001     281875
005     20251208103316.0
024 7 _ |a 10.1093/brain/awaf279
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024 7 _ |a 0006-8950
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024 7 _ |a 1460-2156
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037 _ _ |a DZNE-2025-01246
041 _ _ |a English
082 _ _ |a 610
100 1 _ |a de Bruin, Hannah
|0 0000-0002-9011-1120
|b 0
245 _ _ |a Connectivity as a universal predictor of tau progression in atypical Alzheimer's disease.
260 _ _ |a Oxford
|c 2025
|b Oxford Univ. Press
336 7 _ |a article
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336 7 _ |a Output Types/Journal article
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336 7 _ |a Journal Article
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336 7 _ |a ARTICLE
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336 7 _ |a JOURNAL_ARTICLE
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336 7 _ |a Journal Article
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520 _ _ |a The link between regional tau load and clinical manifestation of Alzheimer's disease (AD) highlights the importance of characterizing spatial tau distribution across disease variants. In typical (memory-predominant) AD, the spatial progression of tau pathology mirrors the functional connections from temporal lobe epicentres. However, given the limited spatial heterogeneity of tau in typical AD, atypical (non-amnestic-predominant) AD variants with distinct tau patterns provide a key opportunity to investigate the universality of connectivity as a scaffold for tau progression. In this large-scale, multicentre study across 14 international sites, we included cross-sectional tau-PET data from 320 individuals with atypical AD (n = 139 posterior cortical atrophy/PCA-AD; n = 103 logopenic variant primary progressive aphasia/lvPPA-AD; n = 35 behavioural variant AD/bvAD; n = 43 corticobasal syndrome/CBS-AD), with a subset of individuals (n = 78) having longitudinal tau-PET data. Additionally, as an independent sample, we included regional post-mortem tau stainings from 93 atypical AD patients from two sites (n = 19 PCA-AD, n = 32 lvPPA-AD, n = 23 bvAD, n = 19 CBS-AD). Gaussian mixture modelling was used to harmonize different tau-PET tracers by transforming tau-PET standardized uptake value ratios to tau positivity probabilities (a uniform scale ranging from 0% to 100%). Using linear regression, we assessed whether brain regions with stronger resting-state functional MRI-based functional connectivity, derived from healthy elderly controls in the Alzheimer's Disease Neuroimaging Initiative (ADNI), showed greater covariance in cross-sectional and longitudinal tau-PET and post-mortem tau pathology. Furthermore, we examined whether functional connectivity of tau-PET epicentres (i.e. the top 5% of regions with the highest baseline tau load) and tau-PET accumulation epicentres (i.e. the top 5% of regions with the highest tau accumulation rates) was associated with cross-sectional and longitudinal tau patterns. Our findings show that tau-PET epicentres aligned with clinical variants, e.g. a visual network predominant pattern in PCA-AD ('visual AD') and left-hemispheric temporal predominance, particularly within the language network, in lvPPA-AD ('language AD'). Moreover, more strongly functionally connected regions showed correlated concurrent tau-PET levels (confirmed with post-mortem data) and tau-PET accumulation rates. The functional connectivity profile of tau-PET epicentres and accumulation epicentres corresponded to tau-PET progression patterns, with higher tau-PET levels and accumulation rates in functionally close regions, and lower tau-PET levels and accumulation rates in functionally distant regions. Our data are consistent with the hypothesis that tau propagation occurs along functional connections originating from local epicentres, across all AD clinical variants. Since tau proteinopathy is a major driver of neurodegeneration and cognitive decline, this finding may advance personalized medicine and participant-specific end points in clinical trials.
536 _ _ |a 352 - Disease Mechanisms (POF4-352)
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588 _ _ |a Dataset connected to CrossRef, PubMed, , Journals: pub.dzne.de
650 _ 7 |a PET
|2 Other
650 _ 7 |a atypical Alzheimer's disease
|2 Other
650 _ 7 |a connectivity
|2 Other
650 _ 7 |a fMRI
|2 Other
650 _ 7 |a heterogeneity
|2 Other
650 _ 7 |a tau
|2 Other
650 _ 7 |a tau Proteins
|2 NLM Chemicals
650 _ 2 |a Humans
|2 MeSH
650 _ 2 |a Alzheimer Disease: diagnostic imaging
|2 MeSH
650 _ 2 |a Alzheimer Disease: metabolism
|2 MeSH
650 _ 2 |a Alzheimer Disease: pathology
|2 MeSH
650 _ 2 |a Female
|2 MeSH
650 _ 2 |a Male
|2 MeSH
650 _ 2 |a Disease Progression
|2 MeSH
650 _ 2 |a Aged
|2 MeSH
650 _ 2 |a tau Proteins: metabolism
|2 MeSH
650 _ 2 |a Positron-Emission Tomography
|2 MeSH
650 _ 2 |a Cross-Sectional Studies
|2 MeSH
650 _ 2 |a Middle Aged
|2 MeSH
650 _ 2 |a Aged, 80 and over
|2 MeSH
650 _ 2 |a Brain: diagnostic imaging
|2 MeSH
650 _ 2 |a Brain: metabolism
|2 MeSH
650 _ 2 |a Brain: pathology
|2 MeSH
650 _ 2 |a Magnetic Resonance Imaging
|2 MeSH
650 _ 2 |a Longitudinal Studies
|2 MeSH
700 1 _ |a Groot, Colin
|b 1
700 1 _ |a Barthel, Henryk
|b 2
700 1 _ |a Bischof, Gérard N
|0 P:(DE-2719)9002485
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700 1 _ |a Blazhenets, Ganna
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700 1 _ |a Boellaard, Ronald
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700 1 _ |a Boon, Baayla D C
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700 1 _ |a Brendel, Matthias
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700 1 _ |a Cash, David M
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700 1 _ |a Coath, William
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700 1 _ |a Day, Gregory S
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700 1 _ |a Dickerson, Bradford C
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700 1 _ |a Doering, Elena
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700 1 _ |a Drzezga, Alexander
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700 1 _ |a van Dyck, Christopher H
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700 1 _ |a Eimeren, Thilo
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700 1 _ |a van der Flier, Wiesje M
|0 0000-0001-8766-6224
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700 1 _ |a Fredericks, Carolyn A
|0 0000-0002-7051-6382
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700 1 _ |a Fryer, Tim D
|b 18
700 1 _ |a van de Giessen, Elsmarieke
|b 19
700 1 _ |a Gordon, Brian A
|0 0000-0003-2109-2955
|b 20
700 1 _ |a Graff-Radford, Jonathan
|0 0000-0003-2770-0691
|b 21
700 1 _ |a Grinberg, Lea T
|0 0000-0002-6809-0618
|b 22
700 1 _ |a Hansson, Oskar
|0 0000-0001-8467-7286
|b 23
700 1 _ |a Hobbs, Diana A
|b 24
700 1 _ |a Hoenig, Merle C
|b 25
700 1 _ |a Höglinger, Günter
|0 P:(DE-2719)2811373
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700 1 _ |a Irwin, David J
|0 0000-0002-5599-5098
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700 1 _ |a Jones, P Simon
|b 28
700 1 _ |a Josephs, Keith A
|0 0000-0003-2930-8634
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700 1 _ |a Katsumi, Yuta
|0 0000-0003-0413-747X
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700 1 _ |a La Joie, Renaud
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700 1 _ |a Lee, Edward B
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700 1 _ |a Levin, Johannes
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700 1 _ |a Malpetti, Maura
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700 1 _ |a McGinnis, Scott M
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700 1 _ |a Mecca, Adam P
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700 1 _ |a Mohanty, Rosaleena
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700 1 _ |a Nasrallah, Ilya M
|b 38
700 1 _ |a O'Brien, John T
|0 0000-0002-0837-5080
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700 1 _ |a O'Dell, Ryan S
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700 1 _ |a Palleis, Carla
|0 P:(DE-2719)9000852
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700 1 _ |a Perneczky, Robert
|0 P:(DE-2719)2812234
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700 1 _ |a Phillips, Jeffrey S
|0 0000-0003-0079-9441
|b 43
700 1 _ |a Putcha, Deepti
|0 0000-0001-5575-5572
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700 1 _ |a Rabinovici, Gil D
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700 1 _ |a Rahmouni, Nesrine
|b 46
700 1 _ |a Rosa-Neto, Pedro
|0 0000-0001-9116-1376
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700 1 _ |a Rowe, James B
|b 48
700 1 _ |a Rullmann, Michael
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700 1 _ |a Sabri, Osama
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700 1 _ |a Saur, Dorothee
|b 51
700 1 _ |a Schildan, Andreas
|b 52
700 1 _ |a Schott, Jonathan M
|0 0000-0003-2059-024X
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700 1 _ |a Schroeter, Matthias L
|0 0000-0001-7977-1083
|b 54
700 1 _ |a Seeley, William W
|b 55
700 1 _ |a Servaes, Stijn
|b 56
700 1 _ |a Sintini, Irene
|b 57
700 1 _ |a Smith, Ruben
|0 0000-0001-7147-0112
|b 58
700 1 _ |a Spina, Salvatore
|0 0000-0003-3570-9143
|b 59
700 1 _ |a Stevenson, Jenna
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700 1 _ |a Stomrud, Erik
|b 61
700 1 _ |a Strandberg, Olof
|b 62
700 1 _ |a Therriault, Joseph
|0 0000-0002-7826-4781
|b 63
700 1 _ |a Tideman, Pontus
|b 64
700 1 _ |a Touroutoglou, Alexandra
|b 65
700 1 _ |a Trainer, Anne E
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700 1 _ |a Visser, Denise
|b 67
700 1 _ |a Wekselman, Fattin
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700 1 _ |a Weston, Philip S J
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700 1 _ |a Whitwell, Jennifer L
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700 1 _ |a Wolk, David A
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700 1 _ |a Yong, Keir
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700 1 _ |a Pijnenburg, Yolande A L
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700 1 _ |a Franzmeier, Nicolai
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700 1 _ |a Ossenkoppele, Rik
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773 _ _ |a 10.1093/brain/awaf279
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