# Core C : Population Genomic Risk Assessment

> **NIH NIH P01** · UNIVERSITY OF CALIFORNIA, SAN FRANCISCO · 2024 · $145,954

## Abstract

CORE C: SUMMARY/ABSTRACT
A polygenic risk score (PRS) combines risk information from many common genetic variants associated with a
disease to predict the risk of that disease. PRS’ for breast cancer are strong predictors of overall and subtype
specific breast cancer risk. The WISDOM Study relies on risk stratification of women, in part, based on genotype
data from PRS and from pathogenic variants in high and intermediate penetrance genes. To implement PRS in
the setting of a prospective clinical study and use it to make informed decisions about initiation and frequency of
screening, the WISDOM Study requires high quality genotype data, imputation and calculation. In addition, the
approach should be amenable to updates since improvements in PRS are expected in the next several years.
Core C, the Population Genomics Core Risk Assessment (PGRA) Core, will be responsible for ensuring high
quality genotype data and PRS integration occurs for each of the projects in the P01. To support Project 1, the
PGRA will oversee processing of low pass whole genome (LPWGS) data into genotypes and integrate these
into PRS for overall breast cancer and for breast cancer subtypes including PRS for fasting growing breast
cancer and estrogen receptor negative breast cancer. The PGRA will also implement newer PRS for fast growing
breast cancer and update this as it is improved by Project 2. In addition, the PGRA will implement PRS as a
modifier of risk for carriers of pathogenic variants in intermediate susceptibility breast cancer genes to inform
screening and prevention by Project 1. The PGRA will support Project 2 by providing genotype data cleaning,
imputation of genotypes across all of the datasets that are used and by providing ancestry estimation. Project 3
will be supported by providing imputation and PRS calculation. For both Project 1 and Project 3, the PGRA will
provide updates for PRS’ for different ancestry populations as work in Project 2 demonstrates improved PRS
across diverse ancestry populations. In addition, the PRS will provide Project 4 with distributions of risk by
different thresholds of PRS, family history and pathogenic variant status across different ancestry and
race/ethnicity populations. The PGRA will collaborate closely with Core B on joint modeling of PRS and non-
genetic risk factors and with Core D to prepare materials for risk communication. Overall, the PGRA will support
all Projects and collaborate closely with other Cores to ensure that genetic risk information is optimally used
throughout the study.

## Key facts

- **NIH application ID:** 10935794
- **Project number:** 1P01CA281826-01A1
- **Recipient organization:** UNIVERSITY OF CALIFORNIA, SAN FRANCISCO
- **Principal Investigator:** Elad Ziv
- **Activity code:** P01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2024
- **Award amount:** $145,954
- **Award type:** 1
- **Project period:** 2024-09-11 → 2029-08-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10935794

## Citation

> US National Institutes of Health, RePORTER application 10935794, Core C : Population Genomic Risk Assessment (1P01CA281826-01A1). Retrieved via AI Analytics 2026-05-26 from https://api.ai-analytics.org/grant/nih/10935794. Licensed CC0.

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