Metabolic resting-state brain networks in health and disease

Abstract

The delineation of resting state networks (RSNs) in the human brain relies on the analysis of temporal fluctuations in functional MRI signal, representing a small fraction of total neuronal activity. Here, we used metabolic PET, which maps nonfluctuating signals related to total activity, to identify and validate reproducible RSN topographies in healthy and disease populations. In healthy subjects, the dominant (first component) metabolic RSN was topographically similar to the default mode network (DMN). In contrast, in Parkinson's disease (PD), this RSN was subordinated to an independent disease-related pattern. Network functionality was assessed by quantifying metabolic RSN expression in cerebral blood flow PET scans acquired at rest and during task performance. Consistent task-related deactivation of the "DMN-like" dominant metabolic RSN was observed in healthy subjects and early PD patients; in contrast, the subordinate RSNs were activated during task performance. Network deactivation was reduced in advanced PD; this abnormality was partially corrected by dopaminergic therapy. Time-course comparisons of DMN loss in longitudinal resting metabolic scans from PD and Alzheimer's disease subjects illustrated that significant reductions appeared later for PD, in parallel with the development of cognitive dysfunction. In contrast, in Alzheimer's disease significant reductions in network expression were already present at diagnosis, progressing over time. Metabolic imaging can directly provide useful information regarding the resting organization of the brain in health and disease.

Keywords: PET; default mode network; neurodegeneration; principal component analysis; resting state networks.

Conflict of interest statement

Conflict of interest statement: D.E. serves on the scientific advisory boards for and has received honoraria from the Michael J. Fox Foundation for Parkinson’s Research and the Bachmann-Strauss Dystonia and Parkinson Foundation; serves on the editorial board of Annals of Neurology and NeuroImage and as Associate Editor for the Journal of Neuroscience; and is listed as coinventor of patents re: Markers for use in screening patients for nervous system dysfunction and a method and apparatus for using same, without financial gain; has received research support from the NIH (National Institute of Neurological Disorders and Stroke, National Institute on Deafness and Other Communication Disorders, National Institute of Allergy and Infectious Diseases), the Dana Foundation, the Bachmann-Strauss Dystonia and Parkinson Foundation, and CHDI Foundation, Inc.; and has served as a consultant for Pfizer.

Figures

Fig. 1.

Metabolic RSNs identified in (A and B) two groups of healthy volunteer subjects (NL1 and NL2) and (C) a group of patients with mild-to-moderate Parkinson’s disease (PD1). Region weights (loadings) on each spatial covariance pattern topography are displayed in orthogonal views through the origin of Montreal Neurological Institute (MNI) space (sagittal X = 0 mm, coronal Y = 0 mm, axial Z = 0 mm). The color stripe represents voxel weights on each topography thresholded at |z| > 0.5. Arrows indicate significant pairwise correlations (r2 ≥ 0.40, P ≤ 0.001) between nonzero voxel weights (|z| > 0) on the two patterns within a common gray matter mask.

Fig. 2.

Metabolic RSN expression values measured at rest (REST) and during motor execution (MOVE) and motor sequence learning (LEARN) in H215O PET scans from (A) healthy subjects (NL3) and (B) early-stage PD patients (PD2). In both groups, NL1-PC1 expression (Left) was consistently reduced (deactivated) during task performance relative to the nonmovement resting state. Analogous deactivation responses were seen in the early PD group for PD1-PC2 (C, Center), the second metabolic RSN identified in the PD1 derivation group. The other metabolic RSNs identified in healthy subjects (A and B, Center and Right) or in PD patients (C, Left and Right) exhibited consistent increases in expression (activation) during task performance. Significance levels (horizontal arrows) were determined by RMANOVA with post hoc Bonferroni tests.

Fig. 3.

(A) Task-related NL1-PC1 deactivation responses were not observed in unmedicated patients with advanced PD who were scanned with H215O PET at rest (REST) and during motor execution (MOVE) and sequence learning (LEARN) task performances. This finding contrasted with corresponding measurements in early stage-PD subjects (Fig. 2B, Left) in whom significant deactivation was observed during both movement and learning. (B) Network deactivation was partially restored when the same patients were rescanned on levodopa treatment. Significance levels (horizontal arrows) were determined by RMANOVA with post hoc Bonferroni tests.

Fig. 4.

Z-scored expression values are displayed for (A) the abnormal PDRP measured in 15 early-stage PD patients (gray bars) scanned longitudinally with FDG PET at baseline, 24 mo, and 48 mo, and (B) the dominant metabolic RSN identified in healthy subjects (NL1-PC1). In A and B, expression values for the two networks are also displayed for 15 later-stage PD patients of similar age with mild cognitive impairment (black bars) and 15 age-matched healthy volunteer subjects (white bars). The two networks exhibited different time courses in members of the early-stage longitudinal PD cohort (P < 0.01, network × time interaction effect; RMANOVA). Significant increases in PDRP expression were present over time in these subjects (main effect of time: P < 0.0005; one-way RMANOVA), without concurrent change in NL1-PC1 expression (P = 0.12). NL1-PC1 expression was reduced, however, in the later-stage PD subjects with cognitive impairment (P < 0.01; Student’s t test with respect to normal control values). (C) NL1-PC1 z-scored expression values in 40 early-stage AD patients (black bars) scanned with FDG PET at baseline, 6, 12, and 24 mo and (D) 40 normal (NL) subjects (white bars). Although NL1-PC1 expression did not change over time in healthy subjects (P = 0.31, one-way RMANOVA), a progressive decline in this measure (P < 0.0001) was present in the AD group. In the AD group, a significant reduction in the expression of this network was present at each time point (P < 0.05, Student’s t tests with respect to normal baseline values). *P < 0.05, **P < 0.01, ***P < 0.001, Student’s t tests. Error bar represents SE.