Early-stage Parkinson's Disease Research Articles

Transmission of Peripheral-blood α-Synuclein Fibrils Exacerbates Synucleinopathy and Neurodegeneration in Parkinson's Disease by Endothelial Lag3 Endocytosis.

Background: Parkinson's disease (PD) is an age-related neurodegenerative disorder. The pathological feature of PD is abnormal alpha-synuclein (α-syn) formation and transmission. Recent evidence demonstrates that α-syn preformed fibrils (α-syn PFF) can be detected in the serum of PD patients. The peripheral-blood α-syn PFF can cross the blood-brain barrier and aggravate neuronal damage, but the mechanism remains to be elucidated. Methods: We constructed the PD mouse models of different severity: the mild pathology (A53T ONLY) and the severe pathology (A53T+Brain FIB); this was followed by α-syn PFFs intravenous injection. Then, we used endothelium-specific Lag3 knockout mice (Lag3-ECs-CKO) to decrease the blood α-syn PFFs spreading. Results: We observed that intravenous transmission of α-syn PFFs significantly aggravated motor deficits, dopaminergic neuron loss, neuroinflammation and pathologic α-syn deposition in A53T ONLY, but not in A53T+Brain FIB. Blocking endothelial Lag3 endocytosis by Lag3-ECs-CKO decreased the blood α-syn PFFs spreading and improved the symptoms and pathogenesis of PD mice. Conclusions: Our findings reveal the role of peripheral-blood α-syn PFFs transmission in the mild pathology or early-stage PD and the mechanism of endothelial Lag3 endocytosis in the pathology of α-syn transmission. Targeting endothelial Lag3 to prevent α-syn from spreading from the blood to the brain may be a disease-modifying therapy in early-stage PD.

Decreased Cortical Sulcus Depth in Parkinson's Disease with Excessive Daytime Sleepiness.

Excessive daytime sleepiness (EDS), aprevalent non-motor symptom in Parkinson's disease (PD), significantly impacts the quality of life for PD patients and elevates the risks of injury. Our study is to investigate the altered cortical surface morphology characteristics in PD patients with EDS (PD-EDS). Clinical data and magnetic resonance imaging were obtained from the Parkinson's Progression Marker Initiative database, comprising 36PD-EDS and 98PD patients without EDS (PD-nEDS). The computational anatomy toolbox was utilized to derive sulcus depth (SD) and deep grey matter (GM) nuclei volumes. PD-EDS patients exhibited significantly decreased SD values in the right caudal middle frontal gyrus, pars opercularis, and superior temporal cortex relative to PD-nEDS patients. However, no significant differences in deep GM nuclei volumes were identified. Receiver operating characteristic (ROC) curve analyses further revealed that these cortical SD values could potentially serve as ascreening index for distinguishing PD-EDS from PD-nEDS. Additionally, although PD-EDS patients had a longer disease duration and poorer performance in motor function and depression compared to PD-nEDS patients, these factors were included as covariates in the neuroimaging analyses. Our study findings demonstrated that decreased cortical SD values might induce sleep-wake state instability and contribute to the pathophysiological mechanisms of EDS in early-stage PD.

Machine Learning for Early Detection of Cognitive Decline in Parkinson’s Disease Using Multimodal Biomarker and Clinical Data

Background: Parkinson’s disease (PD) is the second most common neurodegenerative disease, primarily affecting the middle-aged to elderly population. Among its nonmotor symptoms, cognitive decline (CD) is a precursor to dementia and represents a critical target for early risk assessment and diagnosis. Accurate CD prediction is crucial for timely intervention and tailored management of at-risk patients. This study used machine learning (ML) techniques to predict the CD risk over five-year in early-stage PD. Methods: Data from the Early Parkinson’s Disease Longitudinal Singapore (2014 to 2018) was used to predict CD defined as a one-unit annual decrease or a one-unit decline in Montreal Cognitive Assessment over two consecutive years. Four ML methods—AutoScore, Random Forest, K-Nearest Neighbors and Neural Network—were applied using baseline demographics, clinical assessments and blood biomarkers. Results: Variable selection identified key predictors of CD, including education year, diastolic lying blood pressure, diastolic standing blood pressure, systolic lying blood pressure, Hoehn and Yahr scale, body mass index, phosphorylated tau at threonine 181, total tau, Neurofilament light chain and suppression of tumorigenicity 2. Random Forest was the most effective, achieving an AUC of 0.93 (95% CI: 0.89, 0.97), using 10-fold cross-validation. Conclusions: Here, we demonstrate that ML-based models can identify early-stage PD patients at high risk for CD, supporting targeted interventions and improved PD management.

Spatiotemporal neurodegeneration of the substantia nigra and its connecting cortex and subcortex in Parkinson's disease.

Neurodegeneration is uneven in Parkinson's disease (PD). This study aimed to investigate spatiotemporal neurodegeneration in functional subregions of the substantia nigra (SN) and their connected cortex and subcortex in people with PD. A total of 120 patients with early-stage PD, 45 patients with advanced PD, and 120 healthy controls (HCs) were enrolled. The SN, cortex, and subcortex were divided into sensorimotor, associative, and limbic regions, respectively. Iron deposition in the SN was assessed by quantitative susceptibility mapping (QSM). Cortex and subcortex volumes were calculated based on T1-weighted imaging. Region of interest (ROI) analysis and voxel-based analysis (VBA) were performed to explore spatiotemporal neurodegeneration in patients with PD. p values were corrected for false discovery rate. In the ROI analysis, the QSM values for the limbic (p = 0.018) and sensorimotor SN subregions (p = 0.018) were higher in PD patients than in HCs, but were not higher in the associative SN subregion (p = 0.295). In VBA, all SN functional subregions had clusters with higher QSM values in PD patients than in HCs (p < 0.001). The limbic SN subregion was the only one in which iron deposition increased from early-stage to advanced PD (p = 0.023). The QSM values of VBA_limbic, sensorimotor, and associative SN had subregion-specific correlations with disease severity (p = 0.001 for the limbic and sensorimotor subregions, p = 0.003 for the associative subregion), motor symptoms (p = 0.057 for the limbic and sensorimotor subregion), and depression scores (p = 0.036 for the limbic subregion). Iron deposition in SN functional subregions and atrophy of cortical and subcortical structures connected with the SN showed spatiotemporal selectivity. These findings reveal the potential pathogenesis of clinical heterogeneity in PD.

Modifications of DJ-1 in which pI shifts to acidic in red blood cells a potential biomarker for Parkinson’s disease at early stages

Parkinson’s disease (PD) is one of the most common neurodegenerative diseases, the incidence of which increases with age. However, since there is no fundamental treatment or methods for early diagnosis, new methods of treatment and diagnosis are urgently needed. We focused on post-translational modifications of DJ-1, which is encoded by the familial PD-causative gene PARK7 in red blood cells (RBCs). DJ-1 has three cysteines (Cys46, Cys53, and Cys106), with Cys106 being preferentially oxidized. We previously reported that sulfinated/sulfonated Cys106 DJ-1 (oxDJ-1) is increased in the RBCs of PD patients. In this study, we analyzed RBC-derived DJ-1 from PD patients and control subjects by 2-dimensional electrophoresis. We found that the ratio of the spot of DJ-1 with a more acidic isoelectric point than oxDJ-1 was increased more significantly than that of oxDJ-1 in RBCs from patients at the early stage of unmedicated PD and decreased with the progression of PD stage and treatment. Furthermore, we revealed that this acidic spot of DJ-1 increased upon exposure to H2O2. However, when either Cys53 or Cys106 of DJ-1 was replaced with serine, there was no significant increase in the acidic spot caused by H2O2. In this study, we propose a new biomarker for early diagnosis of PD using both the ratios of oxDJ-1 to total DJ-1 and the acidic spot of DJ-1 to total DJ-1.

Substantia nigra alterations in mice modeling Parkinson’s disease

Substantia nigra alterations in mice modeling Parkinson’s disease

Exposure factors and clinical characteristics associated with Parkinson's disease in GBA1 variant carriers: A Chinese GBA1-PD intrafamilial survey

IntroductionGlucosylceramidase beta 1 (GBA1) mutations are a genetic risk factor for Parkinson's disease (PD), though most carriers do not develop the disease. This study aimed to identify exposure factors linked to PD in GBA1 carriers and assess clinical features and the probability of prodromal PD in non-manifesting carriers. MethodsData from the Parkinson's Disease & Movement Disorders Multicenter Database and Collaborative Network in China was used, including 59 GBA1 non-manifesting carriers, 62 controls, and 107 GBA1-associated PD, of whom 81 were in the early stage. Exposure factors included pesticide/solvent exposure, smoking, alcohol, and tea consumption. Logistic regression assessed the association between exposure factors and PD. Clinical characteristics were evaluated using multiple scales, relevant markers were collected based on the Movement Disorders Society criteria. A naive Bayesian classifier method determined the probability of prodromal PD in GBA1 non-manifesting carriers and controls. ResultsAfter adjusting for sociodemographic variables, pesticide/solvent exposure was positively associated with PD in GBA1 carriers (OR 8.40; 95 % CI 2.50–28.20), while smoking was inversely associated with PD (OR 0.18; 95 % CI 0.05–0.62). Rapid eye movement sleep behavior disorder, constipation, hyposmia, and cognitive deficits were more severe in early-stage GBA1-associated PD than in carriers and controls. Clinical symptoms and the probability of prodromal PD were similar between carriers and controls. ConclusionsPD in GBA1 carriers is closely linked to exposure factors. Early-stage GBA1-associated PD shows significant prodromal symptoms, which are not evident in carriers. The probability of prodromal PD in carriers is similar to that in controls.

An Automated Diagnosis of Parkinson's Disease from MRI Scans Based on Enhanced Residual Dense Network with Attention Mechanism.

The increasing prevalence of neurodegenerative diseases has recently heightened interest in research on early diagnosis of these diseases. Parkinson's disease (PD), among the most prominent of these conditions, is a neurological disorder causing the loss of nerve cells and significantly affecting movement control. Detection of PD in early stages is of critical importance to prevent the progression of the disease and improve treatment processes. The aim of the current study is to develop a deep learning model that can perform accurate classification for early diagnosis of PD from MRI images. In this study, a densely connected feature fusion network with residual learning is designed to diagnose PD patients. The designed network consists of a serial dense block with skip connections and efficient attention mechanisms. In this architecture, squeeze-excitation (SE) blocks with ResNeXt (SE-ResNeXt block) modules are utilized to extract distinctive and high-level features. In the experiments, a publicly available T2-weighted MRI dataset is used, and an offline augmentation process is applied to limited data to increase the generalization ability and classification performance. The proposed method is evaluated and compared with current state-of-the-art deep learning methods. The obtained results show that the proposed model gives higher classification performance with an overall accuracy of 94.44%, precision of 91.67%, sensitivity of 91.67%, specificity of 95.83%, F1-score of 91.67%, and Matthew's correlation coefficient of 87.50% for the PD and healthy control subjects.

Parkinson's Disease: Unravelling the Medicinal Perspectives and Recent Developments of Heterocyclic Monoamine Oxidase-B Inhibitors.

Parkinson's disease is a neurodegenerative condition characterized by slow movement (bradykinesia), tremors, and muscle stiffness. These symptoms occur due to the degeneration of dopamine- producing neurons in the substantia nigra region of the brain, leading to reduced dopamine levels. The development of Parkinson's Disease (PD) involves a combination of genetic and environmental factors. PD is associated with abnormal regulation of the monoamine oxidase (MAO) enzyme. Monoamine oxidase inhibitors (MAOIs) are an important class of drugs used to treat PD and other neurological disorders. In the early stages of PD, monotherapy with MAO-B inhibitors has been shown to be both safe and effective. These inhibitors are also commonly used as adjuncts in long-term disease management, as they can improve both motor and non-motor symptoms, reduce "OFF" periods, and potentially slow disease progression. However, current MAO-B inhibitors come with side effects like dizziness, nausea, vomiting, light-headedness, and fainting. Therefore, accelerating the development of new MAO-B inhibitors with fewer side effects is crucial. This review explores natural compounds that may inhibit monoamine oxidase B (MAO-B), focusing on key findings from the past seven years. It highlights the most effective heterocyclic compounds against MAO-B, including thiazolyl hydrazone, pyridoxine-resveratrol, pyridazine, isoxazole, oxadiazole, benzothiazole, benzoxazole, coumarin, caffeine, pyrazoline, piperazine, piperidine, pyrrolidine, and morpholine derivatives. The review covers in vitro, in silico, and in vivo data, along with the structure- activity relationship of these compounds. These findings offer valuable insights for the development of more effective MAO-B inhibitors and advancements in Parkinson's disease research.

Olfactory and Gustatory Function in Early-Stage Parkinson's Disease: Implications for Cognitive Association.

Olfactory and Gustatory Function in Early-Stage Parkinson's Disease: Implications for Cognitive Association.

Diagnostic Potential of NEAT1, hsa-let-7a-5p, and miR-506-3p in Early-stage Parkinson's Disease.

Parkinson's disease (PD) is a multifaceted disease that is influenced by both genetic and environmental parameters. Non-coding RNAs have been shown to be ideal biomarkers for several diseases, including PD. This study was conducted to evaluate the expression levels of NEAT1, hsa-let-7a-5p, and miR-506-3p in individuals with PD to assess their efficacy for early-stage PD diagnosis. Twenty-four patients with PD and 29 healthy individuals participated in this study. The IntaRNA tool was used to predict potential base pairings between NEAT1 and let-7a-5p, and NEAT1 and miR-506-3p. RT-qPCR was employed to measure the relative expression of tyrosine hydroxylase (TH), as well as nuclear enriched abundant transcript 1 (NEAT1), hsa-let-7a-5p, and miR-506-3p levels in both groups. The area under the receiver operating characteristic curve (AUC) was calculated to evaluate the diagnostic value. The PD group exhibited significantly elevated NEAT1 expression levels compared to the healthy control group. While the PD group exhibited an insignificant decreased TH expression level relative to the healthy group. Furthermore, the levels of hsa-let-7a-5p and miR-506-3p expression were seen to be decreased in patients with PD in comparison to the control group. Integration of NEAT1, hsa-let-7a-5p, and miR-506-3p levels significantly enhanced diagnostic capabilities and increased the AUC to 0.9501 (95% confidence interval: 0.8978-1.000, p < .0001). The elevated NEAT1 expression and the decreased expression of hsalet- 7a-5p and miR-506-3p in PD patients indicate that these factors might contribute to the disease's pathogenesis. Combining the ROC curves of NEAT1 and hsa-let-7a-5p with miR-506-3p showed improved sensitivity and specificity, facilitating more accurate PD diagnosis. More importantly, they may contribute as promising non-invasive biomarkers for PD diagnosis.

Association between serum IGF‑1 levels and non-motor symptoms in Parkinson's disease.

We aimed to measure serum insulin-like growth factor 1 (IGF-1) levels in Parkinson's disease (PD) patients and assess their correlation with non-motor symptoms (NMS). Emerging evidence suggests that abnormal levels of IGF-1 play a crucial role in the development of PD. Further systematic research is needed to explore the potential roles of abnormal IGF-1 levels in NMS of PD. The study enrolled a total of 129 PD patients and 130 healthy controls (HCs). Within the PD cohort, 74 patients were classified as being in the early stage, while 55 were in the moderate stage. This study found no significant difference in serum IGF-1 levels between PD patients and HC. Further analysis revealed no significant difference in IGF-1 levels between early-stage PD and those in the moderate stages. Linear regression analysis indicated a significant association between serum IGF-1 levels and Nonmotor Symptom Scale (NMSS) scores in PD patients. Linear regression analysis revealed significant correlations between serum IGF-1 levels and general cognitive function, information processing speed, and executive function in PD patients. Furthermore, lower serum IGF-1 levels were associated with fatigue in PD patients. In summary, our study suggests a potential association between serum IGF-1 levels and specific NMS in patients with PD. These findings highlight the importance of long-term follow-up studies to determine whether serum biomarkers can serve as valuable tools for early detection of NMS in PD.

Increased dementia risk in patients with Parkinson's disease attributed to metabolic syndrome.

Metabolic syndrome (MetS) manifests resembling pathophysiological mechanisms with Parkinson's disease (PD). Current research on the overall population has emphasized MetS as a freestanding risk factor for cognition. This research aims to explore the impact of MetS on cognition in Parkinson's patients. We involved subjects identified as having early-stage PD patients. The MetS was diagnosed dependent on parameters overviewed in the National Cholesterol Education Program's Adult Treatment Panel III. The clinical severity and stages in patients with PD were dependent on the disease rating scales. The cognition was evaluated by the Turkısh version of the Montreal Cognitive Assessment Scale (MoCA-TR). The cases were categorized according to cognitive failure: mild cognitive impairment in PD (PD-MCI), and PD dementia (PDD). Metabolic syndrome was present in 39.6% of the participants. 22.0% of patients were in the normal cognition, 29.1% in the PD-MCI group, and 48.9% in the PD-D group. The cognitive scores in patients with MetS is considerably lower than MetS negative group. A statistically notable inverse association was detected between fasting blood glucose levels and the visual-spatial/executive functions, naming, language, and orientation scores. The multivariate logistic regression analysis showed individuals with MetS were found to have an 11.308 times higher risk of PD-D (odds ratio [OR]: 11,3, 95% confidence interval [CI]: 1.61-79.2 ). We discerned the occurrence of MetS in PD raises the possibility of advancing dementia. This suggests that considering MetS in this patient group could contribute to the effective management of dementia.

Brain-Region-Specific Differences in Protein Citrullination/Deimination in a Pre-Motor Parkinson's Disease Rat Model.

The detection of early molecular mechanisms and potential biomarkers in Parkinson's disease (PD) remains a challenge. Recent research has pointed to novel roles for post-translational citrullination/deimination caused by peptidylarginine deiminases (PADs), a family of calcium-activated enzymes, in the early stages of the disease. The current study assessed brain-region-specific citrullinated protein targets and their associated protein-protein interaction networks alongside PAD isozymes in the 6-hydroxydopamine (6-OHDA) induced rat model of pre-motor PD. Six brain regions (cortex, hippocampus, striatum, midbrain, cerebellum and olfactory bulb) were compared between controls/shams and the pre-motor PD model. For all brain regions, there was a significant difference in citrullinated protein IDs between the PD model and the controls. Citrullinated protein hits were most abundant in cortex and hippocampus, followed by cerebellum, midbrain, olfactory bulb and striatum. Citrullinome-associated pathway enrichment analysis showed correspondingly considerable differences between the six brain regions; some were overlapping for controls and PD, some were identified for the PD model only, and some were identified in control brains only. The KEGG (Kyoto Encyclopedia of Genes and Genomes) pathways identified in PD brains only were associated with neurological, metabolic, immune and hormonal functions and included the following: "Axon guidance"; "Spinocerebellar ataxia"; "Hippo signalling pathway"; "NOD-like receptor signalling pathway"; "Phosphatidylinositol signalling system"; "Rap1 signalling pathway"; "Platelet activation"; "Yersinia infection"; "Fc gamma R-mediated phagocytosis"; "Human cytomegalovirus infection"; "Inositol phosphate metabolism"; "Thyroid hormone signalling pathway"; "Progesterone-mediated oocyte maturation"; "Oocyte meiosis"; and "Choline metabolism in cancer". Some brain-region-specific differences were furthermore observed for the five PAD isozymes (PADs 1, 2, 3, 4 and 6), with most changes in PAD 2, 3 and 4 when comparing control and PD brain regions. Our findings indicate that PAD-mediated protein citrullination plays roles in metabolic, immune, cell signalling and neurodegenerative disease-related pathways across brain regions in early pre-motor stages of PD, highlighting PADs as targets for future therapeutic avenues.

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.

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.

Gait analysis in the early stage of Parkinson's disease with a machine learning approach.

Gait disorder is a prominent motor symptom in Parkinson's disease (PD), objective and quantitative assessment of gait is essential for diagnosing and treating PD, particularly in its early stage. This study utilized a non-contact gait assessment system to investigate gait characteristics between individuals with PD and healthy controls, with a focus on early-stage PD. Additionally, we trained two machine learning models to differentiate early-stage PD patients from controls and to predict MDS-UPDRS III score. Early-stage PD patients demonstrated reduced stride length, decreased gait speed, slower stride and swing speeds, extended turning time, and reduced cadence compared to controls. Our model, after an integrated analysis of gait parameters, accurately identified early-stage PD patients. Moreover, the model indicated that gait parameters could predict the MDS-UPDRS III score using a machine learning regression approach. The non-contact gait assessment system facilitates the objective and quantitative evaluation of gait disorder in PD patients, effectively distinguishing those in the early stage from healthy individuals. The system holds significant potential for the early detection of PD. It also harnesses gait parameters for a reasoned prediction of the MDS-UPDRS III score, thereby quantifying disease severity. Overall, gait assessment is a valuable method for the early identification and ongoing monitoring of PD.

Monocyte to high-density lipoprotein cholesterol ratio reflects the peripheral inflammatory state in parkinsonian disorders

BackgroundIn Parkinson’s disease (PD) and Parkinson plus syndrome (PPS), inflammation is recognized as a relevant or contributing factor in the advancement of the diseases. For this reason, numerous biomarkers signaling immune alteration in both the central and peripheral nervous systems have been evaluated in PD and PPS. Nonetheless, the comprehensive inflammatory indices derived from readily available standard blood tests in PD, PPS, and healthy controls (HC) were rarely evaluated especially in the early stage of the diseases. ObjectiveThe aim of this study is to explore the serum level of peripheral inflammatory markers among the patients and investigate whether these markers contribute to symptoms. MethodClinical data and blood test results from drug naïve, early-stage 139 PD and 87 PPS patients, along with 139 age- and sex-matched healthy controls (HC) to PD were enrolled, with exclusion criteria applied to conditions potentially affecting inflammation. The study examined the disparities in peripheral inflammation among the groups, using total and subpopulation of white blood cells (WBCs), platelet count, red cell distribution width (RDW), high-density lipoprotein cholesterol (HDL-C), and other composite values reflecting inflammation including RDW to platelet ratio (RPR), neutrophil to lymphocyte ratio (NLR), monocyte to lymphocyte ratio (MLR), platelet to lymphocyte ratio (PLR), neutrophil to HDL-C ratio (NHR), monocyte to HDL-C ratio (MHR), lymphocyte to HDL-C ratio (LHR), platelet to HDL-C ratio (PHR), systemic inflammation index (SII), systemic inflammation response index (SIRI), and aggregate index of systemic inflammation (AISI). ResultThe MHR values were significantly higher in both PD and PPS groups compared to HC (p < 0.001), and NHR was significantly higher in the PPS group only compared to the HC group (p < 0.001). However, no significant differences in all the inflammatory markers were observed between PPS and PD (p > 0.05). Subgroup analysis of progressive supranuclear palsy (PSP) and multiple system atrophy (MSA) patients revealed significantly higher NHR and MHR levels compared to the HC group (p = 0.025, p = 0.050, respectively), with no significant difference among PSP, MSA, and PD groups. After adjustment for age, sex, and disease duration, MHR was positively associated with H&Y in the total population (β = 0.288, p < 0.001), negatively associated with MMSE in the PD group (β = −0.245, p = 0.017), and positively associated with both H&Y (β = 0.432, p < 0.001) and UPDRS part II (β = 0.295, p = 0.018) in PPS group. ConclusionNHR and MHR values are not effective as reliable diagnostic markers due to overlap among groups and their limited discriminative capacity in ROC analyses. However, MHR may potentially serve as an indicator reflecting peripheral inflammation in the early stage of PD and PPS compared to HC.

Distinct Clinical Implications of Patient- Versus Clinician-Rated Motor Symptoms in Parkinson's Disease.

Patient-rated motor symptoms (PRMS) and clinician-rated motor symptoms (CRMS) often differ in Parkinson's disease (PD). Our goal was to investigate the determinants and clinical implications of PRMS compared with CRMS in PD. This retrospective, observational cohort study analyzed the cross-sectional associations and longitudinal impacts of PRMS as assessed by the Movement Disorders Society-sponsored Unified PD Rating Scale (MDS-UPDRS) part 2, while controlling for CRMS measured by MDS-UPDRS part 3. Longitudinal analyses used Cox proportional hazards models and multiple linear mixed-effects random intercepts/slope models, adjusting for many clinical predictors. We conducted propensity score matching (PSM) to reinforce our analyses' robustness and surface-based morphometry to investigate neural correlates. We enrolled 442 patients with early-stage PD. At baseline, regardless of CRMS, PRMS were associated with the severity of postural instability and gait disturbance (PIGD). Notably, PRMS independently and more accurately predicted faster long-term deterioration in motor function than CRMS (Hoehn and Yahr 4, adjusted hazard ratio per +1 point = 1.19 [95% confidence intervals, 1.08-1.32]), particularly in PIGD (PIGD subscore, β-interaction = 0.052 [95% confidence intervals, 0.018-0.086]). PSM confirmed these findings' robustness. Surface-based morphometry suggested that enhanced sensory processing was distinctively associated with PRMS. In early-stage PD, PRMS weighed different aspects of symptoms and more effectively predicted motor deterioration compared to CRMS, with distinctive brain structural characteristics. The superior sensitivity of PRMS to subtle declines in drug-refractory symptoms like PIGD likely underlie our results, highlighting the importance of understanding the differential clinical implications of PRMS to prevent long-term motor deterioration. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.