Background: The ulcerative colitis (UC) associated immune cell network was revealed by analyzing the immune cell composition of inflamed and uninflamed mucosal biopsy samples from the same patients with UC. For differentially expressed macrophages, the differentially expressed genes (DEGs), functional enrichment analyses, and protein–protein interaction (PPI) network was analyzed to understand further the role of macrophages in the occurrence and development of disease.

Methods: GSE 179285 dataset and GSE123141 dataset were downloaded from the GEO database. We used the CIBERSORT algorithm to map immune cell infiltration between paired inflamed and uninflamed intestinal mucosal biopsies. GO and KEGG functional enrichment analyses were used to analyze DEGs in intestinal macrophage populations. The PPI network was constructed by the Search Tool for the Retrieval of Interacting Genes (STRING) database. Immunohistochemistry and qPCR were used to verify hub genes in the mouse model of UC.

Results: The inflamed tissues had a higher infiltration of M1 macrophages and M0 macrophages. M2 macrophages, naive B cells, gamma delta T cells (γδT cells), and resting mast cells were more abundant in uninflamed tissues. Functional enrichment analyses showed that the 141 DEGs are involved in multiple processes in the inflammatory response. The three genes (LCN2, CXCL1, SAA1) had the highest degrees of connectivity and may be hub genes. LCN2 was significantly overexpressed in colitis tissues compared with normal control tissues in the mouse model of UC.

Conclusion: Changes in macrophages were notable in the inflamed mucosa of UC patients. 141 DEGs were entered into GO and KEGG functional enrichment analyses; three hub gene candidates were selected.

Highlights:

1. There were significant differences in the distribution of macrophages in the inflamed and uninflamed mucosa of UC patients.

2. Functional enrichment analyses of DEGs in UC-associated intestinal macrophages were displayed.

3. Three genes (LCN2, CXCL1, SAA1) were identified as hub gene candidates.

背景：通过分析来自同一 UC 患者的发炎和未发炎粘膜活检样本的免疫细胞组成，揭示了与溃疡性结肠炎 (UC) 相关的免疫细胞网络。对于差异表达的巨噬细胞，通过差异表达基因（DEG）、功能富集分析和蛋白质-蛋白质相互作用（PPI）网络进行分析，以进一步了解巨噬细胞在疾病发生和发展中的作用。

方法：从GEO数据库下载GSE 179285数据集和GSE123141数据集。我们使用 CIBERSORT 算法来绘制配对的发炎和未发炎肠粘膜活检之间的免疫细胞浸润图。使用GO和KEGG功能富集分析来分析肠道巨噬细胞群体中的DEG。PPI网络是通过相互作用基因检索搜索工具（STRING）数据库构建的。使用免疫组织化学和 qPCR 验证 UC 小鼠模型中的 hub 基因。

结果：炎症组织中M1型巨噬细胞和M0型巨噬细胞浸润较多。M2 巨噬细胞、初始 B 细胞、γδT 细胞（γδT 细胞）和静息肥大细胞在未发炎的组织中更为丰富。功能富集分析表明，141 个 DEG 参与炎症反应的多个过程。三个基因（LCN2、CXCL1、SAA1）具有最高程度的连接性，可能是枢纽基因。在UC小鼠模型中，与正常对照组织相比，LCN2在结肠炎组织中显着过表达。

结论： UC患者炎症黏膜中巨噬细胞变化显着。141个DEG进入GO和KEGG功能富集分析；选择了三个候选枢纽基因。

强调：

1. UC患者发炎和未发炎粘膜中巨噬细胞的分布存在显着差异。

2. 显示了 UC 相关肠道巨噬细胞中 DEG 的功能富集分析。

3. 三个基因（LCN2、CXCL1、SAA1）被确定为候选枢纽基因。