Joint fluid multi-omics improves diagnostic confidence during evaluation of children with presumed septic arthritis.

An accurate diagnosis of septic versus reactive or autoimmune arthritis remains clinically challenging. A multi-omics strategy comprising metagenomic and proteomic technologies were undertaken for children diagnosed with presumed septic arthritis to advance clinical diagnoses and care for affected individuals. Twelve children with suspected septic arthritis were prospectively enrolled to compare standard of care tests with a rapid multi-omics approach. The multi-omics combined bacterial 16S rRNA metagenomics, single cell transcriptomics, and proteomics on knee joint fluid specimens. The diagnostic value of the multi-omics was ascertained relative to standard of care culture and PCR-negative results. Ten children with suspected primary septic arthritis and two with acute hematogenous osteomyelitis (AHO) diagnoses were assessed. Joint fluid bacterial cultures were positive for 6/12 (50%) patients, consistent with elevated inflammatory markers (IL-4, IL-6, IL-17A, TNF-a, etc.). Metagenomic bacterial sequencing results were 100% concordant with the culture results. Six patients were culture- and PCR-negative. Multiomics analyses of the 6 culture negative patients established that 2/6 culture-negative children had inflammatory arthritis with potential Juvenile idiopathic arthritis (JIA) and 1 had post-Streptococcal Reactive Arthritis. The children without any bacteremia had autoantibodies (IgGs) in the joint-fluid targeting several nuclear antigens (i.e., dsDNA, histones, Jo-1, scl-70, Ro/SS-A, SmDs, CENP-A along with non-nuclear antigens i.e. Albumin, Collagens, Myosin, Laminin, etc. Single cell transcriptomics confirmed an abundance of CD4+ follicular helper T (Tfh), CD8 + T cells and B cells in the autoantibody positive subjects. The combination of 16S DNA sequencing (p = 0.006), cytokine assays (p = 0.009) and autoantibody profiling (p = 0.02) were significantly distinct between those children with and without infections. This improved the diagnostic confidence for 9 of 12 (75%) children, key for treatment decisions. The multiomics approach rapidly identified children with bacterial or autoimmune inflammatory conditions, improving diagnostic and treatment strategies for those with presumptive septic arthritis.