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通过生物信息学分析,确定C1QB,ITGAM和ITGB2作为糖尿病病的潜在诊断候选基因

Yongzheng Hu¹, Yani Yu¹, Hui Dong²

¹Department of Nephrology, The Affiliated Hospital of Qingdao University, Qingdao, Shandong, China.

|May 30, 2023

概括

这项研究确定了C1QB,ITGAM和ITGB2作为诊断糖尿病病 (DN) 的关键基因. 这些发现提供了对DN机制和这种糖尿病并发症的潜在治疗点的见解.

科学领域:

生物信息学是一种生物信息学.
基因组学就是基因组学.
分子生物学分子生物学

背景情况:

糖尿病病 (DN) 是一种严重的糖尿病并发症,导致蛋白尿和降低GFR.
由于缺乏已识别的关键基因,对DN的准确诊断具有挑战性.
在转录层面了解DN机制至关重要.

研究的目的:

使用生物信息学识别糖尿病病 (DN) 诊断的新型候选基因.
阐明DN的潜在分子机制.
开发DN的潜在诊断和治疗策略.

主要方法:

对差异表达基因 (DEGs) 的分析微阵列数据集 GSE30529.
使用GO,GSEA,KEGG和STRING进行路径和网络分析.
使用数据集GSE30122,ROC曲线和DN大鼠模型验证的结果.

主要成果:

确定了463个DEGs,富含免疫反应和凝血通路.
发现了五种高诊断性枢纽基因,包括C1QB,ITGAM和ITGB2.
建立了miRNA-mRNA-TF网络,并证实了与损伤的基因相关性.

结论:

C1QB,ITGAM和ITGB2被确定为DN诊断和治疗的有希望的候选基因.
这项研究提供了对转录组水平DN病原体的洞察.
一个miRNA-mRNA-TF网络表明了DN进展的潜在调节途径.

关键词:

生物信息学分析糖尿病脏病糖尿病脏病关键基因关键基因微阵列的微阵列 RNA调节途径的RNA调节途径 qPCRR 是一个很好的方法.

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Genome-wide Association Studies-GWAS

Genome-wide Association Studies-GWAS

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