Interdisciplinary Neuroscience Program, University of Rhode Island, Kingston, RI, USA.
Butler Hospital Memory & Aging Program, Providence, RI, USA.
J Alzheimers Dis. 2024 Nov;102(1):89-98. doi: 10.1177/13872877241283692. Epub 2024 Oct 3.
Plasma biomarkers have recently emerged for the diagnosis, assessment, and disease monitoring of Alzheimer's disease (AD), but have yet to be fully validated in preclinical AD. In addition to AD pathologic plasma biomarkers (amyloid-β (Aβ) and phosphorylated tau (p-tau) species), a proteomic panel can discriminate between symptomatic AD and cognitively unimpaired older adults in a dementia clinic population.
Examine the added value of a plasma proteomic panel, validated in symptomatic AD, over standard AD pathologic plasma biomarkers and demographic and genetic (apolipoprotein () ɛ4 status) risk factors in detecting preclinical AD.
125 cognitively unimpaired older adults (mean age = 66 years) who completed Aβ PET and plasma draw were analyzed using multiple regression with Aβ PET status (positive versus negative) as the outcome to determine the best fit for predicting preclinical AD. Model 1 included age, education, and gender. Model 2 and 3 added predictors ɛ4 status (carrier versus non-carrier) and AD pathologic blood biomarkers (Aβ ratio, p-tau181), respectively. Random forest modeling established the 5 proteomic markers from the proteomic panel that best predicted Aβ PET status, and these markers were added in Model 4.
The best model for predicting Aβ PET status included age, years of education, ɛ4 status, Aβ ratio, and p-tau181. Adding the top 5 proteomic markers did not significantly improve the model.
Proteomic markers in plasma did not add predictive value to standard AD pathologic plasma biomarkers in predicting preclinical AD in this sample.
血浆生物标志物最近已被用于阿尔茨海默病（AD）的诊断、评估和疾病监测，但尚未在临床前 AD 中得到充分验证。除了 AD 病理血浆生物标志物（β淀粉样蛋白（Aβ）和磷酸化 tau（p-tau））外，蛋白质组学谱可在痴呆症门诊人群中区分有症状的 AD 和认知正常的老年人。
检查经过验证的血浆蛋白质组学谱在检测临床前 AD 方面相对于标准 AD 病理血浆生物标志物以及人口统计学和遗传（载脂蛋白 E4 状态）风险因素的附加价值。
分析了 125 名认知正常的老年人（平均年龄=66 岁）的 Aβ PET 和血浆样本，使用多元回归分析，将 Aβ PET 状态（阳性与阴性）作为结果，以确定预测临床前 AD 的最佳拟合度。模型 1 包括年龄、教育程度和性别。模型 2 和 3 分别添加了载脂蛋白 E4 状态（携带者与非携带者）和 AD 病理血液生物标志物（Aβ 比值、p-tau181）作为预测因子。随机森林模型确定了蛋白质组学谱中预测 Aβ PET 状态的最佳 5 个蛋白质标志物，并在模型 4 中添加了这些标志物。
预测 Aβ PET 状态的最佳模型包括年龄、受教育年限、载脂蛋白 E4 状态、Aβ 比值和 p-tau181。添加顶级 5 个蛋白质标志物并没有显著改善模型。
在该样本中，血浆蛋白质标志物在预测临床前 AD 方面并未为标准 AD 病理血浆生物标志物提供额外的预测价值。
