Diverse Genome Sequences Lead to Creation of Risk Scores
Researchers created polygenic risk scores by studying genetic variants in diverse populations.
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By - By studying diverse populations, researchers found genetic variants associated with blood lipid levels and created a polygenic risk score to predict elevated low-density lipoprotein cholesterol levels.
Lipids are fat-like substances that are found in blood and body tissue. They come in two major forms, cholesterol and triglycerides. For normal function, humans need a certain amount of lipids in the body. However, elevated lipid levels can increase the risk of developing heart conditions.
Polygenic risk scores can use predictive analytics to determine an individual’s risk for specific diseases based on their DNA changes related to the diseases.
“Finding the set of genomic variants that are important for this trait is key for us to understand the biology and identify new drug targets,” senior author and professor of human genetics at the University of Michigan, Ann Arbor, Cristen Willer, PhD, said in a press release. “These genomic variants then inform how well polygenic risk scores work to determine risk for such diseases.”
Over the years, the genomic community has performed over 6,000 studies examining the association of specific genomic variants and cardiovascular disease. However, the studies overwhelmingly examined individuals from European ancestral populations.
For broader results, the research team collected data from 201 previous genome-wide associations studies, including about 1.65 million individuals from five ancestral groups: African, East Asian, European, Hispanic, and South Asian. The studies contained data regarding the blood levels of the different classes of cholesterol and triglycerides.
Researchers calculated the polygenic risk scores using data from each of the different ancestral groups. The risk scores were then tested in a diverse set of studies. The results indicated that a risk score that includes diverse genomic data is highly predictive compared to methods that only include European genomic data.
“The message couldn’t be more clear. To have a fuller understanding of the effects of genomic variation on disease, we simply must include as many diverse groups of people as possible,” said Charles Rotimi, PhD, a co-author on the paper.
“It is the single biggest way by which we can ensure that the gains of genomic medicine and technologies are equitably deployed to serve the health needs of all human populations.”
For each ancestral group, the polygenic risk score that used data from all ancestries worked at least as well as or better than the risk scores derived from data from the same ancestral population.
“These results show that our concerted effort to include many diverse groups of people in genomic research will yield benefits such as new therapeutics and prevention strategies that improve the health of all people,” said Cashell Jaquish, PhD, a genetic epidemiologist and program officer within the Division of Cardiovascular Sciences at the National Heart Lung, and Blood Institute.
