ArticleMedical science monitor : international medical journal of experimental and clinical research2019
Differently Expressed Genes (DEGs) Relevant to Type 2 Diabetes Mellitus Identification and Pathway Analysis via Integrated Bioinformatics Analysis.
Article in Medical science monitor : international medical journal of experimental and clinical research, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers.
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17 citing papers in PubMed, 37 citations in OpenAlex.
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- Temporal Transcriptomic Differences in Stroke Between Diabetic and Non-Diabetic Mice.Journal of molecular neuroscience : MN · 2025Article
- Immune repertoire profiling and T cell dysregulation in Peripheral Blood Mononuclear Cells of Type 2 diabetic patients.PloS one · 2025Article
- Identification of genes related to fatty acid metabolism in type 2 diabetes mellitus.Biochemistry and biophysics reports · 2024Article
- High expression of CNOT6L contributes to the negative development of type 2 diabetes.Scientific reports · 2024Article
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- Exploring early DNA methylation alterations in type 1 diabetes: implications of glycemic control.Frontiers in endocrinology · 2024Article
- Cell-specific gene networks and drivers in rheumatoid arthritis synovial tissues.Frontiers in immunology · 2024Article
- RFC2 promotes aerobic glycolysis and progression of colorectal cancer.BMC gastroenterology · 2023Article
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- Exploring biomarkers and transcriptional factors in type 2 diabetes by comprehensive bioinformatics analysis on RNA-Seq and scRNA-Seq data.Annals of translational medicine · 2022Article
- Comprehensive analysis of key m5C modification-related genes in type 2 diabetes.Frontiers in genetics · 2022Article
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- DNA primase subunit 1 deteriorated progression of hepatocellular carcinoma by activating AKT/mTOR signaling and UBE2C-mediated P53 ubiquitination.Cell & bioscience · 2021Article
- Identification of Three Significant Genes Associated with Immune Cells Infiltration in Dysfunctional Adipose Tissue-Induced Insulin-Resistance of Obese Patients via Comprehensive Bioinformatics Analysis.International journal of endocrinology · 2021Article
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Authors and funding
6 authors.
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No grant is acknowledged in the PubMed record.
Abstract
BACKGROUND The aim of this study was to evaluate the differently expressed genes (DEGs) relevant to type 2 diabetes mellitus (T2DM) and pathway by performing integrated bioinformatics analysis. MATERIAL AND METHODS The gene expression datasets GSE7014 and GSE29221 were downloaded in GEO database, and DEGs from type 2 diabetes mellitus and normal skeletal muscle tissues were identified. Biological function analysis of the DEGs was enriched by GO and KEEG pathway. A PPI network for the identified DEGs was built using the STRING database. RESULTS Thirty top DEGs were identified from 2 datasets: GSE7014 and GSE29221. Of the 30 top DEGs, 20 were up-regulated and 10 were down-regulated. The 20 up-regulated genes were enriched in regulation of mRNA, protein biding, and phospholipase D signaling pathway. The 10 down-regulated genes were enriched in telomere maintenance via semi-conservative replication, AGE-RAGE signaling pathway in diabetic complications, and insulin resistance pathway. In the PPI network of 20 up-regulated DEGs, there were 40 nodes and 84 edges, with an average node degree of 4.2. For the 10 down-regulated DEGs, we found a total of 30 nodes and 105 edges, with an average node degree of 7.0 and local clustering coefficient of 0.812. Among the 30 DEGs, 10 hub genes (CNOT6L, CNOT6, CNOT1, CNOT7, RQCD1, RFC2, PRIM1, RFC4, RFC5, and RFC1) were also identified through Cytoscape. CONCLUSIONS DEGs of T2DM may play an essential role in disease development and may be potential pathogeneses of T2DM.
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