Joshua Sharp stood before a simple analogy—a ball of yarn sprayed with paint—to explain one of the most promising breakthroughs in early disease detection. The University of Mississippi pharmacology professor and his team have just unveiled technology that can visualize how proteins fold and interact within blood samples, potentially revealing signs of disease before a person ever feels sick.
Most medical diagnostics work by counting. A doctor looks at hemoglobin A1C levels during your annual physical to understand glucose control, or measures quantities of specific molecules to diagnose illness. But Sharp and his colleagues discovered something crucial: for many diseases, the earliest warning signs aren't about how much of a protein exists—they're about what that protein is actually doing, how it's shaped, and how it's interacting with other molecules in the body.
This distinction matters enormously for conditions like Type 1 diabetes and traumatic brain injury, where structural changes in proteins may precede any noticeable symptoms. "In order to work, proteins have to form these intricate, folded, three-dimensional structures, and these three-dimensional structures actually do the chemistry that life depends on," Sharp explained. The question became: how could researchers see those three-dimensional changes in living tissue?
The technology, called radical footprinting, uses a chemical reagent and UV light to mark protein structures in blood samples from diseased and healthy subjects. When a protein is exposed to this process, its external surfaces get marked—like spray paint on that ball of yarn. Researchers can then unwind the protein and map exactly which parts were on the outside and which were hidden inside, revealing its precise three-dimensional shape. This is the first time scientists have been able to examine changes in protein structures across many different proteins simultaneously in a clinical blood sample.
The results, published in Nature Communications by Sharp, UC San Diego chemistry professor Lisa Jones, and UM associate professor James Stewart, showed the technology can detect structural changes in disease states. In mice with diabetes, they observed alterations in complement activation and iron handling that showed up as protein shape changes before traditional quantitative markers would flag them. "By capturing how protein structure changes in disease states, such as the complement activation and altered iron handling we observed in diabetes, we can begin to identify structural biomarkers that may appear earlier than traditional biochemical markers," Stewart said.
The potential applications are profound. Sharp's team is already working toward a simple blood test that could screen children for early signs of Type 1 diabetes—early enough that preventative treatment might actually help prevent the disease entirely. They're also exploring whether the same approach can improve diagnosis of traumatic brain injuries, a condition notoriously difficult to confirm with existing tools.
For now, the technology is still in development. But the vision is clear: a future where blood-based tests catch disease at its structural roots, before symptoms emerge, before damage accumulates. "The long-term impact is the potential for more precise and earlier detection of disease because this approach allows us to determine whether that protein is functioning normally or has been structurally altered by disease," Stewart said. That shift—from counting what's there to understanding what's changing—could transform how we diagnose, monitor, and treat disease.