Metabolic abnormalities associated with mild cognitive impairment in Parkinson disease

IGF-1 gene therapy prevents spatial memory deficits and modulates dopaminergic neurodegeneration and inflammation in a parkinsonism model

Cognitive impairment in Parkinson's disease is considered an indicator of the prodromal stages of this condition, occurring prior to the onset of classic and pathognomonic motor symptoms. Among other factors, neuroinflammation is increasingly recognized as a potential mediator of this neurodegenerative process, and glial cells are directly involved. However, the use of neurotrophic factors is associated with neuroprotection and cognitive improvements. Among all those factors, insulin-like growth factor 1 (IGF-1) has attracted considerable attention. In this study, we aimed to investigate the effect of IGF-1 gene therapy in an early animal model of 6-hydroxidopamine (6-OHDA)- induced parkinsonism. For this purpose, we employed male Wistar rats. The animals were first divided into two groups according to the bilateral injection into de Caudate Putamen unit (CPu):(a) VEH group (vehicle solution) and (b) 6-OHDA group (neurotoxic solution). After that, the animals in each group were divided, according to the bilateral injection into the dorsal hippocampus, in a control group (who received a control virus RAd-DSRed) and an experimental group (who received a therapeutic virus (RAd-IGF1). After three weeks of exposure to 6-OHDA, our study showed that IGF-1 gene therapy improved cognitive deficits related to short-term and spatial working memory, it also increased expression levels of tyrosine hydroxylase in the CPu. In addition, the therapy resulted in significant changes in several parameters (area, perimeter, roundness, ramification, and skeleton ́s analyses) related to microglia and astrocyte phenotypes, particularly in the CPu and dorsal hippocampal areas. Our data support the use of IGF-1 as a therapeutic molecule for future gene transfer interventions, that will contribute to a better understanding of the mechanisms correlating cognitive function and inflammatory process.

Pathobiology of Cognitive Impairment in Parkinson Disease: Challenges and Outlooks

Cognitive impairment (CI) is a characteristic non-motor feature of Parkinson disease (PD) that poses a severe burden on the patients and caregivers, yet relatively little is known about its pathobiology. Cognitive deficits are evident throughout the course of PD, with around 25% of subtle cognitive decline and mild CI (MCI) at the time of diagnosis and up to 83% of patients developing dementia after 20 years. The heterogeneity of cognitive phenotypes suggests that a common neuropathological process, characterized by progressive degeneration of the dopaminergic striatonigral system and of many other neuronal systems, results not only in structural deficits but also extensive changes of functional neuronal network activities and neurotransmitter dysfunctions. Modern neuroimaging studies revealed multilocular cortical and subcortical atrophies and alterations in intrinsic neuronal connectivities. The decreased functional connectivity (FC) of the default mode network (DMN) in the bilateral prefrontal cortex is affected already before the development of clinical CI and in the absence of structural changes. Longitudinal cognitive decline is associated with frontostriatal and limbic affections, white matter microlesions and changes between multiple functional neuronal networks, including thalamo-insular, frontoparietal and attention networks, the cholinergic forebrain and the noradrenergic system. Superimposed Alzheimer-related (and other concomitant) pathologies due to interactions between α-synuclein, tau-protein and β-amyloid contribute to dementia pathogenesis in both PD and dementia with Lewy bodies (DLB). To further elucidate the interaction of the pathomechanisms responsible for CI in PD, well-designed longitudinal clinico-pathological studies are warranted that are supported by fluid and sophisticated imaging biomarkers as a basis for better early diagnosis and future disease-modifying therapies.

Slower rates of prism adaptation but intact aftereffects in patients with early to mid-stage Parkinson's disease

There is currently mixed evidence on the effect of Parkinson's disease on motor adaptation. Some studies report that patients display adaptation comparable to age-matched controls, while others report a complete inability to adapt to novel sensory perturbations. Here, early to mid-stage Parkinson's patients were recruited to perform a prism adaptation task. When compared to controls, patients showed slower rates of initial adaptation but intact aftereffects. These results support the suggestion that patients with early to mid-stage Parkinson's disease display intact adaptation driven by sensory prediction errors, as shown by the intact aftereffect. But impaired facilitation of performance through cognitive strategies informed by task error, as shown by the impaired initial adaptation. These results support recent studies that suggest that patients with Parkinson's disease retain the ability to perform visuomotor adaptation, but display altered use of cognitive strategies to aid performance and generalises these previous findings to the classical prism adaptation task.

Functional Brain Networks to Evaluate Treatment Responses in Parkinson's Disease

Network analysis of functional brain scans acquired with [18F]-fluorodeoxyglucose positron emission tomography (FDG PET, to map cerebral glucose metabolism), or resting-state functional magnetic resonance imaging (rs-fMRI, to map blood oxygen level-dependent brain activity) has increasingly been used to identify and validate reproducible circuit abnormalities associated with neurodegenerative disorders such as Parkinson's disease (PD). In addition to serving as imaging markers of the underlying disease process, these networks can be used singly or in combination as an adjunct to clinical diagnosis and as a screening tool for therapeutics trials. Disease networks can also be used to measure rates of progression in natural history studies and to assess treatment responses in individual subjects. Recent imaging studies in PD subjects scanned before and after treatment have revealed therapeutic effects beyond the modulation of established disease networks. Rather, other mechanisms of action may be at play, such as the induction of novel functional brain networks directly by treatment. To date, specific treatment-induced networks have been described in association with novel interventions for PD such as subthalamic adeno-associated virus glutamic acid decarboxylase (AAV2-GAD) gene therapy, as well as sham surgery or oral placebo under blinded conditions. Indeed, changes in the expression of these networks with treatment have been found to correlate consistently with clinical outcome. In aggregate, these attributes suggest a role for functional brain networks as biomarkers in future clinical trials.

Comparison of univariate and multivariate analyses for brain [18F]FDG PET data in α-synucleinopathies

BACKGROUND

Brain imaging with [18F]FDG-PET can support the diagnostic work-up of patients with α-synucleinopathies. Validated data analysis approaches are necessary to evaluate disease-specific brain metabolism patterns in neurodegenerative disorders. This study compared the univariate Statistical Parametric Mapping (SPM) single-subject procedure and the multivariate Scaled Subprofile Model/Principal Component Analysis (SSM/PCA) in a cohort of patients with α-synucleinopathies.

METHODS

We included [18F]FDG-PET scans of 122 subjects within the α-synucleinopathy spectrum: Parkinson's Disease (PD) normal cognition on long-term follow-up (PD - low risk to dementia (LDR); n = 28), PD who developed dementia on clinical follow-up (PD - high risk of dementia (HDR); n = 16), Dementia with Lewy Bodies (DLB; n = 67), and Multiple System Atrophy (MSA; n = 11). We also included [18F]FDG-PET scans of isolated REM sleep behaviour disorder (iRBD; n = 51) subjects with a high risk of developing a manifest α-synucleinopathy. Each [18F]FDG-PET scan was compared with 112 healthy controls using SPM procedures. In the SSM/PCA approach, we computed the individual scores of previously identified patterns for PD, DLB, and MSA: PD-related patterns (PDRP), DLBRP, and MSARP. We used ROC curves to compare the diagnostic performances of SPM t-maps (visual rating) and SSM/PCA individual pattern scores in identifying each clinical condition across the spectrum. Specifically, we used the clinical diagnoses ("gold standard") as our reference in ROC curves to evaluate the accuracy of the two methods. Experts in movement disorders and dementia made all the diagnoses according to the current clinical criteria of each disease (PD, DLB and MSA).

RESULTS

The visual rating of SPM t-maps showed higher performance (AUC: 0.995, specificity: 0.989, sensitivity 1.000) than PDRP z-scores (AUC: 0.818, specificity: 0.734, sensitivity 1.000) in differentiating PD-LDR from other α-synucleinopathies (PD-HDR, DLB and MSA). This result was mainly driven by the ability of SPM t-maps to reveal the limited or absent brain hypometabolism characteristics of PD-LDR. Both SPM t-maps visual rating and SSM/PCA z-scores showed high performance in identifying DLB (DLBRP = AUC: 0.909, specificity: 0.873, sensitivity 0.866; SPM t-maps = AUC: 0.892, specificity: 0.872, sensitivity 0.910) and MSA (MSARP: AUC: 0.921, specificity: 0.811, sensitivity 1.000; SPM t-maps: AUC: 1.000, specificity: 1.000, sensitivity 1.000) from other α-synucleinopathies. PD-HDR and DLB were comparable for the brain hypo and hypermetabolism patterns, thus not allowing differentiation by SPM t-maps or SSM/PCA. Of note, we found a gradual increase of PDRP and DLBRP expression in the continuum from iRBD to PD-HDR and DLB, where the DLB patients had the highest scores. SSM/PCA could differentiate iRBD from DLB, reflecting specifically the differences in disease staging and severity (AUC: 0.938, specificity: 0.821, sensitivity 0.941).

CONCLUSIONS

SPM-single subject maps and SSM/PCA are both valid methods in supporting diagnosis within the α-synucleinopathy spectrum, with different strengths and pitfalls. The former reveals dysfunctional brain topographies at the individual level with high accuracy for all the specific subtype patterns, and particularly also the normal maps; the latter provides a reliable quantification, independent from the rater experience, particularly in tracking the disease severity and staging. Thus, our findings suggest that differences in data analysis approaches exist and should be considered in clinical settings. However, combining both methods might offer the best diagnostic performance.

Subjective cognitive decline in patients with Parkinson's disease: an updated review

Cognitive impairment in patients with Parkinson's disease (PD) worsens the prognosis of PD and increases caregivers' burden and economic consequences. Recently, subjective cognitive decline (SCD), which refers to self-reported cognitive decline without detectable objective cognitive dysfunction, has been regarded as an at-risk state of mild cognitive impairment (MCI) and a prodromal stage for dementia in Alzheimer's disease (AD). However, studies on PD-SCD have thus far been scarce, and at present there is no consensus regarding the definition of SCD nor a gold standard as an evaluation tool. The present review aimed to look for an association between PD-SCD and objective cognitive function and found that PD with SCD occurred with brain metabolic changes, which were consistent with early aberrant pathological changes in PD. Moreover, PD patients with SCD were likely to progress to future cognitive impairment. It is necessary to establish a guideline for the definition and evaluation of SCD in PD. A larger sample size and more longitudinal investigations are needed to verify the predictive effectiveness of PD-SCD and to detect earlier subtle cognitive decline before MCI.

Functional brain networks in the evaluation of patients with neurodegenerative disorders

Network analytical tools are increasingly being applied to brain imaging maps of resting metabolic activity (PET) or blood oxygenation-dependent signals (functional MRI) to characterize the abnormal neural circuitry that underlies brain diseases. This approach is particularly valuable for the study of neurodegenerative disorders, which are characterized by stereotyped spread of pathology along discrete neural pathways. Identification and validation of disease-specific brain networks facilitate the quantitative assessment of pathway changes over time and during the course of treatment. Network abnormalities can often be identified before symptom onset and can be used to track disease progression even in the preclinical period. Likewise, network activity can be modulated by treatment and might therefore be used as a marker of efficacy in clinical trials. Finally, early differential diagnosis can be achieved by simultaneously measuring the activity levels of multiple disease networks in an individual patient's scans. Although these techniques were originally developed for PET, over the past several years analogous methods have been introduced for functional MRI, a more accessible non-invasive imaging modality. This advance is expected to broaden the application of network tools to large and diverse patient populations.

Structural and metabolic correlates of neuropsychological profiles in multiple system atrophy and Parkinson's disease

BACKGROUND

Despite increased recognition of cognitive impairment in Multiple System Atrophy (MSA), its neuroanatomical correlates are not well defined. We aimed to explore cognitive profiles in MSA with predominant parkinsonism (MSA-P) and Parkinson's disease (PD) and their relationship to frontostriatal structural and metabolic changes.

METHODS

Detailed clinical and neuropsychological evaluation was performed together with diffusion tensor imaging (DTI) and [¹⁸F]-fluoro-deoxyglucose positron emission tomography ([¹⁸F]-FDG-PET) in patients with MSA-P (n = 11) and PD (n = 11). We compared clinical and neuropsychological data to healthy controls (n = 9) and correlated neuropsychological data with imaging findings in MSA-P and PD.

RESULTS

Patients with MSA-P showed deficits in executive function (Trail Making Test B-A) and scored higher in measures of depression and anxiety compared to those with PD and healthy controls. Widespread frontostriatal white matter tract reduction in fractional anisotropy was seen in MSA-P and PD compared to an imaging control group. Stroop Test interference performance correlated with [¹⁸F]-FDG uptake in the bilateral dorsolateral prefrontal cortex (DLPFC) and with white matter integrity between the striatum and left inferior frontal gyrus (IFG) in PD. Trail Making Test performance correlated with corticostriatal white matter integrity along tracts from the bilateral IFG in MSA-P and from the right DLPFC in both groups.

CONCLUSION

Executive dysfunction was more prominent in patients with MSA-P compared to PD. DLPFC metabolism and frontostriatal white matter integrity seem to be a driver of executive function in PD, whereas alterations in corticostriatal white matter integrity may contribute more to executive dysfunction in MSA-P.

Deep learning signature of brain [18F]FDG PET associated with cognitive outcome of rapid eye movement sleep behavior disorder

An objective biomarker to predict the outcome of isolated rapid eye movement sleep behavior disorder (iRBD) is crucial for the management. This study aimed to investigate cognitive signature of brain [¹⁸F]FDG PET based on deep learning (DL) for evaluating patients with iRBD. Fifty iRBD patients, 19 with mild cognitive impairment (MCI) (RBD-MCI) and 31 without MCI (RBD-nonMCI), were prospectively enrolled. A DL model for the cognitive signature was trained by using Alzheimer's Disease Neuroimaging Initiative database and transferred to baseline [¹⁸F]FDG PET from the iRBD cohort. The results showed that the DL-based cognitive dysfunction score was significantly higher in RBD-MCI than in RBD-nonMCI. The AUC of ROC curve for differentiating RBD-MCI from RBD-nonMCI was 0.70 (95% CI 0.56-0.82). The baseline DL-based cognitive dysfunction score was significantly higher in iRBD patients who showed a decrease in CERAD scores during 2 years than in those who did not. Brain metabolic features related to cognitive dysfunction-related regions of individual iRBD patients mainly included posterior cortical regions. This work demonstrates that the cognitive signature based on DL could be used to objectively evaluate cognitive function in iRBD. We suggest that this approach could be extended to an objective biomarker predicting cognitive decline and neurodegeneration in iRBD.

The neuroprotective effects of glucagon-like peptide 1 in Alzheimer’s and Parkinson’s disease: An in-depth review

Currently, there is no disease-modifying treatment available for Alzheimer’s and Parkinson’s disease (AD and PD) and that includes the highly controversial approval of the Aβ-targeting antibody aducanumab for the treatment of AD. Hence, there is still an unmet need for a neuroprotective drug treatment in both AD and PD. Type 2 diabetes is a risk factor for both AD and PD. Glucagon-like peptide 1 (GLP-1) is a peptide hormone and growth factor that has shown neuroprotective effects in preclinical studies, and the success of GLP-1 mimetics in phase II clinical trials in AD and PD has raised new hope. GLP-1 mimetics are currently on the market as treatments for type 2 diabetes. GLP-1 analogs are safe, well tolerated, resistant to desensitization and well characterized in the clinic. Herein, we review the existing evidence and illustrate the neuroprotective pathways that are induced following GLP-1R activation in neurons, microglia and astrocytes. The latter include synaptic protection, improvements in cognition, learning and motor function, amyloid pathology-ameliorating properties (Aβ, Tau, and α-synuclein), the suppression of Ca2+ deregulation and ER stress, potent anti-inflammatory effects, the blockage of oxidative stress, mitochondrial dysfunction and apoptosis pathways, enhancements in the neuronal insulin sensitivity and energy metabolism, functional improvements in autophagy and mitophagy, elevated BDNF and glial cell line-derived neurotrophic factor (GDNF) synthesis as well as neurogenesis. The many beneficial features of GLP-1R and GLP-1/GIPR dual agonists encourage the development of novel drug treatments for AD and PD.

Recent Investigations on the Functional Role of Cerebellar Neural Networks in Motor Functions & Nonmotor Functions -Neurodegeneration

The cerebellum is a well-established primary brain center in charge of controlling sensorimotor functions and non-motor functions. Recent reports depicted the significance of cerebellum in higher-order cognitive functions, including emotion-processing, language, reward-related behavior, working memory, and social behavior. As it can influence diverse behavioral patterns, any defects in cerebellar functions could invoke neuropsychiatric diseases as indicated by the incidence of alexithymia and induce alterations in emotional and behavioral patterns. Furthermore, its defects can trigger motor diseases, such as ataxia and Parkinson's disease (PD). In this review, we have extensively discussed the role of cerebellum in motor and non-motor functions and how the cerebellum malfunctions in relation to the neural circuit wiring as it could impact brain function and behavioral outcomes in patients with neuropsychiatric diseases. Relevant data regarding cerebellar non-motor functions have been vividly described, along with anatomy and physiology of these functions. In addition to the defects in basal ganglia, the lack of activity in motor related regions of the cerebellum could be associated with the severity of motor symptoms. All together, this review delineates the importance of cerebellar involvement in patients with PD and unravels a crucial link for various clinical aspects of PD with specific cerebellar sub-regions.

Morphological basis of Parkinson disease-associated cognitive impairment: an update

Cognitive impairment is one of the most salient non-motor symptoms of Parkinson disease (PD) that poses a significant burden on the patients and carers as well as being a risk factor for early mortality. People with PD show a wide spectrum of cognitive dysfunctions ranging from subjective cognitive decline and mild cognitive impairment (MCI) to frank dementia. The mean frequency of PD with MCI (PD-MCI) is 25.8% and the pooled dementia frequency is 26.3% increasing up to 83% 20 years after diagnosis. A better understanding of the underlying pathological processes will aid in directing disease-specific treatment. Modern neuroimaging studies revealed considerable changes in gray and white matter in PD patients with cognitive impairment, cortical atrophy, hypometabolism, dopamine/cholinergic or other neurotransmitter dysfunction and increased amyloid burden, but multiple mechanism are likely involved. Combined analysis of imaging and fluid markers is the most promising method for identifying PD-MCI and Parkinson disease dementia (PDD). Morphological substrates are a combination of Lewy- and Alzheimer-associated and other concomitant pathologies with aggregation of α-synuclein, amyloid, tau and other pathological proteins in cortical and subcortical regions causing destruction of essential neuronal networks. Significant pathological heterogeneity within PD-MCI reflects deficits in various cognitive domains. This review highlights the essential neuroimaging data and neuropathological changes in PD with cognitive impairment, the amount and topographical distribution of pathological protein aggregates and their pathophysiological relevance. Large-scale clinicopathological correlative studies are warranted to further elucidate the exact neuropathological correlates of cognitive impairment in PD and related synucleinopathies as a basis for early diagnosis and future disease-modifying therapies.

Clinical evaluation and resting state fMRI analysis of virtual reality based training in Parkinson’s disease through a randomized controlled trial

There are few studies investigating the short-term effects of Virtual Reality based Exergaming (EG) on motor and cognition simultaneously and pursue the brain functional activity changes after these interventions in patients with Parkinson’s Disease (PD). The purpose of this study was to investigate the synergistic therapeutic effects of Virtual Reality based EG on motor and cognitive symptoms in PD and its possible effects on neuroplasticity. Eligible patients with the diagnosis of PD were randomly assigned to one of the two study groups: (1) an experimental EG group, (2) an active control Exercise Therapy (ET) group. All patients participated in a 4-week exercise program consisting of 12 treatment sessions. Every session lasted 60 min. Participants underwent a motor evaluation, extensive neuropsychological assessment battery and rs-fMRI before and after the interventions. Thirty patients fulfilled the inclusion criteria and were randomly assigned to the EG and ET groups. After the dropouts, 23 patients completed the assessments and interventions (11 in EG, 13 in ET). Within group analysis showed significant improvements in both groups. Between group comparisons considering the interaction of group × time effect, showed superiority of EG in terms of general cognition, delayed visual recall memory and Boston Naming Test. These results were consistent in the within-group and between-group analysis. Finally, rs-fMRI analysis showed increased activity in the precuneus region in the time × group interaction in the favor of EG group. EG can be an effective alternative in terms of motor and cognitive outcomes in patients with PD. Compared to ET, EG may affect brain functional connectivity and can have beneficial effects on patients’ cognitive functions and motor symptoms. Whenever possible, using EG and ET in combination, may have the better effects on patients daily living and patients can benefit from the advantages of both interventions.

Neural correlates and predictors of subjective cognitive decline in patients with Parkinson's disease

BACKGROUND

Subjective cognitive decline (SCD) may occur very early in the course of Parkinson's disease (PD) before the onset of objective cognitive decline. Data on neural correlates and determinants of SCD in PD are rare.

OBJECTIVE

The aim of the present study was to identify neural correlates as well as sociodemographic, clinical, and neuropsychological predictors of SCD in patients with PD.

METHODS

We retrospectively analyzed 30 patients with PD without cognitive impairment (23% female, 66.90 ± 7.20 years, UPDRS-III: 19.83 ± 9.29), of which n = 12 patients were classified as having no SCD (control group, PD-CG) and n = 18 as having SCD (PD-SCD). Neuropsychological testing and 18-fluoro-2-deoxyglucose positron emission tomography (FDG-PET) were conducted. SCD was assessed using a questionnaire covering multiple cognitive domains.

RESULTS

SCD subscores differed significantly between PD-CG and PD-SCD and correlated significantly with other scales measuring related concepts. FDG-PET whole-brain voxel-wise regression analysis revealed hypometabolism in middle frontal, middle temporal, and occipital areas, and the angular gyrus as neural correlates of SCD in PD. Next to this hypometabolism, depressive symptoms were an independent significant determinant of SCD in a stepwise regression analysis (adjusted R2 = 50.3%).

CONCLUSION

This study strengthens the hypothesis of SCD being an early manifestation of future cognitive decline in PD and, more generally, early pathological changes in PD. The early identification of the vulnerability for future cognitive decline constitutes the basis for successful prevention and delay of this non-motor symptom.

Metabolic imaging and plasticity

Positron emission tomography greatly advanced our understanding on the underlying neural mechanisms of movement disorders. PET with flurodeoxyglucose (FDG) is especially useful as it depicts regional metabolic activity level that can predict patients' symptoms. Multivariate pattern analysis has been used to determine and quantify the co-varying brain networks associated with specific clinical traits of neurodegenerative disease. The result is a biomarker, useful for diagnosis, treatments, and follow up studies. Parkinsonian traits and parkinsonisms are associated with specific spatial pattern of metabolic abnormality useful for differential diagnosis. This approach has also been used for monitoring disease progression and novel treatment responses mostly in Parkinson's disease. In this book chapter, we, illustrate and discuss the significance of the brain networks associated with disease and their modification with neuroplastic changes.

The Role of Monoaminergic Tones and Brain Metabolism in Cognition in De Novo Parkinson's Disease

BACKGROUND

Cognitive impairment is frequent in Parkinson's disease (PD) and several neurotransmitter changes have been reported since the time of diagnosis, although seldom investigated altogether in the same patient cohort.

OBJECTIVE

Our aim was to evaluate the association between neurotransmitter impairment, brain metabolism, and cognition in a cohort of de novo, drug-naïve PD patients.

METHODS

We retrospectively selected 95 consecutive drug-naïve PD patients (mean age 71.89±7.53) undergoing at the time of diagnosis a brain [18F]FDG-PET as a marker of brain glucose metabolism and proxy measure of neurodegeneration, [123I]FP-CIT-SPECT as a marker and dopaminergic deafferentation in the striatum and frontal cortex, as well as a marker of serotonergic deafferentation in the thalamus, and quantitative electroencephalography (qEEG) as an indirect measure of cholinergic deafferentation. Patients also underwent a complete neuropsychological battery.

RESULTS

Positive correlations were observed between (i) executive functions and left cerebellar cortex metabolism, (ii) prefrontal dopaminergic tone and working memory (r = 0.304, p = 0.003), (iii) qEEG slowing in the posterior leads and both memory (r = 0.299, p = 0.004) and visuo-spatial functions (r = 0.357, p < 0.001).

CONCLUSIONS

In subjects with PD, the impact of regional metabolism and diffuse projection systems degeneration differs across cognitive domains. These findings suggest possible tailored approaches to the treatment of cognitive deficits in PD.

Imaging Cognitive Impairment and Impulse Control Disorders in Parkinson's Disease

Dementia and mild forms of cognitive impairment as well as neuropsychiatric symptoms (i. e., impulse control disorders) are frequent and disabling non-motor symptoms of Parkinson's disease (PD). The identification of changes in neuroimaging studies for the early diagnosis and monitoring of the cognitive and neuropsychiatric symptoms associated with Parkinson's disease, as well as their pathophysiological understanding, are critical for the development of an optimal therapeutic approach. In the current literature review, we present an update on the latest structural and functional neuroimaging findings, including high magnetic field resonance and radionuclide imaging, assessing cognitive dysfunction and impulse control disorders in PD.

Frontoparietal network resilience is associated with protection against cognitive decline in Parkinson's disease

Though Parkinson's disease is primarily defined as a movement disorder, it is also characterized by a range of non-motor symptoms, including cognitive decline. The onset and progression of cognitive decline in individuals with Parkinson's disease is variable, and the neurobiological mechanisms that contribute to, or protect against, cognitive decline in Parkinson's disease are poorly understood. Using resting-state functional magnetic resonance imaging data collected from individuals with Parkinson's disease with and without cognitive decline, we examined the relationship between topological brain-network resilience and cognition in Parkinson's disease. By leveraging network attack analyses, we demonstrate that relative to individuals with Parkinson's disease experiencing cognitive decline, the frontoparietal network in cognitively stable individuals with Parkinson's disease is significantly more resilient to network perturbation. Our findings suggest that the topological robustness of the frontoparietal network is associated with the absence of cognitive decline in individuals with Parkinson's disease.

Cognition-Related Functional Topographies in Parkinson's Disease: Localized Loss of the Ventral Default Mode Network

Cognitive dysfunction in Parkinson's disease (PD) is associated with increased expression of the PD cognition-related pattern (PDCP), which overlaps with the normal default mode network (DMN). Here, we sought to determine the degree to which the former network represents loss of the latter as a manifestation of the disease process. To address this, we first analyzed metabolic images (fluorodeoxyglucose positron emission tomography [PET]) from a large PD sample with varying cognitive performance. Cognitive impairment in these patients correlated with increased PDCP expression as well as DMN loss. We next determined the spatial relationship of the 2 topographies at the subnetwork level. To this end, we analyzed resting-state functional magnetic resonance imaging (rs-fMRI) data from an independent population. This approach uncovered a significant PD cognition-related network that resembled previously identified PET- and rs-fMRI-based PDCP topographies. Further analysis revealed selective loss of the ventral DMN subnetwork (precuneus and posterior cingulate cortex) in PD, whereas the anterior and posterior components were not affected by the disease. Importantly, the PDCP also included a number of non-DMN regions such as the dorsolateral prefrontal and medial temporal cortex. The findings show that the PDCP is a reproducible cognition-related network that is topographically distinct from the normal DMN.

Meta-Analysis of Cognition in Parkinson's Disease Mild Cognitive Impairment and Dementia Progression

Mild cognitive changes, including executive dysfunction, are seen in Parkinson's Disease (PD). Approximately 30% of individuals with PD develop Parkinson's disease dementia (PDD). Mild cognitive impairment (MCI) has been identified as a transitional state between normal cognition and dementia. Although PD-MCI and its cognitive correlates have been increasingly studied as a risk indicator for development of PDD, investigations into the PD-MCI construct have yielded heterogeneous findings. Thus, a typical PD-MCI cognitive profile remains undefined. The present meta-analysis examined published cross-sectional studies of PD-MCI and cognitively normal PD (PD-CN) groups to provide aggregated effect sizes of group test performance by cognitive domain. Subsequently, longitudinal studies examining PD-MCI to PDD progression were meta-analyzed. Ninety-two cross-sectional articles of PD-MCI vs. PD-CN were included; 5 longitudinal studies of PD-MCI conversion to PDD were included. Random effects meta-analytic models were constructed resulting in effect sizes (Hedges' g) for cognitive domains. Overall performance across all measures produced a large effect size (g = 0.83, 95% CI [0.79, 0.86], t² = 0.18) in cross-sectional analyses, with cognitive screeners producing the largest effect (g = 1.09, 95% CI [1.00, 1.17], t² = 0.19). Longitudinally, overall measures produced a moderate effect (g = 0.47, 95% CI [0.40, 0.53], t² = 0.01), with measures of executive functioning exhibiting the largest effect (g = 0.70, 95% CI [0.51, 0.89], t² = 0.01). Longitudinal effects were made more robust by low heterogeneity. This report provides the first comprehensive meta-analysis of PD-MCI cognitive outcomes and predictors in PD-MCI conversion to PDD. Limitations include heterogeneity of cross-sectional effect sizes and the potential impact of small-study effects. Areas for continued research include visuospatial skills and visual memory in PD-MCI and longitudinal examination of executive dysfunction in PD-MCI.

Modulating brain networks associated with cognitive deficits in Parkinson's disease

Parkinson’s disease (PD) is a relatively well characterised neurological disorder that primarily affects motor and cognitive functions. This paper reviews on how transcranial direct current stimulation (tDCS) can be used to modulate brain networks associated with cognitive deficits in PD. We first provide an overview of brain network abnormalities in PD, by introducing the brain network modulation approaches such as pharmacological interventions and brain stimulation techniques. We then present the potential underlying mechanisms of tDCS technique, and specifically highlight how tDCS can be applied to modulate brain network abnormality associated with cognitive dysfunction among PD patients. More importantly, we address the limitations of existing studies and suggest possible future directions, with the aim of helping researchers to further develop the use of tDCS technique in clinical settings.

The default mode network and cognition in Parkinson's disease: A multimodal resting-state network approach

Involvement of the default mode network (DMN) in cognitive symptoms of Parkinson's disease (PD) has been reported by resting-state functional MRI (rsfMRI) studies. However, the relation to metabolic measures obtained by [18F]-fluorodeoxyglucose positron emission tomography (FDG-PET) is largely unknown. We applied multimodal resting-state network analysis to clarify the association between intrinsic metabolic and functional connectivity abnormalities within the DMN and their significance for cognitive symptoms in PD. PD patients were classified into normal cognition (n = 36) and mild cognitive impairment (MCI; n = 12). The DMN was identified by applying an independent component analysis to FDG-PET and rsfMRI data of a matched subset (16 controls and 16 PD patients) of the total cohort. Besides metabolic activity, metabolic and functional connectivity within the DMN were compared between the patients' groups and healthy controls (n = 16). Glucose metabolism was significantly reduced in all DMN nodes in both patient groups compared to controls, with the lowest uptake in PD-MCI (p < .05). Increased metabolic and functional connectivity along fronto-parietal connections was identified in PD-MCI patients compared to controls and unimpaired patients. Functional connectivity negatively correlated with cognitive composite z-scores in patients (r = -.43, p = .005). The current study clarifies the commonalities of metabolic and hemodynamic measures of brain network activity and their individual significance for cognitive symptoms in PD, highlighting the added value of multimodal resting-state network approaches for identifying prospective biomarkers.

Acylated Ghrelin as a Multi-Targeted Therapy for Alzheimer's and Parkinson's Disease

Much thought has been given to the impact of Amyloid Beta, Tau and Alpha-Synuclein in the development of Alzheimer's disease (AD) and Parkinson's disease (PD), yet the clinical failures of the recent decades indicate that there are further pathological mechanisms at work. Indeed, besides amyloids, AD and PD are characterized by the culminative interplay of oxidative stress, mitochondrial dysfunction and hyperfission, defective autophagy and mitophagy, systemic inflammation, BBB and vascular damage, demyelination, cerebral insulin resistance, the loss of dopamine production in PD, impaired neurogenesis and, of course, widespread axonal, synaptic and neuronal degeneration that leads to cognitive and motor impediments. Interestingly, the acylated form of the hormone ghrelin has shown the potential to ameliorate the latter pathologic changes, although some studies indicate a few complications that need to be considered in the long-term administration of the hormone. As such, this review will illustrate the wide-ranging neuroprotective properties of acylated ghrelin and critically evaluate the hormone's therapeutic benefits for the treatment of AD and PD.

Spectral guided sparse inverse covariance estimation of metabolic networks in Parkinson's disease

In neurodegenerative disorders, a clearer understanding of the underlying aberrant networks facilitates the search for effective therapeutic targets and potential cures. [¹⁸F]-fluorodeoxyglucose (FDG) positron emission tomography (PET) imaging data of brain metabolism reflects the distribution of glucose consumption known to be directly related to neural activity. In FDG PET resting-state metabolic data, characteristic disease-related patterns have been identified in group analysis of various neurodegenerative conditions using principal component analysis of multivariate spatial covariance. Notably, among several parkinsonian syndromes, the identified Parkinson’s disease-related pattern (PDRP) has been repeatedly validated as an imaging biomarker of PD in independent groups worldwide. Although the primary nodal associations of this network are known, its connectivity is not fully understood. Here, we describe a novel approach to elucidate functional principal component (PC) network connections by performing graph theoretical sparse network derivation directly within the disease relevant PC partition layer of the whole brain data rather than by searching for associations retrospectively in whole brain sparse representations. Using sparse inverse covariance estimation of each overlapping PC partition layer separately, a single coherent network is detected for each layer in contrast to more spatially modular segmentation in whole brain data analysis. Using this approach, the major nodal hubs of the PD disease network are identified and their characteristic functional pathways are clearly distinguished within the basal ganglia, midbrain and parietal areas. Network associations are further clarified using Laplacian spectral analysis of the adjacency matrices. In addition, the innate discriminative capacity of the eigenvector centrality of the graph derived networks in differentiating PD versus healthy external data provides evidence of their validity.

Association Between REM Sleep Behavior Disorder and Cognitive Dysfunctions in Parkinson's Disease: A Systematic Review and Meta-Analysis of Observational Studies

Background: Rapid eye movement sleep behavior disorder (RBD) is thought to be a prodromal symptom of Parkinson's disease (PD). RBD is also thought to be involved in cognitive decline and dementia in PD. In PD, although the relationship between RBD and cognitive dysfunctions was confirmed by considerable studies, whether RBD was associated with distinct types of cognitive defects is worth of study. Objectives: This systematic review summarizes the evidence relating to cognitive dysfunction in PD patients with RBD (PD-RBD) and those without and explores their specificity to cognitive domains. Methods: A meta-analysis using a random-effects model was performed for 16 different cognitive domains, including global cognitive function, memory (long-term verbal recall, long-term verbal recognition, long-term visual recall, short-term spatial recall, and short-term verbal recall), executive function (general, fluid reasoning, generativity, shifting, inhibition, and updating), language, processing speed/complex attention/working memory, visuospatial/constructional ability, and psychomotor ability. The cognitive difference between the groups of patients was measured as a standardized mean difference (SMD, Cohen's d). PD-RBD patients were classified into Confirmed-RBD (definite diagnosis with polysomnography, PSG) and Probable-RBD (without PSG re-confirmation). In some domains, RBD patients could not be analyzed separately due to the exiguity of primary studies; this analysis refers to such RBD patients as "Mixed-RBD." Results: Thirty-nine studies with 6,695 PD subjects were finally included. Confirmed-RBD patients showed worse performance than those without in global cognitive function, long-term verbal recall, long-term verbal recognition, generativity, inhibition, shifting, language, and visuospatial/constructional ability; Probable-RBD, in global cognitive function and shifting; and Mixed-RBD, in long-term visual recall, short-term spatial recall, general executive function, and processing speed/complex attention/working memory. Conclusion: This meta-analysis strongly suggests a relationship between RBD, Confirmed-RBD in particular, and cognitive dysfunctions in PD patients. Early and routine screening by sensitive and targeted cognitive tasks is necessary for all PD-RBD patients because it may offer the therapeutic time window before they evolve to irreversible dementia.

Parkinson Disease-Related Pattern of Glucose Metabolism Associated With the Potential for Motor Improvement After Deep Brain Stimulation

BACKGROUND

Motor dysfunctions in Parkinson disease (PD) patients are not completely normalized by deep brain stimulation (DBS), and there is an obvious difference in the degree of symptom improvement after DBS for each patient.

OBJECTIVE

To test our hypothesis that each patient has their own restoration capacity for motor improvement after DBS, and to investigate whether regional cerebral glucose metabolism in 18F-fluorodeoxyglucose positron emission tomography (FDG-PET) scans is associated with the capacity for off-medication motor improvement (MIoff) after DBS.

METHODS

The MIoff (%) was calculated using the Unified Parkinson's Disease Rating Scale part III in 27 PD patients undergoing DBS in the globus pallidus interna. The standardized uptake value ratios (SUVRs) on FDG-PET were quantitatively measured, and the areas where the SUVR correlated with the MIoff (%) were identified. Also, the areas where the SUVR was significantly different between the 2 MIoff groups (≥60% vs <60%) were determined.

RESULTS

Ten patients achieved MIoff > 60% at 12 mo after DBS. In general, the MIoff (%) was positively correlated with preoperative SUVR in the temporo-parieto-occipital lobes, while it was inversely correlated with the metabolism in the primary motor cortex. The patients in the MIoff < 60% group showed a significant decrease in SUVR in the parieto-occipital lobes, while parieto-occipital metabolism in those with MIoff ≥ 60% was relatively preserved (Mann-Whitney U test, P = .03).

CONCLUSION

Our findings suggest that the parieto-occipital lobes may be implicated more generally in the prognosis of motor improvement after DBS in advanced PD than other regions.

Parietal Perfusion Alterations in Parkinson's Disease Patients Without Dementia

Fronto-parietal regions are involved in cognitive processes that are commonly affected in Parkinson's disease (PD). The aims of this study were to investigate cerebral blood flow (CBF) and gray matter (GM) volume within the regions belonging to the fronto-parietal circuit in people with PD (pwPD) without dementia, and to assess their association with cognitive performance. Twenty-seven pwPD without dementia (mean [SD] age = 67.4 [8.1] years, 20 males, mean [SD] Montreal Cognitive Assessment, MoCA score = 24.2 [2.9], median [IQR] Hoehn and Yahr scale = 1.5 [1–2]) and twenty-six age- and sex-matched healthy controls (HC) were scanned with arterial spin labeling (ASL) and T1-weighted magnetic resonance imaging (MRI) sequences to investigate CBF and GM volume, respectively. The cognitive performance of the enrolled pwPD was assessed with MoCA, Trail Making Test (TMT, part A, B, B-A), phonemic fluency and semantic fluency tests. The scores were adjusted for age and education. After standard preprocessing, CBF differences between pwPD and HC were tested with a voxel-wise approach. Voxel-based morphometry was used to compare pwPD and HC in terms of GM volume. Both voxel-wise comparisons between pwPD and HC were restricted to regions of the fronto-parietal circuit. The following additional voxel-wise analyses were performed within regions showing either perfusion or GM volume alterations: (1) correlation with neuropsychological test scores; (2) subgroup comparison after median split on each neuropsychological test score. Family-wise error-corrected (FWE) p-values lower than 0.05 were considered significant. Significant hypoperfusion was identified in the left inferior parietal lobule (IPL, p_peak = 0.037) and in the bilateral superior parietal lobule (SPL, left hemisphere: p_peak = 0.037; right hemisphere: p_peak = 0.049) of pwPD when compared to HC. No significant GM atrophy was observed. Local hypoperfusion did not correlate with any neuropsychological test scores. However, significantly lower CBF was observed in the left SPL and IPL of the pwPD subgroup who performed poorer on TMT part A in comparison with the pwPD subgroup that performed better. Perfusion alterations may occur in parietal regions of pwPD without dementia, and may be associated with lower visuomotor skills. Parietal CBF may be considered as a suitable early biomarker for longitudinal studies investigating cognitive decline in PD.

Cerebellar Contribution to Motor and Non-motor Functions in Parkinson's Disease: A Meta-Analysis of fMRI Findings

Background: Parkinson's disease (PD) results in both motor and non-motor symptoms. Traditionally, the underlying mechanism of PD has been linked to neurodegeneration of the basal ganglia. Yet it does not adequately account for the non-motor symptoms of the disease, suggesting that other brain regions may be involved. One such region is the cerebellum, which is known to be involved, together with the basal ganglia, in both motor and non-motor functions. Many studies have found the cerebellum to be hyperactive in PD patients, a finding that is seldom discussed in detail, and warrants further examination. The current study thus aims to examine quantitively the current literature on the cerebellar involvement in both motor and non-motor functioning in PD. Methods: A meta-analysis of functional neuroimaging literature was conducted with Seed-based D mapping. Only the studies testing functional activation in response to motor and non-motor paradigms in PD and healthy controls (HC) were included in the meta-analysis. Separate analyses were conducted by including only studies with non-motor paradigms, as well as meta-regressions with UPDRS III scores and disease duration. Results: A total of 57 studies with both motor and non-motor paradigms fulfilled our inclusion criteria and were included in the meta-analysis, which revealed hyperactivity in Crus I-II and vermal III in PD patients compared to HC. An analysis including only studies with cognitive paradigms revealed a cluster of increased activity in PD patients encompassing lobule VIIB and VIII. Another meta-analysis including the only 20 studies that employed motor paradigms did not reveal any significant group differences. However, a descriptive analysis of these studies revealed that 60% of them reported cerebellar hyperactivations in PD and included motor paradigm with significant cognitive task demands, as opposed to 40% presenting the opposite pattern and using mainly force grip tasks. The meta-regression with UPDRS III scores found a negative association between motor scores and activation in lobule VI and vermal VII-VIII. No correlation was found with disease duration. Discussion: The present findings suggest that one of the main cerebellar implications in PD is linked to cognitive functioning. The negative association between UPDRS scores and activation in regions implicated in motor functioning indicate that there is less involvement of these areas as the disease severity increases. In contrast, the lack of correlation with disease duration seems to indicate that the cerebellar activity may be a compensatory mechanism to the dysfunctional basal ganglia, where certain sub-regions of the cerebellum are employed to cope with motor demands. Yet future longitudinal studies are needed to fully address this possibility.

Correlations of Neuropsychological and Metabolic Brain Changes in Parkinson's Disease and Other α-Synucleinopathies

Cognitive impairment is a common feature in Parkinson's disease (PD) and other α-synucleinopathies as 80% of PD patients develop dementia within 20 years. Early cognitive changes in PD patients present as a dysexecutive syndrome, broadly characterized as a disruption of the fronto-striatal dopamine network. Cognitive deficits in other domains (recognition memory, attention processes and visuospatial abilities) become apparent with the progression of PD and development of dementia. In dementia with Lewy bodies (DLB) the cognitive impairment develops early or even precedes parkinsonism and it is more pronounced in visuospatial skills and memory. Cognitive impairment in the rarer α-synucleinopathies (multiple system atrophy and pure autonomic failure) is less well studied. Metabolic brain imaging with positron emission tomography and [¹⁸F]-fluorodeoxyglucose (FDG-PET) is a well-established diagnostic method in neurodegenerative diseases, including dementias. Changes in glucose metabolism precede those seen on structural magnetic resonance imaging (MRI). Reduction in glucose metabolism and atrophy have been suggested to represent consecutive changes of neurodegeneration and are linked to specific cognitive disorders (e.g., dysexecutive syndrome, memory impairment, visuospatial deficits etc.). Advances in the statistical analysis of FDG-PET images enabling a network analysis broadened our understanding of neurodegenerative brain processes. A specific cognitive pattern related to PD was identified by applying voxel-based network modeling approach. The magnitude of this pattern correlated significantly with patients' cognitive skills. Specific metabolic brain changes were observed also in patients with DLB as well as in a prodromal phase of α-synucleinopathy: REM sleep behavior disorder. Metabolic brain imaging with FDG-PET is a reliable biomarker of neurodegenerative brain diseases throughout their course, precisely reflecting their topographic distribution, stage and functional impact.

Associations Between Tau, β-Amyloid, and Cognition in Parkinson Disease

Importance

Multiple disease processes are associated with cognitive impairment in Parkinson disease (PD), including Lewy bodies, cerebrovascular disease, and Alzheimer disease. It remains unknown whether tau pathology relates to cognition in patients with PD without dementia.

Objective

To compare tau aggregation in patients with PD who are cognitively normal (PD-CN), patients with PD with mild cognitive impairment (PD-MCI), and healthy control participants, and evaluate the relationships between β-amyloid (Aβ), tau, and cognition in patients with PD who did not have dementia.

Design, Setting, and Participants

This cross-sectional study recruited 30 patients with Parkinson disease (15 with PD-CN and 15 with PD-MCI) from a tertiary care medical center and research institutions from July 2015 through October 2016. One patient with PD-MCI did not receive a magnetic resonance imaging scan and thus was excluded from all analyses; 29 patients with PD were included in the present study. Participants underwent tau positron emission tomographic (PET) scanning with fluorine 18-labeled AV-1451, Aβ PET scanning with carbon 11-labeled Pittsburgh compound B, magnetic resonance imaging, cognitive testing, and neurologic evaluation. Imaging measures were compared with 49 healthy control participants.

Main Outcomes and Measures

Outcomes were tau PET measurements of groups of patients with PD-CN and PD-MCI. We hypothesized that tau aggregation across groups would be related to age and Aβ status.

Results

Of the 78 participants, 47 (60%) were female, and the mean (SD) age was 71.1 (6.6) years. Six patients with PD (21%) were Aβ-positive, of whom 1 was mildly cognitively impaired; 23 were Aβ-negative (79%). (Of the 49 healthy controls, 25 were Aβ-negative and 24 Aβ-positive.) Voxelwise contrasts of whole-brain tau PET uptake between patients with PD-CN and patients with PD-MCI, and additionally between all patients with PD and Aβ-negative controls, did not reveal significant differences. Tau PET binding did not differ between patients with PD-MCI and PD-CN in brain regions reflecting Alzheimer disease Braak stages 1/2, 3/4, or 5/6, and did not differ from Aβ-negative healthy older adults. Mean (SD) tau PET binding was significantly elevated in Aβ-positive patients with PD relative to Aβ-negative patients with PD within brain regions reflecting Alzheimer disease Braak stage 3/4 (1.22 [0.07] vs 1.14 [0.07]; P = .03) and Braak stage 5/6 (1.20 [0.07] vs 1.11 [0.08]; P = .02).

Conclusions and Relevance

These findings suggest that patterns of cortical Aβ and tau do not differ in people with PD-CN, people with PD-MCI, and healthy older adults. Age, Aβ, and tau do not differentiate patients with PD-CN and PD-MCI. Tau deposition is related to Aβ status and age in both people with PD and healthy older adults. Cognitive deficits in people with PD without dementia do not appear to reflect measureable Alzheimer disease.

The Metabolic Activity of Caudate and Prefrontal Cortex Negatively Correlates with the Severity of Idiopathic Parkinson's Disease

Positron emission tomography (PET) scan with tracer [¹⁸F]-fluorodeoxy-glucose (¹⁸F-FDG) is widely used to measure the glucose metabolism in neurodegenerative disease such as Idiopathic Parkinson’s disease (IPD). Previous studies using ¹⁸F-FDG PET mainly focused on the motor or non-motor symptoms but not the severity of IPD. In this study, we aimed to determine the metabolic patterns of ¹⁸F-FDG in different stages of IPD defined by Hoehn and Yahr rating scale (H-Y rating scale) and to identify regions in the brain that play critical roles in disease progression. Fifty IPD patients were included in this study. They were 29 men and 21 women (mean±SD, age 57.7±11.1 years, disease duration 4.0±3.8 years, H-Y 2.2±1.1). Twenty healthy individuals were included as normal controls. Following ¹⁸F-FDG PET scan, image analysis was performed using Statistical Parametric Mapping (SPM) and Resting-State fMRI Data Analysis Toolkit (REST). The metabolic feature of IPD and regions-of-interests (ROIs) were determined. Correlation analysis between ROIs and H-Y stage was performed. SPM analysis demonstrated a significant hypometabolic activity in bilateral putamen, caudate and anterior cingulate as well as left parietal lobe, prefrontal cortex in IPD patients. In contrast, hypermetabolism was observed in the cerebellum and vermis. There was a negative correlation (p=0.007, r=-0.412) between H-Y stage and caudate metabolic activity. Moreover, the prefrontal area also showed a negative correlation with H-Y (P=0.033, r=-0.334). Thus, the uptake of FDG in caudate and prefrontal cortex can potentially be used as a surrogate marker to evaluate the severity of IPD.

Resting functional connectivity and mild cognitive impairment in Parkinson’s disease. An electroencephalogram study

Objective: Parkinson’s disease (PD) is characterized by cognitive deficits. There is not clarity about electroencephalogram (EEG) connectivity related to the cognitive profile of patients. Our objective was to evaluate connectivity over resting EEG in nondemented PD. Methods: PD subjects with and without mild cognitive impairment (MCI) were assessed using coherence from resting EEG for local, intra and interhemispheric connectivity. Results: PD subjects without MCI (PD-nMCI) had lower intra and interhemispheric coherence in alpha2 compared with controls. PD with MCI (PD-MCI) showed higher intra and posterior interhemispheric coherence in alpha2 and beta1, respectively, in comparison to PD-nMCI. PD-MCI presented lower frontal coherence in beta frequencies compared with PD-nMCI. Conclusion: EEG coherence measures indicate distinct cortical activity in PD with and without MCI.

Metabolic patterns across core features in dementia with lewy bodies

OBJECTIVE

To identify brain regions whose metabolic impairment contributes to dementia with Lewy bodies (DLB) clinical core features expression and to assess the influence of severity of global cognitive impairment on the DLB hypometabolic pattern.

METHODS

Brain fluorodeoxyglucose positron emission tomography and information on core features were available in 171 patients belonging to the imaging repository of the European DLB Consortium. Principal component analysis was applied to identify brain regions relevant to the local data variance. A linear regression model was applied to generate core-feature-specific patterns controlling for the main confounding variables (Mini-Mental State Examination [MMSE], age, education, gender, and center). Regression analysis to the locally normalized intensities was performed to generate an MMSE-sensitive map.

RESULTS

Parkinsonism negatively covaried with bilateral parietal, precuneus, and anterior cingulate metabolism; visual hallucinations (VH) with bilateral dorsolateral-frontal cortex, posterior cingulate, and parietal metabolism; and rapid eye movement sleep behavior disorder (RBD) with bilateral parieto-occipital cortex, precuneus, and ventrolateral-frontal metabolism. VH and RBD shared a positive covariance with metabolism in the medial temporal lobe, cerebellum, brainstem, basal ganglia, thalami, and orbitofrontal and sensorimotor cortex. Cognitive fluctuations negatively covaried with occipital metabolism and positively with parietal lobe metabolism. MMSE positively covaried with metabolism in the left superior frontal gyrus, bilateral-parietal cortex, and left precuneus, and negatively with metabolism in the insula, medial frontal gyrus, hippocampus in the left hemisphere, and right cerebellum.

INTERPRETATION

Regions of more preserved metabolism are relatively consistent across the variegate DLB spectrum. By contrast, core features were associated with more prominent hypometabolism in specific regions, thus suggesting a close clinical-imaging correlation, reflecting the interplay between topography of neurodegeneration and clinical presentation in DLB patients. Ann Neurol 2019;85:715-725.

Levodopa-induced dyskinesia is closely linked to progression of frontal dysfunction in PD

OBJECTIVE

To assess the relationship between the development of levodopa-induced dyskinesia (LID) and longitudinal changes in cognition.

METHODS

In this retrospective cohort study, we recruited 119 patients with Parkinson disease (PD) who underwent baseline and follow-up neuropsychological evaluations and were treated with levodopa for >5 years. On the basis of LID development, the patients were classified as patients with LID (PD-LID+, n = 38) or without LID (PD-LID-, n = 81) within 5 years of levodopa administration. After adjusting for age, sex, years of education, body mass index, motor severity at baseline, and levodopa increment per year, we compared the rates of cognitive decline using linear mixed model and dementia conversion using survival analysis between the groups.

RESULTS

Neuropsychological performances and the percentage of patients with mild cognitive impairment (MCI) at baseline did not differ between the groups. The PD-LID+ group showed faster declines in frontal executive function (p = 0.002) and global cognitive function. The conversion rate to dementia was significantly higher in the PD-LID+ group than in the PD-LID- group (adjusted hazard ratio [HR] 3.94, 95% confidence interval [CI] 1.76-8.82). Patients with MCI in the PD-LID+ group had a higher risk of PD dementia conversion than those with normal cognition (adjusted HR 6.08, 95% CI 1.25-29.56) or MCI (adjusted HR 4.05, 95% CI 1.14-14.43) in the PD-LID- group.

CONCLUSIONS

These results demonstrated that LID was closely associated with the progression of cognitive decline, especially frontal executive dysfunction, and the development of PD dementia.

Hybrid PET-MRI Applications in Movement Disorders

Even before the success of combined positron emission tomography and computed tomography (PET/CT), the neuroimaging community was conceiving the idea to integrate the positron emission tomography (PET), with very high molecular quantitative data but low spatial resolution, and magnetic resonance imaging (MRI), with high spatial resolution. Several technical limitations have delayed the use of a hybrid scanner in neuroimaging studies, including the full integration of the PET detector ring within the MRI system, the optimization of data acquisition, and the implementation of reliable methods for PET attenuation, motion correction, and joint image reconstruction. To be valid and useful in clinical and research settings, this instrument should be able to simultaneously acquire PET and MRI, and generate quantitative parametric PET images comparable to PET-CT. While post hoc co-registration of combined PET and MRI data acquired separately became the most reliable technique for the generation of "fused" PET-MRI images, only hybrid PET-MRI approach allows merging these measurements naturally and correlating them in a temporal manner. Furthermore, hybrid PET-MRI represents the most accurate tool to investigate in vivo the interplay between molecular and functional aspects of brain pathophysiology. Hybrid PET-MRI technology is still in the early stages in the movement disorders field, due to the limited availability of scanners with integrated optimized methodological models. This technology is ideally suited to investigate interactions between resting-state functional/arterial spin labeling MRI and [¹⁸F]FDG PET glucose metabolism in the evaluation of the brain "hubs" particularly vulnerable to neurodegeneration, areas with a high degree of connectivity and associated with an efficient synaptic neurotransmission. In Parkinson's disease, hybrid PET-MRI is also the ideal instrument to deeper explore the relationship between resting-state functional MRI and dopamine release at [¹¹C]raclopride PET challenge, in the identification of early drug-naïve Parkinson's disease patients at higher risk of motor complications and in the evaluation of the efficacy of novel neuroprotective treatment able to restore at the same time the altered resting state and the release of dopamine. In this chapter, we discuss the key methodological aspects of hybrid PET-MRI; the evidence in movement disorders of the key resting-state functional and perfusion MRI; [¹⁸F]FDG PET and [¹¹C]raclopride PET challenge studies; the potential advantages of using hybrid PET-MRI to investigate the pathophysiology of movement disorders and neurodegenerative diseases. Future directions of hybrid PET-MRI will be discussed alongside with up-to-date technological innovations on hybrid systems.

Principal Components Analysis of Brain Metabolism Predicts Development of Alzheimer Dementia

The value of ¹⁸F-FDG PET for predicting conversion from mild cognitive impairment (MCI) to Alzheimer dementia (AD) is currently under debate. We used a principal components analysis (PCA) to identify a metabolic AD conversion-related pattern (ADCRP) and investigated the prognostic value of the resulting pattern expression score (PES). Methods: ¹⁸F-FDG PET scans of 544 MCI patients were obtained from the Alzheimer Disease Neuroimaging Initiative database and analyzed. We implemented voxel-based PCA and standard Statistical Parametric Mapping analysis (as a reference) to disclose cerebral metabolic patterns associated with conversion from MCI to AD. By Cox proportional hazards regression, we examined the prognostic value of candidate predictors. Also, we constructed prognostic models with clinical, imaging, and clinical and imaging variables in combination. Results: PCA revealed an ADCRP that involved regions with relative decreases in metabolism (temporoparietal, frontal, posterior cingulate, and precuneus cortices) and relative increases in metabolism (sensorimotor and occipital cortices, cerebellum, and left putamen). Among the predictor variables age, sex, Functional Activities Questionnaire, Mini-Mental State Examination, apolipoprotein E, PES, and normalized ¹⁸F-FDG uptake (regions with significant hypo- and hypermetabolism in patients with conversion vs. those without conversion), PES was the best independent predictor of conversion (hazard ratio, 1.77, per z score increase; 95% CI, 1.24-2.52; P < 0.001). Moreover, adding PES to the model including the clinical variables significantly increased its prognostic value. Conclusion: The ADCRP expression score was a valid predictor of conversion. A combination of clinical variables and PES yielded a higher accuracy than each single tool in predicting conversion from MCI to AD, underlining the incremental utility of ¹⁸F-FDG PET.

PET Imaging in Movement Disorders

Positron emission tomography (PET) has revealed key insights into the pathophysiology of movement disorders. This paper will focus on how PET investigations of pathophysiology are particularly relevant to Parkinson disease, a neurodegenerative condition usually starting later in life marked by a varying combination of motor and nonmotor deficits. Various molecular imaging modalities help to determine what changes in brain herald the onset of pathology; can these changes be used to identify presymptomatic individuals who may be appropriate for to-be-developed treatments that may forestall onset of symptoms or slow disease progression; can PET act as a biomarker of disease progression; can molecular imaging help enrich homogenous cohorts for clinical studies; and what other pathophysiologic mechanisms relate to nonmotor manifestations. PET methods include measurements of regional cerebral glucose metabolism and blood flow, selected receptors, specific neurotransmitter systems, postsynaptic signal transducers, and abnormal protein deposition. We will review each of these methodologies and how they are relevant to important clinical issues pertaining to Parkinson disease.

Clinical utility of FDG PET in Parkinson's disease and atypical parkinsonism associated with dementia

Purpose

There are no comprehensive guidelines for the use of FDG PET in the following three clinical scenarios: (1) diagnostic work-up of patients with idiopathic Parkinson’s disease (PD) at risk of future cognitive decline, (2) discriminating idiopathic PD from progressive supranuclear palsy, and (3) identifying the underlying neuropathology in corticobasal syndrome.

Methods

We therefore performed three literature searches and evaluated the selected studies for quality of design, risk of bias, inconsistency, imprecision, indirectness and effect size. Critical outcomes were the sensitivity, specificity, accuracy, positive/negative predictive value, area under the receiving operating characteristic curve, and positive/negative likelihood ratio of FDG PET in detecting the target condition. Using the Delphi method, a panel of seven experts voted for or against the use of FDG PET based on published evidence and expert opinion.

Results

Of 91 studies selected from the three literature searches, only four included an adequate quantitative assessment of the performance of FDG PET. The majority of studies lacked robust methodology due to lack of critical outcomes, inadequate gold standard and no head-to-head comparison with an appropriate reference standard. The panel recommended the use of FDG PET for all three clinical scenarios based on nonquantitative evidence of clinical utility.

Conclusion

Despite widespread use of FDG PET in clinical practice and extensive research, there is still very limited good quality evidence for the use of FDG PET. However, in the opinion of the majority of the panellists, FDG PET is a clinically useful imaging biomarker for idiopathic PD and atypical parkinsonism associated with dementia.

Structural and Functional Brain Patterns of Non-Motor Syndromes in Parkinson's Disease

Parkinson’s disease (PD) is a common, progressive and multisystem neurodegenerative disorder characterized by motor and non-motor symptoms. Advanced magnetic resonance imaging, positron emission tomography, and functional magnetic resonance imaging can render the view toward understanding the neural basis of these non-motor syndromes, as they help to understand the underlying pathophysiological abnormalities. This review provides an up-to-date description of structural and functional brain alterations in patients with PD with cognitive deficits, visual hallucinations, fatigue, impulsive behavior disorders, sleep disorders, and pain.

LRRK2 mediated Rab8a phosphorylation promotes lipid storage

Background

Several mutations in leucine rich repeat kinase 2 (LRRK2) gene have been associated with pathogenesis of Parkinson’s disease (PD), a neurodegenerative disorder marked by resting tremors, and rigidity, leading to Postural instability. It has been revealed that mutations that lead to an increase of kinase activity of LRRK2 protein are significantly associated with PD pathogenesis. Recent studies have shown that some Rab GTPases, especially Rab8, serve as substrates of LRRK2 and undergo phosphorylation in its switch II domain upon interaction. Current study was performed in order to find out the effects of the phosphorylation of Rab8 and its mutants on lipid metabolism and lipid droplets growth.

Methods

The phosphorylation status of Rab8a was checked by phos-tag gel. Point mutant construct were generated to investigate the function of Rab8a. 3T3L1 cells were transfected with indicated plasmids and the lipid droplets were stained with Bodipy. Fluorescent microscopy experiments were performed to examine the sizes of lipid droplets. The interactions between Rab8a and Optineurin were determined by immunoprecipitation and western blot.

Results

Our assays demonstrated that Rab8a was phosphorylated by mutated LRRK2 that exhibits high kinase activity. Phosphorylation of Rab8a on amino acid residue T72 promoted the formation of large lipid droplets. T72D mutant of Rab8a had higher activity to promote the formation of large lipid droplets compared with wild type Rab8a, with increase in average diameter of lipid droplets from 2.10 μm to 2.46 μm. Moreover, phosphorylation of Rab8a weakened the interaction with its effector Optineurin.

Conclusions

Y1699C mutated LRRK2 was able to phosphorylate Rab8a and phosphorylation of Rab8a on site 72 plays important role in the fusion and enlargement of lipid droplets. Taken together, our study suggests an indirect relationship between enhanced lipid storage capacity and PD pathogenesis.