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LOS ANGELES (CNS) - UCLA Health today announced it is being awarded a $4.8 million grant from the National Institutes of Health to develop ways to improve genetic risk estimates for diverse populations, as current methods are biased toward people of European ancestry.
The grant, which is provided through funding from the National Human Genome Research Institute and National Cancer Institute, will help UCLA develop methods to improve polygenic risk scores for specific diseases in people with mixed ancestries and from diverse populations, the university said.
The funding will help establish a multi-center research consortium that will pool genomic information from existing and new datasets to help researchers develop and evaluate methods of calculating polygenic risk scores. UCLA will be the only funded center focusing on polygenic risk scores for diverse populations and for individuals of “admixed ancestries.'' The research fits into UCLA Institute for Precision Health's mission to facilitate the implementation of precision health and genomic medicine for everyone, including people who have been historically underrepresented in most biomedical research.
“More than 30% of individuals living in the U.S. self-identify as having admixed ancestry, usually defined as those with recent ancestry from two or more continental sources, such as African Americans and/or Latinx individuals,'' said Dr. Bogdan Pasaniuc, an associate professor at the David Geffen School of Medicine at UCLA who specializes in computational medicine, pathology and laboratory medicine, human genetics and bioinformatics.
Pasaniuc's research focuses on statistical and computational methods for understanding risk factors for common diseases, with an emphasis on the study of admixed populations.
Polygenic scores are calculated by comparing the genomic data of people with and without a particular disease, according to UCLA. Statistical calculations are used to estimate how at-risk a person is for that disease. Existing large-scale genomic datasets are biased towards people of European ancestry, and researchers have found it ineffective when applied to diverse populations.
Current risk scores have “the potential to worsen outcomes or widen health disparities in underrepresented groups if these groups are not included in research,'' according to leaders in genomic medicine and health care cited by UCLA.
“Owing to the lack of diversity in existing genomic studies, existing polygenic risk scores perform poorly in individuals with mixed genetic ancestry, particularly for individuals with largely non-European genetic ancestry,'' Pasaniuc said. “Thus, existing PRS could exacerbate health disparities as they cannot be applied equitably across individuals of all ancestries. Diversity in genetic ancestry within admixed genomes raises unique challenges that cannot be addressed by existing paradigms.''
Researchers at the UCLA Center will analyze the genomes of more than 200,000 admixed individuals, in collaboration with the University of Colorado's Colorado Center for Personalized Medicine and Mount Sinai Health System's Institute for Genomic Health in New York to discover accurate and equitable genetic predictions for all people. Biological samples will be provided by the UCLA ATLAS Precision Health Biobank, which codes the samples to remove any personally identifying information.
“Our investment in the UCLA Institute for Precision Health ATLAS project was not only to build an infrastructure for the treatment of our UCLA Health patients using precision medicine approaches, but also to create an infrastructure that would allow our faculty to pursue innovative new research projects and collaborations with other organizations to improve health care practices nationally and globally,'' said Dr. Daniel Geschwind, UCLA Health senior associate dean and associate vice chancellor for Precision Health. “Our participation with this leading-edge consortium is a major step in that direction since it leverages the diversity of our patients, parallel with our goal of reducing disparities.''
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