Project Grant R01HL187295

The National Heart, Lung, and Blood Institute (NHLBI), part of the National Institutes of Health within the Department of Health and Human Services, awarded J. David Gladstone Institutes $925,796 on August 1, 2026, under the Cardiovascular Diseases Research program (CFDA 93.837) to develop machine learning methods for identifying noncoding genetic variants that cause congenital heart disease.

Gladstone will create a deep learning toolkit to predict how rare and de novo noncoding variants—including single nucleotide changes and large structural variants—alter gene regulation during cardiovascular development. The research addresses the gap that while genome sequencing has identified damaging variants in heart development genes, the majority of children with congenital heart disease lack a genetic diagnosis. Each project aim develops a machine learning model targeting one genetic mechanism: three-dimensional chromatin interactions, local nucleosome positioning, or transcription factor binding sites. The methods will predict candidate causal variants and generate mechanistic hypotheses about how high-scoring variants disrupt gene regulation, while identifying target genes, upstream regulators, and affected cell types.

The award is structured as a Project Grant, the standard assistance type for NIH research funding. Work is performed in San Francisco, California, with a period of performance through April 30, 2030.