Standardizing how researchers develop and validate polygenic risk scores

June 23, 2021

UCLA Health will receive a $4.8 million grant from the National Institutes of Health (NIH) to develop methods that will improve genetic risk estimates — polygenic risk scores — for specific diseases in people from diverse populations and mixed ancestries.

The NIH funding comes from grants provided by the National Human Genome Research Institute (NHGRI) and the National Cancer Institute (NCI) to establish a multi-center research consortium that will pool genomic information from existing and new datasets. The researchers will then develop and evaluate methods for calculating polygenic risk scores (PRS) with an emphasis on studying people from different ancestries. Each research center may include several collaborating institutions.

Of the newly funded centers, UCLA’s is the only one focusing not only on polygenic risk scores for diverse populations, but specifically for individuals of “admixed ancestry.” This fits with a key cornerstone of the UCLA IPH’s mission, which is to facilitate the implementation of precision health and genomic medicine for all individuals, including those who are usually underrepresented in most biomedical research.

At UCLA, the funds will be used to establish the PRS Center for Admixed Populations and Health Equity (CAPE), a collaboration between the Department of Computational Medicine and the Institute for Precision Health (IPH) within the David Geffen School of Medicine and UCLA Health. The center will leverage the UCLA ATLAS Community Health Initiative, a large collection of patient blood, saliva and tissue samples being analyzed to help UCLA researchers and clinicians develop and deliver the best care possible.

Researchers and clinicians calculate polygenic risk scores by comparing the genomic data of people with and without a particular disease. Bioinformatic analysis is used to identify groups of genomic variants that are found more frequently in individuals with the disease, and then statistical calculations are used to estimate how a person’s variants affect their risk for that disease.

Although researchers in recent years have been able to calculate risk scores for numerous conditions, and even tailor medical management and interventions accordingly, the existing large-scale genomic datasets are heavily biased toward individuals of European ancestry and are not effective when used in diverse populations. In fact, leaders in genomic medicine, healthcare and research concluded in 2019 that current risk scores have “the potential to worsen outcomes or widen health disparities in underrepresented groups if these groups are not included in research.”

The UCLA center – which will include collaborators from the Colorado Center for Personalized Medicine at the University of Colorado and the Institute for Genomic Health at Mount Sinai Health System in New York – will focus on incorporating genetic diversity in PRS to yield accurate and equitable genetic prediction for any individual, irrespective of their ancestry. The researchers will analyze the genomes of more than 200,000 admixed individuals.

The research will build on and benefit from the UCLA ATLAS Community Health Initiative and the UCLA ATLAS Precision Health Biobank, which collects biological samples from as many people as possible, codes the samples, removes any personally identifying information, and provides the samples to approved researchers who are seeking new ways to prevent, detect and treat health problems.

The consortium will leverage NHGRI’s Genomic Data Science Analysis, Visualization and Informatics Lab-space (AnVIL), a cloud-based resource, to address its computational analysis and storage needs in a shared environment. In addition to developing new approaches and datasets, researchers at the participating institutions will work to increase transparency and standardize practices in the ways in which researchers develop and validate polygenic risk scores.

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