Impaired metabolic brain networks associated with neurotransmission systems in the α-synuclein spectrum

Carli, Giulia; Caminiti, Silvia Paola; Sala, Arianna; Galbiati, Andrea; Padovani, Alessandro; Ferini‐Strambi, Luigi; Padovani, Alessandro; Perani, Daniela

doi:10.1016/j.parkreldis.2020.10.036

Cited by 17 publications

(16 citation statements)

References 52 publications

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“…To do that, we performed direct comparisons between clinical groups (i.e., iRBD vs. PD, iRBD vs. DLB, PD vs. DLB). Specifically, we evaluated the topographical differences, also considering the deviation from HC of each group, using a previously validated metabolic connectivity index: weighted DC coefficient (wDC; Carli et al, 2020c ; Mencarelli et al, 2020 ). Compared to the standard unweighted DC coefficient, the wDC provides a similarity index that considers not only spatial similarity between groups of patients but also the similarity of the connectivity changes that emerged in comparison with HC.…”

Section: Methodsmentioning

confidence: 99%

“…DC measures similarity between large-scale networks by computing the normalized amount of their overlap (i.e., volume overlap between two binary masks divided by their mean volume) ( Savio et al, 2017 ). To evaluate the differences and similarities among clinical groups (i.e., iRBD vs. PD, iRBD vs. DLB, and PD vs. DLB), we computed the weighted wDC ( Carli et al, 2020c ; Mencarelli et al, 2020 ) to account for their deviation from HC RSNs. Compared to the standard unweighted DC coefficient, the wDC provides a similarity index that advantageously takes into account not only spatial similarity but also the similarity of the connectivity signs [i.e., positive (higher connectivity than controls) and negative (lower connectivity than controls)].…”

Section: Methodsmentioning

confidence: 99%

“…Common pathological substrates between PDD/DLB and iRBD also emerged from brain metabolic connectivity targeting the dopaminergic, noradrenergic, and cholinergic systems, known to be affected by alpha-synuclein aggregations ( Uchihara and Giasson, 2016 ). Specifically, iRBD and DLB share similar cholinergic alterations, and in PD without cognitive deterioration, a limited impairment of this neurotransmission system is present ( Carli et al, 2020c ). All the above suggest that iRBD might have more biological mechanisms in common with DLB than PD with a stable clinical progression, providing initial biological support to the definition of iRBD as a risk factor for dementia development to LB diseases ( Carli et al, 2020b ; Galbiati et al, 2021 ).…”

Section: Introductionmentioning

confidence: 99%

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Metabolic connectivity of resting-state networks in alpha synucleinopathies, from prodromal to dementia phase

et al. 2022

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Previous evidence suggests that the derangement of large-scale brain networks reflects structural, molecular, and functional mechanisms underlying neurodegenerative diseases. Although the alterations of multiple large-scale brain networks in Parkinson’s disease (PD) and Dementia with Lewy Bodies (DLB) are reported, a comprehensive study on connectivity reconfiguration starting from the preclinical phase is still lacking. We aimed to investigate shared and disease-specific changes in the large-scale networks across the Lewy Bodies (LB) disorders spectrum using a brain metabolic connectivity approach. We included 30 patients with isolated REM sleep behavior disorder (iRBD), 28 with stable PD, 30 with DLB, and 30 healthy controls for comparison. We applied seed-based interregional correlation analyses (IRCA) to evaluate the metabolic connectivity in the large-scale resting-state networks, as assessed by [18F]FDG-PET, in each clinical group compared to controls. We assessed metabolic connectivity changes by applying the IRCA and specific connectivity metrics, such as the weighted and unweighted Dice similarity coefficients (DC), for the topographical similarities. All the investigated large-scale brain resting-state networks showed metabolic connectivity alterations, supporting the widespread involvement of brain connectivity within the alpha-synuclein spectrum. Connectivity alterations were already evident in iRBD, severely affecting the posterior default mode, attentive and limbic networks. Strong similarities emerged in iRBD and DLB that showed comparable connectivity alterations in most large-scale networks, particularly in the posterior default mode and attentive networks. Contrarily, PD showed the main connectivity alterations limited to motor and somatosensory networks. The present findings reveal that metabolic connectivity alterations in the large-scale networks are already present in the early iRBD phase, resembling the DLB metabolic connectivity changes. This suggests and confirms iRBD as a risk condition for progression to the severe LB disease phenotype. Of note, the neurobiology of stable PD supports its more benign phenotype.

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Section: Methodsmentioning

confidence: 99%

Section: Methodsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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Metabolic connectivity of resting-state networks in alpha synucleinopathies, from prodromal to dementia phase

et al. 2022

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“…Compared with healthy controls, Parkinson's disease patients have alterations in their sleep microstructure that correlate with decreased NET density in regions involved in arousal, including the locus coeruleus, raphe nuclei, thalami and bitemporal cortices [26 ▪▪ ]. Connectivity analysis using FDG-PET data demonstrated early alterations in noradrenergic networks in all idiopathic RBD, Parkinson's disease and DLB groups, changes in dopaminergic networks in only Parkinson's disease and DLB groups, and abnormalities in cholinergic networks that are more severe in idiopathic RBD and DLB groups that may predict disease progression to dementia [56]. The severity of locus coeruleus degeneration may differentiate Parkinson's disease from Parkinson's disease with dementia and DLB, entities that appear to be on a continuum with a stepwise reduction in locus coeruleus neuron count [57 ▪ ].…”

Section: Non-motor and Non-cognitive Symptomsmentioning

confidence: 98%

The role of the locus coeruleus/norepinephrine system in the pathogenesis of neurodegenerative disorders: An update

Malatt

Tagliati²

2022

Current Opinion in Neurology

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Purpose of reviewThe aim of this review was to provide an update on current and emerging knowledge of the neuropathological processes affecting the locus coeruleus/norepinephrine (LC/NE) system, their effect on Alzheimer's disease and Parkinson's disease symptomatology, including efforts to translate these notions into therapeutic actions targeting the noradrenergic system.Recent findingsOver the past 2 years, work from multiple groups has contributed to support an early role of locus coeruleus degeneration and/or hyperactivation in the neurodegenerative process, including a trigger of neuroinflammation. Imaging advances are allowing the quantification of locus coeruleus structural features in vivo, which is critical in the early stages of disease. Nonmotor and noncognitive symptoms, often secondary to the involvement of the LC/NE system, are becoming more important in the definition of these diseases and their treatment.SummaryThe diverse symptomatology of Parkinson's disease and Alzheimer's disease, which is not limited to cardinal motor and cognitive abnormalities, strongly suggests a multisystem neurodegenerative process. In this context, it is increasingly clear how the LC/NE system plays a key role in the initiation and maintenance of the neurodegenerative process.

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“…Carli et al aimed to investigate the derangement in three neurotransmitter systems by applying a region-of-interest (ROI)-based network analysis to 18 F-FDG PET data of subjects with iRBD (n = 34), idiopathic PD (n = 29), DLB (n = 30) and 50 healthy controls (Carli et al 2020b ). For each neurotransmitter system (nigro-striatal-cortical dopaminergic, noradrenergic, cholinergic), specific ROIs were chosen that were likely involved in those particular systems.…”

Section: Neurotransmitter Network In Irbdmentioning

confidence: 99%

Circuit imaging biomarkers in preclinical and prodromal Parkinson's disease

Meles

Oertel

Leenders

2021

Mol Med

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Parkinson’s disease (PD) commences several years before the onset of motor features. Pathophysiological understanding of the pre-clinical or early prodromal stages of PD are essential for the development of new therapeutic strategies. Two categories of patients are ideal to study the early disease stages. Idiopathic rapid eye movement sleep behavior disorder (iRBD) represents a well-known prodromal stage of PD in which pathology is presumed to have reached the lower brainstem. The majority of patients with iRBD will develop manifest PD within years to decades. Another category encompasses non-manifest mutation carriers, i.e. subjects without symptoms, but with a known mutation or genetic variant which gives an increased risk of developing PD. The speed of progression from preclinical or prodromal to full clinical stages varies among patients and cannot be reliably predicted on the individual level. Clinical trials will require inclusion of patients with a predictable conversion within a limited time window. Biomarkers are necessary that can confirm pre-motor PD status and can provide information regarding lead time and speed of progression. Neuroimaging changes occur early in the disease process and may provide such a biomarker. Studies have focused on radiotracer imaging of the dopaminergic nigrostriatal system, which can be assessed with dopamine transporter (DAT) single photon emission computed tomography (SPECT). Loss of DAT binding represents an effect of irreversible structural damage to the nigrostriatal system. This marker can be used to monitor disease progression and identify individuals at specific risk for phenoconversion. However, it is known that changes in neuronal activity precede structural changes. Functional neuro-imaging techniques, such as 18F-2-fluoro-2-deoxy-D-glucose Positron Emission Tomography (18F-FDG PET) and functional magnetic resonance imaging (fMRI), can be used to model the effects of disease on brain networks when combined with advanced analytical methods. Because these changes occur early in the disease process, functional imaging studies are of particular interest in prodromal PD diagnosis. In addition, fMRI and 18F-FDG PET may be able to predict a specific future phenotype in prodromal cohorts, which is not possible with DAT SPECT. The goal of the current review is to discuss the network-level brain changes in pre-motor PD.

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Impaired metabolic brain networks associated with neurotransmission systems in the α-synuclein spectrum

Cited by 17 publications

References 52 publications

Metabolic connectivity of resting-state networks in alpha synucleinopathies, from prodromal to dementia phase

Metabolic connectivity of resting-state networks in alpha synucleinopathies, from prodromal to dementia phase

The role of the locus coeruleus/norepinephrine system in the pathogenesis of neurodegenerative disorders: An update

Circuit imaging biomarkers in preclinical and prodromal Parkinson's disease

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