Say the words “personalized medicine” to people from various walks of life, and you’re likely to get one of about four different reactions.
A. “Personalized medicine? What’s that?” (Usually spoken by 99 percent of patients.)
B. “Personalized medicine will bankrupt the country with expensive new diagnostic tests, and overrated targeted drugs.” (Usually spoken by health economists.)
C. “Personalized medicine is overhyped, a load of bunk.” (Usually spoken by grizzled pharma industry vets who remember the genomics crash of a decade ago, and have a financial interest in preserving the status quo.)
D. “Personalized medicine will revolutionize healthcare, moving us away from reactive sick-care and more toward predictive and preventive strategies focused on wellness.” (Usually spoken by the subset of true believers in science and the biotech industry.)
You can make arguments, buttressed with data, to support any of the last three positions. But none of these positions quite captures the truth. We are in the early days of the personalized medicine movement, and don’t know how the story will unfold. As a journalist who’s followed many different threads of this story for the last decade, I keep getting the feeling that we’re moving further away from one-size-fits-all medicine, and more toward treatment based on extremely detailed molecular readouts on your state of health or disease. People may have snickered at Internet pioneer Larry Smarr and his friends in the “Quantified Self” movement for being weird a couple years ago, but I can easily envision people jumping on this bandwagon sometime not too far out.
I was fascinated this past week when I had a chance to talk with Mike Snyder, a geneticist who has turned himself into a poster child for personalized medicine through his work at Stanford University. After talking with him for about a half hour last week, I hung up thinking his experience today could seem mainstream in another 10 or 20 years.
Snyder, for those who are unfamiliar, was the guy at the center of an important paper published in the journal Cell back in March. This paper described how researchers sequenced Snyder’s genome, and then really got rolling in their quest to understand his biochemical state of being at 20 different snapshots in time over a 14-month period. The scientists took blood samples from him when he was feeling fine, and a few times when he was sick with viral infections. They then ran the samples through instruments that captured an extremely detailed look at 40,000 molecular parameters in his blood. These were metabolites, proteins, RNA transcripts, self-directed antibodies. This hard-core genomic, transcriptomic, metabolomic and proteomic approach (which the scientists called an integrative personal ‘omics profile) could have been just a demonstration of technological overkill, offering very little information that could lead anyone to make better decisions about their health.
But that’s not what happened. It turned out that the results, surprisingly, showed this healthy white guy in his mid-50s was at high risk of getting Type 2 diabetes—which if it’s not controlled, it can lead down the path to blindness, amputations, stroke, or heart attack.
At the time the molecular analysis revealed this trend, it was hard to believe. Snyder had no family history of the disease, and most everybody in his family is thin. His genome said he was at low risk of obesity, and at a shade under 5-foot-10, and 160 pounds, Snyder’s general practitioner thought the idea of him becoming diabetic was far-fetched.
But just as the pan-‘omics tests had predicted, researchers saw over time that something was amiss with Snyder’s ability to control his blood sugar—especially, and oddly, when he had viral infections. When looking at two traditional blood measurements of diabetes—blood sugar concentration levels and hemoglobin A1C counts—both of those numbers progressively climbed into worrisome territory. As the sweeping ‘omics-driven analysis had predicted, Snyder was diagnosed with diabetes.
He remembers the day that word came, April 11, 2011. He decided it was time to change his health habits.
“Up until that point, I had been eating lots of sweets. I’d have ice cream all the time after dinner. It really was a pretty bad diet,” Snyder says. After the diagnosis, it took him six months to get his blood sugar levels back to normal. “I completely cut out all dessert, and have had one bite of wedding cake since,” he says. That one exception came when one of his postdocs got married, he says.
That might be how anybody in this situation would react to a diabetes diagnosis, with enough self-discipline. But what makes this story even more interesting is that when Snyder changed his diet, and ramped up his daily exercise routines, he could see how his biochemical profile changed when his behavior changed. The scientists have kept looking at measurements of 40,000 different molecules in Snyder’s blood, before, during, and after his diagnosis. Suddenly, you can see not only that bicycling 40-50 miles a week instead of 20-30 miles has helped him lose 15 pounds. You can also see the molecular warning signs of diabetes have returned roughly to normal, along with his blood sugar and hemoglobin A1c scores.
“This study is a landmark for personalized medicine,” Eric Topol, a professor of genomics at the Scripps Research Institute in San Diego, told the New York Times.
Months later, Snyder reports that even though he’s not technically cured of diabetes, he’s been able to keep it in remission through these behavior changes, without taking any drugs. That doesn’t mean he’s completely in the clear. He knows his risk will go up again as he gets older. He also knows from his genome that if he gets diabetes, and needs to take the generic drug metformin, he should take a lower-than-usual dose. But most importantly, because he’s a scientist willing to make himself a laboratory subject, he’s more likely to catch diabetes or some other ailment at an early and treatable stage.
After giving 50 samples to his research team over the past 34 months, Snyder says he expects much more interesting data to come. This wasn’t just a case of a single paper which generates some buzz, maybe a few new research ideas, and then fades into the ether. It’s really just the first step in a long-range study of Snyder at the molecular level, and what that means for his health. “I’m sure I’ll be doing this the rest of my life,” Snyder says.
No question, this is all still very much at a research stage. This kind of hard-core data-gathering approach is many years away from being reduced to practical use, or lending itself to new products for diagnosis or treatment. The Stanford team used a next-generation gene sequencing machine, and two different mass spectrometers, which are expensive pieces of equipment. The first study of Snyder’s ‘omics profile generated 50 terabytes of data, and he says the next phase of research will probably double the amount of data. It cost tens of thousands of dollars, and he doesn’t really have a full accounting that includes computer analysis and staff time. And the costs keep recurring. While the team only had to sequence his genome once—because his unique DNA signature doesn’t change over time—the battery of other ‘omic tests will probably cost at least $2,000 each time he gives blood, just for the chemical reagents required, not counting costs for analysis and staff time.
Still, every day as the costs come down, more research ideas become feasible. Snyder’s story, which got a fair bit of media attention in the spring, has inspired a number of volunteers who want to help. The Stanford team is broadening the scope of their personalized medicine vision by looking to analyze the microbes in Snyder’s gut—the microbiome—and his epigenome, which will show how his genes get expressed. Those extra analyses will add cost, but Snyder says he believes it will be soon be possible to capture a simple version of the molecular analysis for maybe $600 each time he gives blood. Once the costs get down into that range, it will be feasible to do one continuous study of 10 volunteers like Snyder, who are willing to subject themselves to all these regular blood draws, when they’re feeling well and when they’re not.
Beyond that study, Snyder says he and his team are exploring a 250-person study of people at high risk for diabetes, or who are pre-diabetic. The idea will be to take these regular personal ‘omic snapshots, connect it with a detailed picture of the person’s environmental stimuli (particularly their diet/exercise habits), and watch over a 5-year period to see whether certain biochemical pathways are truly predictive of whether a person will get diabetes. That kind of study would be clearly more informative to the practice of medicine than just one man’s experience, which could be a fluke.
Certainly, there are going to be experiments that fail, or just give us vague ideas of where an individual’s health is headed. People, being human, won’t always follow their doctor’s advice, even if they know they can stop themselves from getting diabetes. Insurance companies may use this data to their own advantage, and to the disadvantage of the individual. (In fact, Snyder says his life insurance premiums went up once he told his insurer about his diabetes diagnosis. That action is perfectly legal, he notes, because life insurance firms aren’t subject to the Genetic Information Non-Discrimination Act of 2008.)
But I do believe we’re going to learn amazing things that will change our behavior. And I think that within the next decade, a whole lot more people in the U.S. will have the same kind of visibility Snyder got into his individual health, because it really ought to save the whole system money if it scares people into leading healthier lives. The 99 percent of patients will no longer say “Personalized Medicine? What’s that?” People will want this information, they’ll demand it, and many will act on it. Some of today’s skeptics will turn into believers, and they’ll find ways to profit from this movement, by helping people prevent bad things from happening. As Snyder puts it, “This is what personalized medicine is all about. You can look at your altered biochemical state, and you can change things when you catch them early. It’s the name of the game.”