Park Min-Koo, Ahn Jinhyun, Lim Jin-Muk, Hwang Sung-Joo, Kim Keun-Cheol
Department of Biological Sciences, College of Natural Sciences, Kangwon National University, Kangwon, 24341, Republic of Korea.
Genomics Institute, Erom, Inc, Kangwon, 24427, Republic of Korea.
Geroscience. 2025 Sep 6. doi: 10.1007/s11357-025-01869-2.
Alzheimer's disease (AD) represents a growing global health burden, underscoring the urgent need for reliable diagnostic and prognostic biomarkers. Although several disease-modifying treatments have recently become available, their effects remain limited, as they primarily delay rather than halt disease progression. Thus, the early and accurate identification of individuals at elevated risk for conversion to AD dementia is crucial to maximize the effectiveness of these therapies and to facilitate timely intervention strategies. Baseline plasma concentrations of amyloid beta 40 (Aβ40), amyloid beta 42 (Aβ42), glial fibrillary acidic protein (GFAP), neurofilament light chain (NFL), and tau phosphorylated at residue 181 and 217 (pTau181, pTau217) were quantified in 233 non-demented participants from the Alzheimer's Disease Neuroimaging Initiative (ADNI) and followed for up to 11 years. Covariates included demographic variables and neuropsychological measures. Longitudinal cognitive trajectories were modelled with linear mixed-effects models (LMM), and the risk of progression to AD dementia was evaluated with logistic regression and Cox proportional-hazards analyses. Longitudinally, higher baseline plasma levels of GFAP, NFL, pTau181, and pTau217 independently predicted steeper cognitive decline. Cross-sectional analyses demonstrated significant associations of pTau217, pTau181, and Aβ42 with baseline memory impairment. A logistic regression model incorporating five plasma biomarkers-Aβ42, GFAP, NFL, pTau181, and pTau217-demonstrated robust predictive accuracy for discrimination of future converters to AD dementia. The addition of demographic variables and a baseline memory score further improved model specificity and positive predictive value. These findings support the utility of a concise plasma biomarker panel comprising Aβ42, GFAP, NFL, pTau181, and pTau217 for predicting both longitudinal cognitive deterioration and conversion to AD dementia. This less-invasive blood-based panel could serve as a practical triage tool to enrich clinical trials and facilitate timely therapeutic interventions with emerging disease-modifying treatments.
阿尔茨海默病(AD)给全球健康带来日益沉重的负担,凸显了对可靠的诊断和预后生物标志物的迫切需求。尽管最近有几种疾病修饰疗法可供使用,但其效果仍然有限,因为它们主要是延缓而非阻止疾病进展。因此,早期准确识别有转化为AD痴呆高风险的个体对于最大化这些疗法的有效性以及促进及时的干预策略至关重要。在来自阿尔茨海默病神经影像倡议(ADNI)的233名非痴呆参与者中,对淀粉样蛋白β40(Aβ40)、淀粉样蛋白β42(Aβ42)、胶质纤维酸性蛋白(GFAP)、神经丝轻链(NFL)以及在第181和217位残基磷酸化的tau蛋白(pTau181、pTau217)的基线血浆浓度进行了定量,并随访长达11年。协变量包括人口统计学变量和神经心理学测量指标。使用线性混合效应模型(LMM)对纵向认知轨迹进行建模,并通过逻辑回归和Cox比例风险分析评估进展为AD痴呆的风险。纵向来看,较高的基线血浆GFAP、NFL、pTau181和pTau217水平独立预测了更陡峭的认知衰退。横断面分析表明pTau217、pTau181和Aβ42与基线记忆损害存在显著关联。一个包含五种血浆生物标志物——Aβ42、GFAP、NFL、pTau181和pTau217——的逻辑回归模型在区分未来转化为AD痴呆的个体方面显示出强大的预测准确性。加入人口统计学变量和基线记忆评分进一步提高了模型的特异性和阳性预测值。这些发现支持了一个简洁的血浆生物标志物组合(包括Aβ42、GFAP、NFL、pTau181和pTau217)在预测纵向认知恶化和转化为AD痴呆方面的实用性。这种侵入性较小的基于血液的组合可作为一种实用的分类工具,以丰富临床试验并促进使用新兴的疾病修饰疗法进行及时的治疗干预。