Connectivity as a universal predictor of tau spreading in typical and atypical Alzheimer’s disease

Abstract Background There is a strong link between tau and progression of Alzheimer’s disease (AD), necessitating an understanding of tau spreading mechanisms. Prior research, predominantly in typical AD, suggested that tau propagates from epicenters (regions with earliest tau) to functionally connected regions. However, given the constrained spatial heterogeneity of tau in typical AD, validating this connectivity‐based tau spreading model in AD variants with distinct tau deposition patterns is crucial. Method We included 269 amyloid‐β‐positive (PET/CSF) individuals with clinically diagnosed atypical AD (113 posterior cortical atrophy, PCA‐AD; 83 logopenic variant primary progressive aphasia, lvPPA‐AD; 33 behavioural variant AD, bvAD; 40 corticobasal syndrome, CBS‐AD) and 68 with typical AD from 12 international cohorts, who underwent tau‐PET (54% [ 18 F]AV1451/[ 18 F]flortaucipir/Tauvid, 27% [ 18 F]MK6240, 19% [ 18 F]PI2620). Using Gaussian mixture modeling including amyloid‐β‐negative controls, cross‐sectional tau‐PET standardized uptake value ratios within Schaefer‐200 atlas regions were transformed to tau positivity probabilities. Tau epicenters were defined as the 5% regions with highest tau positivity probabilities. For each variant, the association between functional connectivity‐based distance (using the 30% strongest positive region‐to‐region connections of a group‐average connectivity matrix from ADNI elderly controls) and tau‐PET covariance (group‐average correlation per region pair) was assessed through linear regression, adjusting for age, sex, site, and Euclidean distance. Regions were categorized based on functional proximity to the epicenter (quartiles 1‐4) and tau positivity probabilities were assessed accordingly. Result Tau positivity probabilities matched clinical variants, with a posterior pattern in PCA‐AD, left‐hemispheric dominant pattern in lvPPA‐AD, widespread pattern in bvAD, sensorimotor cortex involvement in CBS‐AD, and temporo‐parietal predominance in typical AD (Figure 1). In line with this, tau epicenters were highly heterogeneous across variants (Figure 1). In all variants, greater tau‐PET covariance was associated with shorter functional connectivity‐based distance (Figure 2). We observed that regions in closer functional proximity to the epicenter exhibited higher tau positivity probabilities than regions functionally further away (p<0.05, Figure 3). Conclusion This multi‐center study shows that the brain’s functional architecture serves as a universal predictor of tau spreading in AD. Since tau is a key driver of neurodegeneration and cognitive decline in AD, this finding holds potential for personalized medicine and defining participant‐specific endpoints in clinical trials.

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Publication Details

Journal
Alzheimer s & Dementia
Published
2024-12-01
DOI
https://doi.org/10.1002/alz.085869
Citations
2
Primary Topic
Alzheimer's disease research and treatments
Type
article
Field-Weighted Citation Impact
0.65
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article

Connectivity as a universal predictor of tau spreading in typical and atypical Alzheimer’s disease

Alexandra Touroutoglou, Gérard N. Bischof, Elena Doering, Maura Malpetti et al.
2 citations
Alzheimer s & Dementia
Alzheimer's disease research and treatments
0.65
article

Connectivity as a universal predictor of tau spreading in typical and atypical Alzheimer’s disease

Alexandra Touroutoglou, Gérard N. Bischof, Elena Doering, Maura Malpetti, Keith A. Josephs, Tim D. Fryer, Joseph Therriault, Philip S.J. Weston, Ilya M. Nasrallah, Robert Perneczky, John T. O’Brien, Michael Rullmann, Jonathan Graff‐Radford, Carolyn Fredericks, Rik Ossenkoppele, James B. Rowe, Denise Visser, Ronald Boellaard, Wiesje M. van der Flier, Christopher H van Dyck, Henryk Barthel, Jeffrey S. Phillips, Johannes Levin, Carla Palleis, Osama Sabri, Ryan S. O’Dell, David A. Wolk, Elsmarieke van de Giessen, David M. Cash, Deepti Putcha, Matthias L. Schroeter, Jonathan M. Schott, Brad C. Dickerson, Nesrine Rahmouni, Eddie B Lee, Irene Sintini, Stijn Servaes, William Coath, Gregory Scott Day, Günter U. Höglinger, Dorothee Saur, Diana A. Hobbs, Thilo van Eimeren, Anne Trainer, Yuta Katsumi, P Simon Jones, Alexander Drzezga, Nicolai Franzmeier, David J. Irwin, Adam P. Mecca, Andreas Schildan, Brian A. Gordon, Pedro Rosa‐Neto, Merle C. Hönig, Colin Groot, Yolande A.L. Pijnenburg, Hannah de Bruin, Scott M. McGinnis, Jenna Stevenson, Matthias Brendel, Jennifer L. Whitwell
article en
2 citations

Abstract

Abstract Background There is a strong link between tau and progression of Alzheimer’s disease (AD), necessitating an understanding of tau spreading mechanisms. Prior research, predominantly in typical AD, suggested that tau propagates from epicenters (regions with earliest tau) to functionally connected regions. However, given the constrained spatial heterogeneity of tau in typical AD, validating this connectivity‐based tau spreading model in AD variants with distinct tau deposition patterns is crucial. Method We included 269 amyloid‐β‐positive (PET/CSF) individuals with clinically diagnosed atypical AD (113 posterior cortical atrophy, PCA‐AD; 83 logopenic variant primary progressive aphasia, lvPPA‐AD; 33 behavioural variant AD, bvAD; 40 corticobasal syndrome, CBS‐AD) and 68 with typical AD from 12 international cohorts, who underwent tau‐PET (54% [ 18 F]AV1451/[ 18 F]flortaucipir/Tauvid, 27% [ 18 F]MK6240, 19% [ 18 F]PI2620). Using Gaussian mixture modeling including amyloid‐β‐negative controls, cross‐sectional tau‐PET standardized uptake value ratios within Schaefer‐200 atlas regions were transformed to tau positivity probabilities. Tau epicenters were defined as the 5% regions with highest tau positivity probabilities. For each variant, the association between functional connectivity‐based distance (using the 30% strongest positive region‐to‐region connections of a group‐average connectivity matrix from ADNI elderly controls) and tau‐PET covariance (group‐average correlation per region pair) was assessed through linear regression, adjusting for age, sex, site, and Euclidean distance. Regions were categorized based on functional proximity to the epicenter (quartiles 1‐4) and tau positivity probabilities were assessed accordingly. Result Tau positivity probabilities matched clinical variants, with a posterior pattern in PCA‐AD, left‐hemispheric dominant pattern in lvPPA‐AD, widespread pattern in bvAD, sensorimotor cortex involvement in CBS‐AD, and temporo‐parietal predominance in typical AD (Figure 1). In line with this, tau epicenters were highly heterogeneous across variants (Figure 1). In all variants, greater tau‐PET covariance was associated with shorter functional connectivity‐based distance (Figure 2). We observed that regions in closer functional proximity to the epicenter exhibited higher tau positivity probabilities than regions functionally further away (p<0.05, Figure 3). Conclusion This multi‐center study shows that the brain’s functional architecture serves as a universal predictor of tau spreading in AD. Since tau is a key driver of neurodegeneration and cognitive decline in AD, this finding holds potential for personalized medicine and defining participant‐specific endpoints in clinical trials.

Alzheimer s & DementiaVol. 20(S2)
Yale New Haven Hospital (US), Mayo Clinic (US), Harvard University (US), University of Cologne (DE), Lund University (SE), MRC Cognition and Brain Sciences Unit (GB), Washington University in St. Louis (US), University of Cambridge (GB), German Center for Neurodegenerative Diseases (DE), McGill University Health Centre (CA), WinnMed (US), Cambridge University Hospitals NHS Foundation Trust (GB), LMU Klinikum (DE), Yale University (US), Massachusetts General Hospital (US), Alzheimer’s Disease Neuroimaging Initiative (US), Amsterdam Neuroscience (NL), Institute for Neurodegenerative Disorders (US), Munich Cluster for Systems Neurology (DE), Mayo Clinic in Arizona (US), UK Dementia Research Institute (GB), Penn Center for AIDS Research (US), Max Planck Institute for Human Cognitive and Brain Sciences (DE), Institute on Aging (US), Mayo Clinic in Florida (US), National Hospital for Neurology and Neurosurgery (GB), Amsterdam University Medical Centers (NL), University Hospital Cologne (DE), Imaging Center (US), University College London (GB), McGill University (CA), University of Pennsylvania (US), Ludwig-Maximilians-Universität München (DE), Vrije Universiteit Amsterdam (NL), University of Gothenburg (SE), Medical Research Council (GB), Leipzig University (DE)
Openalex Percentile: Top 27%
Alzheimer's disease research and treatments
0.65
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