de Geus Matthijs B, Nairn Angus C, Arnold Steven E, Carlyle Becky C
Department of Neurology, Massachusetts General Hospital, Charlestown, MA 02129, USA.
Cell & Chemical Biology, Leiden University Medical Center, 2333ZC Leiden, The Netherlands.
Brain Commun. 2025 May 23;7(3):fcaf202. doi: 10.1093/braincomms/fcaf202. eCollection 2025.
Alzheimer's disease is a multifaceted neurodegenerative disorder, with diverse underlying pathophysiological processes extending beyond amyloid-β and tau accumulation. The heterogeneity of Alzheimer's disease necessitates the identification of a broad array of biomarkers that capture the diverse mechanisms contributing to disease onset and progression. In this study, we systematically compiled and analysed cerebrospinal fluid proteomics data from omics studies utilizing mass spectrometry, Olink, or SomaScan platforms. Systematic literature searches for each platform revealed a total of 264 studies. From this, a set of 18 studies were selected based on sample size, number of markers analysed, and open data availability. We found a total of 1,448 differentially expressed proteins between Alzheimer's disease and amyloid negative controls across these datasets, with 635 being found in more than one study. A 'top' set of 61 differentially expressed proteins were consistently reported in at least six studies. Clustering and functional enrichment analysis of the top differentially expressed proteins indicated involvement in metabolic regulation, glutathione metabolism and proteins of the 14-3-3 family, reflecting importance of reactive oxygen species (ROS) response. Synaptic signalling processes were found to generally be downregulated. We further integrated the top differentially expressed proteins with results from a study on familial Alzheimer's disease cerebrospinal fluid to assess at which stage of disease progression these proteins change, highlighting markers shared between sporadic and familial Alzheimer's disease datasets. Lastly, we examine the overlap of the top differentially expressed proteins between cerebrospinal fluid and brain tissue using a publicly available database. This analysis provides a comprehensive overview of the Alzheimer's disease cerebrospinal fluid proteomic landscape, indicating changes in key pathways and cellular processes associated with Alzheimer's disease pathology. By integrating data from different platforms, we highlight reproducible protein changes that may serve as promising candidates for further biomarker research aimed at improving patient stratification, tracking disease progression, and assessing therapeutic interventions.
阿尔茨海默病是一种多方面的神经退行性疾病,其潜在的病理生理过程多种多样,不仅限于淀粉样蛋白-β和tau蛋白的积累。阿尔茨海默病的异质性使得有必要识别出一系列广泛的生物标志物,这些生物标志物能够捕捉导致疾病发生和进展的多种机制。在本研究中,我们系统地整理和分析了来自利用质谱、Olink或SomaScan平台的组学研究的脑脊液蛋白质组学数据。对每个平台进行的系统文献检索共发现264项研究。据此,基于样本量、分析的标志物数量和开放数据的可用性,选择了18项研究。在这些数据集中,我们总共发现了1448种在阿尔茨海默病和淀粉样蛋白阴性对照之间差异表达的蛋白质,其中635种在不止一项研究中被发现。至少六项研究一致报告了一组“顶级”的61种差异表达蛋白质。对顶级差异表达蛋白质的聚类和功能富集分析表明,它们参与代谢调节、谷胱甘肽代谢以及14-3-3家族的蛋白质,反映了活性氧(ROS)反应的重要性。发现突触信号传导过程总体上被下调。我们进一步将顶级差异表达蛋白质与一项关于家族性阿尔茨海默病脑脊液的研究结果相结合,以评估这些蛋白质在疾病进展的哪个阶段发生变化,突出散发性和家族性阿尔茨海默病数据集之间共有的标志物。最后,我们使用一个公开可用的数据库检查脑脊液和脑组织之间顶级差异表达蛋白质的重叠情况。该分析全面概述了阿尔茨海默病脑脊液蛋白质组学概况,表明与阿尔茨海默病病理相关的关键途径和细胞过程发生了变化。通过整合来自不同平台的数据,我们突出了可重复的蛋白质变化,这些变化可能成为进一步生物标志物研究的有希望的候选者,旨在改善患者分层、跟踪疾病进展和评估治疗干预措施。