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

Abstract

Background: 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.

Methods: 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.

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.

Conclusions: The multiomics approach rapidly identified children with bacterial or autoimmune inflammatory conditions, improving diagnostic and treatment strategies for those with presumptive septic arthritis.