Dementia with Lewy bodies: association of Alzheimer pathology with functional connectivity networks

Abstract

Dementia with Lewy bodies (DLB) is neuropathologically defined by the presence of α-synuclein aggregates, but many DLB cases show concurrent Alzheimer's disease pathology in the form of amyloid-β plaques and tau neurofibrillary tangles. The first objective of this study was to investigate the effect of Alzheimer's disease co-pathology on functional network changes within the default mode network (DMN) in DLB. Second, we studied how the distribution of tau pathology measured with PET relates to functional connectivity in DLB. Twenty-seven DLB, 26 Alzheimer's disease and 99 cognitively unimpaired participants (balanced on age and sex to the DLB group) underwent tau-PET with AV-1451 (flortaucipir), amyloid-β-PET with Pittsburgh compound-B (PiB) and resting-state functional MRI scans. The resing-state functional MRI data were used to assess functional connectivity within the posterior DMN. This was then correlated with overall cortical flortaucipir PET and PiB PET standardized uptake value ratio (SUVr). The strength of interregional functional connectivity was assessed using the Schaefer atlas. Tau-PET covariance was measured as the correlation in flortaucipir SUVr between any two regions across participants. The association between region-to-region functional connectivity and tau-PET covariance was assessed using linear regression. Additionally, we identified the region with highest and the region with lowest tau SUVrs (tau hot- and cold spots) and tested whether tau SUVr in all other brain regions was associated with the strength of functional connectivity to these tau hot and cold spots. A reduction in posterior DMN connectivity correlated with overall higher cortical tau- (r = -0.39, P = 0.04) and amyloid-PET uptake (r = -0.41, P = 0.03) in the DLB group, i.e. patients with DLB who have more concurrent Alzheimer's disease pathology showed a more severe loss of DMN connectivity. Higher functional connectivity between regions was associated with higher tau covariance in cognitively unimpaired, Alzheimer's disease and DLB. Furthermore, higher functional connectivity of a target region to the tau hotspot (i.e. inferior/medial temporal cortex) was related to higher flortaucipir SUVrs in the target region, whereas higher functional connectivity to the tau cold spot (i.e. sensory-motor cortex) was related to lower flortaucipir SUVr in the target region. Our findings suggest that a higher burden of Alzheimer's disease co-pathology in patients with DLB is associated with more Alzheimer's disease-like changes in functional connectivity. Furthermore, we found an association between the brain's functional network architecture and the distribution of tau pathology that has recently been described in Alzheimer's disease. We show that this relationship also exists in patients with DLB, indicating that similar mechanisms of connectivity-dependent occurrence of tau pathology might be at work in both diseases.

Keywords: Lewy body dementia; PET; amyloid; resting-state fMRI; tau.

Figure 1

Functional MRI and PET analysis methods. (A) Schaefer functional parcellation that was used for parcellating flortaucipir SUVr and resting state functional MRI (rs-fMRI) images into 100 regions and correspondence with the seven functional networks from Yeo et al. (B) Functional connectivity analysis. (C) Tau covariance analysis. FC = functional connectivity.

Figure 2

Group comparisons. (A) Group comparison of the posterior DMN connectivity between the three diagnostic groups. (B) Group comparison of overall flortaucipir SUVr between the three groups. (C) Group comparison of overall PiB SUVr between the three groups. Overall flortaucipir and PiB SUVr are estimated as the average flortaucipir SUVr from all cortical regions from the ADIR122 atlas. In each box plot, the central line corresponds to the sample median, the upper and lower border of the box represent the 25th and 75th percentile, respectively, and the length of the whiskers is 1.5 times the interquartile range. Posterior DMN connectivity and log-transformed flortaucipir and PiB SUVr were compared between the cognitively unimpaired (CU), Alzheimer’s disease dementia (AD) and DLB groups using univariate ANOVAs with post hoc tests, Bonferroni-corrected for multiple comparisons.

Figure 3

Association between DMN connectivity and flortaucipir uptake. (A) Pearson’s correlation between overall flortaucipir SUVr (estimated from all cortical regions of the ADIR122 atlas) and posterior DMN connectivity in the three diagnostic groups and comparison of posterior DMN (pDMN) connectivity between DLB flortaucipir-positive and DLB flortaucipir-negative groups using a two-sample t-test. (B) Pearson’s correlation between overall PiB SUVr and posterior DMN connectivity in the three diagnostic groups and comparison of posterior DMN connectivity between DLB PiB-positive and DLB PiB-negative groups using a two-sample t-test. AD = Alzheimer’s disease; CU = cognitively unimpaired; flortaucipir+ = patients with DLB with global cortical flortaucipir SUVr ≥1.25; flortaucipir– = patients with DLB with global cortical flortaucipir SUVr <1.25; PiB+ = patients with DLB with global cortical PiB SUVr ≥1.48; PiB− = patients with DLB with global cortical PiB SUVr <1.48.

Figure 4

Network-specificity of flortaucipir uptake. Box plots of goodness-of-fit values assessing the network-specificity of flortaucipir uptake within seven functional networks from Yeo et al. in the (A) Alzheimer’s disease and (B) DLB groups. In each box plot, the central line corresponds to the sample median, the upper and lower border of the box represent the 25th and 75th percentile, respectively, and the length of the whiskers is 1.5 times the interquartile range. Significant P-values from one-sample t-tests (Bonferroni-corrected across the seven networks) are indicated, for all other networks P-values were >0.05 (see Table 2 for details on statistics).

Figure 5

Association between functional connectivity and tau covariance. (A) Linear regression with the group-average functional connectivity matrix as the independent variable and the tau covariance matrix as the dependent variable in the three diagnostic groups. (B) Pearson’s correlation between the association between seed-to-target functional connectivity with flortaucipir SUVr in the target region and flortaucipir SUVr in the seed region. Negative β-values (on the y-axis) indicate that higher seed-to-target connectivity is associated with lower flortaucipir uptake in the target region whereas positive β-values indicate that higher seed-to-target connectivity is associated with higher flortaucipir uptake in the target region. (C) Association between the strength of functional connectivity of a region with the tau hotspot (region with highest flortaucipir SUVr) and flortaucipir SUVr in that target region (linear regression). (D) Association between the strength of functional connectivity of a region with the tau cold spot (region with lowest flortaucipir SUVr) and flortaucipir SUVr in that target region (linear regression).