Systems Biology of Metabolic Dysregulation in Ankylosing Spondylitis Using scRNA-Seq Data

Abstract

Ankylosing spondylitis (AS) is a prevalent autoimmune disorder that primarily affects the spinal joints, leading to chronic pain. Defining immune cell programs that contribute to AS is essential for the discovery of translational targets. Because immune function depends on metabolic state, we analyzed single-cell RNA sequencing data from peripheral blood mononuclear cells (PBMCs) of patients with AS and healthy controls (HCs), and constructed genome-scale metabolic models for each immune cell type to quantify differences in pathway activity and reaction fluxes between diseased and healthy conditions. Across datasets, AS showed consistent metabolic reprogramming, with increased flux through purine metabolism, fatty acid degradation, and glycolysis in CD14 monocytes and T cell subsets, including CD4 memory, CD4 naive, and CD8 T cells, indicating coordinated shifts in energy production and biosynthetic demand. To extend these findings, we constructed cell-type-specific protein–protein interaction networks and evaluated differential connectivity. We identified 63 rewired protein hubs across nine immune cell types. RPS11 emerged as a central hub linked to translation and prior evidence of AS pathogenesis. This integrative systems biology approach connects cell-type-specific metabolic alterations with rewired interaction hubs in an accessible clinical compartment, suggesting that PBMC-based multiomics signatures may support future biomarker development and therapeutic prioritization in autoimmune diseases.