Bioinformatic analysis of the effect of type II diabetes on skin wound healing. 2015

K Ge, and J J Wu, and L Qian, and M J Wu, and F L Wang, and B Xu, and T Xie
Department of Emergency, Shanghai 9th People's Hospital, Shanghai Jiaotong University School of Medicine, Shanghai, China.

We examined the relationship between type 2 diabetes and skin wound healing. GSE38396 was downloaded from the Gene Expression Omnibus database and preprocessed using the RMA function of the Affy package. Differentially expressed genes (DEGs) were identified using the limma package, then DAVID was applied to per-form Gene Ontology functional annotation and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. MicroRNAs and their target genes were screened from the miRecords database and subjected to functional analysis. Finally, the STRING online database was applied to identify the protein-protein interaction relationships, and a combined score > 0.5 was considered to indicate an interaction. A total of 421 DEGs (208 upregulated and 213 downregulated genes) were identified in the skin lymphatic endothelial cells of patients with type II diabetes. Twenty-four microRNAs and 34 target genes were screened, including those involved in cell migration, regulation of cell proliferation, cell death, and cell adhesion regulation, among others. Protein-protein interaction network clustering analysis identified a module composed of 25 genes, and INTERPRO protein domain enrichment analysis showed that the protein domain of the clustering module main-ly contained the insulin-like growth factor binding proteins IGFBP3 and CYR61. IGFBP3 and CYR61 may play important roles in skin wound healing in diabetes patients. This information may be useful for developing methods to treat skin refractory wounds in type II diabetes.

UI MeSH Term Description Entries
D003924 Diabetes Mellitus, Type 2 A subclass of DIABETES MELLITUS that is not INSULIN-responsive or dependent (NIDDM). It is characterized initially by INSULIN RESISTANCE and HYPERINSULINEMIA; and eventually by GLUCOSE INTOLERANCE; HYPERGLYCEMIA; and overt diabetes. Type II diabetes mellitus is no longer considered a disease exclusively found in adults. Patients seldom develop KETOSIS but often exhibit OBESITY. Diabetes Mellitus, Adult-Onset,Diabetes Mellitus, Ketosis-Resistant,Diabetes Mellitus, Maturity-Onset,Diabetes Mellitus, Non-Insulin-Dependent,Diabetes Mellitus, Slow-Onset,Diabetes Mellitus, Stable,MODY,Maturity-Onset Diabetes Mellitus,NIDDM,Diabetes Mellitus, Non Insulin Dependent,Diabetes Mellitus, Noninsulin Dependent,Diabetes Mellitus, Noninsulin-Dependent,Diabetes Mellitus, Type II,Maturity-Onset Diabetes,Noninsulin-Dependent Diabetes Mellitus,Type 2 Diabetes,Type 2 Diabetes Mellitus,Adult-Onset Diabetes Mellitus,Diabetes Mellitus, Adult Onset,Diabetes Mellitus, Ketosis Resistant,Diabetes Mellitus, Maturity Onset,Diabetes Mellitus, Slow Onset,Diabetes, Maturity-Onset,Diabetes, Type 2,Ketosis-Resistant Diabetes Mellitus,Maturity Onset Diabetes,Maturity Onset Diabetes Mellitus,Non-Insulin-Dependent Diabetes Mellitus,Noninsulin Dependent Diabetes Mellitus,Slow-Onset Diabetes Mellitus,Stable Diabetes Mellitus
D006801 Humans Members of the species Homo sapiens. Homo sapiens,Man (Taxonomy),Human,Man, Modern,Modern Man
D012867 Skin The outer covering of the body that protects it from the environment. It is composed of the DERMIS and the EPIDERMIS.
D014945 Wound Healing Restoration of integrity to traumatized tissue. Healing, Wound,Healings, Wound,Wound Healings
D019295 Computational Biology A field of biology concerned with the development of techniques for the collection and manipulation of biological data, and the use of such data to make biological discoveries or predictions. This field encompasses all computational methods and theories for solving biological problems including manipulation of models and datasets. Bioinformatics,Molecular Biology, Computational,Bio-Informatics,Biology, Computational,Computational Molecular Biology,Bio Informatics,Bio-Informatic,Bioinformatic,Biologies, Computational Molecular,Biology, Computational Molecular,Computational Molecular Biologies,Molecular Biologies, Computational
D035683 MicroRNAs Small double-stranded, non-protein coding RNAs, 21-25 nucleotides in length generated from single-stranded microRNA gene transcripts by the same RIBONUCLEASE III, Dicer, that produces small interfering RNAs (RNA, SMALL INTERFERING). They become part of the RNA-INDUCED SILENCING COMPLEX and repress the translation (TRANSLATION, GENETIC) of target RNA by binding to homologous 3'UTR region as an imperfect match. The small temporal RNAs (stRNAs), let-7 and lin-4, from C. elegans, are the first 2 miRNAs discovered, and are from a class of miRNAs involved in developmental timing. RNA, Small Temporal,Small Temporal RNA,miRNA,stRNA,Micro RNA,MicroRNA,Primary MicroRNA,Primary miRNA,miRNAs,pre-miRNA,pri-miRNA,MicroRNA, Primary,RNA, Micro,Temporal RNA, Small,miRNA, Primary,pre miRNA,pri miRNA

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