A New Tool Opens New Door to Personalized Genetic Risk Assessment

PGS Browser integrates thousands of polygenic scores and provides new tools and resources for their interpretation, helping to bridge the gap between genomic research and clinical application.

A new study led by investigators from the Steve and Cindy Rasmussen Institute for Genomic Medicine at Nationwide Children’s is helping make genetic information more accessible through a public platform that could advance disease risk prediction and precision medicine. 

Published in Nature Communications, the study introduces the PGS Browser, an online resource designed to help researchers interpret and apply polygenic scores (PGSs). PGSs estimate an individual’s inherited risk for disease by combining the effects of many genetic variants across the genome.  

Mykyta Artomov, PhD

“Polygenic scores have enormous potential to identify individuals at increased risk for disease long before symptoms appear, but the field has lacked practical tools for interpreting those scores,” says Mykyta Artomov, PhD, principal investigator in the Institute for Genomic Medicine and lead author of the study. “Our goal was to create a resource that makes rigorous, population-scale genetic risk assessment accessible to researchers everywhere.”

Unlike rare disease-causing mutations, the genetic risk behind common conditions is typically distributed across hundreds or thousands of variants. This complexity has limited the practical use of PGSs despite their growing potential in research and clinical settings.

To address this challenge, researchers systematically evaluated 3,168 publicly available PGS models using genetic and clinical data from 473,681 participants in the FinnGenn study, one of the world’s largest biobank initiatives. The team developed a standardized framework for comparing PGS performance across diseases and traits, making it easier to identify the scores with the greatest potential for research and future clinical application.  

The analysis revealed that some PGSs, particularly those related to immune-mediated and metabolic conditions, showed strong predictive performance. Researchers also found that combining multiple related scores often improved performance beyond that of any single score alone. This approach enhanced risk prediction for complex conditions such as obesity, rheumatoid arthritis and inflammatory bowel disease.  

Beyond benchmarking existing models, the team developed PGS reference distributions that allow users to interpret an individual’s score relative to large population datasets, regardless of the individual’s ancestry background. The platform also includes an extensive atlas of genetic associations and provides access to interactive predictive models that estimate how genetic risk may influence the likelihood and timing of disease onset. All of these resources are available through the online PGS Browser platform accessible via pgs.nchigm.org. 

This platform also reflects a commitment to making advanced genomic tools more broadly available.  

“By bringing together validated polygenic scores, population reference data and predictive models in a single public resource, we are helping bridge the gap between genomic discovery and clinical translation. The PGS Browser gives researchers a practical framework for exploring how genetic risk information can ultimately support more personalized prevention and care,” Dr. Artomov says. 

As genomic data becomes increasingly integrated into healthcare, tools such as the PGS Browser may help researchers and clinicians better understand who is at risk of disease and when preventive interventions might have the greatest impact. 

References 

Kolosov, N., Reeve, M. P., Briotta Parolo, P. D., Kurki, M. I., FinnGen, Llorens, V., Sipila, T. P., Herman, A., Molotkov, I., Aavikko, M., Ripatti, S., Palotie, A., Daly, M. J., & Artomov, M. (2026). PGS Browser: a public platform for personalized polygenic score analysis and interpretation. Nature Communications, Advance online publication. https://doi.org/10.1038/s41467-026-74461-7