UCLA study shows accuracy of genetically based disease predictions varies from individual-to-individual

Polygenic scores – estimates of an individual’s predisposition for complex traits and diseases – hold promise for identifying patients at risk of disease and guiding early, personalized treatments, but UCLA experts found the scores fail to account for the wide range of genetic diversity across individuals in all ancestries.

“Polygenic scores can estimate the likelihood of an individual having a certain trait by pulling together and analyzing the small effects of thousands to millions of common genetic variants into a single score, but their performance among individuals from diverse genetic backgrounds is limited,” said Bogdan Pasaniuc, PhD, a UCLA Health expert in statistical and computational methods for understanding genetic risk factors for common diseases.

The researchers’ analysis, published in Nature , shows that the accuracy of polygenic scores (PGSs) varies between individuals across a continuum of genetic ancestry – and this is true even in populations that are traditionally considered as ‘homogeneous,’ (e.g., Europeans) said Pasaniuc, the paper’s senior author. Included in the research team are collaborators from Aarhus University in Denmark and the Novo Nordisk Foundation Center for Genomic Mechanisms of Disease at the Broad Institute of MIT and Harvard, 

Assessing PGS performance has commonly been done at the “population” level, such as in “Europeans,” clumping individuals of similar ancestries in a genetic-ancestry cluster, the authors said.

“Imposing artificial boundaries onto this continuum and ignoring the diversity, or ‘heterogeneity,’ within clusters can obscure variation within a group, conceal the similarities that may exist in individuals in different groups, and leave out individuals who do not fit neatly into a particular genetic ancestry,” said Yi Ding, a graduate student in bioinformatics at UCLA, a member of the Pasaniuc Lab, and the paper’s first author.

This story was adapted from the UCLA Health news release. 

This research was supported in part by the ATLAS Community Health Initiative. The UCLA ATLAS Community Health Initiative in collaboration with UCLA ATLAS Precision Health Biobank is a program of the Institute for Precision Health, which directs and supports the biobanking and genotyping of biospecimen samples from participating patients from UCLA in collaboration with the David Geffen School of Medicine, UCLA Clinical and Translational Science Institute and UCLA Health. The ATLAS Community Health Initiative is supported by UCLA Health, the David Geffen School of Medicine and a grant from the UCLA Clinical and Translational Science Institute (UL1TR001881).

Image caption: Digital illustration of a DNA model on science background.

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