Identification of Crucial Genes and Pathways Associated with Atherosclerotic Plaque in Diabetic Patients

• Main Authors: Li YY, Zhang S, Wang H, Zhang SX, Xu T, Chen SW, Zhang Y, Chen Y
• Format: Article
• Language: English
• Published: Dove Medical Press 2021-02-01
• Series: Pharmacogenomics and Personalized Medicine
• Subjects: diabetes; atherosclerotic plaque; differentially expressed genes; bioinformatics analysis
• Online Access: https://www.dovepress.com/identification-of-crucial-genes-and-pathways-associated-with-atheroscl-peer-reviewed-article-PGPM

Yuan-Yuan Li,* Sheng Zhang,* Hua Wang, Shun-Xiao Zhang, Ting Xu, Shu-Wen Chen, Yan Zhang, Yue Chen Department of Endocrinology, Baoshan Branch, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, Shanghai, 201999, People’s Republic of China*These authors contributed equally to this workCorrespondence: Yan Zhang; Yue ChenDepartment of Endocrinology, Baoshan Branch, Shuguang Hospital Affiliated to Shanghai University of Traditional Chinese Medicine, No. 181 You-Yi Road, Shanghai, 201999, People’s Republic of ChinaTel [phone]; [phone]Email [e-mail]; [e-mail]: Patients with diabetes have more calcification in atherosclerotic plaque and a higher occurrence of secondary cardiovascular events than patients without diabetes. The objective of this study was to identify crucial genes involved in the development of diabetic atherosclerotic plaque using a bioinformatics approach.Methods: Microarray dataset GSE118481 was downloaded from the Gene Expression Omnibus (GEO) database; the dataset included 6 patients with diabetic atherosclerotic plaque (DBT) and 6 nondiabetic patients with atherosclerotic plaque (Ctrl). Differentially expressed genes (DEG) between the DBT and Ctrl groups were identified and then subjected to functional enrichment analysis. Based on the enriched pathways of DEGs, diabetic atherosclerotic plaque-related pathways were screened using the comparative toxicogenomics database (CTD). We then constructed a protein–protein interaction (PPI) network and transcription factor (TF)–miRNA–mRNA network.Results: A total of 243 DEGs were obtained in the DBT group compared with the Ctrl group, including 85 up-regulated and 158 down-regulated DEGs. Functional enrichment analysis showed that up-regulated DEGs were mainly enriched in isoprenoid metabolic process, DNA-binding TF activity, and response to virus. Additionally, DEGs participating in the toll-like receptor signaling pathway were closely related to diabetes, carotid stenosis, and insulin resistance. The TF–miRNA–mRNA network showed that toll-like receptor 4 (TLR4), BCL2-like 11 (BCL2L11), and glutamate-cysteine ligase catalytic subunit (GCLC) were hub genes. Furthermore, TLR4 was regulated by TF signal transducer and activator of transcription 6 (STAT6); BCL2L11 was targeted by hsa-miR-24-3p; and GCLC was regulated by nuclear factor, erythroid 2 like 2 (NFE2L2).Conclusion: Identification of hub genes and pathways increased our understanding of the molecular mechanisms underlying the atherosclerotic plaque in patients with or without diabetes. These crucial genes (TLR4, BC2L11, and GCLC) might function as molecular biomarkers for diabetic atherosclerotic plaque.Keywords: diabetes, atherosclerotic plaque, differentially expressed genes, bioinformatics analysis