More than 275 million never-before-seen gene variants uncovered in US population

Scientists have uncovered more than 275 million previously unknown gene variants in the U.S. population, thanks to an ongoing project that aims to increase the diversity of the human genetic data available in medical research. 

The newfound variants were discovered in an analysis of nearly 250,000 complete genome sequences from more than 413,000 people, 77% of whom belonged to groups that have historically been underrepresented in biomedical research. These include, for example, people in minority ethnic and racial groups, people living in poverty, and those over age 65. 

The participants volunteered to have samples of their DNA taken and analyzed as part of the All of Us Research Program, a National Institutes of Health project intended to collect and study data on more than 1 million people in the U.S. Its goal is to provide a better representation of the demographic makeup of the country than genetic analyses based mostly on white people have historically done. The researchers behind the project believe that resources like All of Us could make drug development more relevant for a wide range of people. 

"All of Us is really meant to represent the full diversity of America," Dr. Alexander Bick, one of the scientists who collaborated on the project and an assistant professor of medicine at Vanderbilt University Medical Center in Tennessee, told Live Science. 

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The new findings were described by Bick and colleagues in a paper published Monday (Feb. 19) in the journal Nature. Beyond showcasing the All of Us database as a "great research tool," four companion papers published at the same time also highlight the database's potential to tangibly affect people's health, Bick said. 

One paper published in the journal Nature Medicine, for instance, used All of Us data to calculate more-reliable estimates of people's risk of developing 10 chronic diseases, such as type 2 diabetes, obesity and cancer. These risk predictions were based on an analysis of their genes. After conducting these calculations with the All of Us data, the researchers could predict future disease risk in 25,000 adults and children in a separate group of diverse ancestry, at least 35% of whom belonged to a racial or ethnic minority or medically underserved population. 

Another study, published in the journal Communications Biology, revealed that the rate of mutations in 73 genes associated with an increased risk of disease is lower in people of African ancestry (1.62%) than in people of European ancestry (2.26%.) These diseases included breast cancer and hypercholesterolemia, a condition in which a person has too much "bad" cholesterol, or low-density lipoprotein (LDL), in their blood. This discrepancy is largely caused by a lack of diversity in existing clinical datasets that didn't include enough people of non-European descent to confirm if these mutations were linked to disease in these individuals or not, Bick said. 

The All of Us project is one of a few initiatives globally that have been working to increase the diversity of genetic databases; until recently, most databases have been focused primarily on people of European ancestry. 

The project started recruiting participants in 2018 and has since been working with more than 50 health systems and community partners across the country to recruit as many people as possible, Bick said. Samples of blood, urine and saliva are donated by participants and then stored in a repository at the Mayo Clinic in Minnesota so they can be used in future research. 

"The enhanced genetic diversity described in this new report by the All of Us research program, combined with related research efforts in the United States and globally, is an important first step toward ensuring equity in precision medicine," Malia Fullerton, a professor of bioethics and humanities at the University of Washington School of Medicine who was not involved in the research, told Live Science in an email. Precision medicine refers to treatments that are tailored to specific patients based on their genetics, environments and lifestyles.

"The next challenge will be to work in close collaboration with underrepresented communities to ensure that the predictive tests and therapies made possible by such datasets will be accessible to all," she said.

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