Situating tau pathology and neuroinflammation along the principal gradients of brain organisation in Alzheimer’s disease

作     者：Julie Ottoy Min Su Kang Yi-Hsuan Yeh Reinder Vos de Wael Bo-yong Park Jonah Isen Mary Agopian Gleb Bezgin Firoza Z Lussier Sulantha Mathotaarachchi Jenna Stevenson Mira Chamoun Nesrine Rahmouni Robert Hopewell Gassan Massarweh Jean-Paul Soucy Serge Gauthier Boris Bernhardt Sandra E. Black Pedro Rosa-Neto Maged Goubran 

作者机构：LC Campbell Cognitive Neurology Research Unit Sunnybrook Research Institute University of Toronto Toronto ON Canada Translational Neuroimaging Laboratory The McGill University Research Centre for Studies in Aging Montréal QC Canada McConnell Brain Imaging Centre Montreal Neurological Institute and Hospital McGill University Montreal QC Canada Department of Data Science Inha University Incheon Korea Republic of (South) Center for Neuroscience Imaging Research Institute for Basic Science Suwon Korea Republic of (South) Montreal Neurological Institute McGill University Montreal QC Canada 

出 版 物：《Alzheimer's & Dementia》 

年 卷 期：2022年第18卷第S5期

学科分类：1002[医学-临床医学] 10[医学] 

摘      要：Background The spread of abnormal tau along connectivity-based networks is a hallmark of Alzheimer’s disease (AD). In addition, activated microglia was shown to affect tau spread across networks. However, traditional network approaches using atlas-defined regions suffer from assuming within-region homogenous connectivity, as well as abrupt and linear connectivity changes between the regions; while, in fact, brain structure and function exist as complex overlapping axes of connectivity variation. Here, we studied smooth/continuous spatial transitions or ‘gradients’ of connectivity and their link to gradients of pathology in AD. This work provides novel insights into brain architecture driving pathology spread. Method We enrolled 220 individuals including 106 cognitively normal Aβ-negative (A-) and 37 A+, and 77 MCI/AD A+ (TRIAD). From diffusion-weighted MRI and fMRI data, we estimated region-to-region fiber count and correlated timeseries, respectively, and averaged subject-wise connectivity matrices to create structural and functional ‘template connectomes’. From 18 F-MK6240 and 11 C-PBR28 PET data, we extracted regional tau and neuroinflammation SUVR values, respectively, and created covariance matrices for each disease stage. Next, the template connectomes/covariance matrices were subjected to non-linear dimensionality reduction to extract embedded components (‘gradients’). We correlated the primary gradients of functional or structural connectivity (G1 FC /G1 SC ) with the primary and secondary gradients of tau or neuroinflammation (G1 TAU /G2 TAU ; G1 INFLAM /G2 INFLAM ). We employed three brain atlases for validation: high-resolution customized Glasser-atlas (1332 equally-sized subregions), DKT, and Schaefer-100. Result G1 FC replicated the previously reported ‘uni-to-transmodal’ functional gradient ( Margulies 2016) and correlated strongly with G1 TAU in cognitively impaired A+ ( Fig.1 A); illustrating a common topographic variation in tau spread and functiona