Gene expression microarray analysis of the sciatic nerve of mice with diabetic neuropathy

Zhang,Lei; Qu,Shen; Liang,Aibin; Jiang,Hong; Wang,Hao

doi:10.3892/ijmm.2014.2011

Gene expression microarray analysis of the sciatic nerve of mice with diabetic neuropathy

Authors:
- Lei Zhang
- Shen Qu
- Aibin Liang
- Hong Jiang
- Hao Wang
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Affiliations: Department of Special Needs Medical Branch, Shanghai Tongji Hospital, School of Medicine, Tongji University, Shanghai 200065, P.R. China, Department of Endocrinology, Shanghai Tenth People's Hospital, School of Medicine, Tongji University, Shanghai 200072, P.R. China, Department of Hematology, Shanghai Tongji Hospital, School of Medicine, Tongji University, Shanghai 200065, P.R. China, Department of Radiology, Shanghai Tongji Hospital, School of Medicine, Tongji University, Shanghai 200065, P.R. China
Published online on: November 26, 2014 https://doi.org/10.3892/ijmm.2014.2011
Pages: 333-339
Copyright: © Zhang et al. This is an open access article distributed under the terms of Creative Commons Attribution License [CC BY_NC 3.0].

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Abstract

The present study aimed to explore novel target genes that regulate the development of diabetic neuropathy (DN) by analyzing gene expression profiles in the sciatic nerve of infected mice. The GSE11343 microarray dataset, which was downloaded from Gene Expression Omnibus, included data on 4 control samples and 5 samples from mice with diabetes induced by streptozotocin (STZ), 5 samples from normal mice treated with rosiglitazone (Rosi) and 5 samples from mice with diabetes induced by STZ and treated with Rosi. Differentially expressed genes (DEGs) between the different groups were identified using the substitution augmentation modification redefinition (SAMR) model. The Gene Ontology (GO) term and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed using the Database for Annotation, Visualization and Integrated Discovery (DAVID). Regulatory and protein‑protein interaction networks were searched using BioCarta and STRING, respectively. The protein structures of potential regulatory genes were predicted using the SYBYL program. Compared with the controls, 1,384 DEGs were identified in the mice with STZ-induced diabetes and 7 DEGs were identified in the mice treated with Rosi. There were 518 DEGs identified between the mice in the STZ + Rosi and STZ groups. We identified 45 GO items, and the calmodulin nerve phosphatase and chemokine signaling pathways were identified as the main pathways. Three genes [myristoylated alanine-rich protein kinase C substrate (Marcks), GLI pathogenesis-related 2 (Glipr2) and centrosomal protein 170 kDa (Cep170)] were found to be co-regulated by both STZ and Rosi, the protein structure of which was predicted and certain binding activity to Rosi was docked. Our study demonstrates that the Marcks, Glipr2 and Cep170 genes may be underlying drug targets in the treatment of DN.

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