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Updated: Jun 23, 2026

Using Human Differentially Expressed Gene Lists to Perform Downstream Pathway Enrichment Analysis and Target Prioritization
Published on: October 3, 2025
Gene-expression profiling in rheumatic disease: tools and therapeutic potential
Jason W Bauer1, Hatice Bilgic, Emily C Baechler
1Division of Rheumatic and Autoimmune Diseases, Department of Medicine, University of Minnesota, Minneapolis, MN 55455, USA.
Gene-expression profiling identifies disease molecular fingerprints. Validating these findings and analyzing protein pathways are crucial for clinical applications in diagnosing and treating diseases like systemic lupus erythematosus.
Area of Science:
- Genomics and Molecular Biology
- Immunology and Rheumatology
Background:
- Gene-expression profiling using microarray technologies analyzes genome-wide messenger RNA transcript levels.
- This technology is a key component of a larger pipeline, from sample collection to clinical use.
Purpose of the Study:
- To highlight the importance of gene-expression profiling in discovering molecular fingerprints of human diseases.
- To emphasize the necessity of validating findings and exploring protein-level pathways for functional insights.
Main Methods:
- Utilizing microarray technology for genome-wide gene-expression analysis.
- Validating key genes and pathways in independent sample sets using alternative technologies.
- Analyzing signaling pathways at the protein level.
- Surveying peripheral blood and purified cell populations for biomarkers.
Main Results:
- Gene-expression profiling has identified molecular fingerprints underlying human diseases.
- Studies in rheumatic diseases, including systemic lupus erythematosus, have elucidated pathogenic mechanisms through transcriptome analysis of immune cells.
- Peripheral blood serves as a valuable source for potential biomarkers.
Conclusions:
- Gene-expression profiling is a powerful tool for disease biomarker discovery.
- Validation and protein-level analysis are essential for translating transcriptomic findings into clinical applications.
- Future applications include improved diagnostics, prognostics, and targeted drug development for complex diseases.
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