生物信息学分析昼夜节律基因脑细胞类型特异性改变对衰老的影响  

Bioinformatics analysis of circadian rhythm gene alterations in relation to brain-cell types and their impact on aging

作　　者：韩雪 顾小萍[1] HAN Xue;CU Xiaoping(Department of Anesthesiology,Nanjing Drum Tower Hospital,Affiliated Hospital of Medical School,Nanjing University,Nanjing 210008,China;Medical School,Nanjing University,Nanjing 210093)

机构地区：[1]南京大学医学院附属鼓楼医院,麻醉科,南京210008 [2]南京大学医学院,南京210093

出　　处：《中国比较医学杂志》2025年第3期15-29,共15页Chinese Journal of Comparative Medicine

基　　金：国家自然科学基金面上项目(82171193);江苏省医学重点学科项目(ZDXK202232)。

摘　　要：目的 面对人口老龄化带来的挑战,衰老相关神经退行性疾病的发病率持续攀升,而其发病机制尚不明晰,治疗手段有限。本研究聚焦于衰老这一发病基础,采用生物信息学方法,探索衰老过程中脑细胞类型特异性基因表达变化及其对衰老的影响,为深入研究脑衰老的生物学机制提供更多依据。方法 利用R软件中的Seurat对青年和老年小鼠脑组织单细胞测序数据集GSE169606进行整合、质量控制、数据标准化和统计分析,通过细胞类型注释与差异基因分析,识别出不同细胞类型下的差异表达基因,并借助基因本体论(Gene Ontology, GO)和京都基因与基因组百科全书(Kyoto Encyclopedia of Genes and Genomes, KEGG)进行功能注释和富集分析,通过蛋白质相互作用网络(protein-protein interaction, PPI)分析差异基因之间的相互作用,最后利用cytoHubba插件中MCC、MNC、DMNC和Dgree 4种算法确定每种细胞中的枢纽基因。结果 通过细胞注释共确定了13个细胞种类,在老年组和青年组比较后,本研究重点对神经元、小胶质细胞、星形胶质细胞和内皮细胞4种主要细胞类型中筛选出的差异基因进行了深入分析。GO分析发现神经元、星形胶质细胞及内皮细胞的差异基因均显著富集于昼夜节律相关生物学途径,KEGG分析发现小胶质细胞和内皮细胞的差异基因均在昼夜节律相关信号通路富集,PPI分析发现神经元、小胶质细胞和内皮细胞的差异基因生物学网络均显著富集于昼夜节律功能聚类模块。进一步,通过对4种算法取交集,筛选出上述细胞类型中的核心基因,在这一过程中,本研究还发现小胶质细胞、星形胶质细胞以及内皮细胞中昼夜节律基因的特异性变化。结论 本研究运用单细胞转录组学技术,揭示了衰老过程中神经元、小胶质细胞、星形胶质细胞及内皮细胞中基因差异表达情况。鉴定出了小胶质细胞、星形胶质细Objective With the intensification of population aging, the incidence of aging-related neurodegenerative diseases continues to rise, however, their pathogenesis remains elusive and therapeutic options are limited. This study used bioinformatics approaches to explore brain cell-type-specific changes in gene expression during brain aging and their impacts, to provide further insights into the biological mechanisms of brain aging. Methods We analyzed single-cell sequencing datasets(GSE169606) from young and old mouse brains, including integration, quality control, normalization, conduct cell-type annotation and differential gene expression analysis to identify differentially expressed genes(DEGs) across various cell types, using the Seurat package in R software. Gene Ontology(GO) and Kyoto Encyclopedia of Genes and Genomes(KEGG) were used for functional annotation and enrichment analyses, and interactions between DEGs were analyzed by protein-protein interaction(PPI) networks. The hub genes in each cell type were identified using the MCC, MNC, DMNC, and Dgree algorithms in the cyto Hubba plugin. Results A total of 13 cell types were identified through cell annotation. After comparing the aged and young groups, we focused on in-depth analyses of the DEGs screened from four major cell types: neurons, microglia, astrocytes, and endothelia. GO analysis revealed that DEGs in neurons, astrocytes, and endothelial cells were significantly enriched in biological pathways related to circadian rhythm, and KEGG analysis indicated that DEGs in microglia and endothelial cells were enriched in circadian rhythm-related signaling pathways. PPI analysis also demonstrated that the biological networks of DEGs in neurons, microglia, and endothelial cells were significantly enriched in circadian rhythm functional clustering modules. Furthermore, based on the intersection of the four algorithms, we identified core genes within these cell types and also identified specific variations in circadian rhythm genes in microglia, astrocytes, and

关 键 词：昼夜节律基因 昼夜节律 衰老 脑细胞 生物信息学 

分 类 号：R-33[医药卫生]