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Clinical use of polygenic risk scores: current status, barriers and future directions

Nature Reviews Genetics (2025)Cite this article

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Abstract

Genome-wide association studies have identified thousands of single-nucleotide variants that are associated with complex traits, including cardiometabolic diseases, cancers and neurological disorders. Polygenic risk scores (PRSs), which aggregate the effects of these variants, can help to identify individuals who are at increased risk of developing such diseases. As PRSs are typically only weakly associated with conventional risk factors for these diseases, they have incremental predictive value and are beginning to be incorporated into clinical practice to guide early detection and preventive strategies. However, challenges to their use — such as suboptimal precision, poor transferability across diverse populations and low familiarity among patients and providers with the concept of polygenic risk — must be addressed before their broader clinical adoption. This Review explores the current state of the field, highlights key challenges and outlines future directions for the use of PRSs to improve risk prediction and to advance personalized prevention in clinical care.

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Fig. 1: The influence of population and evolutionary genetics on polygenic risk scores.
Fig. 2: Potential sources of imprecision in a polygenic risk score for an individual.
Fig. 3: A framework for integrating polygenic risk scores into the electronic health record.

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Acknowledgements

This work was supported by funding from the US National Human Genome Research Institute for the eMERGE Network; the PRIMED Consortium and the ClinGen Consortium. The author is additionally supported by the Mellowes Center for Genomic Sciences and Precision Medicine, the Cardiovascular Research Center and the Advancing a Healthier Wisconsin Endowment, Medical College of Wisconsin. The author thanks L. Wussow for help with manuscript preparation.

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  1. Department of Medicine, Division of Cardiovascular Medicine, the Cardiovascular Research Center and the Mellowes Center for Genomic Sciences and Precision Medicine, Medical College of Wisconsin, Milwaukee, WI, USA

    Iftikhar J. Kullo

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Related links

1000 Genomes Project: https://www.internationalgenome.org/

All of Us: https://www.researchallofus.org/

Australian Genomics: https://www.australiangenomics.org.au/

ClinGen: https://clinicalgenome.org/

DNGC: https://www.eng.ngc.dk/

eMERGE: https://www.genome.gov/Funded-Programs-Projects/Electronic-Medical-Records-and-Genomics-Network-eMERGE

FinnGen: https://www.finngen.fi/en

Genes & Health: https://www.genesandhealth.org/

Genome Canada: https://genomecanada.ca/

GIRA: https://www.mayo.edu/research/emerge-genome-informed-risk-assessment/overview

Human Pangenome Project: https://humanpangenomeproject.org/

Our Future Health: https://ourfuturehealth.org.uk/

PGS Catalog: https://www.pgscatalog.org/

PRECISE: https://www.npm.sg/

QGP: https://www.ga4gh.org/driver_project/qatar-genome-program/

Social Science Genetic Association Consortium: https://www.thessgac.org/

TOPMed: https://topmed.nhlbi.nih.gov/

UK Biobank: https://www.ukbiobank.ac.uk/

Supplementary information

Glossary

Absolute risk

Refers to the actual probability or likelihood of an event occurring in a specific population over a defined time period. It is often expressed as a percentage or a proportion. By contrast, relative risk compares the risk of an event or outcome occurring in two different groups, typically those exposed to a certain factor versus those who are not exposed.

Clinical decision support

(CDS). Refers to various tools and systems designed to enhance the decision-making capabilities of healthcare professionals at the point of care. These tools provide clinicians with knowledge and patient-specific information to help them make informed decisions about patient care.

Disease liability

The unobserved, continuous measure of an individual’s predisposition to disease owing to both genetic and environmental factors, with disease manifesting only if liability exceeds a certain threshold.

Genetic ancestry groups

A set of individuals who share similar genetic ancestries based on quantitative measure(s) of genetic resemblance between individuals.

Genetic architecture

The genetic architecture of a quantitative trait or phenotype refers to the number of genetic variants affecting the trait or phenotype, the magnitude of the variants’ effects, allele frequencies of the variants and interactions of variants with each other and with the environment, all of which contribute to heritability. Most common diseases are highly polygenic or even ‘omnigenic’, whereby many thousands of genetic variants of modest effect sizes could have a cumulative effect on disease predisposition.

Heritability

A statistic that estimates the degree of the variation in a trait that is owing to genetic variation in a population. Broad-sense heritability represents the fraction of phenotypic variation explained by both additive and dominance effects; narrow-sense heritability considers additive effects only and is the proportion of phenotypic variation owing to additive effects of multiple genetic variants.

Linkage disequilibrium

The nonrandom association of alleles at two or more loci on the same chromosome.

Polygenic risk

Refers to the cumulative contribution of many genetic variants across the genome to an individual’s risk of developing a complex trait or disease. A polygenic risk score quantifies polygenic risk for an individual.

SNV heritability

A subset of narrow-sense heritability that refers to the proportion of the phenotypic variability that is explained by all single-nucleotide variants (SNVs) used in a genome-wide association study. SNV heritability sets a limit on the predictive accuracy of a polygenic risk score based on common variants.

Social Determinants of Health

(SDOH). These are environmental conditions in which people are born, grow, live, work and age. They include economic stability, education access and quality, healthcare access and quality, neighbourhood and built environment and social and community context.

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Kullo, I.J. Clinical use of polygenic risk scores: current status, barriers and future directions. Nat Rev Genet (2025). https://doi.org/10.1038/s41576-025-00900-8

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