# Genetic Architecture of Cardiac Structure and Function and Its Impact on Heart Failure

> **NIH NIH R01** · UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON · 2022 · $818,346

## Abstract

Heart failure (HF) increases with age markedly and is associated with a 50% 5-year mortality. Abnormalities of
cardiac structure and impairment of cardiac function precede the development of HF and underlie HF subtypes.
Cardiac structure and function are heritable - genome-wide association studies have identified 57 common
variants associated with cardiac structure and function, however, genetic contribution to newer cardiac function
measures have not been explored. In addition, few data exist comprehensively characterizing genetic
associations (i.e., rare and structural variants) of cardiac structure and function, especially in minorities. Over
the past decade, we have investigated the genetic effect on HF and cross-sectional echo measures within the
setting of the Cohorts for Heart and Aging Research in Genomic Epidemiology (CHARGE) consortium. We now
propose to extend our effort to the Trans-Omics for Precision Medicine (TOPMed) Program by combing our rich
longitudinal phenotypic data with cutting-edge whole genome sequencing data in seven population-bases
cohorts. Our central hypothesis is that specific common, rare and structural genetic variants will be associated
with cardiac structure and function, as well as HF; and incorporating genetic predisposition to cardiac structure
and function alterations will improve HF risk prediction. In Aim 1, we will characterize genetic architecture of
cardiac structure and function and their longitudinal changes, and evaluate their effects on HF. To inform
understanding of HF physiology, we will assess the causal effects of proteins and metabolites on echo and HF
using Mendelian randomization approaches. In Aim 2, we will construct polygenic risk scores for cardiac structure
and function and assess their impact on HF risk prediction. We will apply a new approach for PRS construction,
and will use a machine learning algorithms to evaluate its prediction on the risk of HF. With the completion of
this project, we aim to generate insights into the biological pathways underlying progressive cardiac dysfunction
and HF, and to provide targets for drug development.

## Key facts

- **NIH application ID:** 10521120
- **Project number:** 1R01HL160793-01A1
- **Recipient organization:** UNIVERSITY OF TEXAS HLTH SCI CTR HOUSTON
- **Principal Investigator:** Vasan Ramachandran
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $818,346
- **Award type:** 1
- **Project period:** 2022-08-01 → 2026-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10521120

## Citation

> US National Institutes of Health, RePORTER application 10521120, Genetic Architecture of Cardiac Structure and Function and Its Impact on Heart Failure (1R01HL160793-01A1). Retrieved via AI Analytics 2026-06-02 from https://api.ai-analytics.org/grant/nih/10521120. Licensed CC0.

---

*[NIH grants dataset](/datasets/nih-grants) · CC0 1.0*