RNA is expelled from cells via cell death or active release, and can then find its way into blood plasma. A Cornell University-led collaboration has developed machine learning models that use these cell-free molecular RNA dregs to diagnose pediatric inflammatory conditions that are difficult to differentiate.
Cornell UniversitySep 9 2024
Inflammatory diseases are a particular threat to children because the symptoms – such as fever and rash – are generic, and the patients often get misdiagnosed. If not properly treated, MIS-C can cause swelling in the heart, lungs, brain and other organs. Similarly, KD – the primary cause of acquired heart disease in children – can lead to cardiac aneurysms and heart attack.
The findings stem from a previous collaboration that began four years ago and used next-generation sequencing to characterize the severe cases of COVID-19 and MIS-C in children that spiked during the pandemic. Initially, De Vlaminck and Loy were focused on the potential of using cell-free DNA to investigate the diseases, but they found themselves increasingly interested in cell-free RNA, because of the rich information content it provides.
Beyond developing an accurate model for diagnosis, the researchers also demonstrated that cell-free RNA sequencing can be used to quantify injury to specific tissues and organs, including the liver, heart, endothelium, nervous system and the upper respiratory tract.
Blood Cell Cell Death Children DNA Fever Heart Kawasaki Disease Liver Machine Learning Rash RNA Syndrome
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