Correlations between dopaminergic dysfunction and abnormal metabolic network activity in REM sleep behavior disorder

Clinical features, disease progression, and nuclear imaging in ATXN2-related parkinsonism in a longitudinal cohort

BACKGROUND

Spinocerebellar ataxia 2 (SCA2) with a low range of CAG repeat expansion of ATXN2 gene can present with predominant or isolated parkinsonism that closely resembles Parkinson's disease (PD). This study is aimed at comparing clinical features, disease progression, and nuclear imaging between ATXN2-related parkinsonism (ATXN2-P) and PD.

METHODS

Three hundred and seventy-seven clinically diagnosed PD with family history were screened by multiplex ligation-dependent probe amplification, whole-exome sequencing or target sequencing, and dynamic mutation testing of 10 SCA subtypes. The baseline and longitudinal clinical features as well as the dual-tracer positron emission tomography (PET) imaging were compared between ATXN2-P and genetically undefined familial PD (GU-fPD).

RESULTS

Fifteen ATXN2-P patients from 7 families and 50 randomly selected GU-fPD patients were evaluated. Significantly less resting tremor and more symmetric signs were observed in ATXN2-P than GU-fPD. No significant difference was found in motor progression and duration from onset to occurrence of fluctuation, dyskinesia, and recurrent falls between the two groups. Cognitive impairment and rapid-eye-movement sleep behavior disorder were more common in ATXN2-P. During follow-up, olfaction was relatively spared, and no obvious progression of cognition dysfunction evaluated by Mini-Mental State Examination scores was found in ATXN2-P. PET results of ATXN2-P demonstrated a symmetric, diffuse, and homogenous dopamine transporter loss of bilateral striatum and a glucose metabolism pattern inconsistent with that in PD.

CONCLUSIONS

Symmetric motor signs and unique nuclear imaging might be the clues to distinguish ATXN2-P from GU-fPD.

Investigating the aspect of asymmetry in brain-first versus body-first Parkinson's disease

Parkinson's disease (PD) is characterized by a progressive loss of dopaminergic neurons in the substantia nigra. Recent literature has proposed two subgroups of PD. The "body-first subtype" is associated with a prodrome of isolated REM-sleep Behavior Disorder (iRBD) and a relatively symmetric brain degeneration. The "brain-first subtype" is suggested to have a more asymmetric degeneration and a prodromal stage without RBD. This study aims to investigate the proposed difference in symmetry of the degeneration pattern in the presumed body and brain-first PD subtypes. We analyzed 123I-FP-CIT (DAT SPECT) and 18F-FDG PET brain imaging in three groups of patients (iRBD, n = 20, de novo PD with prodromal RBD, n = 22, and de novo PD without RBD, n = 16) and evaluated dopaminergic and glucose metabolic symmetry. The RBD status of all patients was confirmed with video-polysomnography. The PD groups did not differ from each other with regard to the relative or absolute asymmetry of DAT uptake in the putamen (p = 1.0 and p = 0.4, respectively). The patient groups also did not differ from each other with regard to the symmetry of expression of the PD-related metabolic pattern (PDRP) in each hemisphere. The PD groups had no difference in symmetry considering mean FDG uptake in left and right regions of interest and generally had the same degree of symmetry as controls, while the iRBD patients had nine regions with abnormal left-right differences (p < 0.001). Our findings do not support the asymmetry aspect of the "body-first" versus "brain-first" hypothesis.

International consensus on clinical use of presynaptic dopaminergic positron emission tomography imaging in parkinsonism

PURPOSE

Presynaptic dopaminergic positron emission tomography (PET) imaging serves as an essential tool in diagnosing and differentiating patients with suspected parkinsonism, including idiopathic Parkinson's disease (PD) and other neurodegenerative and non-neurodegenerative diseases. The PET tracers most commonly used at the present time mainly target dopamine transporters (DAT), aromatic amino acid decarboxylase (AADC), and vesicular monoamine type 2 (VMAT2). However, established standards for the imaging procedure and interpretation of presynaptic dopaminergic PET imaging are still lacking. The goal of this international consensus is to help nuclear medicine practitioners procedurally perform presynaptic dopaminergic PET imaging.

METHOD

A multidisciplinary task group formed by experts from various countries discussed and approved the consensus for presynaptic dopaminergic PET imaging in parkinsonism, focusing on standardized recommendations, procedures, interpretation, and reporting.

CONCLUSION

This international consensus and practice guideline will help to promote the standardized use of presynaptic dopaminergic PET imaging in parkinsonism. It will become an international standard for this purpose in clinical practice.

Dopaminergic damage pattern predicts phenoconversion time in isolated rapid eye movement sleep behavior disorder

PURPOSE

The exact phenoconversion time from isolated rapid eye movement (REM) sleep behavior disorder (iRBD) to synucleinopathies remains unpredictable. This study investigated whole-brain dopaminergic damage pattern (DDP) with disease progression and predicted phenoconversion time in individual patients.

METHODS

Age-matched 33 iRBD patients and 20 healthy controls with 11C-CFT-PET scans were enrolled. The patients were followed up 2-10 (6.7 ± 2.0) years. The phenoconversion year was defined as the base year, and every 2 years before conversion was defined as a stage. Support vector machine with leave-one-out cross-validation strategy was used to perform prediction.

RESULTS

Dopaminergic degeneration of iRBD was found to occur about 6 years before conversion and then abnormal brain regions gradually expanded. Using DDP, area under curve (AUC) was 0.879 (90% sensitivity and 88.3% specificity) for predicting conversion in 0-2 years, 0.807 (72.7% sensitivity and 83.3% specificity) in 2-4 years, 0.940 (100% sensitivity and 84.6% specificity) in 4-6 years, and 0.879 (100% sensitivity and 80.7% specificity) over 6 years. In individual patients, predicted stages correlated with whole-brain dopaminergic levels (r =  - 0.740, p < 0.001).

CONCLUSION

Our findings suggest that DDP could accurately predict phenoconversion time of individual iRBD patients, which may help to screen patients for early intervention.

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.

Neuropathology of incidental Lewy body & prodromal Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is a progressive neurodegenerative disorder associated with a loss of dopaminergic (DA) neurons. Despite symptomatic therapies, there is currently no disease-modifying treatment to halt neuronal loss in PD. A major hurdle for developing and testing such curative therapies results from the fact that most DA neurons are already lost at the time of the clinical diagnosis, rendering them inaccessible to therapy. Understanding the early pathological changes that precede Lewy body pathology (LBP) and cell loss in PD will likely support the identification of novel diagnostic and therapeutic strategies and help to differentiate LBP-dependent and -independent alterations. Several previous studies identified such specific molecular and cellular changes that occur prior to the appearance of Lewy bodies (LBs) in DA neurons, but a concise map of such early disease events is currently missing.

METHODS

Here, we conducted a literature review to identify and discuss the results of previous studies that investigated cases with incidental Lewy body disease (iLBD), a presumed pathological precursor of PD.

RESULTS

Collectively, our review demonstrates numerous cellular and molecular neuropathological changes occurring prior to the appearance of LBs in DA neurons.

CONCLUSIONS

Our review provides the reader with a summary of early pathological events in PD that may support the identification of novel therapeutic and diagnostic targets and aid to the development of disease-modifying strategies in PD.

Optimized Cingulate Island Sign in Discriminating Dementia With Lewy Bodies From Alzheimer Disease

PURPOSE

This study aimed to optimize the analysis of cingulate island sign (CIS) to improve its diagnostic accuracy in discriminating dementia with Lewy bodies (DLB) from Alzheimer disease (AD).

PATIENTS AND METHODS

Patients with DLB (n = 80), AD (n = 75), and normal controls (n = 22) with 18 F-FDG PET imaging were enrolled in this study. Sixty-two DLB patients also underwent dopaminergic PET scans. The optimized/conventional CIS ratios and metabolism in associated brain regions were evaluated by diagnostic accuracy among groups and correlation with cognitive/dopaminergic dysfunction.

RESULTS

In discriminating DLB from AD, the optimized CIS ratio calculated by dorsal posterior cingulate cortex (PCC)/lateral occipital lobe metabolism achieved the highest specificity, sensitivity, and accuracy at 0.907, 0.750, and 0.825, respectively. The metabolism of dorsal-PCC positively correlated with cognitive impairment in DLB patients cross-sectionally and longitudinally ( P < 0.001, r = 0.601; P = 0.044, r = 0.645), and also correlated with dopaminergic impairment in the caudate ( P = 0.048, r = 0.315).

CONCLUSIONS

Optimized CIS ratios of incorporated metabolic activity of dorsal-PCC and occipital subregions are clinically useful for differentiating DLB from AD, in which dorsal-PCC metabolism may provide an objective biomarker to reflect the severity of cognitive impairment in DLB.

Louis EK, Savica R, Fields JA, Benarroch EE, Lowe V, Petersen RC, Boeve BF, Kantarci K. Brain glucose metabolism and nigrostriatal degeneration in isolated rapid eye movement sleep behaviour disorder

Alterations of cerebral glucose metabolism can be detected in patients with isolated rapid eye movement sleep behaviour disorder, a prodromal feature of neurodegenerative diseases with α-synuclein pathology. However, metabolic characteristics that determine clinical progression in isolated rapid eye movement sleep behaviour disorder and their association with other biomarkers need to be elucidated. We investigated the pattern of cerebral glucose metabolism on 18F-fluorodeoxyglucose PET in patients with isolated rapid eye movement sleep behaviour disorder, differentiating between those who clinically progressed and those who remained stable over time. Second, we studied the association between 18F-fluorodeoxyglucose PET and lower dopamine transporter availability in the putamen, another hallmark of synucleinopathies. Patients with isolated rapid eye movement sleep behaviour disorder from the Mayo Clinic Alzheimer's Disease Research Center and Center for Sleep Medicine (n = 22) and age-and sex-matched clinically unimpaired controls (clinically unimpaired; n = 44) from the Mayo Clinic Study of Aging were included. All participants underwent 18F-fluorodeoxyglucose PET and dopamine transporter imaging with iodine 123-radiolabeled 2β-carbomethoxy-3β-(4-iodophenyl)-N-(3-fluoropropyl) nortropane on single-photon emission computerized tomography. A subset of patients with isolated rapid eye movement sleep behaviour disorder with follow-up evaluations (n = 17) was classified as isolated rapid eye movement sleep behaviour disorder progressors (n = 7) if they developed mild cognitive impairment or Parkinson's disease; or isolated rapid eye movement sleep behaviour disorder stables (n = 10) if they remained with a diagnosis of isolated rapid eye movement sleep behaviour disorder with no cognitive impairment. Glucose metabolic abnormalities in isolated rapid eye movement sleep behaviour disorder were determined by comparing atlas-based regional 18F-fluorodeoxyglucose PET uptake between isolated rapid eye movement sleep behaviour disorder and clinically unimpaired. Associations between 18F-fluorodeoxyglucose PET and dopamine transporter availability in the putamen were analyzed with Pearson's correlation within the nigrostriatal pathway structures and with voxel-based analysis in the cortex. Patients with isolated rapid eye movement sleep behaviour disorder had lower glucose metabolism in the substantia nigra, retrosplenial cortex, angular cortex, and thalamus, and higher metabolism in the amygdala and entorhinal cortex compared with clinically unimpaired. Patients with isolated rapid eye movement sleep behaviour disorder who clinically progressed over time were characterized by higher glucose metabolism in the amygdala and entorhinal cortex, and lower glucose metabolism in the cerebellum compared with clinically unimpaired. Lower dopamine transporter availability in the putamen was associated with higher glucose metabolism in the pallidum within the nigrostriatal pathway; and with higher 18F-fluorodeoxyglucose uptake in the amygdala, insula, and temporal pole on a voxel-based analysis, although these associations did not survive after correcting for multiple comparisons. Our findings suggest that cerebral glucose metabolism in isolated rapid eye movement sleep behaviour disorder is characterized by hypometabolism in regions frequently affected during the prodromal stage of synucleinopathies, potentially reflecting synaptic dysfunction. Hypermetabolism is also seen in isolated rapid eye movement sleep behaviour disorder, suggesting that synaptic metabolic disruptions may be leading to a lack of inhibition, compensatory mechanisms, or microglial activation, especially in regions associated with nigrostriatal degeneration.

Dopaminergic Dysfunction and Glucose Metabolism Characteristics in Parkin-Induced Early-Onset Parkinson's Disease Compared to Genetically Undetermined Early-Onset Parkinson's Disease

While early-onset Parkinson's disease (EOPD) caused by mutations in the parkin gene (PRKN) tends to have a relatively benign course compared to genetically undetermined (GU)-EOPD, the exact underlying mechanisms remain elusive. We aimed to search for the differences between PRKN-EOPD and GU-EOPD by dopamine transporter (DAT) and glucose metabolism positron-emission-tomography (PET) imaging. Twelve patients with PRKN-EOPD and 16 with GU-EOPD who accepted both 11C-2b-carbomethoxy-3b-(4-trimethylstannylphenyl) tropane (11C-CFT) and 18F-fluorodeoxyglucose PET were enrolled. The 11C-CFT uptake was analyzed on both regional and voxel levels, whereas glucose metabolism was assessed in a voxel-wise fashion. Correlations between DAT and glucose metabolism imaging, DAT imaging and clinical severity, as well as glucose metabolism imaging and clinical severity were explored. Both clinical symptoms and DAT-binding patterns in the posterior putamen were highly symmetrical in patients with PRKN-EOPD, and dopaminergic dysfunction in the ipsilateral putamen was severer in patients with PRKN-EOPD than GU-EOPD. Meanwhile, the DAT binding was associated with the severity of motor dysfunction in  patients with GU-EOPD only. Patients with PRKN-EOPD showed increased glucose metabolism in the contralateral medial frontal gyrus (supplementary motor area (SMA)), contralateral substantia nigra, contralateral thalamus, and contralateral cerebellum. Notably, glucose metabolic activity in the contralateral medial frontal gyrus was inversely associated with regional DAT binding in the bilateral putamen. Patients with PRKN-EOPD showed enhanced metabolic connectivity within the bilateral putamen, ipsilateral paracentral and precentral lobules, and the ipsilateral SMA. Collectively, compared to GU-EOPD, PRKN-EOPD is characterized by symmetrical, more severe dopaminergic dysfunction and relative increased glucose metabolism. Meanwhile, SMA with elevated glucose metabolism and enhanced connectivity may act as compensatory mechanisms in PRKN-EOPD.

Supplementary Information

The online version contains supplementary material available at 10.1007/s43657-022-00077-8.

Research progress on neuromolecular imaging of REM sleep behavior disorder

Idiopathic rapid eye movement sleep behavior disorder (iRBD) is an important non-motor complication of Parkinson's disease. At the same time, iRBD is considered to be the prodromal stage of α-synucleinopathy. This high risk of conversion suggests that iRBD becomes a nerve It is a window for early research on degenerative diseases and is the best candidate for neuroprotection trials. A wide range of neuroimaging techniques has improved our understanding of iRBD as a prodromal stage of the disease. In addition, neuroimaging of abnormal iRBD is expected to be a potential biomarker for predicting clinical phenotypic transformation. This article reviews the research progress of neuromolecular imaging in patients with iRBD from the perspective of iRBD transforming synucleinopathies.

Consistent Abnormalities in Metabolic Patterns of Lewy Body Dementias

BACKGROUND

Whether dementia with Lewy bodies (DLB) and Parkinson's disease (PD) dementia (PDD) represent the same disease, distinct entities, or conditions within the same spectrum remains controversial.

OBJECTIVE

The objective of this study was to provide new insight into this debate by separately identifying disease-specific metabolic patterns and comparing them with each other and with previously established PD-related pattern (PDRP).

METHODS

Patients with DLB (n = 67), patients with PDD (n = 50), and healthy control subjects (HCs; n = 15) with brain ¹⁸ F-fluorodeoxyglucose positron emission tomography were enrolled as cohorts A and B for pattern identification and validation, respectively. Patients with PD (n = 30) were included for discrimination. Twenty-one participants had two scans. The principal component analysis was applied for pattern identification (DLB-related pattern [DLBRP], PDD-related pattern [PDDRP]). Similarities and differences among three patterns were assessed by pattern topography, pattern expression, clinical correlations cross-sectionally, and pattern expression changes longitudinally.

RESULTS

DLBRP and PDDRP shared highly similar topographies, with relative hypometabolism mainly in the middle temporal gyrus, middle occipital gyrus, lingual gyrus, precuneus, cuneus, angular gyrus, superior and inferior parietal gyrus, middle and inferior frontal gyrus, cingulate, and caudate, and relative hypermetabolism in the cerebellum, putamen, thalamus, precentral/postcentral gyrus, and paracentral lobule, which were more extensive than the PDRP. Patients with DLB and PDD could not be distinguished successfully by any pattern, but patients with PD were easily recognized, especially by DLBRP and PDDRP. The pattern expression of DLBRP and PDDRP showed similar efficacy in cross-sectional disease severity assessment and longitudinal progression monitoring.

CONCLUSIONS

The consistent abnormalities in metabolic patterns of DLB and PDD might underline the potential continuum across the clinical spectrum from PD to DLB. © 2022 International Parkinson and Movement Disorder Society.

Decoding the dopamine transporter imaging for the differential diagnosis of parkinsonism using deep learning

Purpose

This work attempts to decode the discriminative information in dopamine transporter (DAT) imaging using deep learning for the differential diagnosis of parkinsonism.

Methods

This study involved 1017 subjects who underwent DAT PET imaging ([¹¹C]CFT) including 43 healthy subjects and 974 parkinsonian patients with idiopathic Parkinson’s disease (IPD), multiple system atrophy (MSA) or progressive supranuclear palsy (PSP). We developed a 3D deep convolutional neural network to learn distinguishable DAT features for the differential diagnosis of parkinsonism. A full-gradient saliency map approach was employed to investigate the functional basis related to the decision mechanism of the network. Furthermore, deep-learning-guided radiomics features and quantitative analysis were compared with their conventional counterparts to further interpret the performance of deep learning.

Results

The proposed network achieved area under the curve of 0.953 (sensitivity 87.7%, specificity 93.2%), 0.948 (sensitivity 93.7%, specificity 97.5%), and 0.900 (sensitivity 81.5%, specificity 93.7%) in the cross-validation, together with sensitivity of 90.7%, 84.1%, 78.6% and specificity of 88.4%, 97.5% 93.3% in the blind test for the differential diagnosis of IPD, MSA and PSP, respectively. The saliency map demonstrated the most contributed areas determining the diagnosis located at parkinsonism-related regions, e.g., putamen, caudate and midbrain. The deep-learning-guided binding ratios showed significant differences among IPD, MSA and PSP groups (P < 0.001), while the conventional putamen and caudate binding ratios had no significant difference between IPD and MSA (P = 0.24 and P = 0.30). Furthermore, compared to conventional radiomics features, there existed average above 78.1% more deep-learning-guided radiomics features that had significant differences among IPD, MSA and PSP.

Conclusion

This study suggested the developed deep neural network can decode in-depth information from DAT and showed potential to assist the differential diagnosis of parkinsonism. The functional regions supporting the diagnosis decision were generally consistent with known parkinsonian pathology but provided more specific guidance for feature selection and quantitative analysis.

Supplementary Information

The online version contains supplementary material available at 10.1007/s00259-022-05804-x.

Predictors of RBD progression and conversion to synucleinopathies

Purpose of review

Rapid eye movement (REM) sleep behaviour disorder (RBD) is considered the expression of the initial neurodegenerative process underlying synucleinopathies and constitutes the most important marker of their prodromal phase. This article reviews recent research from longitudinal research studies in isolated RBD (iRBD) aiming to describe the most promising progression biomarkers of iRBD and to delineate the current knowledge on the level of prediction of future outcome in iRBD patients at diagnosis.

Recent findings

Longitudinal studies revealed the potential value of a variety of biomarkers, including clinical markers of motor, autonomic, cognitive, and olfactory symptoms, neurophysiological markers such as REM sleep without atonia and electroencephalography, genetic and epigenetic markers, cerebrospinal fluid and serum markers, and neuroimaging markers to track the progression and predict phenoconversion. To-date the most promising neuroimaging biomarker in iRBD to aid the prediction of phenoconversion is striatal presynaptic striatal dopaminergic dysfunction.

Summary

There is a variety of potential biomarkers for monitoring disease progression and predicting iRBD conversion into synucleinopathies. A combined multimodal biomarker model could offer a more sensitive and specific tool. Further longitudinal studies are warranted to iRBD as a high-risk population for early neuroprotective interventions and disease-modifying therapies.

Computer-Aided Classification Framework of Parkinsonian Disorders Using 11C-CFT PET Imaging

Purpose

To investigate the usefulness of a novel computer-aided classification framework for the differential diagnosis of parkinsonian disorders (PDs) based on ¹¹C-methyl-N-2β-carbomethoxy-3β-(4-fluorophenyl)-tropanel (¹¹C-CFT) positron emission tomography (PET) imaging.

Methods

Patients with different forms of PDs—including Parkinson's disease (PD), multiple system atrophy (MSA) and progressive supranuclear palsy (PSP)—underwent dopamine transporter (DAT) imaging with ¹¹C-CFT PET. A novel multistep computer-aided classification framework—consisting of magnetic resonance imaging (MRI)-assisted PET segmentation, feature extraction and prediction, and automatic subject classification—was developed. A random forest method was used to assess the diagnostic relevance of different regions to the classification process. Finally, the performance of the computer-aided classification system was tested using various training strategies involving patients with early and advanced disease stages.

Results

Accuracy values for identifying PD, MSA, and PSP were 85.0, 82.2, and 89.7%, respectively—with an overall accuracy of 80.4%. The caudate and putamen provided the highest diagnostic relevance to the proposed classification framework, whereas the contribution of midbrain was negligible. With the exception of sensitivity for diagnosing PSP, the strategy comprising both early and advanced disease stages performed better in terms of sensitivity, specificity, positive predictive value, and negative predictive value within each PDs subtype.

Conclusions

The proposed computer-aided classification framework based on ¹¹C-CFT PET imaging holds promise for improving the differential diagnosis of PDs.

Predict initial subthalamic nucleus stimulation outcome in Parkinson's disease with brain morphology

AIM

Subthalamic nucleus deep brain stimulation (STN-DBS) has been reported to be effective in treating motor symptoms in Parkinson's disease (PD), which may be attributed to changes in the brain network. However, the association between brain morphology and initial STN-DBS efficacy, as well as the performance of prediction using neuroimaging, has not been well illustrated. Therefore, we aim to investigate these issues.

METHODS

In the present study, 94 PD patients underwent bilateral STN-DBS, and the initial stimulation efficacy was evaluated. Brain morphology was examined by magnetic resonance imaging (MRI). The volume of tissue activated in the motor STN was measured with MRI and computed tomography. The prediction of stimulation efficacy was achieved with a support vector machine, using brain morphology and other features, after feature selection and hyperparameter optimization.

RESULTS

A higher stimulation efficacy was correlated with a thicker right precentral cortex. No association with subcortical gray or white matter volumes was observed. These morphological features could estimate the individual stimulation response with an r value of 0.5678, an R² of 0.3224, and an average error of 11.4%. The permutation test suggested these predictions were not based on chance.

CONCLUSION

Our results indicate that changes in morphology are associated with the initial stimulation motor response and could be used to predict individual initial stimulation-related motor responses.

Clinical and imaging evidence of brain-first and body-first Parkinson's disease

Braak's hypothesis has been extremely influential over the last two decades. However, neuropathological and clinical evidence suggest that the model does not conform to all patients with Parkinson's disease (PD). To resolve this controversy, a new model was recently proposed; in brain-first PD, the initial α-synuclein pathology arise inside the central nervous system, likely rostral to the substantia nigra pars compacta, and spread via interconnected structures - eventually affecting the autonomic nervous system; in body-first PD, the initial pathological α-synuclein originates in the enteric nervous system with subsequent caudo-rostral propagation to the autonomic and central nervous system. By using REM-sleep behavior disorder (RBD) as a clinical identifier to distinguish between body-first PD (RBD-positive at motor symptom onset) and brain-first PD (RBD-negative at motor symptom onset), we explored the literature to evaluate clinical and imaging differences between these proposed subtypes. Body-first PD patients display: 1) a larger burden of autonomic symptoms - in particular orthostatic hypotension and constipation, 2) more frequent pathological α-synuclein in peripheral tissues, 3) more brainstem and autonomic nervous system involvement in imaging studies, 4) more symmetric striatal dopaminergic loss and motor symptoms, and 5) slightly more olfactory dysfunction. In contrast, only minor cortical metabolic alterations emerge before motor symptoms in body-first. Brain-first PD is characterized by the opposite clinical and imaging patterns. Patients with pathological LRRK2 genetic variants mostly resemble a brain-first PD profile whereas patients with GBA variants typically conform to a body-first profile. SNCA-variant carriers are equally distributed between both subtypes. Overall, the literature indicates that body-first and brain-first PD might be two distinguishable entities on some clinical and imaging markers.

The Parkinson's Disease Progression Neuroimaging Initiative

The Parkinson's Disease Progressive Neuroimaging Initiative (PDPNI) is a longitudinal observational clinical study. In PDPNI, the clinical and imaging data of patients diagnosed with Parkinsonian syndromes and Idiopathic rapid eye movement sleep behavior disorder (RBD) were longitudinally followed every two years, aiming to identify progression biomarkers of Parkinsonian syndromes through functional imaging modalities including FDG-PET, DAT-PET imaging, ASL MRI, and fMRI, as well as the treatment conditions, clinical symptoms, and clinical assessment results of patients. From February 2012 to March 2019, 224 subjects (including 48 healthy subjects and 176 patients with confirmed PDS) have been enrolled in PDPNI. The detailed clinical information and clinical assessment scores of all subjects were collected by neurologists from Huashan Hospital, Fudan University. All subjects enrolled in PDPNI were scanned with 18F-FDG PET, 11C-CFT PET, and MRI scan sequence. All data were collected in strict accordance with standardized data collection protocols.

The impact of probable rapid eye movement sleep behavior disorder on Parkinson's disease: A dual-tracer PET imaging study

OBJECTIVE

With a dual-tracer PET study design, this study aimed to identify the differences between PD patients with and without probable RBD (PD+RBD+/PD+RBD-) and the influence of timing of RBD onset [probable RBD anterior to PD onset (PD+RBDa)/probable RBD posterior to PD onset (PD+RBDp)].

METHODS

Seventy-four PD+RBD+ patients, sixty-three PD+RBD-patients and twenty healthy controls were enrolled. Clinical variates, striatal DAT tracer uptake, voxel-wise glucose metabolism and Parkinson's disease-related pattern (PDRP) expressions were compared among groups.

RESULTS

No significant difference were found on clinical characteristics between PD+RBD+ and PD+RBD-groups. Compared with PD+RBD-group, PD+RBD+ group had more severe dopaminergic dysfunction (p<0.05) except for posterior putamen in the more affected hemisphere (MAH) (p = 0.350). Meanwhile, it showed relative hypermetabolism in anterior putamen in the less affected hemisphere (LAH), bilateral anterior pallidum with wider involvement in the LAH, hippocampus and para-hippocampus in the LAH and bilateral olfactory gyrus, together with relative hypometabolism in limited bilateral posterio-parietal area (p<0.001). Significantly elevated PDRP expression was also seen in PD+RBD+ group (p < 0.01). For the timing of RBD onset, PD+RBDa patients harbored greater progression rate than PD+RBDp patients (p<0.01), greater DAT declining rates of striatal subregions and greater increasing rate of PDRP expressions than both PD+RBDp and PD+RBD-patients (p<0.05).

CONCLUSION

Our study found that PD patients with probable RBD have worse striatal dopaminergic dysfunction and higher PDRP network activity, supporting the assumption that PD with RBD may be a specific phenotype of PD. Additionally, RBD preceding PD onset may indicate a steeper disease decline.

Circuit imaging biomarkers in preclinical and prodromal Parkinson's disease

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.

Neurochemical Features of Rem Sleep Behaviour Disorder

Dopaminergic deficiency, shown by many studies using functional neuroimaging with Single Photon Emission Computerized Tomography (SPECT) and Positron Emission Tomography (PET), is the most consistent neurochemical feature of rapid eye movement (REM) sleep behaviour disorder (RBD) and, together with transcranial ultrasonography, and determination of alpha-synuclein in certain tissues, should be considered as a reliable marker for the phenoconversion of idiopathic RBD (iRBD) to a synucleopathy (Parkinson’s disease –PD- or Lewy body dementia -LBD). The possible role in the pathogenesis of RBD of other neurotransmitters such as noradrenaline, acetylcholine, and excitatory and inhibitory neurotransmitters; hormones such as melatonin, and proinflammatory factors have also been suggested by recent reports. In general, brain perfusion and brain glucose metabolism studies have shown patterns resembling partially those of PD and LBD. Finally, the results of structural and functional MRI suggest the presence of structural changes in deep gray matter nuclei, cortical gray matter atrophy, and alterations in the functional connectivity within the basal ganglia, the cortico-striatal, and the cortico-cortical networks, but they should be considered as preliminary.

Biomarkers of conversion to α-synucleinopathy in isolated rapid-eye-movement sleep behaviour disorder

Patients with isolated rapid-eye-movement sleep behaviour disorder (RBD) are commonly regarded as being in the early stages of a progressive neurodegenerative disease involving α-synuclein pathology, such as Parkinson's disease, dementia with Lewy bodies, or multiple system atrophy. Abnormal α-synuclein deposition occurs early in the neurodegenerative process across the central and peripheral nervous systems and might precede the appearance of motor symptoms and cognitive decline by several decades. These findings provide the rationale to develop reliable biomarkers that can better predict conversion to clinically manifest α-synucleinopathies. In addition, biomarkers of disease progression will be essential to monitor treatment response once disease-modifying therapies become available, and biomarkers of disease subtype will be essential to enable prediction of which subtype of α-synucleinopathy patients with isolated RBD might develop.

The Correlation Between Parkinson's Disease and Rapid Eye Movement Sleep Behavior Disorder: A Systematic Review

Parkinson's disease (PD) is a neurodegenerative disease caused due to the destruction of dopaminergic neurons and the deposition of α-synuclein proteins, known as Lewy bodies. Generally, the diagnosis of PD is centered around motor symptoms. However, the early recognition of non-motor symptoms such as autonomic dysfunction, sleep disturbances, and cognitive and psychiatric disturbances are gaining increased attention for the early diagnosis of PD. Rapid eye movement (REM) sleep behavior disorder or REM sleep behavior disorder (RBD) is described as parasomnia, which is a condition of loss of normal muscle atonia causing the person to act out vivid dreams and it has been seen to be associated with the misprocessing of intercellular α-synuclein leading to neurodegenerative diseases such as PD. This review's objective is to highlight the significance of RBD as a prodromal premotor marker for the early detection of PD. We used PubMed as our primary database to search for articles on May 2, 2021, and a total of 1849 articles were found in our initial search using keywords and medical subject heading (MeSH) keywords. Thereafter, we removed the duplicates, applied the inclusion/exclusion criteria, and did a quality appraisal to include 10 articles in this study. We concluded that the recognition and diagnosis of RBD are of paramount importance to detect early PD, and further longitudinal studies and clinical trials are of utmost importance to understand their correlation; also, treatment trials are needed to prevent the phenoconversion of RBD into PD.

Quality of life in Parkinson's disease: A systematic review and meta-analysis of comparative studies

BACKGROUND

Studies regarding the impact of Parkinson's disease (PD) on quality of life (QOL) have reported conflicting results, and the underlying QOL domains require further study. In order to understand the association between PD and QOL, we conducted this meta-analysis to systematically compare QOL between PD patients and healthy controls.

METHOD

The PubMed, PsycINFO, EMBASE, and Web of Science databases were systematically searched. Data were analyzed using the random-effects model.

RESULTS

Twenty studies covering 2707 PD patients and 150,661 healthy controls were included in the study. Compared with healthy controls, PD patients had significantly poorer QOL overall and in most domains with moderate to large effects sizes. Different QOL measures varied in their association with quality of life, with the Parkinson's Disease Questionnaire-39 (PDQ-39) having the largest effect size (standard mean difference, SMD = -1.384, 95% CI: -1.607, -1.162, Z = 12.189, P < 0.001), followed by the Europe Quality of Life Questionnaire-visual analogue scale (EQ-VAS) (SMD = -1.081, 95% CI: -1.578, -0.584, Z = -4.265, P < 0.001), Europe Quality of Life Questionnaire-5D (EQ-5D) (SMD = -0.889, 95% CI: -1.181, -0.596, Z = -5.962, P < 0.001), and the Short-form Health Survey (SF) scales (physical dimension: SMD = -0.826, 95% CI: -1.529, -0.123, Z = -2.303, P = 0.021; mental dimension: SMD = -0.376, 95% CI: -0.732, -0.019, Z = -2.064, P = 0.039).

CONCLUSION

PD patients had lower QOL compared with healthy controls in most domains, especially in physical function and mental health. Considering the negative impact of poor QOL on daily life and functional outcomes, effective measures should be developed to improve QOL in this population.

Dopaminergic and Metabolic Correlations With Cognitive Domains in Non-demented Parkinson's Disease

Background

Accruing positron emission tomography (PET) studies have suggested that dopaminergic functioning and metabolic changes are correlated with cognitive dysfunction in Parkinson’s disease (PD). Yet, the relationship between dopaminergic or cerebral metabolism and different cognitive domains in PD is poorly understood. To address this scarcity, we aimed to investigate the interactions among dopaminergic bindings, metabolic network changes, and the cognitive domains in PD patients.

Methods

We recruited 41 PD patients, including PD patients with no cognitive impairment (PD-NC; n = 21) and those with mild cognitive impairment (PD-MCI; n = 20). All patients underwent clinical evaluations and a schedule of neuropsychological tests and underwent both 11C-N-2-carbomethoxy-3-(4-fluorophenyl)-tropane (11C-CFT) and 18F-fluorodeoxyglucose (18F-FDG) PET imaging.

Results

11C-CFT imaging revealed a significant positive correlation between executive function and striatal dopamine transporter (DAT) binding at both the voxel and regional levels. Metabolic imaging revealed that executive function correlated with 18F-FDG uptake, mainly in inferior frontal gyrus, putamen, and insula. Further analysis indicated that striatal DAT binding correlated strictly with metabolic activity in the temporal gyrus, medial frontal gyrus, and cingulate gyrus.

Conclusion

Our findings might promote the understanding of the neurobiological mechanisms underlying cognitive impairment in PD.

Cuneus/precuneus as a central hub for brain functional connectivity of mild cognitive impairment in idiopathic REM sleep behavior patients

PURPOSE

To investigate brain functional correlates of mild cognitive impairment (MCI) in idiopathic REM sleep behavior disorder (iRBD).

METHODS

Thirty-nine consecutive iRBD patients, 17 with (RBD-MCI, 73.6±6.5 years), and 22 without (RBD-NC, 69.6±6.1 years) MCI underwent neuropsychological assessment, ¹⁸F-FDG-PET, and ¹²³I-FP-CIT-SPECT as a marker of nigro-striatal dopaminergic function. Forty-two healthy subjects (69.6±8.5 years) were used as control for ¹⁸F-FDG-PET analysis. Brain metabolism was compared between the three groups by univariate analysis of variance. Post hoc comparison between RBD-MCI and RBD-NC was performed to investigate the presence of an MCI-related volume of interest (MCI-VOI). Brain functional connectivity was explored by interregional correlation analysis (IRCA), using the whole-brain normalized MCI-VOI uptake as the independent variable. Moreover, the MCI-VOI uptake was correlated with ¹²³I-FP-CIT-SPECT specific-to-non displaceable binding ratios (SBR) and neuropsychological variables. Finally, the MCI-VOI white matter structural connectivity was analyzed by using a MRI-derived human atlas.

RESULTS

The MCI-VOI was characterized by a relative hypometabolism involving precuneus and cuneus (height threshold p<0.0001). IRCA (height threshold p<0.0001) revealed a brain functional network involving regions in frontal, temporal, parietal, and occipital lobes, thalamus, caudate, and red nuclei in iRBD patients. In controls, the network was smaller and involved temporal, occipital, cingulate cortex, and cerebellum. Moreover, MCI-VOI metabolism was correlated with verbal memory (p=0.01), executive functions (p=0.0001), and nigro-putaminal SBR (p=0.005). Finally, MCI-VOI was involved in a white matter network including cingulate fasciculus and corpus callosum.

CONCLUSION

Our data suggest that cuneus/precuneus is a hub of a large functional network subserving cognitive function in iRBD.

Metabolic network as an objective biomarker in monitoring deep brain stimulation for Parkinson's disease: a longitudinal study

Background

With the advance of subthalamic nucleus (STN) deep brain stimulation (DBS) in the treatment of Parkinson’s disease (PD), it is desired to identify objective criteria for the monitoring of the therapy outcome. This paper explores the feasibility of metabolic network derived from positron emission tomography (PET) with ¹⁸F-fluorodeoxyglucose in monitoring the STN DBS treatment for PD.

Methods

Age-matched 33 PD patients, 33 healthy controls (HCs), 9 PD patients with bilateral DBS surgery and 9 controls underwent ¹⁸F-FDG PET scans. The DBS patients were followed longitudinally to investigate the alternations of the PD-related metabolic covariance pattern (PDRP) expressions.

Results

The PDRP expression was abnormally elevated in PD patients compared with HCs (P < 0.001). For DBS patients, a significant decrease in the Unified Parkinson’s Disease Rating Scale (UPDRS, P = 0.001) and PDRP expression (P = 0.004) was observed 3 months after STN DBS treatment, while a rollback was observed in both UPDRS and PDRP expressions (both P < 0.01) 12 months after treatment. The changes in PDRP expression mediated by STN DBS were generally in line with UPDRS improvement. The graphical network analysis shows increased connections at 3 months and a return at 12 months confirmed by small-worldness coefficient.

Conclusions

The preliminary results demonstrate the potential of metabolic network expression as complimentary objective biomarker for the assessment and monitoring of STN DBS treatment in PD patients.

Clinical Trial Registration ChiCTR-DOC-16008645. http://www.chictr.org.cn/showproj.aspx?proj=13865.

Hemispheric Network Expression in Parkinson's Disease: Relationship to Dopaminergic Asymmetries

BACKGROUND

Parkinson's disease (PD) is characterized by brain metabolic networks, specifically associated with motor and cognitive manifestations. Few studies have investigated network changes in cerebral hemispheres ipsilateral and contralateral to the clinically more affected body side.

OBJECTIVE

We examined hemispheric network abnormalities and their relationship to striatal dopaminergic deficits in PD patients at different stages.

METHODS

45 PD patients underwent dual-tracer positron emission tomography (PET) with 18F-fluorodeoxyglucose (FDG) and 18F-fluorodopa (FDOPA) in a high-resolution PET scanner. In all patients, we computed expression levels for the PD-related motor/cognition metabolic patterns (PDRP/PDCP) as well as putamen/caudate FDOPA uptake values in both hemispheres. Resulting hemispheric measures in the PD group were compared with corresponding healthy control values and assessed across disease stages.

RESULTS

Hemispheric PDRP and PDCP expression was significantly elevated contralateral and ipsilateral to the more affected body side in patients with unilateral symptoms (H&Y 1: p < 0.01) and in patients with bilateral limb involvement (H&Y 2-3: p < 0.001; H&Y 4: p < 0.003). Elevations in pattern expression were symmetrical at all disease stages. By contrast, FDOPA uptake in the caudate and putamen was reduced bilaterally (p < 0.002), with lower values on both sides at more advanced disease stages. Hemispheric uptake was asymmetrical in both striatal regions, with lower contralateral values at all disease stages. The magnitude of hemispheric uptake asymmetry was smaller with more advanced disease, reflecting greater change ipsilaterally.

CONCLUSION

Symmetrical network expression in PD represents bilateral functional effects unrelated to nigrostriatal dopaminergic asymmetries.

Brain-First versus Gut-First Parkinson's Disease: A Hypothesis

Parkinson’s disease (PD) is a highly heterogeneous disorder, which probably consists of multiple subtypes. Aggregation of misfolded alpha-synuclein and propagation of these proteinacious aggregates through interconnected neural networks is believed to be a crucial pathogenetic factor. It has been hypothesized that the initial pathological alpha-synuclein aggregates originate in the enteric or peripheral nervous system (PNS) and invade the central nervous system (CNS) via retrograde vagal transport. However, evidence from neuropathological studies suggests that not all PD patients can be reconciled with this hypothesis. Importantly, a small fraction of patients do not show pathology in the dorsal motor nucleus of the vagus. Here, it is hypothesized that PD can be divided into a PNS-first and a CNS-first subtype. The former is tightly associated with REM sleep behavior disorder (RBD) during the prodromal phase and is characterized by marked autonomic damage before involvement of the dopaminergic system. In contrast, the CNS-first phenotype is most often RBD-negative during the prodromal phase and characterized by nigrostriatal dopaminergic dysfunction prior to involvement of the autonomic PNS. The existence of these subtypes is supported by in vivo imaging studies of RBD-positive and RBD-negative patient groups and by histological evidence— reviewed herein. The present proposal provides a fresh hypothesis-generating framework for future studies into the etiopathogenesis of PD and seems capable of explaining a number of discrepant findings in the neuropathological literature.

Characterizing the heterogeneous metabolic progression in idiopathic REM sleep behavior disorder

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Imaging biomarkers of the metabolic trajectory from HC, iRBD and PD are identified.

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Frontal, limbic and occipital brain regions as imaging biomarkers in PD.

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Frontal, limbic and occipital brain regions as imaging biomarkers of the phenoconversion from iRBD to PD.

Objective

Idiopathic rapid eye movement (REM) sleep behavior disorder (iRBD) is a prodromal stage of synucleinopathies such as Parkinson’s disease (PD). Positron emission tomography (PET) with ¹⁸F-FDG reveals metabolic perturbations, which are scored by spatial covariance analysis. However, the resultant pattern scores do not capture the spatially heterogeneous trajectories of metabolic changes between individual brain regions. Assuming metabolic progression occurs as a continuum from the healthy control (HC) condition to iRBD and then PD, we investigated spatial dynamics of progressively perturbed glucose metabolism in a cross-sectional study.

Methods

19 iRBD patients, 38 PD patients and 19 HC subjects underwent ¹⁸F-FDG PET. The images were spatially normalized, scaled to the global mean uptake, and automatically parcellated. We contrasted regional metabolism by group, and allocated the inferred progression to one of several possible trajectories. We further investigated the correlations between ¹⁸F-FDG uptake and the disease duration in the iRBD and PD groups, respectively. We also explored relationships between ¹⁸F-FDG uptake and the Unified Parkinson’s Disease Rating Scale motor (UPDRS III) scores in the PD group.

Results

PD patients exhibited more extensive relative hyper- and hypo-metabolism than iRBD patients. We identified three dynamic metabolic trajectories, cross-sectional hypo- or hypermetabolism, cross-sectionally unchanged hypo- or hypermetabolism, cross-sectionally late hypo- or hypermetabolism, appearing only in the contrast of PD with iRBD. No correlation was found between relative ¹⁸F-FDG metabolism and disease duration in the iRBD group. Regional hyper- and hypo-metabolism in the PD patients correlated with disease duration or clinical UPDRS III scores.

Conclusion

Cerebral metabolism changes heterogeneously in a continuum extending from HC to iRBD and PD groups in this preliminary study. The distinctive metabolic trajectories point towards a potential neuroimaging biomarker for conversion of iRBD to frank PD, which should be amenable to advanced pattern recognition analysis in future longitudinal studies.

A Fully Automatic Framework for Parkinson's Disease Diagnosis by Multi-Modality Images

Background

Parkinson’s disease (PD) is a prevalent long-term neurodegenerative disease. Though the criteria of PD diagnosis are relatively well defined, current diagnostic procedures using medical images are labor-intensive and expertise-demanding. Hence, highly integrated automatic diagnostic algorithms are desirable.

Methods

In this work, we propose an end-to-end multi-modality diagnostic framework, including segmentation, registration, feature extraction and machine learning, to analyze the features of striatum for PD diagnosis. Multi-modality images, including T1-weighted MRI and ¹¹C-CFT PET, are integrated into the proposed framework. The reliability of this method is validated on a dataset with the paired images from 49 PD subjects and 18 Normal (NL) subjects.

Results

We obtained a promising diagnostic accuracy in the PD/NL classification task. Meanwhile, several comparative experiments were conducted to validate the performance of the proposed framework.

Conclusion

We demonstrated that (1) the automatic segmentation provides accurate results for the diagnostic framework, (2) the method combining multi-modality images generates a better prediction accuracy than the method with single-modality PET images, and (3) the volume of the striatum is proved to be irrelevant to PD diagnosis.