# Bridging the Precision Gap in Rheumatoid Arthritis: Spatial Transcriptomics, Spatial Proteomics, and Artificial Intelligence in Precision Health

## TL;DR

This review explores how spatial omics and AI can improve personalized treatment for rheumatoid arthritis by mapping immune cell activity in tissues.

## Contribution

The paper highlights the novel integration of spatial transcriptomics, proteomics, and AI to bridge the precision gap in rheumatoid arthritis treatment.

## Key findings

- Spatial transcriptomics and proteomics reveal immune microenvironments in RA tissues.
- AI enhances the ability to identify therapeutic targets based on spatial and molecular data.
- These technologies enable precise targeting of pathogenic subpopulations in RA.

## Abstract

Rheumatoid arthritis (RA) is a chronic autoimmune disease characterized by complex immune cell associations and continuous joint damage. Personalized clinical assessment and treatment options for RA remain hindered by a precision gap due to an inability to precisely match current global treatment strategies to individual molecular and spatial disease profiles. Recent advances in spatial transcriptomics and proteomics offer unprecedented opportunities to map molecular heterogeneity and spatial heterogeneity within RA tissues by identifying immune microenvironments activated during the disease, thus enabling precise therapeutic targeting. These techniques address the precision gap in RA by identifying distinct pathogenic subpopulations and cellular niches, providing insights into the biomolecules that possess significant therapeutic responses and are involved in disease progression. This review synthesizes recent findings demonstrating how spatial omics technologies, including spatial transcriptomics and proteomics, together with artificial intelligence, are transforming precision rheumatology.