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

Grey matter volume differences across Parkinson's disease motor subtypes in the supplementary motor cortex

Parkinson's Disease (PD) is the second most prevalent neurodegenerative disease worldwide due to loss of dopaminergic neurons projecting from the basal ganglia (BG). It is associated with various motor symptoms that are grouped into subtypes, each with different clinical presentations and disease progressions. Neuroimaging biomarkers focusing on regions a part of motor circuits projecting from the BG can distinguish and improve overall subtyping. The supplementary motor cortex (SMC) is well established in PD neuropathology and associated with freezing of gait and bradykinesia, but has not been thoroughly evaluated across subtypes. This study aims to identify volumetric differences of the SMC based on PD subtypes of tremor dominant (TD), postural instability with gait difficulty (PIGD), and akinetic rigid (AR) using data from Parkinson's Progression Markers Initiative. To segment grey matter volume and extract region of interest values, voxel-based processing was used. Multi-factor ANCOVAs, Tukey Honest Significance Test, and Kruskal-Wallis were utilized for volumetric analyses (α < 0.05). Subjects were classified and evaluated using TD, PIGD, and AR subtypes from the MDS-UPDRS rating scales. Inter-subtype differences in SMC GMV between TD and PIGD were significant in the right hemisphere for females (p = 0.01). No significant inter-subtype differences were found in the TD/AR system. These results support the use of broader motor networks, specifically the SMC in further understanding the neuropathological heterogeneity of PD. Furthermore, it reveals SMC differences across sexes, subtypes, and subtyping systems, calling for further evaluation of subtyping schemas, specifically regarding sex differences.

From prodromal stages to clinical trials: The promise of digital speech biomarkers in Parkinson's disease

Speech impairment is a common and disabling symptom in Parkinson's disease (PD), affecting communication and quality of life. Advances in digital speech processing and artificial intelligence have revolutionized objective speech analysis. Given the complex nature of speech impairment, acoustic speech analysis offers unique biomarkers for neuroprotective treatments from the prodromal stages of PD. Digital speech biomarkers can monitor levodopa-induced motor complications, detect the effects of deep brain stimulation, and provide feedback for behavioral speech therapy. This review updates the mechanisms underlying speech impairment, the impact of speech phenotypes, and the effects of interventions on speech. We evaluate the strengths, potential weaknesses, and suitability of promising digital speech biomarkers in PD for capturing disease progression and treatment efficacy. Additionally, we explore the translational potential of PD speech biomarkers to other neuropsychiatric diseases, offering insights into motion, cognition, and emotion. Finally, we highlight knowledge gaps and suggest directions for future research to enhance the use of quantitative speech measures in disease-modifying clinical trials. The findings demonstrate that one year is sufficient to detect disease progression in early PD through speech biomarkers. Voice quality, pitch, loudness, and articulation measures appear to capture the efficacy of treatment interventions most effectively. Certain speech features, such as loudness and articulation rate, behave oppositely in different neurological diseases, offering valuable insights for differential diagnosis. In conclusion, this review highlights speech as a biomarker in tracking disease progression, especially in the prodromal stages of PD, and calls for further longitudinal studies to establish its efficacy across diverse populations.

Identifying genetic targets in clinical subtypes of Parkinson's disease for optimizing pharmacological treatment strategies

The heterogeneity of Parkinson's disease (PD) has been recognized in clinical, with patients categorized into distinct subsets based on motor phenotype, such as tremor-dominant PD (TD), postural instability and gait difficulty-dominant PD (PIGD) and mixed PD (Mix). Despite this categorization, the underlying mechanisms of this heterogeneity remain poorly understood, and there is no personalized effective treatment for each PD subtype. To address this, a rat model for PD subtypes was established by unilateral stereotaxic injection of 6-OHDA, followed by cluster analysis of behavioral data. The serum neurofilament light chain (NfL) and uric acid (UA) levels as well as alterations in brain autonomic activity in rats were consistent with clinical patients, and metabolomics results showed that more than 70% of the metabolites in the serum of different subtypes of PD rats and clinical patients appeared to be consistently altered. Further transcriptomic analysis by RNA-seq has elucidated that the development of PD subtypes is associated with altered gene expression in neurotransmitter, neuronal damage in the central or peripheral nervous system, and lipid metabolism. In addition, based on the subtype-specific differentially expressed genes, 25 potential drug candidates were identified. Notably, the Alox15 inhibitor baicalein showed a greater efficacy on Mix rats, highlighting the possibility of selecting targeted treatments for well-defined individuals.

Relative sparing of dopaminergic terminals in the caudate nucleus is a feature of rest tremor in Parkinson's disease

Resting tremor (RT) is a Parkinson's disease (PD) symptom with an unclear relationship to the dopaminergic system. We analysed data from 432 subjects from the Parkinson's Progression Markers Initiative, 57 additional PD patients and controls and 86 subjects referred for dopamine transporter single-photon emission computed tomography (DaT-SPECT). Caudate binding ratio (CBR), but not putamen binding ratio, was higher in RT patients. Furthermore, higher baseline CBR was linked to RT development. In the smaller cohorts, a 4-6 Hz oscillation-based metric from inertial sensors correlated with RT amplitude, distinguished controls from patients with reduced DaT binding and correlated with CBR in the latter group. In silico modelling uncovered that higher CBR in RT patients explained correlations between RT and DaT-SPECT found in several datasets, supporting a spurious origin for ipsilateral correlations between CBR and RT. These results suggest that caudate dopaminergic terminals integrity is a feature of RT with potential pathophysiological implications.

Cerebellar Structural and N-Acetylaspartate, Choline, and Creatine Metabolic Profiles in Parkinson's Disease and Essential Tremor

BACKGROUND

The role of the cerebellum in Parkinson's disease (PD), particularly in tremor-dominant subtypes, is increasingly recognized. Magnetic resonance imaging (MRI) and magnetic resonance spectroscopy (MRS) provide anatomical and metabolic insights, suggesting compensatory hyperactivity or degenerative changes in the cerebellum in PD. Volumetric analysis of cerebellar structures in MRI images, combined with metabolic profiles from MRS, offers possibilities for differentiating PD from essential tremor (ET). The cerebellum may be a potential therapeutic target due to its role in neurocircuitry of PD and ET.

METHODS

Brain structural data were obtained using MRI, and cerebellar metabolic profiles, focusing on the quantification of N-acetylaspartate (NAA), choline, and creatine peaks were obtained using MRS. This study enrolled patients with ET and PD, both with and without tremor, as well as disease controls with cerebellar atrophy (including spinocerebellar ataxia and multiple system atrophy). Volumetric analysis of cerebellar structures was performed. Differences in MRI and MRS parameters were analyzed using one-way analysis of covariance with a significance threshold of p < 0.05.

RESULTS

From November 2018 to March 2023, 111 patients were enrolled, including 29 ET, 29 cerebellar atrophy, 12 PD without tremor, and 41 PD with tremor. No significant differences in cerebellar volume and N-acetylaspartate/creatine and choline/creatine ratios were found between ET and PD with tremor.

CONCLUSIONS

This preliminary retrospective study suggests similarities in cerebellar structures and metabolic profiles between ET and PD, highlighting the need for advanced imaging techniques to better differentiate between these conditions. Future research should integrate clinical data, such as tremor severity and cognitive assessments, to explore the relationships with cerebellar MRI parameters.

Impaired Gait, Postural Instability, and Rigidity in Relation to CB1 Receptor Availability in Parkinson's Disease

BACKGROUND

In Parkinson's disease (PD), postural instability and gait disorder (PIGD) symptoms are associated with a worse prognosis for an unknown reason.

OBJECTIVE

The objective was to explore the relationship between cannabinoid receptor type 1 (CB1R) availability and motor symptoms in PD with [18F]FMPEP-d2 positron emission tomography (PET).

METHODS

Fifteen individuals with PD underwent [18F]FMPEP-d2 PET to measure cerebral CB1R availability. The Unified Parkinson's Disease Rating Scale motor part (UPDRS-III) was used to evaluate the motor symptoms.

RESULTS

A negative correlation was observed between [18F]FMPEP-d2 VT and PIGD score (P = 0.002) as well as rigidity subscore (P < 0.001). Both clusters covered widespread areas of both hemispheres. In contrast, tremor or bradykinesia did not correlate to [18F]FMPEP-d2 VT.

CONCLUSIONS

Gait, postural instability, and rigidity in PD are associated with decreased CB1R availability, unlike tremor or bradykinesia, suggesting that the endocannabinoid system has a role in the pathophysiology of different motor symptoms in PD. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Rehabilitation Response in Tremor- and Non-Tremor-Dominant Parkinson Disease: A Task-fMRI Study

BACKGROUND

Tremor-dominant (TD) and nontremor-dominant (NTD) Parkinson's disease (PD) showed different responses to rehabilitation. However, the neural mechanism behind this remains unclear.

METHODS

This cohort study explores changes in motor function, brain activation, and functional connectivity following 2 weeks of rehabilitation in TD-PD and NTD-PD patients, respectively. A total of 11 TD-PD patients, 24 NTD-PD patients, and 21 age-matched healthy controls (HCs) were included. At baseline, all participants underwent functional magnetic resonance imaging (fMRI) while performing the foot tapping task. Motor symptoms, gait, balance, and task-based fMRI were then evaluated in patients before and after rehabilitation.

RESULTS

Compared to HCs, TD-PD patients showed increased activity in the left inferior frontal gyrus and the right insula, and NTD-PD patients showed increased activations in the left postcentral gyrus and decreased within-cerebellar connectivity at baseline. Rehabilitation improved motor function in PD patients regardless of motor subtype. TD-PD patients showed increased recruitments of the sensorimotor cortex and the bilateral thalamus after rehabilitation, and NTD-PD patients showed increased cerebellar activation and within-cerebellar connectivity that was associated with better motor performance.

CONCLUSIONS

This study demonstrated that rehabilitation-induced brain functional reorganization varied by motor subtypes in PD, which may have important implications for making individualized rehabilitation programs.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: ChiCTR1900020771.

A causal counterfactual graph neural network for arising-from-chair abnormality detection in parkinsonians

The arising-from-chair task assessment is a key aspect of the evaluation of movement disorders in Parkinson's disease (PD). However, common scale-based clinical assessment methods are highly subjective and dependent on the neurologist's expertise. Alternate automated methods for arising-from-chair assessment can be established based on quantitative susceptibility mapping (QSM) images with multiple-instance learning. However, performance stability for such methods can be typically undermined by the presence of irrelevant or spuriously-relevant features that mask the intrinsic causal features. Therefore, we propose a QSM-based arising-from-chair assessment method using a causal graph-neural-network framework, where counterfactual and debiasing strategies are developed and integrated into this framework for capturing causal features. Specifically, the counterfactual strategy is proposed to suppress irrelevant features caused by background noise, by producing incorrect predictions when dropping causal parts. The debiasing strategy is proposed to suppress spuriously relevant features caused by the sampling bias and it comprises a resampling guidance scheme for selecting stable instances and a causal invariance constraint for improving stability under various interferences. The results of extensive experiments demonstrated the superiority of the proposed method in detecting arising-from-chair abnormalities. Its clinical feasibility was further confirmed by the coincidence between the selected causal features and those reported in earlier medical studies. Additionally, the proposed method was extensible for another motion task of leg agility. Overall, this study provides a potential tool for automated arising-from-chair assessment in PD patients, and also introduces causal counterfactual thinking in medical image analysis. Our source code is publicly available at https://github.com/SJTUBME-QianLab/CFGNN-PDarising.

Simple biomarkers to distinguish Parkinson's disease from its mimics in clinical practice: a comprehensive review and future directions

In the last few years, a plethora of biomarkers have been proposed for the differentiation of Parkinson's disease (PD) from its mimics. Most of them consist of complex measures, often based on expensive technology, not easily employed outside research centers. MRI measures have been widely used to differentiate between PD and other parkinsonism. However, these measurements were often performed manually on small brain areas in small patient cohorts with intra- and inter-rater variability. The aim of the current review is to provide a comprehensive and updated overview of the literature on biomarkers commonly used to differentiate PD from its mimics (including parkinsonism and tremor syndromes), focusing on parameters derived by simple qualitative or quantitative measurements that can be used in routine practice. Several electrophysiological, sonographic and MRI biomarkers have shown promising results, including the blink-reflex recovery cycle, tremor analysis, sonographic or MRI assessment of substantia nigra, and several qualitative MRI signs or simple linear measures to be directly performed on MR images. The most significant issue is that most studies have been conducted on small patient cohorts from a single center, with limited reproducibility of the findings. Future studies should be carried out on larger international cohorts of patients to ensure generalizability. Moreover, research on simple biomarkers should seek measurements to differentiate patients with different diseases but similar clinical phenotypes, distinguish subtypes of the same disease, assess disease progression, and correlate biomarkers with pathological data. An even more important goal would be to predict the disease in the preclinical phase.

The Role of Non-Invasive Brain Modulation in Identifying Disease Biomarkers for Diagnostic and Therapeutic Purposes in Parkinsonism

Over the past three decades, substantial advancements have occurred in non-invasive brain stimulation (NIBS). These developments encompass various non-invasive techniques aimed at modulating brain function. Among the most widely utilized methods today are transcranial magnetic stimulation (TMS) and transcranial electrical stimulation (TES), which include direct- or alternating-current transcranial stimulation (tDCS/tACS). In addition to these established techniques, newer modalities have emerged, broadening the scope of non-invasive neuromodulation approaches available for research and clinical applications in movement disorders, particularly for Parkinson's disease (PD) and, to a lesser extent, atypical Parkinsonism (AP). All NIBS techniques offer the opportunity to explore a wide range of neurophysiological mechanisms and exert influence over distinct brain regions implicated in the pathophysiology of Parkinsonism. This paper's first aim is to provide a brief overview of the historical background and underlying physiological principles of primary NIBS techniques, focusing on their translational relevance. It aims to shed light on the potential identification of biomarkers for diagnostic and therapeutic purposes, by summarising available experimental data on individuals with Parkinsonism. To date, despite promising findings indicating the potential utility of NIBS techniques in Parkinsonism, their integration into clinical routine for diagnostic or therapeutic protocols remains a subject of ongoing investigation and scientific debate. In this context, this paper addresses current unsolved issues and methodological challenges concerning the use of NIBS, focusing on the importance of future research endeavours for maximizing the efficacy and relevance of NIBS strategies for individuals with Parkinsonism.

Analysis of striatal connectivity corresponding to striosomes and matrix in de novo Parkinson's disease and isolated REM behavior disorder

Striosomes and matrix are two compartments that comprise the striatum, each having its own distinct immunohistochemical properties, function, and connectivity. It is currently not clear whether prodromal or early manifest Parkinson's disease (PD) is associated with any striatal matrix or striosomal abnormality. Recently, a method of striatal parcellation using probabilistic tractography has been described and validated, using the distinct connectivity of these two compartments to identify voxels with striosome- and matrix-like connectivity. The goal of this study was to use this approach in tandem with DAT-SPECT, a method used to quantify the level of nigrostriatal denervation, to analyze the striatum in populations of de novo diagnosed, treatment-naïve patients with PD, isolated REM behavioral disorder (iRBD) patients, and healthy controls. We discovered a shift in striatal connectivity, which showed correlation with nigrostriatal denervation. Patients with PD exhibited a significantly higher matrix-like volume and associated connectivity than healthy controls and higher matrix-associated connectivity than iRBD patients. In contrast, the side with less pronounced nigrostriatal denervation in PD and iRBD patients showed a decrease in striosome-like volume and associated connectivity indices. These findings could point to a compensatory neuroplastic mechanism in the context of nigrostriatal denervation and open a new avenue in the investigation of the pathophysiology of Parkinson's disease.

Neuroimaging correlates of postural instability in Parkinson's disease

BACKGROUND

Postural instability (PI) is a common disabling symptom in Parkinson's disease (PD), but little is known on its pathophysiological basis.

OBJECTIVE

In this study, we aimed to identify the brain structures associated with PI in PD patients, using different MRI approaches.

METHODS

We consecutively enrolled 142 PD patients and 45 control subjects. PI was assessed using the MDS-UPDRS-III pull-test item (PT). A whole-brain regression analysis identified brain areas where grey matter (GM) volume correlated with the PT score in PD patients. Voxel-based morphometry (VBM) and Tract-Based Spatial Statistics (TBSS) were also used to compare unsteady (PT ≥ 1) and steady (PT = 0) PD patients. Associations between GM volume in regions of interest (ROI) and several clinical features were then investigated using LASSO regression analysis.

RESULTS

PI was present in 44.4% of PD patients. The whole-brain approach identified the bilateral inferior frontal gyrus (IFG) and superior temporal gyrus (STG) as the only regions associated with the presence of postural instability. VBM analysis showed reduced GM volume in fronto-temporal areas (superior, middle, medial and inferior frontal gyrus, and STG) in unsteady compared with steady PD patients, and the GM volume of these regions was selectively associated with the PT score and not with any other motor or non-motor symptom.

CONCLUSIONS

This study demonstrates a significant atrophy of fronto-temporal regions in unsteady PD patients, suggesting that these brain areas may play a role in the pathophysiological mechanisms underlying postural instability in PD. This result paves the way for further studies on postural instability in Parkinsonism.

Diagnostic utility of 7T neuromelanin imaging of the substantia nigra in Parkinson's disease

Parkinson's disease (PD) is a prevalent neurodegenerative disorder that presents a diagnostic challenge due to symptom overlap with other disorders. Neuromelanin (NM) imaging is a promising biomarker for PD, but adoption has been limited, in part due to subpar performance at standard MRI field strengths. We aimed to evaluate the diagnostic utility of ultra-high field 7T NM-sensitive imaging in the diagnosis of PD versus controls and essential tremor (ET), as well as NM differences among PD subtypes. A retrospective case-control study was conducted including PD patients, ET patients, and controls. 7T NM-sensitive 3D-GRE was acquired, and substantia nigra pars compacta (SNpc) volumes, contrast ratios, and asymmetry indices were calculated. Statistical analyses, including general linear models and ROC curves, were employed. Twenty-one PD patients, 13 ET patients, and 18 controls were assessed. PD patients exhibited significantly lower SNpc volumes compared to non-PD subjects. SNpc total volume showed 100% sensitivity and 96.8% specificity (AUC = 0.998) for differentiating PD from non-PD and 100% sensitivity and 95.2% specificity (AUC = 0.996) in differentiating PD from ET. Contrast ratio was not significantly different between PD and non-PD groups (p = 0.07). There was also significantly higher asymmetry index in SNpc volume in PD compared to non-PD cohorts (p < 0.001). NM signal loss in PD predominantly involved the inferior, posterior, and lateral aspects of SNpc. Akinetic-rigid subtype showed more significant NM signal loss compared to tremor dominant subtype (p < 0.001). 7T NM imaging demonstrates potential as a diagnostic tool for PD, including potential distinction between subtypes, allowing improved understanding of disease progression and subtype-related characteristics.

Auto-Classification of Parkinson's Disease with Different Motor Subtypes Using Arterial Spin Labelling MRI Based on Machine Learning

The purpose of this study was to automatically classify different motor subtypes of Parkinson's disease (PD) on arterial spin labelling magnetic resonance imaging (ASL-MRI) data using support vector machine (SVM). This study included 38 subjects: 21 PD patients and 17 normal controls (NCs). Based on the Unified Parkinson's Disease Rating Scale (UPDRS) subscores, patients were divided into the tremor-dominant (TD) subtype and the postural instability gait difficulty (PIGD) subtype. The subjects were in a resting state during the acquisition of ASL-MRI data. The automated anatomical atlas 3 (AAL3) template was registered to obtain an ASL image of the same size and shape. We obtained the voxel values of 170 brain regions by considering the location coordinates of these regions and then normalized the data. The length of the feature vector depended on the number of voxel values in each brain region. Three binary classification models were utilized for classifying subjects' data, and we applied SVM to classify voxels in the brain regions. The left subgenual anterior cingulate cortex (ACC_sub_L) was clearly distinguished in both NCs and PD patients using SVM, and we obtained satisfactory diagnostic rates (accuracy = 92.31%, specificity = 96.97%, sensitivity = 84.21%, and AUCmax = 0.9585). For the right supramarginal gyrus (SupraMarginal_R), SVM distinguished the TD group from the other groups with satisfactory diagnostic rates (accuracy = 84.21%, sensitivity = 63.64%, specificity = 92.59%, and AUCmax = 0.9192). For the right intralaminar of thalamus (Thal_IL_R), SVM distinguished the PIGD group from the other groups with satisfactory diagnostic rates (accuracy = 89.47%, sensitivity = 70.00%, specificity = 6.43%, and AUCmax = 0.9464). These results are consistent with the changes in blood perfusion related to PD subtypes. In addition, the sensitive brain regions of the TD group and PIGD group involve the brain regions where the cerebellothalamocortical (CTC) and the striatal thalamocortical (STC) loops are located. Therefore, it is suggested that the blood perfusion patterns of the two loops may be different. These characteristic brain regions could become potential imaging markers of cerebral blood flow to distinguish TD from PIGD. Meanwhile, our findings provide an imaging basis for personalised treatment, thereby optimising clinical diagnostic and treatment approaches.

Gait and balance in apolipoprotein Ɛ4 allele carriers in older adults and Parkinson's disease

Background

Gait and balance impairments are among the most troublesome and heterogeneous in Parkinson's disease (PD). This heterogeneity may, in part, reflect genetic variation. The apolipoprotein E (APOE) gene has three major allelic variants (ε2, ε3 and ε4). Previous work has demonstrated that older adult (OA) APOE ε4 carriers demonstrate gait deficits. This study compared gait and balance measures between APOE ε4 carriers and non-carriers in both OA and PD.

Methods

334 people with PD (81 APOE ε4 carriers and 253 non-carriers) and 144 OA (41 carriers and 103 non-carriers) were recruited. Gait and balance were assessed using body-worn inertial sensors. Two-way analyses of covariance (ANCOVA) compared gait and balance characteristics between APOE ε4 carriers and non-carriers in people with PD and OA, controlling for age, gender, and testing site.

Results

Gait and balance were worse in people with PD compared to OA. However, there were no differences between APOE ε4 carriers and non-carriers in either the OA or PD group. In addition, there were no significant group (OA/PD) by APOE ε4 status (carrier/non-carrier) interaction effects for any measures of gait or balance.

Conclusions

Although we found expected impairments in gait and balance in PD compared to OA, gait and balance characteristics did not differ between APOE ε4 carriers and non-carriers in either group. While APOE status did not impact gait and balance in this cross-sectional study, future work is needed to determine whether progression of gait and balance deficits is faster in PD APOE Ɛ4 carriers.

Distribution pattern of iron deposition in the basal ganglia of different motor subtypes of Parkinson's disease

OBJECTIVE

The quantitative susceptibility mapping (QSM) technique was used to analyze the distribution pattern of iron deposition in the basal ganglia region of patients with motor subtypes of Parkinson's disease (PD) and to explore the difference in iron content in the basal ganglia region of PD motor subtypes on the major motor symptomatic side.

METHODS

The study included 76 patients with PD and 37 healthy controls (HC). Patients with PD were divided into two groups: postural instability/gait disorder (PIGD)(n = 48), and tremor dominance (TD)(n = 28). We classified patients with PD according to the side of the major motor symptoms as left PIGD (n = 23), left TD (n = 14), right PIGD (n = 25), and right TD (n = 14). All subjects underwent brain magnetic resonance scanning to obtain QSM and susceptibility values in the corresponding regions of interest (ROI).

RESULTS

(1) Compared with the HC, the bilateral SN in the PD-PIGD and TD group showed greater susceptibility values. The susceptibility values in the left CN, bilateral PUT were also greater in the PD-PIGD group than the HC. (2) Compared with the TD, the left PUT susceptibility values were greater in the PIGD group, especially in patients whose major symptomatic side were on the right limb. (3) Correlation analysis showed that in the PD group, bilateral SN was positively correlated with the unified Parkinson's disease rating scale III part scores of the Movement Disorder Society (MDS-UPDRS III) and the Hoehn-Yahr stage. Bilateral dentate nucleus (DN) susceptibility values were significantly positively correlated with TD scores, and left PUT susceptibility values were positively correlated with PIGD scores. The left SN within the PIGD group was positively correlated with the PIGD score.

CONCLUSION

There were different iron deposition patterns in the basal ganglia between the PD-PIGD and TD groups. There also seems to be a difference in iron deposition in PD motor subtypes on different major motor symptom sides.

Speech and gait abnormalities in motor subtypes of de-novo Parkinson's disease

AIM

To investigate the presence and relationship of temporal speech and gait parameters in patients with postural instability/gait disorder (PIGD) and tremor-dominant (TD) motor subtypes of Parkinson's disease (PD).

METHODS

Speech samples and instrumented walkway system assessments were acquired from a total of 60 de-novo PD patients (40 in TD and 20 in PIGD subtype) and 40 matched healthy controls. Objective acoustic vocal assessment of seven distinct speech timing dimensions was related to instrumental gait measures including velocity, cadence, and stride length.

RESULTS

Compared to controls, PIGD subtype showed greater consonant timing abnormalities by prolonged voice onset time (VOT) while also shorter stride length during both normal walking and dual task, while decreased velocity and cadence only during dual task. Speaking rate was faster in PIGD than TD subtype. In PIGD subtype, prolonged VOT correlated with slower gait velocity (r = -0.56, p = 0.01) and shorter stride length (r = -0.59, p = 0.008) during normal walking, whereas relationships were also found between decreased cadence in dual task and irregular alternating motion rates (r = -0.48, p = 0.04) and prolonged pauses (r = -0.50, p = 0.03). No correlation between speech and gait was detected in TD subtype.

CONCLUSION

Our findings suggest that speech and gait rhythm disorder share similar underlying pathomechanisms specific for PIGD subtype.

Cerebellar alterations in Parkinson's disease with postural instability and gait disorders

BACKGROUND

Few studies interrogated the involvement of cerebellum in modulating gait in Parkinson's disease (PD) patients with postural instability and gait disorders (PD-PIGD). This study aimed at assessing cerebellar atrophy and activity alterations during functional MRI (fMRI) gait-simulating motor- and dual-tasks in PD-PIGD.

METHODS

Twenty-one PD-PIGD and 23 healthy controls underwent clinical assessment, structural MRI, and fMRI including a motor-task (foot anti-phase movements) and a dual-task (foot anti-phase movements while counting backwards by threes). Grey matter cerebellar volumes were assessed using SUIT atlas. FMRI activations were extracted from each cerebellar lobule, and we correlated cerebellar and basal ganglia activity.

RESULTS

PD-PIGD patients had reduced volumes of cerebellar motor and non-motor areas relative to controls. During fMRI motor-task, patients showed greater activation of cognitive cerebellar areas (VI and Crus I-II) vs controls. During fMRI dual-task, PD-PIGD patients showed increased activity of cognitive areas (Crus II) and reduced activity of motor areas (I-IV). Cerebellar structural alterations correlated with increased fMRI activity of cerebellar cognitive areas and with lower executive-attentive performance. The increased activity of Crus I during the motor-task correlated with a better motor performance in PD-PIGD. Moreover, the increased activity of cerebellum correlated with a reduced activity of putamen.

CONCLUSIONS

In PD-PIGD, the increased activity of non-motor cerebellar areas during gait-simulating tasks may be a consequence of grey matter atrophy or an attempt to compensate the functional failure of cerebellar motor areas and basal ganglia. Cerebellar MRI metrics are useful to characterize brain correlates of motor and dual-task abilities in PD-PIGD patients.

Clinical and MRI features of gait and balance disorders in neurodegenerative diseases

Gait and balance disorders are common signs in several neurodegenerative diseases such as Parkinson's disease, atypical parkinsonism, idiopathic normal pressure hydrocephalus, cerebrovascular disease, dementing disorders and multiple sclerosis. According to each condition, patients present with different gait and balance alterations depending on the structural and functional brain changes through the disease course. In this review, we will summarize the main clinical characteristics of gait and balance disorders in the major neurodegenerative conditions, providing an overview of the significant structural and functional MRI brain alterations underlying these deficits. We also will discuss the role of neurorehabilitation strategies in promoting brain plasticity and gait/balance improvements in these patients.

Updated Parkinson's disease motor subtypes classification and correlation to cerebrospinal homovanillic acid and 5-hydroxyindoleacetic acid levels

Introduction

Motor classifications of Parkinson's Disease (PD) have been widely used. This paper aims to update a subtype classification using the MDS-UPDRS-III and determine if cerebrospinal neurotransmitter profiles (HVA and 5-HIAA) differ between these subtypes in a cohort from the Parkinson's Progression Marker Initiative (PPMI).

Methods

UPDRS and MDS-UPDRS scores were collected for 20 PD patients. Akinetic-rigid (AR), Tremor-dominant (TD), and Mixed (MX) subtypes were calculated using a formula derived from UPDRS, and a new ratio was developed for subtyping patients with the MDS-UPDRS. This new formula was subsequently applied to 95 PD patients from the PPMI dataset, and subtyping was correlated to neurotransmitter levels. Data were analyzed using receiver operating characteristic models and ANOVA.

Results

Compared to previous UPDRS classifications, the new MDS-UPDRS TD/AR ratios produced significant areas under the curve (AUC) for each subtype. The optimal sensitivity and specificity cutoff scores were ≥0.82 for TD, ≤0.71 for AR, and >0.71 and <0.82 for Mixed. Analysis of variance showed that the AR group had significantly lower HVA and 5-HIAA levels than the TD and HC groups. A logistic model using neurotransmitter levels and MDS-UPDRS-III could predict the subtype classification.

Conclusions

This MDS-UPDRS motor classification system provides a method to transition from the original UPDRS to the new MDS-UPDRS. It is a reliable and quantifiable subtyping tool for monitoring disease progression. The TD subtype is associated with lower motor scores and higher HVA levels, while the AR subtype is associated with higher motor scores and lower 5-HIAA levels.

Bilateral globus pallidus interna deep brain stimulation in Parkinson's disease: Therapeutic effects and motor outcomes prediction in a short-term follow up

Objective

We aimed to compare the motor effect of bilateral globus pallidus interna (GPi) deep brain stimulation (DBS) on motor subtypes of Parkinson's disease (PD) patients and identify preoperative predictive factors of short-term motor outcome.

Methods

We retrospectively investigated bilateral GPi DBS clinical outcomes in 55 PD patients in 1 year follow up. Motor outcome was measured by the Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III before and 1 year after surgery. Clinical outcomes were compared among different motor subtypes. Preoperative predictors of motor outcome were assessed by performing univariate and multivariate linear regression and logistic regression analyses.

Results

At 1 year following implantation, GPi DBS significantly improved the off-medication MDS-UPDRS III scores in all motor subtype cohorts, with prominent improvement in tremor. No significant difference of postoperative motor symptoms changes was found except greater tremor improvement achieved in both the tremor-dominant (TD) and indeterminate (IND) patients compared to the postural instability and gait difficulty (PIGD) patients. High percentage of PIGD patients were weak responders to DBS. Better levodopa responsiveness and more severe tremor predicted greater overall improvement of motor function in the entire cohort. Similarly, both levodopa responsiveness and tremor improvement were confirmed as predictors for motor improvement in PIGD patients.

Conclusion

Bilateral GPi DBS could effectively improve motor outcomes in PD patients regardless of motor subtypes. Both TD and IND patients obtained larger tremor improvement. The intensity of levodopa responsiveness and the severity of tremor could serve as predictors of motor improvement 1 year after GPi DBS.

White matter hyperintensity presence, quantity, and location exhibits no association with motor and non-motor manifestations of PD

INTRODUCTION

Nonspecific areas of brain white matter hyperintensity (WMH) are commonly found in the elderly. Some studies have shown that the presence, quantity, and location of WMHs may be associated with the development of cognitive and motor decline in patients with Parkinson's disease (PD), but the results remain controversial. This study aimed to evaluate the relationship of WMH to motor and non-motor symptoms, including dysautonomia and rapid eye movement sleep behavior disorder (RBD), in patients with PD.

METHODS

Brain magnetic resonance images were acquired from 120 patients diagnosed with PD and analyzed for WMH classification and quantification. Motor symptoms were quantified using sub-scores of the Movement Disorder Society-Unified Parkinson Disease Rating Scale (MDS-UPDRS)-III. Dysautonomia was evaluated by autonomic reactivity tests, and polysomnography was used for the diagnosis of RBD.

RESULTS

Age, total value of the MDS-UPDRS-III tremor sub-score, and the presence of dysautonomia were found to be linearly positively associated. Specifically, the duration of PD was positively associated with rigidity, bradykinesia, axial symptoms, prevalence of dysautonomia, and RBD sub-scores. However, in the multivariate analysis adjusted for variables of interest, no statistical significance was found for any of the models.

CONCLUSION

The presence, quantity, and location of WMH were not associated with the analyzed motor and non-motor manifestations of PD.

Brain network characteristics and cognitive performance in motor subtypes of Parkinson's disease: A resting state fMRI study

INTRODUCTION

Parkinson's disease (PD) is a heterogeneous disorder with great variability in motor and non-motor manifestations. It is hypothesized that different motor subtypes are characterized by different neuropsychiatric and cognitive symptoms, but the underlying correlates in cerebral connectivity remain unknown. Our aim is to compare brain network connectivity between the postural instability and gait disorder (PIGD) and tremor-dominant (TD) subtypes, using both a within- and between-network analysis.

METHODS

This cross-sectional resting-state fMRI study includes 81 PD patients, 54 belonging to the PIGD and 27 to the TD subgroup. Group-level spatial maps were created using independent component analysis. Differences in functional connectivity were investigated using dual regression analysis and inter-network connectivity analysis. An additional voxel-based morphometry analysis was performed to examine if results were influenced by grey matter atrophy.

RESULTS

The PIGD subgroup scored worse than the TD subgroup on all cognitive domains. Resting-state fMRI network analyses suggested that the connection between the visual and sensorimotor network is a potential differentiator between PIGD and TD subgroups. However, after correcting for dopaminergic medication use these results were not significant anymore. There was no between-group difference in grey matter volume.

CONCLUSION

Despite clear motor and cognitive differences between the PIGD and TD subtypes, no significant differences were found in network connectivity. Methodological challenges, substantial symptom heterogeneity and many involved variables make analyses and hypothesis building around PD subtypes highly complex. More sensitive visualisation methods combined with machine learning approaches may be required in the search for characteristic underpinnings of PD subtypes.

Cerebro-cerebellar motor networks in clinical subtypes of Parkinson's disease

Parkinson's disease (PD) patients can be classified in tremor-dominant (TD) and postural-instability-and-gait-disorder (PIGD) motor subtypes. PIGD represents a more aggressive form of the disease that TD patients have a potentiality of converting into. This study investigated functional alterations within the cerebro-cerebellar system in PD-TD and PD-PIGD patients using stepwise functional connectivity (SFC) analysis and identified neuroimaging features that predict TD to PIGD conversion. Thirty-two PD-TD, 26 PD-PIGD patients and 60 healthy controls performed clinical/cognitive evaluations and resting-state functional MRI (fMRI). Four-year clinical follow-up data were available for 28 PD-TD patients, who were classified in 10 converters (cTD-PD) and 18 non-converters (ncTD-PD) to PIGD. The cerebellar seed-region was identified using a fMRI motor task. SFC analysis, characterizing regions that connect brain areas to the cerebellar seed at different levels of link-step distances, evaluated similar and divergent alterations in PD-TD and PD-PIGD. The discriminatory power of clinical data and/or SFC in distinguishing cPD-TD from ncPD-TD patients was assessed using ROC curve analysis. Compared to PD-TD, PD-PIGD patients showed decreased SFC in temporal lobe and occipital lobes and increased SFC in cerebellar cortex and ponto-medullary junction. Considering the subtype-conversion analysis, cPD-TD patients were characterized by increased SFC in temporal and occipital lobes and in cerebellum and ponto-medullary junction relative to ncPD-TD group. Combining clinical and SFC data, ROC curves provided the highest classification power to identify conversion to PIGD. These findings provide novel insights into the pathophysiology underlying different PD motor phenotypes and a potential tool for early characterization of PD-TD patients at risk of conversion to PIGD.

Molecular Imaging in Parkinsonian Disorders—What’s New and Hot?

Highlights

Abstract

Neurodegenerative parkinsonian disorders are characterized by a great diversity of clinical symptoms and underlying neuropathology, yet differential diagnosis during lifetime remains probabilistic. Molecular imaging is a powerful method to detect pathological changes in vivo on a cellular and molecular level with high specificity. Thereby, molecular imaging enables to investigate functional changes and pathological hallmarks in neurodegenerative disorders, thus allowing to better differentiate between different forms of degenerative parkinsonism, improve the accuracy of the clinical diagnosis and disentangle the pathophysiology of disease-related symptoms. The past decade led to significant progress in the field of molecular imaging, including the development of multiple new and promising radioactive tracers for single photon emission computed tomography (SPECT) and positron emission tomography (PET) as well as novel analytical methods. Here, we review the most recent advances in molecular imaging for the diagnosis, prognosis, and mechanistic understanding of parkinsonian disorders. First, advances in imaging of neurotransmission abnormalities, metabolism, synaptic density, inflammation, and pathological protein aggregation are reviewed, highlighting our renewed understanding regarding the multiplicity of neurodegenerative processes involved in parkinsonian disorders. Consequently, we review the role of molecular imaging in the context of disease-modifying interventions to follow neurodegeneration, ensure stratification, and target engagement in clinical trials.

Nigral neuropathology of Parkinson's motor subtypes coincide with circuitopathies: a scoping review

The neuropathological substrates of Parkinson’s disease (PD) patients with motor subtypes tremor-dominance (TD), non-tremor dominance (nTD), postural instability and gait difficulty (PIGD), and akinetic-rigid (AR) are not completely differentiated. While extensive pathological research has been conducted on neuronal tissue of PD patients, data have not been discussed in the context of mechanistic circuitry theories differentiating motor subtypes. It is, therefore, expected that a more specific and tailored management of PD symptoms can be accomplished by understanding symptom-specific neuropathological mechanisms with the detail histology can provide. This scoping review gives an overview of the literature comparing TD and nTD PD motor subtypes by clarify observed pathology with underlying physiological circuitry theories. Studies using an array of pathological examination techniques have shown significant differences between TD and nTD PD subtypes. nTD PD patients show higher neuronal loss, gliosis, extraneuronal melanin deposits, and neuroaxonal dystrophy in multiple subregions of the substantia nigra (SN) related to the overactivity of the indirect motor loop. TD patients show more severe cell loss specifically in medial SN subdivisions, and have damage in the retrorubral field A-8 that projects to the dorsolateral striatum and ventromedial thalamus in the direct motor loop. Pathological studies are consistent with neuroimaging data and support contemporary mechanistic circuitry theories of PD motor symptom genesis. Further multimodal neuroimaging and histological studies are required to validate and expand upon these findings.

Gray and white matter alterations in different predominant side and type of motor symptom in Parkinson's disease

Background

Parkinson's disease (PD) is highly heterogeneous reflected by different affected side of body and type of motor symptom. We aim to explore clinical characteristics and underlying brain structure alterations in PD with different predominant sides and motor types.

Methods

We recruited 161 PD patients and 50 healthy controls (HC). Patients were classified into four subtypes according to their predominant side and motor type: left akinetic/rigid‐dominant (LAR), left tremor‐dominant (LTD), right akinetic/rigid‐dominant (RAR), and right tremor‐dominant (RTD). All participants assessed motor and cognitive performances, then underwent T1‐weighted and diffusion tensor imaging scanning. A general linear model was used to compare neuroimaging parameters among five groups.

Results

Among four PD subtypes, patients of LAR subtype experienced the worst motor impairment, and only this subtype showed worse cognitive performance compared with HC. Compared with HC and other subtypes, LAR subtype showed a significant reduction in cortical thickness of the right caudal‐anterior‐cingulate gyrus and fractional anisotropy of the right cingulum bundle.

Conclusions

We demonstrated that LAR subtype had the worst clinical performance, which the severer damage in the right cingulate region might be the underlying mechanism. This study underscores the importance of classifying PD subtypes based on both the side and type of motor symptom for clinical intervention and research to optimize behavioral outcomes in the future.

Imaging modalities in differential diagnosis of Parkinson’s disease: opportunities and challenges

Background

Parkinson’s disease (PD) diagnosis is yet largely based on the related clinical aspects. However, genetics, biomarkers, and neuroimaging studies have demonstrated a confirming role in the diagnosis, and future developments might be used in a pre-symptomatic phase of the disease.

Main text

This review provides an update on the current applications of neuroimaging modalities for PD diagnosis. A literature search was performed to find published studies that were involved on the application of different imaging modalities for PD diagnosis. An organized search of PubMed/MEDLINE, Embase, ProQuest, Scopus, Cochrane, and Google Scholar was performed based on MeSH keywords and suitable synonyms. Two researchers (TM and JPI) independently and separately performed the literature search. Our search strategy in each database was done by the following terms: ((Parkinson [Title/Abstract]) AND ((“Parkinsonian syndromes ”[Mesh]) OR Parkinsonism [Title/Abstract])) AND ((PET [Title/Abstract]) OR “SPECT”[Mesh]) OR ((Functional imaging, Transcranial sonography [Title/Abstract]) OR “Magnetic resonance spectroscopy ”[Mesh]). Database search had no limitation in time, and our last update of search was in February 2021. To have a comprehensive search and to find possible relevant articles, a manual search was conducted on the reference list of the articles and limited to those published in English.

Conclusion

Early diagnosis of PD could be vital for early management and adequate neuroprotection. Recent neuroimaging modalities such as SPECT and PET imaging using radiolabeled tracers, MRI, and CT are used to discover the disease. By the modalities, it is possible to early diagnose dopaminergic degeneration and also to differentiate PD from others parkinsonian syndromes, to monitor the natural progression of the disease and the effect of neuroprotective treatments on the progression. In this regard, functional imaging techniques have provided critical insights and roles on PD.

Diffusion Measure Changes of Substantia Nigra Subregions and the Ventral Tegmental Area in Newly Diagnosed Parkinson's Disease

Historically, studies have extensively examined the basal ganglia in Parkinson’s disease for specific characteristics that can be observed with medical imaging. One particular methodology used for detecting changes that occur in Parkinson’s disease brains is diffusion tensor imaging, which yields diffusion indices such as fractional anisotropy and radial diffusivity that have been shown to correlate with axonal damage. In this study, we compare the diffusion measures of basal ganglia structures (with substantia nigra divided into subregions, pars compacta, and pars reticula), as well as the diffusion measures of the diffusion tracts that pass through each pair of basal ganglia structures to see if significant differences in diffusion measures can be observed in structures or tracts in newly diagnosed Parkinson’s disease patients. Additionally, we include the ventral tegmental area, a structure connected to various basal ganglia structures affected by dopaminergic neuronal loss and have historically shown significant alterations in Parkinson’s disease, in our analysis. We found significant fractional anisotropy differences in the putamen, and in the diffusion tracts that pass through pairs of both substantia nigra subregions, subthalamic nucleus, parabrachial pigmental nucleus, ventral tegmental area. Additionally, we found significant radial diffusivity differences in diffusion tracts that pass through the parabrachial nucleus, putamen, both substantia nigra subregions, and globus pallidus externa. We were able to find significant diffusion measure differences in structures and diffusion tracts, potentially due to compensatory mechanisms in response to dopaminergic neuronal loss that occurs in newly diagnosed Parkinson’s disease patients.

Premotor antidepressants use differs according to Parkinson's disease subtype: A cohort study

BACKGROUND

Depression is more frequently associated with akinetic-rigid/postural instability gait difficulty subtypes of Parkinson's disease than with tremor-dominant subtype.

OBJECTIVES

The aim of the study is to investigate the frequency of exposure to antidepressant drugs, as proxy of depression, before motor onset according to Parkinson's disease subtypes.

METHOD

Based on a historical cohort design, the exposure to antidepressant drugs before Parkinson's disease motor onset was obtained from the drug prescription database and assessed in the resident population of the Local Healthcare Trust of Bologna (443,117 subjects older than 35 years). Diagnosis of Parkinson's disease and subtype (tremor dominant, non-tremor dominant) at onset were recorded by neurologists and obtained from the "ParkLink Bologna" record linkage system. Exposure to antidepressants was compared both to the general population and between the two subtypes.

RESULTS

From 2006 to 2018, 198 patients had a tremor dominant subtype at onset whereas 450 did not. Comparison with the general population for antidepressant exposure showed an adjusted hazard ratio of 0.86 (95% CI 0.44-1.70) for the tremor dominant subtype and 1.66 (1.16-2.39) for the non-tremor dominant subtype. Comparison of non-tremor dominant with tremor dominant subtypes showed an adjusted odds ratio of 1.86 (1.05-3.95) for antidepressant exposure.

CONCLUSIONS

In our study, non-tremor dominant Parkinson's disease at onset was significantly associated with exposure to antidepressants in comparison to the general population and in comparison with the tremor dominant subtype. These results support the hypothesis of different biological substrates for different Parkinson's disease subtypes even before motor onset.