Identification of Inflammation-Related Biomarkers in Diabetes of the Exocrine Pancreas With the Use of Weighted Gene Co-Expression Network Analysis.
Identification of Inflammation-Related Biomarkers in Diabetes of the Exocrine Pancreas With the Use of Weighted Gene Co-Expression Network Analysis.
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DOI：
10.3389/fendo.2022.839865
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发表时间：
2022
影响因子：
5.2
通讯作者：
中科院分区：
文献类型：
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作者：
胰腺外分泌糖尿病（DEP），通常也被描述为胰源性糖尿病，是继发于胰腺或胰腺外分泌异常的糖尿病类型。然而，其发病机制尚不清楚。本文旨在探讨DEP的生物标志物及其潜在的分子机制。基于基因表达数据库GSE 76896数据集，通过加权基因共表达网络分析（WGCNA）和差异表达分析，我们识别了373个基因。此外，蛋白质-蛋白质相互作用（PPI）网络分析和cytoHubba被用来筛选潜在的枢纽基因。确定了五个枢纽基因，包括Toll样受体4（TLR 4）、ITGAM、ITGB 2、PTPRC和CSF 1 R。基因本体论（GO）分析和京都基因与基因组百科全书（KEGG）通路提示巨噬细胞活化和Toll样受体信号通路是DEP的重要病理生理特征。CIBERSORT认为TLR 4可能通过巨噬细胞调节免疫通路。接下来，我们使用GSE 164416数据集验证了枢纽基因的表达和受试者工作特征曲线（ROC）。此外，我们使用miRNet来预测枢纽基因的靶miRNA，并将其与人类MicroRNA疾病数据库（HMDD）中的糖尿病常见miRNA进行比对，以提出DEP的可能机制模型。miRNA-mRNA网络显示has-miR-155- 5 p/has-miR-27 a-3 p/has-miR-21- 5 p-TLR 4可能导致DEP中TLR 4信号通路的激活。总之，我们确定了五个枢纽基因，即TLR 4，ITGAM，ITGB 2，PTPRC和CSF 1 R，作为生物标志物，以帮助诊断DEP，并在遗传水平上对DEP的发病机制进行了深入研究。
Diabetes of the exocrine pancreas (DEP), also commonly described as pancreatogenic diabetes mellitus, is a type of diabetes secondary to abnormalities in pancreatic or exocrine secretion of the pancreas. However, its pathogenesis is not yet known. The aim of this article was to explore the biomarkers of DEP and their potential molecular mechanisms. Based on GSE76896 dataset, which was acquired from Gene Expression Omnibus (GEO), we identified 373 genes by weighted gene co-expression network analysis (WGCNA) and differential expression analysis. In addition, protein–protein interaction (PPI) network analysis and cytoHubba were used to screen potential hub genes. Five hub genes were determined, comprising Toll-like receptor 4 (TLR4), ITGAM, ITGB2, PTPRC, and CSF1R. Gene Ontology (GO) analysis and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways suggested macrophage activation and Toll-like receptor signaling pathway as important pathophysiological features of DEP. CIBERSORT suggested that TLR4 may regulate the immune pathway via macrophages. Next, we validated the expression and receiver operating characteristic curve (ROC) of the hub genes using the GSE164416 dataset. In addition, we used miRNet to predict the target miRNAs of hub genes and intersected them with common miRNAs in diabetes from the Human MicroRNA Disease Database (HMDD), which was used to propose a possible mechanistic model for DEP. The miRNA–mRNA network showed that has-miR-155-5p/has-miR-27a-3p/has-miR-21-5p-TLR4 might lead to TLR4 signaling pathway activation in DEP. In conclusion, we identified five hub genes, namely, TLR4, ITGAM, ITGB2, PTPRC, and CSF1R, as biomarkers to aid in the diagnosis of DEP and conducted an in-depth study of the pathogenesis of DEP at the genetic level.
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WGCNA：用于加权相关网络分析的 R 包。
影响因子：
3
作者：
Langfelder P;Horvath S
通讯作者：
Horvath S
DOI：
10.1111/dom.13031
发表时间：
2017-09
期刊：
Diabetes, obesity & metabolism
影响因子：
--
作者：
Aamodt KI;Powers AC
通讯作者：
Powers AC
影响因子：
14.9
作者：
The Gene Ontology Consortium
通讯作者：
The Gene Ontology Consortium
影响因子：
7.3
作者：
Lu MY;Lin YL;Kuo Y;Chuang CF;Wang JR;Liao F
通讯作者：
Liao F
DOI：
10.4049/jimmunol.1602175
发表时间：
2017-06-15
期刊：
Journal of immunology (Baltimore, Md. : 1950)
影响因子：
--
作者：
Aziz MH;Cui K;Das M;Brown KE;Ardell CL;Febbraio M;Pluskota E;Han J;Wu H;Ballantyne CM;Smith JD;Cathcart MK;Yakubenko VP
通讯作者：
Yakubenko VP