To scientists like Michael Snyder, chair of the genetics department at Stanford University, the future of medicine is data — lots and lots of data.
He and others predict that one day doctors won’t just take your blood pressure and check your temperature. They will scrutinize your genome for risk factors and track tens of thousands of molecules active in your body.
By doing so, the doctors of the future will identify diseases, and treat them, long before symptoms appear.
The approach has a number of critics, who say it will never be cost-effective and will instead lead to wild overtreatment of anxious patients.
But on Wednesday, Dr. Snyder and his colleagues published a study suggesting that big data may succeed where conventional medicine fails.
In 109 volunteers whose bodies were closely tracked and analyzed, the researchers discovered a host of hidden conditions that required medical attention, including diabetes and heart disease.
“It turns out 53 out of 109 people learned something really, really important from doing these deep profiles,” Dr. Snyder said.
The research offers an unprecedented look at how common diseases may arise in different people along different molecular paths, said Ali Torkamani, director of genome informatics at Scripps Research Translational Institute, who was not involved in the new study.
Once doctors are able to record genetic activity in their patients, “then you could start thinking about more rational ways of intervening,” he added.
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The new study is the result of a remarkable scientific journey.
For a decade, Dr. Snyder has been trying to learn everything he can about his own body, down to its molecular building blocks. He has turned himself into a big-data guinea pig.
First, he and his colleagues sequenced his genome. Dr. Snyder learned to his surprise that he had several mutations linked to diabetes. The team analyzed his blood over the course of 14 months, tracking 40,000 molecules.
In 2011, that monitoring revealed that Dr. Snyder was indeed developing diabetes. He started treating the condition, and his symptoms improved.
In 2012, when Dr. Snyder and his colleagues published a study describing these efforts, no one had seen anything quite like it.
Along with his genome (all his genes), Dr. Snyder published his transcriptome (the molecular signature of which of his genes were active), his proteome (all the new proteins his body produced), and his metabolome (all the molecules involved in his metabolism).
Dr. Snyder, chair of the genetics department at Stanford University. Intense genetic analysis turned up early signs of diabetes in the researcher.CreditPaul Sakuma/Stanford School of Medicine
By vacuuming up data with the latest technologies, doctors one day may produce a razor-sharp picture of each patient’s health, and then devise individualized treatments when illness appears.
It was a seductive prospect. When Dr. Snyder decided to launch a larger project, he had little trouble attracting 108 other volunteers.
He and his colleagues started by sequencing each subject’s genome and performing in-depth physicals. Every three months, the volunteers returned to Stanford to give blood, urine, stool and cheek swabs. Some wore continuous glucose monitors, and some wore heartbeat trackers on their wrists.
The initial exams revealed a number of conditions. Eighteen people were diagnosed with Stage II hypertension. One volunteer had full-blown diabetes, without having ever been diagnosed with pre-diabetes in conventional exams.
Genome sequencing also revealed medical insights. One subject who suffered recurring strokes turned out to be taking the wrong medication, thanks to a mutation that made the drug ineffective.
Other volunteers discovered they had mutations that may cause serious illness. One had a genetic variant linked to enlarged, weakened heart muscles. An imaging test revealed the volunteer’s heart was indeed defective.
The researchers then analyzed the data they gathered from each patient to determine their healthy baselines.
In standard medicine, researchers determine baselines by taking an average across thousands of people. But while the average body temperature, for example, is around 98.6 degrees, that doesn’t mean that it’s normal for a given individual.
Some people just run hot or cold. To determine whether a patient’s temperature change might indicate illness, a doctor needs an individualized baseline.
Dr. Snyder and his colleagues worked out healthy baselines for each patient — not just for body temperature, but heart rate and balances of various proteins.
Some subjects veered from their baselines as they were struck by illnesses, the researchers found. One volunteer underwent such a shift before getting diagnosed with lymphoma.
“We were able to go back and see molecules that were clearly starting to rise months before the diagnosis and then dropped with treatment,” said Sophia Miryam Schüssler-Fiorenza Rose, an instructor in neurosurgery at Stanford who was the lead author of the study.
“We think these might be very valuable early markers of disease,” she said.
Nine volunteers developed diabetes, but they reached that diagnosis by different paths. The condition worsened in two volunteers as they gained weight, but seven developed diabetes without getting fat.
Some turned out to produce very little insulin; others produced enough insulin, but it failed to lower their levels of glucose.
“We learned that people are Type 2 diabetic in very different ways,” said Dr. Snyder.
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 diseases earlier, and treat them more precisely.
But critics questioned whether Dr. Snyder’s big-data firehouse will actually make patients healthier — or just leave them floating in a sea of uncertainty and anxiety.
“They carpet-bomb the body with tests and basically assume that the discovery of everything they hit is beneficial,” said Dr. Henrik Vogt, a postdoctoral researcher at the University of Oslo. “But there may be lots of collateral damage they don’t consider.”
Dr. Vogt, an outspoken critic of precision medicine, also noted Dr. Snyder and his colleagues did not compare the outcomes of their volunteers to people who were getting standard medical care. The extra cost and effort might not have led to comparatively better health.
“It’s hard to know what the results mean,” Dr. Vogt said.
Those criticisms haven’t stopped scientists from starting up companies that offer “deep profiles” to people who are willing to foot the bill. Dr. Snyder, for example, co-founded a company called Q, which promises “a comprehensive picture of your health — in 75 minutes or less.”
But precision medicine is proving to be a tough sell. In April, one well-financed start-up called Arivale abruptly shut down. “The cost of providing the service exceeds what our customers can pay for it,” the company announced.
Karen Meagher, a bioethicist at the Mayo Clinic who was not involved in the new study, cautioned that these are still early days for precision medicine.
She wondered if most patients could manage constant monitoring as well as Dr. Snyder’s volunteers. “Some people are going to be really overwhelmed by the technology,” Dr. Meagher said.
Dr. Vogt was even more skeptical.
“The approach is unlikely to work for people most in need — those who are poor, are barely hanging on, and have other things to worry about than monitoring themselves constantly,” he said.
Tracking the biological workings of his own body for a decade has been enlightening for Dr. Snyder, but far from a panacea.
After learning he had diabetes in 2011, he managed to keep his blood sugar levels in check for three years. In 2014, he crossed back over the line again.
“It turns out I’m slow in releasing insulin,” he said. “We can see exactly where my defect is.”
That finding led one doctor to suggest Dr. Snyder take medications that boost the release of insulin. Another recommended a drug that helps expel sugar from the body.
Five years after his second diagnosis, he still has diabetes. For now, he is trying long walks after eating instead of new drugs.
“I like to only change one variable at a time, so I can understand what is going on,” he said.