npj Parkinson's Disease

Extracellular vesicles (EVs) hold promise as minimally invasive biomarkers for neurodegenerative proteinopathies, but disease- and stage-specific profiles remain unclear. For this study, we enrolled 378 participants across five centers and the MJFF-BioFIND cohort: 100 healthy controls [HC], 64 isolated REM sleep behavior disorder [iRBD], 41 DeNovo Parkinsons Disease [PD], 89 Late PD, 32 other Synucleinopathies, and 52 Tauopathies. All participants underwent clinical evaluation and blood collection. The 77 subjects from the BioFIND cohort also provided CSF samples. EV concentration and size were assessed by nanoparticle tracking analysis; flow cytometry quantified tetraspanins (CD9/CD63/CD81) and 37 surface markers. Multivariable logistic regression, receiver operating characteristic analyses (ROC), and repeated random forest (rRF) classifiers evaluated diagnostic utility. Late PD showed the highest EV concentrations compared to HC and other disease groups. Participants exhibited distinct EV surface immunophenotypes, with the iRBD group displaying the most extensive immune activation signature vs HC, followed by PD patients. Multivariate logistic regression analysis identified diagnostic marker panels: CD3/CD9/CD25/CD56 for iRBD, SSEA4 for Late PD, CD146/CD209 for Synucleinopathies, and CD8/CD45/CD62P for Tauopathies. ROC confirmed good discriminatory performance, with CD56 emerging as the strongest single predictor for iRBD vs HC, SSEA4 showing high sensitivity for Late PD, and marker combinations providing optimal balance for Synucleinopathy/Tauopathy classification vs HC. In the CSF BioFIND subset, Late PD EVs exhibited increased myeloid (CD1c), adhesion (CD29), activation (CD69), and epithelial (CD326) markers compared to HC. Among these, CD326 was independently associated with Late PD diagnosis. Machine learning classifiers using all 37 surface antigens achieved excellent training performance (91.7-94.3% accuracy for iRBD/Synucleinopathies vs HC) and maintained robust validation accuracy, particularly for iRBD (77.8%) and DeNovo PD (76.6%) vs HC. EV immuno-phenotyping reveals distinct signatures across the neurodegenerative proteinopathies spectrum, with the highest diagnostic utility for prodromal iRBD detection. Longitudinal validation and cell-of-origin refinement represent key next steps toward clinical translation.

Parkinsons disease (PD) is a neurodegenerative disorder characterized by a prolonged prodromal stage that culminates in motor deficits. Current PD therapies primarily alleviate symptoms, underscoring the need for disease-modifying strategies. Glucagon-like peptide-1 (GLP-1) analogs showed early promise as candidate disease modifiers, but recent clinical results have been inconsistent, and their mechanism of action remains poorly defined. Here, we employed our SncaG51D/G51D knock-in mouse model to investigate the effects of subcutaneously administered GLP-1 analogs, semaglutide and lixisenatide. Both analogs reversed motor and non-motor deficits and reduced gliosis and detergent-insoluble -synuclein. Bulk and single-nuclei transcriptomics together with CellChat-based intercellular communication analysis revealed that GLP-1 analogs normalize early striatal mitochondrial and inflammatory dysregulation and restore neuregulin (NRG) and neurexin (NRXN) signaling networks to wild-type levels. Treatment was effective when initiated either before or shortly after symptom onset, defining an early therapeutic window for GLP-1 analog therapy in PD.

Background: Parkinson's disease (PD) has a prolonged prodromal phase during which non-motor symptoms (NMS) may emerge years before the appearance of classical motor signs. This makes NMS a promising and clinically accessible source of information for early risk stratification. Objective: In this study, we investigated whether NMS alone can serve as reliable predictors of PD risk using clinical data from the Parkinson's Progression Markers Initiative (PPMI) cohort. Methods: We developed a stacked ensemble machine learning framework that integrates feature-level modelling, a global multivariate model, and a patient-similarity component to capture complementary patterns within NMS profiles. The model was trained using leakage-controlled patient-level validation and evaluated on an independent held-out test set. Results: The final ensemble achieved strong predictive performance, with an area under the ROC curve of 0.955, sensitivity of 0.929, and specificity of 0.900. Explainability analysis further showed that olfactory dysfunction, gastrointestinal symptoms, urinary and other autonomic features, and selected cognitive measures were among the most influential predictors. These findings support the hypothesis that NMS are not merely associated features of PD, but can function as meaningful predictors of disease risk even without imaging or biomarker inputs. Additionally, the final validated model is implemented as a web-based research prototype to demonstrate real-time translational feasibility. Conclusion: Overall, this study highlights the predictive value of NMS for PD risk assessment and supports their use in research-oriented early screening frameworks.

Background: Parkinson's disease (PD) is the second most common progressive neurological disorder that is pathologically characterized by the loss of dopaminergic neurons within the substantia nigra (SN). However, disease progression probably involves coordinated changes across both neuronal and glial cell populations. Although single-nucleus RNA-seq resolved cell-type-specific transcriptional profiling, differential expression and regulatory interpretation are commonly reported separately; however, they may limit the mechanistic prioritization to uncover novel therapeutic targets. Methods: Here, we performed sample-aware pseudobulk framework analysis on single-nucleus transcriptomes obtained SN of PD and control donors. Cell-type-specific differential expression for PD vs. control was identified using edgeR quasi-likelihood modeling (FDR < 0.05; |log2FC| > 0.5). Further, to quantify disease-specific remodelling, we computed one-vs-rest cell-type specificity scores in each condition and defined delta-specificity as the PD-control shift. We further prioritized the gene-set for dopaminergic neurons and microglia based on edge R significance and delta-specificity shifts, followed by upstream regulatory assessment using transcription factor enrichment and subnetwork visualization using ChEA-KG. Moreover, we used Cellchat to identify altered cell-cell communication networks to infer differences between both conditions. Results: Dopaminergic neurons demonstrated upregulation of neuronal-state remodeling transcriptional programs related gene sets in PD group, including receptor signaling and contact/guidance pathways (e.g., CHRM3, ROBO1, PLXNA4, UNC5D, EFNA5), neuronal excitability homeostatsis, RNA components, cellular traffickings and proteostasis, suggesting coordinated remodeling in surviving neuronal population. Microglia exhibited a compact PD-associated signature enriched for regulatory and activation state-related genes. TF networks analysis revealed distinct regulatory subnetwork in each population,including BNC2-centered network in microglia and an NPAS3-centered network in dopaminergic neurons with embedded ZNF804A and chromatin-associated components. Conclusions: In summary, integrating pseudobulk, delta-specificity scoring and TF-network enrichment analysis provides coherent dopaminergic and microglial programs in PD substantia nigra. This framework prioritizes cell-type-specific potential candidate mechanisms for downstream validation. The inferred regulatory networks and interactions are hypothesis generating and need orthogonal validation, such as spatial or proteomics approaches and independent cohorts.

Aggregates of misfolded -synuclein (Syn) and neuroinflammation are pathological features of Parkinsons disease (PD). These, misfolded conformations of Syn promote cytokine and chemokine signaling in the surrounding microenvironment by triggering activation of glial cells through pattern recognition receptors. Microglia and astrocytes act as innate mediators of the neuroimmune response in the brain by regulating inflammatory signaling via paracrine and autocrine forms of cell communication. Extracellular vesicles (EVs) represent a form of glial cell to cell communication that can regulate the glial neuroimmune responses depending on the phenotype of the donor cell. Research has shown that the contents of EVs can be altered via pharmacologically altering the donor cell which offers a potential avenue for the regulation of inflammation. As such, we analyzed enriched mouse cortical primary astrocytes and characterized their response to Syn exposure in the absence and presence of microglia-derived EVs. Using trans-resveratrol, a naturally occurring polyphenol implicated for its anti-inflammatory properties, as our pharmacological agent to generate an anti-inflammatory microglial-derived EV phenotype we found that EVs derived from resveratrol-treated microglia decreased the production of proinflammatory molecules in enriched astrocytes exposed to Syn. Sequencing of EV miRNAs revealed two miRNAs (miR-5099 and miR-115) with significant up-regulation in resveratrol EVs compared to control EVs. Astrocytes transfected with corresponding miRNA mimics prior to Syn exposure showed a dramatic decrease in inflammatory biomarker production. These findings show that microglia-derived EVs and their specific miRNA cargo can attenuate Syn-directed inflammation in astrocytes and may serve as a novel therapeutic for proteinopathies like PD.

Background: PD GENEration (NCT04057794, NCT04994015), sponsored by the Parkinson's Foundation in partnership with Aligning Science Across Parkinson's (ASAP) through the Global Parkinson's Genetics Program (GP2), is an international, observational, clinical research study that offers genetic testing and counseling to people living with Parkinson's disease (PwP) at no cost. PD GENEration has aimed to empower PwP and their clinicians with knowledge of their genetic status, to accelerate recruitment into precision medicine trials, and to advance research through data sharing. Since its launch in 2019, the study has expanded to enroll over 32,000 PwP (as of March 31, 2026), from 10 countries across North, Central, and South America, the Caribbean, and Israel. Methods: Over the course of 6 years, PD GENEration has evolved to accommodate the growing scientific and research needs of the Parkinson's community while also increasing the ability to return genetic test results to PwP at a greater scale. Participants with a diagnosis of Parkinson's disease (PD) may enroll in-person or virtually where informed consent and blood sample collection can occur. Samples are analyzed at a College of American Pathologists/Clinical Laboratory Improvement Amendments (CAP/CLIA)-certified laboratory using whole genome sequencing, with variants curated for a primary panel of seven PD-associated genes. Results are disclosed during a genetic counseling visit, where further testing is offered for two optional additional gene panels. Those who consent undergo analysis of additional genes, and results are returned during a genetic counseling visit for those that test positive for a variant. In addition to returning genetic results to PwP, a central pillar of the study design has been the open sharing of genomic data to advance discovery in PD research in partnership with ASAP and GP2. Discussion: PD GENEration applies a flexible framework, allowing for country specific considerations and the integration of multiple site models, evolving based on participant needs and the prioritization of equity and accessibility. We summarize PD GENEration's implementation and scaling, highlight key accomplishments and lessons learned, and provide guidance for those interested in implementing large-scale clinical genetic testing studies across other diseases and therapeutic domains.

Objective To map national Parkinsons disease (PD) research capability to inform an inclusive delivery strategy for a large-scale clinical trial. Background Few people with PD participate in clinical trials, particularly from under-served populations. The Edmond J Safra Accelerating Clinical Trials in PD initiative (EJS ACT-PD) aims to deliver an inclusive multi-arm multi-stage (MAMS) disease modification PD trial. Methods A survey disseminated to National Health Service (NHS) hospitals assessed PD research capability regarding trial experience, rater expertise, trial facilities and specialist investigations. A process was developed to categorise sites into 3 tiers, with tier 1 having the least PD-research capability or experience, and tier 3 being experienced specialist centres. We mapped tiers to PD prevalence, social deprivation and ethnic diversity to identify infrastructure gaps. We developed trial delivery strategies to facilitate rapid and inclusive recruitment. Results Out of 97 survey responses, 43 sites were categorised as tier 1, 33 as tier 2 and 21 as tier 3. Diversity and social deprivation index were higher for tier 3 sites (predominantly urban). A greater proportion of tier 1 and 2 sites were situated in areas of higher PD prevalence (predominantly rural). Ninety one percent of sites reported experience with remote trial delivery methods. Our delivery strategy included: initial trial set-up at tier 3 sites to enable rapid and ethnically diverse recruitment; core funded staff within strategic sites to develop regional solutions for inclusive trial participation and to enable research opportunity provision in areas where currently very little exists, and a hybrid delivery model of in-person and remote study visits, ensuring maximal acceptability and deliverability. Conclusions The mapping of current PD research delivery capability has allowed us to develop a trial delivery strategy that will broaden the provision of research participation opportunity to under-served groups. It has also enabled existing infrastructure to be maximised while mitigating identified gaps.

BackgroundHeterozygous mutations in the GBA1 gene encoding the enzyme glucocerebrosidase (GCase) represent the most common genetic risk factor for developing Parkinsons disease (PD). The underlying mechanisms by which GBA1 mutations lead to PD through both loss- and gain-of-function effects remain unclear. There is a strong rationale for the generation and characterisation of a humanised GBA1 mouse model to allow the effect of GBA1 mutations on GCase function to be studied within the context of the human protein. MethodsWe have generated novel humanised mutant GBA-L444P and wild type GBA-WT mouse models using BAC recombineering and site-specific integration allowing the incorporation of the whole GBA1 locus as a transgene, including the endogenous promoter, all exons and introns, and flanking regions. Our experimental design crossed each GBA1 transgene onto a Gba+/- background and included Gba+/- littermate controls in our cohorts, allowing us to explore both the loss- and gain-of-function of GBA1 mutations. We have carried out "deep phenotyping" to characterise these mice by biochemical, stereological and behavioural testing, and assess dopamine release and content using fast-scan cyclic voltammetry and high performance liquid chromatography. ResultsThe GBA-L444P mice showed a significant reduction in GCase activity by 18 months of age and preferentially expressed a high molecular weight form of the GCase protein, likely due to retention in the ER and aberrant glycosylation. The GBA-L444P, but not Gba+/-, mice demonstrated an early and persistent reduction in dorsal striatal dopamine release in the absence of any dopaminergic cell loss or deficits in dopamine synthesis or reuptake, compared to human wild-type controls. GBA-L444P and Gba+/- mice developed an accumulation of oligomeric -synuclein pathology, but only GBA-L444P mice demonstrated subtle but significant changes in behaviour. ConclusionsThe novel humanised GBA-L444P mouse model described here helps to resolve gain- or loss-of-function effects of GBA1 mutations seen in Parkinsons as well as providing a novel set of models to investigate the human protein. Our work demonstrates that changes in dopamine release and behavioural deficits arise from a gain-of-function mechanism, whereas -synuclein pathology arises from GCase loss-of-function.

Background: Reliable biomarkers for Parkinson's disease (PD) pathology detection are essential for research. The alpha-synuclein (aSyn) seed amplification assay (SAA) is a validated biomarker for misfolded aSyn. Objectives: To assess the association between aSyn SAA and LRRK2-related PD (LRRK2-PD) and its link to mitochondrial genetic burden. Methods: We included N=76 LRRK2 p.Gly2019Ser variant carriers (N=22 affected, N=54 unaffected), N=714 patients with idiopathic PD (iPD), and N=411 controls from Norway. We analyzed cerebrospinal fluid (CSF)-based aSyn SAA in N=10 PD patients and N=30 unaffected LRRK2 p.Gly2019Ser carriers, alongside N=6 controls and N=56 iPD patients. A mitochondrial polygenic score (MGS) was derived from genotyping data, using PPMI as an additional cohort (iPD: N=355, LRRK2-PD: N=118). Results: Seeding was observed in 80% of patients with LRRK2-PD, and in one unaffected variant carrier (AUC=0.97, CI 0.92-1.00). In a meta-analysis across two PD cohorts, higher MGS was associated with increased aSyn seeding (pooled beta=0.38, p=0.028). Conclusions: CSF-based aSyn SAA can discriminate between LRRK2-PD and unaffected carriers. Our findings support an association with mitochondrial burden and aSyn seeding.

-Synuclein nitration is a prominent post-translational modification in Parkinsons disease, but whether nitrated -synuclein merely reflects oxidative stress or actively contributes to pathology remains unclear. Here, we generated and characterized 6G6, an antibody selective for Tyr39-nitrated -synuclein, and tested whether targeting this modified -synuclein species affected pathology in different mouse models of -synuclein aggregation and spread. In two models of -synuclein overexpression targeting medullary vagal neurons, oxidative stress was induced by either exposure to the herbicide paraquat or transgenic heterozygous expression of the Gba1-L444P mutation. Both conditions were characterized by robust -synuclein spreading that was markedly counteracted by 6G6 administration. A third model consisted of an injection of -synuclein fibrils into the striatum of -synuclein-overexpressing mice. In this model, treatment with 6G6 protected against fibril-induced aggregate pathology and ensuing degeneration of nigral dopaminergic neurons. In a pilot human study, CSF levels of Tyr39-nitrated -synuclein were measured and found increased in Parkinson patients as compared to controls. These findings identify Tyr39-nitrated -synuclein as a pathogenic, therapeutically targetable -synuclein species linking oxidative/nitrative stress to PD pathological processes.

Background Sleep disturbances affect up to 60-80% of people with Parkinsons disease (PD) and are associated with worse clinical outcomes and reduced quality of life. Dyskinesia is a common motor complication of dopaminergic therapy, but its relationship with sleep quality remains incompletely defined. Methods Forty-seven people with PD (median age 68 years; 44.7% female; median disease duration 5 years; 38.3% from non-White ethnic background) were assessed for sleep quality on Pittsburgh Sleep Quality Index (PSQI). Dyskinesia was assessed using Movement Disorder Society-Unified Parkinsons Disease Rating Scale (MDS-UPDRS) Part IV items 4.1 and 4.2, and 7-day wearable monitoring with the Parkinsons KinetiGraph (PKG) to derive median dyskinesia score (DK_50) and fluctuation dyskinesia score (FDS). All analyses were conducted using multivariate regression. Associations with sleep quality were adjusted for age, sex, and disease severity (MDS-UPDRS Part III) in Model A; additionally for levodopa equivalent daily dose (LEDD) in Model B; and further for disease duration in Model C. Results In Model A, all four dyskinesia measures were significantly associated with sleep quality. After adjusting for LEDD in Model B, only DK_50 remained a significant predictor of worse sleep (B=0.18, 95CI: 0.003-0.357, P=0.047). With additional adjustment for disease duration in Model C, the association for DK_50 was attenuated (B=0.18, 95%CI: -0.001 to 0.356, P=0.051). Conclusions Wearable-derived continuous dyskinesia burden was independently associated with worse sleep quality, whereas clinician-rated dyskinesia was not, highlighting the added clinical value of objective motor monitoring in PD. Disease duration may partly confound this relationship. Larger prospective studies are warranted.

BackgroundParkinsons disease (PD) gut metagenomic studies have repeatedly reported disease-associated shifts in microbial taxa, genes, and pathways. However, the field still lacks transparent trait-level indices that summarize biologically coherent microbial exposures. Curli fibres are extracellular bacterial amyloids produced by several Enterobacteriaceae and related taxa, and they provide a plausible microbiological bridge between gut microbial ecology, epithelial/immune interfaces, and alpha-synuclein-centered gut-brain-axis hypotheses. We introduced Curli Carrier Burden (CCB), a mathematically explicit, taxon-informed index that estimates the aggregate abundance of curated curli-carrier bacterial taxa in processed metagenomic profiles. MethodsA curated curli-carrier candidate panel was converted into an evidence-weighted taxon set. For sample s, CCB was defined as [Formula], where ais is the processed relative abundance of matched curli-carrier taxon i and wi is an evidence weight reflecting curli-carrier confidence. We evaluated CCB in five main PD gut metagenomic evidence streams: Wallen 2022, Integrated-US, Mao Central China, Romano non-Wallen, and DuruIC 2024. Results were interpreted cohort-wise rather than as a formal meta-analysis. ResultsThe CCB framework generated a reproducible sample-level microbial trait variable and enabled cohort-wise comparison of amyloidogenic bacterial burden. Wallen showed discovery-stage PD-associated elevation (724 samples; 31 matched curli taxa; Mann-Whitney p = 0.0020). Integrated-US provided supportive independent evidence (244 samples; 18 matched taxa; p = 0.0079). Mao Central China and DuruIC 2024 showed the same PD-greater-than-control direction by mean and median CCB, although their individual comparisons were not nominally significant. Romano non-Wallen provided a large multi-study analysis (600 samples; 29 matched curli-associated mOTUs taxa), with higher PD mean and median CCB in pooled analysis (p = 0.0036, Cliffs{delta} = 0.137) and cohort-sensitive behavior under study-stratified permutation (p = 0.1974). Additional processed-cohort checks indicated that CCB interpretability depends on taxonomic representation and matched curli-candidate coverage, reinforcing the value of explicit compatibility reporting. ConclusionsCCB is a novel, extensible, microbiology-informed index for quantifying amyloidogenic curli-carrier bacterial burden in processed gut metagenomic profiles. The current results support CCB as a useful exploratory trait-level variable for PD microbiome research and provide a principled route toward future raw-read, csg-operon, strain-resolved, and phenotype-aware studies of the curli-vagal PD axis.

Introduction. The cerebellum is increasingly recognized as a key contributor to cognitive reserve and network adaptation in Parkinsons disease (PD). However, how cerebellocortical and cerebellobasal ganglia connectivity reorganizes across disease duration and cognitive status remains incompletely understood. Methods. Resting state fMRI data from the Parkinsons Progression Markers Initiative were analyzed in 172 individuals with PD. We investigated cerebellobasal ganglia and cerebellocortical connectivity using ROI to ROI and seed to voxel pipelines respectively, providing novel insights into both subcortical and cortical effects. Effects of age, disease duration, cognitive status, motor symptom severity, and dopaminergic medication were assessed. Results. Across all participants, cerebellar lobule VI and vermis VI showed robust positive connectivity with the pallidum, along with high intracerebellar coupling. When controlling for dopaminergic medication, lobule V connectivity with the primary motor cortex was reduced. Age was associated with lower cerebellobasal ganglia connectivity widespread across nodes, evident across medication states. Disease duration showed region specific effects: in cognitively normal PD, longer duration corresponded to stronger lobule V and temporal cortex connectivity as well as higher Crus I and precentral gyrus connectivity than PD with cognitive dysfunction. Motor symptom severity was not related to connectivity. Conclusions. Cerebellar connectivity patterns in PD are linked to disease duration and cognitive preservation. Enhanced cerebellocortical coupling in cognitively normal PD may reflect compensatory network recruitment that diminishes with cognitive decline.

Background Neuropsychiatric fluctuations in Parkinson's disease (PD) often accompany motor fluctuations, but their temporal relationship during the acute levodopa response remains unclear. Objectives To determine whether motor and neuropsychiatric responses occur synchronously during the OFF-to-ON transition. Methods Nineteen fluctuating PD patients underwent a high-resolution levodopa challenge with repeated assessments every 10 minutes for 60 minutes after levodopa administration. Motor symptoms (akinesia, rigidity) and neuropsychiatric fluctuations were quantified. Transition times (t25%-t50%-t75%-t100%) and response profiles were analyzed using correlation and clustering approaches. Results Motor and neuropsychiatric transition times were not correlated at any threshold (all FDR-corrected p>0.05; Bayes factors <1), supporting temporal dissociation. Among 18 patients with complete data, clustering revealed synchronous (6/18), neuropsychiatric-preceding (7/18), and motor-preceding (3/18) profiles. Conclusion Motor and neuropsychiatric responses to levodopa during PD fluctuations are partly independent and follow heterogeneous, patient-specific temporal profiles, supporting the search for distinct biomarkers and future individualized adaptative therapies

Increased iron in the substantia nigra has been thought to be a mechanism potentially related to the etiology and/or progression of Parkinson's disease (PD). We hypothesized that genetic variants of HFE, a major iron regulatory gene, would influence substantia nigra iron accumulation in PD. The HFE genotype was obtained from 195 subjects (102 PD and 83 Controls) who participated in the PD biomarker program (PDBP) in central Pennsylvania, United States. For this study, carriers of two SNPs (HFE H63D and/or C282Y) were considered as variants and the others as wildtype. Susceptibility MRI metrics (QSM, R2*) were assessed at baseline, 18, and 36 months. The primary region of interest was the substantia nigra, the key pathology focus of PD. Group differences in substantia nigra QSM and R2* between HFE variants carriers and wildtype were compared between PD patients and controls at baseline and in progression over time using linear mixed-effects model. We also used interaction analyses to explore if HFE genotype impacts clinical measures of PD progression. Of the 102 PD patients, 72 were wildtype, and 30 HFE variant. Of the 83 controls, 56 were wildtype and 27 were HFE variants. There was a total of 451 data points available for analysis. Compared to wildtype patients, patients with HFE variants showed higher baseline substantia nigra QSM (p=0.006), but not higher R2* (p=0.487). Controls had no HFE-dependent differences. Longitudinally, substantia nigra QSM and R2* increased significantly over both 18- and 36-months regardless of HFE status (p's<0.05). Compared to wildtype, PD subjects with HFE variants showed an overall faster increase in R2* (p=0.004) and QSM (p=0.003) over the total 36-month epoch, and this reached the statistical significance for R2* during the first 18-months (p=0.026) and for QSM in 36-months (p=0.005). HFE status showed a significant interaction with motor scales [MDS-UPDRS II (p=0.006), III (p=0.0002)], suggesting a faster symptomatic progression in PD patients with HFE variants compared to wildtype. Although HFE genotype has been shown not to associate with the occurrence of PD, these data demonstrate for the first time that in PD patients substantia nigra iron accumulation and disease progression are affected by HFE genotype. The underlying mechanisms may be important in the progression of PD and the development of personalized treatment.

Subthalamic local field potential (STN-LFP) activity within patient-specific beta frequency ranges is an established biomarker for adaptive deep brain stimulation (aDBS) in Parkinsons disease (PD). While beta power correlates with akinetic-rigid symptoms, it is also modulated by physiological states such as sleep, highlighting the importance of understanding state-dependent spectral dynamics for adaptive stimulation. We continuously recorded STN-LFP spectra in ten PD patients over two weeks in both conventional and adaptive DBS. We show that sleep-related reductions in beta power occur independently of stimulation mode and are primarily associated with broadband aperiodic spectral changes across both low and high beta bands rather than periodic beta oscillations. These findings support the integration of aperiodic spectral features into future adaptive neuromodulation algorithms to improve biomarker specificity and optimize aDBS in PD.

Astrocytes are key regulators of lipid metabolism, and dysregulated astrocytic lipid processing is implicated in Parkinsons disease (PD) pathogenesis. Our prior genome-wide screens identified ACSBG1, an astrocyte-enriched acyl-CoA synthetase, as a candidate regulator of -synuclein (-Syn) levels. However, how ACSBG1 links lipid reprogramming to inflammatory astrocyte activation and -Syn pathology remains unknown. We compared the transcriptomic, cytokine, and lipid secretomes of TNF- and IL-1 stimulated primary astrocytes from wild-type (WT) and Acsbg1 knockout (KO) mice. In vivo, we crossed Acsbg1 KO mice with a Thy1--Syn PD model to assess behavior, neuroinflammation, synaptic integrity, and -Syn levels. Following cytokine exposure, Acsbg1 KO astrocytes mounted an attenuated inflammatory transcriptional response, secreting significantly fewer inflammatory mediators (e.g., IL-6, RANTES, MIP-3) and less long-chain Sphingosine 20:1 than WT astrocytes. Importantly, exogenous Sphingosine 20:1 or cytokines from WT reactive astrocytes induced neuronal -Syn phosphorylation (pS129). In vivo, Acsbg1 deletion in Thy1--Syn mice reduced astrogliosis, rescued synaptic and behavioral deficits, and decreased total and pS129--Syn. These findings establish ACSBG1 as a key regulator of inflammatory astrocyte signaling that contributes to -Syn phosphorylation via specific cytokine and lipid mediators, identifying ACSBG1 as a novel therapeutic target for modulating astrocyte-neuron communication in PD.

Parkinsons disease (PD) pathogenesis often involves progressive -synuclein (-Syn)-mediated neuronal dysfunction, yet the earliest cellular events that link -Syn pathology to circuit failure remain poorly defined. Here, we used human induced pluripotent stem cell (iPSC)-derived dopaminergic (DA) neurons from patients carrying the familial A53T SNCA mutation to reconstruct a temporal course of dysfunction in vitro. We identified a biphasic trajectory with an early phase of hyperexcitability, characterized by elevated spontaneous firing, followed by a progressive transition into hypoexcitability as the neurons mature, accompanied by reduced network activity, synaptic dysfunction, and -Syn accumulation. Transcriptomic profiling at the critical transition point revealed a dual transcriptional signature, with upregulation of stress-inflammatory pathways (p53, JAK-STAT, apoptosis) coupled with systematic downregulation of metabolic and synaptic maintenance genes. This molecular profile preceded functional collapse, linking early hyperactivity-driven metabolic stress to subsequent neuronal exhaustion. To counteract this pathology, we used extracellular vesicles (EVs), small membrane-bound particles carrying intercellular signals, as a cell-free treatment approach. Strikingly, treatment with EVs derived from healthy iPSCs completely rescued both electrophysiological deficits and pathological -Syn accumulation, restoring normal firing patterns, synaptic function, and network activity. Consistent with these observations, EV treatment reduced -Syn aggregation and improved motor responses in -Syn fibril-injected mice, which are characterized by pathological -Syn accumulation and motor deficits. Overall, these findings demonstrate that EVs derived from healthy iPSCs can reverse PD-related phenotypes in human and mouse models.

Cognitive decline is a major non-motor feature of Parkinsons disease (PD), but reliable and accessible biomarkers remain limited. Resting-state electroencephalography (EEG) is a promising candidate because it is low-cost, portable, and well suited to repeated assessment. Recent work has increasingly focused on source-space functional connectivity (FC) for the prediction of cognition. However, the influence of source-modelling based on an individualized MRI-based head model relative to that based on standard template model is unknown. To compare these two source-space EEG FC methods, we analysed EEG data from the New Zealand Parkinsons Progression Programme, including 136 people with PD and 51 age-similar controls. Source reconstructed resting-state EEG was parcellated with the HCP-MMP1 atlas, and used to derive amplitude envelope correlation (AEC) and debiased weighted phase lag index (dwPLI) across six canonical frequency bands. The twenty-four FC modalities were evaluated using six machine-learning regression algorithms within a nested cross-validation framework. Theta-, alpha-, and beta-band FC showed the most consistent prediction of global cognition, with the strongest performance observed for theta- and alpha-band AEC and dwPLI features (maximum R{superscript 2} = 0.170, r = 0.439). Standard and individualized head models showed comparable predictive performance across nearly all modalities. Feature-importance patterns for Cole-Anticevic networks were also highly similar between the two head-model options. These findings show that source-space resting-state EEG FC can predict cognitive performance in PD. The comparability of the two head models suggests that the more user-friendly and less resource intense standard head model template is satisfactory. This supports feasible, scalable, and clinically accessible EEG-based biomarkers of cognition in PD.

AO_SCPLOWBSTRACTC_SCPLOWO_ST_ABSBackgroundC_ST_ABSExcessive or unregulated iron in the brain can lead to toxicity via ferroptosis and related mechanisms. Iron accumulation in the substantia nigra (SN) occurs with Parkinsons disease (PD) progression and has been hypothesized to be an etiological mechanism. ObjectiveBased on emerging clinical observations, we tested the hypothesis that iron accumulation in the SN is a consequence of levodopa administration and is treatment-related rather than an intrinsic etiological mechanism. MethodsWe used both unilaterally lesioned 6-OHDA and unlesioned rats. We administered levodopa to rats at doses that were allometrically calculated to be similar to those used in mid-stages of PD. Iron-sensitive MRI (R2*) was used to quantify iron in the brain. Both group and intra-subject analyses were done using paired t-tests and linear mixed models. ResultsExperiment 1 used the unilateral 6-OHDA model to take advantage of the almost complete lack of dopamine neurons on the lesioned side. This permitted testing if levodopa-induced iron accumulation occurred in and/or depended on dopamine neurons. Fifteen days of levodopa treatment caused a marked increase in Fe in both the lesioned (p = 0.042) and unlesioned sides (p = 0.005), showing that iron accumulation does not depend on the presence of dopamine neurons. Based on these data, in experiment 2 unlesioned rats were administered levodopa daily for four months, and iron (R2*) values were assessed at baseline, 1, 2, and 4 months. In these normal rats, the levodopa-treated group had significantly increased Fe (R2*) in the substantia nigra compared to the vehicle group (p = 0.013). Interestingly, these effects were limited to the striatum, with no increases seen in the striatum, ventral tegmental area, or frontal cortex ConclusionLevodopa triggers processes that increase iron deposition in the substantia nigra, but this process may not depend on dopamine neurons. The underlying mechanisms and the effect on PD progression are important to elucidate and may transform how we understand PD and related neurodegenerative disorders