Elsevier

NeuroImage

Volume 100, 15 October 2014, Pages 684-691
NeuroImage

Reduced glucose uptake and Aβ in brain regions with hyperintensities in connected white matter

https://doi.org/10.1016/j.neuroimage.2014.06.060Get rights and content

Highlights

  • Abnormalities in connectivity due to WM lesions were quantified via the ChaCo score.

  • Subcortical regions (caudate and putamen) had WM connections with the most lesions.

  • GM regions with more lesions in connecting WM had lower FDG-PET and lower PiB.

  • Regression revealed that both ChaCo and FDG-PET were significant predictors of PiB.

Abstract

Interstitial concentration of amyloid beta (Aß) is positively related to synaptic activity in animal experiments. In humans, Aß deposition in Alzheimer's disease overlaps with cortical regions highly active earlier in life. White matter lesions (WML) disrupt connections between gray matter (GM) regions which in turn changes their activation patterns. Here, we tested if WML are related to Aß accumulation (measured with PiB-PET) and glucose uptake (measured with FDG-PET) in connected GM. WML masks from 72 cognitively normal (age 61.7 ± 9.6 years, 71% women) individuals were obtained from T2-FLAIR. MRI and PET images were normalized into common space, segmented and parcellated into gray matter (GM) regions. The effects of WML on connected GM regions were assessed using the Change in Connectivity (ChaCo) score. Defined for each GM region, ChaCo is the percentage of WM tracts connecting to that region that pass through the WML mask. The regional relationship between ChaCo, glucose uptake and Aß was explored via linear regression. Subcortical regions of the bilateral caudate, putamen, calcarine, insula, thalamus and anterior cingulum had WM connections with the most lesions, followed by frontal, occipital, temporal, parietal and cerebellar regions. Regional analysis revealed that GM with more lesions in connecting WM and thus impaired connectivity had lower FDG-PET (r = 0.20, p < 0.05 corrected) and lower PiB uptake (r = 0.28, p < 0.05 corrected). Regional regression also revealed that both ChaCo (β = 0.045) and FDG-PET (β = 0.089) were significant predictors of PiB. In conclusion, brain regions with more lesions in connecting WM had lower glucose metabolism and lower Aß deposition.

Introduction

Animal experiments show that interstitial concentration of amyloid beta (Aß) increases with synaptic activity (Bero et al., 2011, Cirrito et al., 2005). Diurnal fluctuation of cerebrospinal fluid Aß42 in humans peaks in the evening and decreases at night, supporting a relationship to neuronal activity (Kang et al., 2009). Imaging techniques have shown that the highly active heteromodal association cortices in healthy subjects spatially overlap with patterns of Aß deposition in patients with Alzheimer's disease. A hypothesis has therefore been proposed that states that regions with high levels of connectivity and cortical activation throughout the life span may be more prone to greater Aß burden (Buckner et al., 2009, Jagust and Mormino, 2011).

White matter (WM) tracts interconnect gray matter (GM) areas allowing propagation of activation from one cortical region to another (Filley, 2010). White matter lesions (WML) manifesting as areas of hyperintense signal on MRI images are, alongside brain atrophy, the most common pathological findings associated with aging (de Leeuw et al., 2001). Regardless of the mechanism, which is debated (Scarpelli et al., 1994, Scheltens et al., 1995), WML indicate a disruption of normal pattern of brain connections, and have been linked to metabolic changes in distal areas and clinical symptoms (DeCarli et al., 1995, Nordahl et al., 2006).

Here we test the following hypothesis: Aß load and glucose metabolism in a given cortical region is inversely related to the amount of connecting WM fibers with hyperintensities. Although relationships between measures of WML burden, glucose metabolism and Aß accumulation have been previously reported (DeCarli et al., 1995, Hedden et al., 2012, Kuczynski et al., 2008, Marchant et al., 2012, Provenzano et al., 2013, Reed et al., 2004, Sultzer et al., 2002, Tullberg et al., 2004), none consider the topology of the WM fiber network. In this study, we examine relationships between WM connectivity disruption and fluorodeoxyglucose (FDG) uptake and Pittsburgh compound B (PiB) deposition on a region-wise basis.

Section snippets

Subjects

Seventy-two subjects were studied (mean age 61.7 ± 9.6 years, 71% women, education 17 ± 1.9 years). All were recruited in the Center for Brain Health New York University School of Medicine, and signed IRB approved consents for protocols investigating risk factors of cognitive decline and Alzheimer's disease. The clinical evaluation included an interview according to the Brief Cognitive Rating Scale and rating on Global Deterioration Scale (Reisberg et al., 1993). Based on clinical assessment, all

Results

The mean fVWML was .37% ± .41% (median .33%, interquartile range .22%, min .01%, max 2.5%). The ChaCo scores varied across the population — Fig. 1 shows the lesion masks and the corresponding ChaCo scores for three different individuals via the glassbrain display. The glassbrain display depicts each region as a sphere, where the size is proportional to the ChaCo score and the color denotes regional (cortical lobe and subcortical) membership. The mean ChaCo score over the population for each GM

Discussion

Cognitively normal elderly subjects with WML had implied connectivity loss mostly in subcortical regions, particularly the caudate nucleus. Frontal and occipital lobes had some disconnection as well, with the temporal and parietal showing little and the cerebellum showing no disruptions in connection. Most importantly, when examined on region to region basis, the correlations between ChaCo, FDG-PET and PiB-PET indicate that regions with more lesions in connecting WM have less glucose metabolism

Acknowledgments

This work was supported by a Leon Levy Foundation Neuroscience Fellowship and the following NIH grants: P41 RR023953-02, P41 RR023953-02S1, R01 NS075425, 2R01AG013616-22, R01-AG035137, RC2-AG036502, P30 AG008051 and HL111724-01.

Conflicts of interest

We would like to disclose the following possible conflicts. Dr. Glodzik was a PI on an Investigator Initiated project funded by Forest Laboratories, Inc., and received a travel grant from Roche Pharma. Drs. Mosconi, Tsui and de Leon have a patent on

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