Stanford researchers see 'genome cloaking' as a way to alleviate patient privacy fears

Researchers at Stanford University may have discovered a way to address latent privacy concerns associated with genetic data, while also advancing the genomic research driving precision medicine initiatives across the country.

A group of computer scientists, engineers, biologists and geneticists found an approach that allows researchers access to specific gene mutations while hiding the remainder of the patient’s genetic information. Using cryptography, the Stanford researchers were able to mask more than 99% of genetic information, according to a study published in Science.

“There are ways to simultaneously share and protect this information,” Gill Bejerano, Ph.D., associate professor of developmental biology, of pediatrics and of computer science, said in a press release. “Now we can perform powerful genetic analyses while also completely protecting our participants’ privacy.”

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Patient privacy has been an underlying concern as the medical community pushes forward with large-scale research efforts like the Precision Medicine Initiative and the Cancer Moonshot that incorporate genomic data from millions of people. Some worry those initiatives will be forced to confront privacy hurdles that could prevent patients from voluntarily submitting patient data.

A major concern for patients is how their genetic information would be used by insurers or employers. A widely criticized House bill introduced in May proposed allowing employers to punish employees that don’t participate in wellness programs that collect genetic information.

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The approach used by Stanford researchers allows individuals to encrypt their genetic data which is uploaded to the cloud. Researchers use cryptography to limit their search to the gene variants they are investigating. The researchers hope this approach entices people who have genetic diseases to feel more comfortable turning over their information.

“Basically, if you have 1 million people with genomic data they would like to keep private, this approach lets researchers analyze the data in aggregate and only report on findings that are pertinent,” Dan Boneh, Ph.D., professor of computer science and of electrical engineering at Stanford University, said. “An individual might have dozens of anomalous genes, but the researchers and clinicians will only learn about the genes relevant to the study, and nothing else.”