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Differential gene expression profiling of the sciatic nerve in type 1 and type 2 diabetic mice

Diabetic peripheral neuropathy (DPN) is a common complication of diabetes mellitus (DM). The pathogenic mechanisms of DPN and the therapeutic interventions required may be distinct between type 1 (T1) and type 2 (T2) DM. However, the molecular mechanisms underlying the pathogenesis of DPN in both types of diabetes remain unclear. The aim of the current study was to identify the changes in genes and pathways associated with DPN in sciatic nerves of T1- and T2DM mice using bioinformatics analysis. The microarray profiles of sciatic nerves of T1DM (GSE11343) and T2DM (GSE27382) mouse models were downloaded from the Gene Expression Omnibus database to identify differentially expressed genes (DEGs) in each. DEGs in the two types of DM (with fold change ≥2 and P<0.05) were identified with BRB-ArrayTools. 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. A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins and visualized using Cytoscape. Compared with control samples, 623 and 1,890 DEGs were identified in sciatic nerves of T1- and T2DM mice, respectively. Of these, 75 genes were coordinately dysregulated in the sciatic nerves of both models. Many DEGs unique to T1DM mice were localized to the nucleoplasm and were associated with regulation of transcription processes, while many unique to T2DM mice were localized at cell junctions and were associated with ion transport. In addition, certain DEGs may be associated with the different treatment strategies used for the two types of DM. This analysis provides insight into the functional gene sets and pathways operating in sciatic nerves in T1- and T2DM. The results should improve understanding of the molecular mechanisms underlying the pathophysiology of DPN, and provide information for the development of therapeutic strategies for DPN specific to each type of DM.


Introduction
Diabetic peripheral neuropathy (DPN) is a common complication of diabetes mellitus (DM). More than half of patients with DM worldwide suffer from DPN during the course of the disease (1,2). DPN is characterized by distal-to-proximal nerve damage leading to neuropathic pain and loss of sensation (3). It is also associated with notably high morbidity and mortality: Previous studies reported that the mortality rate approximated to 25-50% within 5-10 years following onset of diabetic neuropathy (4,5). Strict maintenance of normal glycemic level is the only effective treatment available for DPN at present (6).
Though the occurrence of DPN is common to both type 1 (T1) and type 2 (T2)DM, a number of studies have suggested that its pathogenic mechanism may differ between the two (7,8). For example, more abnormalities at the molecular, functional and morphometric levels including increased frequencies of denervated Schwann cells and significant fiber loss have been observed in the peripheral nerve of T1DM mice compared with in T2DM mice (8,9). In addition, different structural changes may lead to variation in nerve conduction velocity for DPN in the two diabetic models (10). These fundamentally different mechanisms for DPN may lead to varying effects of the common treatments, such as in control of glucose, which has been suggested to be more beneficial for DPN in T1DM than in T2DM (7). Therefore, determining the distinct molecular mechanisms underlying DPN in T1-and T2DM is of paramount importance for the development of successful therapeutic interventions.
In the last decade, the development of high-throughput platforms including microarray technology has allowed researchers to concurrently determine the expression levels of several thousands of differentially expressed genes (DEGs) in diseases (11,12). In addition, the comparison of gene expression profiles of DEGs through microarray technology using bioinformatics analysis has determined distinct pathophysiological mechanisms in different diseases or syndromes including neuropathic pain and chronic radicular pain (13). For instance, Zhang et al (14) screened a number of DEGs in a control (healthy) group of mice and a group with streptozotocin (STZ)-induced diabetes, and identified genes co-regulated by both STZ and rosiglitazone, which may be potential targets in the treatment of DPN. However, there are few studies that have compared the gene expression profiles of DEGs between DPN in T1-and T2DM through microarray profiling. In the present study, the aim was to compare the DEGs between the sciatic nerves of T1-and T2DM mouse models by microarray profiling. Furthermore, the distinct biological processes and pathways associated with DPN in T1-or T2DM were analyzed and compared based on gene ontology (GO) and pathway enrichment analyses. This was hoped to provide novel insights into the distinct pathophysiological mechanisms and implicate drug therapies for DPN specific to the different types of DM.

Materials and methods
Source of microarray data. The gene expression profiles of GSE11343 and GSE27382 were obtained from the Gene Expression Omnibus (GEO) database (http://www.ncbi.nlm. nih.gov/geo/). The annotation platforms for GSE11343 and GSE27382 were GPL1261 and GPL9746, respectively.

Pre-processing of microarray data and identification of DEGs.
Pre-processing for the cell intensity (CEL) files including conversion into expression measures, background correction and quartile data normalization was performed with BRB-ArrayTools (version 4.5.1) (17). The univariate t-test with a fold change ≥2 and nominal significance level of 0.05 was applied in BRB-ArrayTools to identify the DEGs between the diabetic and normal groups.
Gene ontology and pathway enrichment analyses. To identify the DEGs determined with BRB-ArrayTools, GO and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway enrichment analyses were performed via the Database for Annotation, Visualization and Integrated Discovery (DAVID 6.8; http://david.abcc.ncifcrf.gov/) (18,19). GO terms [categorized into molecular function (MF), biological process (BP) and cellular component (CC)] and KEGG pathways with P<0.05 were considered significantly enriched by the DEGs.
Construction of protein-protein interaction (PPI) network and module analysis. With the purpose of evaluating the relationships among DEGs from the perspective of protein interaction, a protein-protein interaction (PPI) network was constructed with the Search Tool for the Retrieval of Interacting Genes/Proteins (STRING 10.5; http://www.string-db.org) and visualized using Cytoscape software (version 3.4.0; http://cytoscape.org/) (18). A combined score >0.4 was selected to determine significant interactions among DEGs. In accordance with a previous analysis (20), the connectivity degree of a protein, namely the number of proteins it connected with, was considered to indicate importance of the protein in the PPI network.
Module analysis was performed in the plugin ClusterONE (version 1.0) in Cytoscape with a threshold of P<0.001. In addition, function and pathway enrichment analyses were performed for DEGs in the modules with a threshold of P<0.05.

Results
Identification of DEGs. Based on the criteria of a nominal significance level of 0.05 and fold change ≥2, 623 and 1,890 DEGs were identified in sciatic nerves of T1DM (GSE11343) and T2DM (GSE27382) mice, respectively, as compared with the control samples. Among them, 75 genes were identified to be coordinately dysregulated in sciatic nerves of both models, with 20 genes upregulated and 55 genes downregulated ( Fig. 1 and Table SI). Meanwhile, 160 upregulated and 388 downregulated DEGs were unique to T1DM ( Fig. 1 and Table SII), and 721 upregulated and 1,094 downregulated DEGs were unique to T2DM ( Fig. 1 and Table SIII).
GO and pathway enrichment analyses. There were 60 coincident enriched GO terms for DEGs in T1-and T2DM, the top 20 of which are listed in Table I. In addition, the top 20 enriched GO terms for DEGs that were unique to sciatic nerves from the T1-or T2DM model are presented in Table II. Besides these, Figure 1. Numbers of (A) upregulated and (B) downregulated differentially expressed genes in the sciatic nerve of T1-and T2DM mouse models. T1DM, type 1 diabetes mellitus; T2DM, type 2 diabetes mellitus. 21 and 27 KEGG pathways were enriched for DEGs in T1-and T2DM, respectively. Among them, 4 pathways were coincident in both models (Table III), while 17 and 23 pathways were unique to T1-and T2DM respectively (Table IV).
PPI network. A total of 419 nodes and 1,343 edges were involved in the PPI for T1DM, whereas 1,416 nodes and 11,077 edges were involved in that for T2DM (data not shown). The top 10 proteins in each of T1-and T2DM with a relatively high degree of connectivity in the PPI network are presented in Table V.
Extent of enriched function and topological structure analysis for the modules of the PPI networks. Based on the module analysis by ClusterONE, a single module was determined in the PPI for T1DM ( Fig. 2A) and 7 modules for T2DM ( Fig. 2B-H). The information on the modules, including node number, P-value, protein with highest degree of connectivity, and numbers of GO terms and KEGG pathways are shown in Table VI.

Discussion
DPN is among the most frequent complications for T1-and T2DM. It is generally considered that DPN results from damage by hyperglycemia, regardless of the type of DM (3). In  recent decades, distinct molecular functions and morphometric abnormalities between DPN in T1-and T2DM have been reported (7,8). In addition, it has been proposed that the therapeutic interventions for DPN should differ based on the type of diabetes (7). For DPN in T1DM, it has been suggested that improved glycemic control may preserve nerve function and/or          decrease the likelihood of developing DPN (6). By contrast, for DPN in T2DM, not only glycemic control, but treatments for other risk factors including obesity may be equally critical in preventing DPN (6). Therefore, since the molecular mechanisms underlying the pathogenesis of DPN in each type of DM may differ, understanding the mechanisms may lead to novel therapeutic approaches for prevention or treatment.
In the present study, there were marked differences between the gene expression profiles, GO terms and KEGG pathways of DEGs in the sciatic nerves of T1-and T2DM mouse models. This was in accordance with previous studies revealing considerable alterations in global gene expression profiles of several tissues including skeletal muscles and adipose tissue (21), and organs such as the intestine (22), liver (23) and brain (24) in the two types of DM. It is established that T1DM is characterized by destruction of pancreatic islet cells by autoimmunity, with loss of pancreatic insulin production, while T2DM is a metabolic disease with high pancreatic insulin production in the setting of insulin resistance (6). Therefore, the different insulin level and insulin signaling pathways between the two types of DM may converge on and modulate the transcription of genes (25); it thus seemed reasonable to search for altered gene expression patterns in DPN between T1-and T2DM models characterized by absolute or relative insulin deficiency.
A number of DEGs unique to the sciatic nerve of T1DM mice were associated with cell proliferation, as well as the mitogen-activated protein kinase signaling pathway, which is a critical pathway for cell proliferation (26). In neuropathic pain, a correlation has been determined between the proliferation of nerve cells including microglia and astrocyte and the abnormal pain responses (27,28). In addition, previous study has demonstrated that the proliferation of glia cells including astrocyte was associated with structural changes in the nervous system, such as axonal growth (29). Furthermore, with loss of C-fibers, increased frequencies of denervated Schwann cells and regenerating fibers have been identified in T1DM mice but not in T2DM mice (8). Therefore, the DEGs associated with cell proliferation may serve a crucial role during the pathological changes of DPN in T1DM.
Insulin resistance is among the major factors that leads to the development and progression of complications in T2DM (30).        Regarding DPN, it has been suggested that perturbation of insulin receptor signaling due to insulin resistance may cause neurons to become more vulnerable to metabolic insults and contribute to the pathogenesis of neuropathy (31). However, how gene expression is altered under the insulin-resistant state in nerve tissue remains unclear for T2DM. In the present study, a number of unique GO terms and signaling pathways were determined for the sciatic nerve profile of T2DM mice, which may result from an insulin-resistant state. For instance, a majority of the GO terms among the top 20 enriched terms unique to T2DM were related to the biological processes associated with cell junctions, ion activity and membrane activity. Previous studies indicated that the insulin-resistant state induced phosphorylation and downregulated of the expression of certain connexin (Cx) proteins including Cx43, which may constitute a potential mechanism underlying the pathogenesis of insulin resistance and its complications (32,33). Furthermore, it was demonstrated that Ca 2+ overload in the mitochondria caused production of superoxide and functional impairment of multiple tissues, which may result in β-cell failure and insulin resistance in target tissues, further aggravating the complications of diabetes (34). Therefore, it may be speculated that the impairment of nerve tissues under the insulin-resistant state is attributable to these DEGs in the aforementioned biological processes in T2DM. In addition, it was apparent that the efficacy of different treatment strategies for the two types of DM may be attributed to certain DEGs. For example, treatment of obesity appeared as critical as glycemic control for preventing the development of DPN in T2DM (5). In the present study, C-C chemokine receptor 7 (Ccr7), which was among the proteins with the highest degrees of connectivity in the PPI network for T2DM, could interact with the chemokine ligand 19 (Ccl19). The Ccl19-Ccr7 pathway may serve an important role in development of high-fat-induced obesity and subsequent insulin resistance (35). Therefore, it may be suggested that a potential treatment strategy is through Ccr7 targeting to alleviate insulin resistance and neuropathy in T2DM. Limitation of the current study included the data being obtained from online databases, meaning the genetic backgrounds of the mice could vary substantially. Further genetic analyses are therefore warranted to identify genes and determine the molecular differences in neuropathy between the two types of DM based on different strains of mice.
In conclusion, the present study revealed the gene expression profiles and signaling pathways associated with the sciatic nerve in T1-and T2DM mouse models. The DEGs and signaling pathways may indicate unique biological processes and treatment strategies for the two types of DM. Further molecular biological experiments are required to validate the function of the DEGs and signaling pathways in DPN.