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多分析物蛋白质组学分析鉴定出临床前阿尔茨海默病患者血液中的神经炎症、脑血管和突触生物标志物。

Multi-analyte proteomic analysis identifies blood-based neuroinflammation, cerebrovascular and synaptic biomarkers in preclinical Alzheimer's disease.

机构信息

Department of Psychiatry, School of Medicine, University of Pittsburgh, 3811 O'Hara Street, Pittsburgh, PA, 15213, USA.

Department of Chemistry, University of Pittsburgh, Pittsburgh, PA, 15213, USA.

出版信息

Mol Neurodegener. 2024 Oct 10;19(1):68. doi: 10.1186/s13024-024-00753-5.

Abstract

BACKGROUND

Blood-based biomarkers are gaining grounds for the detection of Alzheimer's disease (AD) and related disorders (ADRDs). However, two key obstacles remain: the lack of methods for multi-analyte assessments and the need for biomarkers for related pathophysiological processes like neuroinflammation, vascular, and synaptic dysfunction. A novel proteomic method for pre-selected analytes, based on proximity extension technology, was recently introduced. Referred to as the NULISAseq CNS disease panel, the assay simultaneously measures ~ 120 analytes related to neurodegenerative diseases, including those linked to both core (i.e., tau and amyloid-beta (Aβ)) and non-core AD processes. This study aimed to evaluate the technical and clinical performance of this novel targeted proteomic panel.

METHODS

The NULISAseq CNS disease panel was applied to 176 plasma samples from 113 individuals in the MYHAT-NI cohort of predominantly cognitively normal participants from an economically underserved region in southwestern Pennsylvania, USA. Classical AD biomarkers, including p-tau181, p-tau217, p-tau231, GFAP, NEFL, Aβ40, and Aβ42, were independently measured using Single Molecule Array (Simoa) and correlations and diagnostic performances compared. Aβ pathology, tau pathology, and neurodegeneration (AT(N) statuses) were evaluated with [C] PiB PET, [F]AV-1451 PET, and an MRI-based AD-signature composite cortical thickness index, respectively. Linear mixed models were used to examine cross-sectional and Wilcoxon rank sum tests for longitudinal associations between NULISA and neuroimaging-determined AT(N) biomarkers.

RESULTS

NULISA concurrently measured 116 plasma biomarkers with good technical performance (97.2 ± 13.9% targets gave signals above assay limits of detection), and significant correlation with Simoa assays for the classical biomarkers. Cross-sectionally, p-tau217 was the top hit to identify Aβ pathology, with age, sex, and APOE genotype-adjusted AUC of 0.930 (95%CI: 0.878-0.983). Fourteen markers were significantly decreased in Aβ-PET + participants, including TIMP3, BDNF, MDH1, and several cytokines. Longitudinally, FGF2, IL4, and IL9 exhibited Aβ PET-dependent yearly increases in Aβ-PET + participants. Novel plasma biomarkers with tau PET-dependent longitudinal changes included proteins associated with neuroinflammation, synaptic function, and cerebrovascular integrity, such as CHIT1, CHI3L1, NPTX1, PGF, PDGFRB, and VEGFA; all previously linked to AD but only reliable when measured in cerebrospinal fluid. The autophagosome cargo protein SQSTM1 exhibited significant association with neurodegeneration after adjusting age, sex, and APOE ε4 genotype.

CONCLUSIONS

Together, our results demonstrate the feasibility and potential of immunoassay-based multiplexing to provide a comprehensive view of AD-associated proteomic changes, consistent with the recently revised biological and diagnostic framework. Further validation of the identified inflammation, synaptic, and vascular markers will be important for establishing disease state markers in asymptomatic AD.

摘要

背景

基于血液的生物标志物在阿尔茨海默病(AD)和相关疾病(ADRDs)的检测中得到了广泛应用。然而,目前仍存在两个关键障碍:缺乏多分析物评估方法和需要与神经炎症、血管和突触功能障碍等相关病理生理过程相关的生物标志物。最近引入了一种基于邻近延伸技术的新型蛋白质组学方法用于预筛选分析物。该方法被称为 NULISAseq CNS 疾病面板,可同时测量与神经退行性疾病相关的约 120 种分析物,包括与核心(即 tau 和淀粉样蛋白-β(Aβ))和非核心 AD 过程相关的分析物。本研究旨在评估这种新型靶向蛋白质组学面板的技术和临床性能。

方法

NULISAseq CNS 疾病面板应用于来自美国宾夕法尼亚州西南部经济欠发达地区的 MYHAT-NI 队列中 113 名认知正常参与者的 176 份血浆样本。经典 AD 生物标志物,包括 p-tau181、p-tau217、p-tau231、GFAP、NEFL、Aβ40 和 Aβ42,使用单分子阵列(Simoa)独立测量,并比较相关性和诊断性能。[C]PiB PET、[F]AV-1451 PET 和基于 MRI 的 AD 特征复合皮质厚度指数分别用于评估 Aβ 病理学、tau 病理学和神经退行性变(AT(N) 状态)。使用线性混合模型检查 NULISA 与神经影像学确定的 AT(N)生物标志物之间的横断面和 Wilcoxon 秩和检验的纵向关联。

结果

NULISA 同时测量了 116 种具有良好技术性能的血浆生物标志物(97.2±13.9%的目标信号超过检测限),与 Simoa 检测经典生物标志物的相关性显著。横断面研究显示,p-tau217 是识别 Aβ 病理学的最佳标志物,调整年龄、性别和 APOE 基因型后的 AUC 为 0.930(95%CI:0.878-0.983)。在 Aβ-PET+参与者中,有 14 种标志物显著降低,包括 TIMP3、BDNF、MDH1 和几种细胞因子。纵向研究显示,在 Aβ-PET+参与者中,FGF2、IL4 和 IL9 表现出与 Aβ PET 相关的逐年增加。与 tau PET 相关的纵向变化的新型血浆生物标志物包括与神经炎症、突触功能和脑血管完整性相关的蛋白质,如 CHIT1、CHI3L1、NPTX1、PGF、PDGFRB 和 VEGFA;所有这些标志物以前都与 AD 相关,但只有在脑脊液中测量时才可靠。自噬体货物蛋白 SQSTM1 在调整年龄、性别和 APOE ε4 基因型后,与神经退行性变显著相关。

结论

总之,我们的结果表明,基于免疫测定的多重分析具有提供 AD 相关蛋白质组变化综合视图的可行性和潜力,与最近修订的生物学和诊断框架一致。进一步验证鉴定出的炎症、突触和血管标志物对于确定无症状 AD 的疾病状态标志物将很重要。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/3159/11465638/f561af9419da/13024_2024_753_Fig1_HTML.jpg

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