of clinical expression from severe early onset disease
to minimal or no symptoms. While genetic mutations can provide a highly useful biomarker to indicate risk for
developing disease, the highly level of variability associated with most mutations makes it difficult to accurately
predict clinical courses. Similar to genetically complex diseases, genetic variations in noncoding regulatory
regions are thought to play an important role in modifying phenotypes for these single gene disorders. The
overall goal of this proposal is to study noncoding regulatory variation linked to known cardiomyopathy genes
with the goal to better understand phenotypic heterogeneity in genetic cardiomyopathy. We hypothesize that
variation in enhancer regions will modify cardiomyopathy gene expression and thus, also modify clinical
phenotypes. The overall organization of this proposal is to identify candidate enhancer regions, validate
enhancer regions, and study how variation affects their function. In Aim 1, we will identify candidate enhancers
for cardiomyopathy genes using bioinformatic approaches to intersect data from human hearts and
cardiomyocytes derived from induced pluripotent stem cells. By focusing on enhancers active in the human
adult heart and in the failed heart, and only on those that interact with a subset of cardiomyopathy genes, we
will determine the reliability of prediction protocols for enhancer identification. Preliminary data supports that
this approach identifies previously known enhancers and also classifies other regions as strong enhancer
candidates. The goal of Aim 2 is to validate these enhancer predictions using reporter expression studies and
deletion of candidate enhancers. Finally, Aim 3 will evaluate genetic variation found in whole genome
sequencing data from a cohort of cardiomyopathy patients to characterize how sequence variation in enhancer
regions affects expression and correlates with phenotypes. Preliminary data indicates that sequence variants
present in the cardiomyopathy cohort fall within predicted transcription factor binding sites and thus, are
potentially functional. The proposed approach can improve phenotypic prediction in genetic cardiomyopathy
and revolutionize the clinical care of these patients. Moreover, these studies serve as a novel framework to
characterize noncoding variation, which can be applied to many other genetically and phenotypically
heterogeneous diseases that affect the heart.

## Key facts

- **NIH application ID:** 9936403
- **Project number:** 5F30HL142187-03
- **Recipient organization:** NORTHWESTERN UNIVERSITY
- **Principal Investigator:** Anthony Martin Gacita
- **Activity code:** F30 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $41,309
- **Award type:** 5
- **Project period:** 2018-06-01 → 2022-05-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/9936403

## Citation

> US National Institutes of Health, RePORTER application 9936403, Defining regulatory regions for cardiomyopathy genes (5F30HL142187-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/9936403. Licensed CC0.

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