One way to make health care more personalized is to use a person’s DNA sequence — or genome — to predict their risk of disease. But as the field of precision medicine grows, so have concerns that we may be leaving a large fraction of Americans out.
Disease prevalence and severity can vary considerably across racial and ethnic groups due to genetic and social factors. However, most of what we know about the genetics of human disease comes from datasets of predominantly white, European people. This lack of genomic data from people of other backgrounds makes it harder to accurately predict their health outcomes. Even less is known about the genomes of “admixed” individuals whose DNA reflect multiple ancestries.
So the question is: How do we ensure that advancements in genomic medicine will be accessible to all?
Lucila Ohno-Machado, MD, PhD (left), Kelly Frazer, PhD, (center), and Melissa Gymrek, PhD, (right) are principal investigators of the new genomics center at UC San Diego.
Researchers at University of California San Diego School of Medicine have been awarded $11.7 million to launch the Genetic & Social Determinants of Health: Center for Admixture Science and Technology (CAST) to address this issue. CAST will use the largest genomic datasets of individuals with diverse ancestry, in combination with socioeconomic data, to better predict health and disease in admixed individuals.
Historical and recent mixing of Europeans, Native Americans, Africans and Asians has resulted in a relatively large number of admixed individuals in the U.S. Their genomes are a patchwork of DNA segments associated with different races and ethnicities, and may reflect ancestries outside of the individual’s self-identified race. The issue is physicians do not yet know how these DNA segments interact with each other to shape health outcomes, so these genomes are more difficult for them to interpret.
CAST is one of the latest additions to the renowned Centers of Excellence in Genomic Science (CEGS) funded by the National Institutes of Health (NIH). Each center focuses on a unique aspect of genomics research with the intention of blazing new trails in our understanding of human biology and disease.
“To bring the CEGS program to our campus is a huge honor, and a national recognition of UC San Diego as a major player in genomics,” said Lucila Ohno-Machado, MD, PhD, Distinguished Professor of Medicine at UC San Diego School of Medicine, chair of the Department of Biomedical Informatics at UC San Diego Health, and founding faculty of the Halıcıoğlu Data Science Institute. Ohno-Machado will lead the center with Kelly Frazer, PhD, professor of pediatrics and director of the Institute for Genomic Medicine at UC San Diego School of Medicine, and Melissa Gymrek, PhD, assistant professor at UC San Diego School of Medicine and Jacobs School of Engineering.
Researchers need data on many people’s genomes and health outcomes in order to find consistent relationships among them. The health of individuals from different racial and ethnic groups is also affected by social factors, so this information must be included in models of disease. To do all this, CAST will develop computational tools to combine, protect and analyze data from two national studies: All of Us Research Program and the Million Veterans Program. These projects aim to recruit one million participants each, equipping CAST with an unprecedentedly large and diverse pool of data.
Their ultimate goal is for anyone to be able to visit their physician, have their genome sequenced, and learn not only if they are at higher risk for any particular disease, but also which prevention and treatment plans are best suited for them.
“As it stands, white people will be able to do this, but our existing knowledge may not be useful to most others,” said Gymrek. “We want to bring the genomic revolution to everyone.”
“People may not realize that a large number of people living in America are likely admixed, so we would be excluding a large portion of our community if we were not taking these mixed genomes into account,” said Ohno-Machado.
CAST will use advanced approaches to study admixed genomes. Their models will consider each individual’s unique patchwork of ancestry, rather than grouping individuals into established categories like “white” or “Asian.” And while most groups focus on changes in individual DNA nucleotides, known as single nucleotide polymorphisms (SNPs), the CAST team will consider a much broader spectrum of genetic variation. This includes investigating tandem repeats, or short lengths of DNA that are repeated at different frequencies in each person, and a region called the major histocompatibility complex (MHC). The MHC is one of the most diverse sections of the genome across races, in part because it is related to immune function, which is tailored to each population’s local environment.
CAST will also innovate the way large-scale and complex data is processed. The team will develop privacy-preserving algorithms that consult the data in the All of Us and the Million Veterans enclaves without needing to centralize the data in a single place. They will also use natural language processing to extract information on social determinants of health from patients’ clinical notes. These innovations will come from collaborations between informatics researchers at UC San Diego, the Broad Institute, University of Texas Health, Indiana University and the Veterans Administration.
“I really think we have the dream team here,” said Frazer. “We’re excited to use our complementary expertise to push the limits of genomic medicine at UC San Diego and beyond.”
Co-investigators at the Center for Admixture Science and Technology include: Lisa Madlensky, PhD, Cheryl Anderson, PhD, MPH, Cinnamon Bloss, PhD, Vineet Bafna, PhD, Niema Moshiri, PhD, Tim Kuo, PhD, Olivier Harismendy, PhD, Matteo D’Antonio, PhD, and Jihoon Kim, MS, of UC San Diego. Principal collaborators include Hoon Cho, PhD, of the Broad Institute, Hua Xu, PhD, of University of Texas Health, Haixu Tang, PhD, of Indiana University and Philip Tsao, PhD, of the Veterans Administration.