Stanford symposium: the potential of smartphones to better understand diseases, including ME/CFS
“We think smartphones will be the most important health tool in future”, said Dr Michael Snyder at the recent Stanford ME/CFS symposium. Snyder heads up the Stanford Centre for Genomics and Precision Medicine, as well as the Genetics Department at Stanford University.
His presentation highlighted the potential of technologies to monitor health and better understand diseases – including ME/CFS.
Snyder’s work on personal, data-driven medicine kicked off with a landmark paper in 2012 (which wasn’t covered in his talk). This revealed insights from deep molecular profiling over 14 months of a single person – Snyder himself.
The study tracked over 40,000 different biological molecules and integrated the findings with data from clinical tests and other sources. This is in addition to analysing Snyder’s full genome sequence.
From data to diagnosis
The study team’s analysis uncovered extensive changes in biological pathways over time, both when Snyder was healthy and when he was sick. But the standout finding was spotting diabetes as it developed in Snyder.
Snyder had no family history of diabetes, nor any lifestyle factor such as carrying too much weight. Even so, the genome analysis indicated he had a genetic risk of type II diabetes. And after one viral infection, his blood glucose levels ramped up to much higher levels than before the infection: it looked like he might have developed by diabetes. Snyder had no obvious signs of the illness, but a visit to the doctor confirmed that he did indeed now have type II diabetes.
Prompt detection of the disease the moment it developed gave Snyder the chance to act fast. And he has been able to manage his illness through dietary and lifestyle changes, and without needing any medication.
A second study showed this early detection was no one-off. Taking a similar approach, Snyder and his team made over 50 discoveries of significant health problems, including heart problems, a blood cancer and two precancerous conditions, among the 109 people studied. Most cases involved early detection of disease before symptoms had even started.
Taking it to the masses: the shift to wearable devices
The results were impressive but depended on a large budget and access to a state-of-the-art lab. Snyder wondered if a simpler approach would work.
The expanded study had included data from wearables, such as Fitbits, tracking a range of factors including physical activity, heart rate and skin temperature. Could wearables alone provide useful information about health?
So, Snyder began tracking himself with wearables. At one point in his talk, he held up his arms to show he was manacled with wearables devices. He said that even his ring was actually a biosensor. To top it all, he produced a radiation monitor from his pocket.
Snyder was able to make important insights about health and sickness analysing data from wearables, much as his first study had done using molecular data.
Spotting sickness at altitude
He noticed something curious. Whenever Snyder took a flight there was a marked drop in the amount of oxygen that his blood was carrying, but it bounced back afterwards. ( It turns out that cabin pressure is a little below atmospheric pressure, and this means the air carries a little less oxygen, so the blood picks up less oxygen).
While this might seem to be just a curiosity, on one flight from Germany to Norway Snyder noticed that his blood saturation fell more than usual and didn’t bounce back in the normal way on landing.
Not long after he began to feel unwell and Snyder had a sudden realisation about what was probably happening. A couple of weeks earlier he had been putting up a fence with his brother who lives in rural Massachusetts, where most ticks carry the bacteria that cause Lyme disease, Borrelia Burgdorferi. Snyder thought he had been bitten by a tick and been infected.
Suspecting this was the case, he found a doctor in Norway and a blood test confirmed that, yes, he did have an infection (though not what type of infection). He was treated with antibiotics and made a good recovery.
On his return to the US, a blood test showed that he had been infected by the Lyme-disease bacteria. But his blood samples from a little earlier showed no sign of it, indicating that this was a new infection.
Just as with molecular profiling in his first study, wearables had effectively detected an illness before Snyder was even aware of it himself.
Broadening out
Snyder had also spotted that when he got Lyme disease, his heart had also been a little higher than was usual. Maybe, he had thought, this could be used more generally to detect infections.
That was the case: there had been the same pattern of increased heart rate increase during two previous infections. And wearable data from other people (presumably the study of 109 people mentioned earlier) showed a similar pattern. This had potential.
The power of the personal approach
In each case, the differences were subtle and could only be detected by looking at the data for each person, establish their normal pattern, then measuring slight deviations from this.
Snyder is creating an app with a personal dashboard (see below), one that would show what was changing and significant for each person.
The big plus of wearables is they provide real-time continuous data and, with the right analysis, this can spot whatever happens for reach individual as it happens. This is helpful for individuals as well as researchers.
Mike Snyder’s ME/CFS studies
Snyder revealed that his group was working with Ron Davis on an ME/CFS study. His group have already taken samples from 300-plus families – more than a thousand people in total. But, unfortunately, he gave no more details than that.
The Good Day/Bad Day study
Snyder said they are planning a wearables study on Lyme disease. The Lyme study will ask patient to report on an app when they have a good or a bad day – then try to identify what triggers the bad day, from each patient’s data. They hope this might identify what triggers bad days for Lyme patients.
Snyder said that they are working on a modified approach with a substantial delay so that it can be used to identify triggers of post-exertional malaise in ME/CFS.
The future: how wearables could benefit people with ME
It is still early days, but it strikes me that wearables have the potential to help people with ME in several important ways:
1. We still don’t know the underlying problem in ME/CFS. Real-time tracking of activity and biological measures such as heart rate add an extra dimension to research, and that could help to reveal what’s going wrong.
2. The good day/bad day study could spawn an app that would help warn people with ME when they are heading for PEM – before we even realise there is a problem.
3. Hard data carries the potential to make an invisible illness visible. Doubting doctors might view ME/CFS differently if they could see how physical activity triggered later PEM. Perhaps they would be even more convinced if it turns out there are also changes in biological measures, such as skin temperature and heart rate.
Mike Snyder talked about the promise of wearables to transform health care and understanding of diseases. If things work out, this will could spark a health revolution. And this one should include people with ME.
Image credits: Feature image, unknown provenance (please contact me if it’s yours); all other images taken from Dr Michael Snyder’s presentation at the 2019 Stanford Symposium on the Molecular Basis of ME/CFS.
4 thoughts on “Stanford symposium: the potential of smartphones to better understand diseases, including ME/CFS”
Very interesting: it underlines our frustrations as ME patients when we keep getting told that various test results are normal. What is actually meant is that the readings are within the wide variations found in the population in general. What this research also is suggesting is that it would be useful to carry out basic blood tests when folk are healthy, so that we know what is truly normal for them.
while doing graded exercise I used a fitbit and also kept a separate diary with my level of fatigue. I pretty soon realised that there was a clear correlation between rises in RHR and fatigue. It’s now one of my early warning signals, along with other physical and mental symptoms. Brilliant idea!
Interesting that resting heart rate does it. Mike Sneijder said they were looking at using resting heart rate increases to detect infections – but he added that he felt heart rate during a fixed activity, such as walking, might be a better measure
Nice for you to highlight this Snyder work! It was striking in the simplicity of the measurements made but they will provide powerful data (over time) that clinicians rarely see. I too have an elevated resting HR on a bad day – those days when it takes great effort to lift your head off the pillow. It suggests an ongoing illness process vs. an “overtraining” response seen in athletes.
This is exactly why I can’t fly anymore. The headaches are too bad with the low pO2.
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