J Nucl Med 2001 Nov;42(11):1591-5
Metabolic network abnormalities in early Huntington's disease: an [(18)F]FDG
PET study.
Feigin A, Leenders KL, Moeller JR, Missimer J, Kuenig G, Spetsieris P, Antonini
A, Eidelberg D.
The identification of discrete patterns of altered functional brain circuitry in
preclinical Huntington's disease (HD) gene carriers is important to
understanding the pathophysiology of this disorder and could be useful as a
biologic disease marker. The purpose of this study was to use PET imaging of
regional cerebral glucose metabolism to identify abnormal networks of brain
regions that are specifically related to the preclinical phase of HD. METHODS:
Eighteen presymptomatic HD gene carriers, 13 early-stage HD patients, and 8
age-matched gene-negative relatives were scanned using PET with [(18)F]FDG to
quantify regional glucose utilization. A network modeling strategy was applied
to the FDG PET data to identify disease-related regional metabolic covariance
patterns in the preclinical HD cohort. The outcome measures were the region
weights defining the metabolic topography of the HD gene carriers and the
subject scores quantifying the expression of the pattern in individual subjects.
RESULTS: Network analysis of the presymptomatic carriers and the gene-negative
control subjects revealed a significant metabolic covariance pattern
characterized by caudate and putamenal hypometabolism but also included
mediotemporal metabolic reductions as well as relative metabolic increases in
the occipital cortex. Subject scores for this pattern were abnormally elevated
in the preclinical group compared with those of the control group (P < 0.005)
and in the early symptomatic group compared with those of the presymptomatic
group (P < 0.005). CONCLUSION: These findings show that FDG PET with network
analysis can be used to identify specific patterns of abnormal brain function in
preclinical HD. The presence of discrete patterns of metabolic abnormality in
preclinical HD carriers may provide a useful means of quantifying the rate of
disease progression during the earliest phases of this illness.
