Parkinson's Disease Motor Subtypes Research Articles

High correlation of quantitative susceptibility mapping and echo intensity measurements of nigral iron overload in Parkinson's disease.

Quantitative susceptibility mapping (QSM) and transcranial sonography (TCS) offer proximal evaluations of iron load in the substantia nigra. Our prospective study aimed to investigate the relationship between QSM and TCS measurements of nigral iron content in patients with Parkinson's disease (PD). In secondary analyses, we wanted to explore the correlation of substantia nigra imaging data with clinical and laboratory findings. Eighteen magnetic resonance imaging and TCS examinations were performed in 15 PD patients at various disease stages. Susceptibility measures of substantia nigra were calculated from referenced QSM maps. Echogenicity of substantia nigra on TCS was measured planimetrically (echogenic area) and by digitized analysis (echo-intensity). Iron-related blood serum parameters were measured. Clinical assessments included the Unified PD Rating Scale and non-motor symptom scales. Substantia nigra susceptibility correlated with echogenic area (Pearson correlation, r = 0.53, p = 0.001) and echo-intensity (r = 0.78, p < 0.001). Individual asymmetry indices correlated between susceptibility and echogenic area measurements (r = 0.50, p = 0.042) and, more clearly, between susceptibility and echo-intensity measurements (r = 0.85, p < 0.001). Substantia nigra susceptibility (individual mean of bilateral measurements) correlated with serum transferrin saturation (Spearman test, r = 0.78, p < 0.001) and, by trend, with serum iron (r = 0.69, p = 0.004). Nigral echogenicity was not clearly related to serum values associated with iron metabolism. Susceptibility and echogenicity measurements were unrelated to PD duration, motor subtype, and severity of motor and non-motor symptoms. The present results support the assumption that iron accumulation is involved in the increase of nigral echogenicity in PD. Nigral echo-intensity probably reflects ferritin-bound iron, e.g. stored in microglia.

Multi-modality radiomics of conventional T1 weighted and diffusion tensor imaging for differentiating Parkinson’s disease motor subtypes in early-stages

This study aimed to develop and validate a multi-modality radiomics approach using T1-weighted and diffusion tensor imaging (DTI) to differentiate Parkinson's disease (PD) motor subtypes, specifically tremor-dominant (TD) and postural instability gait difficulty (PIGD), in early disease stages. We analyzed T1-weighted and DTI scans from 140 early-stage PD patients (70 TD, 70 PIGD) and 70 healthy controls from the Parkinson's Progression Markers Initiative database. Radiomics features were extracted from 16 brain regions of interest. After harmonization and feature selection, four machine learning classifiers were trained and evaluated for both three-class (HC vs TD vs PIGD) and binary (TD vs PIGD) classification tasks. The light gradient boosting machine (LGBM) classifier demonstrated the best overall performance. For the three-class classification, LGBM achieved an accuracy of 85% and an area under the receiver operating characteristic curve (AUC) of 0.94 using combined T1 and DTI features. In the binary classification task, LGBM reached an accuracy of 95% and AUC of 0.95. Key discriminative features were identified in the Thalamus, Amygdala, Hippocampus, and Substantia Nigra for the three-group classification, and in the Pallidum, Amygdala, Hippocampus, and Accumbens for binary classification. The combined T1 + DTI approach consistently outperformed single-modality classifications, with DTI alone showing particularly low performance (AUC 0.55–0.62) in binary classification. The high accuracy and AUC values suggest that this approach could significantly improve early diagnosis and subtyping of PD. These findings have important implications for clinical management, potentially enabling more personalized treatment strategies based on early, accurate subtype identification.

Causal associations between Helicobacter Pylori infection and the risk and symptoms of Parkinson's disease: a Mendelian randomization study.

Increasing evidence suggests an association between Helicobacter pylori (HP) infection and Parkinson's disease (PD) and its clinical manifestations, but the causal relationship remain largely unknown. To investigate the causal relationship between HP infection and PD risk, PD symptoms, and secondary parkinsonism, we conducted two-sample Mendelian randomization (MR). We obtained summary data from genome-wide association studies for seven different antibodies specific to HP proteins and five PD-related phenotypes. The inverse-variance weighted (IVW), weighted median, weighted mode, and MR-Egger methods were used to assess the causal relationships. Sensitivity analyses were performed to examine the stability of the MR results and reverse MR analysis was conducted to evaluate the presence of reverse causality. Genetically predicted HP antibodies were not causally associated with an increased risk of PD. However, HP cytotoxin-associated gene-A (CagA) and outer membrane protein (OMP) antibody level were causally associated with PD motor subtype (tremor to postural instability/gait difficulty score ratio; β = -0.16 and 0.46, P = 0.002 and 0.048, respectively). HP vacuolating cytotoxin-A (VacA) antibody level was causally associated with an increased risk of PD dementia [odds ratio (OR) = 1.93, P = 0.040]. Additionally, HP OMP antibody level was identified as a risk factor for drug-induced secondary parkinsonism (OR = 2.08, P = 0.033). These results were stable, showed no evidence of heterogeneity or directional pleiotropy, and no evidence of a reverse causal relationship. Our findings indicate that HP infection does not increase the risk of PD, but contributes to PD motor and cognitive symptoms. Different types of HP antibodies affect different symptoms of PD. Eradication of HP infection may help modulate and improve symptoms in PD patients.

Resting-state functional connectivity of the occipital cortex in different subtypes of Parkinson's disease.

To examine whether functional connectivity (FC) of the occipital gyrus differs between patients with Parkinson's disease (PD) motor subtypes and healthy controls (HCs). We enrolled 30 PD patients exhibiting tremor dominance (TD), 43 PD patients with postural instability and gait disturbance (PIGD), and 42 HCs. The occipital gyrus was partitioned into six areas of interest, as seed points, via the Anatomical Automatic Labeling template to compare the FC of the three groups and analyze the relationship of FC with clinical scales. Compared with the PIGD group, the TD group showed increased FC between the left superior occipital gyrus (SOG.L) and right median cingulate and paracingulate gyri (DCG.R)/right paracentral lobule/bilateral inferior parietal, but supramarginal and angular gyri; the left middle occipital gyrus (MOG.L) and left posterior cingulate gyrus (PCG.L); the MOG.R and SOG.L/right calcarine fissure and surrounding cortex/DCG.R/PCG.L/right cuneus; the left inferior occipital gyrus (IOG.L) and right caudate nucleus; and the IOG.R and PCG.L. Differentiated FC between the occipital gyrus and other brain areas within the PD motor subtypes, which may serve as neural markers to distinguish between patients with TD and PIGD PD.

CHRONOTYPE AND DAILY FUNCTIONING OF PATIENTS WITH DIFFERENT MOTOR SUBTYPES OF PARKINSON DISEASE

Introduction. Sleep and circadian rhythm disturbances can occur at any stage of Parkinson disease (PD) and significantly affect quality of life. Chronotypes of patients with PD are associated with different phenotypes, in particular with the motor subtype. Thus, we hypothesized that patients with different motor subtypes of PD may have differences in the distribution of chronotypes and patterns of daily activity. Methods and materials. We conducted clinical research on the basis of the Centre for Parkinson Disease and Neurodegenerative Diseases of the Department of Neurological Diseases of Poltava State Medical University. PD was verified according to the recommendations of the International Movement Disorders and Parkinson's Disease Society. The motor subtype of PD was determined by the Stebbin method, which is based on the calculation of the Stebbins coefficient by the sum of the Unified PD Rating Scale scores. The examined patients were divided into 3 groups according to the motor subtype of PD: group 1 (n = 38) - patients with PD subtype with the predominance of postural instability and gait disorders (PIGD); group 2 (n = 26) - patients with PD subtype with the predominance of tremor and mixed subtype; control group (n = 30) - conditionally healthy individuals without CNS lesions. Circadian patterns were analyzed using the Munich Chronotype Questionnaire (MCTQ). Results. It was found that in PD patients sleep onset and time of getting out of bed was later (p&lt;0.001 and p=0.042, respectively), sleep latency was longer (p&lt;0.001), sleep duration was shorter (p=0.001), the mid-sleep corresponded to a later time (p&lt;0.001). Patients with the PIGD subtype had a later time of getting out of bed (p=0.038), longer sleep inertia (p&lt;0.001), shorter sleep duration (p&lt;0.001), and later mid-sleep time (p=0.028). We have shown the tendency of patients with PD, mostly in the PIGD subtype, to later chronotypes (p&lt;0.001). Light exposure indirectly moderately correlated with mid-sleep in all study groups. It was found that both the motor subtype (p&lt;0.001) and the level of light exposure during the day (p&lt;0.001) statistically significantly affect the mid-sleep. Conclusion. Thus, we have found that patients with PD differ from age-matched controls without neurodegenerative diseases by chronotype and circadian pattern of functioning. The motor subtype of the disease is associated with circadian differences, namely, the PIGD subtype is associated with shorter sleep duration, a predisposition to a later chronotype, and longer sleep inertia.

Exploring obstructive sleep apnea and sleep architecture in Parkinson's disease motor subtypes

IntroductionParkinson's disease (PD) can be divided into motor subtypes: postural instability/gait difficulty (PIGD), tremor dominant, and indeterminate. This study aimed to assess differences in sleep structure and obstructive sleep apnea (OSA) between the PIGD and non-PIGD subtypes. MethodsPD participants with or without OSA (defined as apnea-hypopnea index (AHI) ≥ 15 events/hour on overnight polysomnography) were included. Patients were separated into two groups: PIGD and non-PIGD. Linear regression was used to explore differences in sleep, AHI, and other respiratory parameters between groups (adjusted for variables determined a priori). Logistic regression adjusted for the same variables was used to determine if the proportion of patients with OSA differed across groups. Subset analyses were performed: subset 1 excluding patients on psychoactive medication; subset 2 excluding patients taking levodopa or dopaminergic agonists (DAs) at nighttime and subset 3 excluding patients on either of the abovementioned drugs. Results146 participants were studied. The non-PIGD group had less N3 sleep compared to the PIGD group (12.4% vs 16.9% p = 0.06), reaching significance in subsets 1 and 3. The AHI was significantly lower in the PIGD group (p = 0.047), including when medication effects were removed (p < 0.05). OSA was more frequent in the non-PIGD group, but only significantly in subset 3 (adjusted OR 0.3, p = 0.04). ConclusionOSA may be more severe in non-PIGD subtypes, and more frequent, in a subset free of psychoactive medication, and of levodopa and DAs, possibly owing to motor complications and dyskinesia. Future studies are required to confirm this.

18F-FP-DTBZ PET/CT detectable associations between monoaminergic depletion in the putamen with rigidity and the pallidus with tremor in Parkinson's disease

IntroductionThe motor subtypes of Parkinson's disease (PD) are widely accepted and implemented. However, the motor subtypes have been thought to represent different stages of PD recently because some patients experience tremor-dominant (TD) conversion to the non-tremor-dominant subtype, such as postural instability–gait difficulty (PIGD). In this study, we explore the monoaminergic denervation features of the striatal and extra-striatal areas in patients with different subtypes of PD with 18F-9-fluoropropyl-(+)-dihydrotetrabenazine (18F-FP-DTBZ) PET/CT. MethodsSixty-five patients diagnosed with PD were included and classified as TD (n = 25) and PIGD (n = 40). We evaluated the difference of monoaminergic features of each subregion of brain between motor subtypes of PD, as well as associations between these features and Parkinsonian motor symptoms. ResultsThe striatal standardized uptake value ratios (SUVR) showed that dopaminergic disruption of patients with PIGD was more symmetrical in the posterior ventral putamen (p < 0.001) and more severe in the ipsilateral posterior dorsal putamen (p < 0.001 corrected) compared with that of patients with TD. The severity of PIGD scores was associated with striatal dopaminergic depletion, while tremor was associated with monoaminergic changes in extra-striatal areas, including pallidus, thalamus, and raphe nuclie. ConclusionThese results indicate that patients with different motor subtypes may have different underlying mechanisms of PD pathogenesis. Therefore, accurate diagnosis of PD subtypes can aid prognosis evaluation and treatment decision-making.

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.

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.

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.

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.

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.

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.

Introversion and Neuroticism in Akinetic-Rigid Parkinson's Disease: Association With Frontal-Executive Dysfunction.

Personality changes have often been reported among people with Parkinson's disease (PD); however, no studies have investigated the associations between personality traits, cognitive function, and specific motor symptoms. In this study, the investigators assessed whether particular personality traits were associated with specific motor subtypes of PD (e.g., tremor-dominant and akinetic-rigid phenotypes) and whether frontal-executive functions were associated with personality traits among patients with a specific motor phenotype. Forty-one people with PD and 40 healthy control participants were enrolled in the study. All participants underwent assessments of cognitive and psychological function and personality traits. The study was conducted in Italy. Tremor-dominant symptoms occurred among 20 (48.8%) people with PD, whereas 21 (51.2%) patients exhibited akinetic-rigid symptoms. Multivariate analyses of variance revealed that participants with akinetic-rigid PD demonstrated significantly poorer performance on frontal-executive tests compared with those with tremor-dominant PD. Moreover, those with akinetic-rigid PD exhibited more psychopathological symptoms and higher neuroticism and introversion compared with those with tremor-dominant PD. Correlations revealed that among participants with akinetic-rigid PD, psychopathological symptoms and neuroticism and introversion personality traits were associated with frontal-executive dysfunction, whereas among those with tremor-dominant PD, no significant associations were found between personality traits and cognitive abilities. These findings suggest that specific personality and frontal-executive profiles are associated with the akinetic-rigid motor subtype of PD, thus helping to refine the different clinical manifestations of PD. A better understanding of the psychological, personality, and cognitive mechanisms in PD could also help to develop more targeted treatments.

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.

Non-motor effects of deep brain stimulation in Parkinson's disease motor subtypes

IntroductionDeep brain stimulation (DBS) is a well-established treatment for patients with Parkinson's disease (PD) improving quality of life, motor, and non-motor symptoms. However, non-motor effects in PD subtypes are understudied. We hypothesized that patients with ‘postural instability and gait difficulty’ (PIGD) experience more beneficial non-motor effects than ‘tremor-dominant’ patients undergoing DBS for PD. MethodsIn this prospective, observational, international multicentre study with a 6-month follow-up, we assessed the Non-Motor Symptom Scale (NMSS) as primary and the following secondary outcomes: Unified PD Rating Scale-motor examination (UPDRS-III), Scales for Outcomes in PD (SCOPA)-activities of daily living (ADL) and -motor complications, PDQuestionnaire-8 (PDQ-8), and levodopa-equivalent daily dose (LEDD). We analysed within-group longitudinal changes with Wilcoxon signed-rank test and Benjamini-Hochberg correction for multiple comparisons. Additionally, we explored outcome between-group differences of motor subtypes with Mann-Whitney U-tests. ResultsIn 82 PIGD and 33 tremor-dominant patients included in this study, baseline NMSS total scores were worse in PIGD patients, both groups experienced postoperative improvements of the NMSS sleep/fatigue domain, and between-group differences in postoperative outcomes were favourable in the PIGD group for the NMSS total and miscellaneous domain scores. ConclusionsThis study provides evidence of a favourable outcome of total non-motor burden in PIGD compared to tremor-dominant patients undergoing DBS for PD. These differences of clinical efficacy on non-motor aspects should be considered when advising and monitoring patients with PD undergoing DBS.

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

IntroductionMotor 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). MethodsUPDRS 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. ResultsCompared 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. ConclusionsThis 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.

Value of functional connectivity in outcome prediction for pallidal stimulation in Parkinson disease.

Functional connectivity shows the ability to predict the outcome of subthalamic nucleus deep brain stimulation (DBS) in Parkinson disease (PD). However, evidence supporting its value in predicting the outcome of globus pallidus internus (GPi) DBS remains scarce. In this study the authors investigated patient-specific functional connectivity related to GPi DBS outcome in PD and established connectivity models for outcome prediction. The authors reviewed the outcomes of 21 patients with PD who received bilateral GPi DBS and presurgical functional MRI at the Ruijin Hospital. The connectivity profiles within cortical areas identified as relevant to DBS outcome in the literature were calculated using the intersection of the volume of tissue activated (VTA) and the local structures as the seeds. Combined with the leave-one-out cross-validation strategy, models of the optimal connectivity profile were constructed to predict outcome. Connectivity between the pallidal areas and primary motor area, supplementary motor area (SMA), and premotor cortex was identified through the literature as related to GPi DBS outcome. The similarity between the connectivity profile within the primary motor area, SMA, pre-SMA, and premotor cortex seeding from the VTA-GPi intersection from an out-of-sample patient and the constructed in-sample optimal connectivity profile predicts GPi DBS outcome (R = 0.58, p = 0.006). The predictions on average deviated by 13.1% ± 11.3% from actual improvements. On the contrary, connectivity profiles seeding from the GPi (R = -0.12, p = 0.603), the VTA (R = 0.23, p = 0.308), the VTA outside the GPi (R = 0.12, p = 0.617), or other local structures were found not to be predictive. The results showed that patient-specific functional connectivity seeding from the VTA-GPi intersection could help in GPi DBS outcome prediction. Reproducibility remains to be determined across centers in larger cohorts stratified by PD motor subtype.

Identification of novel proteins associated with movement-related adverse antipsychotic effects by integrating GWAS data and human brain proteomes

Genome-wide association studies (GWAS) have identified some variants for movement-related adverse antipsychotic effects (MAAE), while how these variants confer MAAE remains unclear. We used the probabilistic Mendelian randomization (PMR) method to identify candidate proteins for MAAE by integrating MAAE GWASs and protein quantitative trait loci (pQTL) data. An independent pQTL data from the Banner project and brain-derived eQTL data were used to perform confirmatory PMR. A total of 56 proteins were identified as candidate targets for MAAE after false discovery rates (FDR) correction, such as GRIN2B, ADRA1A, and PED4B. 12 genes were replicated in the confirmatory PMR, and 18 genes had consistent evidence at the transcript level. Furthermore, we investigated the associations between candidate proteins and the motor symptoms of Parkinson's disease (PD). There were 24, 38, and 10 candidate proteins that were significantly associated with PD, PD motor subtypes, and PD motor progression, respectively. Enrichment analysis identified 34 GO terms and 17 pathways that may be involved in MAAE, such as glutamatergic synapse, glutamate receptor complex, and GABAergic synapse. Our study identified multiple candidate genes and pathways that were associated with MAAE, providing new insights into the biological mechanism of MAAE and targets for further mechanistic and therapeutic studies.