Tremor Dominant Research Articles

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.

Motor subtypes and clinical characteristics in sporadic and genetic Parkinson's disease groups: analysis of the PPMI cohort.

The extensive clinical variations observed in Parkinson's disease (PD) pose challenges in early diagnosis and treatment initiation. However, genetic research in PD has significantly transformed the clinical approach to its treatment. Moreover, researchers have adopted a subtyping strategy based on homogeneous clinical symptoms to improve clinical diagnosis and treatment approaches. We conducted a study to explore clinical characteristics in genetic PD groups with motor symptom subtyping. Data was driven from the Parkinson's Progression Markers Initiative (PPMI) database. The sporadic PD (sPD) group and the genetic PD group including patients with leucine-rich kinase 2 (LRRK2) or glucosylceramidase β (GBA) mutations were analyzed. Motor subtyping was performed using Movement Disorder Society-Unified Parkinson's disease rating scale (MDS-UPDRS) scores. I-123 FP-CIT SPECT scans were used to calculate specific binding ratios (SBRs) in the caudate and putamen. Clinical symptoms of each group were also compared. MDS-UPDRS III scores were lower in the LRRK2 group, compared with the GBA and sPD group (P < 0.001), but no significant differences in striatal SBRs. The putaminal SBR value of the LRRK2 group was higher than the sPD group (P < 0.05). Within the GBA group, we observed lower SBR values in the postural instability/gait difficulty (PIGD) subtype GBA group compared to the tremor-dominant (TD) subtype GBA group (P < 0.05). The TD subtype GBA group exhibited superior putaminal SBRs compared to the TD subtype sPD group (P < 0.05). The TD subtype LRRK2 group had better putaminal SBR values (P < 0.001) and MDS-UPDRS Part III scores (P < 0.05) compared to the TD sPD group. Our subtyping approach offers valuable insights into the clinical characteristics and progression of different genetic PD subtypes. To further validate and expand these findings, future research with larger groups and long-term follow-up data is needed. The subtyping strategy based on motor symptoms holds promise in enhancing the diagnosis and treatment of genetic PD.

Structural and Functional Alterations of Motor-Thalamus in Different Motor Subtype of Parkinson’s Disease: An Individual Study

This study aimed to investigate the structural and functional alterations occurring within bilateral premotor thalamus (mPMtha) in motor subtypes of Parkinson's disease (PD). Sixty-one individuals with instability and gait difficulty (PIGD) subtype, 60individuals with tremor-dominant (TD) subtype and 66healthy controls (HCs) participated in the study. All participants underwent resting-state functional magnetic resonance imaging (rs-fMRI) and 3D T1-weighted (3DT1) scans. Functional connectivity (FC) analysis and Voxel-based morphometry (VBM) analysis were performed to evaluate the function and volume of mPMtha. Additionally, correlations between motor performance and FC values, volumes were examined separately. Support vector machine (SVM) model based on FC values and thalamic volumes was conducted to assist in the clinical diagnosis of PD motor subtype. Compared toHCs and PIGD, TD subtype showed increased FC between the bilateral mPMtha and left middle occipital gyrus, left inferior parietal lobule (IPL). While PIGD subtype demonstrated decreased FC between right mPMtha and precentral gyrus (PreCG), supramarginal, IPL and superior parietal lobule. FC of bilateral mPMtha with the identified regions were significantly correlated with motor performance scores in PD patients. The SVM classification based on FC values demonstrated a high level of efficiency (AUC=0.874). The volumes of the bilateral mPMtha were indifferent among three groups. We noted distinct FC alterations of mPMtha in TD and PIGD subtypes, and these changes were correlated with motor performance. Furthermore, the machine learning based on statistically significant FC might be served as an alternative approach for automatically classifying PD motor subtypes individually.

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.

Classifying Tremor Dominant and Postural Instability and Gait Difficulty Subtypes of Parkinson's Disease from Full-Body Kinematics.

Characterizing motor subtypes of Parkinson's disease (PD) is an important aspect of clinical care that is useful for prognosis and medical management. Although all PD cases involve the loss of dopaminergic neurons in the brain, individual cases may present with different combinations of motor signs, which may indicate differences in underlying pathology and potential response to treatment. However, the conventional method for distinguishing PD motor subtypes involves resource-intensive physical examination by a movement disorders specialist. Moreover, the standardized rating scales for PD rely on subjective observation, which requires specialized training and unavoidable inter-rater variability. In this work, we propose a system that uses machine learning models to automatically and objectively identify some PD motor subtypes, specifically Tremor-Dominant (TD) and Postural Instability and Gait Difficulty (PIGD), from 3D kinematic data recorded during walking tasks for patients with PD (MDS-UPDRS-III Score, 34.7 ± 10.5, average disease duration 7.5 ± 4.5 years). This study demonstrates a machine learning model utilizing kinematic data that identifies PD motor subtypes with a 79.6% F1 score (N = 55 patients with parkinsonism). This significantly outperformed a comparison model using classification based on gait features (19.8% F1 score). Variants of our model trained to individual patients achieved a 95.4% F1 score. This analysis revealed that both temporal, spectral, and statistical features from lower body movements are helpful in distinguishing motor subtypes. Automatically assessing PD motor subtypes simply from walking may reduce the time and resources required from specialists, thereby improving patient care for PD treatments. Furthermore, this system can provide objective assessments to track the changes in PD motor subtypes over time to implement and modify appropriate treatment plans for individual patients as needed.

Histogram analysis of diffusion kurtosis imaging of deep brain nuclei in Parkinson's disease with different motor subtypes

To evaluate the diagnostic and differential efficacy of diffusion kurtosis imaging (DKI) histogram analysis for different motor subtypes of Parkinson's disease (PD). Seventy PD patients including 40 with postural instability and gait disorder (PIGD) and 30 with tremor-dominant (TD) and 36 healthy controls (HC) were enrolled prospectively and underwent MRI examinations. The regions of interest (ROI) in the deep brain nuclei were delineated and features were extracted on the map of mean kurtosis (MK), axial kurtosis (Ka), and radial kurtosis (Kr), respectively. The differences in histogram features between PD patients and HC and between patients with PIGD and TD were compared. The areas under the curve (AUCs) were calculated to evaluate the diagnostic efficacy of all histogram features. The correlations between histogram features and clinical indicators were evaluated. Some DKI histogram features were significantly different between PD patients and HC, and also different between patients with PIGD and TD (all p<0.05). MK of the substantia nigra pars reticulate (SNprkurtosis), Ka of the substantia nigra pars compacta (SNpc) 50 percentile (SNpcP50), and Kr of SNpc 90th percentile showed the highest AUC for distinguishing patients with PIGD from HC. MK-SNpc 10th percentile, Ka-SNpc 25th percentile, and Kr of the head of the caudate nucleus (CN) 90th percentile had the highest AUC for distinguishing patients with TD from HC. MK of the putamen 10th percentile combined with Ka of the bilateral red nucleus RNkurtosis yielded the highest diagnostic performance with an AUC of 0.762 for distinguishing patients with PIGD from TD. Certain DKI histogram features were correlated with Hoehn-Yahr (H&Y) stage, Mini Mental State Examination (MMSE) score, tremor score, and PIGD score (all p<0.05). DKI histogram analysis was useful to diagnose and discriminate different motor subtypes of PD. Certain DKI histogram features correlated with clinical indicators.

Autonomic function and motor subtypes in Parkinson’s disease: a multicentre cross-sectional study

Autonomic symptoms (AS) are critical in Parkinson’s disease (PD). We aimed to determine the relative significance of clinical factors allowing predictions about incidence of AS, and examine AS profiles among PD patients by motor subtype and its relation to AS. The cross-sectional data of a multicentre sample, including 714 PD patients and 194 healthy controls from Parkinson’s Progression Marker Initiative study and Pingchan granule study were analyzed, stratified by PD subtypes [postural instability and gait disturbances (PIGD), tremor dominant (TD), and indeterminate] and domain autonomic dysfunction. Compared with healthy controls, PD patients scored higher in the total Scales for Outcomes in Parkinson's Disease-Autonomic dysfunction score and in several domain scores in particular, and there was a significant overlap in domain AS. Risk factors of individual domain autonomic dysfunction were heterogeneous. PIGD and indeterminate were the predominant subtypes in pupillomotor and thermoregulatory symptoms. TD and indeterminate were more likely to suffer from cardiovascular problem. The odd in sexual dysfunction was significant for PIGD. Gastrointestinal and urinary symptoms seemed not to be associated with a specific subtype. Our study demonstrated that AS were highly heterogeneous and 3 subtypes differed in autonomic performance, providing clues to understand mechanisms underlying AS in PD.

Do motor subtypes of Parkinson’s disease impact the learning of motor tasks?

BACKGROUND:Previous studies have demonstrated that people with Parkinson's disease (PD) can acquire postural control skills even with the degeneration of motor areas responsible for consolidation of the representation regarding the learned motor skill in long-term memory. However, these findings have not considered the PD motor subtypes – tremor-dominant (TD), and postural instability and gait difficulty (PIGD). Although there is considerable heterogeneity in motor and non-motor symptoms between TD and PIGD, no study has addressed the effect of the PD subtype on learning postural control skills. AIM:We investigated the influence of PD motor subtypes on the learning of tasks with different postural control demands. METHOD:Fourteen individuals with PD (7 TD, 7 PIGD) practiced four motor tasks with high postural and cognitive demands. Participants completed 13 one-hour sessions (2x/week for 7 weeks). We considered the first and last practice sessions, pre-test and post-test, respectively. Also, we conducted one-week and one-month retention tests to assess performance persistence (motor learning). We assessed motor performance through the scores achieved on each motor task. RESULTS:Both groups demonstrated improvement in performance during the acquisition phase. However, the TD group outperformed the PIGD group in all motor tasks, despite both groups showing improvement in motor performance when comparing the results of pre-test with the post-test, and the improved performance was maintained in retention tests. The performance differences between groups are dissipated during consolidation, and they did not directly affect motor learning. INTERPRETATION: The TD and PIGD motor subtypes learned postural control tasks with different motor and cognitive demands.

IgA-Biome Profiles Correlate with Clinical Parkinson's Disease Subtypes.

Parkinson's disease is a heterogeneous neurodegenerative disorder with distinctive gut microbiome patterns suggesting that interventions targeting the gut microbiota may prevent, slow, or reverse disease progression and severity. Because secretory IgA (SIgA) plays a key role in shaping the gut microbiota, characterization of the IgA-Biome of individuals classified into either the akinetic rigid (AR) or tremor dominant (TD) Parkinson's disease clinical subtypes was used to further define taxa unique to these distinct clinical phenotypes. Flow cytometry was used to separate IgA-coated and -uncoated bacteria from stool samples obtained from AR and TD patients followed by amplification and sequencing of the V4 region of the 16 S rDNA gene on the MiSeq platform (Illumina). IgA-Biome analyses identified significant alpha and beta diversity differences between the Parkinson's disease phenotypes and the Firmicutes/Bacteroides ratio was significantly higher in those with TD compared to those with AR. In addition, discriminant taxa analyses identified a more pro-inflammatory bacterial profile in the IgA+ fraction of those with the AR clinical subclass compared to IgA-Biome analyses of those with the TD subclass and with the taxa identified in the unsorted control samples. IgA-Biome analyses underscores the importance of the host immune response in shaping the gut microbiome potentially affecting disease progression and presentation. In the present study, IgA-Biome analysis identified unique proinflammatory microbial signature in the IgA+ fraction of those with AR that would have otherwise been undetected using conventional microbiome analysis approaches.

Structural and functional differences of the thalamus between drug-naïve Parkinson's disease motor subtypes.

The thalamus is an integrative hub of motor circuits in Parkinson's disease (PD). This study aimed to investigate the alterations of structure and functional connectivity (FC) of the thalamic subregions in the tremor-dominant (TD) subtype and the postural instability and gait difficulty (PIGD) subtype in PD. A total of 59 drug-naïve patients (24 TD and 35 PIGD) and 37 healthy controls were recruited. The volumes of the thalamus and the thalamic subregions were calculated using FreeSurfer. Functional connectivity (FC) analysis of the resting-state functional MRI (rsfMRI) was conducted on the thalamic subregions. Finally, the altered structure and FC were used for correlation analysis with clinical motor scores and for further motor subtypes differentiation. The volumes of the left posterior parietal thalamus (PPtha) in TD patients were significantly lower than those of PIGD patients. Compared with PIGD patients, TD patients exhibited higher FC between the thalamic subregions, the left middle temporal gyrus (MTG), the right dorsolateral superior frontal gyrus (SFGdl), the left middle occipital gyrus (MOG), and the right superior temporal gyrus (STG). Compared with HCs, TD patients showed higher FC between the thalamic subregions and the right SFGdl, as well as the left MOG. Compared with HCs, PIGD patients showed lower FC between the thalamic subregions and the left MTG. In addition, the altered FC was closely related to clinical symptoms and performed high-discriminative power in differentiating the motor subtypes. Increased FC between the thalamic subregions and the sensory cortices in TD patients may indicate a better compensatory capacity for impairment of sensory information integration than that in PIGD patients. The altered FC between the thalamus and the MTG was a potential biomarker for the distinction of the PD motor subtypes.

Clinical Symptoms Influencing Parkinson's Patients' Quality of Life in Latvia: A Single-Center Cohort Study.

Background and Objectives: Parkinson's disease (PD) is a chronic, progressive illness with a profound impact on health-related quality of life, and it is crucial to know what factors influence the quality of life throughout the course of the disease. This study aimed to evaluate PD patients' motor and non-motor symptoms to compare symptom severity between PD clinical phenotypes and to assess the impact of disease symptoms on quality of life in a cohort of Latvian patients. Materials and Methods: We evaluated 43 patients with Parkinson's disease. Fourteen patients had tremor dominant (TD) PD, twenty-five patients had postural instability/gait difficulty (PIGD), and four patients had a mixed phenotype. Results: The patients' mean age was 65.21 years, and the disease's mean duration was 7 years. The most common non-motor symptoms were fatigue (95.3%), sleep disturbance (83.7%), daytime sleepiness (83.7%), and pain and other sensations (81.4%). PIGD patients had a higher prevalence of depressed mood, daytime sleepiness, constipation, lightheadedness on standing, cognitive impairment, and severe gastrointestinal and urinary disturbances (as assessed using the SCOPA-AUT domains) compared with TD patients. A high prevalence of fatigue was assessed in both disease subtypes. Health-related quality of life significantly statistically correlated with MDS-UPDRS parts III and IV (r = 0.704), the Hoehn and Yahr scale (r = 0.723), as well as the SCOPA-AUT scale's gastrointestinal (r = 0.639), cardiovascular (r = 0.586), thermoregulatory (r = 0.566) and pupillomotor domains (r = 0.597). Conclusions: The severity of motor symptoms, as well as non-motor symptoms, such as fatigue, apathy, sleep problems and daytime sleepiness, pain, and disturbances in gastrointestinal and cardiovascular function, negatively affect PD patients' health-related quality of life. Thermoregulatory and pupillomotor symptoms also significantly affect PD patients' well-being.

β Oscillations of Dorsal STN as a Potential Biomarker in Parkinson's Disease Motor Subtypes: An Exploratory Study.

Parkinson's disease (PD) can be divided into postural instability and difficult gait (PIGD) and tremor dominance (TD) subtypes. However, potential neural markers located in the dorsal ventral side of the subthalamic nucleus (STN) for delineating the two subtypes of PIGD and TD have not been demonstrated. Therefore, this study aimed to investigate the spectral characteristics of PD on the dorsal ventral side. The differences in the β oscillation spectrum of the spike signal on the dorsal and ventral sides of the STN during deep brain stimulation (DBS) were investigated in 23 patients with PD, and coherence analysis was performed for both subtypes. Finally, each feature was associated with the Unified Parkinson's Disease Rating Scale (UPDRS). The β power spectral density (PSD) in the dorsal STN was found to be the best predictor of the PD subtype, with 82.6% accuracy. The PSD of dorsal STN β oscillations was greater in the PIGD group than in the TD group (22.17% vs. 18.22%; p < 0.001). Compared with the PIGD group, the TD group showed greater consistency in the β and γ bands. In conclusion, dorsal STN β oscillations could be used as a biomarker to classify PIGD and TD subtypes, guide STN-DBS treatment, and relate to some motor symptoms.

Phenotyping Motor-subtypes of Parkinsonism from Full-body Kinematics using Machine Learning (P6-11.007)

<h3>Objective:</h3> The purpose of this study is to use whole-body kinematics data during walking to accurately identify motor subtypes of Parkinson’s disease (PD) and parkinsonism. <h3>Background:</h3> Two major motor subtypes of PD have been described, Postural Instability and Gait Disorder (PIGD) and Tremor Dominant (TD), which differ in the disease prognosis. Prior studies have explored quantifying motor subtypes via gait analysis, which lacks data for whole-body movements that are required when analyzing an entire gait cycle. In this study, we measure whole-body kinematics while walking, which is then analyzed to classify PIGD vs. TD subtypes using machine learning (ML) models. <h3>Design/Methods:</h3> The whole-body kinematic marker time series were collected from 57 patients (including 5 patients with atypical parkinsonism) while walking in off medication state using a motion capture system from 2015 to 2017. From all marker kinematics data, we extracted various features beyond gait-related features, including time series and spectral features. Then, ML models were used to classify the extracted features into the corresponding motor subtypes assessed with Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS). <h3>Results:</h3> Compared to the clinically assessed motor subtypes, our model classified whole-body kinematics while walking with a 97.0% F1 score, which significantly outperformed the gait-based analysis which showed a 55.8% F1 score. Both upper and lower body movements were found to be useful indicators to distinguish between PIGD and TD. <h3>Conclusions:</h3> Our findings strongly supported our hypothesis that accurately quantifying motor subtypes requires more than gait-related or lower-body movement features that are typically used in previous work. This feature analysis may lead to novel hypotheses for fine-grained upper-body motion phenotypes related to motor subtypes. More importantly, our techniques can help monitor changes in motor subtypes for guiding appropriate intervention through objective quantification of walking movements. <b>Disclosure:</b> The institution of an immediate family member of Mr. Gong has received research support from National Science Foundation. Dr. Kwon has nothing to disclose. Prof. Clifford has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Alivecor. Prof. Clifford has stock in Mindchild Medical. Prof. Clifford has received intellectual property interests from a discovery or technology relating to health care. Prof. Clifford has received publishing royalties from a publication relating to health care. Dr. Esper has received research support from Centers for Disease Control and Prevention. Dr. Esper has received publishing royalties from a publication relating to health care. Dr. Factor has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Acorda. Dr. Factor has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Sunovion. Dr. Factor has received personal compensation in the range of $5,000-$9,999 for serving as a Consultant for Alterity. Dr. Factor has received personal compensation in the range of $10,000-$49,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Lundbeck. Dr. Factor has received personal compensation in the range of $5,000-$9,999 for serving on a Scientific Advisory or Data Safety Monitoring board for Biogen. The institution of Dr. Factor has received research support from Impax. The institution of Dr. Factor has received research support from Biohaven. The institution of Dr. Factor has received research support from Sunovion. The institution of Dr. Factor has received research support from Vaccinex. The institution of Dr. Factor has received research support from Voyager. The institution of Dr. Factor has received research support from Neurocrine. The institution of Dr. Factor has received research support from US World Meds. The institution of Dr. Factor has received research support from Addex. The institution of Dr. Factor has received research support from Prelinia. The institution of Dr. Factor has received research support from Medtronics. The institution of Dr. Factor has received research support from Boston Scientific. Dr. Factor has received publishing royalties from a publication relating to health care. Dr. Factor has received publishing royalties from a publication relating to health care. Dr. Factor has received publishing royalties from a publication relating to health care. Dr. Factor has received publishing royalties from a publication relating to health care. Dr. McKay has received personal compensation in the range of $500-$4,999 for serving as a Consultant for Biocircuit Technologies. The institution of Dr. McKay has received research support from NIH. The institution of Dr. McKay has received research support from the McCamish Foundation.

Updated Parkinson's disease motor subtypes classification and correlation to CSF HVA and 5-HIAA levels (P3-11.005)

<h3>Objective:</h3> To update a motor subtypes classification using the MDS-UPDRS and determine if CSF neurotransmitter profiles (HVA and 5-HIAA) are different between MDS-UPDRS subtypes in a cohort from the Parkinson9s Progression Marker Initiative (PPMI). <h3>Background:</h3> Schiess <i>et al</i> designed a UPDRS motor classification of Parkinson9s Disease (PD) that has been widely used, but in the last decade, the field has moved towards the use of the MDS-UPDRS. <h3>Design/Methods:</h3> 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 UPDRS formula, and a new ratio was developed for 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. <h3>Results:</h3> Compared to previous UPDRS classifications, the new MDS-UPDRS AR/TD ratios produced significantly different areas under the curves (AUC). The optimal sensitivity and specificity cutoff scores were ≥0.82 for TD, ≤0.71 for AR classifications and Mixed &gt;0.71 and &lt;0.82. Analysis of variance showed significant differences in 5-HIAA levels between the HC and AR group. Logistic models utilizing neurotransmitter levels and MDS-UPDRS motor scores showed significant AUCs for MDS-UPDRS classifications. <h3>Conclusions:</h3> This MDS-UPDRS motor subtype classification system provides a method to transition from the original UPDRS to the newer MDS-UPDRS and offers a reliable and quantifiable tool for monitoring disease progression that is supported by neurotransmitter levels. <b>Disclosure:</b> Dr. Suescun has nothing to disclose. Dr. Adams has stock in Medtronic. Dr. Block has nothing to disclose. Dr. Tharp has nothing to disclose. The institution of Prof. Ellmore has received research support from NIMH. Dr. Schiess has nothing to disclose.

Altered Cerebral Vasoreactivity on Transcranial Color-Coded Sonography Related to Akinetic-Rigid Phenotype of Parkinson's Disease: Interim Analysis of a Cross-Sectional Study.

A correlation between worse functional outcomes in Parkinson's disease (PD) patients with cerebrovascular disease (CVD) or the Akinetic-rigid phenotype has been argued in recent studies. We aimed to evaluate the association of cerebral hemodynamics impairments, assessed by Transcranial Color-coded Doppler sonography (TCCS), on PD patients with different phenotypes of the disease and with risk factors for CVD. Idiopathic PD patients (n = 51) were divided into motor subtypes: Akinetic-rigid (AR) (n = 27) and Tremor-dominant (TD) (n = 24) and into two groups regarding vascular risk factors: when ≥2 were present (PDvasc) (n = 18) and <2 (PDnvasc) (n = 33). In a parallel analysis, the Fazekas scale on brain magnetic resonance imaging (MRI) was applied to a sample to assess the degree of leukoaraiosis. TCCS examinations were prospectively performed obtaining middle cerebral artery Mean Flow Velocities (Vm), Resistance Index (RI), and Pulsatility Index (PI). The Breath-Holding Index (BHI) was calculated to assess cerebrovascular reactivity (cVR). Standardized functional scales were administered (UPDRS III and Hoehn&Yahr). The phenotype groups were similar in age, disease duration and demographic parameters, but there were significantly higher H&Y scores than TD group. cVR was impaired in 66.7% of AR vs. 37.5% of TD. AR group exhibited lower BHI (0.53 ± 0.31 vs. 0.91 ± 0.62; p = 0.000), lower Vm after apnea (44.3 ± 9.0 cm/s vs. 53.4 ± 11.4 cm/s; p = 0.003), higher PI (0.91 ± 0.26 vs. 0.76 ± 0.12; p = 0.000) and RI (0.58 ± 0.11 vs. 0.52 ± 0.06; p = 0.021). PDvasc group showed higher PI (0.98 vs. 0.76; p = 0.001) and higher frequency of altered cVR (72.2% vs. 42.2%; p = 0.004). There was a significant predominance of higher values on Fazekas scale in the PDvasc group. We found no difference between the Fazekas scale when comparing motor subtypes groups but there was a trend toward higher scores in the AR phenotype. TCCS, a cost-effective method, displayed impaired cVR in Parkinsonian patients with risk factors for CVD with higher degree of MRI leukoaraiosis. PD patients with the AR disease phenotype also presented impaired cVR on TCCS and greater functional impairment, although with just a trend to higher scores on MRI Fazekas.

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

ObjectiveThe 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. MethodsThe 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. ConclusionThere 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.

Cerebrospinal fluid alpha-synuclein, amyloid beta, total tau, and phosphorylated tau in tremor-dominant Parkinson's disease.

Protein misfolding within specific brain regions is a common characteristic of neurodegenerative diseases, such as Alzheimer's disease and Parkinson's disease (PD). Therefore, a common term often used for these disorders is "proteinopathy". Currently, there has been increasing attention toward the overlap of pathogenesis between proteinopathies. We aimed to explore the cross-sectional and longitudinal level of the CSF α-synuclein (α-syn), amyloid βeta (Aβ1-42), total tau (t-tau), and phosphorylated tau (p-tau) in PD subjects with tremor dominant (TD) and a non-tremor dominant (nonTD) subtype from the Parkinson Progression Markers Initiative (PPMI). We enrolled 411 early-stage PD patients and 187 healthy controls (HCs) from the PPMI. We compared the level of CSF biomarkers at four time points including baseline, 6months, 1year, and 2years. To investigate longitudinal changes in CSF proteins within each group, we used linear mixed models. The level of CSF biomarkers was significantly lower in PD patients compared to HCs at any visit. Moreover, there was no statistically significant difference in the level of CSF α-syn, Aβ1-42, t-tau, and p-tau between PD-TD and PD-nonTD. Longitudinal analysis showed significant CSF α-syn reduction after one year from baseline in PD-TD patients (P = 0.047). Also, there was a significant reduction in the level of CSF Aβ1-42 after two years in PD-nonTD patients but not HCs and PD-TD (P = 0.033). Our results indicate that different patterns in longitudinal changes of CSF biomarkers could be due to different pathophysiological mechanisms involved in each PD motor subtype.

Clinical features of minor hallucinations in different phenotypes of Parkinson's disease: A cross-sectional study.

Minor hallucinations (MHs) are the most common psychiatric symptom associated with Parkinson's disease (PDPsy), but little is known about their characteristics in different motor phenotypes, especially postural instability gait difficulty (PIGD). The aim of this study was to explore the clinical features of MHs in different subtypes of PD. In this cross-sectional study, 213 patients with Parkinson's disease (PD) were recruited, and the data obtained included comprehensive demographics, motor subtypes, clinical scale scores, and MH contents. Motor subtypes were classified as tremor-dominant (TD), PIGD or indeterminate according to Stebbins' method. A total of 213 PD patients were included: 90 (42.3%) TD patients, 98 (46.0%) PIGD patients and 25 (11.7%) indeterminate. In total, 70 (32.9%) patients experienced MHs. Compared to patients with the TD phenotype, we found that patients with the PIGD phenotype had more severe motor and nonmotor symptoms. They also had a higher incidence of visual illusions (VIs) and a shorter MH latency. Our study demonstrated that compared to patients with the TD phenotype, patients with the PIGD phenotype had a higher incidence of MHs, especially VIs, which may lead to a higher incidence of visual hallucinations (VHs). They also had a shorter latency of MHs than patients with the TD phenotype, suggesting an earlier onset of MHs and a worse prognosis.

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

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

Abnormal cerebellum connectivity patterns related to motor subtypes of Parkinson’s disease

Cerebellar dysfunction may substantially contribute to the clinical symptoms of Parkinson’s disease (PD). The role of cerebellar subregions in tremors and gait disturbances in PD remains unknown. To investigate alterations in cerebellar subregion volumes and functional connectivity (FC), as well as FC between the dentate nucleus (DN) and ventral lateral posterior nucleus (VLp) of the thalamus, which are potentially involved in different PD motor subtypes. We conducted morphometric and resting-state functional connectivity analyses in various cerebellar subregions in 22 tremor-dominant (TD)-PD and 35 postural instability gait difficulty dominant (PIGD)-PD patients and 38 sex- and age-matched healthy controls (HCs). The volume and FC alterations in various cerebellar subregions and the neural correlates of these changes with the clinical severity scores were investigated. The PIGD-PD group showed greater FC between the right motor cerebellum (CBMm) and left postcentral gyrus than the HC group, and a higher FC was associated with less severe PIGD symptoms. In contrast, the TD-PD group had decreased FC between the right DN and left VLp compared with the PIGD-PD and HC groups, and lower FC was associated with worse TD symptoms. Furthermore, the PIGD-PD group had higher FC between the left DN and left inferior temporal gyrus than the TD-PD group. Morphometric analysis revealed that the TD-PD group showed a significantly higher volume of left CBMm than the HC group. Our findings point to differential alteration patterns in cerebellar subregions and offer a new perspective on the pathophysiology of motor subtypes of PD.