Within-patient correspondence of amyloid-β and intrinsic network connectivity in Alzheimer's disease.
There is striking overlap between the spatial distribution of amyloid-β pathology in patients with Alzheimer's disease and the spatial distribution of high intrinsic functional connectivity in healthy persons. This overlap suggests a mechanistic link between amyloid-β and intrinsic connectivity, and indeed there is evidence in patients for the detrimental effects of amyloid-β plaque accumulation on intrinsic connectivity in areas of high connectivity in heteromodal hubs, and particularly in the default mode network. However, the observed spatial extent of amyloid-β exceeds these tightly circumscribed areas, suggesting that previous studies may have underestimated the negative impact of amyloid-β on intrinsic connectivity. We hypothesized that the known positive baseline correlation between patterns of amyloid-β and intrinsic connectivity may mask the larger extent of the negative effects of amyloid-β on connectivity. Crucially, a test of this hypothesis requires the within-patient comparison of intrinsic connectivity and amyloid-β distributions. Here we compared spatial patterns of amyloid-β-plaques (measured by Pittsburgh compound B positron emission tomography) and intrinsic functional connectivity (measured by resting-state functional magnetic resonance imaging) in patients with prodromal Alzheimer's disease via spatial correlations in intrinsic networks covering fronto-parietal heteromodal cortices. At the global network level, we found that amyloid-β and intrinsic connectivity patterns were positively correlated in the default mode and several fronto-parietal attention networks, confirming that amyloid-β aggregates in areas of high intrinsic connectivity on a within-network basis. Further, we saw an internetwork gradient of the magnitude of correlation that depended on network plaque-load. After accounting for this globally positive correlation, local amyloid-β-plaque concentration in regions of high connectivity co-varied negatively with intrinsic connectivity, indicating that amyloid-β pathology adversely reduces connectivity anywhere in an affected network as a function of local amyloid-β-plaque concentration. The local negative association between amyloid-β and intrinsic connectivity was much more pronounced than conventional group comparisons of intrinsic connectivity would suggest. Our findings indicate that the negative impact of amyloid-β on intrinsic connectivity in heteromodal networks is underestimated by conventional analyses. Moreover, our results provide first within-patient evidence for correspondent patterns of amyloid-β and intrinsic connectivity, with the distribution of amyloid-β pathology following functional connectivity gradients within and across intrinsic networks.
1 Department of Neuroradiology, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany2 TUM-Neuroimaging Centre, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany3 Department of Experimental Psychology, Oxford University, 9 South Parks Road, Oxford OX1 3UD, UK nicholas.myers@psy.ox.ac.uk.
Nicholas
N
Myers
1 Department of Neuroradiology, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany2 TUM-Neuroimaging Centre, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Lorenzo
L
Pasquini
1 Department of Neuroradiology, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany2 TUM-Neuroimaging Centre, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Jens
J
Göttler
4 Department of Psychiatry, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Timo
T
Grimmer
1 Department of Neuroradiology, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany2 TUM-Neuroimaging Centre, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Kathrin
K
Koch
4 Department of Psychiatry, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Marion
M
Ortner
1 Department of Neuroradiology, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany2 TUM-Neuroimaging Centre, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Julia
J
Neitzel
2 TUM-Neuroimaging Centre, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany5 Department of Neurology of Klinikum rechts der Isar, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Mark
M
Mühlau
2 TUM-Neuroimaging Centre, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany6 Department of Nuclear Medicine, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Stefan
S
Förster
4 Department of Psychiatry, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Alexander
A
Kurz
4 Department of Psychiatry, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Hans
H
Förstl
1 Department of Neuroradiology, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Claus
C
Zimmer
1 Department of Neuroradiology, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany2 TUM-Neuroimaging Centre, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Afra M
AM
Wohlschläger
1 Department of Neuroradiology, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany2 TUM-Neuroimaging Centre, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany6 Department of Nuclear Medicine, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Valentin
V
Riedl
6 Department of Nuclear Medicine, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany7 Department of Nuclear Medicine, University of Cologne, Kerpener Straße 62, 50937 Köln, Germany.
Alexander
A
Drzezga
1 Department of Neuroradiology, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany2 TUM-Neuroimaging Centre, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany4 Department of Psychiatry, Technische Universität München, Ismaningerstr. 22, 81675 Munich, Germany.
Christian
C
Sorg
D000368:Aged; D000369:Aged, 80 and over; D000544:Alzheimer Disease / Q000378:metabolism* / Q000473:pathology*; D016229:Amyloid beta-Peptides / Q000378:metabolism*; D000704:Analysis of Variance; D000814:Aniline Compounds; D001921:Brain / Q000000981:diagnostic imaging / Q000473:pathology*; D001931:Brain Mapping; D005260:Female; D006801:Humans; D008279:Magnetic Resonance Imaging; D008297:Male; D008875:Middle Aged; D009434:Neural Pathways / Q000000981:diagnostic imaging / Q000473:pathology*; D009483:Neuropsychological Tests; D058225:Plaque, Amyloid / Q000378:metabolism / Q000473:pathology; D049268:Positron-Emission Tomography; D013844:Thiazoles
C475519:2-(4'-(methylamino)phenyl)-6-hydroxybenzothiazole; D016229:Amyloid beta-Peptides; D000814:Aniline Compounds; D013844:Thiazoles
Alzheimer’s disease; PiB-PET; amyloid-β plaques; intrinsic connectivity; resting-state functional MRI