Brain Molecular Connectivity in Neurodegenerative Diseases: Recent Advances and New Perspectives Using Positron Emission Tomography

Sala, Arianna; Perani, Daniela

doi:10.3389/fnins.2019.00617

Cited by 66 publications

(70 citation statements)

References 127 publications

(215 reference statements)

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“…Building on the core principle that brain regions whose metabolism is correlated at rest are functionally interconnected (Horwitz, Duara, & Rapoport, ), we applied a voxelwise seed‐based interregional correlation analysis (Lee et al, ). This method was previously validated for [18F]FDG–PET data (Horwitz et al, ; Lee et al, ) and allows to derive resting‐state metabolic networks starting from proper seed regions (Ballarini et al, ; Iaccarino et al, ; Perani et al, ; Sala et al, ; Tomasi et al, ; see also Sala & Perani, for a recent review).…”

Section: Methodsmentioning

confidence: 99%

Vulnerability of multiple large‐scale brain networks in dementia with Lewy bodies

Sala

Caminiti

Iaccarino

et al. 2019

Human Brain Mapping

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Aberrations of large‐scale brain networks are found in the majority of neurodegenerative disorders. The brain connectivity alterations underlying dementia with Lewy bodies (DLB) remain, however, still elusive, with contrasting results possibly due to the pathological and clinical heterogeneity characterizing this disorder. Here, we provide a molecular assessment of brain network alterations, based on cerebral metabolic measurements as proxies of synaptic activity and density, in a large cohort of DLB patients (N = 72). We applied a seed‐based interregional correlation analysis approach (p < .01, false discovery rate corrected) to evaluate large‐scale resting‐state networks' integrity and their interactions. We found both local and long‐distance metabolic connectivity alterations, affecting the posterior cortical networks, that is, primary visual and the posterior default mode network, as well as the limbic and attention networks, suggesting a widespread derangement of the brain connectome. Notably, patients with the lowest visual and attention cognitive scores showed the most severe connectivity derangement in regions of the primary visual network. In addition, network‐level alterations were differentially associated with the core clinical manifestations, namely, hallucinations with more severe metabolic dysfunction of the attention and visual networks, and rapid eye movement sleep behavior disorder with alterations of connectivity of attention and subcortical networks. These multiple network‐level vulnerabilities may modulate the core clinical and cognitive features of DLB and suggest that DLB should be considered as a complex multinetwork disorder.

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Section: Methodsmentioning

confidence: 99%

Vulnerability of multiple large‐scale brain networks in dementia with Lewy bodies

Sala

Caminiti

Iaccarino

et al. 2019

Human Brain Mapping

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“…In EOAD, [ 18 F]-FDG PET imaging studies showed, at a comparable level of clinical severity, a greater brain hypometabolism than in LOAD [5,[23][24][25] and an extension of the hypometabolism in frontal and occipital regions in atypical presentations [26,27]. More recently, [ 18 F]-FDG PET measures have been used for the evaluation of brain metabolic connectivity [28]. [ 18 F]-FDG PET brain glucose consumption reflects neuronal communication signaling, both locally and between distant brain regions, and is closely associated with functional connectivity [29].…”

Section: Introductionmentioning

confidence: 99%

The combined effects of microglia activation and brain glucose hypometabolism in early-onset Alzheimer’s disease

Tondo¹,

Iaccarino²,

Caminiti³

et al. 2020

Alz Res Therapy

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Background: Early-onset Alzheimer's disease (EOAD) is characterized by young age of onset (< 65 years), severe neurodegeneration, and rapid disease progression, thus differing significantly from typical late-onset Alzheimer's disease. Growing evidence suggests a primary role of neuroinflammation in AD pathogenesis. However, the role of microglia activation in EOAD remains a poorly explored field. Investigating microglial activation and its influence on the development of synaptic dysfunction and neuronal loss in EOAD may contribute to the understanding of its pathophysiology and to subject selection in clinical trials. In our study, we aimed to assess the amount of neuroinflammation and neurodegeneration and their relationship in EOAD patients, through positron emission tomography (PET) measures of microglia activation and brain metabolic changes. Methods: We prospectively enrolled 12 EOAD patients, classified according to standard criteria, who underwent standard neurological and neuropsychological evaluation, CSF analysis, brain MRI, and both [ 18 F]-FDG PET and [ 11 C]-(R)-PK11195 PET. Healthy controls databases were used for statistical comparison. [ 18 F]-FDG PET brain metabolism in single subjects and as a group was assessed by an optimized SPM voxel-wise single-subject method. [ 11 C]-PK11195 PET binding potentials were obtained using reference regions selected with an optimized clustering procedure followed by a parametric analysis. We performed a topographic interaction analysis and correlation analysis in ADsignature metabolic dysfunctional regions and regions of microglia activation. A network connectivity analysis was performed using the interaction regions of hypometabolism and [ 11 C]-PK11195 PET BP increases. Results: EOAD patients showed a significant and extended microglia activation, as [ 11 C]-PK11195 PET binding potential increases, and hypometabolism in typical AD-signature brain regions, i.e., temporo-parietal cortex, with additional variable frontal and occipital hypometabolism in the EOAD variants. There was a spatial concordance in the interaction areas and significant correlations between the two biological changes. The network analysis showed

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“…As non-invasive technique, [ 18 F]FDG PET has also been used to monitor the regional effects of potential CNS drugs and/or pharmacological challenges with repeated scans [ 3 – 6 ]. More recently, [ 18 F]FDG brain PET was also applied to unravel brain networks in healthy and diseased brains [ 7 ]. Many quantification approaches exist to determine brain glucose metabolism, hence questioning the accuracy of the different [ 18 F]FDG PET quantification methods.…”

Section: Introductionmentioning

confidence: 99%

Comparative test-retest variability of outcome parameters derived from brain [18F]FDG PET studies in non-human primates

et al. 2020

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Introduction Knowledge of the repeatability of quantitative parameters derived from [ 18 F]FDG PET images is essential to define the group size and allow correct interpretation. Here we tested repeatability and accuracy of different [ 18 F]FDG absolute and relative quantification parameters in a standardized preclinical setup in nonhuman primates (NHP). Material and methods Repeated brain [ 18 F]FDG scans were performed in 6 healthy NHP under controlled experimental factors likely to account for variability. Regional cerebral metabolic rate of glucose (CMRglu) was calculated using a Patlak plot with blood input function Semi-quantitative approaches measuring standard uptake values (SUV, SUV×glycemia and SUVR (SUV Ratio) using the pons or cerebellum as a reference region) were considered. Test-retest variability of all quantification parameters were compared in different brain regions in terms of absolute variability and intra-and-inter-subject variabilities. In an independent [ 18 F]FDG PET experiment, robustness of these parameters was evaluated in 4 naive NHP. Results Experimental conditions (injected dose, body weight, animal temperature) were the same at both imaging sessions (p >0.4). No significant difference in the [ 18 F]FDG quantification parameters was found between test and retest sessions. Absolute variability of CMRglu, SUV, SUV×glycemia and normalized SUV ranged from 25 to 43%, 16 to 21%, 23 to 28%, and 7 to 14%, respectively. Intra-subject variability largely explained the absolute variability of all quantitative parameters. They were all significantly correlated to each other and they were all robust. Arterial and venous glycemia were highly correlated (r = 0.9691; p<0.0001).

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Brain Molecular Connectivity in Neurodegenerative Diseases: Recent Advances and New Perspectives Using Positron Emission Tomography

Cited by 66 publications

References 127 publications

Vulnerability of multiple large‐scale brain networks in dementia with Lewy bodies

Vulnerability of multiple large‐scale brain networks in dementia with Lewy bodies

The combined effects of microglia activation and brain glucose hypometabolism in early-onset Alzheimer’s disease

Comparative test-retest variability of outcome parameters derived from brain [18F]FDG PET studies in non-human primates

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