Brown Christopher A, Mundada Nidhi S, Cousins Katheryn A Q, Sadeghpour Niyousha, Lyu Xueying, McGrew Emily, Korecka Magdalena, Chen-Plotkin Alice, Xie Long, Wisse Laura E M, Detre John A, McMillan Corey T, Lee Edward B, Nasrallah Ilya M, Das Sandhitsu R, Mechanic-Hamilton Dawn, Yushkevich Paul A, Shaw Leslie M, Wolk David A
Department of Neurology, University of Pennsylvania, Philadelphia, PA, USA.
Department of Bioengineering, University of Pennsylvania, Philadelphia, PA, USA.
medRxiv. 2025 Jul 25:2025.07.25.25332195. doi: 10.1101/2025.07.25.25332195.
The heterogeneous course of Alzheimer's disease makes it difficult to predict individuals' cognitive trajectories, which is particularly important in the era of disease modifying therapy. Identifying individuals more likely to have co-pathology and differing disease courses using clinically practical tools remains a critical gap.
To evaluate tau-clinical mismatch for identifying resilient and vulnerable individuals and compare levels of co-pathology and clinical trajectories between groups.
Participants were selected from the Alzheimer's Disease Neuroimaging Initiative (ADNI, inclusion from 2005-2024), Penn Alzheimer's Disease Research Center Cohort (Penn-ADRC, inclusion from 2002-2025), and Penn Anti-amyloid Therapy Monitoring (Penn-ATM) cohort (inclusion from 2024-2025). All participants were amyloid-β positive, had clinical assessment, and measures of Tau-PET or plasma p-tau available.
Clinical assessment (CDR-SB) and tau burden (tau-PET or p-tau) for mismatch group classification.
Cross-sectional measures of neurodegeneration (medial temporal lobe volume and thickness, cortical thickness, TAR DNA-binding protein 43 [TDP-43] imaging signature), α-synuclein cerebrospinal fluid seed-amplification assay, longitudinal CDR-SB.
365 ADNI Tau-PET participants (ages 55-93, 52.6% women) and 524 ADNI p-tau participants (ages 56-95, 49.0% women) were used to generate tau-clinical mismatch models with 55.6-57.1% classified as canonical (CDR-SB ~ Tau), 23.7-24.7% as resilient (CDR-SB < Tau), and 19.3-19.7% as vulnerable (CDR-SB > Tau). Groups showed diverging clinical courses with earlier cognitive impairment seen in vulnerable groups and later impairment in resilient groups. Vulnerable groups showed higher frequencies of co-pathology, with TDP-43 neurodegeneration patterns and α-synuclein positivity. Similar findings were seen when applying these models to an independent dataset of 244 individuals (54-92 age, 57.0% women) in Penn-ADRC. Finally, these models were applied to a cohort receiving anti-amyloid therapy to show the utility of this method for predicting individual cognitive trajectories during therapy.
Tau-clinical mismatch identifies individuals more likely to harbor co-pathology and have diverging clinical trajectories. Plasma-based models produced similar results to Tau-PET models and could be replicated in independent datasets. These models provide an important tool that can be implemented in clinical practice to provide improved individualized prognosis and, potentially, monitoring of response to disease-modifying therapy.
阿尔茨海默病病程的异质性使得难以预测个体的认知轨迹，在疾病修饰治疗时代这一点尤为重要。利用临床实用工具识别更可能存在共病病理和不同疾病病程的个体仍然是一个关键差距。
评估tau-临床不匹配以识别有弹性和易损个体，并比较各组之间的共病病理水平和临床轨迹。
设计、地点和参与者：参与者选自阿尔茨海默病神经影像倡议（ADNI，2005年至2024年纳入）、宾夕法尼亚大学阿尔茨海默病研究中心队列（Penn-ADRC，2002年至2025年纳入）和宾夕法尼亚大学抗淀粉样蛋白治疗监测（Penn-ATM）队列（2024年至2025年纳入）。所有参与者均为淀粉样β蛋白阳性，有临床评估，且可获得Tau-PET或血浆p-tau测量值。
用于不匹配组分类的临床评估（CDR-SB）和tau负荷（tau-PET或p-tau）。
神经退行性变的横断面测量指标（内侧颞叶体积和厚度、皮质厚度、TAR DNA结合蛋白43 [TDP-43]成像特征）、α-突触核蛋白脑脊液种子扩增试验、纵向CDR-SB。
365名ADNI Tau-PET参与者（年龄55 - 93岁，52.6%为女性）和524名ADNI p-tau参与者（年龄56 - 95岁，49.0%为女性）被用于生成tau-临床不匹配模型，其中55.6 - 57.1%被分类为典型（CDR-SB ~ Tau），23.7 - 24.7%为有弹性（CDR-SB < Tau），19.3 - 19.7%为易损（CDR-SB > Tau）。各组显示出不同的临床病程，易损组出现较早的认知障碍，有弹性组出现较晚的障碍。易损组共病病理的频率更高，具有TDP-43神经退行性变模式和α-突触核蛋白阳性。将这些模型应用于Penn-ADRC中244名个体（年龄54 - 92岁，57.0%为女性）的独立数据集时也观察到类似结果。最后，这些模型被应用于接受抗淀粉样蛋白治疗的队列，以显示该方法在预测治疗期间个体认知轨迹方面的效用。
tau-临床不匹配可识别更可能存在共病病理且有不同临床轨迹的个体。基于血浆的模型产生的结果与Tau-PET模型相似，且可在独立数据集中复制。这些模型提供了一种重要工具，可在临床实践中实施，以改善个体化预后，并有可能监测对疾病修饰治疗的反应。
