What Is Health, Precisely?

Researchers are aiming to discover new signals or insights that correlate to health or disease.(Getty Images)

I was racing the clock. My task: Put nine small pegs into the equally small holes of a 3×3 grid, then take them out again. I was starting to sweat. The blood draw had been a breeze, the body composition assessment didn’t faze me, and even a tough appraisal of my episodic memory went OK. But I had met my match in this test of dexterity, which declines with age and is key to many activities of daily living. And mine, I was learning, was not great.

I was in the beta version of Lab100, a slick hybrid clinic-research center that Mount Sinai Health System in New York will officially open this year. By completing a one-hour assessment, I was gearing up to gain insights on my general health and how it’s affected by my behavior and lifestyle. And with each detail I shared, I was also becoming a single data point in the emerging field of precision health. Lab100 joins several much larger efforts – including All of Us, from the National Institutes of Health, and Project Baseline, from Google’s sister company Verily and partner institutions – in trying to develop a more nuanced picture of just how different health can look from you to me, as well as the quiet changes the body makes en route from wellness to disease.

Painting a total-continuum-of-health picture will require data – lots and lots of data. You’ve probably heard of precision medicine, which aims to better tailor treatments to a patient’s individual characteristics. Think of precision health as the front end of that effort. The big idea behind these projects is that gathering information on genetics, biomarkers and lifestyle and environmental factors from many thousands of volunteers will give researchers a trove of data that they can mine to discover better ways of spotting – and perhaps preventing – disease, while accounting for our unique differences even more precisely than before.

“What we’re hoping to do is to go from a reactive approach, when we only encounter people when they’re sick, to a more proactive, preventive approach,” says Adrian Hernandez, a cardiologist and vice dean for clinical research at Duke University School of Medicine, a Project Baseline study site and partner. Hernandez compares the vision to how smartphone apps flag upcoming road congestion. “When you see a traffic jam down the road on a map, you have choices and can take alternate routes,” he says. “We’ve got to get better in terms of saying, ‘What’s that person’s risk over a 10-year or shorter period and what are the interventions that can dramatically change that risk?’ ”

Of course, finding and addressing conditions earlier isn’t a new goal, nor is it always the case that doing so saves lives or improves health, as the overscreening controversy surrounding certain cancer tests has shown. And while these ambitious efforts to collect and analyze data may pay off with new detection and prevention strategies, questions remain about whether they will outperform our current tools – and at what cost. Managing expectations about when precision health research will bear fruit is a chief concern of its proponents. “The human body is more complicated than we think,” says Sanjiv Sam Gambhir, professor and chair of radiology at Stanford Medicine, another Project Baseline partner. “People want quicker solutions, but there are no quicker wins in health and disease.”

But given that caution, let’s imagine one precision health world that might emerge from these efforts, as envisioned by Gambhir and his colleagues in a recent Science Translational Medicine paper. Your disease risk would be estimated very early in life – even before birth – using genetics and family history. Based on those results, you’d be tracked by specific devices that capture a range of continuous health data, including familiar indicators (e.g., blood pressure), new biomarkers, environmental factors (e.g., air quality) and behavioral ones (think sleep activity or exercise levels). Some of that information would come from the kinds of wearables you’re used to (e.g., fitness trackers), but Gambhir foresees a whole new set of passive – but smart – monitors that would gather data without necessarily requiring individuals to strap them on daily.

Among the possibilities, some of which are being developed or studied: Sheets to monitor heart-and-lung function; toilets that analyze urine and stool for glucose and other biomarkers; mirrors that capture facial changes that might signal disease onset; a bra that detects early signs of breast cancer; and smartphones that spot usage patterns linked to anxiety. Those devices would “learn” your individual variation to differentiate between a random quirk and a potentially disturbing pattern. That information would feed into a health portal where data analytics suggest next steps, such as scheduling a doctor’s visit, health coaching session, treatments or tests.

New gadgets have natural appeal, but Gambhir emphasizes that they must also be accurate and reliable. Moreover, the information they provide must be predictive, actionable and not prone to false alarms that prompt unnecessary and costly follow-up tests. That will all require a lot of research, data collection and machine learning. And some of the biomarkers these devices might detect – such as molecules in urine or breath that could indicate disease – simply haven’t been discovered.

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Several precision health efforts varying in size and scope are underway. The NIH’s All of Us project, with $1.5 billion in authorized funding over 10 years, kicked off in May of 2018 with the ultimate goal of gathering genomic and other key information from 1 million Americans, allowing researchers to study that data to ask fundamental questions about health and disease. “We still don’t understand how environmental and genetic and socioeconomic and behavioral factors combine to make one person healthy and another not healthy,” says Eric Dishman, All of Us director. The project aims to develop improved treatments, yes, but also to discover new risk markers for disease and to give participants data to improve their health.

Through more than 270 planned study sites, All of Us aims to reach a more diverse group of people – in terms of race, ethnicity, income, age, sexual orientation and geography – than has historically been achieved in large, long-term, government-funded studies. (Because the project will still rely on a self-selecting group of volunteers, though, it may not truly represent the U.S. population as a whole.) As of mid-June 2018, All of Us had collected blood and urine samples from more than 34,000 people who also granted access to their electronic medical records. Soon participants will be able to provide researchers with information from their own wearable devices; the next step is to begin analyzing the genes of those who opt into that part of the program. (Achieving the project’s goals of sequencing the genomes of participants will take time – for starters, it will require many more sequencing machines than are currently available in the U.S.)

Project Baseline is also trying to capture a more comprehensive picture of human health by recruiting 10,000 participants who visit sites at Duke, Stanford and elsewhere. Launched in 2017, the study is collecting information through health tests, wearables (such as a special watch equipped with sensors not available for sale to the public), and app-based health diaries. Researchers will comb those datasets to ideally discover new signals or insights that correlate to health or disease. Scarlet Shore, the initiative’s product manager, says that Verily hopes the project will expand, either virtually or with more physical sites.

Not everyone is convinced that these large-scale data-gathering efforts will pay off with big improvements in health. “The question I’d ask is, ‘What hole is being filled? What are we attempting to solve here?’ ” says Nigel Paneth, a professor of epidemiology and biostatistics and of pediatrics and human development at Michigan State University’s College of Human Medicine. There’s already significant opportunity to change health outcomes by addressing societal issues, he says. In the U.S., for example, an individual’s ZIP code may be as important as his or her genetic code for health. “Those with the lowest income and who were least educated were consistently least healthy,” concluded a 2010 paper published in the American Journal of Public Health. Moreover, any new biomarkers would have to improve on the pretty high levels of risk prediction we get from factors such as body mass index, cholesterol and blood pressure, Paneth says. “Strong signals don’t take a lot of data to reveal,” says H. Gilbert Welch, a professor of medicine at the Dartmouth Institute for Health Policy and Clinical Practice.

As for the future vision of monitoring constant streams of data from healthy people? The more health information that’s gathered, the more likely it is that things will pop up that are outside the “normal” range – even if they don’t signal disease, Welch notes. (Gambhir counters that knowing a person’s serial measurements over time will lower the chance of false positives, however.)

Leaders of these precision health projects must also wrestle with what data should be returned to research participants – and how. Consider genetic-risk information, which isn’t usually assessed in healthy people without a specific reason, such as having a strong family history of certain cancers or other diseases.

The American College of Medical Genetics and Genomics, or ACMG, has a list of potentially harmful gene variants that, if discovered incidentally, it recommends people be told about, as they both carry significant risk of health problems and could potentially be mitigated. (Examples are variants tied to diseases including breast and ovarian cancers, the heart-rhythm disorder Long QT syndrome and aortic aneurysm.) Statistically, 1 to 2 percent of All of Us participants will have those variants, Dishman says, and a pilot project starting this year will help determine how best to return that information. That means figuring out how to provide genetic counseling or other health care to people who may not have a doctor, he says. Project Baseline, for its part, has a committee of experts working to determine what information should be shared.

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Separate from those efforts, at Pennsylvania’s Geisinger health system, the MyCode Community Health Initiative, a research project, has registered more than 200,000 participants since 2007 who’ve agreed to have their DNA sequenced. (Sequencing began in 2014.) The information is stored for research, but Geisinger has also notified nearly 600 participants so far whose sequencing turned up risk-carrying variants. Geisinger is taking a conservative approach based on ACMG’s recommendations, says its executive vice president and chief scientific officer David H. Ledbetter. As more evidence on the role of additional genes emerges, he expects to have reportable information for 5 percent of participants in the next few years, and 10 percent in the next five to 10 years. That, he says, has “profound health implications.” (In May of 2018, Geisinger announced it will start a 1,000-person pilot project to incorporate DNA sequencing into standard clinical care.)

For now, most MyCode participants are like 75-year-old Philip Jewell, who signed up hoping researchers could ferret out useful information in his DNA. “I had throat and neck cancer. My daughter died of breast cancer. I did this not for ourselves, but to add to their studies. Maybe they can find something.”

Lab100 won’t return genetic information to its initial participants, though with consent, researchers can use that data. But participants will pay an as-yet-undetermined fee for feedback from their assessment, which is intended to complement (not replace) usual health care visits and includes questionnaires on medical and family history, nutrition, physical activity and sleep. At each station, information is collected: bloodwork, body composition, the results of five different cognitive tests, grip strength, balance and dexterity metrics, among others. Patients sit down with a provider at the end of the hour – as I did – facing an array of screens to discuss what lifestyle steps they could take to improve health.

Additional information is gathered that isn’t ready for prime time but feeds into research, says David Stark, who heads up Lab100. For example, the balance station collects data to see if a smart TV might someday passively collect those same insights. (Poor balance is linked to falls.) Videos of patients’ dexterity tests may be correlated with their outcomes to see if tremors can be predicted or detected early. And overall outcomes will be tracked to see if this type of personalized assessment improves health.

It’s not clear whether all this data-gathering will ultimately provide new knowledge about what lifestyle changes we should be making, or how to put them in motion. We already know many of the things we should be doing. A recent study confirmed the obvious: Avoiding smoking, maintaining a normal-range BMI, getting at least 30 minutes of daily physical activity, eating a high-quality diet and going easy on alcohol were associated with an extra 12 years of life for men and 14 for women. But Dishman says that even these known lifestyle factors need more nuanced research. “Exercise ends up being very effective for certain people and not for others,” he says. “We’re going to become more predictive about these things, so you can focus on the things that will matter for your body, depending on what it’s been exposed to and your genetics.”

Even when we know the route to health, the irritating reality remains: It’s really hard to change our behavior. At Lab100, you learn how your test results stack up against people of similar age and gender, which might prod the competitive into action. Not only did I discover that my fine-motor skills are lacking, but my balance was comparatively average. That has motivated me to stand on one leg and close my eyes when I brush my teeth, but I don’t know how long I’ll keep it up or if improving my balance will boost my health. What is clear? Opportunities to amass heaps of data about ourselves will only expand. Whether that data flood will buoy our health remains to be seen.

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