Hole Detection in Metabolic Connectivity of Alzheimer’s Disease Using k −Laplacian

Glucose hypometabolism in the pre-clinical stage of Alzheimer’s disease (AD) has been primarily associated with the APOE ɛ4 genotype, rather than fibrillar β-amyloid. In contrast, aberrant patterns of metabolic connectivity are more strongly related to β-amyloid burden than APOE ɛ4 status. A major limitation of previous studies has been the dichotomous classification of subjects as amyloid-positive or amyloid-negative. Dichotomous treatment of a continuous variable, such as β-amyloid, potentially obscures the true relationship with metabolism and reduces the power to detect significant changes in connectivity. In the present work, we assessed alterations of glucose metabolism and metabolic connectivity as continuous function of β-amyloid burden using positron emission tomography scans from the Alzheimer’s Disease Neuroimaging Initiative study. Modeling β-amyloid as a continuous variable resulted in better model fits and improved power compared to the dichotomous model. Using this continuous model, we found that both APOE ɛ4 genotype and β-amyloid burden are strongly associated with glucose hypometabolism at early stages of Alzheimer’s disease. We also determined that the cumulative effects of β-amyloid deposition result in a particular pattern of altered metabolic connectivity, which is characterized by global, synchronized hypometabolism at early stages of the disease process, followed by regionally heterogeneous, progressive hypometabolism.

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Metabolic connectivity for differential diagnosis of dementing disorders

Journal of Cerebral Blood Flow & Metabolism ◽

10.1177/0271678x15622465 ◽

2016 ◽

Vol 37 (1) ◽

pp. 252-262 ◽

Cited By ~ 20

Author(s):

Dmitry Titov ◽

Janine Diehl-Schmid ◽

Kuangyu Shi ◽

Robert Perneczky ◽

Na Zou ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Differential Diagnosis ◽

Frontotemporal Lobar Degeneration ◽

Elderly Subjects ◽

Single Subject ◽

Linear Discriminant ◽

Healthy Elderly ◽

Metabolic Connectivity ◽

Dementing Disorders

Presently, visual and quantitative approaches for image-supported diagnosis of dementing disorders rely on regional intensity rather than on connectivity measurements. Here, we test metabolic connectivity for differentiation between Alzheimer’s disease and frontotemporal lobar degeneration. Positron emission tomography with 18F-fluorodeoxyglucose was conducted in 47 patients with mild Alzheimer’s disease, 52 patients with mild frontotemporal lobar degeneration, and 45 healthy elderly subjects. Sparse inverse covariance estimation and selection were used to identify patterns of metabolic, inter-subject covariance on the basis of 60 regional values. Relative to healthy subjects, significantly more pathological within-lobe connections were found in the parietal lobe of patients with Alzheimer’s disease, and in the frontal and temporal lobes of subjects with frontotemporal lobar degeneration. Relative to the frontotemporal lobar degeneration group, more pathological connections between the parietal and temporal lobe were found in the Alzheimer’s disease group. The obtained connectivity patterns differentiated between two patients groups with an overall accuracy of 83%. Linear discriminant analysis and univariate methods provided an accuracy of 74% and 69%, respectively. There are characteristic patterns of abnormal metabolic connectivity in mild Alzheimer’s disease and frontotemporal lobar degeneration. Such patterns can be utilized for single-subject analyses and might be more accurate in the differential diagnosis of dementing disorders than traditional intensity-based analyses.

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Genetic interaction is associated with lower metabolic connectivity and memory impairment in clinically mild Alzheimer's disease

Genes Brain & Behavior ◽

10.1111/gbb.12490 ◽

2018 ◽

Vol 18 (5) ◽

pp. e12490 ◽

Cited By ~ 1

Author(s):

Y.-T. Chang ◽

C.-W. Huang ◽

S.-H. Huang ◽

S.-W. Hsu ◽

W.-N. Chang ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Memory Impairment ◽

Genetic Interaction ◽

Metabolic Connectivity

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Characteristic patterns of inter- and intra-hemispheric metabolic connectivity in patients with stable and progressive mild cognitive impairment and Alzheimer’s disease

Scientific Reports ◽

10.1038/s41598-018-31794-8 ◽

2018 ◽

Vol 8 (1) ◽

Cited By ~ 3

Author(s):

Sheng-Yao Huang ◽

◽

Jung-Lung Hsu ◽

Kun-Ju Lin ◽

Ho-Ling Liu ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Cognitive Impairment ◽

Mild Cognitive Impairment ◽

Metabolic Connectivity

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Resting metabolic connectivity in Alzheimer’s disease

Clinical and Translational Imaging ◽

10.1007/s40336-013-0027-x ◽

2013 ◽

Vol 1 (4) ◽

pp. 271-278 ◽

Cited By ~ 6

Author(s):

Silvia Morbelli ◽

Dario Arnaldi ◽

Selene Capitanio ◽

Agnese Picco ◽

Ambra Buschiazzo ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Metabolic Connectivity

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Resting metabolic connectivity in prodromal Alzheimer's disease. A European Alzheimer Disease Consortium (EADC) project

Neurobiology of Aging ◽

10.1016/j.neurobiolaging.2012.01.005 ◽

2012 ◽

Vol 33 (11) ◽

pp. 2533-2550 ◽

Cited By ~ 80

Author(s):

Silvia Morbelli ◽

Alex Drzezga ◽

Robert Perneczky ◽

Giovanni B. Frisoni ◽

Anna Caroli ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

Alzheimer Disease ◽

Prodromal Alzheimer’S Disease ◽

Metabolic Connectivity

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Investigating the clinico-anatomical dissociation in the behavioral variant of Alzheimer’s disease

10.1101/19006676 ◽

2019 ◽

Cited By ~ 1

Author(s):

Ellen H. Singleton ◽

Yolande A. L. Pijnenburg ◽

Carole H. Sudre ◽

Colin Groot ◽

Elena Kochova ◽

...

Keyword(s):

Alzheimer’S Disease ◽

Alzheimer's Disease ◽

San Francisco ◽

White Matter Hyperintensity ◽

Group Differences ◽

Characteristic Analysis ◽

Metabolic Connectivity ◽

Relevant Group ◽

The University ◽

Gray Matter Volumes

ABSTRACTObjectiveWe previously found temporoparietal “Alzheimer-typical” atrophy in patients with the behavioral variant of Alzheimer’s disease (bvAD) with relative sparing of frontal regions. Here, we aimed to understand the pathophysiological mechanisms of bvAD based on alternative neuroimaging markers.MethodsWe retrospectively included 150 participants at the University of California San Francisco and University of Berkeley, including 29 bvAD, 28 “typical” amnestic-predominant AD (tAD), 28 behavioral variant of frontotemporal dementia (bvFTD), and 65 cognitively normal participants. Patients with bvAD were compared with other groups on glucose metabolism and metabolic connectivity on [18F]FDG-PET, and subcortical gray matter volumes and white matter hyperintensity volumes (WMHV) on MRI. A receiver-operating-characteristic-analysis was performed to determine the measures yielding the highest contrast between groups.ResultsbvAD and tAD showed predominant temporoparietal hypometabolism compared to controls, and did not differ in direct contrasts. However, overlaying statistical maps from contrasts between patients and controls revealed broader frontoinsular hypometabolism in bvAD compared to tAD, partially overlapping with bvFTD. Metabolic connectivity analyses indicated greater anterior default mode network (DMN) involvement in bvAD compared to tAD, mimicking bvFTD. Analyses of subcortical volume and WMHV showed no relevant group differences. The top-3 discriminative measures for bvAD vs. bvFTD were: metabolism in posterior (bvAD<bvFTD), anterior DMN (bvAD>bvFTD) and parietal cortex (bvAD<bvFTD; AUC: 0.80-0.91, p<0.01), while the top-3 discriminators for bvAD vs. tAD were amygdalar volume (bvAD>tAD), anterior DMN (bvAD<tAD) and salience network metabolism (bvAD<tAD; AUC: 0.66-0.75, p<0.05).ConclusionSubtle frontoinsular hypometabolism and anterior DMN involvement may underlie the prominent behavioral phenotype in bvAD.

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