NEW YORK – A team led by researchers from the University of California, San Francisco; the University of Cambridge; and Boulder, Colorado-based proteomics firm SomaLogic has demonstrated the potential of large-scale protein measurements to provide health information, including identifying patients at risk of developing certain diseases.
In a study published Monday in Nature Medicine, the scientists used SomaLogic's aptamer-based proteomic platform, called SomaScan, to measure the expression of 5,000 proteins in plasma samples from roughly 17,000 patients. They then applied machine learning to this dataset in an effort to identify protein profiles that correlated with different health measures and disease risks.
The researchers built protein panels for 11 different health indicators: liver fat, kidney filtration, percentage body fat, visceral fat mass, lean body mass, cardiopulmonary fitness, physical activity, alcohol consumption, cigarette smoking, diabetes risk, and primary cardiovascular event risk.
They found that their protein models outperformed existing clinical methods for predicting liver fat, percent body fat, and lean body mass. For predicting conversion from pre-diabetes to diabetes within 10 years, the protein test had an accuracy of 67 percent compared to 61 percent for an oral glucose tolerance method. The protein test also predicted primary cardiovascular events within five years with a C-statistic of .66, compared to .65 for the 2013 American College of Cardiology/American Heart Association atherosclerotic CV risk score.
Protein models were also able to distinguish between subjects who drank more or less than 14 units of alcohol per week and between smokers and non-smokers with accuracy rates in the 80 percent range.
The researchers were not able to find protein profiles that predicted body weight five years in the future or proteins that predicted macronutrient intake.
The models used between 13 and 375 proteins, with a total of 891 different proteins used across all of them. While in many cases they offered only a modest improvement over existing measures, the study authors suggested that the protein tests, which require only a blood draw, offer an advantage in terms of cost and convenience that could "add value in overcoming the incomplete utilization of risk calculation in primary care."
The findings, the authors wrote, suggest that it is "conceivable that, with further validation and the potential for expansion of the number of tests, a comprehensive, holistic health evaluation using a battery of protein models derived from a single blood sample could be performed."
The next step, they wrote, is to test the protein models they developed "under research conditions in real-world healthcare systems."
In September, SomaLogic began commercially offering laboratory-developed tests on the SomaScan platform for risk of cardiovascular events, heavy drinking, aerobic fitness, the presence of excess liver fat, and percent body fat and lean tissue for an initial price of $199.