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Updated: May 7, 2026

Assessment of Kidney Function in Mouse Models of Glomerular Disease
Published on: June 30, 2018
Life cycle analysis of kidney gene expression in male F344 rats
Joshua C Kwekel1, Varsha G Desai, Carrie L Moland
1Personalized Medicine Branch, Division of Systems Biology, National Center for Toxicological Research, U.S. Food and Drug Administration, Jefferson, Arkansas, United States of America.
Abstract:
Age is a predisposing condition for susceptibility to chronic kidney disease and progression as well as acute kidney injury that may arise due to the adverse effects of some drugs. Age-related differences in kidney biology, therefore, are a key concern in understanding drug safety and disease progression. We hypothesize that the underlying suite of genes expressed in the kidney at various life cycle stages will impact susceptibility to adverse drug reactions. Therefore, establishing changes in baseline expression data between these life stages is the first and necessary step in evaluating this hypothesis. Untreated male F344 rats were sacrificed at 2, 5, 6, 8, 15, 21, 78, and 104 weeks of age. Kidneys were collected for histology and gene expression analysis. Agilent whole-genome rat microarrays were used to query global expression profiles. An ANOVA (p<0.01) coupled with a fold-change>1.5 in relative mRNA expression, was used to identify 3,724 unique differentially expressed genes (DEGs). Principal component analyses of these DEGs revealed three major divisions in life-cycle renal gene expression. K-means cluster analysis identified several groups of genes that shared age-specific patterns of expression. Pathway analysis of these gene groups revealed age-specific gene networks and functions related to renal function and aging, including extracellular matrix turnover, immune cell response, and renal tubular injury. Large age-related changes in expression were also demonstrated for the genes that code for qualified renal injury biomarkers KIM-1, Clu, and Tff3. These results suggest specific groups of genes that may underlie age-specific susceptibilities to adverse drug reactions and disease. This analysis of the basal gene expression patterns of renal genes throughout the life cycle of the rat will improve the use of current and future renal biomarkers and inform our assessments of kidney injury and disease.
Insights
Kidney gene expression changes with age, impacting drug safety and disease risk. Identifying these age-specific gene patterns is crucial for understanding kidney injury and improving biomarker use.
Area of Science:
- Nephrology
- Genomics
- Toxicology
Background:
- Aging influences kidney susceptibility to disease and drug toxicity.
- Understanding age-related kidney biology is vital for drug safety and disease progression assessment.
Purpose of the Study:
- To investigate age-related changes in kidney gene expression.
- To identify gene expression patterns associated with different life stages in rats.
- To establish a baseline for evaluating how gene expression impacts susceptibility to adverse drug reactions.
Main Methods:
- Gene expression profiling using whole-genome rat microarrays in kidneys from rats aged 2 to 104 weeks.
- Statistical analysis (ANOVA, fold-change) to identify differentially expressed genes (DEGs).
- Principal component and K-means cluster analyses to reveal age-specific expression patterns and gene networks.
Main Results:
- Identified 3,724 differentially expressed genes (DEGs) across different ages.
- Revealed three major divisions in life-cycle renal gene expression.
- Discovered age-specific gene networks involved in kidney function, aging, immune response, and tubular injury.
- Observed significant age-related changes in expression for renal injury biomarkers (KIM-1, Clu, Tff3).
Conclusions:
- Age-specific gene expression patterns in the kidney are linked to susceptibility to disease and adverse drug reactions.
- This study provides a foundation for understanding age-related kidney vulnerabilities.
- Findings will aid in the improved use of renal biomarkers for injury and disease assessment.

