Abstract
Axial spondyloarthritis (axSpA) is a chronic inflammatory disease characterized by a complex interplay of molecular factors. Despite advances in understanding its pathophysiology, diagnostic delays and the absence of personalized treatment strategies remain significant challenges. This review provides a comprehensive analysis of imaging techniques and molecular approaches to improve disease characterization. Advanced imaging methods, including magnetic resonance imaging, positron emission tomography, and artificial intelligence (AI)-driven models, have enhanced diagnostic accuracy, reduced variability in interpretation, and facilitated early disease detection. In parallel, omics technologies have provided valuable insights into disease pathogenesis. Genomic studies have identified susceptibility loci beyond human leukocyte antigen B27, implicating key immune pathways such as interleukin-23/interleukin-17 signaling. Epigenomic modifications, particularly DNA methylation, play a key role in regulating gene expression in immune cells, especially within genetically predisposed loci. Transcriptomic studies have uncovered dysregulated immune pathways and revealed novel cellular players in disease pathogenesis, including CD99(+) neutrophils, natural killer cells, and microRNAs-important post-transcriptional regulators that have shown high diagnostic accuracy when assessed in peripheral blood mononuclear cells. Proteomic analyses have further contributed by identifying potential biomarkers and therapeutic targets in blood using advanced technologies, highlighting molecules such as tumor necrosis factor, FK506-binding protein-like (FKBPL), mitogen-activated protein kinase 14 (MAPK14), interleukin 7 receptor, and interleukin-23 receptor, among others. Future research should focus on combining multi-omics data with AI-driven approaches to improve biomarker discovery, optimize patient classification, and guide personalized treatments. Bridging the gap between molecular insights and clinical applications will enable precision medicine strategies, improving early diagnosis and therapeutic outcomes in axSpA.