Abstract：
UNASSIGNED: Early-onset Alzheimer\'s disease (EOAD) exhibits a notable degree of heterogeneity as compared to late-onset Alzheimer\'s disease (LOAD). The proteins and pathways contributing to the pathophysiology of EOAD still need to be completed and elucidated.
UNASSIGNED: Using correlation network analysis and machine learning to analyze cerebrospinal fluid (CSF) proteomics data to identify potential biomarkers and pathways associated with EOAD.
UNASSIGNED: We employed mass spectrometry to conduct CSF proteomic analysis using the data-independent acquisition method in a Chinese cohort of 139 CSF samples, including 40 individuals with normal cognition (CN), 61 patients with EOAD, and 38 patients with LOAD. Correlation network analysis of differentially expressed proteins was performed to identify EOAD-associated pathways. Machine learning assisted in identifying crucial proteins differentiating EOAD. We validated the results in an Western cohort and examined the proteins expression by enzyme-linked immunosorbent assay (ELISA) in additional 9 EOAD, 9 LOAD, and 9 CN samples from our cohort.
UNASSIGNED: We quantified 2,168 CSF proteins. Following adjustment for age and sex, EOAD exhibited a significantly greater number of differentially expressed proteins than LOAD compared to CN. Additionally, our data indicates that EOAD may exhibit more pronounced synaptic dysfunction than LOAD. Three potential biomarkers for EOAD were identified: SH3BGRL3, LRP8, and LY6 H, of which SH3BGRL3 also accurately classified EOAD in the Western cohort. LY6 H reduction was confirmed via ELISA, which was consistent with our proteomic results.
UNASSIGNED: This study provides a comprehensive profile of the CSF proteome in EOAD and identifies three potential EOAD biomarker proteins.
UNASSIGNED: Using correlation network analysis and machine learning to analyze cerebrospinal fluid (CSF) proteomics data to identify potential biomarkers and pathways associated with EOAD.
UNASSIGNED: We employed mass spectrometry to conduct CSF proteomic analysis using the data-independent acquisition method in a Chinese cohort of 139 CSF samples, including 40 individuals with normal cognition (CN), 61 patients with EOAD, and 38 patients with LOAD. Correlation network analysis of differentially expressed proteins was performed to identify EOAD-associated pathways. Machine learning assisted in identifying crucial proteins differentiating EOAD. We validated the results in an Western cohort and examined the proteins expression by enzyme-linked immunosorbent assay (ELISA) in additional 9 EOAD, 9 LOAD, and 9 CN samples from our cohort.
UNASSIGNED: We quantified 2,168 CSF proteins. Following adjustment for age and sex, EOAD exhibited a significantly greater number of differentially expressed proteins than LOAD compared to CN. Additionally, our data indicates that EOAD may exhibit more pronounced synaptic dysfunction than LOAD. Three potential biomarkers for EOAD were identified: SH3BGRL3, LRP8, and LY6 H, of which SH3BGRL3 also accurately classified EOAD in the Western cohort. LY6 H reduction was confirmed via ELISA, which was consistent with our proteomic results.
UNASSIGNED: This study provides a comprehensive profile of the CSF proteome in EOAD and identifies three potential EOAD biomarker proteins.
摘要：
与晚发性阿尔茨海默病(LOAD)相比,早发性阿尔茨海默病(EOAD)表现出显著程度的异质性。有助于EOAD病理生理学的蛋白质和途径仍需要完成和阐明。
■使用相关网络分析和机器学习分析脑脊液（CSF）蛋白质组学数据，以识别与EOAD相关的潜在生物标志物和途径。
■我们采用质谱技术对中国139份脑脊液样本进行脑脊液蛋白质组分析，采用独立于数据的采集方法，包括40名认知正常的人（CN），61例EOAD患者，和38名负载患者。进行差异表达蛋白的相关网络分析以鉴定EOAD相关途径。机器学习有助于识别区分EOAD的关键蛋白质。我们在Western队列中验证了结果，并通过酶联免疫吸附测定（ELISA）检查了另外9个EOAD中的蛋白质表达，9LOAD,和我们队列中的9个CN样本。
■我们定量了2,168种CSF蛋白。根据年龄和性别调整后，与CN相比,EOAD表现出比LOAD显著更多数量的差异表达蛋白。此外,我们的数据表明,EOAD可能比LOAD表现出更明显的突触功能障碍.确定了三种潜在的EOAD生物标志物：SH3BGRL3，LRP8和LY6H，其中SH3BGRL3还在西方队列中准确地对EOAD进行了分类。通过ELISA确认LY6H减少，这与我们的蛋白质组学结果一致。
■这项研究提供了EOAD中CSF蛋白质组的全面概况，并鉴定了三种潜在的EOAD生物标记蛋白。
■使用相关网络分析和机器学习分析脑脊液（CSF）蛋白质组学数据，以识别与EOAD相关的潜在生物标志物和途径。
■我们采用质谱技术对中国139份脑脊液样本进行脑脊液蛋白质组分析，采用独立于数据的采集方法，包括40名认知正常的人（CN），61例EOAD患者，和38名负载患者。进行差异表达蛋白的相关网络分析以鉴定EOAD相关途径。机器学习有助于识别区分EOAD的关键蛋白质。我们在Western队列中验证了结果，并通过酶联免疫吸附测定（ELISA）检查了另外9个EOAD中的蛋白质表达，9LOAD,和我们队列中的9个CN样本。
■我们定量了2,168种CSF蛋白。根据年龄和性别调整后，与CN相比,EOAD表现出比LOAD显著更多数量的差异表达蛋白。此外,我们的数据表明,EOAD可能比LOAD表现出更明显的突触功能障碍.确定了三种潜在的EOAD生物标志物：SH3BGRL3，LRP8和LY6H，其中SH3BGRL3还在西方队列中准确地对EOAD进行了分类。通过ELISA确认LY6H减少，这与我们的蛋白质组学结果一致。
■这项研究提供了EOAD中CSF蛋白质组的全面概况，并鉴定了三种潜在的EOAD生物标记蛋白。
