Levodopa response differs in Parkinson's motor subtypes: A task-based effective connectivity study

Exploring Brain Effective Connectivity Networks Through Spatiotemporal Graph Convolutional Models

Learning brain effective connectivity networks (ECN) from functional magnetic resonance imaging (fMRI) data has gained much attention in recent years. With the successful applications of deep learning in numerous fields, several brain ECN learning methods based on deep learning have been reported in the literature. However, current methods ignore the deep temporal features of fMRI data and fail to fully employ the spatial topological relationship between brain regions. In this article, we propose a novel method for learning brain ECN based on spatiotemporal graph convolutional models (STGCM), named STGCMEC, in which we first adopt the temporal convolutional network to extract the deep temporal features of fMRI data and utilize the graph convolutional network to update the spatial features of each brain region by aggregating information from neighborhoods, which makes the features of brain regions more discriminative. Then, based on such features of brain regions, we design a joint loss function to guide STGCMEC to learn the brain ECN, which includes a task prediction loss and a graph regularization loss. The experimental results on a simulated dataset and a real Alzheimer's disease neuroimaging initiative (ADNI) dataset show that the proposed STGCMEC is able to better learn brain ECN compared with some state-of-the-art methods.

Midbrain dopaminergic degeneration differentially modulates primary motor cortex activity and motor behavior in hemi-parkinsonian rats

Parkinson's disease (PD) is marked by degeneration in the nigrostriatal dopaminergic pathway, affecting motor control via complex changes in the cortico-basal ganglia-thalamic motor network, including the primary motor cortex (M1). The modulation of M1 neuronal activity by dopaminergic inputs, particularly from the ventral tegmental area (VTA) and substantia nigra pars compacta (SNc), plays a crucial role in PD pathophysiology. This study investigates how nigrostriatal dopaminergic degeneration influences M1 neuronal activity in rats using in vivo calcium imaging. Histological analysis confirmed dopaminergic lesion severity, with high lesion level rats showing significant motor deficits. Levodopa treatment improved fine motor abilities, particularly in high lesion level rats. Analysis of M1 calcium signals based on dopaminergic lesion severity revealed distinct M1 activity patterns. Animals with low dopaminergic lesion showed increased calcium events, while high lesion level rats exhibited decreased activity, partially restored by levodopa. These findings suggest that M1 activity is more sensitive to transient fluctuations in dopaminergic transmission, rather than to chronic high or low dopaminergic signaling. This study underscores the complex interplay between dopaminergic signaling and M1 neuronal activity in PD symptoms development. Further research integrating behavioral and calcium imaging data can elucidate mechanisms underlying motor deficits and therapeutic responses in PD.

Free water imaging unravels unique patterns of longitudinal structural brain changes in Parkinson's disease subtypes

Background

Research shows that individuals with Parkinson's disease (PD) who have a postural instability and gait difficulties (PIGD) subtype have a faster disease progression compared to those with a tremor dominant (TD) subtype. Nevertheless, our understanding of the structural brain changes contributing to these clinical differences remains limited, primarily because many brain imaging techniques are only capable of detecting changes in the later stages of the disease.

Objective

Free water (FW) has emerged as a robust progression marker in several studies, showing increased values in the posterior substantia nigra that predict symptom worsening. Here, we examined longitudinal FW changes in TD and PIGD across multiple brain regions.

Methods

Participants were TD and PIGD enrolled in the Parkinson's Progression Marker Initiative (PPMI) study who underwent diffusion MRI at baseline and 2 years later. FW changes were quantified for regions of interest (ROI) within the basal ganglia, thalamus, brainstem, and cerebellum.

Results

Baseline FW in all ROIs did not differ between groups. Over 2 years, PIGD had a greater percentage increase in FW in the putamen, globus pallidus, and cerebellar lobule V. A logistic regression model incorporating percent change in motor scores and FW in these brain regions achieved 91.4% accuracy in discriminating TD and PIGD, surpassing models based solely on clinical measures (74.3%) or imaging (76.1%).

Conclusion

The results further suggest the use of FW to study disease progression in PD and provide insight into the differential course of brain changes in early-stage PD subtypes.

Distinct changes in global brain synchronization in different motor subtypes of Parkinson's disease

This study investigated alterations in degree centrality (DC) in different motor subtypes of Parkinson's disease (PD) and analyzed its clinical significance during disease occurrence. A total of 146 subjects were recruited in the study, including 90 patients with PD [51 and 39 with tremor dominant (TD) and akinetic-rigid dominant (ARD) disease, respectively] and 56 healthy controls (HCs). The resting-state functional magnetic resonance imaging data of all the subjects were obtained by 3.0 T magnetic resonance scans. The DC values, an indicator of whole brain synchronization, were calculated and compared among the TD, ARD, and HC groups. Disparities in DC values among the three groups were evaluated by analysis of variance and post hoc two-sample t-tests. Correlation between brain regions with DC differences and clinical variables were performed using partial correlation analysis after controlling for age, gender, and disease duration. Compared to the HCs, both TD and ARD groups demonstrated increased DC values bilaterally in the cerebellum; DC values were decreased in the left putamen and paracentral lobule in the TD group and in the left anterior cingulate gyrus and right supplementary motor area in the ARD group. Compared to the ARD group, the TD group showed decreased DC values in bilateral cerebellar hemispheres and increased DC values in the left anterior cingulate gyrus and right supplementary motor area. The DC of the whole brain showed inconsistencies and shared neural bases among patients with the two subtypes of PD. The differences between brain regions with abnormal DC values may be closely related to different clinical presentations of the two motor subtypes. Our findings provide new insights into the clinical heterogeneity of PD with respect to different motor subtypes.

Resting-state functional magnetic resonance imaging study comparing tremor-dominant and postural instability/gait difficulty subtypes of Parkinson's disease

PURPOSE

The symptom-specific intrinsic neural mechanisms underlying Parkinson's disease (PD) subtypes (tremor dominant [TD] and postural instability gait difficulty [PIGD]) remain unclarified. We examined spontaneous brain activity patterns in TD and PIGD.

MATERIAL AND METHODS

We included 49 patients with PD (21 with TD/28 with PIGD) and 32 healthy controls (HCs) in this study. We conducted analysis of variance and post-hoc analyses of the amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) values of the three groups, with age, sex, and gray matter volume as covariates, and a relationship analysis of the ALFF and ReHo values with clinical variables.

RESULTS

In comparison with HCs, PIGD PD patients had increased ALFF values in the right middle occipital gyrus and left superior occipital gyrus and decreased values primarily in the bilateral inferior frontal gyrus (triangular part). TD PD patients had lower ALFF values in the right inferior frontal gyrus (triangular part) and left insula. In comparison to TD PD patients, PIGD PD patients had higher ALFF values in the left middle occipital gyrus and left superior occipital gyrus. In contrast to HCs, TD PD patients demonstrated a reduction of ReHo values in the left middle temporal gyrus, and PIGD patients showed a decrease of ReHo values in the left inferior temporal gyrus.

CONCLUSION

ALFF values increased in the occipital gyrus of the PIGD PD patients, thus providing evidence of a compensatory mechanism of altered motor function in comparison with the TD PD patients.

Real-World Driving Data Indexes Dopaminergic Treatment Effects in Parkinson's Disease

Background

Driving is a complex, everyday task that impacts patient agency, safety, mobility, social connections, and quality of life. Digital tools can provide comprehensive real-world (RW) data on driver behavior in patients with Parkinson's disease (PD), providing critical data on disease status and treatment efficacy in the patient's own environment.

Objective

This pilot study examined the use of driving data as a RW digital biomarker of PD symptom severity and dopaminergic therapy effectiveness.

Methods

Naturalistic driving data (3974 drives) were collected for 1 month from 30 idiopathic PD drivers treated with dopaminergic medications. Prescriptions data were used to calculate levodopa equivalent daily dose (LEDD). The association between LEDD and driver mobility (number of drives) was assessed across PD severity, measured by the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS).

Results

PD drivers with worse motor symptoms based on self-report (Part II: P = 0.02) and clinical examination (Part III: P < 0.001) showed greater decrements in driver mobility. LEDD levels >400 mg/day were associated with higher driver mobility than those with worse PD symptoms (Part I: P = 0.02, Part II: P < 0.001, Part III: P < 0.001).

Conclusions

Results suggest that comprehensive RW driving data on PD patients may index disease status and treatment effectiveness to improve patient symptoms, safety, mobility, and independence. Higher dopaminergic treatment may enhance safe driver mobility in PD patients with worse symptom severity.

Chaudhuri's Dashboard of Vitals in Parkinson's syndrome: an unmet need underpinned by real life clinical tests

We have recently published the notion of the "vitals" of Parkinson's, a conglomeration of signs and symptoms, largely nonmotor, that must not be missed and yet often not considered in neurological consultations, with considerable societal and personal detrimental consequences. This "dashboard," termed the Chaudhuri's vitals of Parkinson's, are summarized as 5 key vital symptoms or signs and comprise of (a) motor, (b) nonmotor, (c) visual, gut, and oral health, (d) bone health and falls, and finally (e) comorbidities, comedication, and dopamine agonist side effects, such as impulse control disorders. Additionally, not addressing the vitals also may reflect inadequate management strategies, leading to worsening quality of life and diminished wellness, a new concept for people with Parkinson's. In this paper, we discuss possible, simple to use, and clinically relevant tests that can be used to monitor the status of these vitals, so that these can be incorporated into clinical practice. We also use the term Parkinson's syndrome to describe Parkinson's disease, as the term "disease" is now abandoned in many countries, such as the U.K., reflecting the heterogeneity of Parkinson's, which is now considered by many as a syndrome.

Postural control of Parkinson's disease: A visualized analysis based on Citespace knowledge graph

Postural control impairment is one of the primary motor symptoms in patients with Parkinson's disease, leading to an increased risk of falling. Several studies have been conducted on postural control disorders in Parkinson's disease patients, but no relevant bibliometric analysis has been found. In this paper, the Web of Science Core Collection database was searched for 1,295 relevant papers on postural control in Parkinson's disease patients from December 2011 to December 2021. Based on the Citespace knowledge graph, these relevant papers over the last decade were analyzed from the perspectives of annual publication volume, countries and institutes cooperation, authors cooperation, dual-map overlay of journals, co-citation literature, and keywords. The purpose of this study was to explore the current research status, research hotspots, and frontiers in this field, and to provide a reference for further promoting the research on postural control in Parkinson's disease patients.

Acupuncture Regulates Symptoms of Parkinson’s Disease via Brain Neural Activity and Functional Connectivity in Mice

Parkinson’s disease (PD) is a multilayered progressive brain disease characterized by motor dysfunction and a variety of other symptoms. Although acupuncture has been used to ameliorate various symptoms of neurodegenerative disorders, including PD, the underlying mechanisms are unclear. Here, we investigated the mechanism of acupuncture by revealing the effects of acupuncture treatment on brain neural responses and its functional connectivity in an animal model of PD. We observed that destruction of neuronal network between many brain regions in PD mice were reversed by acupuncture. Using machine learning analysis, we found that the key region associated with the improvement of abnormal behaviors might be related to the neural activity of M1, suggesting that the changes of c-Fos in M1 could predict the improvement of motor function induced by acupuncture treatment. In addition, acupuncture treatment was shown to significantly normalize the brain neural activity not only in M1 but also in other brain regions related to motor behavior (striatum, substantia nigra pars compacta, and globus pallidus) and non-motor symptoms (hippocampus, lateral hypothalamus, and solitary tract) of PD. Taken together, our results demonstrate that acupuncture treatment might improve the PD symptoms by normalizing the brain functional connectivity in PD mice model and provide new insights that enhance our current understanding of acupuncture mechanisms for non-motor symptoms.

The Effects of Non-Invasive Brain Stimulation on Quantitative EEG in Patients With Parkinson's Disease: A Systematic Scoping Review

Parkinson's disease (PD) is a progressive neurodegenerative disorder characterized by motor and non-motor symptoms, aside from alterations in the electroencephalogram (EEG) already registered. Non-invasive brain stimulation (NIBS) techniques have been suggested as an alternative rehabilitative therapy, but the neurophysiological changes associated with these techniques are still unclear. We aimed to identify the nature and extent of research evidence on the effects of NIBS techniques in the cortical activity measured by EEG in patients with PD. A systematic scoping review was configured by gathering evidence on the following bases: PubMed (MEDLINE), PsycINFO, ScienceDirect, Web of Science, and cumulative index to nursing & allied health (CINAHL). We included clinical trials with patients with PD treated with NIBS and evaluated by EEG pre-intervention and post-intervention. We used the criteria of Downs and Black to evaluate the quality of the studies. Repetitive transcranial magnetic stimulation (TMS), transcranial electrical stimulation (tES), electrical vestibular stimulation, and binaural beats (BBs) are non-invasive stimulation techniques used to treat cognitive and motor impairment in PD. This systematic scoping review found that the current evidence suggests that NIBS could change quantitative EEG in patients with PD. However, considering that the quality of the studies varied from poor to excellent, the low number of studies, variability in NIBS intervention, and quantitative EEG measures, we are not yet able to use the EEG outcomes to predict the cognitive and motor treatment response after brain stimulation. Based on our findings, we recommend additional research efforts to validate EEG as a biomarker in non-invasive brain stimulation trials in PD.

Temporal dynamics of cortical activity and postural control in response to the first levodopa dose of the day in people with Parkinson's disease

BACKGROUND

Our understanding of how balance control responds to levodopa over the course of a single day in people with Parkinson's disease (PD) is limited with the majority of studies focused on isolated comparisons of ON vs. OFF levodopa medication.

OBJECTIVE

To evaluate the temporal dynamics of postural control following the first levodopa dose of the day during a challenging standing task in a group of people with PD.

METHODS

Changes in postural control were evaluated by monitoring cortical activity (covering frontal, motor, parietal and occipital areas), body sway parameters (force platform), and lower limb muscle activity (tibialis anterior and gastrocnemius medialis) in 15 individuals with PD during a semi-tandem standing task. Participants were assessed during two 60 second trials every 30 minutes (ON-30 ON-60 etc.) for 3 hours after the first matinal dose (ON-180).

RESULTS

Compared to when tested OFF-medication, cortical activity was increased across all four regions from ON-60 to ON-120 with early increases in alpha and beta band activity observed at ON-30. Levodopa was associated with increased gastrocnemius medialis activity (ON-30 to ON-120) and ankle co-contraction (ON-60 to ON-120). Changes in body sway outcomes (particularly in the anterior-posterior direction) were evident from ON-60 to ON-120.

CONCLUSIONS

Our results reveal a 60-minute window within which postural control outcomes may be obtained that are different compared to OFF-state and remain stable (from 60-minutes to 120-minutes after levodopa intake). Identifying a window of opportunity for measurement when individuals are optimally medicated is important for observations in a clinical and research setting.

Does Subthalamic Deep Brain Stimulation Impact Asymmetry and Dyscoordination of Gait in Parkinson's Disease?

Background. Subthalamic deep brain stimulation (STN-DBS) is an effective treatment for selected Parkinson's disease (PD) patients. Gait characteristics are often altered after surgery, but quantitative therapeutic effects are poorly described. Objective. The goal of this study was to systematically investigate modifications in asymmetry and dyscoordination of gait 6 months postoperatively in patients with PD and compare the outcomes with preoperative baseline and to asymptomatic controls without PD. Methods. A convenience sample of thirty-two patients with PD (19 with postural instability and gait disorder (PIGD) type and 13 with tremor dominant disease) and 51 asymptomatic controls participated. Parkinson patients were tested prior to the surgery in both OFF and ON medication states, and 6-months postoperatively in the ON stimulation condition. Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) I to IV and medication were compared to preoperative conditions. Asymmetry ratios, phase coordination index, and walking speed were assessed. Results. MDS-UPDRS I to IV at 6 months improved significantly, and levodopa equivalent daily dosages significantly decreased. STN-DBS increased step time asymmetry (hedges' g effect sizes [95% confidence interval] between pre- and post-surgery: .27 [-.13, .73]) and phase coordination index (.29 [-.08, .67]). These effects were higher in the PIGD subgroup than the tremor dominant (step time asymmetry: .38 [-.06, .90] vs .09 [-.83, 1.0] and phase coordination index: .39 [-.04, .84] vs .13 [-.76, .96]). Conclusions. This study provides objective evidence of how STN-DBS increases asymmetry and dyscoordination of gait in patients with PD and suggests motor subtypes-associated differences in the treatment response.

Quantitative Electroencephalography Characteristics for Parkinson's Disease: A Systematic Review

BACKGROUND

Individualized treatment guided by biomarkers certainly will play a crucial role in the more effective treatment of various neurological diseases in the near future. Identifying the electroencephalographic biomarkers in the brain of patients with Parkinson's disease (PD) may help in the decision-making process of health professionals regarding the non-invasive brain stimulation (NIBS) protocols.

OBJECTIVE

To summarize quantitative electroencephalographic (qEEG) characteristics of patients with PD with motor symptoms at rest or during movement to identify potential biomarker associated with motor impairment in PD.

METHODS

A systematic search was conducted in the databases MEDLINE/PubMed, LILACS/BIREME, CINAHL/EBSCO, Web of Science, and CENTRAL, performed according to PRISMA-statement guidelines. Two independent authors searched for studies that reported qEEG data related to motor outcomes at rest or during movements in patients with PD and compared the data with control healthy group. The studies' methodological quality was examined using the Cochrane Handbook. Studies/sample characteristics, qEEG parameters/analyses, and the studies' results were summarized. Prospero-register: CRD42018085660.

RESULTS

Nineteen studies (18 cross-sectional/one cross-over) with 312 PD patients and 277 controls, published between 1994-2018, were included for the qualitative analysis. In comparison to healthy controls, our findings suggest a slowing down of the cortical activity in patients with PD due to an increase of slower band waves activity and a decrease of fast band waves at resting and during complex movement execution mainly in the central and frontal cortex.

CONCLUSION

Slowing down of cortical waves suggest excitatory NIBS for motor impairment in PD. However, qEEG biomarker for motor symptoms of PD cannot be established yet because the studies that related qEEG with motor outcomes presented methodological poor quality.

Altered Spontaneous Neural Activity and Functional Connectivity in Parkinson's Disease With Subthalamic Microlesion

Background

Transient improvement in motor symptoms are immediately observed in patients with Parkinson's disease (PD) after an electrode has been implanted into the subthalamic nucleus (STN) for deep brain stimulation (DBS). This phenomenon is known as the microlesion effect (MLE). However, the underlying mechanisms of MLE is poorly understood.

Purpose

We utilized resting state functional MRI (rs-fMRI) to evaluate changes in spontaneous brain activity and networks in PD patients during the microlesion period after DBS.

Method

Overall, 37 PD patients and 13 gender- and age-matched healthy controls (HCs) were recruited for this study. Rs-MRI information was collected from PD patients three days before DBS and one day after DBS, whereas the HCs group was scanned once. We utilized the amplitude of low-frequency fluctuation (ALFF) method in order to analyze differences in spontaneous whole-brain activity among all subjects. Furthermore, functional connectivity (FC) was applied to investigate connections between other brain regions and brain areas with significantly different ALFF before and after surgery in PD patients.

Result

Relative to the PD-Pre-DBS group, the PD-Post-DBS group had higher ALFF in the right putamen, right inferior frontal gyrus, right precentral gyrus and lower ALFF in right angular gyrus, right precuneus, right posterior cingulate gyrus (PCC), left insula, left middle temporal gyrus (MTG), bilateral middle frontal gyrus and bilateral superior frontal gyrus (dorsolateral). Functional connectivity analysis revealed that these brain regions with significantly different ALFF scores demonstrated abnormal FC, largely in the temporal, prefrontal cortices and default mode network (DMN).

Conclusion

The subthalamic microlesion caused by DBS in PD was found to not only improve the activity of the basal ganglia-thalamocortical circuit, but also reduce the activity of the DMN and executive control network (ECN) related brain regions. Results from this study provide new insights into the mechanism of MLE.

Quadruple Decision Making for Parkinson's Disease Patients: Combining Expert Opinion, Patient Preferences, Scientific Evidence, and Big Data Approaches to Reach Precision Medicine

Clinical decision making for Parkinson’s disease patients is supported by a combination of three distinct information resources: best available scientific evidence, professional expertise, and the personal needs and preferences of patients. All three sources have clear value but also share several important limitations, mainly regarding subjectivity, generalizability and variability. For example, current scientific evidence, especially from controlled clinical trials, is often based on selected study populations, making it difficult to translate the outcome to the care for individual patients in everyday clinical practice. Big data, including data from real-life unselected Parkinson populations, can help to bridge this information gap. Fine-grained patient profiles created from big data have the potential to aid in identifying therapeutic approaches that will be most effective given each patient’s individual characteristics, which is particularly important for a disorder characterized by such tremendous interindividual variability as Parkinson’s disease. In this viewpoint, we argue that big data approaches should be acknowledged and harnessed, not to replace existing information resources, but rather as a fourth and complimentary source of information in clinical decision making, helping to represent the full complexity of individual patients. We introduce the ‘quadruple decision making’ model and illustrate its mode of action by showing how this can be used to pursue precision medicine for persons living with Parkinson’s disease.

Neuroimaging Detectable Differences between Parkinson's Disease Motor Subtypes: A Systematic Review

BACKGROUND

The neuroanatomical substrates of Parkinson's disease (PD) with tremor-dominance (TD) and those with non-tremor dominance (nTD), postural instability and gait difficulty (PIGD), and akinetic-rigid (AR) are not fully differentiated. A better understanding of symptom specific pathoanatomical markers of PD subtypes may result in earlier diagnosis and more tailored treatment. Here, we aim to give an overview of the neuroimaging literature that compared PD motor subtypes.

METHODS

A systematic literature review on neuroimaging studies of PD subtypes was conducted according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Search terms submitted to the PubMed database included: "Parkinson's disease", "MRI" and "motor subtypes" (TD, nTD, PIGD, AR). The results are first discussed from macro to micro level of organization (i.e., (1) structural; (2) functional; and (3) molecular) and then by applied imaging methodology.

FINDINGS

Several neuroimaging methods including diffusion imaging and positron emission tomography (PET) distinguish specific PD motor subtypes well, although findings are mixed. Furthermore, our review demonstrates that nTD-PD patients have more severe neuroalterations compared to TD-PD patients. More specifically, nTD-PD patients have deficits within striato-thalamo-cortical (STC) circuitry and other thalamocortical projections related to cognitive and sensorimotor function, while TD-PD patients tend to have greater cerebello-thalamo-cortical (CTC) circuitry dysfunction.

CONCLUSIONS

Based on the literature, STC and CTC circuitry deficits seem to be the key features of PD and the subtypes. Future research should make greater use of multimodal neuroimaging and techniques that have higher sensitivity in delineating subcortical structures involved in motor diseases.

Brain Motor Network Changes in Parkinson's Disease: Evidence from Meta-Analytic Modeling

Background

Motor‐related brain activity in Parkinson's disease has been investigated in a multitude of functional neuroimaging studies, which often yielded apparently conflicting results. Our previous meta‐analysis did not resolve inconsistencies regarding cortical activation differences in Parkinson's disease, which might be related to the limited number of studies that could be included. Therefore, we conducted a revised meta‐analysis including a larger number of studies. The objectives of this study were to elucidate brain areas that consistently show abnormal motor‐related activation in Parkinson's disease and to reveal their functional connectivity profiles using meta‐analytic approaches.

Methods

We applied a quantitative meta‐analysis of functional neuroimaging studies testing limb movements in Parkinson's disease comprising data from 39 studies, of which 15 studies (285 of 571 individual patients) were published after the previous meta‐analysis. We also conducted meta‐analytic connectivity modeling to elucidate the connectivity profiles of areas showing abnormal activation.

Results

We found consistent motor‐related underactivation of bilateral posterior putamen and cerebellum in Parkinson's disease. Primary motor cortex and the supplementary motor area also showed deficient activation, whereas cortical regions localized directly anterior to these areas expressed overactivation. Connectivity modeling revealed that areas showing decreased activation shared a common pathway through the posterior putamen, whereas areas showing increased activation were connected to the anterior putamen.

Conclusions

Despite conflicting results in individual neuroimaging studies, this revised meta‐analytic approach identified consistent patterns of abnormal motor‐related activation in Parkinson's disease. The distinct patterns of decreased and increased activity might be determined by their connectivity with different subregions of the putamen. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

GraphNet-based imaging biomarker model to explain levodopa-induced dyskinesia in Parkinson's disease

BACKGROUND AND OBJECTIVE

Levodopa-induced dyskinesia (LID) is a disabling complication of Parkinson's disease (PD). Imaging-based measurements, especially those related to the surface shape of the basal ganglia, have shown potential for explaining the severity of LID in PD. Here, we aimed to explore a novel application of the methodology to find biomarkers of LID severity in PD using regularization.

METHODS

We proposed an application of graph-constrained elastic net (GraphNet) regularization to detect surface-based shape biomarkers explaining the severity of LID and compared the approach with other conventional regularization methods. To examine the methods, we used two independent datasets, one as a training dataset to build the model, and the other dataset was used to validate the constructed model.

RESULTS

We found that the left striatum (putamen was the greatest and the caudate was second) was the most significant surface-based biomarker related to the severity of LID. Our results improved the interpretability of identified surface-based biomarkers compared to competing methods. We also found that GraphNet regularization improved prediction of the severity of LID better than the conventional regularization methods. Our model performed better in terms of root-mean-squared error and correlation coefficient between predicted and actual clinical scores.

CONCLUSION

The proposed algorithm offers an advantage of interpretable anatomical variations related to the deformation of the cortical surface. The experimental results showed that GraphNet regularization was robust to identify surface-based shape biomarkers related to both hypokinetic and hyperkinetic movement disorders.

Levodopa Changes Functional Connectivity Patterns in Subregions of the Primary Motor Cortex in Patients With Parkinson's Disease

Background

The primary motor cortex (M1) is a critical node in Parkinson’s disease (PD)-related motor circuitry; however, the functional roles of its subregions are poorly understood. In this study, we investigated changes in the functional connectivity patterns of M1 subregions and their relationships to improved clinical symptoms following levodopa administration.

Methods

Thirty-six PD patients and 37 healthy controls (HCs) were enrolled. A formal levodopa challenge test was conducted in the PD group, and the Unified Parkinson’s Disease Rating Scale motor section (UPDRS-III) was assessed before (off state) and 1 h after administration of levodopa (on state). The PD group underwent resting-state functional magnetic resonance imaging in both off and on states, whereas the HC group was scanned once. We used the Human Brainnetome Atlas template to subdivide M1 into twelve regions of interest (ROIs). Functional connectivity (FC) was compared between PD on and off states [paired t-test, voxel-level p < 0.001, cluster-level p < 0.05, Gaussian random field (GRF) correction] and between patients and HC (two-sample t-test voxel-level p < 0.001, cluster-level p < 0.05). Correlations between ΔFC (differences in FC between PD off and on states) and clinical symptom improvements were examined.

Results

There was decreased FC between the right caudal dorsolateral area 6 and the anterior cingulate gyrus (ACC), the right upper limb region and the left medial dorsal thalamus (mdTHA), as well as increased FC between the left tongue and larynx region and the left medial frontal gyrus. ΔFC between the right caudal dorsolateral area 6 and ACC was positively correlated with improvements in UPDRS-III total scores as well as the rigidity (item 22) and bradykinesia (items 23–26 and 31) subscores. ΔFC between the right upper limb region and left thalamus was positively correlated with improvements in the left upper limb tremor (items 20c and 21b) and postural tremor (item 21b) subscores.

Conclusions

Our results reveal novel information regarding the underlying mechanisms in the motor circuits in the M1 and a promising way to explore the internal function of the M1 in PD patients. Notably, M1 is a potential therapeutic target in PD, and the exploration of its subregions provides a basis and a source of new insights for clinical intervention and precise drug treatment.

Assessing White Matter Pathology in Early-Stage Parkinson Disease Using Diffusion MRI: A Systematic Review

Structural brain white matter (WM) changes such as axonal caliber, density, myelination, and orientation, along with WM-dependent structural connectivity, may be impacted early in Parkinson disease (PD). Diffusion magnetic resonance imaging (dMRI) has been used extensively to understand such pathological WM changes, and the focus of this systematic review is to understand both the methods utilized and their corresponding results in the context of early-stage PD. Diffusion tensor imaging (DTI) is the most commonly utilized method to probe WM pathological changes. Previous studies have suggested that DTI metrics are sensitive in capturing early disease-associated WM changes in preclinical symptomatic regions such as olfactory regions and the substantia nigra, which is considered to be a hallmark of PD pathology and progression. Postprocessing analytic approaches include region of interest-based analysis, voxel-based analysis, skeletonized approaches, and connectome analysis, each with unique advantages and challenges. While DTI has been used extensively to study WM disorganization in early-stage PD, it has several limitations, including an inability to resolve multiple fiber orientations within each voxel and sensitivity to partial volume effects. Given the subtle changes associated with early-stage PD, these limitations result in inaccuracies that severely impact the reliability of DTI-based metrics as potential biomarkers. To overcome these limitations, advanced dMRI acquisition and analysis methods have been employed, including diffusion kurtosis imaging and q-space diffeomorphic reconstruction. The combination of improved acquisition and analysis in DTI may yield novel and accurate information related to WM-associated changes in early-stage PD. In the current article, we present a systematic and critical review of dMRI studies in early-stage PD, with a focus on recent advances in DTI methodology. Yielding novel metrics, these advanced methods have been shown to detect diffuse WM changes in early-stage PD. These findings support the notion of early axonal damage in PD and suggest that WM pathology may go unrecognized until symptoms appear. Finally, the advantages and disadvantages of different dMRI techniques, analysis methods, and software employed are discussed in the context of PD-related pathology.

Beneficial effects of the phytocannabinoid Δ9-THCV in L-DOPA-induced dyskinesia in Parkinson's disease

The antioxidant and CB₂ receptor agonist properties of Δ⁹-tetrahydrocannabivarin (Δ⁹-THCV) afforded neuroprotection in experimental Parkinson's disease (PD), whereas its CB₁ receptor antagonist profile at doses lower than 5 mg/kg caused anti-hypokinetic effects. In the present study, we investigated the anti-dyskinetic potential of Δ⁹-THCV (administered i.p. at 2 mg/kg for two weeks), which had not been investigated before. This objective was investigated after inducing dyskinesia by repeated administration of L-DOPA (i.p. at 10 mg/kg) in a genetic model of dopaminergic deficiency, Pitx3^ak mutant mice, which serves as a useful model for testing anti-dyskinetic agents. The daily treatment of these mice with L-DOPA for two weeks progressively increased the time spent in abnormal involuntary movements (AIMs) and elevated their horizontal and vertical activities (as measured in a computer-aided actimeter), signs that reflected the dyskinetic state of these mice. Interestingly, when combined with L-DOPA from the first injection, Δ⁹-THCV delayed the appearance of all these signs and decreased their intensity, with a reduction in the levels of FosB protein and the histone pAcH3 (measured by immunohistochemistry), which had previously been found to be elevated in the basal ganglia in L-DOPA-induced dyskinesia. In addition to the anti-dyskinetic effects of Δ⁹-THCV when administered at the onset of L-DOPA treatment, Δ⁹-THCV was also effective in attenuating the intensity of dyskinesia when administered for three consecutive days once these signs were already present (two weeks after the onset of L-DOPA treatment). In summary, our data support the anti-dyskinetic potential of Δ⁹-THCV, both to delay the occurrence and to attenuate the magnitude of dyskinetic signs. Although further studies are clearly required to determine the clinical significance of these data in humans, the results nevertheless situate Δ⁹-THCV in a promising position for developing a cannabinoid-based therapy for patients with PD.

Learning Brain Effective Connectivity Network Structure Using Ant Colony Optimization Combining With Voxel Activation Information

Learning brain effective connectivity (EC) networks from functional magnetic resonance imaging (fMRI) data has become a new hot topic in the neuroinformatics field. However, how to accurately and efficiently learn brain EC networks is still a challenging problem. In this paper, we propose a new algorithm to learn the brain EC network structure using ant colony optimization (ACO) algorithm combining with voxel activation information, named as VACOEC. First, VACOEC uses the voxel activation information to measure the independence between each pair of brain regions and effectively restricts the space of candidate solutions, which makes many unnecessary searches of ants be avoided. Then, by combining the global score increase of a solution with the voxel activation information, a new heuristic function is designed to guide the process of ACO to search for the optimal solution. The experimental results on simulated datasets show that the proposed method can accurately and efficiently identify the directions of the brain EC networks. Moreover, the experimental results on real-world data show that patients with Alzheimers disease (AD) exhibit decreased effective connectivity not only in the intra-network within the default mode network (DMN) and salience network (SN), but also in the inter-network between DMN and SN, compared with normal control (NC) subjects. The experimental results demonstrate that VACOEC is promising for practical applications in the neuroimaging studies of geriatric subjects and neurological patients.

Imaging of Motor Cortex Physiology in Parkinson's Disease

There is abundant evidence that the pathophysiology of Parkinson's disease (PD) is not confined to the nigrostriatal dopaminergic pathway but propagates along the cortico‐basal ganglia‐thalamo‐cortical neural network. A critical node in this functional circuit impacted by PD is the primary motor cortex (M1), which plays a key role in generating neural impulses that regulate movements. The past several decades have lay witness to numerous in vivo neuroimaging techniques that provide a window into the function and structure of M1. A consistent observation from numerous studies is that during voluntary movement, but also at rest, the functional activity of M1 is altered in PD relative to healthy individuals, and it relates to many of the motor signs. Although this abnormal functional activity can be partially restored with acute dopaminergic medication, it continues to deteriorate with disease progression and may predate structural degeneration of M1. The current review discusses the evidence that M1 is fundamental to the pathophysiology of PD, as measured by neuroimaging techniques such as positron emission tomography, single‐photon emission computed tomography, electroencephalography, magnetoencephalography, and functional and structural MRI. Although novel treatments that target the cortex will not cure PD, they could significantly slow down and alter the progressive course of the disease and thus improve clinical care for this degenerative disease. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society

Patterns of striatal and cerebellar functional connectivity in early-stage drug-naïve patients with Parkinson's disease subtypes

PURPOSE

Both the striatal-thalamo-cortical (STC) circuit and cerebello-thalamo-cortical (CTC) circuit play a critical role in Parkinson's disease (PD).

METHODS

Resting-state functional MRI was used to assess functional connectivity (FC) focusing on the basal ganglia (BG) and cerebellum among early-stage drug-naïve PD patients with tremor-dominant (TD) PD patients with postural instability and gait dysfunction (PIGD) and healthy controls (HCs).

RESULTS

Compared to HCs, both PD subgroups had higher FC between the cerebellum and paracentral lobule, sensorimotor areas; lower FC between the BG and superior frontal gyrus, and within the BG circuit; PD-TD patients showed higher FC between the BG and fusiform, paracentral lobule, cerebellum Lobule VI, and between the cerebellum and supplementary motor areas (SMA), insula; lower FC between the BG and rectus, sensorimotor areas, and within the cerebellum circuit; PD-PIGD patients showed higher FC between the cerebellum and middle frontal gyrus, precuneus; lower FC between the BG and cerebellum Crus II. Besides, compared to PD-PIGD patients and HCs, PD-TD patients had higher FC between the BG and calcarine region. In all PD patients, FC in paracentral lobule, SMA, and cerebellum Lobule VI positively correlated with tremor scores, and FC in calcarine area positively correlated with tremor scores, but negatively correlated with PIGD scores.

CONCLUSION

Our findings mainly suggested that the BG and cerebellum had hyper-connectivity with the cortical motor cortex, and the BG had prominent hyper-connectivity with the visual cortex in early-stage PD-TD patients. These findings may be helpful for facilitating the further understanding of potential mechanisms in the early-stage PD-TD. However, our results are preliminary, and further investigations are needed.

Deep Brain Stimulation and L-DOPA Therapy: Concepts of Action and Clinical Applications in Parkinson's Disease

L-DOPA is still the most effective pharmacological therapy for the treatment of motor symptoms in Parkinson's disease (PD) almost four decades after it was first used. Deep brain stimulation (DBS) is a safe and highly effective treatment option in patients with PD. Even though a clear understanding of the mechanisms of both treatment methods is yet to be obtained, the combination of both treatments is the most effective standard evidenced-based therapy to date. Recent studies have demonstrated that DBS is a therapy option even in the early course of the disease, when first complications arise despite a rigorous adjustment of the pharmacological treatment. The unique feature of this therapeutic approach is the ability to preferentially modulate specific brain networks through the choice of stimulation site. The clinical effects have been unequivocally confirmed in recent studies; however, the impact of DBS and the supplementary effect of L-DOPA on the neuronal network are not yet fully understood. In this review, we present emerging data on the presumable mechanisms of DBS in patients with PD and discuss the pathophysiological similarities and differences in the effects of DBS in comparison to dopaminergic medication. Targeted, selective modulation of brain networks by DBS and pharmacodynamic effects of L-DOPA therapy on the central nervous system are presented. Moreover, we outline the perioperative algorithms for PD patients before and directly after the implantation of DBS electrodes and strategies for the reduction of side effects and optimization of motor and non-motor symptoms.

Functional MRI in Idiopathic Parkinson's Disease

Functional MRI (fMRI) has been widely used to study abnormal patterns of brain connectivity at rest and activation during a variety of tasks in patients with idiopathic Parkinson's disease (PD). fMRI studies in PD have led to a better understanding of many aspects of the disease including both motor and non-motor symptoms. Although its translation into clinical practice is still at an early stage, fMRI measures hold promise for multiple clinical applications in PD, including the early detection, predicting future change in clinical status, and as a marker of alterations in brain physiology related to neurotherapeutic agents and neurorehabilitative strategies.

Insights into the Molecular Mechanisms of Alzheimer's and Parkinson's Diseases with Molecular Simulations: Understanding the Roles of Artificial and Pathological Missense Mutations in Intrinsically Disordered Proteins Related to Pathology

Amyloid-β and α-synuclein are intrinsically disordered proteins (IDPs), which are at the center of Alzheimer's and Parkinson's disease pathologies, respectively. These IDPs are extremely flexible and do not adopt stable structures. Furthermore, both amyloid-β and α-synuclein can form toxic oligomers, amyloid fibrils and other type of aggregates in Alzheimer's and Parkinson's diseases. Experimentalists face challenges in investigating the structures and thermodynamic properties of these IDPs in their monomeric and oligomeric forms due to the rapid conformational changes, fast aggregation processes and strong solvent effects. Classical molecular dynamics simulations complement experiments and provide structural information at the atomic level with dynamics without facing the same experimental limitations. Artificial missense mutations are employed experimentally and computationally for providing insights into the structure-function relationships of amyloid-β and α-synuclein in relation to the pathologies of Alzheimer's and Parkinson's diseases. Furthermore, there are several natural genetic variations that play a role in the pathogenesis of familial cases of Alzheimer's and Parkinson's diseases, which are related to specific genetic defects inherited in dominant or recessive patterns. The present review summarizes the current understanding of monomeric and oligomeric forms of amyloid-β and α-synuclein, as well as the impacts of artificial and pathological missense mutations on the structural ensembles of these IDPs using molecular dynamics simulations. We also emphasize the recent investigations on residual secondary structure formation in dynamic conformational ensembles of amyloid-β and α-synuclein, such as β-structure linked to the oligomerization and fibrillation mechanisms related to the pathologies of Alzheimer's and Parkinson's diseases. This information represents an important foundation for the successful and efficient drug design studies.

Brain Magnetic Resonance Imaging (MRI) as a Potential Biomarker for Parkinson's Disease (PD)

Magnetic resonance imaging (MRI) has the potential to serve as a biomarker for Parkinson's disease (PD). However, the type or types of biomarker it could provide remain to be determined. At this time there is not sufficient sensitivity or specificity for MRI to serve as an early diagnostic biomarker, i.e., it is unproven in its ability to determine if a single individual is normal, has mild PD, or has some other forms of degenerative parkinsonism. However there is accumulating evidence that MRI may be useful in staging and monitoring disease progression (staging biomarker), and also possibly as a means to monitor pathophysiological aspects of disease and associated response to treatments, i.e., theranostic marker. As there are increasing numbers of manuscripts that are dedicated to diffusion- and neuromelanin-based imaging methods, this review will focus on these topics cursorily and will delve into pharmacodynamic imaging as a means to get at theranostic aspects of PD.