通过生物信息学分析探索 2 型糖尿病患者脂肪组织胰岛素抵抗的分子机制。

IF 2.5 Q3 ENDOCRINOLOGY & METABOLISM Minerva endocrinology Pub Date : 2023-12-01 Epub Date: 2023-08-03 DOI:10.23736/S2724-6507.22.03771-X
Yujing Wang, Weiyu Zhou, Dana Liu, Zhiying Zhang, Yuanxin Xu, Xiaojing Wan, Haiqiao Yu, Shuang Yan
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引用次数: 0

摘要

背景:我们旨在确定胰岛素抵抗(IR)相关通路中差异表达基因(DEGs)的顺式表达定量遗传位点(cis-eQTL)和反式表达定量遗传位点(trans-eQTL):从基因表达总库(Gene Expression Omnibus)数据库中获得了2型糖尿病(T2DM)患者脂肪组织中胰岛素敏感性(IS)和胰岛素抵抗(IR)的表达谱数据。然后,用基因组富集分析(GSEA)和基因组变异分析(GSVA)方法确定IS组和IR组之间潜在的京都基因组百科全书(KEGG)通路的显著富集,并用Wilcoxon秩和检验确定与KEGG通路相关的DEGs。最后,从 eQTLGen 数据库中筛选出影响 DEGs 表达的顺式-eQTLs 和反式-eQTLs:GSEA和GSVA分析表明,mTOR信号通路、胰岛素信号通路与T2DM的病理过程密切相关。此外,我们还发现 6 个基因(ACACA、GYS2、PCK1、PRKAR1A、SLC2A4 和 VEGFA)在 IR 相关通路中有显著差异表达。最后,我们共鉴定出 1073 个顺式-eQTL 和 24 个反式-eQTL:结论:我们筛选出了在红外相关通路中显著差异表达的六个基因,包括 ACACA、GYS2、PCK1、PRKAR1A、SLC2A4 和 VEGFA。此外,我们还发现这六个基因受到 1073 个顺式-eQTL 和 24 个反式-eQTL 的影响。
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Exploration of the molecular mechanism of insulin resistance in adipose tissue of patients with type 2 diabetes mellitus through a bioinformatic analysis.

Background: We aimed to determine the cis-expression Quantitative Trait Loci (cis-eQTL) and trans-eQTL of differentially expressed genes (DEGs) in insulin resistance (IR) related pathways.

Methods: The expression profile data for insulin sensitivity (IS) and IR in the adipose tissue of patients with type 2 diabetes mellitus (T2DM) were acquired from the Gene Expression Omnibus databases. Then, the Gene set enrichment analysis (GSEA) and Gene set variation analysis (GSVA) methods were performed to identify the significant enrichment of potential Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways between IS and IR groups, and the Wilcoxon rank sum test was carried out to identify the DEGs related to KEGG pathways. Finally, the cis-eQTLs and trans-eQTLs that can affect the expression of DEGs were screened from the eQTLGen database.

Results: The GSEA and GSVA analysis indicated that the mTOR signaling pathway, insulin signaling pathway and T2DM had a strong correlation with the pathological process of T2DM. Furthermore, six genes (ACACA, GYS2, PCK1, PRKAR1A, SLC2A4, and VEGFA) were found to be significantly differentially expressed in IR-related pathways. Finally, we have identified a total of 1073 cis-eQTLs and 24 trans-eQTLs.

Conclusions: We screened out six genes that were significantly differentially expressed in IR-related pathways, including ACACA, GYS2, PCK1, PRKAR1A, SLC2A4, and VEGFA. Moreover, we discovered that these six genes were affected by 1073 cis-eQTLs and 24 trans-eQTLs.

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