Early Parkinson's Disease Research Articles

Increasing Sensitivity in Patient-Reported MDS-UPDRS Items for Predicting Medication Initiation in Early PD.

The MDS-UPDRS Parts IB and II are self-reported items providing a direct patient voice to the experiences of PD. To determine the most sensitive combination of MDS-UPDRS Parts IB and II items that accurately predicted the clinically relevant target of dopaminergic therapy initiation. Utilizing a longitudinal cohort of de novo non-treated PD patients, we applied item response theory (IRT) and survival analysis to assess the relationship between baseline patient-reported symptoms and the later initiation of dopaminergic therapy. The 20 MDS-UPDRS Parts IB and II items were analyzed for their relationship to PD severity (discrimination) and the amount of information they provided in this determination (information). These parameters were used to develop models of predictive accuracy for initiation of dopaminergic therapy. A six-item version showed a significantly higher C-index as compared to the full 20 item model (P = 0.001). This shortened version of the MDS-UPDRS contained only Part II items and provided a predictive accuracy for initiation of dopaminergic therapy better than the total combined scale score or any other combination. A six-item "Baseline Outcome Voice" version of patient-reported MDS-UPDRS items significantly increases the sensitivity of predicting the key future clinical outcome of starting dopaminergic treatment in early PD. This study also demonstrates how IRT modeling can provide information useful to refining existing measures to identify the most sensitive combination of items honoring the voice of the patient in determining key clinically pertinent decisions. Further research is needed to validate these findings in underrepresented populations.

An Exploratory Study on the Effects of Souchard Postural Gymnastics in Parkinson's Disease Patients with Camptocormia: A Quasi-Experimental Approach.

Background/Objective: Parkinson's disease (PD), a prevalent neurodegenerative disorder, leads to motor and non-motor impairments, affecting quality of life. Camptocormia can be one of the motor signs of PD, characterized by a severe and abnormal forward flexion of the thoracolumbar spine that typically occurs when walking or standing. The following study aims to verify whether postural gymnastics can be an effective treatment for trunk control, balance, activities of daily living, and general well-being in patients with early-stage PD and camptocormia. Methods: Nine participants (mean age 67.7 ± 7.8) with early PD (Hoehn and Yahr Scale ≤ 2) received 10 biweekly physiotherapy sessions. Outcomes were measured using the Parkinson's Disease Questionnaire (PDQ-39) and Berg Balance Scale (BBS) along with trunk mobility and muscle tests according to the Medical Research Council (MRC) scale. Results: Statistically significant results were noted in the PDQ-39 mobility, ADLs and emotional well-being subscales and in the BBS; statistically significant improvements were also seen in trunk mobility and muscle strength. Conclusions: This study shows that the postural gymnastic treatment, according to Souchard, in patients with PD's camptocormia has obtained good results and has the potential timprove mobility and balance, encouraging and motivating patients in their rehabilitation journeys.

Deficiency of parkin causes neurodegeneration and accumulation of pathological α-synuclein in monkey models.

Parkinson's disease (PD) is characterized by age-dependent neurodegeneration and the accumulation of toxic phosphorylated α-synuclein (pS129-α-syn). The mechanisms underlying these crucial pathological changes remain unclear. Mutations in parkin RBR E3 ubiquitin protein ligase (PARK2), the gene encoding parkin that is phosphorylated by PTEN-induced putative kinase 1 (PINK1) to participate in mitophagy, cause early onset PD. However, current parkin-KO mouse and pig models do not exhibit neurodegeneration. In the current study, we utilized CRISPR/Cas9 technology to establish parkin-deficient monkey models at different ages. We found that parkin deficiency leads to substantia nigra neurodegeneration in adult monkey brains and that parkin phosphorylation decreases with aging, primarily due to increased insolubility of parkin. Phosphorylated parkin is important for neuroprotection and the reduction of pS129-α-syn. Consistently, overexpression of WT parkin, but not a mutant form that cannot be phosphorylated by PINK1, reduced the accumulation of pS129-α-syn. These findings identify parkin phosphorylation as a key factor in PD pathogenesis and suggest it as a promising target for therapeutic interventions.

A prediction model for the walking and balance milestone in Parkinson's disease

BackgroundWalking and balance impairments, represented by freezing of gait and falls, are significant contributors to disability in advanced Parkinson's disease (PD) patients. However, the composite measure of the Walking and Balance Milestone (WBMS) has not been thoroughly investigated. MethodsThis study included 606 early-stage PD patients from the Parkinson's Progression Markers Initiative (PPMI) database, with a disease duration of less than 2 years and no WBMS at baseline. Patients were divided into a model development cohort (70 %) and a validation cohort (30 %) according to the enrollment site. Longitudinal follow-up data over a period of 12 years were analyzed. ResultsAmong all 606 patients, the estimated probability of being WBMS-free at the 5th and 10th year was 88 % and 60 %, respectively. Five clinical variables (Age, Symbol Digit Modalities Test (SDMT), postural instability and gait difficulty (PIGD) score, Movement Disorder Society-Unified Parkinson's Disease Rating Scale Part I (MDS-UPDRS-I) score, and REM Sleep Behavior Disorder (RBD) were used to construct the Cox predictive model. The C-index of the model was 0.75 in the development cohort and 0.76 in the validation cohort. By optimizing the PIGD and MDS-UPDRS-I variables, an easy-to-use model was achieved with comparable predictive performance. ConclusionA predictive model based on five baseline clinical measures (Age, SDMT, PIGD score, MDS-UPDRS-I score, RBD) could effectively estimate the risk of the WBMS in early PD patients. This model is valuable for prognostic counseling and clinical intervention trials for gait and balance impairment.

Parkinson biomarker determination with an Au microflower-enhanced electrochemical immunosensor using non-Faradaic capacitancemeasurements.

This work comprehends the development and characterization of a carbon black-based electrode modified with Au microflowers to increase its effect as a capacitance biosensor for the determination of PARK7/DJ-1. Due to its high surface-to-volume ratio and biocompatibility, Au particles are suitable for antibody binding, and by monitoring surface capacitance, it is possible to identify the immune-pair interaction. Au microflowers allowed the adequate immobilization of Parkinsonian-related proteins: PARK7/DJ-1 and its antibody. The protein is associated with several antioxidant mechanisms, but its abnormal concentrations or mutations can be the cause of the loss of dopaminergic neurons, leading to Parkinson's disease. The device was characterized by scanning electron microscopy and cyclic voltammetry, revealing the flower-like structures and the electrochemically-interest enhancements they provide, such as increased heterogeneous electron transfer rate coefficient and electroactive area. The self-assembled monolayers of different molecules were optimized with the aid of 22 central composite experiments and a linear calibration curve was obtained between 0.700 and 120ngmL-1 of PARK7/DJ-1, with a limit of detection of 0.207ngmL-1. The data confirms that the addition of Au microflowers enhanced the electrochemical signal of the device, as well as allowed for the determination of an early stage Parkinson's disease biomarker with appreciable analytical performance.

Eleven Years of Change: Disease Progression in Biomarker-Defined Sporadic Parkinson's Disease.

Long-term longitudinal data on outcomes in sporadic Parkinson's Disease are limited, especially from cohorts with extensive biological characterization. Recent advances in biomarkers characterization of Parkinson's Disease necessitate an updated examination of long-term progression within contemporary cohorts like the Parkinson's Progression Markers Initiative, which enrolled individuals within 2 years of clinical diagnosis of Parkinson's Disease. Our study leverages the Neuronal Synuclein Disease framework, which defines the disease based on biomarker assessed presence of neuronal alpha-synuclein and dopamine deficit, rather than based on conventional clinical diagnostic criteria. In this study we aimed to provide a comprehensive long-term description of disease progression using the integrated biological and clinical staging system framework. We analyzed data from 344 participants from the sporadic Parkinson's Disease cohort in the Parkinson's Progression Markers Initiative, who met Neuronal Synuclein Disease criteria. We assessed 11-year progression in a spectrum of clinical measures. We used Cox proportional hazards models to assess the association between baseline stage and time to key outcomes, including survival, postural instability (Hoehn & Yahr ≥ 3), loss of independence (Schwab & England < 80%), cognitive decline, and domain-based milestones such as walking and balance, motor complications, autonomic dysfunction, and activities of daily living. Additional analyses were completed to account for death and participant dropout. Biomarker analysis included dopamine transporter binding measures, as well as serum urate, neurofilament light chain and CSF amyloid-beta, phosphorylated tau and total tau. At baseline, despite the cohort consisting of individuals within 2 years of clinical diagnosis, there was clear separation of participants in Neuronal Synuclein Disease Stages (23% Stage 2b, 67% Stage 3, 10% Stage 4). At 11 years, data were available for 153 participants; 35 participants had died over the follow up period. Of retained participants, 59% presented normal cognition, 24% had evidence of postural instability and mean Schwab & England score was 78.5. Serum neurofilament light chain consistently increased over time. No other biofluids had a consistent change in trajectory. Of importance, baseline Neuronal Synuclein Disease Stage predicted progression to clinically meaningful milestones. This study provides data on longitudinal, 11-year progression in Neuronal Synuclein Disease participants within 2 years of clinical diagnosis. We observed better long-term outcomes in this contemporary observational study cohort. It highlights the heterogeneity in the early Parkinson's Disease population as defined by clinical diagnostic criteria and underscores the importance of shifting from clinical to biologically and functionally based inclusion criteria in the design of new clinical trials.

Sustained effect of prasinezumab on Parkinson's disease motor progression in the open-label extension of the PASADENA trial.

The Phase II trial of Anti-alpha-Synuclein Antibody in Early Parkinson's Disease (PASADENA) is an ongoing double-blind, placebo-controlled trial evaluating the safety and efficacy of prasinezumab in early-stage Parkinson's disease (PD). During the double-blind period, prasinezumab-treated individuals showed less progression of motor signs (Movement Disorders Society-sponsored revision of the Unified Parkinson's Disease Rating Scale (MDS-UPDRS) Part III) than placebo-treated individuals. We evaluated whether the effect of prasinezumab on motor progression, assessed as a change in MDS-UPDRS Part III score in the OFF and ON states, and MDS-UPDRS Part II score, was sustained for 4 years from the start of the trial. We compared participants enrolled in the PASADENA open-label extension study with those enrolled in an external comparator arm derived from the Parkinson's Progression Markers Initiative observational study. The PASADENA delayed-start (n = 94) and early-start (n = 177) groups showed a slower decline (a smaller increase in score) in MDS-UPDRS Part III scores in the OFF state (delayed start, -51%; early start, -65%), ON state (delayed start, -94%; early start, -118%) and MDS-UPDRS Part II (delayed start, -48%; early start, -40%) than did the Parkinson's Progression Markers Initiative external comparator (n = 303). This exploratory analysis, which requires confirmation in future studies, suggested that the effect of prasinezumab in slowing motor progression in PD may be sustained long term. PASADENA ClinicalTrials.gov no. NCT03100149 .

Evaluating a motor progression connectivity model across Parkinson's disease stages.

Stimulation of a specific site in the dorsolateral subthalamic nucleus (STN) was recently associated with slower motor progression in Parkinson's Disease (PD), based on the deep brain stimulation (DBS) in early-stage PD pilot clinicaltrial. Here, subject-level visualizations are presented of this early-stage PD dataset to further describe the relationship between active contacts and motor progression. This study also evaluates whether stimulation of the sweet spot and connectivity model associated with slower motor progression is alsoassociated with improvements in long-term motor outcomes in patients with advanced-stage PD. Active contacts of the early-stage PD cohort (N = 14) were analyzed alongside the degree of two-year motor progression. Sweet spot and connectivity models derived from the early-stage PD cohort were then used to determine how well they can estimate the variance inlong-term motor outcomes in an independent STN-DBS cohort of advanced-stage PD patients (N = 29). In early-stage PD, proximity of stimulation to the dorsolateral STN wasassociated with slower motor progression. In advanced-stage PD, stimulation proximity to the early PD connectivity model and sweet spot were associated with better long-term motor outcomes (R = 0.60, P < 0.001; R = 0.37, P = 0.046, respectively). Results suggest stimulation of a specific site in the dorsolateral STN isassociated with both slower motor progression and long-term motor improvements in PD.

Association between the Val66Met (rs6265) polymorphism of the brain-derived neurotrophic factor (BDNF) gene, BDNF protein level in the blood and the risk of developing early‑onset Parkinson's disease.

Brain-derived neurotrophic factor (BDNF) is involved in the maintenance of dopamine level and the survival of dopaminergic neurons, which may affect the functionality of brain structures responsible for motor and cognitive function. The aim of the study was to assess the association of individual and combined single nucleotide polymorphism (SNP) in the rs6265 BDNF (Val66Met), rs397595 DAT (SLC6A3), and rs4680 COMT (Val158Met) genes with early‑onset of Parkinson's disease (PD) patients. Moreover, we assessed the association between the BDNF Val66Met polymorphism and the level of BDNF protein in the serum of patients with PD and controls. The study involved 163 patients with idiopathic PD divided into early onset (<55 years) and late‑onset (>55 years) groups and 91 healthy age‑matched people (Control). The SNP were determined using the TaqMan Real‑Time PCR method. Serum BDNF levels were determined by ELISA assay. The risk of developing early PD in people with the BDNF genotype AG increases threefold in comparison with the carriers of the BDNF genotype GG. In PD patients and healthy people with the BDNF genotypes AG and AA, a lower serum BDNF level was found compared to those with the BDNF genotype GG in both groups. The results of our study indicate that the presence of the Val66Met BDNF gene polymorphism is associated with reduced blood BDNF levels and an elevated risk of developing early‑onset PD. This effect appears to be more pronounced in men.

Approaches to Early Parkinson's Disease Subtyping.

Parkinson's disease (PD) unfolds with pathological processes and neurodegeneration well before the emergence of noticeable motor symptoms, providing a window for early identification. The extended prodromal phase allows the use of risk stratification measures and prodromal markers to pinpoint individuals likely to develop PD. Importantly, a growing body of evidence emphasizes the heterogeneity within prodromal and clinically diagnosed PD. The disease likely comprises distinct subtypes exhibiting diverse clinical manifestations, pathophysiological mechanisms, and patterns of α-synuclein progression in the central and peripheral nervous systems. There is a pressing need to refine the definition and early identification of these prodromal subtypes. This requires a comprehensive strategy that integrates genetic, pathological, imaging, and multi-omics markers, alongside careful observation of subtle motor and non-motor symptoms. Such multi-dimensional classification of early PD subtypes will improve our understanding of underlying disease pathophysiology, improve predictions of clinical endpoints, progression trajectory and medication response, contribute to drug discovery and personalized medicine by identifying subtype-specific disease mechanisms, and facilitate drug trials by reducing confounding effects of heterogeneity. Here we explore different subtyping methodologies in prodromal and clinical PD, focusing on clinical, imaging, genetic and molecular subtyping approaches. We also emphasize the need for refined, theoretical a priori disease models. These will be prerequisite to understanding the biological underpinnings of biological subtypes, which have been defined by large scale data-driven approaches and multi-omics fingerprints.

Genetic Analysis of Neurite Outgrowth Inhibitor-Associated Genes in Parkinson's Disease: A Cross-Sectional Cohort Study.

Parkinson's disease (PD) is a neurodegenerative disease caused by a combination of aging, environmental, and genetic factors. Previous research has implicated both causative and susceptibility genes in PD development. Nogo-A, a neurite outgrowth inhibitor, has been shown to impact axon growth through ligand-receptor interactions negatively, thereby involved in the deterioration of dopaminergic neurons. However, rare genetic studies have identified the relationship between neurite outgrowth inhibitor (Nogo)-associated genes and PD from a signaling pathway perspective. We enrolled 3959 PD patients and 2931 healthy controls, categorized into two cohorts based on their family history and age at onset: sporadic early Parkinson's disease & familial Parkinson's disease (sEOPD & FPD) cohort and sporadic late Parkinson's disease (sLOPD) cohort. We selected 17 Nogo-associated genes and stratified them into three groups via their function, respectively, ligand, receptors, and signaling pathway groups. Additionally, we conducted the burden analysis in rare variants, the logistic regression analysis in common variants, and the genotype-phenotype association analysis. Last, bioinformatics analysis and functional experiments were conducted to identify the role of the MTOR gene in PD. Our findings demonstrated that the missense variants in the MTOR gene might increase PD risk, while the deleterious variants in the receptor subtype of Nogo-associated genes might mitigate PD risk. However, common variants of Nogo-associated genes showed no association with PD development in two cohorts. Furthermore, genotype-phenotype association analysis suggested that PD patients with MTOR gene variants exhibited relatively milder motor symptoms but were more susceptible developing dyskinesia. Additionally, bioinformatics analysis results showed MTOR gene was significantly decreased in PD, indicating a potential negative role of the mTOR in PD pathogenesis. Experimental data further demonstrated that MHY1485, a mTOR agonist, could rescue MPP+-induced axon inhibition, further implicating the involvement of mTOR protein in PD by regulating cell growth and axon growth. Our preliminary investigation highlights the association of Nogo-associated genes with PD onset in the Chinese mainland population and hints at the potential role of the MTOR gene in PD. Further research is warranted to elucidate the mechanistic pathways underlying these associations and their therapeutic implications.

TMS-evoked potentials unveil occipital network involvement in patients diagnosed with Parkinson’s disease within 5 years of inclusion

Distinguishing Parkinson’s disease (PD) subgroups may be achieved by observing network responses to external stimuli. We compared TMS-evoked potential (TEP) measures from stimulation of bilateral motor cortex (M1), dorsolateral prefrontal cortex (DLPFC), and visual cortex (V1) between 62 PD patients (age: 69.9 ± 7.5) and 76 healthy controls (age: 69.2 ± 4.3) using a TMS–EEG protocol. TEP measures were analyzed using two-way ANCOVA adjusted for MOCA. PD patients were divided into tremor dominant (TD), non-tremor dominant (NTD) and rapid disease progression (RDP) subgroups. PD patients showed lower wide-waveform adherence (wWFA) (p = 0.025) and interhemispheric connectivity (IHCCONN) (p < 0.001) compared to healthy controls. Lower occipital IHCCONN correlated with advanced disease stage (r = −0.37, p = 0.0039). The RDP and NTD groups showed lower wWFA in response to occipital stimulation than the TD group (p = 0.005). Occipital TEP measures identified RDP patients with 85% accuracy. These findings demonstrate occipital network involvement in early PD stages, suggesting that TEP measures offer insights into altered networks in PD subgroups.

Neuronal alpha-Synuclein Disease integrated staging system performance in PPMI, PASADENA, and SPARK baseline cohorts

The Neuronal alpha-Synuclein Disease (NSD) biological definition and Integrated Staging System (NSD-ISS) provide a research framework to identify individuals with Lewy body pathology and stage them based on underlying biology and increasing degree of functional impairment. Utilizing data from the PPMI, PASADENA, and SPARK studies, we developed and applied biologic and clinical data-informed definitions for the NSD-ISS across the disease continuum. Individuals enrolled as Parkinson’s disease, Prodromal, or Healthy Controls were defined and staged based on biological, clinical, and functional anchors at baseline. Across the three studies 1741 participants had SAA data and of these 1030 (59%) were S+ consistent with NSD. Among sporadic PD, 683/736 (93%) were NSD, and the distribution for Stages 2B, 3, and 4 was 25%, 63%, and 9%, respectively. Median (95% CI) time to developing a clinically meaningful outcome was 8.3 (6.2, 10.1), 5.9 (4.1, 6.0), and 2.4 (1.0, 4.0) years for baseline stage 2B, 3, and 4, respectively. We propose pilot biologic and clinical anchors for NSD-ISS. Our results highlight the baseline heterogeneity of individuals currently defined as early PD. Baseline stage predicts time to progression to clinically meaningful milestones. Further research on validation of the anchors in longitudinal cohorts is necessary.

Cortical microstructural alterations in different stages of Parkinson's disease.

To explore the cortical microstructural alterations in Parkinson's disease (PD) at different stages.149 PD patients and 76 healthy controls were included. PD patients were divided into early stage PD (EPD) (Hoehn-Yahr stage ≤ 2) and moderate-to-late stage PD (MLPD) (Hoehn-Yahr stage ≥ 2.5) according to their Hoehn-Yahr stages. All participants underwent two-shell diffusion MRI and the images were fitted to Neurite Orientation Dispersion and Density Imaging (NODDI) model to obtain the neurite density index (NDI) and orientation dispersion index (ODI) to reflect the cortical microstructure. We used gray matter-based spatial statistics method to compare the voxel-wise cortical NODDI metrics between groups. Partial correlation was used to correlate the NODDI metrics and global composite outcome in PD patients.Compared with healthy controls, EPD patients showed lower ODI in widespread regions, covering bilateral frontal, temporal, parietal and occipital cortices, as well as regional lower NDI in bilateral cingulate and frontal lobes. Compared with healthy controls, MLPD patients showed lower ODI and NDI in more widespread regions. Compared with EPD patients, MLPD patients showed lower ODI in bilateral temporal, parietal and occipital cortices, where the ODI values were negatively correlated with global composite outcome in PD patients.PD patients showed widespread cortical microstructural degeneration, characterized by reduced neurite density and orientation dispersion, and the cortical neuritic microstructure exhibit progressive degeneration during the progression of PD.

Late feature fusion using neural network with voting classifier for Parkinson’s disease detection

Parkinson’s disease (PD) is classified as a neurological, progressive illness brought on by cell death in the posterior midbrain. Early PD detection will assist doctors in reducing the disease’s consequences. A collection of skilled models that may be applied to regression as well as classification is known as artificial intelligence (AI). PD can be detected using a variety of dataset formats, including text, speech, and picture datasets. For the purpose of classifying Parkinson’s disease, this study suggests merging deep with machine learning recognition approaches. The three primary components of the suggested approach are designed to enhance the accuracy of Parkinson’s disease early diagnosis. These sections cover the topics of categorising, combining, and separating. Convolutional Neural Networks (CNN) as well as attention procedures are used to create feature extractors. The related motion signals are fed to a combination of convolutional neural network and long-short-memory model for feature extraction. Besides, for the classification of patients from non-suffers of Parkinson’s disease, Random Forest, Logistic Regression, Support Vector Machine, Extreme Boot Classifier, and voting classifier were used. Our result shows that for the PD handwriting and related motion datasets, using the proposed CNN with an attention and voting classifier yields 99.95% accuracy, 99.99% precision, 99.98% sensitivity, and 99.95% F1-score. Based on these results, it is warranted to conclude that the proposed methodology of feature extraction from photos of handwriting and relating motor symptoms, fusing of those features, and following it with a voting classifier yields excellent results for PD classification.

In Silico Decoding of Parkinson's: Speech & Writing Analysis.

Background: Parkinson's disease (PD) has transitioned from a rare condition in 1817 to the fastest-growing neurological disorder globally. The significant increase in cases from 2.5 million in 1990 to 6.1 million in 2016, coupled with predictions of a further doubling by 2040, underscores an impending healthcare challenge. This escalation aligns with global demographic shifts, including rising life expectancy and a growing global population. The economic impact, notably in the U.S., reached $51.9 billion in 2017, with projections suggesting a 46% increase by 2037, emphasizing the substantial socio-economic implications for both patients and caregivers. Coupled with a worldwide demand for health workers that is expected to rise to 80 million by 2030, we have fertile ground for a pandemic. Methods: Our transdisciplinary research focused on early PD detection through running speech and continuous handwriting analysis, incorporating medical, biomedical engineering, AI, and linguistic expertise. The cohort comprised 30 participants, including 20 PD patients at stages 1-4 on the Hoehn and Yahr scale and 10 healthy controls. We employed advanced AI techniques to analyze correlation plots generated from speech and handwriting features, aiming to identify prodromal PD biomarkers. Results: The study revealed distinct speech and handwriting patterns in PD patients compared to controls. Our ParkinsonNet model demonstrated high predictive accuracy, with F1 scores of 95.74% for speech and 96.72% for handwriting analyses. These findings highlight the potential of speech and handwriting as effective early biomarkers for PD. Conclusions: The integration of AI as a decision support system in analyzing speech and handwriting presents a promising approach for early PD detection. This methodology not only offers a novel diagnostic tool but also contributes to the broader understanding of PD's early manifestations. Further research is required to validate these findings in larger, diverse cohorts and to integrate these tools into clinical practice for timely PD pre-diagnosis and management.

The Contribution of Cognitive Control Networks in Word Selection Processing in Parkinson's Disease: Novel Insights from a Functional Connectivity Study.

Parkinson's disease (PD) patients are impaired in word production when the word has to be selected among competing alternatives requiring higher attentional resources. In PD, word selection processes are correlated with the structural integrity of the inferior frontal gyrus, which is critical for response selection, and the uncinate fasciculus, which is necessary for processing lexical information. In early PD, we investigated the role of the main cognitive large-scale networks, namely the salience network (SN), the central executive networks (CENs), and the default mode network (DMN), in word selection. Eighteen PD patients and sixteen healthy controls were required to derive nouns from verbs or generate verbs from nouns. Participants also underwent a resting-state functional MRI. Functional connectivity (FC) was examined using independent component analysis. Functional seeds for the SN, CENs, and DMN were defined as spheres, centered at the local activation maximum. Correlations were calculated between the FC of each functional seed and word production. A significant association between SN connectivity and task performance and, with less evidence, between CEN connectivity and the task requiring selection among a larger number of competitors, emerged in the PD group. These findings suggest the involvement of the SN and CEN in word selection in early PD, supporting the hypothesis of impaired executive control.

Neuronal alpha-Synuclein Disease Integrated Staging System performance in PPMI, PASADENA, and SPARK baseline cohorts.

The Neuronal alpha-Synuclein Disease (NSD) biological definition and Integrated Staging System (NSD-ISS) provide a research framework to identify individuals with Lewy body pathology and stage them based on underlying biology and increasing degree of functional impairment. Utilizing data from the PPMI, PASADENA and SPARK studies, we developed and applied biologic and clinical data-informed definitions for the NSD-ISS across the disease continuum. Individuals enrolled as Parkinson's disease, Prodromal, or Healthy Controls were defined and staged based on biological, clinical, and functional anchors at baseline. Across the three studies 1,741 participants had SAA data and of these 1,030 (59%) were S+ consistent with NSD. Among sporadic PD, 683/736 (93%) were NSD, and the distribution for Stages 2B, 3, and 4 was 25%, 63%, and 9%, respectively. Median (95% CI) time to developing a clinically meaningful outcome was 8.3 (6.2, 10.1), 5.9 (4.1, 6.0), and 2.4 (1.0, 4.0) years for baseline stage 2B, 3, and 4, respectively. We propose pilot biologic and clinical anchors for NSD-ISS. Our results highlight the baseline heterogeneity of individuals currently defined as early PD. Baseline stage predicts time to progression to clinically meaningful milestones. Further research on validation of the anchors in longitudinal cohorts is necessary.

Relationships of B12 and Homocysteine with Outcomes in the SURE-PD, SURE-PD3, and STEADY-PDIII Trials.

DATATOP was a study of early Parkinson's disease (PD) conducted in the 1980 s, before mandatory folic acid fortification in the United States. Our analysis of its baseline serum samples revealed a geometric mean vitamin B12 of 369 pg/mL and homocysteine (tHcy) of 9.5μmol/l. We also found that low B12 predicted greater worsening of ambulatory capacity (AC) and elevated tHcy (>15μmol/L) predicted greater declines in cognitive function. We sought to measure B12 and tHcy in contemporary trial participants with early PD who had not started dopaminergic treatment and to determine whether these analytes were associated with clinical progression. We measured B12 and tHcy from baseline and end-of-study blood samples from three recent clinical trials. Baseline geometric mean B12 levels for these studies ranged from 484- 618 pg/ml and for tHcy ranged from 7.4- 10μmol/L. Use of B12-containing supplements ranged from 41- 61%, and those taking supplements had higher B12 and lower tHcy. Those who began levodopa, but were not taking B12-supplements, had greater end-of-study tHcy. There was no association of baseline tHcy > 15μmol/L with annualized change in Montreal Cognitive Assessment and no association of baseline B12 tertiles with change in AC. In these longitudinal trials, B12 levels were higher than for DATATOP, due in large part to increased B12-supplement intake, while tHcy levels were similar. Initiation of levodopa was associated with increases of tHcy in those not taking a B12-containing supplement. These smaller studies did not replicate prior findings of low B12 and elevated tHcy with features of progression, possibly due to higher baseline B12.

Rest Tremor in Parkinson's Disease Is Associated with Ipsilateral Striatal Dopamine Transporter Binding.

The cardinal motor symptoms of Parkinson's disease (PD) include rigidity, bradykinesia, and rest tremor. Rigidity and bradykinesia correlate with contralateral nigrostriatal degeneration and striatal dopamine deficit, but association between striatal dopamine function and rest tremor has remained unclear. The aim of this study was to investigate the possible link between dopamine function and rest tremor using Parkinson's Progression Markers Initiative dataset, the largest prospective neuroimaging cohort of patients with PD. Clinical, [123I]N-ω-fluoropropyl-2β-carbomethoxy-3β-(4-iodophenyl)nortropane ([123I]FP-CIT) single photon emission computed tomography (SPECT), and structural magnetic resonance imaging data from 354 early PD patients and 166 healthy controls were included in this study. We employed a novel approach allowing nonlinear registration of individual scans accurately to a standard space and voxelwise analyses of the association between motor symptoms and striatal dopamine transporter (DAT) binding. Severity of both rigidity and bradykinesia was negatively associated with contralateral striatal DAT binding (PFWE < 0.05 [FWE, family-wise error corrected]). However, rest tremor amplitude was positively associated with increased ipsilateral DAT binding (PFWE < 0.05). The association between rest tremor and binding remained the same controlling for Hoehn & Yahr stage, Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III score, bradykinesia-rigidity score, or motor phenotype. The association between rest tremor and binding was independent of bradykinesia-rigidity and replicated using 2-year follow-up data (PFWE < 0.05). In agreement with the existing literature, we did not find a consistent association between rest tremor and contralateral dopamine defect. However, our results demonstrate a link between rest tremor and increased or less decreased ipsilateral DAT binding. Our findings provide novel information about the association between dopaminergic function and parkinsonian rest tremor. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.