Ankylosing spondylitis (AS) exhibits marked clinical heterogeneity that is poorly captured by conventional disease-centric analyses, hindering the development of personalized therapies. We propose a symptom-centered network pharmacology framework that directly links individual clinical symptoms to their underlying molecular mechanisms and therapeutic targets. AS- and symptom-associated genes were collected from GeneCards and prioritized using centrality analysis within protein–protein interaction networks. Symptom relevance was validated using patient-derived transcriptomic datasets. Network proximity between symptom modules and FDA-approved drug targets was assessed. A refined gene set, integrating TNF-associated neighbors and highly central nodes, was subjected to pathway enrichment analysis. Disease-centric analysis yielded a restricted 18-gene core enriched mainly in broad immune pathways. In contrast, the symptom-centered network identified 145 genes associated with specific symptoms such as inflammatory back pain and morning stiffness. Key genes, including PTEN, TLR4, JAK2, NRAS, and NR3C1, were significantly upregulated in AS patients. TNF showed local connectivity but limited global proximity, while IL17A- and JAK inhibitor-related targets were absent. A refined 24-gene module revealed enrichment in interleukin- and cytokine-mediated signaling pathways. Symptom-centered network analysis more effectively captures molecular heterogeneity in AS, providing a robust framework for symptom-specific target discovery and personalized therapeutic strategies.
Choi et al. (Wed,) studied this question.