# Advancing precision medicine in axial spondyloarthritis: insights from multi-omics approaches

## TL;DR

This review discusses how combining multi-omics and AI can improve understanding and treatment of axial spondyloarthritis.

## Contribution

The paper highlights novel applications of multi-omics and AI in advancing precision medicine for axial spondyloarthritis.

## Key findings

- Multi-omics technologies reveal genetic and metabolic factors in axial spondyloarthritis.
- AI enhances analysis of multi-omics data to build dynamic disease networks.
- Integration of these approaches may lead to better diagnostics and personalized treatments.

## Abstract

Axial Spondyloarthritis (axSpA) is a chronic inflammatory disease influenced by genetic, immune, metabolic, and environmental factors, significantly impacting patients’ quality of life. Recent advancements in multi-omics technologies—such as genomics, transcriptomics, proteomics, and metabolomics—provide new insights into axSpA pathogenesis and precision medicine. These technologies reveal genetic susceptibility, immune responses, and metabolic alterations, uncovering potential biomarkers and therapeutic targets. This review explores multi-omics applications in understanding axSpA mechanisms, developing targeted therapies, and advancing precision diagnostics. It also addresses challenges in data integration and highlights the role of artificial intelligence (AI) in enhancing analysis precision and constructing dynamic disease networks. Combining AI with multi-omics could revolutionize diagnosis, personalized treatment, and clinical translation for axSpA, driving the future of precision medicine.