A bioinformatics analysis of the contribution of m6A methylation to the occurrence of diabetes mellitus.
A bioinformatics analysis of the contribution of m6A methylation to the occurrence of diabetes mellitus.
复制标题
m6A甲基化对糖尿病发生影响的生物信息学分析
DOI：
10.1530/ec-21-0328
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发表时间：
2021-10-04
影响因子：
2.9
通讯作者：
Wang JP
中科院分区：
文献类型：
--
作者：
Lei L;Bai YH;Jiang HY;He T;Li M;Wang JP
据报道，N6-甲基腺苷（m6 A）甲基化在2型糖尿病（T2 D）中起作用。然而，m6 A甲基化的关键成分尚未在T2 D中得到充分研究。本研究探讨了m6 A甲基化基因在T2 D中的生物学作用和潜在机制。利用基因表达综合数据库（GEO）结合T2 D患者m6 A甲基化和转录组数据，筛选m6 A甲基化差异表达基因（mMDEG）。采用免疫抑制途径分析（IPA）预测T2 D相关差异表达基因（DEG）。使用基因本体论（GO）术语富集和京都基因和基因组百科全书（KEGG）来确定mMDEG的生物学功能。进行基因集富集分析（GSEA）以进一步确认mMDEG的功能富集并确定候选枢纽基因。采用最小绝对收缩选择算子（LASSO）回归分析筛选T2 D的最佳预测因子，并采用RT-PCR和Western blot验证预测因子的表达。共检测到194个重叠mMDEG。GO、KEGG和GSEA分析表明，mMDEG在T2 D和胰岛素信号通路中富集，其中发现了胰岛素基因（INS）、2型膜糖蛋白基因（MAFA）和己糖激酶2（HK 2）基因，LASSO回归分析表明INS基因可作为T2 D的预测基因。INS、MAFA和HK 2基因参与了T2 D的发病过程，但INS能更好地预测T2 D的发生。
N6-methyladenosine (m6A) methylation has been reported to play a role in type 2 diabetes (T2D). However, the key component of m6A methylation has not been well explored in T2D. This study investigates the biological role and the underlying mechanism of m6A methylation genes in T2D. The Gene Expression Omnibus (GEO) database combined with the m6A methylation and transcriptome data of T2D patients were used to identify m6A methylation differentially expressed genes (mMDEGs). Ingenuity pathway analysis (IPA) was used to predict T2D-related differentially expressed genes (DEGs). Gene ontology (GO) term enrichment and the Kyoto Encyclopedia of Genes and Genomes (KEGG) were used to determine the biological functions of mMDEGs. Gene set enrichment analysis (GSEA) was performed to further confirm the functional enrichment of mMDEGs and determine candidate hub genes. The least absolute shrinkage and selection operator (LASSO) regression analysis was carried out to screen for the best predictors of T2D, and RT-PCR and Western blot were used to verify the expression of the predictors. A total of 194 overlapping mMDEGs were detected. GO, KEGG, and GSEA analysis showed that mMDEGs were enriched in T2D and insulin signaling pathways, where the insulin gene (INS), the type 2 membranal glycoprotein gene (MAFA), and hexokinase 2 (HK2) gene were found. The LASSO regression analysis of candidate hub genes showed that the INS gene could be invoked as a predictive hub gene for T2D. INS, MAFA,and HK2 genes participate in the T2D disease process, but INS can better predict the occurrence of T2D.