Parkinson's Disease Subtypes Research Articles

Functional connectivity compensation in Parkinson's disease with freezing of gait.

Freezing of gait (FOG) is a disabling motor symptom prevalent in patients with Parkinson's disease (PD); however, its pathophysiological mechanisms are poorly understood. This study aimed to investigate whole-brain functional connectivity (FC) pattern alterations in PD patients with FOG. A total of 18 PD patients, 10 with FOG (PD-FOG) and 8 without FOG (PD-nFOG), and 10 healthy controls were enrolled. High-resolution 3D T1-weighted and resting-state functional MRI (rs-fMRI) data were obtained from all participants. The groups' internetwork connectivity differences were explored with rs-fMRI FC using seed-based analysis and graph theory. Multiple linear regression analysis estimated the relationship between FC changes and clinical measurements. Rs-fMRI analysis demonstrated alterations in FC in various brain regions between the three groups. Freezing of Gait Questionnaire severity was correlated with decreased brain functional connection between Vermis12 and the left temporal occipital fusiform cortex (r = -0.82, P < .001). Graph theory topological metrics indicated a decreased clustering coefficient in the right superior temporal gyrus in the PD-nFOG group. PD-FOG patients exhibited a compensatory increase in connectivity between the left inferior frontal gyrus language network and the postcentral gyrus compared to PD-nFOG patients. Further, the decreased connection between Vermis 12 and the left temporal occipital fusiform cortex may serve as a potential neuroimaging biomarker for tracking PD-FOG and distinguishing between PD subtypes.

Rehabilitation Response in Tremor- and Non-Tremor-Dominant Parkinson Disease: A Task-fMRI Study.

Tremor-dominant (TD) and nontremor-dominant (NTD) Parkinson's disease (PD) showed different responses to rehabilitation. However, the neural mechanism behind this remains unclear. This cohort study explores changes in motor function, brain activation, and functional connectivity following 2 weeks of rehabilitation in TD-PD and NTD-PD patients, respectively. A total of 11 TD-PD patients, 24 NTD-PD patients, and 21 age-matched healthy controls (HCs) were included. At baseline, all participants underwent functional magnetic resonance imaging (fMRI) while performing the foot tapping task. Motor symptoms, gait, balance, and task-based fMRI were then evaluated in patients before and after rehabilitation. Compared to HCs, TD-PD patients showed increased activity in the left inferior frontal gyrus and the right insula, and NTD-PD patients showed increased activations in the left postcentral gyrus and decreased within-cerebellar connectivity at baseline. Rehabilitation improved motor function in PD patients regardless of motor subtype. TD-PD patients showed increased recruitments of the sensorimotor cortex and the bilateral thalamus after rehabilitation, and NTD-PD patients showed increased cerebellar activation and within-cerebellar connectivity that was associated with better motor performance. This study demonstrated that rehabilitation-induced brain functional reorganization varied by motor subtypes in PD, which may have important implications for making individualized rehabilitation programs. ClinicalTrials.gov identifier: ChiCTR1900020771.

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.

Urodynamic study and its correlation with cardiac meta-iodobenzylguanidine (MIBG) in body-first and brain-first subtypes of Parkinson's disease.

Lower urinary tract symptoms (LUTS) are frequently observed in patients with Parkinson's disease (PD), but the underlying mechanism remains elusive. The concept of "body-first" and "brain-first" subtypes in PD has been proposed, but the correlation of PD subtype with LUTS remains unclear. We aimed to investigate the disparities in urological dysfunctions between body-first and brain-first subtypes of PD using urodynamic studies (UDS). We reviewed patients with PD (disease duration <3 years) who had undergone UDS and completed urological questionnaires (Overactive Bladder Symptom Score [OABSS] and International Prostate Symptom Score [IPSS]) and a voiding diary. Patients were categorized as having body-first or brain-first PD based on cardiac sympathetic denervation (CSD) using cardiac meta-iodobenzylguanidine (MIBG) uptake and the presence of rapid eye movement sleep behavior disorder (RBD), assessed using a questionnaire (PD with CSD and RBD indicating the body-first subtype). A total of 55 patients with PD were categorized into body-first PD (n = 37) and brain-first PD (n = 18) groups. The body-first PD group exhibited smaller voiding volume and first desire volume (FDV) than the brain-first PD group (p < 0.05 in both). Also, the body-first PD group had higher OABSS and IPSS scores, and higher prevalence of overactive bladder diagnosed by OABSS, compared to the brain-first PD group. In multiple linear regression, cardiac MIBG uptake was positively correlated with FDV and voiding volume andnegatively correlated with OABSS and IPSS (p < 0.05 in all). Patients with the body-first PD subtype exhibited more pronounced overactive bladder symptoms and impaired storage function in the early stage of disease. Additionally, cardiac MIBG was significantly associated with urological dysfunction.

Enhancing early Parkinson’s disease detection through multimodal deep learning and explainable AI: insights from the PPMI database

Parkinson’s is the second most common neurodegenerative disease, affecting nearly 8.5M people and steadily increasing. In this research, Multimodal Deep Learning is investigated for the Prodromal stage detection of Parkinson's Disease (PD), combining different 3D architectures with the novel Excitation Network (EN) and supported by Explainable Artificial Intelligence (XAI) techniques. Utilizing data from the Parkinson’s Progression Markers Initiative, this study introduces a joint co-learning approach for multimodal fusion, enabling end-to-end training of deep neural networks and facilitating the learning of complementary information from both imaging and clinical modalities. DenseNet with EN outperformed other models, showing a substantial increase in accuracy when supplemented with clinical data. XAI methods, such as Integrated Gradients for ResNet and DenseNet, and Attention Heatmaps for Vision Transformer (ViT), revealed that DenseNet focused on brain regions believed to be critical to prodromal pathophysiology, including the right temporal and left pre-frontal areas. Similarly, ViT highlighted the lateral ventricles associated with cognitive decline, indicating their potential in the Prodromal stage. These findings underscore the potential of these regions as early-stage PD biomarkers and showcase the proposed framework's efficacy in predicting subtypes of PD and aiding in early diagnosis, paving the way for innovative diagnostic tools and precision medicine.

Cerebellar involvement in Parkinson's disease: Pathophysiology and neuroimaging.

Parkinson's disease (PD) is a neurodegenerative disease characterized by various motor and non-motor symptoms. The complexity of its symptoms suggests that PD is a heterogeneous neurological disorder. Its pathological changes are not limited to the substantia nigra-striatal system, but gradually extending to other regions including the cerebellum. The cerebellum is connected to a wide range of central nervous system regions that form essential neural circuits affected by PD. In addition, altered dopaminergic activity and α-synuclein pathology are found in the cerebellum, further suggesting its role in the PD progression. Furthermore, an increasing evidence obtained from imaging studies has demonstrated that cerebellar structure, functional connectivity, and neural metabolism are altered in PD when compared to healthy controls, as well as among different PD subtypes. This review provides a comprehensive summary of the cerebellar pathophysiology and results from neuroimaging studies related to both motor and non-motor symptoms of PD, highlighting the potential significance of cerebellar assessment in PD diagnosis, differential diagnosis, and disease monitoring.

Progressive gray matter atrophy in parkinsonian variant of multiple system atrophy assessed by using causal structural covariance network.

Multiple system atrophy (MSA), a rare neurodegenerative disease, is usually accompanied by brain morphological alterations. However, the causal relationships between progressive gray matter atrophy in MSA parkinsonian (MSA-P) subtype remain unknown. In total, thirty-five MSA-P patients and thirty-five healthy controls (HC) underwent three-dimensional high-resolution T1-weighted structural imaging and voxel-based morphometry analysis. The causal structural covariance network (CaSCN) of gray matter was assessed to explore the causal relationships in MSA-P. With greater illness duration, the reduction of gray matter was originated from right cerebellum and progressed to bilateral cerebellum, fusiform gyrus, insula, putamen, caudate nucleus, frontal lobe, right angular gyrus, right precuneus, left middle occipital lobe and left inferior temporal lobe, then expanded to midbrain, bilateral para-hippocampus, thalamus, temporal lobe, inferior parietal lobule (IPL), precentral gyrus, postcentral gyrus and middle cingulate cortex. The right cerebellum was revealed to be the core node of the directional network and projected positive causal effects to bilateral cerebellum, caudate nucleus and left IPL. MSA-P patients showed progression of gray matter atrophy over time, with the right cerebellum probably as a primary hub. Furthermore, the early structural vulnerability of cerebellum in MSA-P may play a pivotal role in the modulation of motor and non-motor circuits at the structural level.

Anticipating Tomorrow: Tailoring Parkinson's Symptomatic Therapy Using Predictors of Outcome.

Although research into Parkinson's disease (PD) subtypes and outcome predictions has continued to advance, recommendations for using outcome prediction to guide current treatment decisions remain sparse. To provide expert opinion-based recommendations for individually tailored PD symptomatic treatment based on knowledge of risk prediction and subtypes. Using a modified Delphi approach, members of the Movement Disorders Society (MDS) Task Force on PD subtypes generated a series of general recommendations around the question: "Using what you know about genetic/biological/clinical subtypes (or any individual-level predictors of outcome), what advice would you give for selecting symptomatic treatments for an individual patient now, based on what their subtype or individual characteristics predict about their future disease course?" After four iterations and revisions, those recommendations with over 75% endorsement were adopted. A total of 19 recommendations were endorsed by a group of 13 panelists. The recommendations primarily centered around two themes: (1) incorporating future risk of cognitive impairment into current treatment plans; and (2) identifying future symptom clusters that might be forestalled with a single medication. These recommendations provide clinicians with a framework for integrating future outcomes into patient-specific treatment choices. They are not prescriptive guidelines, but adaptable suggestions, which should be tailored to each individual. They are to be considered as a first step of a process that will continue to evolve as additional stakeholders provide new insights and as new information becomes available. As individualized risk prediction advances, the path to better tailored treatment regimens will become clearer.

Differences in gray matter atrophy and functional connectivity between motor subtypes of Parkinson's disease.

Parkinson's disease (PD) patients with postural gait abnormalities exhibit poorer motor function scores, more severe non-motor symptoms, faster cognitive function deterioration, and a less favorable response to drugs and surgery compared to PD patients with tremor. This discrepancy is believed to be associated with more pronounced gray matter atrophy and abnormal functional connectivity. To investigate the distinctive pathological mechanisms between PD subtypes, we examined gray matter volume (GMV) and functional connectivity in patients with Parkinson's disease presenting with postural instability/gait difficulty (PD-PIGD), patients with tremor-dominant Parkinson's disease (PD-TD), and healthy controls. Voxel-based morphometry (VBM) of T1-weighted images was conducted to compare GMV among 64 PD-PIGD patients, 44 PD-TD patients, and 32 controls. Subsequently, functional connectivity within regions showing reduced GMV was compared across the groups. We analyzed whether differences among the groups were associated with clinical characteristics and neuroimaging biomarkers using partial correlation and binary logistic regression. Our comparison between PD-PIGD and PD-TD patients revealed a link between PD-PIGD and more extensive frontotemporal atrophy, potentially indicating increased basal ganglia activity accompanied by decreased cerebellum activity. Furthermore, in addition to the smaller GMV in the left middle temporal gyrus, the increased functional connectivity between this brain region and the right caudate was also the independent risk factor for PD-PIGD. In addition, we compared brain network connectivity between the PIGD and TD subtypes, using an independent component analysis (ICA). We found that Compared to PD-TD, PD-PIGD patients showed an enhanced sensorimotor network (SMN) around the left supplementary motor area. These findings suggest that severe gray matter atrophy and abnormal functional connectivity and brain networks may serve as pathophysiological mechanisms distinguishing PD-PIGD patients from other subtypes.

Differential diagnosis value of sympathetic skin response and cutaneous silent period on early-stage multiple system atrophy and Parkinson disease

PurposeEarly differentiation between Parkinson's disease (PD) and Multiple system atrophy (MSA), particularly the parkinsonian subtypes (MSA-P), is challenging due to similar clinical symptoms. We aimed to evaluate Sympathetic skin response (SSR) and Cutaneous silent period (CSP) parameters in patients with MSA-P and PD to identify possible biomarkers that could distinguish the two groups of patients in early stage. Methods22 individuals with early-stage MSA-P, 29 with early-stage PD, and 28 healthy controls were recruited from Guangdong Provincial People's Hospital. Demographic data was collected for all participants. Their SSR and CSP were evaluated using clinical electromyography equipment. Data were compared between different groups. The diagnostic accuracy of SSR and CSP parameters was calculated using the ROC curve. Logistic regression was used to produce an integration model to enhance diagnostic utility. ResultsFoot amplitude, CSP end latency and duration distinguished MSA-P from PD with the area under the curve (AUC) 0.770, 0.806, and 0.776, respectively. Foot and hand SSR amplitude distinguished PD from HC with the AUC 0.871 and 0.768, respectively. Foot SSR amplitude, hand SSR amplitude, and CSP end latency distinguished MSA-P from HC with the AUC 0.964, 0.872, and 0.812, respectively. The combination of SSR and CSP parameters differentiation between MSA-P and PD, PD and HC with the AUC 0.829 and 0.879, respectively. ConclusionsAnalysis of SSR and CSP parameters showed excellent diagnostic accuracy in discriminating patients with early-stage MSA-P from HC and good diagnostic accuracy in discriminating patients with MSA-P from PD with early stages.

Genetic analysis and natural history of Parkinson's disease due to the LRRK2 G2019S variant.

The LRRK2 G2019S variant is the most common cause of monogenic Parkinson's disease (PD); however, questions remain regarding the penetrance, clinical phenotype and natural history of carriers. We performed a 3.5-year prospective longitudinal online study in a large number of 1286 genotyped LRRK2 G2019S carriers and 109 154 controls, with and without PD, recruited from the 23andMe Research Cohort. We collected self-reported motor and non-motor symptoms every 6 months, as well as demographics, family histories and environmental risk factors. Incident cases of PD (phenoconverters) were identified at follow-up. We determined lifetime risk of PD using accelerated failure time modelling and explored the impact of polygenic risk on penetrance. We also computed the genetic ancestry of all LRRK2 G2019S carriers in the 23andMe database and identified regions of the world where carrier frequencies are highest. We observed that despite a 1 year longer disease duration (P = 0.016), LRRK2 G2019S carriers with PD had similar burden of motor symptoms, yet significantly fewer non-motor symptoms including cognitive difficulties, REM sleep behaviour disorder (RBD) and hyposmia (all P-values ≤ 0.0002). The cumulative incidence of PD in G2019S carriers by age 80 was 49%. G2019S carriers had a 10-fold risk of developing PD versus non-carriers. This rose to a 27-fold risk in G2019S carriers with a PD polygenic risk score in the top 25% versus non-carriers in the bottom 25%. In addition to identifying ancient founding events in people of North African and Ashkenazi descent, our genetic ancestry analyses infer that the G2019S variant was later introduced to Spanish colonial territories in the Americas. Our results suggest LRRK2 G2019S PD appears to be a slowly progressive predominantly motor subtype of PD with a lower prevalence of hyposmia, RBD and cognitive impairment. This suggests that the current prodromal criteria, which are based on idiopathic PD, may lack sensitivity to detect the early phases of LRRK2 PD in G2019S carriers. We show that polygenic burden may contribute to the development of PD in the LRRK2 G2019S carrier population. Collectively, the results should help support screening programmes and candidate enrichment strategies for upcoming trials of LRRK2 inhibitors in early-stage disease.

CAP2 contributes to Parkinson's disease diagnosed by neutrophil extracellular trap-related immune activity.

Neutrophil extracellular traps (NETs) constitute a crucial element of the immune system, and dysfunction in immune responses is implicated in the susceptibility and progression of Parkinson's disease (PD). Nevertheless, the mechanism connecting PD and NETs remains unclear. This study aims to uncover potential NETs-related immune biomarkers and elucidate their role in PD pathogenesis. Through differential gene analysis of PD and NETs in GSE7621 datasets, we identified two PD subtypes and explored potential biological pathways. Subsequently, using ClusterWGCNA, we pinpointed pertinent genes and developed clinical diagnostic models. We then optimized the chosen model and evaluated its association with immune infiltration. Validation was conducted using the GSE20163 dataset. Screening the single-cell dataset GSE132758 revealed cell populations associated with the identified gene. Our findings identified XGB as the optimal diagnostic model, with CAP2 identified as a pivotal gene. The risk model effectively predicted overall diagnosis rates, demonstrating a robust correlation between infiltrating immune cells and genes related to the XGB model. In conclusions, we identified PD subtypes and diagnostic genes associated with NETs, highlighting CAP2 as a pivotal gene. These findings have significant implications for understanding potential molecular mechanisms and treatments for PD.

Replication and reliability of Parkinson's disease clinical subtypes

BackgroundWe recently identified three distinct Parkinson's disease subtypes: “motor only” (predominant motor deficits with intact cognition and psychiatric function); “psychiatric & motor” (prominent psychiatric symptoms and moderate motor deficits); “cognitive & motor” (cognitive and motor deficits). ObjectiveWe used an independent cohort to replicate and assess reliability of these Parkinson's disease subtypes. MethodsWe tested our original subtype classification with an independent cohort (N = 100) of Parkinson's disease participants without dementia and the same comprehensive evaluations assessing motor, cognitive, and psychiatric function. Next, we combined the original (N = 162) and replication (N = 100) datasets to test the classification model with the full combined dataset (N = 262). We also generated 10 random split-half samples of the combined dataset to establish the reliability of the subtype classifications. Latent class analyses were applied to the replication, combined, and split-half samples to determine subtype classification. ResultsFirst, LCA supported the three-class solution – Motor Only, Psychiatric & Motor, and Cognitive & Motor– in the replication sample. Next, using the larger, combined sample, LCA again supported the three subtype groups, with the emergence of a potential fourth group defined by more severe motor deficits. Finally, split-half analyses showed that the three-class model also had the best fit in 13/20 (65%) split-half samples; two-class and four-class solutions provided the best model fit in five (25%) and two (10%) split-half replications, respectively. ConclusionsThese results support the reproducibility and reliability of the Parkinson's disease behavioral subtypes of motor only, psychiatric & motor, and cognitive & motor groups.

Swallowing Characteristics and Water Swallow Capacity in Patients with Parkinsonism.

Prevalence and characteristics of dysphagia (including aspiration) in patients with parkinsonism is variable, depending on type of assessment, diagnosis, disease stage and duration. The aim of this study was to further evaluate dysphagia characteristics in patients with different types of parkinsonism with both instrumental (Flexible Endoscopic Evaluation of Swallowing, FEES) and non-instrumental (Timed Water Swallow Test, TWST) assessments. Swallowing characteristics in 74 patients with parkinsonism were prospectively assessed using FEES and TWST. Statistics employed were (a) Spearman rank correlation to measure correlation between dysphagia results and Parkinson subtypes, disease severity and duration and (b) the non-parametric tests Mann Whitney U and Kruskal Wallis to measure difference between groups. Dysphagia was common, with 50 (67.6%) of the patients demonstrating a mild-severe Dysphagia Outcome Severity Scale (DOSS, level 1-5). During FEES, 42% aspirated and 68% of these had silent aspiration. Aspiration was seen more frequently with increased disease severity as per Hoehn and Yahr (H&Y) (r = .459, p = < 0.001) and disease duration (r = .269, p = .021). Thin liquid (IDDSI level 0) was the most common consistency to aspirate, and the frequency of aspiration decreased with thicker liquids. Dysphagia and aspiration are common in all subgroups of parkinsonism and seen in early stages of H&Y and within the first year of disease duration. Hence, it is recommended that these patients are evaluated early for optimal management and to avoid aspiration-related complications.

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

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

How Lifetime Evolution of Parkinson's Disease Could Shape Clinical Trial Design: A Shared Patient-Clinician Viewpoint.

Parkinson's disease (PD) has a long, heterogeneous, pre-diagnostic phase, during which pathology insidiously accumulates. Increasing evidence suggests that environmental and lifestyle factors in early life contribute to disease risk and progression. Thanks to the extensive study of this pre-diagnostic phase, the first prevention trials of PD are being designed. However, the highly heterogenous evolution of the disease across the life course is not yet sufficiently taken into account. This could hamper clinical trial success in the advent of biological disease definitions. In an interdisciplinary patient-clinician study group, we discussed how an approach that incorporates the lifetime evolution of PD may benefit the design of disease-modifying trials by impacting population, target and outcome selection. We argue that the timepoint of exposure to risk and protective factors plays a critical role in PD subtypes, influencing population selection. In addition, recent developments in differential disease mechanisms, aided by biological disease definitions, could impact optimal treatment targets. Finally, multimodal biomarker panels using this lifetime approach will likely be most sensitive as progression markers for more personalized trials. We believe that the lifetime evolution of PD should be considered in the design of clinical trials, and that such initiatives could benefit from more patient-clinician partnerships.

Causal role of myeloid cells in Parkinson's disease: Mendelian randomization study.

Previous studies have observed elevated myeloid cells in the peripheral blood of patients with Parkinson's disease (PD), but the causal relationship between them remains to be elucidated. We investigated whether there is a causal relationship between different subtypes of peripheral blood myeloid cells and PD using Mendelian randomization (MR) combined with bioinformatics analysis. Exploring the etiology of PD from the perspective of genetics can remove confounding factors and provide a more reliable theoretical basis for elucidating the pathogenesis of PD. Comprehensive two-sample MR analysis and sensitivity analyses were conducted to explore the causal associations between 64 myeloid cell signatures and PD risk. The Venn diagram and protein-protein interaction network analysis of instrumental variables (IV) corresponding genes were used to further investigate the potential mechanism of myeloid cells influencing the pathogenesis of PD. We investigated the impact of four immunophenotypes on the risk of PD, including Im MDSC% CD33dim HLA DR- CD66b- (relative count), CD33dim HLA DR+ CD11b+% CD33dim HLA DR+ (relative count), and CD11b on Mo MDSC (MFI) and CD11b on CD33br HLA DR+ CD14dim (MFI), while an immunophenotype's protective effect on PD was observed CD45 on Im MDSC (MFI). The results of bioinformatics analysis showed that CD33, NTRK2, PLD2, GRIK2 and RELN had protein interactions with the risk genes of PD. Our study has demonstrated a close genetic correlation between different subtypes of myeloid cells and PD, providing guidance for early identification and immunotherapeutic development in patients with PD.

Discovery of a Gut Bacterial Metabolic Pathway that Drives α-Synuclein Aggregation.

Parkinson's disease (PD) etiology is associated with aggregation and accumulation of α-synuclein (α-syn) proteins in midbrain dopaminergic neurons. Emerging evidence suggests that in certain subtypes of PD, α-syn aggregates originate in the gut and subsequently spread to the brain. However, mechanisms that instigate α-syn aggregation in the gut have remained elusive. In the brain, the aggregation of α-syn is induced by oxidized dopamine. Such a mechanism has not been explored in the context of the gastrointestinal tract, a niche harboring 46% of the body's dopamine reservoirs. Here, we report that Enterobacteriaceae, a bacterial family prevalent in human gut microbiotas, induce α-syn aggregation. More specifically, our in vitro data indicate that respiration of nitrate by Escherichia coli K-12, which results in production of nitrite that mediates oxidation of Fe2+ to Fe3+, creates an oxidizing redox potential. These oxidizing conditions enabled the formation of dopamine-derived quinones and α-syn aggregates. Exposing nitrite, but not nitrate, to enteroendocrine STC-1 cells induced aggregation of α-syn that is natively expressed in these cells, which line the intestinal tract. Taken together, our findings indicate that bacterial nitrate reduction may be critical for initiating intestinal α-syn aggregation.

The Analysis of relation to brain iron deposition of Parkinson’s Disease using Quantitative Susceptibility Mapping

Objectives: This study aimed to investigate the levels of brain iron deposition in Parkinson's disease (PD) patients using Quantitative Susceptibility Mapping (QSM) and to determine whether distinctions compared to the general population exist. Furthermore, we examined potential variations in iron deposition among different PD subtypes.Methods: Structural brain imaging was conducted on 75 participants at Gangdong Kyung Hee University Hospital between August 2017 and May 2020. PD patients were categorized into Tremor Dominant (TD) and Postural Instability and Gait Difficulty (PIGD) subtypes. Voxel-based morphometry and QSM were employed to compare voxel-wise magnetic susceptibility across the entire brain between Normal Controls (NC) and PD groups. Subsequently, QSM values were compared between TD and PIGD groups.Results: QSM values were compared among 46 PD patients and 23 normal controls, as well as between TD (n=22) and PIGD (n=24) groups. Voxel-based QSM analysis revealed no significant differences between groups. Similarly, ROI-based QSM analysis showed no significant distinctions.Conclusions: No significant variations were observed between the PD patient group, NC group, or PD subtypes. This study systematically compared QSM values across a broad range of brain regions potentially linked to PD pathology. Additionally, the subdivision of the PD group into TD and PIGD subtypes for QSM-based iron deposition analysis represents a meaningful and innovative approach.

A systematic review of salivary biomarkers in Parkinson's disease.

The search for reliable and easily accessible biomarkers in Parkinson's disease is receiving a growing emphasis, to detect neurodegeneration from the prodromal phase and to enforce disease-modifying therapies. Despite the need for non-invasively accessible biomarkers, the majority of the studies have pointed to cerebrospinal fluid or peripheral biopsies biomarkers, which require invasive collection procedures. Saliva represents an easily accessible biofluid and an incredibly wide source of molecular biomarkers. In the present study, after presenting the morphological and biological bases for looking at saliva in the search of biomarkers for Parkinson's disease, we systematically reviewed the results achieved so far in the saliva of different cohorts of Parkinson's disease patients. A comprehensive literature search on PubMed and SCOPUS led to the discovery of 289 articles. After screening and exclusion, 34 relevant articles were derived for systematic review. Alpha-synuclein, the histopathological hallmark of Parkinson's disease, has been the most investigated Parkinson's disease biomarker in saliva, with oligomeric alpha-synuclein consistently found increased in Parkinson's disease patients in comparison to healthy controls, while conflicting results have been reported regarding the levels of total alpha-synuclein and phosphorylated alpha-synuclein, and few studies described an increased oligomeric alpha-synuclein/total alpha-synuclein ratio in Parkinson's disease. Beyond alpha-synuclein, other biomarkers targeting different molecular pathways have been explored in the saliva of Parkinson's disease patients: total tau, phosphorylated tau, amyloid-β1-42 (pathological protein aggregation biomarkers); DJ-1, heme-oxygenase-1, metabolites (altered energy homeostasis biomarkers); MAPLC-3beta (aberrant proteostasis biomarker); cortisol, tumor necrosis factor-alpha (inflammation biomarkers); DNA methylation, miRNA (DNA/RNA defects biomarkers); acetylcholinesterase activity (synaptic and neuronal network dysfunction biomarkers); Raman spectra, proteome, and caffeine. Despite a few studies investigating biomarkers targeting molecular pathways different from alpha-synuclein in Parkinson's disease, these results should be replicated and observed in studies on larger cohorts, considering the potential role of these biomarkers in determining the molecular variance among Parkinson's disease subtypes. Although the need for standardization in sample collection and processing, salivary-based biomarkers studies have reported encouraging results, calling for large-scale longitudinal studies and multicentric assessments, given the great molecular potentials and the non-invasive accessibility of saliva.