The mystery of motor asymmetry in Parkinson's disease

The effect of pallidal stimulation on sleep outcomes and related brain connectometries in Parkinson's disease

Sleep difficulties affect up to 98% of Parkinson's disease (PD) patients and are often not well treated. How globus pallidus internus (GPi)-DBS could help is less understood. We retrospectively analyzed sleep outcomes in 32 PD patients after GPi-DBS with a two-year follow-up. We observed high heterogeneity in sleep response to pallidal stimulation: 16 patients showed clinically meaningful improvement, 9 had minor changes, and 7 experienced worsened sleep quality, with no overall significant change on the Parkinson's Disease Sleep Scale-2 (P = 0.19). Further analysis revealed that stimulation of the left sensorimotor GPi was significantly associated with sleep improvement. Fiber tracts from the left sensorimotor GPi to the bilateral sensorimotor cortex, right GPi, brainstem, and bilateral cerebellum were linked to better sleep, while projections to the left hippocampus correlated with worsened sleep. These findings may guide personalized GPi-DBS lead placement to optimize sleep outcomes in PD.

Motor compensation in Parkinson's disease: an empirical challenge with clinical implications

This scientific commentary refers to ‘Neurophysiological markers of motor compensatory mechanisms in early Parkinson’s disease’ by Passaretti et al. (https://doi.org/10.1093/brain/awae210).

Classification of Parkinson's disease severity using gait stance signals in a spatiotemporal deep learning classifier

Parkinson's disease (PD) is a degenerative nervous system disorder involving motor disturbances. Motor alterations affect the gait according to the progression of PD and can be used by experts in movement disorders to rate the severity of the disease. However, this rating depends on the expertise of the clinical specialist. Therefore, the diagnosis may be inaccurate, particularly in the early stages of PD where abnormal gait patterns can result from normal aging or other medical conditions. Consequently, several classification systems have been developed to enhance PD diagnosis. In this paper, a PD gait severity classification algorithm was developed using vertical ground reaction force (VGRF) signals. The VGRF records used are from a public database that includes 93 PD patients and 72 healthy controls adults. The work presented here focuses on modeling each foot's gait stance phase signals using a modified convolutional long deep neural network (CLDNN) architecture. Subsequently, the results of each model are combined to predict PD severity. The classifier performance was evaluated using ten-fold cross-validation. The best-weighted accuracies obtained were 99.296(0.128)% and 99.343(0.182)%, with the Hoehn-Yahr and UPDRS scales, respectively, outperforming previous results presented in the literature. The classifier proposed here can effectively differentiate gait patterns of different PD severity levels based on gait signals of the stance phase.

Reaching and stepping respond differently to medication and cueing in Parkinson's disease

The basal ganglia contribute to internal timekeeping, and dopaminergic medication has been observed to moderate timing deficits associated with Parkinson's Disease (PD) during single joint movements. However, it is unclear whether similar effects can be observed in multi-joint movements. Twenty-five people with PD and twelve healthy peers performed repetitive reaching and stepping-in-place tasks with and without auditory cues at their self-selected maximal cadence. The PD group was measured ON and OFF medication. Reduced cadence error was found for both groups and tasks when cued, and ON PD exhibited decreased cadence compared to OFF PD. Overall timing variability was no different from controls, but differences were found in estimates of clock and motor variance using the Wing-Kristofferson model of interval timing. A medication and cueing interaction during the reaching task produced increased clock variance in uncued, ON PD. During the stepping task, clock and motor variance of the PD group were unaffected by cues, in contrast to the control group. Serial lag-one correlation was reduced in both groups for cued reaching, but was unaffected by cueing or medication in the PD group when stepping-in-place. These findings suggest that overall timing variability may not capture timing deficits in PD.

Deep learning-based detection of affected body parts in Parkinson's disease and freezing of gait using time-series imaging

We proposed a deep learning method using a convolutional neural network on time-series (TS) images to detect and differentiate affected body parts in people with Parkinson's disease (PD) and freezing of gait (FOG) during 360° turning tasks. The 360° turning task was performed by 90 participants (60 people with PD [30 freezers and 30 nonfreezers] and 30 age-matched older adults (controls) at their preferred speed. The position and acceleration underwent preprocessing. The analysis was expanded from temporal to visual data using TS imaging methods. According to the PD vs. controls classification, the right lower third of the lateral shank (RTIB) on the least affected side (LAS) and the right calcaneus (RHEE) on the LAS were the most relevant body segments in the position and acceleration TS images. The RHEE marker exhibited the highest accuracy in the acceleration TS images. The identified markers for the classification of freezers vs. nonfreezers vs. controls were the left lateral humeral epicondyle (LELB) on the more affected side and the left posterior superior iliac spine (LPSI). The LPSI marker in the acceleration TS images displayed the highest accuracy. This approach could be a useful supplementary tool for determining PD severity and FOG.

Adjustability of Gait Speed in Clinics and Free-Living Environments for People With Parkinson's Disease

OBJECTIVE

Gait speed is regulated by varying gait parameters depending on the diverse contexts of the environment. People with Parkinson's disease (PwPD) have difficulty adapting to gait control in their environment; however, the relationships between gait speed and spatiotemporal parameters in free-living environments have not been clarified. This study aimed to compare gait parameters according to gait speed in clinics and free-living environments.

METHODS

PwPD were assessed at the clinic and in a free-living environment using an accelerometer on the lower back. By fitting a bimodal Gaussian model to the gait speed distribution, gait speed was divided into lower and higher speeds. We compared the spatiotemporal gait parameters using a 2 × 2 (environment [clinic/free-living] × speed [lower/higher]) repeated-measures analysis of variance. Associations between Parkinson's disease symptoms and gait parameters were evaluated using Bayesian Pearson's correlation coefficients.

RESULTS

In the 41 PwPD included in this study, spatiotemporal gait parameters were significantly worse in free-living environments than in clinics and at lower speeds than at higher speeds. The fit of the walking speed distribution to the bimodal Gaussian model (adjustability of gait speed) in free-living environments was related to spatiotemporal gait parameters, severity of Parkinson's disease, number of falls, and quality of life.

CONCLUSION

The findings suggest that gait control, which involves adjusting gait speed according to context, differs between clinics and free-living environments in PwPD. Gait assessments for PwPD in both clinical and free-living environments should interpret gait impairments in a complementary manner.

Is speech function lateralised in the basal ganglia? Evidence from de novo Parkinson's disease

BACKGROUND

Research on the possible influence of lateralised basal ganglia dysfunction on speech in Parkinson's disease is scarce. This study aimed to compare speech in de-novo, drug-naive patients with Parkinson's disease (PD) with asymmetric nigral dopaminergic dysfunction, predominantly in either the right or left hemisphere.

METHODS

Acoustic analyses of reading passages were performed. Asymmetry of nigral dysfunction was defined using dopamine transporter-single-photon emission CT (DAT-SPECT).

RESULTS

From a total of 135 de novo patients with PD assessed, 47 patients had a lower right and 36 lower left DAT availability in putamen based on DAT-SPECT. Patients with PD with lower left DAT availability had higher dysarthria severity via composite dysarthria index compared with patients with lower right DAT availability (p=0.01).

CONCLUSION

Our data support the crucial role of DAT availability in the left putamen in speech. This finding might provide important clues for managing speech following deep brain stimulation.

Brain (EEG) and muscle (EMG) activity related to 3D sit-to-stand kinematics in healthy adults and in central neurological pathology - A systematic review

BACKGROUND

The sit-to-stand transfer is a fundamental functional movement during normal activities of daily living. Central nervous system disorders can negatively impact the execution of sit-to-stand transfers, often impeding successful completion. Despite its importance, the neurophysiological basis at muscle (electromyography (EMG)) and brain (electroencephalography (EEG)) level as related to the kinematic movement is not well understood.

OBJECTIVES

This review synthesises the published literature addressing central and peripheral neural activity during 3D kinematic capture of sit-to-stand transfers.

METHODS

A pre-registered systematic review was conducted. Electronic databases (PubMed, CINAHL Plus, Web of Science, Scopus and EMBASE) were searched from inception using search operators that included sit-to-stand, kinematics and EMG and/or EEG. The search was not limited by study type but was limited to populations comprising of healthy individuals or individuals with a central neurological pathology.

RESULTS

From a total of 28,770 identified papers, 59 were eligible for inclusion. Ten of these 59 studies received a moderate quality rating; with the remainder rated as weak using the Effective Public Health Practice Project tool. Fifty-eight studies captured kinematic data of sit-to-stand with associated EMG activity only and one study captured kinematics with co-registered EMG and EEG data. Fifty-six studies examined sit-to-stand transfer in healthy individuals, reporting four dynamic movement phases and three muscle synergies commonly used by most individuals to stand-up. Pre-movement EEG activity was reported in one study with an absence of data during execution. Eight studies examined participants following stroke and two examined participants with Parkinson's disease, both reporting no statistically significant differences between their kinematics and muscle activity and those of healthy controls.

SIGNIFICANCE

Little is known about the neural basis of the sit-to-stand transfer at brain level with limited focus in central neurological pathology. This poses a barrier to targeted mechanistic-based rehabilitation of the sit-to-stand movement in neurological populations.

Subthalamic DBS does not restore deficits in corticospinal suppression during movement preparation in Parkinson's disease

OBJECTIVE

Parkinson's disease (PD) patients exhibit changes in mechanisms underlying movement preparation, particularly the suppression of corticospinal excitability - termed "preparatory suppression" - which is thought to facilitate movement execution in healthy individuals. Deep brain stimulation (DBS) of the subthalamic nucleus (STN) being an attractive treatment for advanced PD, we aimed to study the potential contribution of this nucleus to PD-related changes in such corticospinal dynamics.

METHODS

On two consecutive days, we applied single-pulse transcranial magnetic stimulation to the primary motor cortex of 20 advanced PD patients treated with bilateral STN-DBS (ON vs. OFF), as well as 20 healthy control subjects. Motor-evoked potentials (MEPs) were elicited at rest or during movement preparation in an instructed-delay choice reaction time task including left- or right-hand responses. Preparatory suppression was assessed by expressing MEPs during movement preparation relative to rest.

RESULTS

PD patients exhibited a deficit in preparatory suppression when it was probed on the responding hand side, particularly when this corresponded to their most-affected hand, regardless of their STN-DBS status.

CONCLUSIONS

Advanced PD patients displayed a reduction in preparatory suppression which was not restored by STN-DBS.

SIGNIFICANCE

The current findings confirm that PD patients lack preparatory suppression, as previously reported. Yet, the fact that this deficit was not responsive to STN-DBS calls for future studies on the neural source of this regulatory mechanism during movement preparation.

Clinical asymmetry in Parkinson's disease is characterized by prevalence of subthalamic pause-burst neurons and alpha-beta oscillations

OBJECTIVE

We aimed to establish specific biomarkers of Parkinson's disease (PD) by comparing activity of more affected (MA) and less affected (LA) subthalamic nucleus (STN) of patients with prominent clinical asymmetry.

METHODS

We recorded single unit activity and local field potentials (LFP) of the STN during deep brain stimulation surgeries. Neuronal firing patterns and discharge rate, as well as oscillatory features of both single cells and LFP, were analyzed.

RESULTS

We observed notable differences in proportions of irregular-burst and pause-burst, but not tonic neurons, between the hemispheres. Oscillations of pause-burst neurons correlated significantly with the bradykinesia and rigidity scores of the corresponding hemibody. LFP derived from MA STN featured greater power in 12-15 Hz.

CONCLUSIONS

Our results provide evidence that the increased proportion of units with prolonged pauses may be associated with PD. We also speculate that some of them may gain rhythmicity in the alpha-beta range in relation to hypokinetic symptoms, long-term disease, or both.

SIGNIFICANCE

Our findings highlight the relation between specific oscillatory features of the STN, predominance of subthalamic pause-burst units and PD pathophysiology.

Habenula volume change in Parkinson's disease: A 7T MRI study

OBJECTIVE

Parkinson's disease (PD) is a progressive neurodegenerative disease characterized by motor and early non-motor symptoms. The habenula is implicated in the pathophysiology of depression. This study investigates habenular volume in PD patients without clinical depression to show the changes in PD unrelated to depression.

METHODS

The study used high-resolution 7 Tesla MRI data from the TRACK-PD study involving 104 PD patients and 44 healthy controls (HCs). The habenula was manually segmented, and volumes were measured, considering demographic data and depression scores via the Beck Depression Inventory (BDI).

RESULTS

No significant correlation was found between habenular volume and BDI scores in PD patients or HCs. However, the PD group exhibited a significantly larger mean and right habenular volume than HCs. Although PD patients showed higher BDI scores, indicating more subthreshold depression, these did not correlate with the habenular volume.

CONCLUSION

The results suggest that while the habenula may be involved in the symptoms of PD, its role in depression within this cohort is unclear. The changes might be related to the role of the habenula in motor symptoms. This study provides a new perspective on the role of the habenula in PD, but future research could lead to a greater understanding of the neuroanatomical features of the habenula in PD.

Kinematic network of joint motion provides insight on gait coordination: An observational study on Parkinson's disease

The analysis of gait kinematics requires to encode and collapse multidimensional information from multiple anatomical elements. In this study, we address this issue by analyzing the joints' coordination during gait, borrowing from the framework of network theory. We recruited twenty-three patients with Parkinson's disease and twenty-three matched controls that were recorded during linear gait using a stereophotogrammetric motion analysis system. The three-dimensional angular velocity of the joints was used to build a kinematic network for each participant, and both global (average whole-body synchronization) and nodal (individual joint synchronization, i.e., nodal strength) were extracted. By comparing the two groups, the results showed lower coordination in patients, both at global and nodal levels (neck, shoulders, elbows, and hips). Furthermore, the nodal strength of the left elbow and right hip in the patients, as well as the average joints' nodal strength were significantly correlated with the clinical motor condition and were predictive of it. Our study highlights the importance of integrating whole-body information in kinematic analyses and the advantages of using network theory. Finally, the identification of altered network properties of specific joints, and their relationship with the motor impairment in the patients, suggests a potential clinical relevance for our approach.

Glymphatic function from diffusion-tensor MRI to predict conversion from mild cognitive impairment to dementia in Parkinson's disease

BACKGROUND

Although brain glymphatic dysfunction is a contributing factor to the cognitive deficits in Parkinson's disease (PD), its role in the longitudinal progression of cognitive dysfunction remains unknown.

OBJECTIVE

To investigate the glymphatic function in PD with mild cognitive impairment (MCI) that progresses to dementia (PDD) and to determine its predictive value in identifying individuals at high risk for developing dementia.

METHODS

We included 64 patients with PD meeting criteria for MCI and categorized them as either progressed to PDD (converters) (n = 29) or did not progress to PDD (nonconverters) (n = 35), depending on whether they developed dementia during follow-up. Meanwhile, 35 age- and gender-matched healthy controls (HC) were included. Bilateral diffusion-tensor imaging analysis along the perivascular space (DTI-ALPS) indices and enlarged perivascular spaces (EPVS) volume fraction in bilateral centrum semiovale, basal ganglia (BG), and midbrain were compared among the three groups. Correlations among the DTI-ALPS index and EPVS, as well as cognitive performance were analyzed. Additionally, we investigated the mediation effect of EPVS on DTI-ALPS and cognitive function.

RESULTS

PDD converters had lower cognitive composites scores in the executive domains than did nonconverters (P < 0.001). Besides, PDD converters had a significantly lower DTI-ALPS index in the left hemisphere (P < 0.001) and a larger volume fraction of BG-PVS (P = 0.03) compared to HC and PDD nonconverters. Lower DTI-ALPS index and increased BG-PVS volume fraction were associated with worse performance in the global cognitive performance and executive function. However, there was no significant mediating effect. Receiver operating characteristic analysis revealed that the DTI-ALPS could effectively identify PDD converters with an area under the curve (AUC) of 0.850.

CONCLUSION

The reduction of glymphatic activity, measured by the DTI-ALPS, could potentially be used as a non-invasive indicator in forecasting high risk of dementia conversion before the onset of dementia in PD patients.

Gene expression asymmetry in Parkinson's Disease; variation of CCT and BEX gene expression levels are correlated with hemisphere specific severity

Parkinson's Disease (PD) develops unilaterally, which may be related to brain hemispheric differences in gene expression. Here we measured bulk RNA-seq levels in neuronal nuclei obtained from prefrontal cortex postmortem brain samples from males and females with PD and from healthy controls. Left and right hemispheres from each brain were related the side of symptom onset and compared. We employed two a priori approaches; first we identified genes differentially expressed between PD and controls and between left vs right PD brain hemispheres. Second, we examined the presence of, and correlates to, variable asymmetry seen in candidate PD differentially expressed genes. We found large variation among individuals with PD, and PD stratification by gene expression similarity was required for patterns of genetic asymmetry to emerge. For a subset of PD brains, hemispherical variation of CCT and BEX gene levels correlated with the side of PD symptom onset.

Firing Patterns of Mitral Cells and Their Transformation in the Main Olfactory Bulb

Mitral cells (MCs) in the main olfactory bulb relay odor information to higher-order olfactory centers by encoding the information in the form of action potentials. The firing patterns of these cells are influenced by both their intrinsic properties and their synaptic connections within the neural network. However, reports on MC firing patterns have been inconsistent, and the mechanisms underlying these patterns remain unclear. Using whole-cell patch-clamp recordings in mouse brain slices, we discovered that MCs exhibit two types of integrative behavior: regular/rhythmic firing and bursts of action potentials. These firing patterns could be transformed both spontaneously and chemically. MCs with regular firing maintained their pattern even in the presence of blockers of fast synaptic transmission, indicating this was an intrinsic property. However, regular firing could be transformed into bursting by applying GABAA receptor antagonists to block inhibitory synaptic transmission. Burst firing could be reverted to regular firing by blocking ionotropic glutamate receptors, rather than applying a GABAA receptor agonist, indicating that ionotropic glutamatergic transmission mediated this transformation. Further experiments on long-lasting currents (LLCs), which generated burst firing, also supported this mechanism. In addition, cytoplasmic Ca2+ in MCs was involved in the transformation of firing patterns mediated by glutamatergic transmission. Metabotropic glutamate receptors also played a role in LLCs in MCs. These pieces of evidence indicate that odor information can be encoded on a mitral cell (MC) platform, where it can be relayed to higher-order olfactory centers through intrinsic and dendrodendritic mechanisms in MCs.

Exploring brain asymmetry in early-stage Parkinson's disease through functional and structural MRI

OBJECTIVE

This study explores the correlation between asymmetrical brain functional activity, gray matter asymmetry, and the severity of early-stage Parkinson's disease (PD).

METHODS

Ninety-three early-stage PD patients (ePD, H-Y stages 1-2.5) were recruited, divided into 47 mild (ePD-mild, H-Y stages 1-1.5) and 46 moderate (ePD-moderate, H-Y stages 2-2.5) cases, alongside 43 matched healthy controls (HCs). The study employed the Hoehn and Yahr (H-Y) staging system for disease severity assessment and utilized voxel-mirrored homotopic connectivity (VMHC) for analyzing brain functional activity asymmetry. Asymmetry voxel-based morphometry analysis (VBM) was applied to evaluate gray matter asymmetry.

RESULTS

The study found that, relative to HCs, both PD subgroups demonstrated reduced VMHC values in regions including the amygdala, putamen, inferior and middle temporal gyrus, and cerebellum Crus I. The ePD-moderate group also showed decreased VMHC in additional regions such as the postcentral gyrus, lingual gyrus, and superior frontal gyrus, with notably lower VMHC in the superior frontal gyrus compared to the ePD-mild group. A negative correlation was observed between the mean VMHC values in the superior frontal gyrus and H-Y stages, UPDRS, and UPDRS-III scores. No significant asymmetry in gray matter was detected.

CONCLUSIONS

Asymmetrical brain functional activity is a significant characteristic of PD, which exacerbates as the disease severity increases, resembling the dissemination of Lewy bodies across the PD neurological framework. VMHC emerges as a potent tool for characterizing disease severity in early-stage PD.

Gait asymmetry and symptom laterality in Parkinson's disease: two of a kind?

BACKGROUND

The laterality of motor symptoms is considered a key feature of Parkinson's disease (PD). Here, we investigated whether gait and turning asymmetry coincided with symptom laterality as determined by the MDS-UPRDS part III and whether it was increased compared to healthy controls (HC).

METHODS

We analyzed the asymmetry of gait and turning with and without a cognitive dual task (DT) using motion capture systems and wearable sensors in 97 PD patients mostly from Hoehn & Yahr stage II and III and 36 age-matched HC. We also assessed motor symptom asymmetry using the bilateral sub-items of the MDS-UPDRS-III. Finally, we examined the strength of the association between gait asymmetry and symptom laterality.

RESULTS

Participants with PD had increased gait but not more turning asymmetry compared to HC (p < 0.05). Only 53.7% of patients had a shorter step length on the more affected body side as determined by the MDS-UPDRS-III. Also, 54% took more time and 29% more steps during turns toward the more affected side. The degree of asymmetry in the different domains did not correlate with each other and was not influenced by DT-load.

CONCLUSIONS

We found a striking mismatch between the side and the degree of asymmetry in different motor domains, i.e., in gait, turning, and distal symptom severity in individuals with PD. We speculate that motor execution in different body parts relies on different neural control mechanisms. Our findings warrant further investigation to understand the complexity of gait asymmetry in PD.

Clinical findings of hyperechoic substantia nigra in patients with Parkinson's disease

This study aims to analyse hyperechoic substantia nigra (HSN) characteristics and the correlation of HSN with clinical features and blood biomarkers in patients with Parkinson's disease (PD). Transcranial sonography (TCS) evaluations of the substantia nigra (SN) were performed in 40 healthy controls and 71 patients with PD, including patients with SN hyperechogenicity (SN+) and those with normal SN echogenicity (SN-). Evaluation of motor and non-motor symptoms was assessed by a series of rating scales. The uricase method was used to determine serum uric acid (UA) levels, and enzyme-linked immunosorbent assay (ELISA) was used to measure plasma interleukin (IL)-1β levels. TCS showed 92.50% specificity and 61.97% sensitivity in differentiating PD patients from controls. The area of SN+ contralateral to the side of initial motor symptoms (SNcontra) was larger than that ipsilateral to the side of initial motor symptoms (SNipsi). The PDSN+ group had lower Argentine Hyposmia Rating Scale (AHRS) scores and UA levels than the PDSN- group. Binary logistic regression analysis revealed that AHRS scores and UA levels could be independent predictors for HSN. The larger SN echogenic area (SNL) sizes positively correlated with plasma IL-1β levels in PD patients with SN+. The present study provides further evidence of the potential of SN echogenicity as an imaging biomarker for PD diagnosis. PD patients with HSN have more severe non-motor symptoms of hyposmia. HSN in PD patients is related to the mechanism of abnormal iron metabolism and microglial activation.

The impact of subthalamic deep-brain stimulation in restoring motor symmetry in Parkinson's disease patients: a prospective study

BACKGROUND AND OBJECTIVES

The impact of subthalamic deep-brain stimulation (STN-DBS) on motor asymmetry and its influence on both motor and non-motor outcomes remain unclear. The present study aims at assessing the role of STN-DBS on motor asymmetry and how its modulation translates into benefits in motor function, activities of daily living (ADLs) and quality of life (QoL).

METHODS

Postoperative motor asymmetry has been assessed on the multicentric, prospective Predictive Factors and Subthalamic Stimulation in Parkinson's Disease cohort. Asymmetry was evaluated at both baseline (pre-DBS) and 1 year after STN-DBS. A patient was considered asymmetric when the right-to-left MDS-UPDRS part III difference was ≥ 5. In parallel, analyses have been carried out using the absolute right-to-left difference. The proportion of asymmetric patients at baseline was compared to that in the post-surgery evaluation across different medication/stimulation conditions.

RESULTS

537 PD patients have been included. The proportion of asymmetric patients was significantly reduced after both STN-DBS and medication administration (asymmetric patients: 50% in pre-DBS MedOFF, 35% in MedOFF/StimON, 26% in MedON/StimOFF, and 12% in MedON/StimON state). Older patients at surgery and with higher baseline UPDRS II scores were significantly less likely to benefit from STN-DBS at the level of motor asymmetry. No significant correlation between motor asymmetry and ADLs (UPDRS II) or overall QoL (PDQ-39) score was observed. Asymmetric patients had significantly higher mobility, communication, and daily living PDQ-39 sub-scores.

CONCLUSIONS

Both STN-DBS and levodopa lead to a reduction in motor asymmetry. Motor symmetry is associated with improvements in certain QoL sub-scores.

Consistent abnormal activity in the putamen by dopamine modulation in Parkinson's disease: A resting-state neuroimaging meta-analysis

OBJECTIVE

This study aimed to elucidate brain areas mediated by oral anti-parkinsonian medicine that consistently show abnormal resting-state activation in PD and to reveal their functional connectivity profiles using meta-analytic approaches.

METHODS

Searches of the PubMed, Web of Science databases identified 78 neuroimaging studies including PD OFF state (PD-OFF) versus (vs.) PD ON state (PD-ON) or PD-ON versus healthy controls (HCs) or PD-OFF versus HCs data. Coordinate-based meta-analysis and functional meta-analytic connectivity modeling (MACM) were performed using the activation likelihood estimation algorithm.

RESULTS

Brain activation in PD-OFF vs. PD-ON was significantly changed in the right putamen and left inferior parietal lobule (IPL). Contrast analysis indicated that PD-OFF vs. HCs had more consistent activation in the right paracentral lobule, right middle frontal gyrus, right thalamus, left superior parietal lobule and right putamen, whereas PD-ON vs. HCs elicited more consistent activation in the bilateral middle temporal gyrus, left occipital gyrus, right inferior frontal gyrus and right caudate. MACM revealed coactivation of the right putamen in the direct contrast of PD-OFF vs. PD-ON. Subtraction analysis of significant coactivation clusters for PD-OFF vs. PD-ON with the medium of HCs showed effects in the sensorimotor, top-down control, and visual networks. By overlapping the MACM maps of the two analytical strategies, we demonstrated that the coactivated brain region focused on the right putamen.

CONCLUSIONS

The convergence of local brain regions and co-activation neural networks are involved the putamen, suggesting its potential as a specific imaging biomarker to monitor treatment efficacy.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/PROSPERO/], identifier [CRD CRD42022304150].

Functional activation of dorsal striatum astrocytes improves movement deficits in hemi-parkinsonian mice

Parkinson's disease (PD) is characterized by the degeneration of dopaminergic nigrostriatal inputs, which causes striatal network dysfunction and leads to pronounced motor deficits. Recent evidence highlights astrocytes as a potential local source of striatal network modulation. However, it remains unknown how dopamine loss affects striatal astrocyte activity and whether astrocyte activity regulates behavioral deficits in PD. We addressed these questions by performing astrocyte-specific calcium recordings and manipulations using in vivo fiber photometry and chemogenetics. We find that locomotion elicits astrocyte calcium activity over a slower timescale than neurons. Unilateral dopamine depletion reduced locomotion-related astrocyte responses. Chemogenetic activation facilitated astrocyte activity, and improved asymmetrical motor deficits and open field exploratory behavior in dopamine lesioned mice. Together, our results establish a novel role for functional striatal astrocyte signaling in modulating motor function in PD and highlight non-neuronal targets for potential PD therapeutics.

Distinguishing features of Parkinson's disease fallers based on wireless insole plantar pressure monitoring

Postural instability is one of the most disabling motor signs of Parkinson's disease (PD) and often underlies an increased likelihood of falling and loss of independence. Current clinical assessments of PD-related postural instability are based on a retropulsion test, which introduces human error and only evaluates reactive balance. There is an unmet need for objective, multi-dimensional assessments of postural instability that directly reflect activities of daily living in which individuals may experience postural instability. In this study, we trained machine-learning models on insole plantar pressure data from 111 participants (44 with PD and 67 controls) as they performed simulated static and active postural tasks of activities that often occur during daily living. Models accurately classified PD from young controls (area under the curve (AUC) 0.99+/- 0.00), PD from age-matched controls (AUC 0.99+/- 0.01), and PD fallers from PD non-fallers (AUC 0.91+/- 0.08). Utilizing features from both static and active postural tasks significantly improved classification performances, and all tasks were useful for separating PD from controls; however, tasks with higher postural threats were preferred for separating PD fallers from PD non-fallers.

Dopamine neuron activity encodes the length of upcoming contralateral movement sequences

Dopaminergic neurons (DANs) in the substantia nigra pars compacta (SNc) have been related to movement speed, and loss of these neurons leads to bradykinesia in Parkinson's disease (PD). However, other aspects of movement vigor are also affected in PD; for example, movement sequences are typically shorter. However, the relationship between the activity of DANs and the length of movement sequences is unknown. We imaged activity of SNc DANs in mice trained in a freely moving operant task, which relies on individual forelimb sequences. We uncovered a similar proportion of SNc DANs increasing their activity before either ipsilateral or contralateral sequences. However, the magnitude of this activity was higher for contralateral actions and was related to contralateral but not ipsilateral sequence length. In contrast, the activity of reward-modulated DANs, largely distinct from those modulated by movement, was not lateralized. Finally, unilateral dopamine depletion impaired contralateral, but not ipsilateral, sequence length. These results indicate that movement-initiation DANs encode more than a general motivation signal and invigorate aspects of contralateral movements.

Characterization of graded 6-Hydroxydopamine unilateral lesion in medial forebrain bundle of mice

Parkinson's disease (PD) is the second most common age-related neurodegenerative disease, with a progressive loss of dopaminergic cells and fibers. The purpose of this study was to use different doses of 6-hydroxydopamine (6-OHDA) injection into the medial forebrain bundle (MFB) of mice to mimic the different stages of the disease and to characterize in detail their motor and non-motor behavior, as well as neuropathological features in the nigrostriatal pathway. MFB were injected with 0.5 μg, 1 μg, 2 μg of 6-OHDA using a brain stereotaxic technique. 6-OHDA induced mitochondrial damage dose-dependently, as well as substantia nigra pars compacta (SNpc) tyrosine hydroxylase-positive (TH+) cell loss and striatal TH fiber loss. Activation of astrocytes and microglia in the SNpc and striatum were consistently observed at 7 weeks, suggesting a long-term glial response in the nigrostriatal system. Even with a partial or complete denervation of the nigrostriatal pathway, 6-OHDA did not cause anxiety, although depression-like behavior appeared. Certain gait disturbances were observed in 0.5 μg 6-OHDA lesioned mice, and more extensive in 1 μg group. Despite the loss of more neurons from 2 μg 6-OHDA, there was no further impairment in behaviors compared to 1 μg 6-OHDA. Our data have implications that 1 μg 6-OHDA was necessary and sufficient to induce motor and non-motor symptoms in mice, thus a valuable mouse tool to explore disease progression and new treatment in PD.

Interhemispheric reactivity of the subthalamic nucleus sustains progressive dopamine neuron loss in asymmetrical parkinsonism

Parkinson's disease (PD) is characterized by the progressive and asymmetrical degeneration of the nigrostriatal dopamine neurons and the unilateral presentation of the motor symptoms at onset, contralateral to the most impaired hemisphere. We previously developed a rat PD model that mimics these typical features, based on unilateral injection of a substrate inhibitor of excitatory amino acid transporters, L-trans-pyrrolidine-2,4-dicarboxylate (PDC), in the substantia nigra (SN). Here, we used this progressive model in a multilevel study (behavioral testing, in vivo 1H-magnetic resonance spectroscopy, slice electrophysiology, immunocytochemistry and in situ hybridization) to characterize the functional changes occurring in the cortico-basal ganglia-cortical network in an evolving asymmetrical neurodegeneration context and their possible contribution to the cell death progression. We focused on the corticostriatal input and the subthalamic nucleus (STN), two glutamate components with major implications in PD pathophysiology. In the striatum, glutamate and glutamine levels increased from presymptomatic stages in the PDC-injected hemisphere only, which also showed enhanced glutamatergic transmission and loss of plasticity at corticostriatal synapses assessed at symptomatic stage. Surprisingly, the contralateral STN showed earlier and stronger reactivity than the ipsilateral side (increased intraneuronal cytochrome oxidase subunit I mRNA levels; enhanced glutamate and glutamine concentrations). Moreover, its lesion at early presymptomatic stage halted the ongoing neurodegeneration in the PDC-injected SN and prevented the expression of motor asymmetry. These findings reveal the existence of endogenous interhemispheric processes linking the primary injured SN and the contralateral STN that could sustain progressive dopamine neuron loss, opening new perspectives for disease-modifying treatment of PD.

Imbalanced motivated behaviors according to motor sign asymmetry in drug-naïve Parkinson's disease

Few studies have considered the influence of motor sign asymmetry on motivated behaviors in de novo drug-naïve Parkinson's disease (PD). We tested whether motor sign asymmetry could be associated with different motivated behavior patterns in de novo drug-naïve PD. We performed a cross-sectional study in 128 de novo drug-naïve PD patients and used the Ardouin Scale of Behavior in Parkinson's disease (ASBPD) to assess a set of motivated behaviors. We assessed motor asymmetry based on (i) side of motor onset and (ii) MDS-UPDRS motor score, then we compared right hemibody Parkinson's disease to left hemibody Parkinson's disease. According to the MDS-UPDRS motor score, patients with de novo right hemibody PD had significantly lower frequency of approach behaviors (p = 0.031), including nocturnal hyperactivity (p = 0.040), eating behavior (p = 0.040), creativity (p = 0.040), and excess of motivation (p = 0.017) than patients with de novo left hemibody PD. Patients with de novo left hemibody PD did not significantly differ from those with de novo right hemibody PD regarding avoidance behaviors including apathy, anxiety and depression. Our findings suggest that motor sign asymmetry may be associated with an imbalance between motivated behaviors in de novo drug-naïve Parkinson's disease.

Dysconnectivity of the parafascicular nucleus in Parkinson's disease: A dynamic causal modeling analysis

BACKGROUND

Recent animal model studies have suggested that the parafascicular nucleus has the potential to be an effective deep brain stimulation target for Parkinson's disease. However, our knowledge on the role of the parafascicular nucleus in Parkinson's disease patients remains limited.

OBJECTIVE

We aimed to investigate the functional alterations of the parafascicular nucleus projections in Parkinson's disease patients.

METHODS

We enrolled 72 Parkinson's disease patients and 60 healthy controls, then utilized resting-state functional MRI and spectral dynamic causal modeling to explore the effective connectivity of the bilateral parafascicular nucleus to the dorsal putamen, nucleus accumbens, and subthalamic nucleus. The associations between the effective connectivity of the parafascicular nucleus projections and clinical features were measured with Pearson partial correlations.

RESULTS

Compared with controls, the effective connectivity from the parafascicular nucleus to dorsal putamen was significantly increased, while the connectivity to the nucleus accumbens and subthalamic nucleus was significantly reduced in Parkinson's disease patients. There was a significantly positive correlation between the connectivity of parafascicular nucleus-dorsal putamen projection and motor deficits. The connectivity from the parafascicular nucleus to the subthalamic nucleus was negatively correlated with motor deficits and apathy, while the connectivity from the parafascicular nucleus to the nucleus accumbens was negatively associated with depression.

CONCLUSION

The present study demonstrates that the parafascicular nucleus-related projections are damaged and associated with clinical symptoms of Parkinson's disease. Our findings provide new insights into the impaired basal ganglia-thalamocortical circuits and give support for the parafascicular nucleus as a potential effective neuromodulating target of the disease.

Detecting early-stage Parkinson's disease from gait data

Parkinson's disease is a chronic and progressive neurodegenerative disorder with an estimated 10 million people worldwide living with PD. Since early signs are benign, many patients go undiagnosed until the symptoms get severe and the treatment becomes more difficult. The symptoms start intermittently and gradually become continuous as the disease progresses. In order to detect and classify these minute differences between gaits in early PD patients, we propose to use dynamic time warping (DTW). For a given set of gait data from a patient, the DTW algorithm computes the difference between any two gait cycles in the form of a warping path, which reveals small time differences between gait cycles. Once the time-warping information between all possible pairs of gait cycles is used as the main source of gait features, K-means clustering is used to extract the final features. These final features are fed to a simple logistic regression to easily and successfully detect early PD symptoms, which was reported as challenging using conventional statistical features. In addition, the use of DTW ensures that the obtained results are not affected by the differences in the style and speed of walking of a subject. Our approach is validated for the gait data from 83 subjects at early stages of PD, 10 subjects at moderate stages of PD, and 73 controls using the Leave-One-Out and N-fold cross-validation techniques, with a detection accuracy of over 98%. The high classification accuracy validated from a large data set suggests that these new features from DTW can be effectively used to help clinicians diagnose the disease at the earliest. Even though PD is not completely curable, early diagnosis would help clinicians to start the treatment from the beginning thereby reducing the intensity of symptoms at later stages.

Study of the relationship between onset lateralization and hemispheric white matter asymmetry in Parkinson's disease

BACKGROUND

Parkinson's disease (PD) is characterized by a lateralized onset, but its cause and mechanism are still unclear.

METHODS

Obtaining diffusion tensor imaging (DTI) data from the Parkinson's Progression Markers Initiative (PPMI). Tract-based spatial statistics analysis and region-of-interest-based analysis were performed to evaluate the white matter (WM) asymmetry using original DTI parameters, Z Score normalized parameters, or the asymmetry index (AI). Hierarchical cluster analysis and least absolute shrinkage and selection operator regression were performed to construct predictive models for predicting the PD onset side. DTI data from The Second Affiliated Hospital of Chongqing Medical University were obtained for external validation of the prediction model.

RESULTS

118 PD patients and 69 healthy controls (HC) from PPMI were included. Right-onset PD patients presented more asymmetric areas than left-onset PD patients. The inferior cerebellar peduncle (ICP), superior cerebellar peduncle (SCP), external capsule (EC), cingulate gyrus (CG), superior fronto-occipital fasciculus (SFO), uncinate fasciculus (UNC), and tapetum (TAP) showed significant asymmetry in left-onset and right-onset PD patients. An onset-side-specific pattern of WM alterations exists in PD patients, and a prediction model was constructed. The predicting models based on AI and ΔZ Score presented favorable efficacy in predicting PD onset side by external validation in 26 PD patients and 16 HCs from our hospital.

CONCLUSIONS

Right-onset PD patients may have more severe WM damage than left-onset PD patients. WM asymmetry in ICP, SCP, EC, CG, SFO, UNC, and TAP may predict PD onset side. Imbalances in the WM network may underlie the mechanism of lateralized onset in PD.

Quantitative [123]I-Ioflupane DaTSCAN single-photon computed tomography-computed tomography in Parkinsonism

AIM

[123]I-Ioflupane (DaTSCAN) binds to the presynaptic dopamine transporter (DAT) and with a lower affinity to the serotonin transporter (SERT). We aimed to develop a novel method to quantify absolute uptake in the striatal (predominantly DAT binding) and extra-striatal regions (mainly SERT binding) using single-photon computed tomography-computed tomography (SPECT-CT) DaTSCAN and to improve DaTSCAN image quality.

METHOD

Twenty-six patients with Parkinsonism underwent DaTSCAN SPECT-CT prospectively. The scans were visually analyzed independently by two experienced reporters. Specific binding ratios (SBRs) from Chang attenuation corrected SPECT were obtained using GE DaTQuant. Normalized concentrations and specific uptakes (NSU) from measured attenuation and modelled scatter-corrected SPECT-CT were obtained using HERMES Hybrid Recon and Affinity and modified EARL volumes of interest.

RESULTS

Striatal NSU and SBR positively correlate ( R  = 0.65-0.88, P  = 0.00). SBR, normalized concentrations, and NSU box plots differentiated between scans without evidence of dopaminergic deficit and abnormal scans. Interestingly, body weight inversely correlated with normalized concentrations values in extra-striatal regions [frontal ( R  = 0.81, P  = 0.00); thalamus ( R  = 0.58, P  = 0.00); occipital ( R  = 0.69, P  = 0.00)] and both caudate nuclei [ R  = 0.42, P  = 0.03 (Right), R  = 0.52, P  = 0.01 (Left)]. Both reporters noted improved visual quality of SPECT-CT versus SPECT images for all scans.

CONCLUSION

DaTSCAN SPECT-CT resulted in more accurate quantification, improved image quality, and enabled absolute quantification of extra-striatal regions. More extensive studies are required to establish the full value of absolute quantification for diagnosis and monitoring the progression of neurodegenerative disease, to assess an interplay between DAT and SERT, and to verify whether serotonin and DATs are potentially dysfunctional in obesity.

Exploring Asymmetric Fine Motor Impairment Trends in Early Parkinson's Disease via Keystroke Typing

Background

The nQiMechPD algorithm transforms natural typing data into a numerical index that characterizes motor impairment in people with Parkinson's Disease (PwPD).

Objectives

Use nQiMechPD to compare asymmetrical progression of PD-related impairment in dominant (D-PD) versus non-dominant side onset (ND-PD) de-novo patients.

Methods

Keystroke data were collected from 53 right-handed participants (15 D-PD, 13 ND-PD, 25 controls). We apply linear mixed effects modeling to evaluate participants' right, left, and both hands nQiMechPD relative change by group.

Results

The 6-month nQiMechPD trajectories of right (**P = 0.002) and both (*P = 0.043) hands showed a significant difference in nQiMechPD trends between D-PD and ND-PD participants. Left side trends were not significantly different between these two groups (P = 0.328).

Conclusions

Significant differences between D-PD and ND-PD groups were observed, likely driven by contrasting dominant hand trends. Our findings suggest disease onset side may influence motor impairment progression, medication response, and functional outcomes in PwPD.

Gender may be related to the side of the motor syndrome and cognition in idiopathic Parkinson's disease

BACKGROUND

and Sex and cognitive profile may be related to the laterality of motor symptoms in idiopathic Parkinson's disease.

INTRODUCTION

Parkinson's disease (PD) is well recognised as an inherently asymmetric disease with unilateral onset of motor symptoms. The laterality of motor symptoms may be linked to sex, clinical and demographic variables, and neuropsychological disorders. However, the available data are inconsistent. This study aimed to explore the potential association between the laterality of motor symptoms and clinical and demographic variables and deficits in specific cognitive domains.

MATERIAL AND METHODS

We retrospectively recruited 97 participants with idiopathic PD without dementia; 60 presented motor symptoms on the left side and 37 on the right side. Both groups were comparable in terms of age, age at disease onset, disease duration, and severity of the neurological deficits according to the Unified Parkinson's Disease Rating Scale and the Hoehn and Yahr scale.

RESULTS

Participants with left-side motor symptoms scored lower on the Schwab and England Activities of Daily Living scale. Our sample included more men than women (67% vs. 33%). Both sexes were not equally represented in the 2 groups: there were significantly more men than women in the group of patients with left-side motor symptoms (77% vs. 23%), whereas the percentages of men and women in the group of patients with right-side motor symptoms were similar (51% vs. 49%). Both groups performed similarly in all neuropsychological tasks, but women, independently of laterality, performed better than men in the naming task.

CONCLUSION

We found a clear prevalence of men in the group of patients with left-side motor symptoms; this group also scored lower on the Schwab and England Scale. Female sex was predictive of better performance in the naming task. Sex should always be considered in disorders that cause asymmetric involvement of the brain, such as PD.

The brain-first vs. body-first model of Parkinson's disease with comparison to alternative models

The ultimate origin of Lewy body disorders, including Parkinson's disease (PD) and Dementia with Lewy bodies (DLB), is still incompletely understood. Although a large number of pathogenic mechanisms have been implicated, accumulating evidence support that aggregation and neuron-to-neuron propagation of alpha-synuclein may be the core feature of these disorders. The synuclein, origin, and connectome (SOC) disease model of Lewy body disorders was recently introduced. This model is based on the hypothesis that in the majority of patients, the first alpha-synuclein pathology arises in single location and spreads from there. The most common origin sites are the enteric nervous system and the olfactory system. The SOC model predicts that gut-first pathology leads to a clinical body-first subtype characterized by prodromal autonomic symptoms and REM sleep behavior disorder. In contrast, olfactory-first pathology leads to a brain-first subtype with fewer non-motor symptoms before diagnosis. The SOC model further predicts that body-first patients are older, more commonly develop symmetric dopaminergic degeneration, and are at increased risk of dementia-compared to brain-first patients. In this review, the SOC model is explained and compared to alternative models of the pathogenesis of Lewy body disorders, including the Braak staging system, and the Unified Staging System for Lewy Body Disorders. Postmortem evidence from brain banks and clinical imaging data of dopaminergic and cardiac sympathetic loss is reviewed. It is concluded that these datasets seem to be more compatible with the SOC model than with those alternative disease models of Lewy body disorders.

In vivo18F-DOPA PET imaging identifies a dopaminergic deficit in a rat model with a G51D α-synuclein mutation

Parkinson's disease (PD) is a neurodegenerative condition with several major hallmarks, including loss of substantia nigra neurons, reduction in striatal dopaminergic function, and formation of α-synuclein-rich Lewy bodies. Mutations in SNCA, encoding for α-synuclein, are a known cause of familial PD, and the G51D mutation causes a particularly aggressive form of the condition. CRISPR/Cas9 technology was used to introduce the G51D mutation into the endogenous rat SNCA gene. SNCA^G51D/+ and SNCA^G51D/G51D rats were born in Mendelian ratios and did not exhibit any severe behavourial defects. L-3,4-dihydroxy-6-¹⁸F-fluorophenylalanine (¹⁸F-DOPA) positron emission tomography (PET) imaging was used to investigate this novel rat model. Wild-type (WT), SNCA^G51D/+ and SNCA^G51D/G51D rats were characterized over the course of ageing (5, 11, and 16 months old) using ¹⁸F-DOPA PET imaging and kinetic modelling. We measured the influx rate constant (K_i) and effective distribution volume ratio (EDVR) of ¹⁸F-DOPA in the striatum relative to the cerebellum in WT, SNCA^G51D/+ and SNCA^G51D/G51D rats. A significant reduction in EDVR was observed in SNCA^G51D/G51D rats at 16 months of age indicative of increased dopamine turnover. Furthermore, we observed a significant asymmetry in EDVR between the left and right striatum in aged SNCA^G51D/G51D rats. The increased and asymmetric dopamine turnover observed in the striatum of aged SNCA^G51D/G51D rats reflects one aspect of prodromal PD, and suggests the presence of compensatory mechanisms. SNCA^G51D rats represent a novel genetic model of PD, and kinetic modelling of ¹⁸F-DOPA PET data has identified a highly relevant early disease phenotype.

Asymmetric Presynaptic Depletion of Dopamine Neurons in a Drosophila Model of Parkinson's Disease

Parkinson's disease (PD) often displays a strong unilateral predominance in arising symptoms. PD is correlated with dopamine neuron (DAN) degeneration in the substantia nigra pars compacta (SNPC), and in many patients, DANs appear to be affected more severely on one hemisphere than the other. The reason for this asymmetric onset is far from being understood. Drosophila melanogaster has proven its merit to model molecular and cellular aspects of the development of PD. However, the cellular hallmark of the asymmetric degeneration of DANs in PD has not yet been described in Drosophila. We ectopically express human α-synuclein (hα-syn) together with presynaptically targeted syt::HA in single DANs that innervate the Antler (ATL), a symmetric neuropil located in the dorsomedial protocerebrum. We find that expression of hα-syn in DANs innervating the ATL yields asymmetric depletion of synaptic connectivity. Our study represents the first example of unilateral predominance in an invertebrate model of PD and will pave the way to the investigation of unilateral predominance in the development of neurodegenerative diseases in the genetically versatile invertebrate model Drosophila.

An Explainable Spatial-Temporal Graphical Convolutional Network to Score Freezing of Gait in Parkinsonian Patients

Freezing of gait (FOG) is a poorly understood heterogeneous gait disorder seen in patients with parkinsonism which contributes to significant morbidity and social isolation. FOG is currently measured with scales that are typically performed by movement disorders specialists (i.e., MDS-UPDRS), or through patient completed questionnaires (N-FOG-Q) both of which are inadequate in addressing the heterogeneous nature of the disorder and are unsuitable for use in clinical trials The purpose of this study was to devise a method to measure FOG objectively, hence improving our ability to identify it and accurately evaluate new therapies. A major innovation of our study is that it is the first study of its kind that uses the largest sample size (>30 h, N = 57) in order to apply explainable, multi-task deep learning models for quantifying FOG over the course of the medication cycle and at varying levels of parkinsonism severity. We trained interpretable deep learning models with multi-task learning to simultaneously score FOG (cross-validated F1 score 97.6%), identify medication state (OFF vs. ON levodopa; cross-validated F1 score 96.8%), and measure total PD severity (MDS-UPDRS-III score prediction error ≤ 2.7 points) using kinematic data of a well-characterized sample of N = 57 patients during levodopa challenge tests. The proposed model was able to explain how kinematic movements are associated with each FOG severity level that were highly consistent with the features, in which movement disorders specialists are trained to identify as characteristics of freezing. Overall, we demonstrate that deep learning models' capability to capture complex movement patterns in kinematic data can automatically and objectively score FOG with high accuracy. These models have the potential to discover novel kinematic biomarkers for FOG that can be used for hypothesis generation and potentially as clinical trial outcome measures.

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.

An explainable spatial-temporal graphical convolutional network to score freezing of gait in parkinsonian patients

Freezing of gait (FOG) is a poorly understood heterogeneous gait disorder seen in patients with parkinsonism which contributes to significant morbidity and social isolation. FOG is currently measured with scales that are typically performed by movement disorders specialists (ie. MDS-UPDRS), or through patient completed questionnaires (N-FOG-Q) both of which are inadequate in addressing the heterogeneous nature of the disorder and are unsuitable for use in clinical trials The purpose of this study was to devise a method to measure FOG objectively, hence improving our ability to identify it and accurately evaluate new therapies. We trained interpretable deep learning models with multi-task learning to simultaneously score FOG (cross-validated F1 score 97.6%), identify medication state (OFF vs. ON levodopa; cross-validated F1 score 96.8%), and measure total PD severity (MDS-UPDRS-III score prediction error ≤ 2.7 points) using kinematic data of a well-characterized sample of N=57 patients during levodopa challenge tests. The proposed model was able to identify kinematic features associated with each FOG severity level that were highly consistent with the features that movement disorders specialists are trained to identify as characteristic of freezing. In this work, we demonstrate that deep learning models' capability to capture complex movement patterns in kinematic data can automatically and objectively score FOG with high accuracy. These models have the potential to discover novel kinematic biomarkers for FOG that can be used for hypothesis generation and potentially as clinical trial outcome measures.

Evaluating Note Frequency and Velocity During Improvised Active Music Therapy in Clients With Parkinson's Disease

The purpose of this article was to report on the findings of the note frequency and velocity measures during Improvised Active Music Therapy (IAMT) sessions with individuals with Parkinson's disease (PD). In this single-subject multiple baseline design across subjects, the article reports the note frequency (note count) and velocity of movement (mean note velocity) played by three right-handed participants while playing uninterrupted improvised music on a simplified electronic drum-set. During baseline, the music therapist played rhythmic accompaniment on guitar using a low-moderate density of syncopation. During treatment, the Music Therapist introduced rhythms with a moderate-high density of syncopation. The music content of the sessions was transformed into digital music using a musical instrument digital interface. Results of this study indicated that all participants exhibited an increase in note count during baseline until reaching a plateau at treatment condition and were found to be significantly positively correlated with the Music Therapist's note count. All participants played more notes with upper extremity (UE) across conditions than with lower extremity. All participants also scored similar total mean velocity across conditions. Two participants demonstrated higher mean note velocity with UE than right foot, whereas the other participant did not demonstrate this difference. Two participants also exhibited greater mean note velocity variability with left foot within and across conditions. More research is required to identify commonalities in note count and mean note velocity measures in individuals with PD during IAMT sessions.

Isolating the speed factor is crucial in gait analysis for Parkinson's disease

Introduction

Parkinson's disease (PD) is characterized by an alteration of the walking gait, frequently including a slower self-selected walking speed (SSWS). Although the reduction of walking speed is inherent to people with PD, such speed reduction also represents a potential confounding factor that might partly explain the observed gait differences between PD and control participants.

Methods

In this study, each participant walked along a 25 m level corridor during which vertical ground reaction force signals were recorded using shoes equipped with eight pressure sensors. Vertical ground reaction force signals (using statistical parametric mapping) and temporal and kinetic variables as well as their related variability and asymmetry (using Student's t-test) were compared between PD (n = 54) and walking-speed-matched control subjects (n = 39).

Results

Statistical parametric mapping did not yield significant differences between PD and control groups for the vertical ground reaction force signal along the walking stance phase. Stride time and single support time (equivalent to swing time) were shorter and peak vertical ground reaction force was larger in PD patients compared to controls (p ≤ 0.05). However, the single support time was no longer different between people with PD and healthy subjects when expressed relatively to stride time (p = 0.07). While single support, double support, and stance times were significantly more variable and asymmetric for PD than for the control group (p ≤ 0.05), stride time was similar (p ≥ 0.07).

Discussion

These results indicate that at matched SSWS, PD patients adopt a higher cadence than control participants. Moreover, the temporal subdivision of the walking gait of people with PD is similar to healthy individuals but the coordination during the double support phase is different. Hence, this study indicates that isolating the speed factor is crucial in gait analysis for PD.

Keystroke-Dynamics for Parkinson's Disease Signs Detection in an At-Home Uncontrolled Population: A New Benchmark and Method

Parkinson's disease (PD) is the second most prevalent neurodegenerative disease disorder in the world. A prompt diagnosis would enable clinical trials for disease-modifying neuroprotective therapies. Recent research efforts have unveiled imaging and blood markers that have the potential to be used to identify PD patients promptly, however, the idiopathic nature of PD makes these tests very hard to scale to the general population. To this end, we need an easily deployable tool that would enable screening for PD signs in the general population. In this work, we propose a new set of features based on keystroke dynamics, i.e., the time required to press and release keyboard keys during typing, and used to detect PD in an ecologically valid data acquisition setup at the subject's homes, without requiring any pre-defined task. We compare and contrast existing models presented in the literature and present a new model that combines a new type of keystroke dynamics signal representation using hold time and flight time series as a function of key types and asymmetry in the time series using a convolutional neural network. We show how this model achieves an Area Under the Receiving Operating Characteristic curve ranging from 0.80 to 0.83 on a dataset of subjects who actively interacted with their computers for at least 5 months and positively compares against other state-of-the-art approaches previously tested on keystroke dynamics data acquired with mechanical keyboards.

Association Between White Matter Networks and the Pattern of Striatal Dopamine Depletion in Patients With Parkinson Disease

OBJECTIVES

Individual variability in nigrostriatal dopaminergic denervation is an important factor underlying clinical heterogeneity in Parkinson disease (PD). This study aimed to explore whether the pattern of striatal dopamine depletion was associated with white matter (WM) networks in PD.

METHODS

A total of 240 newly diagnosed patients with PD who underwent 18F-FP-CIT PET scans and brain diffusion tensor imaging at initial assessment were enrolled in this study. We measured 18F-FP-CIT tracer uptake as an indirect marker for striatal dopamine depletion. Factor analysis-derived striatal dopamine loss patterns were estimated in each patient to calculate the composite scores of 4 striatal subregion factors (caudate, more-affected and less-affected sensorimotor striata, and anterior putamen) based on the availability of striatal dopamine transporter. The WM structural networks that were correlated with the composite scores of each striatal subregion factor were identified using a network-based statistical analysis.

RESULTS

A higher composite score of caudate (i.e., relatively preserved dopaminergic innervation in the caudate) was associated with a strong structural connectivity in a single subnetwork comprising the left caudate and left frontal gyri. Selective dopamine loss in the caudate was associated with strong connectivity in the structural subnetwork whose hub nodes were bilateral thalami and left insula, which were connected to the anterior cingulum. However, no subnetworks were correlated with the composite scores of other striatal subregion factors. The connectivity strength of the network with a positive correlation with the composite score of caudate affected the frontal/executive function either directly or indirectly through the mediation of dopamine depletion in the caudate.

CONCLUSIONS

Our findings indicate that different patterns of striatal dopamine depletion are closely associated with WM structural alterations, which may contribute to heterogeneous cognitive profiles in individuals with PD.

Effective R2 relaxation rate, derived from dual-contrast fast-spin-echo MRI, enables detection of hemisphere differences in iron level and dopamine function in Parkinson's disease and healthy individuals

BACKGROUND

Clinical estimates of brain iron concentration are achievable with quantitative transverse relaxation rate R₂, via time-consuming multiple spin-echo (SE) sequences. The objective of this study was to investigate whether quantitative iron-sensitive information may be derived from 3.0 T dual-contrast fast-spin-echo (FSE) sequences (typically employed in anatomical non-quantitative evaluations), as a routinely-collected alternative to evaluate iron levels in healthy (HC) and Parkinson's disease (PD) brains.

NEW METHOD

MRI 3.0 T FSE data from the Parkinson's Progression Markers Initiative (PPMI) (12 PD, 12 age- and gender-matched HC subjects) were cross-sectionally and longitudinally evaluated. A new measure, 'effective R₂', was calculated for bilateral subcortical grey matter (caudate nucleus, putamen, globus pallidus, red nucleus, substantia nigra). Linear regression analysis was performed to correlate 'effective R₂' with models of age-dependent brain iron concentration and striatal dopamine transporter (DaT) receptor binding ratio.

RESULTS

Effective R₂ was strongly correlated with estimated brain iron concentration. In PD, putaminal effective R₂ difference was observed between the hemispheres contra-/ipsi-lateral to the predominantly symptomatic side at onset. This hemispheric difference was correlated with the putaminal DaT binding ratios in PD.

COMPARISON WITH EXISTING METHOD(S)

Effective R₂, derived from rapid dual-contrast FSE sequences, showed viability as an alternative to R₂ from SE sequences. Linear correlation of effective R₂ with estimated iron concentration was comparable to documented iron-dependent R₂. The effective R₂ correlation coefficient was consistent with theoretical R₂ iron-dependence at 3.0 T.

CONCLUSIONS

Effective R₂ has clinical potential as a fast quantitative method, as an alternative to R₂, to aid evaluation of brain iron levels and DaT function.

Association of Total Bilirubin with Motor Signs in Early Parkinson's Disease in LRRK2 Variant Carriers

Oxidative stress is considered a possible mechanism in Parkinson's disease (PD) progression. Bilirubin has been recognized as a powerful antioxidant that increases due to heme-oxygenase activity. We aimed to investigate the association of total bilirubin (TB) with motor signs and asymmetry in different stages of early PD. A case-control study was performed to investigate the differences in TB levels in PD patients and healthy controls (HC) both carrying LRRK2 variants. We compared TB levels in HC and Hoehn and Yahr (HY) I and II cohorts separately, followed by multiple linear regression analysis to evaluate the association between TB and motor dysfunction in each stage. We used Movement Disorder Society-Sponsored Revision of the Unified Parkinson's Disease Rating Scale (UPDRS) part III scores and asymmetry scores to address motor disability. Asymmetry scores were calculated from the corresponding UPDRS III tasks. TB was significantly increased in HY II compared to HC (P < 0.001). Positive correlations with TB were found for UPDRS III total score (ρ = 0.303, P = 0.034) and asymmetry score (ρ = 0.418, P = 0.003) in HY I. Multiple linear regression found a significant relationship between TB and asymmetry scores in HY I (R² = 0.261, P = 0.037), but no relationship was achieved with UPDRS III total scores. Increased TB serves as an important diagnostic marker in earlier stages of PD. A significant relationship was found between TB and motor asymmetry in HY I patients. According to our findings, bilirubin mainly exhibits its protective effects in HY I population.

Topological patterns of motor networks in Parkinson’s disease with different sides of onset: A resting-state-informed structural connectome study

Parkinson’s disease (PD) has a characteristically unilateral pattern of symptoms at onset and in the early stages; this lateralization is considered a diagnostically important diagnosis feature. We aimed to compare the graph-theoretical properties of whole-brain networks generated by using resting-state functional MRI (rs-fMRI), diffusion tensor imaging (DTI), and the resting-state-informed structural connectome (rsSC) in patients with left-onset PD (LPD), right-onset PD (RPD), and healthy controls (HCs). We recruited 26 patients with PD (13 with LPD and 13 with RPD) as well as 13 age- and sex-matched HCs. Rs-fMRI and DTI were performed in all subjects. Graph-theoretical analysis was used to calculate the local and global efficiency of a whole-brain network generated by rs-fMRI, DTI, and rsSC. Two-sample t-tests and Pearson correlation analysis were conducted. Significantly decreased global and local efficiency were revealed specifically in LPD patients compared with HCs when the rsSC network was used; no significant intergroup difference was found by using rs-fMRI or DTI alone. For rsSC network analysis, multiple network metrics were found to be abnormal in LPD. The degree centrality of the left precuneus was significantly correlated with the Unified Parkinson’s Disease Rating Scale (UPDRS) score and disease duration (p = 0.030, r = 0.599; p = 0.037, r = 0.582). The topological properties of motor-related brain networks can differentiate LPD and RPD. Nodal metrics may serve as important structural features for PD diagnosis and monitoring of disease progression. Collectively, these findings may provide neurobiological insights into the lateralization of PD onset.

Voice Alterations, Dysarthria, and Respiratory Derangements in Patients With Parkinson's Disease

PURPOSE

Almost 90% of people with Parkinson's disease (PD) develop voice and speech disorders during the course of the disease. Ventilatory dysfunction is one of the main causes. We aimed to evaluate relationships between respiratory impairments and speech/voice changes in PD.

METHOD

At Day 15 from admission, in consecutive clinically stable PD patients in a neurorehabilitation unit, we collected clinical data as follows: comorbidities, PD severity, motor function and balance, respiratory function at rest (including muscle strength and cough ability), during exercise-induced desaturation and at night, voice function (Voice Handicap Index [VHI] and acoustic analysis [Praat]), speech disorders (Robertson Dysarthria Profile [RDP]), and postural abnormalities. Based on an arbitrary RDP cutoff, two groups with different dysarthria degree were identified-moderate-severe versus no-mild dysarthria-and compared.

RESULTS

Of 55 patients analyzed (median value Unified Parkinson's Disease Rating Scale Part II 9 and Part III 17), we found significant impairments in inspiratory and expiratory muscle pressure (&gt; 90%, both), exercise tolerance at 6-min walking distance (96%), nocturnal (12.7%) and exercise-induced (21.8%) desaturation, VHI (34%), and Praat Shimmer% (89%). Patients with moderate-severe dysarthria (16% of total sample) had more comorbidities/disabilities and worse respiratory pattern and postural abnormalities (camptocormia) than those with no-mild dysarthria. Moreover, the risk of presenting nocturnal desaturation, reduced peak expiratory flow, and cough ability was about 11, 13, and 8 times higher in the moderate-severe group.

CONCLUSIONS

Dysarthria and respiratory dysfunction are closely associated in PD patients, particularly nocturnal desaturation and reduced cough ability. In addition, postural condition could be at the base of both respiratory and voice impairments.

SUPPLEMENTAL MATERIAL

https://doi.org/10.23641/asha.21210944.

Contribution of cognitive and bodily navigation cues to egocentric and allocentric spatial memory in hallucinations due to Parkinson's disease: A case report

Parkinson's disease (PD) manifestations can include visual hallucinations and illusions. Recent findings suggest that the coherent integration of bodily information within an egocentric representation could play a crucial role in these phenomena. Egocentric processing is a key aspect of spatial navigation and is supported by the striatum. Due to the deterioration of the striatal and motor systems, PD mainly impairs the egocentric rather than the allocentric spatial frame of reference. However, it is still unclear the interplay between spatial cognition and PD hallucinations and how different navigation mechanisms can influence such spatial frames of reference. We report the case of A.A., a patient that suffers from PD with frequent episodes of visual hallucinations and illusions. We used a virtual reality (VR) navigation task to assess egocentric and allocentric spatial memory under five navigation conditions (passive, immersive, map, path decision, and attentive cues) in A.A. and a PD control group without psychosis. In general, A.A. exhibited a statistically significant classical dissociation between the egocentric and allocentric performance with a greater deficit for the former. In particular, the dissociation was statistically significant in the "passive" and "attentive cues" conditions. Interestingly in the "immersive" condition, the dissociation was not significant and, in contrast to the other conditions, trends showed better performance for egocentric than allocentric memory. Within the theories of embodiment, we suggest that body-based information, as assessed with VR navigation tasks, could play an important role in PD hallucinations. In addition, the possible neural underpinnings and the usefulness of VR are discussed.

Association Between Asymmetry of Substantia Nigra Hyperechogenicity and Clinical Characteristics in Different Parkinson Disease Subtypes: A 5-Year Follow-up Study

Our study focused on three aspects to determine whether bilateral substantia nigra hyperechogenicity (SN+) is asymmetrical, whether the asymmetry of SN+ is related to the clinical features and whether there is variation in SN+ asymmetry during the progression of Parkinson disease (PD). This follow-up study included 234 patients with PD, who were divided into tremor PD (TD, n = 67) and non-tremor PD (NTD, n = 167) groups based on the Unified Parkinson's Disease Rating Scale (UPDRS) Part III. All participants underwent transcranial sonography (TCS) and clinical assessment. In both the TD and NTD groups, the initial SN+ was larger than the non-initial SN+. The initial SN+ was associated with Hoehn and Yahr (H&amp;Y) stage, PD duration and initial UPDRS III, and the SN+ asymmetry index was associated with motor asymmetry index in the TD group. In the NTD group, the initial SN+ was associated only with initial UPDRS III. After a 5-year follow-up, the area of SN+ on both sides was gradually inclining to symmetry in the NTD group. Our study determined that SN+ asymmetry could reflect asymmetrical characteristics of PD. Furthermore, we inferred that the dynamic change in SN+ asymmetry might reflect a dynamic change in motor asymmetry in the NTD group.

The kinectome: A comprehensive kinematic map of human motion in health and disease

Human voluntary movement stems from the coordinated activations in space and time of many musculoskeletal segments. However, the current methodological approaches to study human movement are still limited to the evaluation of the synergies among a few body elements. Network science can be a useful approach to describe movement as a whole and to extract features that are relevant to understanding both its complex physiology and the pathophysiology of movement disorders. Here, we propose to represent human movement as a network (that we named the kinectome), where nodes represent body points, and edges are defined as the correlations of the accelerations between each pair of them. We applied this framework to healthy individuals and patients with Parkinson's disease, observing that the patients' kinectomes display less symmetrical patterns as compared to healthy controls. Furthermore, we used the kinectomes to successfully identify both healthy and diseased subjects using short gait recordings. Finally, we highlighted topological features that predict the individual clinical impairment in patients. Our results define a novel approach to study human movement. While deceptively simple, this approach is well-grounded, and represents a powerful tool that may be applied to a wide spectrum of frameworks.