Minimal correlation but complementary diagnostic utility for plasma cell-free RNA and proteins

Proteins and RNA circulate in plasma and can offer insights into human physiology. Yet, despite their clinical importance, direct comparisons between these analytes remain unexplored. Here, we measure and compare plasma cell-free RNA (cfRNA) and protein levels for 263 children diagnosed with inflammatory diseases, specifically either Kawasaki disease (KD) or Multisystem Inflammatory Syndrome in Children (MIS-C), by RNA sequencing (n = 108 KD and n = 47 MIS-C, mean age=4.2 years) and SomaScan proteomics (n = 70 KD and n = 101 MIS-C, mean age=6.8 years). Here we show that cell-free RNA and protein levels are largely uncorrelated across samples (feature-by-sample correlation coefficient 0.052; median feature-level correlation coefficient 0.009). Nonetheless, machine learning models based on either modality distinguish KD from MIS-C with similar high accuracy (median area under the curve greater than 0.93). Analysis of KD subtypes reveals distinct cell-free RNA and protein signatures, with one group showing molecular similarity to MIS-C. These findings underscore the complementary nature of cell-free RNA and protein profiling and highlight the utility of integrating multiple plasma analytes to improve disease classification and deepen our understanding of complex inflammatory conditions. Proteins and cell-free RNA are molecules in the blood that can be measured in plasma, but it is unknown whether they contain overlapping or non-overlapping information about disease. We compared these two plasma analytes in children with Kawasaki disease and MIS-C, two serious pediatric inflammatory illnesses. We collected plasma samples and used laboratory tests to measure thousands of proteins and cell-free RNA and applied statistical and machine-learning methods to compare them. We found that protein and cell-free RNA levels were weakly related, but both can be used to differentiate Kawasaki Disease and MIS-C with high accuracy. These results suggest that combining several blood analytes may improve diagnosis and deepen understanding of inflammatory diseases. Bliss et al. compare plasma cell-free RNA and protein profiles in children with Kawasaki disease and Multisystem Inflammatory Syndrome in Children. They find that the two analytes are largely uncorrelated yet each alone classifies disease with high accuracy, revealing complementary biological information.