Explaining Type 2 Diabetes with Transcriptomic Signatures of Pancreatic β-Cell Dysfunction and Death Induced by Human Islet Amyloid Polypeptide

被引:0
作者
Roham, Pratiksha H. [1 ]
Yadav, Saurabh Singh [1 ]
Senthilnathan, Brindha [2 ]
Potdar, Pranjali [1 ]
Roy, Sujata [2 ]
Sharma, Shilpy [1 ]
机构
[1] Savitribai Phule Pune Univ, Dept Biotechnol, Pune 411007, Maharashtra, India
[2] Rajalakshmi Engn Coll, Dept Biotechnol, Thandalam 602105, India
关键词
type 2 diabetes mellitus; differential gene expression; hIAPP-transgenic pancreatic islets; transcriptomics; weighted gene coexpression network analysis; PROLIFERATOR-ACTIVATED RECEPTOR; RENIN-ANGIOTENSIN SYSTEM; INSULIN-RESISTANCE; C-JUN; GLUCOSE; GAMMA; OVEREXPRESSION; EXPRESSION; AMYLIN; HYPERGLYCEMIA;
D O I
10.1089/omi.2024.0216
中图分类号
Q81 [生物工程学(生物技术)]; Q93 [微生物学];
学科分类号
071005 ; 0836 ; 090102 ; 100705 ;
摘要
Amyloid deposits formed by misfolding and aggregation of human islet amyloid polypeptide (hIAPP) are one of the key pathophysiological features of type 2 diabetes mellitus (T2DM) and have been associated with the loss of function and viability of the pancreatic beta-cells. The molecular processes by which hIAPP induces cytotoxicity in these cells are not well understood. To the best of our knowledge, this is the first report describing findings from the combined analysis of Affymetrix microarray and high-throughput sequencing (HTS) Gene Expression Omnibus (GEO) datasets of hIAPP-transgenic (Tg) mice islets. In brief, using GEO data, we compared in silico the pancreatic islets obtained from hIAPP-Tg and wild-type mice. Affymetrix microarray datasets (GSE84423, GSE85380, and GSE94672) and HTS datasets (GSE135276 and GSE148809) were chosen. Weighted gene coexpression network analysis was performed using GSE135276 to identify the coexpressed gene networks and establish a correlation pattern between gene modules and hIAPP overexpression under hyperglycemic conditions. Subsequently, we analyzed differential gene expression with the remaining datasets. Network analysis was performed to identify hub genes and the associated pathways using Cytoscape. Key findings from the present study include identification of seven hub genes, namely, Ins2, Agt, Jun, Fos, CD44, Igf1, and Ppar-gamma, significantly involved in the process(es) of insulin synthesis and secretion, development of insulin resistance, oxidative stress, inflammation, mitophagy, and apoptosis. In conclusion, we propose that these hub genes can help explain T2DM pathogenesis and can be potentially utilized to develop therapeutic interventions targeting hIAPP for clinical management of T2DM.
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