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. 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 [11C] PiB PET, [18F]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. 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. 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.

中文翻译：

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多分析物蛋白质组学分析可识别临床前阿尔茨海默病中基于血液的神经炎症、脑血管和突触生物标志物


基于血液的生物标志物在阿尔茨海默病 （AD） 和相关疾病 （ADRD） 的检测中越来越受欢迎。然而，仍然存在两个主要障碍：缺乏多分析物评估的方法，以及需要相关病理生理过程（如神经炎症、血管和突触功能障碍）的生物标志物。最近推出了一种基于邻近扩展技术的预选分析物的新型蛋白质组学方法。该检测被称为 NULISAseq CNS 疾病面板，可同时测量 ~ 120 种与神经退行性疾病相关的分析物，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。NULISAseq CNS 疾病面板应用于 MYHAT-NI 队列中 113 人的 176 个血浆样本，这些参与者来自美国宾夕法尼亚州西南部经济服务不足地区，主要是认知正常的参与者。使用单分子阵列 （Simoa） 独立测量经典 AD 生物标志物，包括 p-tau181 、 p-tau217 、 p-tau231 、 GFAP 、 NEFL 、 Aβ40 和 Aβ42 ，并比较相关性和诊断性能。分别用 [11C] PiB PET 、 [18F] AV-1451 PET 和基于 MRI 的 AD 特征复合皮质厚度指数评估 Aβ 病理、 tau 病理和神经变性 （AT（N） 状态）。线性混合模型用于检查 NULISA 和神经影像学确定的 AT（N） 生物标志物之间纵向关联的横截面和 Wilcoxon 秩和检验。NULISA 同时测量了 116 个具有良好技术性能的血浆生物标志物 （97.2 ± 13.9% 的靶标给出的信号高于检测限），并且与经典生物标志物的 Simoa 检测显著相关。从横断面上看，p-tau217 是鉴定 Aβ 病理学的首要结果，年龄、性别和 APOE 基因型调整后的 AUC 为 0.930 （95%CI： 0.878–0.983）。Aβ-PET + 参与者中有 14 个标志物显着降低，包括 TIMP3 、 BDNF 、 MDH1 和几种细胞因子。纵向上，FGF2 、 IL4 和 IL9 在 Aβ-PET + 参与者中表现出 Aβ PET 依赖性年增加。具有 tau PET 依赖性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;所有这些都以前与 AD 有关，但仅在脑脊液中测量时才可靠。自噬体转运蛋白 SQSTM1 在调整年龄、性别和 APOE ε4 基因型后与神经退行性变呈显著关联。总之，我们的结果证明了基于免疫测定的多重分析的可行性和潜力，以提供与 AD 相关的蛋白质组学变化的全面视图，与最近修订的生物学和诊断框架一致。进一步验证已识别的炎症、突触和血管标志物对于在无症状 AD 中建立疾病状态标志物非常重要。