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Multiple statistical methods for assessing differential gene expression in microarray data of diabetic model rats to
1Department of Endocrinology, Shanghai East Hospital, Tongji University School of Medicine, Shanghai, China.
Background:
Many evidences indicate that statins have pleiotropic effects that are lipid-lowering independent. These effects could suggest attenuation of many of the stages critical to atherosclerosis. However, the specific molecular mechanisms of statins on atherogenesis are still unknown. The goal is to detect and analyze the altered gene expression of the artery after atorvastatin treatment in streptozocin (STZ)-induced diabetic rats, and to predict the possible cholesterol-independent effects of atorvastatin on anti-atherogenesis.
Methods:
A total of 33 Sprague Dawley (SD) rats were randomly divided into 3 groups: control group, diabetic group, and diabetic group with atorvastatin treatment (receiving 50 mg/kg qd atorvastatin). Rats were sacrificed at the end of 4 weeks, and the aortas were obtained. The pathological changes were observed by Hematoxylin and eosin (HE) staining. A cDNA microarray analysis was carried out, and the results were analyzed by the random variance model (RVM) t-test, Stc analysis, Stc-Gene Ontology (GO) analysis, Stc-pathway analysis, and GeneFunNet analysis. Then reverse transcription polymerase chain reaction (RT-PCR) was used to evaluate the mRNA expression of Cathepsin S (Cat S),Which was one of the significant genes obtained by statistical analysis, in the aortas of rats in control group (Wistar rats), DM group (Goto Kakisaki rats) and atorvastatin treated DM group (Goto Kakisaki rats with 50 mg/kg qd atorvastatin) for 12 weeks.
Results:
A total of 1 073 differential expression genes were found in the 3 groups. 2 tendency profiles of gene expression, which represented the medicine effect, were picked out by Stc analysis of gene expression. The main functions of genes and the significant pathways in the 2 profiles were figured out by Stc-go analysis and Stc-pathway analysis. The core regulatory factors in the co-expression network were shown by GeneFunNet analysis. Among these significant genes, Cat S was chosen to be further evaluated as a target gene. Expression of Cat S was upregulated in the aortas of the diabetic rats and downregulated with statistical significance by atorvastatin treatment.
Conclusions:
Atorvastatin can influence the expression of many genes and signal pathways, some may be significant and produce their marked effects on all of the processes of atherogenesis. Cat S is one of them. These data thus predict the possible molecular mechanism of pleiotropic effects of atorvastatin, which is useful for further experimental design.
