BACKGROUND Models of Alzheimer's disease (AD) pathophysiology posit that amyloidosis [A] precedes and accelerates tau pathology [T] that leads to neurodegeneration [N]. Besides this A-T-N sequence, other biomarker sequences are possible. This current work investigates and compares the longitudinal trajectories of Alzheimer's ATN biomarker profiles in non-demented elderly adults from the Alzheimer's Disease Neuroimaging Initiative (ADNI) cohort. METHODS Based on the ATN classification system, 262 individuals were identified before dementia diagnosis and accompanied by baseline and follow-up data of ATN biomarkers (CSF Aβ42, p-tau, and FDG-PET). We recorded the conversion processes in ATN biomarkers during follow-up, then analyzed the possible longitudinal trajectories and estimated the conversion rate and temporal evolution of biomarker changes. To evaluate how biomarkers changed over time, we used linear mixed-effects models. RESULTS During a 6-120-month follow-up period, there were four patterns of longitudinal changes in Alzheimer's ATN biomarker profiles, from all negative to positive through the course of the disease. The most common pattern is that A pathology biomarker first emerges. As well as the classical A-T-N sequence, other "A-first," "T-first," and "N-first" biomarker pathways were found. The N-A-T sequence had the fastest rate of pathological progression (mean 65.00 months), followed by A-T-N (mean 67.07 months), T-A-N (mean 68.85 months), and A-N-T sequences (mean 98.14 months). CONCLUSIONS Our current work presents a comprehensive analysis of longitudinal trajectories of Alzheimer's ATN biomarkers in non-demented elderly adults. Stratifying disease into subtypes depending on the temporal evolution of biomarkers will benefit the early recognition and treatment.

中文翻译：

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老年痴呆症患者中阿尔茨海默氏病ATN生物标记物的纵向轨迹。

背景技术阿尔茨海默氏病（AD）的病理生理学模型假定淀粉样变性[A]先于并加速tau病理[T]，其导致神经变性[N]。除了该ATN序列之外，其他生物标记序列也是可能的。这项当前的研究调查并比较了阿尔茨海默氏病神经影像学倡议（ADNI）队列中非痴呆老年人的阿尔茨海默氏病ATN生物标志物谱的纵向轨迹。方法基于ATN分类系统，在痴呆症诊断之前鉴定出262名个体，并伴有ATN生物标志物（CSFAβ42，p-tau和FDG-PET）的基线和随访数据。在随访期间，我们在ATN生物标志物中记录了转化过程，然后分析可能的纵向轨迹，并估算生物标志物变化的转化率和时间演变。为了评估生物标志物随时间的变化，我们使用了线性混合效应模型。结果在6-120个月的随访期内，阿尔茨海默氏病ATN生物标志物谱存在四种纵向变化模式，从整个疾病过程的阴性到阳性。最常见的模式是病理生物标志物首先出现。除了经典的ATN序列外，还发现了其他“ A优先”，“ T优先”和“ N优先”生物标志物途径。NAT序列的病理进展速度最快（平均65.00个月），其次是ATN（平均67.07个月），TAN（平均68.85个月）和ANT序列（平均98.14个月）。结论我们目前的工作提供了对非痴呆老年人的阿尔茨海默氏病ATN生物标志物纵向轨迹的综合分析。根据生物标志物的时间演变将疾病分为亚型将有利于早期识别和治疗。