# Next-generation, pathway-specific, polygenic risk scores

> **NIH NIH R01** · ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI · 2021 · $635,256

## Abstract

PROJECT SUMMARY
The key appeal of polygenic risk scores (PRS) is the provision of individual-level estimates of genetic liability to
complex disease. These proxies of genetic liability enable a raft of applications across clinical and basic research
settings. However, while PRS are set to play a pivotal role in the future of biomedical research, their present
formulation is suboptimal since it fails to directly account for substructure in genetic disease risk.
The overarching goal of our proposal is to introduce a new generation of pathway-specific PRS, informed by
biological function. Rather a single genome-wide PRS for each individual, they will have a set of k PRS over k
pathways. Pathways will be defined according to multiscale integration of ‘omics data, exploiting co-expression
networks, the transcriptome and the epigenome. The key deliverable from this project will be the production of a
powerful and comprehensive pathway-specific PRS computational tool, PRSet, informed by biological function.
The rationale is that PRS calculated for individuals by aggregating the effects of all risk variants genome-wide,
results in a loss of vital individual-level information. Providing pathway-specific estimates of genetic liability,
computed in a scalable, statistically rigorous way, informed by latest multi-omic data, could enable researchers
to better decompose heterogenous complex disease, identify key pathways that explain overlap or
differences among disorders, and explain problems of portability of PRS between and within populations.
Applying our pathway-specific PRS tool, we seek to stratify patients into more homogenous subgroups by their
liability over key pathways. We will use PRSet for stratification in three ways: (i) stratifying within SCZ/BiP, testing
if liability over different pathways forms multiple routes to disease, (ii) differentiating between SCZ and BiP, testing
if key pathways differentiate these highly overlapping disorders, (iii) testing whether variation in treatment
response can be explained by pathway liability. Such stratification could help explain past successes, failures
and adverse-effects in clinical trials, and provide new therapeutic targets tailored to subsets of patients.
Our proposal is significant because the burgeoning application of PRS means that any advance in the PRS
approach will have immediate, high impact across psychiatric research. Pathway-specific PRS could open-up
routes to hypotheses that cannot be answered by genome-wide PRS. If PRSet reveals that genetic liability is
more stratified than presently modelled, then this would call for a focus on pathways and their multi-omic
integration, paving a new path towards precision medicine.
Our proposal is innovative because we develop the first pathway-specific, function-informed, PRS tool, we
propose that disease risk may be influenced by multiple genetic liabilities, and we stratify patients according to
pathway-specific genetic risk for the first time.
In ...

## Key facts

- **NIH application ID:** 10136725
- **Project number:** 5R01MH122866-02
- **Recipient organization:** ICAHN SCHOOL OF MEDICINE AT MOUNT SINAI
- **Principal Investigator:** Paul Francis O'Reilly
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $635,256
- **Award type:** 5
- **Project period:** 2020-04-01 → 2025-02-28

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10136725

## Citation

> US National Institutes of Health, RePORTER application 10136725, Next-generation, pathway-specific, polygenic risk scores (5R01MH122866-02). Retrieved via AI Analytics 2026-05-22 from https://api.ai-analytics.org/grant/nih/10136725. Licensed CC0.

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