Longitudinal brain metabolic changes from amnestic mild cognitive impairment to Alzheimer's disease.
ABSTRACT A sensitive marker for monitoring progression of early Alzheimer's disease would help to develop and test new therapeutic strategies. The present study is aimed at investigating brain metabolism changes over time, as a potential monitoring marker, in patients with amnestic mild cognitive impairment, according to their clinical outcome (converters or non-converters), and in relation to their cognitive decline. Seventeen amnestic mild cognitive impairment patients underwent magnetic resonance imaging and 18FDG-positron emission tomography scans both at inclusion and 18 months later. Baseline and follow-up positron emission tomography data were corrected for partial volume effects and spatially normalized using magnetic resonance imaging data, scaled to the vermis and compared using SPM2. 'PET-PAC' maps reflecting metabolic per cent annual changes were created for correlation analyses with cognitive decline. In the whole sample, the greatest metabolic decrease concerned the posterior cingulate-precuneus area. Converters had significantly greater metabolic decrease than non-converters in two ventro-medial prefrontal areas, the subgenual (BA25) and anterior cingulate (BA24/32). PET-PAC in BA25 and BA24/32 combined allowed complete between-group discrimination. BA25 PET-PAC significantly correlated with both cognitive decline and PET-PAC in the hippocampal region and temporal pole, while BA24/32 PET-PAC correlated with posterior cingulate PET-PAC. Finally, the metabolic change in BA8/9/10 was inversely related to that in BA25 and showed relative increase with cognitive decline, suggesting that compensatory processes may occur in this dorso-medial prefrontal region. The observed ventro-medial prefrontal disruption is likely to reflect disconnection from the hippocampus, both indirectly through the cingulum bundle and posterior cingulate cortex for BA24/32, and directly through the uncinate fasciculus for BA25. Altogether, our findings emphasize the potential of 18FDG-positron emission tomography for monitoring early Alzheimer's disease progression.
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ABSTRACT: Perturbations of brain energy metabolism are involved in Alzheimer's disease (AD). Adenosine monophosphate-activated kinase (AMPK) is a master energy sensor that monitors the levels of key energy metabolites. Electroacupuncture (EA) has demonstrated therapeutic potential for the treatment of AD. The effects of EA on cognitive functions and the changes of AMPK and its phosphorylated form (p-AMPK) expression were investigated in senescence-accelerated mouse prone 8 (SAMP8) mice. Cognitive function of SAMP8 mice was assessed using Morris water maze test after EA treatment. Then mice were sacrificed for immunohistochemistry and western blot analysis. EA stimulation significantly alleviated memory impairment of AD mice, and increased the levels of p-AMPK in the hippocampus. These results suggest that EA improved cognitive function associated with AMPK activation, AMPK may be a molecular target of EA in treating AD.Metabolic Brain Disease 12/2014; · 2.40 Impact Factor
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ABSTRACT: Statistical analysis in neuroimaging (referred to as "neurostatistical imaging") is important in clinical neurology. Here, neurostatistical imaging and its superiority for diagnosing dementia are reviewed. In neurodegenerative dementia, the proportional distribution of brain perfusion, metabolism, or atrophy is important for understanding the symptoms and status of patients and for identifying regions of pathological damage. Although absolute quantitative changes are important in vascular disease, they are less important than relative values in neurodegenerative dementia. Even under resting conditions in healthy individuals, the distribution of brain perfusion and metabolism is asymmetrical and differs among areas. To detect small changes, statistical analysis such as the Z-score - the number of standard deviations by which a patient's voxel value differs from the normal mean value - comparing normal controls is useful and also facilitates clinical assessment. Our recent finding of a longitudinal one-year reduction of glucose metabolism around the olfactory tract in Alzheimer's disease using the recently-developed DARTEL normalization procedure is also presented. Furthermore, a newly-developed procedure to assess brain atrophy with CT-based voxel-based morphometry is illustrated. The promising possibilities of CT in neurostatistical imaging are also presented.Neuroscience Bulletin 09/2014; 30(5). · 1.83 Impact Factor
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ABSTRACT: Evaluating the symptomatic progression of mild cognitive impairment (MCI) caused by Alzheimer disease (AD) is practically accomplished by tracking performance on cognitive tasks, such as the Alzheimer Disease Assessment Scale's cognitive subscale (ADAS_cog), the Mini-Mental Status Examination (MMSE), and the Functional Activities Questionnaire (FAQ). The longitudinal relationships between cognitive decline and metabolic function as assessed using (18)F-FDG PET are needed to address both the cognitive and the biologic progression of disease state in individual subjects. We conducted an exploratory investigation to evaluate longitudinal changes in brain glucose metabolism of individual subjects and their relationship to the subject's changes of cognitive status. METHODS: We describe a method to determine correlations in (18)F-FDG spatial distribution over time. This parameter is termed the regional (18)F-FDG time correlation coefficient (rFTC). By using linear mixed-effects models, we determined the difference in the rFTC decline rate between controls and subjects at high risk of developing AD, such as individuals with MCI or the presence of apolipoprotein E (APOE)-epsilon4 allele. The association between each subject's rFTC and performance on cognitive tests (ADAS_cog, MMSE, and FAQ) was determined with 2 different correlation methods. All subject data were downloaded from the Alzheimer Disease Neuroimaging Initiative. RESULTS: The rFTC values of controls remained fairly constant over time (-0.003 annual change; 95% confidence interval, -0.010-0.004). In MCI patients, the rFTC declined faster than in controls by an additional annual change of -0.02 (95% confidence interval, -0.030 to -0.010). In MCI patients, the decline in rFTC was associated with cognitive decline (ADAS_cog, P = 0.011; FAQ, P = 0.0016; MMSE, P = 0.004). After a linear effect of time was accounted for, visit-to-visit changes in rFTC correlated with visit-to-visit changes in all 3 cognitive tests. CONCLUSION: Longitudinal changes in rFTC detect subtle metabolic changes in individuals associated with variations in their cognition. This analytic tool may be useful for a patient-based monitoring of cognitive decline.Journal of Nuclear Medicine 09/2013; 54(9):1564-9. · 5.56 Impact Factor