Plasma Cell-free RNA Signatures of Inflammatory Syndromes in Children

• DOI: 10.1101/2024.03.06.24303645
• Publication Date: 2024-03-08T17:15:14Z
• Authors: Conor J. Loy; Venice Servellita; Alicia Sotomayor-...; Andrew Bliss; Joan Lenz; Emma Belcher; Will Suslovic; Jenny Nguyen; Meagan E. Williams; Miriam Oseguera; Michael A. Gardiner; ; ; Jong-Ha Choi; Hui-Mien Hsiao; Hao Wang; Jihoon Kim; Chisato Shimizu; Adriana Tremoulet; Meghan Delaney; Roberta L. DeBiasi; Christina A. Rostad; Jane C. Burns; Charles Y. Chiu; Iwijn De Vlaminck
• Keywords: Male; pediatrics; Adolescent; cell-free RNA; 610; Mucocutaneous Lymph Node Syndrome; 618; Machine Learning; Diagnosis, Differential; Diagnosis; diagnostics; Humans; Preschool; Child; Inflammation; Infant; COVID-19; Bacterial Infections; Biological Sciences; Systemic Inflammatory Response Syndrome; machine learning; inflammation; Virus Diseases; Child, Preschool; Differential; Female; Cell-Free Nucleic Acids; Biomarkers

ABSTRACT Inflammatory syndromes, including those caused by infection, are a major cause of hospital admissions among children and often misdiagnosed because lack advanced molecular diagnostic tools. In this study, we explored the utility circulating cell-free RNA (cfRNA) in plasma as an analyte for differential diagnosis characterization pediatric inflammatory syndromes. We profiled cfRNA 370 samples from patients with range conditions, Kawasaki disease (KD), Multisystem Syndrome Children (MIS-C), viral infections bacterial infections. developed machine learning models based on these profiles, which effectively differentiated KD MIS-C — two conditions presenting overlapping symptoms high performance (Test Area Under Curve (AUC) = 0.97). further extended methodology into multiclass framework that achieved 81% accuracy distinguishing KD, MIS-C, viral, demonstrated profiles can be used to quantify injury specific tissues organs, liver, heart, endothelium, nervous system, upper respiratory tract. Overall, study identified versatile wide