Department of Psychiatry and Neurochemistry, Institute of Neuroscience and Physiology, Sahlgrenska Academy at the University of Gothenburg, Mölndal, Sweden.
Graduate Program in Biological Sciences: Biochemistry, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil.
Nat Aging. 2023 Sep;3(9):1079-1090. doi: 10.1038/s43587-023-00471-5. Epub 2023 Aug 31.
Cost-effective strategies for identifying amyloid-β (Aβ) positivity in patients with cognitive impairment are urgently needed with recent approvals of anti-Aβ immunotherapies for Alzheimer's disease (AD). Blood biomarkers can accurately detect AD pathology, but it is unclear whether their incorporation into a full diagnostic workflow can reduce the number of confirmatory cerebrospinal fluid (CSF) or positron emission tomography (PET) tests needed while accurately classifying patients. We evaluated a two-step workflow for determining Aβ-PET status in patients with mild cognitive impairment (MCI) from two independent memory clinic-based cohorts (n = 348). A blood-based model including plasma tau protein 217 (p-tau217), age and APOE ε4 status was developed in BioFINDER-1 (area under the curve (AUC) = 89.3%) and validated in BioFINDER-2 (AUC = 94.3%). In step 1, the blood-based model was used to stratify the patients into low, intermediate or high risk of Aβ-PET positivity. In step 2, we assumed referral only of intermediate-risk patients to CSF Aβ42/Aβ40 testing, whereas step 1 alone determined Aβ-status for low- and high-risk groups. Depending on whether lenient, moderate or stringent thresholds were used in step 1, the two-step workflow overall accuracy for detecting Aβ-PET status was 88.2%, 90.5% and 92.0%, respectively, while reducing the number of necessary CSF tests by 85.9%, 72.7% and 61.2%, respectively. In secondary analyses, an adapted version of the BioFINDER-1 model led to successful validation of the two-step workflow with a different plasma p-tau217 immunoassay in patients with cognitive impairment from the TRIAD cohort (n = 84). In conclusion, using a plasma p-tau217-based model for risk stratification of patients with MCI can substantially reduce the need for confirmatory testing while accurately classifying patients, offering a cost-effective strategy to detect AD in memory clinic settings.
在最近批准了针对阿尔茨海默病(AD)的抗 Aβ 免疫疗法后,迫切需要制定出针对认知障碍患者中淀粉样蛋白-β(Aβ)阳性的具有成本效益的策略。血液生物标志物可以准确检测 AD 病理学,但尚不清楚将其纳入完整的诊断工作流程是否可以减少确认性脑脊液(CSF)或正电子发射断层扫描(PET)检查的次数,同时准确地对患者进行分类。我们评估了一种两步工作流程,用于确定来自两个独立记忆诊所队列(n=348)的轻度认知障碍(MCI)患者的 Aβ-PET 状态。在 BioFINDER-1 中开发了一种基于血液的模型,该模型包括血浆 tau 蛋白 217(p-tau217)、年龄和 APOE ε4 状态(曲线下面积(AUC)=89.3%),并在 BioFINDER-2 中进行了验证(AUC=94.3%)。在第 1 步中,使用基于血液的模型将患者分为 Aβ-PET 阳性的低、中、高风险组。在第 2 步中,我们假设仅对中间风险患者进行 CSF Aβ42/Aβ40 检测,而第 1 步单独确定低风险和高风险组的 Aβ 状态。根据第 1 步中使用的宽松、中度或严格阈值,两步工作流程的整体准确性分别为 88.2%、90.5%和 92.0%,同时减少了 85.9%、72.7%和 61.2%的必要 CSF 检测。在二次分析中,在认知障碍患者的 TRIAD 队列(n=84)中,使用 BioFINDER-1 模型的改编版本,用不同的血浆 p-tau217 免疫分析成功验证了两步工作流程。总之,使用基于血浆 p-tau217 的模型对 MCI 患者进行风险分层,可以大大减少确认性检查的需要,同时准确地对患者进行分类,为在记忆诊所环境中检测 AD 提供了一种具有成本效益的策略。