Mechanistic insights into silica-associated immune dysregulation and diseases: A multi-dataset integrative analysis

Crystalline silica is recognized as an occupational hazard with well-established causal links to silicosis and lung cancer and increasing evidence implicating its role in systemic inflammatory and autoimmune diseases. To understand the mechanistic basis of silica-induced disease, we employed an integrative systems toxicology approach combining curated data from DisGeNET, CTD, AOP-Wiki, in vivo rodent transcriptomics data (GEO), and literature-mining tools (AOP-helpFinder 3.0). The transcriptomic datasets were used to identify silica-responsive genes in lung tissue and to complement curated mechanistic information with unbiased, high-throughput evidence of pathway activation. Overlapping gene signatures and enriched pathways were evaluated across silicosis, autoimmune diseases, and fibrotic pulmonary disorders to identify conserved and divergent biological processes. Consistent activation of cytokine signalling, leukocyte recruitment, and damage-associated molecular pattern (DAMP) pathways suggests a shared inflammatory axis. Our study quantitatively identifies a core set of 29 genes and recurring biological themes (like cytokine signalling, leukocyte activation, and TLR4/HMGB1 pathways) that remain consistently activated despite the inherent noise, curation bias, and biological variability across the different datasets. This convergence, detailed in the gene/pathway lists, offers a high-confidence, consensus molecular signature. However, interspecies differences, differences in exposure protocols, tissue sources of transcriptomic data, and temporal resolution present challenges in cross-study comparison and interpretation of the findings. Future work incorporating tissue-specific, multi-omics and harmonized experimental designs will be critical to understanding silica’s systemic health impacts.