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

Understanding REM Sleep Behavior Disorder through Functional MRI: A Systematic Review

Neuroimaging studies in rapid eye movement sleep behavior disorder (RBD) can inform fundamental questions about the pathogenesis of Parkinson's disease (PD). Across modalities, functional magnetic resonance imaging (fMRI) may be better suited to identify changes between neural networks in the earliest stages of Lewy body diseases when structural changes may be subtle or absent. This review synthesizes the findings from all fMRI studies of RBD to gain further insight into the pathophysiology and progression of Lewy body diseases. A total of 32 studies were identified using a systematic review conducted according to PRISMA guidelines between January 2000 to February 2024 for original fMRI studies in patients with either isolated RBD (iRBD) or RBD secondary to PD. Common functional alterations were detectable in iRBD patients compared with healthy controls across brainstem nuclei, basal ganglia, frontal and occipital lobes, and whole brain network measures. Patients with established PD and RBD demonstrated decreased functional connectivity across the whole brain and brainstem nuclei, but increased functional connectivity in the cerebellum and frontal lobe compared with those PD patients without RBD. Finally, longitudinal changes in resting state functional connectivity were found to track with disease progression. Currently, fMRI studies in RBD have demonstrated early signatures of neurodegeneration across both motor and non-motor pathways. Although more work is needed, such findings have the potential to inform our understanding of disease, help to distinguish between prodromal PD and prodromal dementia with Lewy bodies, and support the development of fMRI-based outcome measures of phenoconversion and progression in future disease modifying trials. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Tai Chi-Induced Exosomal LRP1 is Associated With Memory Function and Hippocampus Plasticity in aMCI Patients

OBJECTIVES

The study was designed to identify the potential peripheral processes of circulating exosome in response to Tai Chi (TC) exercise and the possibility of its loaded cargos in mediating the effects of TC training on cognitive function among older adults with amnestic mild cognitive impairment (aMCI).

DESIGN, SETTING, AND PARTICIPANTS

This was a multicenter randomized controlled trial. One hundred community-dwelling old adults with aMCI were randomly assigned (1:1) to experimental (n = 50) and control groups (n = 50).

INTERVENTION

The experimental group participated in TC exercise 5 times/week, with each session lasting 60 minutes for 12 weeks. Both experimental and control groups received health education every 4 weeks.

MEASUREMENTS

The primary outcome was global cognitive function. Neurocognitive assessments, MRI examination, and large-scale proteomics analysis of peripheric exosome were conducted at baseline and after 12-week training. Outcome assessors and statisticians were blinded to group allocation.

RESULTS

A total of 96 participants (96%) completed all outcome measurements. TC training improved global cognitive function (adjusted mean difference [MD] = 1.9, 95%CI 0.93-2.87, p <0.001) and memory (adjusted MD = 6.42, 95%CI 2.09-10.74, p = 0.004), increased right hippocampus volume (adjusted MD = 88.52, 95%CI 13.63-163.4, p = 0.021), and enhanced rest state functional connectivity (rsFC) between hippocampus and cuneus, which mediated the group effect on global cognitive function (bootstrapping CIs: [0.0208, 1.2826], [0.0689, 1.2211]) and verbal delay recall (bootstrapping CI: [0.0002, 0.6277]). Simultaneously, 24 differentially expressed exosomal proteins were detected in tandem mass tag-labelling proteomic analysis. Of which, the candidate protein low-density lipoprotein receptor-related protein 1 (LRP1) was further confirmed by parallel reaction monitoring and ELISA. Moreover, the up-regulated LRP1 was both positively associated with verbal delay recall and rsFC (left hippocampus-right cuneus).

CONCLUSION

TC promotes LRP1 release via exosome, which was associated with enhanced memory function and hippocampus plasticity in aMCI patients. Our findings provided an insight into potential therapeutic neurobiological targets focusing on peripheric exosome in respond to TC exercise.

Utilizing graph convolutional networks for identification of mild cognitive impairment from single modal fMRI data: a multiconnection pattern combination approach

Mild cognitive impairment plays a crucial role in predicting the early progression of Alzheimer's disease, and it can be used as an important indicator of the disease progression. Currently, numerous studies have focused on utilizing the functional brain network as a novel biomarker for mild cognitive impairment diagnosis. In this context, we employed a graph convolutional neural network to automatically extract functional brain network features, eliminating the need for manual feature extraction, to improve the mild cognitive impairment diagnosis performance. However, previous graph convolutional neural network approaches have primarily concentrated on single modes of brain connectivity, leading to a failure to leverage the potential complementary information offered by diverse connectivity patterns and limiting their efficacy. To address this limitation, we introduce a novel method called the graph convolutional neural network with multimodel connectivity, which integrates multimode connectivity for the identification of mild cognitive impairment using fMRI data and evaluates the graph convolutional neural network with multimodel connectivity approach through a mild cognitive impairment diagnostic task on the Alzheimer's Disease Neuroimaging Initiative dataset. Overall, our experimental results show the superiority of the proposed graph convolutional neural network with multimodel connectivity approach, achieving an accuracy rate of 92.2% and an area under the Receiver Operating Characteristic (ROC) curve of 0.988.

Diagnostic deep learning algorithms that use resting EEG to distinguish major depressive disorder, bipolar disorder, and schizophrenia from each other and from healthy volunteers

BACKGROUND

Mood disorders and schizophrenia affect millions worldwide. Currently, diagnosis is primarily determined by reported symptomatology. As symptoms may overlap, misdiagnosis is common, potentially leading to ineffective or destabilizing treatment. Diagnostic biomarkers could significantly improve clinical care by reducing dependence on symptomatic presentation.

METHODS

We used deep learning analysis (DLA) of resting electroencephalograph (EEG) to differentiate healthy control (HC) subjects (N = 239), from those with major depressive disorder (MDD) (N = 105), MDD-atypical (MDD-A) (N = 27), MDD-psychotic (MDD-P) (N = 35), bipolar disorder-depressed episode (BD-DE) (N = 71), BD-manic episode (BD-ME) (N = 49), and schizophrenia (SCZ) (N = 122) and also differentiate subjects with mental disorders on a pair-wise basis. DSM-III-R diagnoses were determined and supplemented by computerized Quick Diagnostic Interview Schedule. After EEG preprocessing, robust exact low-resolution electromagnetic tomography (ReLORETA) computed EEG sources for 82 brain regions. 20 % of all subjects were then set aside for independent testing. Feature selection methods were then used for the remaining subjects to identify brain source regions that are discriminating between diagnostic categories.

RESULTS

Pair-wise classification accuracies between 90 % and 100 % were obtained using independent test subjects whose data were not used for training purposes. The most frequently selected features across various pairs are in the postcentral, supramarginal, and fusiform gyri, the hypothalamus, and the left cuneus. Brain sites discriminating SCZ from HC were mainly in the left hemisphere while those separating BD-ME from HC were on the right.

LIMITATIONS

The use of superseded DSM-III-R diagnostic system and relatively small sample size in some disorder categories that may increase the risk of overestimation.

CONCLUSIONS

DLA of EEG could be trained to autonomously classify psychiatric disorders with over 90 % accuracy compared to an expert clinical team using standardized operational methods.

Tracking the progression of Alzheimer's disease: Insights from metabolic patterns of SOMI stages

BACKGROUND

SOMI (Stages of Objective Memory Impairment) is a novel classification that identifies six stages of memory decline in Alzheimer's Disease (AD) using the Free and Cued Selective Reminding Test (FCSRT). However, the relationship between SOMI stages and brain metabolism remains unexplored. This study aims to investigate the metabolic correlates of SOMI stages using FDG-PET in Mild Cognitive Impairment due to AD (MCI-AD) and early AD patients.

METHODS

One hundred twenty-nine-patients (99 aMCI-AD and 30 AD), and 42 healthy controls (HCs) (MMSE = 29.2 ± .8; age:69.1 ± 8.6 years; education:10.7 ± 3.8 years) who underwent an extensive neuropsychological battery including FCSRT and brain FDG-PET were enrolled. According to their clinical relevance and available sample sizes, SOMI-4 (N = 24 subjects; MMSE score:26.6 ± 2.6: age:75.4 ± 3.2; education:9.9 ± 4.5) and SOMI-5 groups (N = 97; MMSE:25.3 ± 2.6; age:73.9 ± 5.8; education:9.4 ± 4.1) were investigated.

RESULTS

Compared to HCs, SOMI-4 showed hypometabolism in the precuneus, medial temporal gyrus bilaterally, right pecuneus and angular gyrus. SOMI-5 exhibited broader hypometabolism, extending to the left posterior cingulate and medial frontal gyrus bilaterally. The conjunction analysis revealed overlapping areas in the precuneus, medial temporal gyrus bilaterally, and in the right angular gyrus and cuneus. The disjunction analysis identified SOMI-5 specific hypometabolism encompassing left inferior temporal gyrus, uncus and parahippocampal gyrus, and medial frontal gyrus bilaterally (p < .001, p-value (FWE) < .05).

DISCUSSION

SOMI-4 relates to posterior hypometabolism, while SOMI-5 to more extensive hypometabolism further encompassing frontal cortices, suggesting SOMI as a biologically relevant classification system of memory decline.

CONCLUSION

Memory decline staged with SOMI is associated with hypometabolism spreading in amnesic MCI-AD/AD, suggesting its usefulness as a clinical marker of increasing neurodegeneration.

Aberrant dynamic functional network connectivity in type 2 diabetes mellitus individuals

An increasing number of recent brain imaging studies are dedicated to understanding the neuro mechanism of cognitive impairment in type 2 diabetes mellitus (T2DM) individuals. In contrast to efforts to date that are limited to static functional connectivity, here we investigate abnormal connectivity in T2DM individuals by characterizing the time-varying properties of brain functional networks. Using group independent component analysis (GICA), sliding-window analysis, and k-means clustering, we extracted thirty-one intrinsic connectivity networks (ICNs) and estimated four recurring brain states. We observed significant group differences in fraction time (FT) and mean dwell time (MDT), and significant negative correlation between the Montreal Cognitive Assessment (MoCA) scores and FT/MDT. We found that in the T2DM group the inter- and intra-network connectivity decreases and increases respectively for the default mode network (DMN) and task-positive network (TPN). We also found alteration in the precuneus network (PCUN) and enhanced connectivity between the salience network (SN) and the TPN. Our study provides evidence of alterations of large-scale resting networks in T2DM individuals and shed light on the fundamental mechanisms of neurocognitive deficits in T2DM.

Diagnosis of Alzheimer's disease by joining dual attention CNN and MLP based on structural MRIs, clinical and genetic data

Alzheimer's disease (AD) is an irreversible central nervous degenerative disease, while mild cognitive impairment (MCI) is a precursor state of AD. Accurate early diagnosis of AD is conducive to the prevention and early intervention treatment of AD. Although some computational methods have been developed for AD diagnosis, most employ only neuroimaging, ignoring other data (e.g., genetic, clinical) that may have potential disease information. In addition, the results of some methods lack interpretability. In this work, we proposed a novel method (called DANMLP) of joining dual attention convolutional neural network (CNN) and multilayer perceptron (MLP) for computer-aided AD diagnosis by integrating multi-modality data of the structural magnetic resonance imaging (sMRI), clinical data (i.e., demographics, neuropsychology), and APOE genetic data. Our DANMLP consists of four primary components: (1) the Patch-CNN for extracting the image characteristics from each local patch, (2) the position self-attention block for capturing the dependencies between features within a patch, (3) the channel self-attention block for capturing dependencies of inter-patch features, (4) two MLP networks for extracting the clinical features and outputting the AD classification results, respectively. Compared with other state-of-the-art methods in the 5CV test, DANMLP achieves 93% and 82.4% classification accuracy for the AD vs. MCI and MCI vs. NC tasks on the ADNI database, which is 0.2%∼15.2% and 3.4%∼26.8% higher than that of other five methods, respectively. The individualized visualization of focal areas can also help clinicians in the early diagnosis of AD. These results indicate that DANMLP can be effectively used for diagnosing AD and MCI patients.

Severity of REM sleep without atonia correlates with measures of cognitive impairment and depressive symptoms in REM sleep behaviour disorder

This study aimed to correlate REM sleep without atonia (RSWA) and neuropsychological data in patients with idiopathic/isolated REM sleep behaviour disorder (iRBD) and those with RBD associated with Parkinson's disease (PDRBD), in order to assess whether higher degrees of RSWA are related to poorer cognitive performance. A total of 142 subjects were enrolled: 48 with iRBD, 55 with PDRBD, and 39 PD without RBD (PDnoRBD). All participants underwent video-polysomnographic recording, clinical and neuropsychological assessment. RSWA was quantified according to two manual scoring methods (Montréal, SINBAR) and one automated (REM atonia index, RAI). Mild cognitive impairment (MCI) was diagnosed according to diagnostic criteria for MCI in Parkinson's disease. The relationship between neuropsychological scores and RSWA metrics was explored by multiple linear regression analysis and logistic regression models. Patients with iRBD showed significantly lower visuospatial functions and working memory, compared with the others. More severe RSWA was associated with a higher risk of reduced visuospatial abilities (OR 0.15), working memory (OR 2.48), attention (OR 2.53), and semantic fluency (OR 0.15) in the iRBD. In the whole group, a greater RSWA was associated with an increased risk for depressive symptoms (OR 3.6). A total of 57(40%) MCI subjects were found (17 iRBD, 26 PDRBD, and 14 PDnoRBD). Preserved REM-atonia was associated with a reduced odds of multi-domain MCI in the whole study population (OR 0.54). In conclusion, a greater severity of RSWA was associated with an increased risk for poor cognitive performance and depressive mood in patients with RBD. Moreover, higher RAI was associated with a lower risk of multi-domain MCI.

Nucleus basalis of Meynert predicts cognitive changes in isolated REM sleep behavior disorder

BACKGROUND

Degeneration of the nucleus basalis of Meynert (NBM) has been implicated in cognitive impairments in Parkinson's disease. The role of the NBM volumes in the cognitive function in isolated rapid eye movement (REM) sleep behavior disorder (iRBD) has not been explored.

METHOD

We investigated changes in NBM volumes and their associations with cognitive deficits in iRBD. Baseline NBM volumes were compared between 29 iRBD patients and 29 healthy controls by using structural MRI data from the Parkinson Progression Marker Initiative database. Partial correlation analyses were used to evaluate cross-sectional relationships between baseline NBM volumes and cognitive performance in iRBD. Linear mixed models were applied to assess between-group differences in longitudinal cognitive changes, and whether baseline NBM volumes could predict longitudinal changes of cognition in iRBD.

RESULTS

Compared with controls, NBM volumes were significantly reduced in iRBD patients. In patients with iRBD, higher NBM volumes were significantly associated with greater performance in global cognition function. In the longitudinal analyses, iRBD patients showed more severe and rapid decline on tests of global cognition compared to healthy controls. Furthermore, greater baseline NBM volumes were significantly associated with greater follow-up Montreal Cognitive Assessment (MoCA) scores, thus predicting less longitudinal cognitive changes in iRBD.

CONCLUSION

This study provides important in vivo evidence for an association between the NBM degeneration and cognitive impairments in iRBD.

Validation of the REM behaviour disorder phenoconversion-related pattern in an independent cohort

BACKGROUND

A brain glucose metabolism pattern related to phenoconversion in patients with idiopathic/isolated REM sleep behaviour disorder (iRBDconvRP) was recently identified. However, the validation of the iRBDconvRP in an external, independent group of iRBD patients is needed to verify the reproducibility of such pattern, so to increase its importance in clinical and research settings. The aim of this work was to validate the iRBDconvRP in an independent group of iRBD patients.

METHODS

Forty iRBD patients (70 ± 5.59 years, 19 females) underwent brain [18F]FDG-PET in Seoul National University. Thirteen patients phenoconverted at follow-up (7 Parkinson disease, 5 Dementia with Lewy bodies, 1 Multiple system atrophy; follow-up time 35 ± 20.56 months) and 27 patients were still free from parkinsonism/dementia after 62 ± 29.49 months from baseline. We applied the previously identified iRBDconvRP to validate its phenoconversion prediction power.

RESULTS

The iRBDconvRP significantly discriminated converters from non-converters iRBD patients (p = 0.016; Area under the Curve 0.74, Sensitivity 0.69, Specificity 0.78), and it significantly predicted phenoconversion (Hazard ratio 4.26, C.I.95%: 1.18-15.39).

CONCLUSIONS

The iRBDconvRP confirmed its robustness in predicting phenoconversion in an independent group of iRBD patients, suggesting its potential role as a stratification biomarker for disease-modifying trials.

Parkinson's Disease: A Narrative Review on Potential Molecular Mechanisms of Sleep Disturbances, REM Behavior Disorder, and Melatonin

Parkinson's disease (PD) is one of the most common neurodegenerative diseases. There is a wide range of sleep disturbances in patients with PD, such as insomnia and rapid eye movement (REM) sleep behavior disorder (or REM behavior disorder (RBD)). RBD is a sleep disorder in which a patient acts out his/her dreams and includes abnormal behaviors during the REM phase of sleep. On the other hand, melatonin is the principal hormone that is secreted by the pineal gland and significantly modulates the circadian clock and mood state. Furthermore, melatonin has a wide range of regulatory effects and is a safe treatment for sleep disturbances such as RBD in PD. However, the molecular mechanisms of melatonin involved in the treatment or control of RBD are unknown. In this study, we reviewed the pathophysiology of PD and sleep disturbances, including RBD. We also discussed the potential molecular mechanisms of melatonin involved in its therapeutic effect. It was concluded that disruption of crucial neurotransmitter systems that mediate sleep, including norepinephrine, serotonin, dopamine, and GABA, and important neurotransmitter systems that mediate the REM phase, including acetylcholine, serotonin, and norepinephrine, are significantly involved in the induction of sleep disturbances, including RBD in PD. It was also concluded that accumulation of α-synuclein in sleep-related brain regions can disrupt sleep processes and the circadian rhythm. We suggested that new treatment strategies for sleep disturbances in PD may focus on the modulation of α-synuclein aggregation or expression.

Discrepancy Between Patient and Caregiver Estimate of Apathy Predicts Dementia in Patients with Amnestic Mild Cognitive Impairment

BACKGROUND

Apathy is a frequent behavioral symptom of Alzheimer's disease (AD). The Apathy Evaluation Scale (AES) is a tool exploring the perception of apathy by both caregivers (CG-AES) and patients (PT-AES), and the discrepancy in their ratings is a proxy of patients' disease unawareness.

OBJECTIVE

To assess in a cohort study of patients with amnesic mild cognitive impairment (aMCI) whether apathy and awareness of apathy predict progression to dementia and timing.

METHODS

From the global AES scores of 110 patients with aMCI and their caregivers, we obtained two principal indices for analysis: 1) 'Apathy', the mean of PT-AES and CG-AES, and 2) 'Discrepancy', obtained by subtracting CG-AES from PT-AES. Patients were followed with visits every six months for three years or until dementia. AES indices and the principal demographical/neuropsychological variables were filtered from multicollinearity. The most robust variables entered a logistic regression model and survival analyses (Cox regression, log-rank test of Kaplan-Meier curves) to estimate which predicted the risk and timing of progression, respectively.

RESULTS

Sixty patients (54.5%) developed dementia (57 AD) after 6.0-36.0 months, 22 (20%) remained in an MCI stage, and 28 (25.5%) dropped out. 'Discrepancy' was a robust and accurate predictor of the risk of progression (AUC = 0.73) and, after binarization according to a computed cutoff, of timing to dementia.

CONCLUSION

A structured evaluation of apathy, both self-assessed and estimated by caregivers, can provide useful information on the risk and timing of progression from aMCI to dementia. The discrepancy between the two estimates is a fairly reliable index for prediction purposes as a proxy of disease unawareness.

Assessing functional connectivity differences and work-related fatigue in surviving COVID-negative patients

The Coronavirus Disease 2019 (COVID-19) has affected all aspects of life around the world. Neuroimaging evidence suggests the novel coronavirus can attack the central nervous system (CNS), causing cerebro-vascular abnormalities in the brain. This can lead to focal changes in cerebral blood flow and metabolic oxygen consumption rate in the brain. However, the extent and spatial locations of brain alterations in COVID-19 survivors are largely unknown. In this study, we have assessed brain functional connectivity (FC) using resting-state functional MRI (RS-fMRI) in 38 (25 males) COVID patients two weeks after hospital discharge, when PCR negative and 31 (24 males) healthy subjects. FC was estimated using independent component analysis (ICA) and dual regression. When compared to the healthy group, the COVID group demonstrated significantly enhanced FC in the basal ganglia and precuneus networks (family wise error (fwe) corrected, pfwe < 0.05), while, on the other hand, reduced FC in the language network (pfwe < 0.05). The COVID group also experienced higher fatigue levels during work, compared to the healthy group (p < 0.001). Moreover, within the precuneus network, we noticed a significant negative correlation between FC and fatigue scores across groups (Spearman's ρ = -0.47, p = 0.001, r2 = 0.22). Interestingly, this relationship was found to be significantly stronger among COVID survivors within the left parietal lobe, which is known to be structurally and functionally associated with fatigue in other neurological disorders.

Neuropsychiatric, neuropsychological, and neuroimaging features in isolated REM sleep behavior disorder: The importance of MCI

BACKGROUND

Mild cognitive impairment (MCI) is frequently diagnosed in patients with isolated rapid eye movement (REM) sleep behavior disorder (iRBD), although the extent of MCI-associated neuropathology has not yet been quantified. The present study compared the differences in neuropsychiatric, neuropsychological, and neuroimaging markers of neurodegeneration in MCI-iRBD and iRBD patients with normal cognition.

METHODS

Sixty-one patients with iRBD were included in the study: 30 patients were included in the MCI subgroup (RBD-MCI) and 31 in the normal cognition subgroup (RBD-NC). Both groups underwent neuropsychiatric and neuropsychological assessments to evaluate psychopathological symptoms and neuropsychological functions. Brain [18F]FDG PET and 123I-FP-CIT-SPECT were performed to evaluate brain glucose metabolism and nigrostriatal dopaminergic function in convenient subgroups of patients, respectively.

RESULTS

Neuropsychological measures generally confirmed overall cognitive decline in patients with iRBD-MCI. Immediate long-term verbal memory and visuospatial functions, as well as attentional-executive impairment were evident in the MCI group compared to the NC group. Neuroimaging results indicated reduced brain glucose uptake in the bilateral posterior cingulate cortex and more evident nigrostriatal deafferentation in the RBD-MCI group. There were no differences in psychopathological symptoms between the two groups.

CONCLUSIONS

This study confirmed that iRBD patients with MCI had a more impaired cognitive status that those with NC. Moreover, the MCI subgroup presented reduced cerebral glucose consumption in brain areas critical for cognition, and a more severe deafferentation of the nigro-striatal regions, highlighting the importance of identifying iRBD patients with MCI for urgent neuroprotective trials.

Cognitive and Brain Metabolism Profiles of Mild Cognitive Impairment in Prodromal Alpha-Synucleinopathy

Background: Mild cognitive impairment (MCI) is a heterogeneous condition. Idiopathic REM sleep behavior disorder (iRBD) can be associated with MCI (MCI-RBD). Objective: To investigate neuropsychological and brain metabolism features of patients with MCI-RBD by comparison with matched MCI-AD patients. To explore their predictive value toward conversion to a full-blown neurodegenerative disease. Methods: Seventeen MCI-RBD patients (73.6±6.5 years) were enrolled. Thirty-four patients with MCI-AD were matched for age (74.8±4.4 years), Mini-Mental State Exam score and education with a case-control criterion. All patients underwent a neuropsychological assessment and brain 18F-FDG-PET. Images were compared between groups to identify hypometabolic volumes of interest (MCI-RBD-VOI and MCI-AD-VOI). The dependency of whole-brain scaled metabolism levels in MCI-RBD-VOI and MCI-AD-VOI on neuropsychological test scores was explored with linear regression analyses in both groups, adjusting for age and education. Survival analysis was performed to investigate VOIs phenoconversion prediction power. Results: MCI-RBD group scored lower in executive functions and higher in verbal memory compared to MCI-AD group. Also, compared with MCI-AD, MCI-RBD group showed relative hypometabolism in a posterior brain area including cuneus, precuneus, and occipital regions while the inverse comparison revealed relative hypometabolism in the hippocampus/parahippocampal areas in MCI-AD group. MCI-RBD-VOI metabolism directly correlated with executive functions in MCI-RBD (p = 0.04). MCI-AD-VOI metabolism directly correlated with verbal memory in MCI-AD (p = 0.001). MCI-RBD-VOI metabolism predicted (p = 0.03) phenoconversion to an alpha-synucleinopathy. MCI-AD-VOI metabolism showed a trend (p = 0.07) in predicting phenoconversion to dementia. Conclusion: MCI-RBD and MCI-AD showed distinct neuropsychological and brain metabolism profiles, that may be helpful for both diagnosis and prognosis purposes.

Brain Metabolism Related to Mild Cognitive Impairment and Phenoconversion in Patients With Isolated REM Sleep Behavior Disorder

Background and Objectives

Mild cognitive impairment (MCI) in isolated REM sleep behavior disorder (iRBD) is a risk factor for subsequent neurodegeneration. We aimed to identify brain metabolism and functional connectivity changes related to MCI in patients with iRBD and the neuroimaging markers' predictive value for phenoconversion.

Methods

This is a prospective cohort study of patients with iRBD with a mean follow-up of 4.2 ± 2.6 years. At baseline, patients with iRBD and age- and sex-matched healthy controls (HCs) underwent ¹⁸F-fluorodeoxyglucose (FDG)–PET and resting-state fMRI scans and a comprehensive neuropsychological test battery. Voxel-wise group comparisons for FDG-PET data were performed using a general linear model. Seed-based connectivity maps were computed using brain regions showing significant hypometabolism associated with MCI in patients with iRBD and compared between groups. A Cox regression analysis was applied to investigate the association between brain metabolism and risk of phenoconversion.

Results

Forty patients with iRBD, including 21 with MCI (iRBD-MCI) and 19 with normal cognition (iRBD-NC), and 24 HCs were included in the study. The iRBD-MCI group revealed relative hypometabolism in the inferior parietal lobule, lateral and medial occipital, and middle and inferior temporal cortex bilaterally compared with HC and the iRBD-NC group. In seed-based connectivity analyses, the iRBD-MCI group exhibited decreased functional connectivity of the left angular gyrus with the occipital cortex. Of 40 patients with iRBD, 12 patients converted to Parkinson disease (PD) or dementia with Lewy bodies (DLB). Hypometabolism of the occipital pole (hazard ratio [95% CI] 6.652 [1.387–31.987]), medial occipital (4.450 [1.143–17.327]), and precuneus (3.635 [1.009–13.093]) was associated with higher phenoconversion rate to PD/DLB.

Discussion

MCI in iRBD is related to functional and metabolic changes in broad brain areas, particularly the occipital and parietal areas. Moreover, hypometabolism in these brain regions was a predictor of phenoconversion to PD or DLB. Evaluation of cognitive function and neuroimaging characteristics could be useful for risk stratification in patients with iRBD.

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.

Alerting network alteration in isolated rapid eye movement sleep behavior disorder patients with mild cognitive impairment

OBJECTIVE

Mild cognitive impairment (MCI) was found in 30-50% of the isolated REM sleep behavior disorder (iRBD) patients. Furthermore, it is known that patients with Parkinson's disease have attention network defects. Given that iRBD is known to be the prodromal disease of α-synucleinopathies, our aim was to investigate whether there are attention network dysfunctions in iRBD patients following the presence of MCI.

METHODS

14 healthy controls, 48 iRBD patients, 24 with MCI and 24 without MCI, were included in this study. Attention network task (ANT) was used to assess alerting, orienting, and executive control networks. Event-related potentials (ERPs) and behavioral performances were recorded during the ANT. Parietal N1 and P3 components were analyzed to find effects of the three attention networks.

RESULTS

IRBD patients without MCI showed neuropsychological, behavioral, and ERP results similar to those of healthy controls. On the other hand, iRBD patients with MCI showed a general decline in cognitive domains with no alerting effect (controls, p = 0.043; iRBD-noMCI, p = 0.014; iRBD-MCI, p = 0.130) while preserving orienting and executive control effect. Furthermore, iRBD patients with MCI had impairments in executive function and verbal memory domains, compared to iRBD patients without MCI.

CONCLUSIONS

Our findings indicate that when cognition is reduced to MCI levels in iRBD patients, the attention network, especially the alerting component, is impaired. The attention network and cognition, on the other hand, can be preserved in iRBD patients due to the compensatory mechanism.

Polysomnographic correlates of sleep disturbances in de novo, drug naïve Parkinson's Disease

Background

Sleep disturbances are common non-motor symptoms of Parkinson’s Disease (PD).

Methods

The aim of this study was to investigate the polysomnographic correlates of sleep changes, as investigated by the Parkinson’s Disease Sleep Scale-2 (PDSS-2), in a cohort of sixty-two consecutive de novo, drug naïve PD patients (71.40 ± 7.84 y/o).

Results

PDSS-2 total score showed a direct correlation with stage shifts (p = 0.008). Fragmented sleep showed an inverse correlation with sleep efficiency (p = 0.012). Insomnia symptoms showed an inverse correlation with wake after sleep onset (p = 0.005) and direct correlation with periodic leg movements (p = 0.006) and stage shift indices (p = 0.003). Motor Symptoms showed a direct correlation with Apnoea-Hypopnoea (AHI; p = 0.02) and awakenings indices (p = 0.003). Dream distressing showed a direct correlation with REM without atonia (RWA, p = 0.042) and an inverse correlation with AHI (p = 0.012). Sleep quality showed an inverse correlation with RWA (p = 0.008).

Conclusion

PDSS-2 features are significantly correlated with polysomnography objective findings, thus further supporting its reliability to investigate sleep disturbances in PD patients.

Stratification Tools for Disease-Modifying Trials in Prodromal Synucleinopathy

Background

Dopamine transporter single photon‐emission computed tomography (DAT‐SPECT) is the strongest risk factor for phenoconversion in patients with idiopathic rapid eye movement (REM)‐sleep behavior disorder (iRBD). However, it might be used as a second‐line stratification tool in clinical trials, because it is expensive and mini‐invasive.

Objective

Aim of the study is to investigate whether other cost‐effective and non‐invasive biomarkers may be proposed as first‐line stratification tools.

Methods

Forty‐seven consecutive iRBD patients (68.53 ± 7.16 years, 40 males) underwent baseline clinical and neuropsychological assessment, olfaction test, resting electroencephalogram (EEG), and DAT‐SPECT. All patients underwent 6 month‐based clinical follow‐up to investigate the emergence of parkinsonism and/or dementia. Survival analysis and Cox regression were used to estimate conversion risk.

Results

Seventeen patients developed an overt synucleinopathy (eight Parkinsonism and nine dementia) 32.8 ± 22 months after diagnosis. The strongest risk factors were putamen specific to non‐displaceable binding ratio (SBR) (hazard ratio [HR], 7.3), attention/working memory cognitive function (NPS‐AT/WM) (HR, 5.9), EEG occipital mean frequency (HR, 2.7) and clinical motor assessment (HR, 2.3). On multivariate Cox‐regression analysis, only putamen SBR and NPS‐AT/WM significantly contributed to the model (HR, 6.2, 95% confidence interval [CI], 1.9–19.8). At post‐hoc analysis, the trail‐making test B (TMT‐B) was the single most efficient first‐line stratification tool that allowed to reduce the number of eligible subjects to 76.6% (sensitivity 1, specificity 0.37). Combining TMT‐B and DAT‐SPECT further reduced the sample to 66% (sensitivity 0.88, specificity 0.47).

Conclusion

The TMT‐B seems to be a cost‐effective and efficient first‐line screening tool, to be used to select patients that deserve DAT‐SPECT as second‐line screening tool for disease‐modifying clinical trials. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society

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.

Dopaminergic and Serotonergic Degeneration and Cortical [18 F]Fluorodeoxyglucose Positron Emission Tomography in De Novo Parkinson's Disease

BACKGROUND

Degeneration of the nigrostriatal dopaminergic (DA) and the raphe-thalamic serotonergic (SE) systems is among the earliest changes observed in Parkinson's disease (PD). The consequences of those changes on brain metabolism, especially regarding their impact on the cortex, are poorly understood.

OBJECTIVES

Using multi-tracer molecular imaging, we assessed in a cohort of drug-naive PD patients the association between cortical metabolism and DA and SE system deafferentation of either striatum or thalamus, and we explored whether this association was mediated by either striatum or thalamus metabolism.

METHODS

We recruited 96 drug-naive PD patients (aged 71.9 ± 7.5 years) who underwent [¹²³ I]ioflupane single-photon emission computed tomography ([¹²³ I]FP-CIT-SPECT) and brain [¹⁸ F]fluorodeoxyglucose positron emission tomography ([¹⁸ F]FDG-PET). We used a voxel-wise analysis of [¹⁸ F]FDG-PET images to correlate regional metabolism with striatal DA and thalamic SE innervation as assessed using [¹²³ I]FP-CIT-SPECT.

RESULTS

We found that [¹²³ I]FP-CIT specific to nondisplaceable binding ratio (SBR) and glucose metabolism positively correlated with one another in the deep gray matter (thalamus: P = 0.001, r = 0.541; caudate P = 0.001, r = 0.331; putamen P = 0.001, r = 0.423). We then observed a direct correlation between temporoparietal metabolism and caudate DA innervation, as well as a direct correlation between prefrontal metabolism and thalamus SE innervation. The effect of caudate [¹²³ I]FP-CIT SBR values on temporoparietal metabolism was mediated by caudate metabolic values (percentage mediated: 89%, P-value = 0.008), and the effect of thalamus [¹²³ I]FP-CIT SBR values on prefrontal metabolism was fully mediated by thalamus metabolic values (P < 0.001).

CONCLUSIONS

These data suggest that the impact of deep gray matter monoaminergic deafferentation on cortical function is mediated by striatal and thalamic metabolism in drug-naive PD. © 2021 International Parkinson and Movement Disorder Society.