GeneHarmony: Mapping Shared Genes in Autoimmune Disease

Autoimmune diseases such as Sjögren’s Disease (SjD), Rheumatoid Arthritis (RA), and Systemic Lupus Erythematosus (SLE) present overlapping clinical and genetic features, but remain poorly understood at the molecular level. Despite advances in genomics, extracting actionable insights from gene–disease associations and expression data remains complex and resource-intensive.

To address this, the authors of a study published in June 2025 in the International Journal of Molecular Sciences developed GeneHarmony: a user-friendly tool designed to simplify the integration and analysis of gene-disease relationships with tissue-specific expression profiles. Drawing from publicly available datasets like Diseasesv2.0 and GTExv8, GeneHarmony enables researchers to identify candidate biomarkers across diseases with shared pathogenesis.

The study applies the tool to SjD, RA, and SLE, demonstrating its potential for biomarker discovery and pathway analysis. Here’s a look at what it found.

Common Genes, Distinct Roles
Using filtered confidence scores (2.5–5.0), the authors identified seven genes shared across the three diseases: CD4, CD8A, IL6, IL17A, TNFSF13B, TNF, and TRIM21. Of these, TNF and IL6 emerged as central nodes, appearing in 85 percent and 80 percent of the top 20 KEGG pathways respectively, including those associated with RA, SLE, hematopoietic lineage, and IL-17 signaling.

However, their biological roles are not uniformly therapeutic targets. While TNF inhibitors have proven effective in RA, they show limited or adverse outcomes in SjD and SLE. Similarly, IL6's involvement in promoting Th17 differentiation complicates its targeting, especially given conflicting clinical trial results for IL6-blocking agents like tocilizumab in SjD.

A striking observation was the lack of IL17A expression in any of the 54 GTEx tissue types, despite its known role in Th17 signaling. This discrepancy flags the potential limitations of transcriptomic data in capturing context-specific immune activation, particularly in diseases like SjD where tissue infiltration and microenvironmental cues shape pathology.

Overlooked Targets and Sex-Specific Bias
Beyond canonical cytokines, the study points to TRIM21 and CD4 as promising but underexplored targets. TRIM21, involved in intracellular antibody-mediated immunity, showed consistent associations but has not yet been tested therapeutically in these autoimmune conditions. Similarly, the CD4-targeting agent ibalizumab, though approved for HIV, has yet to be evaluated for its potential to disrupt T-cell trafficking mechanisms implicated in RA and SLE.

GeneHarmony’s current version lacks sex-specific gene expression filters—a notable gap given the high female predominance in these diseases (for example, SjD with a 14:1 female-to-male ratio). The authors underscore this limitation and propose future integration of sex-biased gene data, such as from the SAGD database, alongside microbiome and eQTL data to improve biomarker resolution and mechanistic insights.

A Scalable Framework for Systems Autoimmunity
GeneHarmony stands as a practical interface for exploring the genetic architecture of autoimmune disease. By enabling rapid cross-disease gene comparison and overlaying tissue-level expression, it democratizes a task often limited to bioinformatics specialists. Its potential lies in adaptation: integration of sex, microbiome, and regulatory datasets could transform it from a static lookup tool to a dynamic hypothesis generator for systems immunology.

While experimental validation and broader integration remain future priorities, the current version delivers on its central promise: simplifying biomarker discovery across clinically entangled autoimmune syndromes and highlighting new candidates for diagnostic and therapeutic development.

Reference:
Beckman MF, Alexander A, Mougeot J-LC, Bahrani Mougeot F. GeneHarmony: A Knowledge-Based Tool for Biomarker Discovery in Disease: Sjögren’s Disease vs. Rheumatoid Arthritis and Systemic Lupus Erythematosus. International Journal of Molecular Sciences. 2025; 26(13):6379. https://doi.org/10.3390/ijms26136379