# Mapping, modeling, and manipulating 3D contacts in vascular cells to connect risk variants to disease genes

> **NIH NIH R01** · STANFORD UNIVERSITY · 2023 · $693,228

## Abstract

PROJECT SUMMARY
Genome-wide association studies have identified thousands of noncoding genetic variants associated with
common vascular diseases and traits. Each of these associations could point to a gene and vascular cell type to
teach us about mechanisms of disease. Yet, it has been difficult to connect these noncoding variants to their
molecular functions, in large part because they can act via long-range 3D contacts to regulate distant genes. To
connect these variants to target genes, we will need to answer: How do cell-type and disease-specific features
of the 3D genome impact gene expression in vascular cells?
Our recent work suggests a new strategy to systematically map and computationally predict how the 3D genome
connects vascular disease variants to their target genes. By collecting data on thousands of CRISPR
perturbations of regulatory elements, we developed the Activity-by-Contact Model to describe how 3D features
of the genome control enhancer-promoter regulation. By analyzing 3D contacts in human vascular cells in vitro,
we connected one vascular disease variant to a target gene, endothelin-1, located >600 Kb away. These results
provide a predictive framework to understand how 3D contacts impact gene expression, and reveal a strategy
to systematically connect variants to function by mapping the 3D genome in vivo.
We propose to map, model, and manipulate 3D enhancer-promoter contacts in vascular cells to connect risk
variants for vascular diseases to target genes and cell types. We will: (1) generate a resource of genome-wide
3D contact maps in primary human vascular cells; (2) dissect how 3D contacts guide enhancers to target genes
using combinatorial CRISPR perturbations; and (3) computationally and experimentally link vascular disease
GWAS variants to effects on 3D contacts and gene expression.
Our team includes experts in human genetics, vascular biology, genome engineering, 3D genome mapping, and
computational genomics to map 3D contacts to identify targets for atherosclerosis. The environments at Stanford
University, the Broad Institute, and Baylor College of Medicine are ideal for supporting these innovative and
cross-collaborative studies. This study will provide a resource for studying genetic variants that influence
vascular biology, illuminate a mechanism by the 3D genome regulates gene expression, and demonstrate a
general strategy to identify biological mechanisms that influence risk for common vascular diseases and traits.

## Key facts

- **NIH application ID:** 10591585
- **Project number:** 5R01HL159176-02
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** JESSE M ENGREITZ
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2023
- **Award amount:** $693,228
- **Award type:** 5
- **Project period:** 2022-04-01 → 2026-03-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10591585

## Citation

> US National Institutes of Health, RePORTER application 10591585, Mapping, modeling, and manipulating 3D contacts in vascular cells to connect risk variants to disease genes (5R01HL159176-02). Retrieved via AI Analytics 2026-05-24 from https://api.ai-analytics.org/grant/nih/10591585. Licensed CC0.

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