Utilizing rat kidney gene co-expression networks to enhance safety assessment biomarker identification and human translation

This study focuses on improving how we understand drug-related kidney damage. By analysing large datasets from rats, researchers identified patterns in gene activity that reveal how kidneys respond to different drugs. They built an interactive tool called TXG-MAPr to help visualize these patterns and connect them to signs of kidney stress and injury. Many of these patterns were consistent across different species and even showed similarities in human data, suggesting they could help predict kidney damage in people. Overall, this work provides a powerful resource for identifying potential risks of new drugs and chemicals, making drug development safer and more informed.

Highlights

• Mechanistic insights obtained by gene cluster analysis
• Identification of potential biomarker genes through module association with pathology
• Evidence showing Injury and inflammation responses are comparable in rat and human
• Chemical hazard identification acceleration with Rat kidney TXG-MAPr tool

Abstract

Toxicogenomic data provide key insights into molecular mechanisms underlying drug-induced organ toxicities. To simplify transcriptomic data interpretation, we applied weighted gene co-expression network analysis to rat kidney transcriptomics data from TG-GATEs and DrugMatrix, covering time- and dose-response data for 180 compounds. A total of 347 gene modules were incorporated into the rat kidney TXG-MAPr web-tool, that interactively visualizes and quantifies module activity using eigengene scores. Several modules annotated for cellular stress, injury and inflammation were associated with renal pathologies and included established and candidate biomarker genes. Many rat kidney modules were preserved across transcriptome datasets, suggesting potential applicability to other kidney injury contexts. Cross-species preservation analysis using human kidney data further supported the translational potential of these rat-derived modules. The TXG-MAPr platform facilitates upload and analysis of gene expression data in the context of rat kidney co-expression networks, which could identify mechanisms and safety liabilities of chemical or drug exposures.