# Genomic Approaches to Population Health in Multi-Ethnic Hospital Systems

> **NIH NIH R01** · UNIVERSITY OF COLORADO DENVER · 2022 · $768,596

## Abstract

Project Summary
Genomic medicine is a rapidly emerging medical discipline that incorporates the use of genomic information in
patient care. Understanding an individual's genetic information holds the potential to improve diagnostic and
therapeutic decision-making in clinical care, impact health outcomes and inform policy making. Yet the
genomic datasets driving these decisions are often focused on populations of European descent. When these
limited discoveries drive genomic medicine, understudied groups are frequently the last to benefit from
advances in research, technology and clinical best practices. For true adoption, precision medicine needs to
account for genomic diversity inherent to modern health systems.
 To address the importance of understanding disease risk in fine-scale populations present in modern
health systems, and foster opportunities for advancement of genomic medicine in diverse populations, we have
assembled a multi-ethnic cohort of over one million genotyped individuals from five international biobanks in
health systems linked to electronic medical records. Leveraging this unique research cohort from our institutes,
we will engineer fine-scale population detection and monitoring for population health powered by novel
statistical and population genetics methods. These in turn can help us understand disease prevalence and
refine our understanding of clinical variant pathogenicity. The systems we develop within hospitals will help
characterize risk profiles for both rare (via Phenotype Scores) and common (via Polygenic Scores) traits, a
necessary step to work in realistic, modern multi-ethnic hospital settings. These goals are implemented
through three specific aims:
Aim 1: Implement a monitoring system for differences in disease burden between fine-scale populations
defined via identity-by-descent (IBD) inferred from genome-wide data across multiple biobanks. In so doing, we
will apply a high-throughput, portable method to improve fine-scale ancestry and use it to improve disease and
trait monitoring across multiple health systems.
Aim 2: Improve our characterization of clinical variant pathogenicity, penetrance and expressivity via improved
allele frequency examination through the fine-scale populations determined in Aim 1.
Aim 3: Model risk via improved phenotype risk score (PheRS) for rare disease and polygenic risk score (PRS)
for common traits across the fine-scale populations determined in Aim 1. We will develop improved trans-
ethnic risk models and demonstrate their utility in improving our population-based understanding of disease
outcomes.
 Our long-collaborating interdisciplinary team including clinical, statistical, and population geneticists has
already produced preliminary data demonstrating not only a high likelihood of success, but also a desire and
capacity to translate results into implemented changes in clinical care. This project will drive a new
understanding of human disease, as well as opportunities for ...

## Key facts

- **NIH application ID:** 10474584
- **Project number:** 5R01HG011345-03
- **Recipient organization:** UNIVERSITY OF COLORADO DENVER
- **Principal Investigator:** Valerie A Arboleda
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2022
- **Award amount:** $768,596
- **Award type:** 5
- **Project period:** 2020-09-16 → 2024-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10474584

## Citation

> US National Institutes of Health, RePORTER application 10474584, Genomic Approaches to Population Health in Multi-Ethnic Hospital Systems (5R01HG011345-03). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10474584. Licensed CC0.

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