Lack of Diversity in Genetic Datasets is Risky for Treating Disease

Certain populations have been historically underrepresented in genome sequencing studies, but the NIH, private clinics, and 23andMe and other companies are trying to fix that.

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Not too long ago, a couple came to see Neil Risch, a human geneticist at the University of California, San Francisco, in the hope that he could identify rare gene variants in their child, who had an undiagnosed disease. Not a problem, Risch thought. He’d sequence the exomes of the parents and child and run the data through a rare-variants database to identify the faulty genes underlying the child’s illness. The case wasn’t so straightforward, though. The parents didn’t have European ancestry but were descendants of a population not well represented in the database.

“For individuals with genetic backgrounds not represented in [the database], there can be additional challenges in properly identifying genetic variants that cause the patient’s symptoms,” Risch says. Namely, it’s hard to identify any genetic link to symptoms, perhaps because the disease is caused by novel variants not yet identified as pathogenic.

The case, Risch says, is ...

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Meet the Author

  • Ashley Yeager

    Ashley started at The Scientist in 2018. Before joining the staff, she worked as a freelance editor and writer, a writer at the Simons Foundation, and a web producer at Science News, among other positions. She holds a bachelor’s degree in journalism from the University of Tennessee, Knoxville, and a master’s degree in science writing from MIT. Ashley edits the Scientist to Watch and Profile sections of the magazine and writes news, features, and other stories for both online and print.

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