Your doctor still does a blood test to check your cholesterol and gauge your risk for heart disease by considering traditional risk factors (like smoking, diabetes, blood pressure) — an evaluation that has not changed in decades.
But a high-risk number alone is not enough to tell accurately whether you will suffer from heart disease. It just reflects your risk compared to population-level averages. In other words, not every person with elevated "bad" cholesterol will have a heart attack, so how can doctors determine who truly needs to give up the cheeseburgers and who doesn't?
Now, an emerging area of research may unlock some real-time answers. For the first time, as reported in the journal Nature Medicine last week, scientists have measured thousands of proteins from a single blood test to assess many individualized health conditions at once, including liver and kidney function, diabetes risk, body fat, cardiopulmonary fitness, and even smoking and alcohol consumption. Proteins can give a clear snapshot of how your body is faring at any given moment, as well as a sneak preview at what diseases may be lurking under the surface.
"Years from now," says study co-author Peter Ganz of UCSF, "we will probably be looking back on this paper as a milestone in personalized medicine."
We spoke to Ganz about the significance of this milestone. Our interview has been edited and condensed.
Is this the first study of its kind?
Yes, it is. This is a study where we measured 5,000 proteins at once to look for patterns that could either predict the risk of future diseases or inform the current state of health. Previous to this, people have measured typically one protein at a time, and some of these individual proteins have made it into clinical practice.
An example would be a protein called C-reactive protein, which is a measure of inflammation and is used sometimes in cardiology to predict the risk of future heart attacks. But what's really new is this scale. We wanted to get away from just focusing on one problem that the patient may have at a time, whether it's heart disease or kidney disease, and by measuring a much greater number of proteins, the hope is that we could inform the health of ultimately just about every organ in the body or every tissue. It's a step forward for what I would call "a one-stop shop."
Three things get me excited about this. One is the convenience for the patient of a single test to determine many different diseases. The second thing is the healthcare cost savings. We estimated what the cost would be to get these 11 healthcare measures that we reported on using traditional testing and the cost was upwards of 3,000 British pounds. And even though I don't know for sure what the cost of the protein tests would ultimately be, [it could come down to about $50 to $100].
The last thing is that the measurement of proteins is part of what people have called personalized medicine or precision medicine. If you look at risk factors across the population, it may not apply to individuals. In contrast, proteins are downstream of risk factors. So proteins actually tell us whether the traditional risk factors have set in motion the necessary machinery to cause disease. Proteins are the worker bees that regulate what the human body does, and so if you can find some anomalies in the proteins, that may inform us if a disease is likely to be ongoing even in its earliest stages.
Does protein testing have advantages over genetic testing for predicting future health risks?
The problem with genomics is that genes usually don't take care of the environment. It's a blueprint, but your blueprint has no idea what you will be exposed to during your lifetime in terms of the environment and lifestyle that you may choose and medications that you may be on. These are things that proteins can account for. I'm very excited about personalized medicine through proteins as opposed to genes because you get both the nature and nurture as opposed to genomics, which only gives you nature but doesn't account for anything else.
Proteins can also be tracked over time and that's not something you can do with genes. So if your behavior improves, your genes won't change, but your proteins will.
Could this new test become a regular feature of your annual physical?
That's the idea. This would be basically almost a standalone test that you could have done every year. And hopefully you wouldn't need other tests to complement this. This could be your yearly physical.
How much more does it need to be validated before it can enter the clinic and patients can trust the results?
This was a proof-of concept study. To really make this useful, we need to expand from 11 measures of health to a hundred or more health insights, to cover the whole body. And we need to expand this to all racial groups. Three of the five centers in the study were European – all Caucasian – so it's one of our high priorities to find groups of patients with better representation of minorities.
When do you expect doctors to be routinely giving this test to patients?
Much closer to five years than 20 years. We're scaling up from 11 disease states to 100, and many of those studies are underway. Results should be done within three to five years.
Do you think insurance will cover it?
Good question. I have been approached by an insurance company that wanted to understand the product better – a major insurer, with the possibility that this could actually be cost saving.
I have to ask you a curveball -- do you think that the downfall of Theranos will make consumers hesitant to trust a new technology that relies on using a single blood sample to screen for multiple health risks?
[Laughs] You're not the first person to ask me that today. I actually got a call from Elizabeth Holmes [in 2008 when I was at Harvard]. I met with her for an afternoon and met her team two more times. I gave them advice that they completely disregarded.
In many ways, what we do is diametrically opposite to Theranos. They had a culture of secrecy, and what we do is about openness. We publish, like this paper in Nature Medicine, to show the scientific details. Our supplement is much longer than the typical academic paper. We reveal everything we know. A lot of the research we do is funded by [the National Institutes of Health], and they have strict expectations about data sharing. So we agree to make the data available on a public website. If there is something we haven't done with the data, others can do it.
So you're saying that this is not another Theranos.
No, God forbid. We hope to be the opposite.
Scientists have been using MRI images (like the ones pictured here) to train artificial intelligence to detect cancers earlier and with more accuracy. Here, MIT's AI system, MIRAI, looks for patterns in a patient's mammograms to detect breast cancer earlier than ever before. news.mit.edu 
