Iturria-Medina Yasser, Poole Victoria N, Zammit Andrea R, Yu Lei, Tasaki Shinya, Hong Joon Hwan, Lopes Katia de Paiva, Batalha Caio, Ridwan Abdur Raquib, Vialle Ricardo A, Sanchez-Rodriguez Lazaro, Geddes Maiya Rachel, Abadir Peter, Ortlund Eric, De Jager Philip, Menon Vilas, Beeri Michal Schnaider, Buchman Aron S, Levin Yishai, Morgenstern David, Schneider Julie A, Daouk Rima Kaddurah, Wyss-Coray Tony, Seyfried Nicholas T, Arfanakis Konstantinos, Rosa-Neto Pedro, Wang Yanling, Bennett David A
Neurology and Neurosurgery Department, Montreal Neurological Institute, Montreal, Canada.
McConnell Brain Imaging Centre, Montreal Neurological Institute, Montreal, Canada.
bioRxiv. 2025 Mar 24:2025.03.20.644323. doi: 10.1101/2025.03.20.644323.
Alzheimer's disease (AD) dementia is characterized by significant molecular and phenotypic heterogeneity, which confounds its mechanistic understanding, diagnosis, and effective treatment. In this study, we harness the most comprehensive dataset of paired blood omics, clinical, psychological, and brain multi-omics data and neuroimaging to extensively characterize and translate the molecular taxonomy of AD dementia to living individuals. First, utilizing a comprehensive integration of eight complementary molecular layers from brain multi-omics data (N = 1,189), we identified three distinct molecular AD dementia subtypes exhibiting strong associations with cognitive decline, sex, psychological traits, brain morphology, and characterized by specific cellular and molecular drivers involving immune, vascular, and oligodendrocyte precursor cells. Next, in a significant translational effort, we developed predictive models to convert these advanced brain-derived molecular profiles (AD dementia pseudotimes and subtypes) into blood-, MRI- and psychological traits-based markers. The translation results underscore both the promise of these models and the opportunities for further enhancement. Our findings enhance the understanding of AD heterogeneity, underscore the value of multi-scale molecular approaches for elucidating causal mechanisms, and lay the groundwork for the development of novel therapies in living persons that target multi-level brain molecular subtypes of AD dementia.
阿尔茨海默病（AD）性痴呆的特征是存在显著的分子和表型异质性，这使得人们对其发病机制的理解、诊断及有效治疗都变得困难重重。在本研究中，我们利用了配对的血液组学、临床、心理以及大脑多组学数据和神经影像学的最全面数据集，对AD性痴呆的分子分类进行广泛描述，并将其转化应用于活体个体。首先，通过对来自大脑多组学数据（N = 1,189）的八个互补分子层面进行全面整合，我们识别出三种不同的分子AD性痴呆亚型，这些亚型与认知衰退、性别、心理特征、脑形态学表现出强烈关联，并具有涉及免疫、血管和少突胶质前体细胞的特定细胞和分子驱动因素。接下来，在一项重要的转化研究工作中，我们开发了预测模型，将这些源自大脑的先进分子特征（AD性痴呆伪时间和亚型）转化为基于血液、磁共振成像和心理特征的标志物。转化结果凸显了这些模型的前景以及进一步改进的机会。我们的研究结果增进了对AD异质性的理解，强调了多尺度分子方法在阐明因果机制方面的价值，并为开发针对AD性痴呆多水平脑分子亚型的活体新型疗法奠定了基础。
