We have constructed a large-scale transcriptome database of rat liver treated with various drugs. In an effort to identify a biomarker for diagnosis of hepatic phospholipidosis, we extracted 78 probe sets of rat hepatic genes from data of 5 drugs, amiodarone, amitriptyline, clomipramine, imipramine, and ketoconazole, which actually induced this phenotype. Principal component analysis (PCA) using these probes clearly separated dose- and time-dependent clusters of treated groups from their controls. Moreover, 6 drugs (chloramphenicol, chlorpromazine, gentamicin, perhexiline, promethazine, and tamoxifen), which were reported to cause phospholipidosis but judged as negative by histopathological examination, were designated as positive by PCA using these probe sets. Eight drugs (carbon tetrachloride, coumarin, tetracycline, metformin, hydroxyzine, diltiazem, 2-bromoethylamine, and ethionamide), which showed phospholipidosis-like vacuolar formation in the histopathology, could be distinguished from the typical drugs causing phospholipidosis. Moreover, the possible induction of phospholipidosis was predictable by the expression of these genes 24 h after single administration in some of the drugs. We conclude that these identified 78 probe sets could be useful for diagnosis of phospholipidosis, and that toxicogenomics would be a promising approach for prediction of this type of toxicity.
- Principal component analysis
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