{"title":"糖尿病视网膜病变和非酒精性脂肪性肝病的免疫调节和细胞动力学探讨肝眼轴。","authors":"Shuyan Zhang, Jiajun Wu, Leilei Wang, Cheng Zhang, Yinjian Zhang, Yibin Feng","doi":"10.1186/s40246-025-00730-z","DOIUrl":null,"url":null,"abstract":"<p><strong>Background: </strong>Dysfunctions within the liver system are intricately linked to the progression of diabetic retinopathy (DR) and non-alcoholic fatty liver disease (NAFLD). This study leverages systematic analysis to elucidate the complex cross-talk and communication pathways among diverse cell populations implicated in the pathogenesis of DR and NAFLD.</p><p><strong>Methods: </strong>Single-cell RNA sequencing data for proliferative diabetic retinopathy (PDR) and NAFLD were retrieved from the Gene Expression Omnibus (GEO) database. Differential gene expression analysis was conducted and followed by pseudo-time analysis to delineate dynamic changes in core cells and differentially expressed genes (DEGs). CellChat was employed to predict intercellular communication and signaling pathways. Additionally, gene set enrichment and variation analyses (GSEA and GSVA) were performed to uncover key functional enrichments.</p><p><strong>Results: </strong>Our comparative analysis of the two datasets focused on T cells, macrophages and endothelial cells, revealing SYNE2 as a notable DEG. Notably, common genes including PYHIN1, SLC38A1, ETS1 (T cells), PPFIBP1, LIFR, HSPG2 (endothelial cells), and MSR1 (macrophages), emerged among the top 50 DEGs across these cell types. The CD45 signaling pathway was pivotal for T cells and macrophages, exerting profound effects on other cells in both PDR and NAFLD. Moreover, GSEA and GSVA underscored their involvement in cellular communication, immune modulation, energy metabolism, mitotic processes.</p><p><strong>Conclusion: </strong>The comprehensive investigation of T cells, macrophages, endothelial cells, and the CD45 signaling pathway advances our understanding of the intricate biological processes underpinning DR and NAFLD. This research underscores the imperative of exploring immune-related cell interactions, shedding light on novel therapeutic avenues in these disease contexts.</p>","PeriodicalId":13183,"journal":{"name":"Human Genomics","volume":"19 1","pages":"19"},"PeriodicalIF":3.8000,"publicationDate":"2025-02-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11866823/pdf/","citationCount":"0","resultStr":"{\"title\":\"Exploring the hepatic-ophthalmic axis through immune modulation and cellular dynamics in diabetic retinopathy and non-alcoholic fatty liver disease.\",\"authors\":\"Shuyan Zhang, Jiajun Wu, Leilei Wang, Cheng Zhang, Yinjian Zhang, Yibin Feng\",\"doi\":\"10.1186/s40246-025-00730-z\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Background: </strong>Dysfunctions within the liver system are intricately linked to the progression of diabetic retinopathy (DR) and non-alcoholic fatty liver disease (NAFLD). 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引用次数: 0
摘要
背景:肝系统功能障碍与糖尿病视网膜病变(DR)和非酒精性脂肪性肝病(NAFLD)的进展有着复杂的联系。本研究利用系统分析来阐明DR和NAFLD发病机制中涉及的不同细胞群之间复杂的串扰和通信途径。方法:从Gene Expression Omnibus (GEO)数据库中检索增殖性糖尿病视网膜病变(PDR)和NAFLD的单细胞RNA测序数据。进行差异基因表达分析,然后进行伪时间分析,以描绘核心细胞和差异表达基因(DEGs)的动态变化。CellChat用于预测细胞间通讯和信号通路。此外,进行基因集富集和变异分析(GSEA和GSVA)以揭示关键功能富集。结果:我们对T细胞、巨噬细胞和内皮细胞的两个数据集进行了比较分析,发现SYNE2是一个显著的DEG。值得注意的是,包括PYHIN1、SLC38A1、ETS1 (T细胞)、PPFIBP1、LIFR、HSPG2(内皮细胞)和MSR1(巨噬细胞)在内的常见基因出现在这些细胞类型的前50个DEG中。CD45信号通路是T细胞和巨噬细胞的关键,在PDR和NAFLD中对其他细胞都有深远的影响。此外,GSEA和GSVA强调了它们参与细胞通讯、免疫调节、能量代谢和有丝分裂过程。结论:对T细胞、巨噬细胞、内皮细胞和CD45信号通路的综合研究有助于我们了解DR和NAFLD复杂的生物学过程。这项研究强调了探索免疫相关细胞相互作用的必要性,揭示了这些疾病背景下新的治疗途径。
Exploring the hepatic-ophthalmic axis through immune modulation and cellular dynamics in diabetic retinopathy and non-alcoholic fatty liver disease.
Background: Dysfunctions within the liver system are intricately linked to the progression of diabetic retinopathy (DR) and non-alcoholic fatty liver disease (NAFLD). This study leverages systematic analysis to elucidate the complex cross-talk and communication pathways among diverse cell populations implicated in the pathogenesis of DR and NAFLD.
Methods: Single-cell RNA sequencing data for proliferative diabetic retinopathy (PDR) and NAFLD were retrieved from the Gene Expression Omnibus (GEO) database. Differential gene expression analysis was conducted and followed by pseudo-time analysis to delineate dynamic changes in core cells and differentially expressed genes (DEGs). CellChat was employed to predict intercellular communication and signaling pathways. Additionally, gene set enrichment and variation analyses (GSEA and GSVA) were performed to uncover key functional enrichments.
Results: Our comparative analysis of the two datasets focused on T cells, macrophages and endothelial cells, revealing SYNE2 as a notable DEG. Notably, common genes including PYHIN1, SLC38A1, ETS1 (T cells), PPFIBP1, LIFR, HSPG2 (endothelial cells), and MSR1 (macrophages), emerged among the top 50 DEGs across these cell types. The CD45 signaling pathway was pivotal for T cells and macrophages, exerting profound effects on other cells in both PDR and NAFLD. Moreover, GSEA and GSVA underscored their involvement in cellular communication, immune modulation, energy metabolism, mitotic processes.
Conclusion: The comprehensive investigation of T cells, macrophages, endothelial cells, and the CD45 signaling pathway advances our understanding of the intricate biological processes underpinning DR and NAFLD. This research underscores the imperative of exploring immune-related cell interactions, shedding light on novel therapeutic avenues in these disease contexts.
期刊介绍:
Human Genomics is a peer-reviewed, open access, online journal that focuses on the application of genomic analysis in all aspects of human health and disease, as well as genomic analysis of drug efficacy and safety, and comparative genomics.
Topics covered by the journal include, but are not limited to: pharmacogenomics, genome-wide association studies, genome-wide sequencing, exome sequencing, next-generation deep-sequencing, functional genomics, epigenomics, translational genomics, expression profiling, proteomics, bioinformatics, animal models, statistical genetics, genetic epidemiology, human population genetics and comparative genomics.