Polygenic risk scores (PRS) are promising tools for predicting disease risk, but current versions have built-in bias that can affect their accuracy in some populations and result in health disparities. However, a team of researchers from Massachusetts General Hospital (MGH), the Broad Institute of MIT and Harvard, and Shanghai Jiao Tong University in Shanghai, China, have designed a new method for generating PRS that more accurately predict disease risk across populations, which they report in Nature Genetics.
New tool more accurately uses genomic data to predict disease risk across diverse populations
Polygenic risk scores (PRS) are promising tools for predicting disease risk, but current versions have built-in bias that can affect their accuracy in some populations and result in health disparities. However, a team of researchers from Massachusetts General Hospital (MGH), the Broad Institute of MIT and Harvard, and Shanghai Jiao Tong University in Shanghai, China, have designed a new method for generating PRS that more accurately predict disease risk across populations, which they report in Nature Genetics.