Diverging patterns of amyloid deposition and hypometabolism in clinical variants of probable Alzheimer's disease

Abstract

The factors driving clinical heterogeneity in Alzheimer's disease are not well understood. This study assessed the relationship between amyloid deposition, glucose metabolism and clinical phenotype in Alzheimer's disease, and investigated how these relate to the involvement of functional networks. The study included 17 patients with early-onset Alzheimer's disease (age at onset <65 years), 12 patients with logopenic variant primary progressive aphasia and 13 patients with posterior cortical atrophy [whole Alzheimer's disease group: age = 61.5 years (standard deviation 6.5 years), 55% male]. Thirty healthy control subjects [age = 70.8 (3.3) years, 47% male] were also included. Subjects underwent positron emission tomography with (11)C-labelled Pittsburgh compound B and (18)F-labelled fluorodeoxyglucose. All patients met National Institute on Ageing-Alzheimer's Association criteria for probable Alzheimer's disease and showed evidence of amyloid deposition on (11)C-labelled Pittsburgh compound B positron emission tomography. We hypothesized that hypometabolism patterns would differ across variants, reflecting involvement of specific functional networks, whereas amyloid patterns would be diffuse and similar across variants. We tested these hypotheses using three complimentary approaches: (i) mass-univariate voxel-wise group comparison of (18)F-labelled fluorodeoxyglucose and (11)C-labelled Pittsburgh compound B; (ii) generation of covariance maps across all subjects with Alzheimer's disease from seed regions of interest specifically atrophied in each variant, and comparison of these maps to functional network templates; and (iii) extraction of (11)C-labelled Pittsburgh compound B and (18)F-labelled fluorodeoxyglucose values from functional network templates. Alzheimer's disease clinical groups showed syndrome-specific (18)F-labelled fluorodeoxyglucose patterns, with greater parieto-occipital involvement in posterior cortical atrophy, and asymmetric involvement of left temporoparietal regions in logopenic variant primary progressive aphasia. In contrast, all Alzheimer's disease variants showed diffuse patterns of (11)C-labelled Pittsburgh compound B binding, with posterior cortical atrophy additionally showing elevated uptake in occipital cortex compared with early-onset Alzheimer's disease. The seed region of interest covariance analysis revealed distinct (18)F-labelled fluorodeoxyglucose correlation patterns that greatly overlapped with the right executive-control network for the early-onset Alzheimer's disease region of interest, the left language network for the logopenic variant primary progressive aphasia region of interest, and the higher visual network for the posterior cortical atrophy region of interest. In contrast, (11)C-labelled Pittsburgh compound B covariance maps for each region of interest were diffuse. Finally, (18)F-labelled fluorodeoxyglucose was similarly reduced in all Alzheimer's disease variants in the dorsal and left ventral default mode network, whereas significant differences were found in the right ventral default mode, right executive-control (both lower in early-onset Alzheimer's disease and posterior cortical atrophy than logopenic variant primary progressive aphasia) and higher-order visual network (lower in posterior cortical atrophy than in early-onset Alzheimer's disease and logopenic variant primary progressive aphasia), with a trend towards lower (18)F-labelled fluorodeoxyglucose also found in the left language network in logopenic variant primary progressive aphasia. There were no differences in (11)C-labelled Pittsburgh compound B binding between syndromes in any of the networks. Our data suggest that Alzheimer's disease syndromes are associated with degeneration of specific functional networks, and that fibrillar amyloid-β deposition explains at most a small amount of the clinico-anatomic heterogeneity in Alzheimer's disease.

Figure 1

Patterns of FDG and PIB binding in early-onset Alzheimer’s disease (EOAD), logopenic variant PPA (lvPPA) and posterior cortical atrophy (PCA) compared with healthy controls. Shown are T-maps after correction for multiple comparisons (FWE at P < 0.05) rendered on the ch2 template brain. Blue in the FDG maps indicates significantly lower FDG uptake in the patient groups compared with controls, whereas warmer colours in the PIB maps indicate significantly greater PIB binding in the patient groups.

Figure 2

Differences in FDG uptake between (A) early-onset Alzheimer’s disease (EOAD) and posterior cortical atrophy (PCA), (B) logopenic variant PPA (lvPPA) and posterior cortical atrophy, (C) logopenic variant PPA and early-onset Alzheimer’s disease, and (D) PIB uptake in posterior cortical atrophy compared with early-onset Alzheimer’s disease. Shown are T-maps after correction for multiple comparisons (FWE at P < 0.05) rendered on the ch2 template brain. Blue in the FDG maps indicates less FDG uptake in posterior cortical atrophy compared with early-onset Alzheimer’s disease and logopenic variant PPA, and in early-onset Alzheimer’s disease compared with logopenic variant PPA. Warmer colours in the PIB map indicate significantly more PIB binding in posterior cortical atrophy compared with early-onset Alzheimer’s disease. Between-patient group comparisons not shown did not return statistically significant differences after FWE-correction.

Figure 3

Region of interest (ROI) correlation maps for FDG (top) and PIB (bottom). Shown are T-values after multiple comparisons correction (FWE at P < 0.05) rendered on the ch2 template brain. Red maps show correlations with the early-onset Alzheimer’s disease (EOAD) seed region of interest (right middle frontal gyrus); blue maps show correlations with the logopenic variant PPA (lvPPA) seed region of interest (left superior temporal sulcus); green maps show correlations with the posterior cortical atrophy (PCA) seed region of interest (right middle occipital gyrus). The overlap map shows the overlap of all three correlation maps for each tracer.

Figure 4

Overlap maps showing each region of interest (ROI) correlation map with the best-fitting network template (i.e. network with highest goodness-of-fit score) for FDG and PIB. Red, blue and green maps represent T-values for significant (FWE P < 0.05) correlations with the respective seed regions of interest for early-onset Alzheimer’s disease (EOAD), logopenic variant PPA (lvPPA) and posterior cortical atrophy (PCA), respectively, whereas yellow represents the corresponding network template.

Figure 5

Mean FDG and PIB values for each group and the functional network templates. All Alzheimer’s disease groups showed significantly lower FDG and higher PIB compared with controls. Asterisk denote FDG in logopenic variant PPA significantly higher than in early-onset Alzheimer’s disease and posterior cortical atrophy P < 0.05; double asterisk denotes FDG in logopenic variant PPA significantly higher than in early-onset Alzheimer’s disease and posterior cortical atrophy P < 0.01; triple asterisks denote FDG in posterior cortical atrophy significantly lower than in early-onset Alzheimer’s disease and logopenic variant PPA P < 0.0001. DMN = default mode network; ECN = executive-control network.