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Updated: Mar 29, 2026

Spatial Profiling of Protein and RNA Expression in Tissue: An Approach to Fine-Tune Virtual Microdissection

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Published on: July 6, 2022

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

Maliha Mashkoor^1,2, Shihua Zhang^2,3,4,5, Allan Stensballe^1,6

¹Department of Health Science and Technology, The Faculty of Medicine, Aalborg University, 9000 Aalborg, Denmark.

|March 28, 2026

Summary

This summary is machine-generated.

Spatial omics technologies like transcriptomics and proteomics are revolutionizing rheumatoid arthritis (RA) treatment by mapping disease heterogeneity. This enables precise targeting of immune cells and biomarkers for personalized rheumatology care.

Keywords:

artificial intelligence large language models machine learning multiomics proteomics rheumatoid arthritis spatial omics transcriptomics

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Area of Science:

Rheumatology
Immunology
Genomics
Proteomics
Artificial Intelligence

Background:

Rheumatoid arthritis (RA) is a chronic autoimmune disease with complex immune cell interactions causing joint damage.
Current RA treatments face a precision gap, limiting personalized clinical assessment and treatment strategies.
Understanding molecular and spatial disease profiles is crucial for effective RA management.

Purpose of the Study:

To review recent advances in spatial omics technologies for RA research.
To highlight how these technologies address the precision gap in RA treatment.
To explore the integration of spatial omics and AI in precision rheumatology.

Main Methods:

Spatial transcriptomics to map molecular heterogeneity within RA tissues.
Spatial proteomics to identify immune microenvironments and cellular niches.
Integration of artificial intelligence for data analysis and interpretation.

Main Results:

Spatial omics identify distinct pathogenic subpopulations and cellular niches in RA.
These techniques reveal immune microenvironments activated during RA pathogenesis.
Biomolecules with significant therapeutic responses and disease progression roles are identified.

Conclusions:

Spatial omics technologies offer unprecedented opportunities for precise therapeutic targeting in RA.
These advancements are transforming precision rheumatology by providing detailed molecular and spatial insights.
The integration of spatial omics and AI promises more personalized and effective RA treatments.