Department of Neurology, Washington University in St. Louis, St. Louis, MO 63110, USA.
Department of Radiology, Washington University in St. Louis, St. Louis, MO 63110, USA.
Brain. 2023 Jul 3;146(7):2944-2956. doi: 10.1093/brain/awac484.
Heterogeneity in progression to Alzheimer's disease (AD) poses challenges for both clinical prognosis and clinical trial implementation. Multiple AD-related subtypes have previously been identified, suggesting differences in receptivity to drug interventions. We identified early differences in preclinical AD biomarkers, assessed patterns for developing preclinical AD across the amyloid-tau-(neurodegeneration) [AT(N)] framework, and considered potential sources of difference by analysing the CSF proteome. Participants (n = 10) enrolled in longitudinal studies at the Knight Alzheimer Disease Research Center completed four or more lumbar punctures. These individuals were cognitively normal at baseline. Cerebrospinal fluid measures of amyloid-β (Aβ)42, phosphorylated tau (pTau181), and neurofilament light chain (NfL) as well as proteomics values were evaluated. Imaging biomarkers, including PET amyloid and tau, and structural MRI, were repeatedly obtained when available. Individuals were staged according to the amyloid-tau-(neurodegeneration) framework. Growth mixture modelling, an unsupervised clustering technique, identified three patterns of biomarker progression as measured by CSF pTau181 and Aβ42. Two groups (AD Biomarker Positive and Intermediate AD Biomarker) showed distinct progression from normal biomarker status to having biomarkers consistent with preclinical AD. A third group (AD Biomarker Negative) did not develop abnormal AD biomarkers over time. Participants grouped by CSF trajectories were re-classified using only proteomic profiles (AUCAD Biomarker Positive versus AD Biomarker Negative = 0.857, AUCAD Biomarker Positive versus Intermediate AD Biomarkers = 0.525, AUCIntermediate AD Biomarkers versus AD Biomarker Negative = 0.952). We highlight heterogeneity in the development of AD biomarkers in cognitively normal individuals. We identified some individuals who became amyloid positive before the age of 50 years. A second group, Intermediate AD Biomarkers, developed elevated CSF ptau181 significantly before becoming amyloid positive. A third group were AD Biomarker Negative over repeated testing. Our results could influence the selection of participants for specific treatments (e.g. amyloid-reducing versus other agents) in clinical trials. CSF proteome analysis highlighted additional non-AT(N) biomarkers for potential therapies, including blood-brain barrier-, vascular-, immune-, and neuroinflammatory-related targets.
阿尔茨海默病(AD)进展的异质性给临床预后和临床试验实施带来了挑战。先前已经确定了多种与 AD 相关的亚型,这表明药物干预的接受程度存在差异。我们在 AD 前临床生物标志物中发现了早期差异,评估了在淀粉样蛋白-tau-(神经退行性变)[AT(N)]框架下发展 AD 前临床的模式,并通过分析 CSF 蛋白质组来考虑差异的潜在来源。参加者(n = 10)在 Knight 阿尔茨海默病研究中心的纵向研究中完成了 4 次或更多的腰椎穿刺。这些人在基线时认知正常。评估了脑脊液中淀粉样蛋白-β(Aβ)42、磷酸化 tau(pTau181)和神经丝轻链(NfL)的测量值以及蛋白质组学值。当有可用的时,反复获得成像生物标志物,包括 PET 淀粉样蛋白和 tau 以及结构 MRI。根据淀粉样蛋白-tau-(神经退行性变)框架对个体进行分期。无监督聚类技术生长混合物建模,确定了 CSF pTau181 和 Aβ42 测量的三种生物标志物进展模式。两组(AD 生物标志物阳性和中间 AD 生物标志物)表现出从正常生物标志物状态到具有与 AD 前临床一致的生物标志物的明显进展。第三组(AD 生物标志物阴性)随时间推移并未发展出异常 AD 生物标志物。仅使用蛋白质组谱对根据 CSF 轨迹分组的参与者进行重新分类(AUCAD 生物标志物阳性与 AD 生物标志物阴性=0.857,AUCAD 生物标志物阳性与中间 AD 生物标志物=0.525,AUC 中间 AD 生物标志物与 AD 生物标志物阴性=0.952)。我们强调了认知正常个体中 AD 生物标志物发展的异质性。我们发现一些人在 50 岁之前就变成了淀粉样蛋白阳性。第二组,中间 AD 生物标志物,在成为淀粉样蛋白阳性之前显著升高 CSF ptau181。第三组在反复测试中为 AD 生物标志物阴性。我们的结果可能会影响临床试验中特定治疗方法(例如,减少淀粉样蛋白与其他药物)的参与者选择。CSF 蛋白质组分析突出了潜在治疗方法的其他非 AT(N)生物标志物,包括血脑屏障、血管、免疫和神经炎症相关靶点。