Background
Age- and sex-related susceptibility to adverse drug reactions and disease is a key concern in understanding drug safety and disease progression. We hypothesize that the underlying suite of hepatic genes expressed at various life cycle stages will impact susceptibility to adverse drug reactions. Understanding the basal liver gene expression patterns is a necessary first step in addressing this hypothesis and will inform our assessments of adverse drug reactions as the liver plays a central role in drug metabolism and biotransformation. Untreated male and female F344 rats were sacrificed at 2, 5, 6, 8, 15, 21, 52, 78, and 104 weeks of age. Liver tissues were collected for histology and gene expression analysis. Whole-genome rat microarrays were used to query global expression profiles.
Conclusions
These results suggest an underlying role for genes in specific clusters in potentiating age- and sex-related differences in susceptibility to adverse health effects. Furthermore, such a comprehensive picture of life cycle changes in gene expression deepens our understanding and informs the utility of liver gene expression biomarkers.
Results
An initial list of differentially expressed genes was selected using criteria based upon p-value (p < 0.05) and fold-change (+/- 1.5). Three dimensional principal component analyses revealed differences between males and females beginning at 2 weeks with more divergent profiles beginning at 5 weeks. The greatest sex-differences were observed between 8 and 52 weeks before converging again at 104 weeks. K-means clustering identified groups of genes that displayed age-related patterns of expression. Various adult aging-related clusters represented gene pathways related to xenobiotic metabolism, DNA damage repair, and oxidative stress. Conclusions: These results suggest an underlying role for genes in specific clusters in potentiating age- and sex-related differences in susceptibility to adverse health effects. Furthermore, such a comprehensive picture of life cycle changes in gene expression deepens our understanding and informs the utility of liver gene expression biomarkers.