Reproducible metabolic topographies associated with multiple system atrophy: Network and regional analyses in Chinese and American patient cohorts

Shen, Bo; Wei, Sidi; Ge, Jingjie; Peng, Shichun; Liu, Fengtao; Li, Ling; Guo, Sisi; Wu, Ping; Zuo, Chuantao; Eidelberg, David; Wang, Jian; Ma, Yilong

doi:10.1016/j.nicl.2020.102416

Cited by 13 publications

(14 citation statements)

References 41 publications

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“…Compared with 15 healthy controls, metabolic characteristics of MSA patients, MSA-D, MSA-MCI, and MSA-NC were all in accordance with MSA-related pattern (MSARP) observed by previous study ( 34 , 35 ) ( Supplementary Figure 2 ).…”

Section: Resultssupporting

confidence: 87%

Cerebral Metabolism Related to Cognitive Impairments in Multiple System Atrophy

Shen

Chen

et al. 2021

Front. Neurol.

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Objective: We aimed to characterize the cognitive profiles in multiple system atrophy (MSA) and explore the cerebral metabolism related to the cognitive decline in MSA using 18F-fluorodeoxyglucose (18F-FDG) Positron Emission Tomography (PET).Methods: In this study, 105 MSA patients were included for cognitive assessment and 84 of them were enrolled for 18F-FDG PET analysis. The comprehensive neuropsychological tests covered five main domains including execution, attention, memory, language, and visuospatial function. The cognitive statuses were classified to MSA with normal cognition (MSA-NC) and MSA with cognitive impairment (MSA-CI), including dementia (MSA-D), and mild cognitive impairment (MSA-MCI). With 18F-FDG PET imaging, the cerebral metabolism differences among different cognitive statuses were analyzed using statistical parametric mapping and post-hoc analysis.Results: Among 84 MSA patients, 52 patients were found with MSA-CI, including 36 patients as MSA-MCI and 16 patients as MSA-D. In detail, the cognitive impairments were observed in all the five domains, primarily in attention, executive function and memory. In 18F-FDG PET imaging, MSA-D and MSA-MCI patients exhibited hypometabolism in left middle and superior frontal lobe compared with MSA-NC (p < 0.001). The normalized regional cerebral metabolic rate of glucose (rCMRglc) in left middle frontal lobe showed relative accuracy in discriminating MSA-CI and MSA-NC [areas under the curve (AUC) = 0.750; 95%CI = 0.6391–0.8609].Conclusions: Cognitive impairments were not rare in MSA, and the hypometabolism in frontal lobe may contribute to such impairments.

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Section: Resultssupporting

confidence: 87%

Cerebral Metabolism Related to Cognitive Impairments in Multiple System Atrophy

Shen

Chen

et al. 2021

Front. Neurol.

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“…This pattern was also observed in Chinese and American patient cohorts where the metabolic topography of MSA‐P includes hypermetabolism in the superior frontal gyrus. 24 However, considering that iRBD patients rarely develop MSA instead of PD or DLB, 10 the impact of metabolic patterns associated with MSA needs to be further investigated in large sample data. Interestingly, metabolic decrease in the right premotor cortex correlated with decline in the TMT‐B performance in iRBD patients.…”

Section: Discussionmentioning

confidence: 99%

Longitudinal Changes in Isolated Rapid Eye Movement Sleep Behavior Disorder‐Related Metabolic Pattern Expression

et al. 2021

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A BS TRACT: Background: It remains unclear whether and how the isolated rapid eye movement (REM) sleep behavior disorder (iRBD)-related metabolic pattern (RBDRP) changes with disease progression in iRBD. Objective: To examine longitudinal changes in RBDRP expression in iRBD patients and to explore trajectories of relative metabolic activities of individual brain regions constituting RBDRP. Methods: In this cohort study, 25 iRBD patients (mean age [AEstandard deviation], 69.2 AE 5.3 years; 12 [48%] patients were men) and 24 age-matched healthy controls were included. The patients underwent at least two 18 F-fluorodeoxyglucose positron emission tomography scans at baseline and at the 2-year and/or 4-year followups. We measured the RBDRP expression of the patients and controls which was validated by reproduction in a separate iRBD cohort (n = 13). Results: At baseline, the RBDRP expression discriminated iRBD patients from healthy controls. However, the RBDRP expression z scores tended to decrease over time in the patients, especially with longer follow-ups, and this tendency was observed even in patients with high-risk of phenoconversion. Furthermore, the degree of RBDRP expression at baseline did not predict the disease conversion. The RBDRP breakdown was mainly provoked by the attenuation of relative hypermetabolism in the frontal cortex including premotor areas and relative hypometabolism in the occipital cortex. The putaminal metabolic activity increased steadily with the disease progression. Conclusions: The RBDRP expression in iRBD patients was altered significantly over time. Some of the brain metabolic changes seem to represent attempted functional compensation against ongoing neurodegeneration. The RBDRP expression measurement at one time point may not be a reliable biomarker for predicting disease conversion.

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“…The last decade has witnessed the development and clinical validation of large-scale metabolic brain networks involving widely-distributed functional neuroanatomical structures. This was especially true with FDG PET in patients with PD and atypical PD such as multiple system atrophy, progressive supranuclear palsy and cortico-basal degeneration (Teune et al, 2013 , Niethammer et al, 2014 , Peng et al, 2014b , Ge et al, 2018 , Schindlbeck and Eidelberg, 2018 , Meles et al, 2020 , Shen et al, 2020 ). Novel classification algorithms based on the expression levels of these networks provided accurate differential diagnosis even in early-stage parkinsonian populations (Tang et al, 2010 , Tripathi et al, 2016 ), given that DBS was ineffective in pathologically-confirmed patients with atypical PD who were inadvertently misdiagnosed to receive the invasive treatment (Meissner et al, 2016 ).…”

Section: Development Of New Frontiersmentioning

confidence: 99%

Neuroimaging evaluation of deep brain stimulation in the treatment of representative neurodegenerative and neuropsychiatric disorders

et al. 2021

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Brain stimulation technology has become a viable modality of reversible interventions in the effective treatment of many neurological and psychiatric disorders. It is aimed to restore brain dysfunction by the targeted delivery of specific electronic signal within or outside the brain to modulate neural activity on local and circuit levels. Development of therapeutic approaches with brain stimulation goes in tandem with the use of neuroimaging methodology in every step of the way. Indeed, multimodality neuroimaging tools have played important roles in target identification, neurosurgical planning, placement of stimulators and post-operative confirmation. They have also been indispensable in pre-treatment screen to identify potential responders and in post-treatment to assess the modulation of brain circuitry in relation to clinical outcome measures. Studies in patients to date have elucidated novel neurobiological mechanisms underlying the neuropathogenesis, action of stimulations, brain responses and therapeutic efficacy. In this article, we review some applications of deep brain stimulation for the treatment of several diseases in the field of neurology and psychiatry. We highlight how the synergistic combination of brain stimulation and neuroimaging technology is posed to accelerate the development of symptomatic therapies and bring revolutionary advances in the domain of bioelectronic medicine.

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Reproducible metabolic topographies associated with multiple system atrophy: Network and regional analyses in Chinese and American patient cohorts

Cited by 13 publications

References 41 publications

Cerebral Metabolism Related to Cognitive Impairments in Multiple System Atrophy

Cerebral Metabolism Related to Cognitive Impairments in Multiple System Atrophy

Longitudinal Changes in Isolated Rapid Eye Movement Sleep Behavior Disorder‐Related Metabolic Pattern Expression

Neuroimaging evaluation of deep brain stimulation in the treatment of representative neurodegenerative and neuropsychiatric disorders

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