Department of Endocrinology, Yunnan Province Clinical Medical Center for Endocrine and Metabolic Disease, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Department of Geriatric Medicine, The First Affiliated Hospital of Kunming Medical University, Kunming, China.
Front Endocrinol (Lausanne). 2023 Mar 9;14:1132194. doi: 10.3389/fendo.2023.1132194. eCollection 2023.
Type 2 diabetes (T2D) is a common chronic heterogeneous metabolic disorder. However, the roles of pyroptosis and infiltrating immune cells in islet dysfunction of patients with T2D have yet to be explored. In this study, we aimed to explore potential crucial genes and pathways associated with pyroptosis and immune infiltration in T2D.
To achieve this, we performed a conjoint analysis of three bulk RNA-seq datasets of islets to identify T2D-related differentially expressed genes (DEGs). After grouping the islet samples according to their ESTIMATE immune scores, we identified immune- and T2D-related DEGs. A clinical prediction model based on pyroptosis-related genes for T2D was constructed. Weighted gene co-expression network analysis was performed to identify genes positively correlated with pyroptosis-related pathways. A protein-protein interaction network was established to identify pyroptosis-related hub genes. We constructed miRNA and transcriptional networks based on the pyroptosis-related hub genes and performed functional analyses. Single-cell RNA-seq (scRNA-seq) was conducted using the GSE153885 dataset. Dimensionality was reduced using principal component analysis and t-distributed statistical neighbor embedding, and cells were clustered using Seurat. Different cell types were subjected to differential gene expression analysis and gene set enrichment analysis (GSEA). Cell-cell communication and pseudotime trajectory analyses were conducted using the samples from patients with T2D.
We identified 17 pyroptosis-related hub genes. We determined the abundance of 13 immune cell types in the merged matrix and found that these cell types were correlated with the 17 pyroptosis-related hub genes. Analysis of the scRNA-seq dataset of 1892 islet samples from patients with T2D and controls revealed 11 clusters. INS and IAPP were determined to be pyroptosis-related and candidate hub genes among the 11 clusters. GSEA of the 11 clusters demonstrated that the myc, G2M checkpoint, and E2F pathways were significantly upregulated in clusters with several differentially enriched pathways.
This study elucidates the gene signatures associated with pyroptosis and immune infiltration in T2D and provides a critical resource for understanding of islet dysfunction and T2D pathogenesis.
2 型糖尿病(T2D)是一种常见的慢性异质性代谢紊乱。然而,细胞焦亡和浸润免疫细胞在 T2D 患者胰岛功能障碍中的作用尚未得到探索。在本研究中,我们旨在探索与 T2D 中细胞焦亡和免疫浸润相关的潜在关键基因和途径。
为此,我们对三个胰岛的批量 RNA-seq 数据集进行了联合分析,以鉴定 T2D 相关的差异表达基因(DEG)。根据 ESTIMATE 免疫评分对胰岛样本进行分组后,我们鉴定了免疫和 T2D 相关的 DEG。构建了基于细胞焦亡相关基因的 T2D 临床预测模型。进行了加权基因共表达网络分析,以鉴定与细胞焦亡相关途径呈正相关的基因。建立了蛋白质-蛋白质相互作用网络,以鉴定细胞焦亡相关的枢纽基因。基于细胞焦亡相关枢纽基因构建了 miRNA 和转录网络,并进行了功能分析。使用 GSE153885 数据集进行单细胞 RNA-seq(scRNA-seq)。使用主成分分析和 t 分布统计邻域嵌入对数据进行降维,使用 Seurat 对细胞进行聚类。对不同的细胞类型进行差异基因表达分析和基因集富集分析(GSEA)。使用来自 T2D 患者的样本进行细胞-细胞通讯和伪时间轨迹分析。
我们鉴定了 17 个细胞焦亡相关的枢纽基因。我们确定了合并矩阵中 13 种免疫细胞类型的丰度,并发现这些细胞类型与 17 个细胞焦亡相关的枢纽基因相关。对来自 T2D 患者和对照的 1892 个胰岛样本的 scRNA-seq 数据集进行分析,发现了 11 个簇。在这 11 个簇中,INS 和 IAPP 被确定为与细胞焦亡相关的候选枢纽基因。对 11 个簇的 GSEA 分析表明,在具有多个差异富集途径的簇中,myc、G2M 检查点和 E2F 途径显著上调。
本研究阐明了与 T2D 中细胞焦亡和免疫浸润相关的基因特征,并为理解胰岛功能障碍和 T2D 发病机制提供了重要资源。