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Showing the Power of Molecular Self-Tracking

An unprecedented study shows how personalized medicine could help head off disease.

Michael Snyder knows his body better than anyone in history.

Testing, testing: Via self-tracking, Michael Snyder learned he was vulnerable to diabetes. Soon thereafter, he developed the actual disease.

For two-and-a-half years, he’s had regular blood samples drawn, and tracked the ebb and flow of 40,000 different molecules within his cells, from hormones to blood sugar, to the proteins of the immune system and mutated genes. Snyder also watched as his genetic vulnerability to diabetes turned into actual disease.

In a paper published today in the journal Cell, Snyder, a genetics professor at Stanford University, and his collaborators recount 14 months of living a Truman Show kind of life, but with a microscope instead of a television camera. His story marks the first time anyone’s physiology has ever been followed this closely, and portends the future of personalized medicine, according to Snyder and others.

“This article reminds us that the future is now,” says Charis Eng, a professor of genomic medicine at the Cleveland Clinic. “I think we’re heading in this direction, and I think we must prepare in every way, not just scientifically, not just medically, but as a society—[considering] all the ethical, moral, and regulatory issues.”

The cost of providing such analysis—genomics, metabolomics, proteomics, and transcriptomics, along with immune system measures—was significant. Snyder, who is also director of the Center for Genomics and Personalized Medicine at Stanford, says it cost about $2,500 to collect molecular data from each blood sample, not counting the price of analyzing it or the millions of dollars in setup costs to purchase equipment.

Snyder, however, predicts the costs of such studies could drop dramatically, and become a common part of medicine. “In my case, it potentially saved a lot of damage,” he says.

During the course of the study, Snyder had his genome sequenced. The DNA testing suggested he was at risk for type 2 diabetes. Although his doctors didn’t see any outward signs that he might be developing the condition, his self-testing revealed early signs. He later developed the disease.

After being diagnosed, Snyder cleaned up his diet and stepped up his exercise routine, losing weight and bringing markers of the disease back under control.

A close reading of his body’s data suggested to Snyder that his diabetes could have been triggered by a “pretty nasty cold” that forced him to skip work for a few days. 

Betul Hatipoglu, an endocrinologist at the Cleveland Clinic, doesn’t think any specific virus caused Snyder’s diabetes. But she says the coincident timing supports the idea that stress can unmask underlying vulnerabilities. “It could have been any other kind of stress that turned on that event,” she says. “If you carry these genes, a big stress like a huge car accident could turn that on. The body uses many pathways to respond to stress.”

Eng, the geneticist, agrees that the power of this kind of multilayer analysis is the insight it offers into gene-environment interactions—how the environment “talks” to DNA. “It was caught in the act by modern technology,” she says.

The challenge for expanding this kind of analysis beyond the lab, Eng says, will be finding people who can interpret all this physiologic data and make it meaningful. Data analyzed incorrectly could be dangerous, she says; data presented badly could stoke unnecessary fears. “The people who are very facile at interpreting [information] to the patient are very few and far between.”

Snyder admits that integrating 40,000 pieces of data collected over irregular periods “wasn’t so trivial,” which is why he and his collaborators hope to narrow the data down to the most telling markers. His next research goal, he says, is to do a similar long-term analysis of 250 people who are at elevated risk for diabetes, so he can watch the disease develop.

He is also doing preliminary research on people with other common diseases, such as asthma, and with complex disorders like schizophrenia and autism. He wants to add measures that can detect changes related to aging and environmental exposure to toxins.

Eventually, Synder says, he hopes people can analyze a full range of molecular information at birth and then again every six months to catch medical warning flags and make lifestyle or medication changes before problems develop. 

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