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UCLA Receives $4.8M NIH Grant to Improve Genetic Risk Estimates

UCLA will receive a $4.8M NIH grant to establish methods of improving genetic disease risk estimates for diverse populations using genomic data.

UCLA Receives $4.8M NIH Grant to Improve Genetic Risk Estimates

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By Jill McKeon

- UCLA Health will receive a $4.8M National Institutes of Health (NIH) grant to improve upon genetic disease risk estimates for diverse populations. The grant will enable researchers to establish polygenic risk scores (PRS) for particular diseases using genomic datasets and form a multi-center research consortium.

The funding comes from NIH’s National Human Genome Research Institute (NHGRI) and the National Cancer Institute (NCI). Researchers will focus on finding innovative ways to calculate polygenic risk scores specifically for people of mixed ancestries, or “admixed ancestry.” These populations tend to be overlooked when it comes to biomedical research, which is the reasoning behind the project’s focus. 

"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," Bogdan Pasaniuc, PhD, an associate professor at the David Geffen School of Medicine at UCLA, said in a press release.

UCLA will establish the PRS Center for Admixed Populations and Health Equity (CAPE) and use blood, tissue, and saliva samples from the UCLA ATLAS Community Health Initiative. CAPE will be a collaborative effort between the Institute for Precision Health (IPH) and the Department of Computational Medicine at UCLA Health.

Researchers will compare the genomic data of people with and without certain diseases and use bioinformatic analysis to pinpoint genetic variations. Next, they can calculate risk scores based on a person’s specific gene variants.

The majority of currently available datasets are comprised largely of health data from people of European ancestry, which makes it difficult to study and develop precision medicine treatments for diverse populations.

"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 continued.

“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 will utilize over 200,000 deidentified genetic samples from admixed populations with the help of the UCLA ATLAS Community Health Initiative and the UCLA ATLAS Precision Health Biobank. In addition, the NHGRI’s Genomic Data Science Analysis, Visualization and Informatics Lab-space (AnVIL) will assist with the project’s storage and computational analysis requirements.

"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," Daniel Geschwind, MD, PhD, UCLA Health senior associate dean and associate vice chancellor for Precision Health, explained in the press release.

"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."

In other news, the NIH also recently gave a $3 million grant to a University of Massachusetts Amherst researcher to study the effects of accountable care organizations on childhood asthma care, and the University of Pittsburgh Graduate School of Public Health and Washington University School of Medicine received a $10.7 million grant to explore genomic data’s role in Alzheimer’s.