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Healthy Big Data Firehose?

Stanford University genetics researcher Mike Snyder and his colleagues are digging into deep datasets — including genome, transcriptome, microbiome assessments, physiological tests, and much more — generated over time for 109 healthy individuals. Their initial results are outlined in a paper published online in Nature Medicine yesterday.

The team unearthed dozens of clinically actionable results over three years of follow-up per participant, on average, including cancer susceptibility variants, early stage cancers, arrhythmias, MODY-related mutations, and other insights that may influence participants' health now or in the future.

In The New York Times, Snyder touts the big data-approach for personalizing care and preventing disease, noting that 53 of the study's participants have received crucial health information based on their multi-pronged profiles. Other experts interviewed for the piece argue that the individuals' outcomes should be compared with those receiving typical medical care, and suggest the strategy "will never be cost-effective and will instead lead to wild over-treatment of anxious patients."

"Dr. Snyder and his colleagues argue that examining the genomes of patients and carefully tracking them will make people healthier. Doctors will be able to catch disease earlier, and treat them more precisely," Carl Zimmer writes. "But critics questioned whether Dr. Snyder's big data firehose will actually make patients healthier — or just leave them floating in a sea of uncertainty and anxiety."

As our sister publication GenomeWeb Daily News reports, findings from the study have encouraged Snyder and his colleagues to launch a commercial profiling and monitoring company called Q Bio, which offers comprehensive genetic testing, whole-body MRI, and other longitudinal tests for an annual membership of less than $5,000.