Emily Chan
“This gives you a huge advantage. In inflammatory conditions, there’s lots of cell death. Cells are, in some cases, exploding, and their RNA gets released into plasma. By isolating that RNA and sequencing it, we can discover biomarkers for disease and backtrack where the RNA is coming from to measure cell death.”
The research team’s analysis showed distinct cfRNA signatures for different inflammatory conditions.
They even managed to develop a machine-learning model that could distinguish between KD and MIS-C with an accuracy of 98 percent.
These two illnesses can be tough to tell apart, yet they require different treatments, so the team’s results are highly significant.
The researchers also created another model that could differentiate between KD, MIS-C, viral infections, and bacterial infections. The model had an 80 percent accuracy rate in distinguishing the four types of illness.
Furthermore, cfRNA could indicate damage to specific organs that traditional clinical tests don’t show.
This is important because MIS-C can cause swelling in the heart, lungs, brain, or other organs, while KD can lead to heart attacks and cardiac aneurysms.
The new blood test involving cfRNA profiles could be life-changing. Currently, the diagnosis process of inflammatory diseases in children often requires various blood tests, a combination of clinical symptoms, and sometimes even invasive procedures.
A single blood test that can accurately distinguish between conditions and reveal organ involvement can make diagnosis faster and bring about better outcomes for patients.
Although the results are promising, the researchers noted that more work needs to be done before the test can be used in clinical settings. The study was published in the Proceedings of the National Academy of Sciences.
