T2DM、Obesity、NASH、PCOS共同致病因素相关的分子机制

doi:10.3877/cma.j.issn.1674-0785.2024.05.007

目的

探讨T2DM、Obesity、NASH、PCOS共同致病基因和潜在分子机制。

方法

从GEO数据库下载了GSE20966、GSE17470、GSE88837、GSE34526基因表达谱（DEGs），使用limma包分别进行差异分析，再对4组差异基因取交集，确定并进行功能富集分析，构建蛋白-蛋白相互作用网络（PPI）。采用CIBERSORT算法对不同患者RNA-seq数据进行分析，用来推断22种免疫浸润细胞的相对比例。采用GSVA算法对每个基因集合进行综合打分，评估不同样本潜在的生物学功能变化。

结果

5个交集基因被确定，分别为PTPN3、GBP2、ARL1、NEDD4L、PTPN11。其中PTPN11、NEDD4L、GBP2与胰岛素相关通路相关。进一步通过GSVA验证3个核心基因涉及的具体信号通路，为高表达GBP2与P53 PATHWAY、KRAS SIGNALING、APOPTOSIS等信号通路相关；高表达NEDD4L与G2M CHECKPOINT、TGF BETA SIGNALING、ADIPOGENESIS等信号通路相关；高表达PTPN11与PROTEIN SECRETION、ADIPOGENESIS、FATTY ACID METABOLISM等信号通路相关。

结论

新发现2型糖尿病、肥胖、非酒精性脂肪肝/非酒精性脂肪性肝炎、多囊卵巢综合征的共病基因及其代谢相关信号通路，为其治疗及诊断提供了新靶点及生物标志物。

关键词: 2型糖尿病, 肥胖, 非酒精性脂肪性肝炎, 多囊卵巢综合征, 致病因素

Objective

To explore the co-pathogenic genes and potential common molecular mechanisms of type 2 diabetes mellitus (T2DM), obesity, nonalcoholic steatohepatitis (NASH), and polycystic ovary syndrome (PCOS).

Methods

The gene expression datasets GSE20966, GSE17470, GSE88837, and GSE34526 were downloaded from the GEO database, and differentially expressed genes were identified with limma package. Then, the four groups of differentially expressed genes were intersected, and function enrichment analysis was performed to construct a protein-protein interaction (PPI) network. CIBERSORT algorithm was used to analyze the RNA-seq data of different patients, so as to infer the relative proportion of 22 kinds of immune infiltrating cells. GSVA algorithm was used to comprehensively score each gene set and evaluate the potential biological function changes of different samples.

Results

Five intersecting genes were identified, namely, PTPN3, GBP2, ARL1, NEDD4L, and PTPN11. PTPN11, NEDD4L, and GBP2 are related to insulin-related pathways. Furthermore, the specific signal pathways involved in the three core genes were verified by GSVA, which showed that the high expression of GBP2 is related to P53 PATHWAY, KRAS SIGNALING, APOPTOSIS, and other signal pathways. The high expression of NEDD4L is related to G2M CHECKPOINT, TGF BETA SIGNALING, and ADIPOGENESIS. High expression of PTPN11 is related to PROTEIN SECRETION, ADIPOGENESIS, FATTY ACID METABOLISM, and other signal pathways.

Conclusion

The newly discovered comorbid genes and the related metabolic signal pathways in T2DM, obesity, NASH, and PCOS provide new targets and biomarkers for their treatment and diagnosis.

Key words: Type 2 diabetes, Obesity, Nonalcoholic steatohepatitis, Polycystic ovary syndrome, Pathogenic factor

图1 差异基因Venn图

图2a 差异基因通路富集分析

图2b 关键基因PPI网络

图3 关键基因与胰岛素相关通路

图4 疾病组T cells CD8、Macrophages M2均显著上调

图5a 为GBP2与Macrophages M2显著正相关，与B cells memory、Macrophages M0显著负相关

图5b NEDD4L与Eosinophils显著正相关，与Monocytes、Macrophages M1显著负相关

图5c PTPN11与Dendritic cells activated、Eosinophils、B cells naïve显著正相关，与Monocytes、Plasma cells、Dendritic cells resting、T cells CD8显著负相关

图6a 高表达GBP2相关信号通路

图6b 高表达NEDD4L相关信号通路

图6c 高表达PTPN11相关通路

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Co-pathogenic genes and potential common molecular mechanisms of type 2 diabetes mellitus, obesity, nonalcoholic steatohepatitis, and polycystic ovary syndrome

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Co-pathogenic genes and potential common molecular mechanisms of type 2 diabetes mellitus, obesity, nonalcoholic steatohepatitis, and polycystic ovary syndrome