Scientists have developed a blood test that can predict whether someone is at high risk of a heart attack, stroke, heart failure or dying from one of these conditions within the next four years.
The test, which relies of measurements of proteins in the blood, has roughly twice the accuracy of existing risk scores. It could enable doctors to determine whether patients’ existing medications are working or whether they need additional drugs to reduce their risk.
“I think this is the new frontier of personalized medicine, to be able to answer the question, does this person need enhanced treatment? And when you’ve treated someone, did it actually work?” said Dr Stephen Williams at SomaLogic in Boulder, Colorado, who led the research.
It could also be used to hasten the development of new cardiovascular drugs by providing a faster means of assessing whether drug candidates are working during clinical trials.
The test is already being used in four healthcare systems within the US and Williams hopes it could be introduced to the UK in the near future. “The NHS is definitely on our radar screen, and we are talking to people about how it might work,” he said.
Whereas genetic tests can provide an idea of someone’s risk of certain diseases, protein analysis can provide a more accurate snapshot of what someone’s organs, tissues and cells are doing at any given moment in time.
Williams and his colleagues used machine learning to analyze 5,000 proteins in blood plasma samples from 22,849 people and identify a signature of 27 proteins that could predict the four-year likelihood of heart attack, stroke, heart failure or death.
When validated in 11,609 individuals, they found their model was roughly twice as good as existing risk scores, which use a person’s age, sex, race, medical history, cholesterol and blood pressure to assess their likelihood of having a cardiovascular event. The results were published in Science Translational Medicine.
Importantly, the test can also accurately assess risk in people who have previously had a heart attack or stroke, or have additional illnesses, and are taking drugs to reduce their risk, which is where existing risk prediction scores tend to fall down.
“There wouldn’t be an issue if everyone was the same. But the problem is that you can follow the treatment guidelines and some people will go back to having the same risks as a 40- or 30-year-old, whereas others are going to have another event within the next year, and they look the same from the outside,” Williams said.
“Being able to discriminate between those two people, so that you can give enhanced cardioprotective drugs to those at risk is an unmet medical need.”
SomaLogic’s test uses protein measurements to categorize people from high to low risk, as well as providing a percentage likelihood that they’ll suffer a cardiovascular event within the next four years. “If it turned out that your score was high, you would have a roughly one in two chance of an event, but the average time to that event would be just over 18 months, and the most likely event type would be death,” said Williams. “That person will need immediate enhanced cardio protection [in the form of drugs or other interventions]because those are near-term catastrophic risks.
“And the nice thing is that treatments already exist. The problem is matching them to the people who need them the most, and measuring whether they worked well enough.”
He said the test could eventually be used as a surrogate end point in clinical trials to assess how well experimental therapies were working, rather than waiting months or years for patients’ health to improve or deteriorate, which slowed down the rate of drug development.
Prof Manuel Mayr, the British Heart Foundation professor of cardiovascular proteomics at King’s College London, said: “Proteins are the building blocks of our body. This study provides measurements for a quarter of all proteins that are encoded by our genes, which has become possible because of emerging, new technologies that allow measurement of thousands of proteins and offers new opportunities to assess risk in patients.
“While this study uncovers new associations between proteins in blood and death by all causes, more research is needed to assess the potential clinical impact of using these 27 proteins, compared to current risk prediction tools for cardiovascular disease.”