Parkinson's Disease Progression Research Articles

Emerging role of Nrf2 in Parkinson's disease therapy: a critical reassessment.

Parkinson's disease (PD) is the neurodegenerative disorder characterized by the progressive degeneration of nigrostriatal dopaminergic neurons, leading to the range of motor and non-motor symptoms. There is mounting evidence suggesting that oxidative stress, neuroinflammation and mitochondrial dysfunction play pivotal roles in the pathogenesis of PD. Current therapies only alleviate perturbed motor symptoms. Therefore, it is essential to find out new therapies that allow us to improve not only motor symptoms, but non-motor symptoms like cognitive impairment and modulate disease progression. Nuclear factor erythroid 2-related factor 2 (Nrf2) is transcription factor that regulates the expression of numerous anti-oxidants and cytoprotective genes can counteract oxidative stress, neuroinflammation and mitochondrial dysfunction, thereby potentially ameliorating PD-associated pathology. The current review discusses about the Nrf2 structure and function with special emphasis on various molecular signalling pathways involved in positive and negative modulation of Nrf2, namely Glycogen synthase kinase-3β, Phosphoinositide-3-kinase, AMP-activated protein kinase, Mitogen activated protein kinase, nuclear factor-κB and P62. Furthermore, this review highlights the various Nrf2 activators as promising therapeutic agents for slowing down the progression of PD.

Parkinson's disease subtypes and their association with probable rapid eye movement sleep behavior disorder severity: a brainstem tractography and machine learning investigation.

Rapid Eye Movement (REM) sleep behavior disorder (RBD) affects nearly half of Parkinson's disease (PD) patients. However, the structural heterogeneity within the brainstem, which regulates REM sleep, remains largely unexplored in PD. Our objective was to identify distinct PD subtypes based on microstructural characteristics in the brainstem and examine their associations with the severity of RBD. Data, including diffusion tensor imaging and REM sleep behavior disorder screening questionnaire (RBDSQ) responses, were obtained from 124 PD patients and 61 healthy controls through the Parkinson's Progression Marker Initiative database. Mean Quantitative Anisotropy (QA) values, representing axonal density, were extracted from 14 brainstem tracts and input into the semi-supervised machine learning algorithm, Heterogeneity through Discriminative Analysis (HYDRA), to cluster subtypes. Applying HYDRA, we identified two distinct PD subtypes (Subtype 1: n = 66, Subtype 2: n = 58). Subtype 2 exhibited reduced QA across assessed brainstem tracts and significantly higher RBDSQ scores than Subtype 1 and healthy controls (p < 0.001). Conversely, Subtype 1, characterized by lower RBDSQ scores, exhibited increased QA, notably in the right medial longitudinal fasciculus, when compared to Subtype 2 and controls (p < 0.001). These findings suggest that heterogeneous axonal damage in brainstem circuits correlates with variations in RBD severity, providing insights into the neurobiological underpinnings of early PD.

Association between the Amplification Parameters of the α-Synuclein Seed Amplification Assay and Clinical and Genetic Subtypes of Parkinson's Disease.

α-Synuclein seed amplification assay on cerebrospinal fluid (CSF-αSyn-SAA) has shown high accuracy for Parkinson's disease (PD) diagnosis. The analysis of CSF-αSyn-SAA parameters may provide useful insight to dissect the heterogeneity of synucleinopathies. To assess differences in CSF-αSyn-SAA amplification parameters in participants with PD stratified by rapid eye movement (REM) sleep behavior disorder (RBD), dysautonomia, GBA, and LRRK2 variants. Clinical and CSF-αSyn-SAA data from the Parkinson's Progression Marker Initiative dataset were used. CSF-αSyn-SAA parameters included maximum fluorescence (Fmax), time to reach 50% of Fmax (T50), time to threshold (TTT), slope, and area under the curve (AUC). Sporadic PD (n = 371) was stratified according to RBD and dysautonomia (DysA) symptoms. Genetic PD included carriers of pathogenic variants of GBA (GBA-PD, n = 52) and LRRK2 (LRRK2-PD, n = 124) gene. CSF-αSyn-SAA was positive in 77% of LRRK2-PD, 92.3% of GBA-PD, and 93.8% of sporadic PD. The LRRK2-PD cohort showed longer T50 and TTT, and smaller AUC than GBA-PD (P = 0.029, P = 0.029, P = 0.016, respectively) and sporadic PD (P = 0.034, P = 0.033, P = 0.014, respectively). In the sporadic cohort, CSF-αSyn-SAA parameters were similar between PD with (n = 157) and without (n = 190) RBD, whereas participants with DysA (n = 193) presented shorter T50 (P = 0.026) and larger AUC (P = 0.029) than those without (n = 150). CSF-αSyn-SAA parameters vary across genetic and non-genetic PD subtypes at the group level. These differences are mostly driven by the presence of LRRK2 variants and DysA. Significant overlaps in the amplification parameter values exist between groups and limit their use at the individual level. Further studies are necessary to understand the mechanisms of CSF-αSyn-SAA parameter differences. © 2024 International Parkinson and Movement Disorder Society.

Anti-Collapsin Response Mediator Protein 5(CV2/CRMP5) and Anti-Glutamic Acid Decarboxylase (GAD) Antibodies-Mediated Encephalopathy Mimicking Atypical Parkinsonism

Background: Paraneoplastic neurological syndromes (PNSs) are rare conditions characterized by immune-mediated pathogenesis, frequently associated with the presence of a neoplasm. Although a single antineuronal antibody mediates a specific syndrome, atypical manifestations mediated by the same antibody have been described. Methods: The aim of this study was to report on an atypical case of PNS with dual positivity for anti-GAD65 and anti-CRMP5/CV2 antibodies, simultaneously characterized by cognitive decline associated with progressive ataxia and parkinsonism. We also reviewed the current literature for published cases of PNSs with parkinsonism associated with anti-GAD65 and anti- CRMP5/CV2 antibodies. Results: A 68-year-old man with an insidious onset of bradykinesia, cognitive decline, and gait instability that began the year before our evaluation had been diagnosed with parkinsonian syndrome. Analysis of the cerebrospinal fluid showed lymphocytic pleocytosis, and a panel for PNS tested positive for anti-GAD65 and anti- CRMP5/CV2 antibodies. After investigation, a microcitoma was found in the lung. Conclusions: In light of our findings, we suggest considering PNS as an alternative diagnosis to parkinsonism-plus syndromes, in particular if bradykinetic syndrome is accompanied by other clinical manifestations including cognitive decline or ataxia in rapidly deteriorating patients. Earlier detection of PNS would lead to timelier identification of any occult tumors, therein promising improvement in the patient’s prognosis.

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.

Comparison of Clinical and Electrophysiologic Characteristics of Peripheral Neuropathy in Progressive Supranuclear Palsy and Parkinson's Disease: An Observational Study.

Although widely described in Parkinson's disease (PD), peripheral neuropathy (PNP) is scarcely reported in progressive supranuclear palsy (PSP). We aimed to compare the frequency, clinical and electrophysiologic characteristics of PNP in PSP and PD patients. This cross-sectional study included 23 PSP and 93 PD patients. Demographic data, Movement Disorders Society-Unified Parkinson's Disease Rating Scale-III (MDS-UPDRS-III), Hoehn-Yahr staging, Toronto Clinical Neuropathy Score, nerve conduction study (NCS), and sympathetic skin response (SSR) were recorded. Diagnosing isolated large fiber neuropathy required abnormal NCS. Isolated small fiber neuropathy required clinical findings of pinprick and thermal sensory loss and/or allodynia and/or hyperalgesia with/without impaired SSR, along with normal NCS. PNP was commoner in PSP than PD (65.2% vs. 50.5%, P = 0.21). While a comparable proportion in both groups had clinical neuropathy, NCS abnormalities predominated in PSP (65.2% vs. 39.8%, P = 0.03). All patients had distal symmetrical axonal polyneuropathy. A significantly higher proportion of PSP patients had large fiber involvement (65.21% vs. 39.78%, χ2 = 4.82; P = 0.03) and mixed fiber PNP (60.9% vs. 33.3%, P = 0.01). PSP patients with neuropathy had a significantly shorter disease duration [median (interquartile range {IQR} = 2 (2-3) years vs. 6 (3-9) years, P < 0.001], higher MDS-UPDRS-III score [median (IQR) = 47 (36-54) vs. 34 (28-49), P = 0.049], higher Hoehn-Yahr stage [median (IQR) = 4 (2-5) vs. 3 (1-5), P < 0.001], and shorter duration of levodopa use [median (IQR) = 2 (1-2) years vs. 3.5 (2-5) years, P = 0.006]. NCS parameters were comparable between PSP and PD patients with neuropathy. While PNP in PSP was not associated with any of the clinical variables, a longer disease duration was independently associated with PNP in PD. PNP affected two-thirds of PSP patients and was more prevalent than PD. Both groups had distal symmetrical axonal polyneuropathy, with mixed fiber PNP predominating in PSP. A longer disease duration in PD was associated with PNP.

Exploring Acoustic Detection of α-Synuclein Fibrils.

Over the past decades, the incidence of Parkinson's disease (PD) cases has doubled in industrialized countries. While patients over 70years old still represent more than half of the cases, the disease is increasingly affecting younger individuals. Environmental factors have been implicated, such as the effects of certain pesticides or chemicals on neurons, such as rotenone or 1-methyl-4-phenyl-1,2,3,6-tetrahydropyridine (MPTP). Researchers have also demonstrated the influence of genetic mutations in younger patients. A-synuclein is a protein encoded by the SNCA gene, known to undergo various mutations in hereditary cases of PD. These mutations alter the composition and spatial arrangements of α-synuclein. The proteins, originally of linear shape, aggregate during the progression of PD, forming fibrillary structures that propagate through brain tissues. Among the physical therapies investigated for treating α-synuclein aggregation, ultrasonic waves, capable of altering protein and cell behaviors, have recently been used to disrupt α-synuclein fibrils within tissues in cellular and animal models, with the hope of developing treatments based on ultrasound properties. However, detecting fibrils typically requires invasive and non-biocompatible chemical compounds or cumbersome machinery. In this study, our acoustic experimental setup allowed us to investigate the response of α-synuclein to ultrasound perturbations. By capturing the transmitted wave across proteins over a frequency range 10kHz to 10MHz, no ultrasound signature indicating the presence of proteins was observed.Significance Statement: The results report there is no ultrasound signature of the presence of α-synuclein fibrils, from 10kHz to 10MHz.

Functional Brain Network Disruptions in Parkinson's Disease: Insights from Information Theory and Machine Learning.

Objectives: This study investigates disruptions in functional brain networks in Parkinson's Disease (PD), using advanced modeling and machine learning. Functional networks were constructed using the Nonlinear Autoregressive Distributed Lag (NARDL) model, which captures nonlinear and asymmetric dependencies between regions of interest (ROIs). Key network metrics and information-theoretic measures were extracted to classify PD patients and healthy controls (HC), using deep learning models, with explainability methods employed to identify influential features. Methods: Resting-state fMRI data from the Parkinson's Progression Markers Initiative (PPMI) dataset were used to construct NARDL-based networks. Metrics, such as Degree, Closeness, Betweenness, and Eigenvector Centrality, along with Network Entropy and Complexity, were analyzed. Convolutional Neural Networks (CNNs), Recurrent Neural Networks (RNNs), and Long Short-Term Memory (LSTM) models, classified PD and HC groups. Explainability techniques, including SHAP and LIME, identified significant features driving the classifications. Results: PD patients showed reduced Closeness (22%) and Betweenness Centrality (18%). CNN achieved 91% accuracy, with Network Entropy and Eigenvector Centrality identified as key features. Increased Network Entropy indicated heightened randomness in PD brain networks. Conclusions: NARDL-based analysis with interpretable deep learning effectively distinguishes PD from HC, offering insights into neural disruptions and potential personalized treatments for PD.

Lipid-based nanoparticles for drug delivery in Parkinson's disease.

Parkinson's disease (PD) is a neurodegenerative disorder that predominantly affects dopaminergic neurons in the substantia nigra and ventral tegmental area, resulting in symptoms such as tremors, muscle rigidity, bradykinesia, and potential cognitive and affective disturbances. The effective delivery of pharmacological agents to the central nervous system is hindered by various factors, including the restrictive properties of the blood‒brain barrier and blood‒spinal cord barrier, as well as the physicochemical characteristics of the drugs. Traditional drug delivery methods may not provide the therapeutic concentrations necessary for functional restoration in PD patients. However, lipid-based nanoparticles (NPs) offer new possibilities for enhancing the bioavailability of established treatment regimens and developing innovative therapies that can modify the course of the disease. This review provides a concise overview of recent advances in lipid-based NP strategies aimed at mitigating specific pathological mechanisms relevant to PD progression. This study also explores the potential applications of nanotechnological innovations in the development of advanced treatment modalities for individuals with PD.

Digital Outcomes as Biomarkers of Disease Progression in Early Parkinson's Disease: A Systematic Review.

Outcomes derived from digital health technologies (DHTs) are promising candidate markers for monitoring Parkinson's disease (PD) progression. They have the potential to represent a significant shift in clinical research and therapeutic development in PD. However, their ability to track disease progression is yet to be established. This systematic review aimed to identify digital biomarkers capable of tracking early PD progression (disease duration <5 years) by reviewing longitudinal studies (minimum follow-up of 6 months). We evaluated study design and quality, population features, reported DHTs and their performance to track progression. Of 1507 records screened, 15 studies were selected, published between 2009 and 2023, with the majority coming from the last 5 years. Of the 15, 11 were observational and four were interventional trials (follow-up range: 6-60 months). Twelve different DHTs were used (8 required active tests, 8 in-hospital use), capturing features related to motor function and daily activities, including five DHTs focused on gait/posture. Rating scales were used as comparators in all but one study. Three DHTs detected longitudinal changes when scales did not, with one study showing larger effect sizes for change over time of selected DHT features compared to rating scales. Four studies showed longitudinal correlations among DHT features and rating scales. Preliminary promising data suggest that DHT-derived outcomes may help reduce sample sizes in disease-modifying trials. There is a need to standardize study methodologies and facilitate data sharing to confirm these results and further validate the sensitivity of DHTs to track disease progression in PD. © 2024 The Author(s). Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Enhancing MRI radiomics feature reproducibility and classification performance in Parkinson's disease: a harmonization approach to gray-level discretization variability.

This study aimed to assess the reproducibility of MRI-derived radiomic features across multiple gray-level discretization levels for classifying Parkinson's disease (PD) subtypes, and to evaluate the impact of ComBat harmonization on feature stability and machine learning performance. T1-weighted MRI scans from 140 PD patients (70 tremor-dominant, 70 postural instability gait difficulty) and 70 healthy controls were obtained from the Parkinson's progression markers initiative (PPMI) database. Radiomic features were extracted from 16 brain regions using 6 discretization levels (8, 16, 32, 64, 128, and 256 bins). ComBat harmonization was applied using a combined batch variable incorporating both scanner models and discretization levels. Intraclass correlation coefficients (ICC) and Kruskal-Wallis tests assessed feature reproducibility before and after harmonization. Support vector machine classifiers were used for PD subtype classification. ComBat harmonization significantly improved feature reproducibility across all feature groups. The percentage of features showing excellent robustness (ICC ≥ 0.90) increased substantially after harmonization. The proportion of features significantly affected by discretization levels was reduced following harmonization. Classification accuracy improved dramatically, from a range of 0.42-0.49 before harmonization to 0.86-0.96 after harmonization across most discretization levels. AUC values similarly increased from 0.60-0.67 to 0.93-0.99 after harmonization. ComBat harmonization significantly enhanced the reproducibility of radiomic features across discretization levels and improved PD subtype classification performance. This study highlights the importance of harmonization in radiomics research for PD and suggests potential clinical applications in personalized treatment planning.

Associations of motor and neuropsychiatric symptoms with comorbidities in prodromal Parkinson's disease.

To investigate the associations between comorbidities and multimorbidity patterns with motor and neuropsychiatric symptoms in patients with Parkinson's disease (PD) in prodromal PD. Multimorbidity is defined as the coexistence of two or more long-term conditions (LTCs) (also known as multiple comorbidities). A total of 921 participants without PD were included in the Parkinson's Progression Markers Initiative (PPMI) database and were categorized according to the LTC count. Participants were evaluated on motor and psychiatric symptoms. Pearson correlation to examine relationship of comorbidities and target symptoms. The baseline population was analyzed using Multiple linear regression model, while mixed effects model was utilized for longitudinal analysis. Fuzzy C-means clustering analysis was conducted to identify comorbidity patterns, followed by multiple linear regression for further analysis. At baseline, a higher LTC count was significantly correlated with more severe motor (MDS-UPDRS I, II, ADL, all P < 0.05) and neuropsychiatric symptoms (QUIP, P < 0.001). Three multimorbidity patterns were identified. Among them, the cardiometabolic multimorbidity pattern (CAR) had the most significant correlation with the aforementioned symptoms. Our longitudinal analysis indicated that an increase in the LTC count was associated with the exacerbation of motor and neuropsychiatric symptoms. Comorbidities were cross-sectionally and longitudinally associated with the motor and neuropsychiatric symptoms of patients with prodromal PD. Among the three multimorbidity patterns, CAR posed the highest threat to the risk of more severe motor and neuropsychiatric symptoms.

White matter lesions contribute to motor and non-motor disorders in Parkinson's disease: a critical review.

Parkinson's disease (PD) is a prevalent neurodegenerative disease, characterized by movement disorders and non-motor symptoms like cognitive impairment and depression. Degeneration of dopaminergic neurons in the substantia nigra and Lewy bodies have long been considered as main neuropathological changes. However, recent magnetic resonance imaging (MRI) studies have shown that white matter lesions (WMLs) were present in PD patients. WMLs are characterized by loss or impairment of myelin sheath in central nerve fibers, which are closely correlated with motor and cognitive dysfunction in PD. WMLs alterations precede nigrostriatal neuronal losses and can independently affect the clinical severity or characteristics of motor coordination in PD patients. Currently, the exact mechanism of WMLs involvement in the occurrence and development of PD remains unclear. It is speculated that WMLs may participate in the pathogenesis of PD by disrupting important connections in brain or promoting axonal degeneration. In this review, we will discuss the pathological changes and mechanisms of WMLs, elaborate the impact of WMLs on the progression of PD, clarify the importance of WMLs in PD pathogenesis, and thus provide novel targets for PD treatments.

Decreased SNCA Expression in Whole-Blood RNA Analysis of Parkinson's Disease Adjusting for Lymphocytes.

Blood-based RNA transcriptomics offers a promising avenue for identifying biomarkers of Parkinson's Disease (PD) progression and may provide mechanistic insights into the systemic biological processes underlying its pathogenesis beyond the well-defined neurodegenerative features. Previous studies have indicated an age-dependent increase in neutrophil-enriched gene expression, alongside a reduction in lymphocyte counts, in individuals with PD. These immune cell changes can obscure disease-relevant transcriptomic signals. In this study, we performed differential expression (DE) analysis of whole-blood RNA sequencing data from PD cohorts, incorporating a correction for immune cell-enriched gene expression, particularly neutrophil-related pathways, to improve the resolution of PD-associated molecular changes. Using 1,254 Parkinson's Progression Markers Initiative (PPMI) samples with complete blood count (CBC) data, we developed a predictive model to estimate neutrophil percentages in a 6,987 PPMI and Parkinson's Disease Biomarkers Program (PDBP) samples. We mitigated the confounding effects of immune cell-enriched gene expression by integrating predicted neutrophil percentages as a covariate in DE analysis. This approach revealed a consistent and significant downregulation of SNCA across all PD cohorts, a finding previously obscured by immune cell signatures. Lowered SNCA expression was found in individuals with known predisposition genes (e.g., SNCA, GBA, LRRK2) and in non-genetic PD cohorts lacking known pathogenic mutations, suggesting it may represent a key transcriptomic hallmark of the disease.

Unpredictable mild stress accelerates the emergence of motor deficits in a rat model of progressive parkinsonism

Parkinson&amp;rsquo;s disease (PD) is a multifactorial condition associated with genetic and environmental factors. In recent years, the role of chronic psychophysiological stress as a predisposing factor for PD is gaining increasing attention. Clinical and experimental evidence indicates that chronic stress exerts adverse effects on the brain. Nevertheless, the potential role of chronic stress in the predisposition to PD remains poorly understood. This study aimed to investigate the effects of exposure to a chronic unpredictable mild stress (UMS) protocol on the onset of parkinsonism in Wistar rats repeatedly treated with a low dose of reserpine. Wistar rats were either exposed to UMS for 1 week or not exposed (control group). Then, the animals were repeatedly treated with a low dose of reserpine or vehicle every other day for 20 days. Behavioral motor evaluations were conducted using catalepsy and open field tests. Moreover, plasma corticosterone (CORT) levels and lipid peroxidation were evaluated. As expected, the UMS protocol increased plasma CORT levels, and reserpine treatment led to a progressive enhancement of cataleptic behavior. Animals exposed to UMS and treated with reserpine exhibited motor alteration earlier during the protocol. No differences were observed in oxidative stress between experimental and control groups, as evaluated through lipid peroxidation assay. Our results showed that chronic mild stress accelerated the onset of motor deficits in reserpine-treated animals.

Formation of CSE-YAP complex drives FOXD3-mediated transition of neurotoxic astrocytes in Parkinson’s disease

Astrocytes, constituting the predominant glial cells in the brain, undergo significant morphological and functional transformations amidst the progression of Parkinson’s disease (PD). A majority of these reactive astrocytes display a neurotoxic phenotype, intensifying inflammatory responses. Nonetheless, the molecular underpinnings steering neurotoxic astrocyte reactivity during PD progression remain mostly uncharted. Here, we uncover the unique role of cystathionine γ-lyase (CSE) in shaping astrocyte reactivity, primarily channeling astrocytes towards a neurotoxic phenotype, thereby escalating neuroinflammation in PD. Single-cell sequencing data drawn from PD patients coupled with RNA sequencing data from MPP+-treated astrocytes, highlighted a marked positive association between increased expression of Cth, the gene that encodes CSE, and neurotoxic astrocyte reactivity. Employing genetic manipulation of Cth in astrocytes, we evidenced that CSE instigates a transition to a neurotoxic state in PD-afflicted astrocytes under in vitro and in vivo settings. Moreover, we identified a CSE-Yes-associated protein (YAP) complex within astrocytes via label-free mass spectrometry. An increased formation of the CSE-YAP complex was found to facilitate the expression of gene patterns tied to neurotoxic astrocytes, driven by the transcription factor, forkhead box protein D3 (FOXD3). Consequently, our work unveils valuable insights into the cell type-specific function of CSE in the brain, and presents FOXD3 as a novel transcription factor influencing astrocyte phenotypes in PD. These findings lay the groundwork for the development of potential strategies intended to manage conditions associated with neuroinflammation.

Targeting Glucose Metabolism: A Novel Therapeutic Approach for Parkinson's Disease.

Glucose metabolism is essential for the maintenance and function of the central nervous system. Although the brain constitutes only 2% of the body weight, it consumes approximately 20% of the body's total energy, predominantly derived from glucose. This high energy demand of the brain underscores its reliance on glucose to fuel various functions, including neuronal activity, synaptic transmission, and the maintenance of ion gradients necessary for nerve impulse transmission. Increasing evidence shows that many neurodegenerative diseases, including Parkinson's disease (PD), are associated with abnormalities in glucose metabolism. PD is characterized by the progressive loss of dopaminergic neurons in the substantia nigra, accompanied by the accumulation of α-synuclein protein aggregates. These pathological features are exacerbated by mitochondrial dysfunction, oxidative stress, and neuroinflammation, all of which are influenced by glucose metabolism disruptions. Emerging evidence suggests that targeting glucose metabolism could offer therapeutic benefits for PD. Several antidiabetic drugs have shown promise in animal models and clinical trials for mitigating the symptoms and progression of PD. This review explores the current understanding of the association between PD and glucose metabolism, emphasizing the potential of antidiabetic medications as a novel therapeutic approach. By improving glucose uptake and utilization, enhancing mitochondrial function, and reducing neuroinflammation, these drugs could address key pathophysiological mechanisms in PD, offering hope for more effective management of this debilitating disease.

Angiotensin type-1 receptor autoantibodies promote alpha-synuclein aggregation in dopaminergic neurons.

Angiotensin, through its type-1 receptor (AT1), is a major inducer of inflammation and oxidative stress, contributing to several diseases. Autoimmune processes have been involved in neurodegeneration, including Parkinson's disease (PD). AT1 autoantibodies (AT1-AA) enhance neurodegeneration and PD, which was related to increased neuronal oxidative stress and neuroinflammation. However, the effect of AT1-AA on α-synuclein aggregation, a major factor in PD progression, has not been studied. In cultures of dopaminergic neurons, we observed that AT1-AA promote aggregation of α-synuclein, as AT1-AA upregulated major mechanisms involved in the α-synuclein aggregation process such as NADPH-oxidase activation and intracellular calcium raising. The results further support the role of AT1 receptors in dopaminergic neuron degeneration, and several recent clinical studies observing the neuroprotective effects of AT1 receptor blockers.

Deciphering Parkinson's Disease Progression Using Deep Learning Techniques

Deciphering Parkinson's Disease Progression Using Deep Learning Techniques

Impact of Harmonization on MRI Radiomics Feature Variability Across Preprocessing Methods for Parkinson's Disease Motor Subtype Classification.

This study aimed to assess the reproducibility of MRI-derived radiomic features across multiple preprocessing methods for classifying Parkinson's disease (PD) motor subtypes and to evaluate the impact of ComBat harmonization on feature stability and machine learning performance. T1-weighted MRI scans from 140 PD patients (70 tremor-dominant and 70 postural instability gait difficulty) and 70 healthy controls were obtained from the Parkinson's Progression Markers Initiative (PPMI) database, acquired using different scanner models. Radiomic features were extracted from 16 brain regions using various preprocessing pipelines. ComBat harmonization was applied using a combined batch variable incorporating both scanner models and preprocessing methods. Intraclass correlation coefficients (ICC) and Kruskal-Wallis tests assessed feature reproducibility before and after harmonization. Feature selection was performed using Linear Support Vector Classifier with L1 regularization. Support vector machine classifiers were used for PD subtype classification. ComBat harmonization significantly improved feature reproducibility across all feature groups. The percentage of features showing excellent robustness (ICC ≥ 0.90) increased from 40.2 to 56.3% after harmonization. First-order statistic features showed the highest robustness, with 71.11% demonstrating excellent ICC after harmonization. The proportion of features significantly affected by preprocessing methods was reduced following harmonization. Classification accuracy improved dramatically, from a range of 34-75% before harmonization to 89-96% after harmonization across all preprocessing methods. AUC values similarly increased from 0.28-0.87 to 0.95-0.99 after harmonization. ComBat harmonization significantly enhanced the reproducibility of radiomic features across preprocessing methods and improved PD motor subtype classification performance. This study highlights the importance of harmonization in radiomics research for PD and suggests potential clinical applications in personalized treatment planning.