# New methods for constructing and evaluating polygenic scores

> **NIH NIH R01** · STANFORD UNIVERSITY · 2020 · $821,103

## Abstract

ABSTRACT
In the last decade there has been major progress toward identifying the genetic bases of complex diseases
and developing polygenic predictors for individuals who are at increased risk. Polygenic prediction models are
now approaching the point of clinical relevance for several important diseases. However, since most of the
polygenic risk is due to extremely large numbers of small-effect variants it is difficult to construct maximally
efficient prediction models even using very large GWAS samples. At present, the largest samples are currently
available for European ancestry individuals. Prediction models developed in these samples usually do not port
well into other groups, although the precise reasons for the limited portability are not yet fully understood. In
this project we will (1) measure the specific importance of different factors that contribute to the limited
portability across groups; (2) implement and evaluate new statistical methods for computing polygenic
predictors using joint inference across populations, and using functional information as priors; and (3)
implement and evaluate new statistical methods for combining genetic information with other types of clinical
data for prospective prediction in clinical settings. In summary our project will provide a framework of efficient
statistical methods for polygenic prediction within and across populations.

## Key facts

- **NIH application ID:** 10073318
- **Project number:** 1R01HG011432-01
- **Recipient organization:** STANFORD UNIVERSITY
- **Principal Investigator:** JONATHAN K PRITCHARD
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2020
- **Award amount:** $821,103
- **Award type:** 1
- **Project period:** 2020-09-14 → 2024-06-30

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10073318

## Citation

> US National Institutes of Health, RePORTER application 10073318, New methods for constructing and evaluating polygenic scores (1R01HG011432-01). Retrieved via AI Analytics 2026-05-21 from https://api.ai-analytics.org/grant/nih/10073318. Licensed CC0.

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