Journal of Parkinson’s Disease

Background: People with Parkinsons disease (PD) experience substantial psychosocial burden, but the extent of their concern about the future is not well characterized. Objective: The objective of the present study is to characterize concerns about the future among people with PD (PwP), with an emphasis on the clinical and demographic correlates of future-oriented concerns. Methods: A survey in the online Fox Insight study platform asked PwP to rate their degree of concern about the future across seven domains: quality of life, disease progression, healthcare needs, social relationships, financial responsibilities, stigma, and specific symptoms. Relationships among uncertainty and demographic and clinical features, such as age of onset, gender, and disease severity, were examined. Latent class analysis was conducted to identify patterns of fear/uncertainty. Results: Among 3372 respondents, concerns about the future were common and spanned cognitive, functional, social, and symptom-related domains. Concerns about future cognitive impairment, independence, mobility, and disease progression were most prominent. Women and individuals with young-onset PD reported higher levels of concern than other groups. Latent class analysis revealed two clear patterns, including a high-concern subgroup with elevated worry across nearly all domains. Fewer than half of respondents had discussed these concerns with a healthcare professional. Conclusion: Future-related concerns are common among people with PD but is not routinely explored in clinical care. Greater attention to these concerns, especially for young-onset individuals and women, may help clinicians offer more timely and supportive guidance.

We report here, based on Parkinson's Progression Markers Initiative (PPMI) data, on the Cerebrospinal Fluid (CSF) profile of a group of 12 Parkinson's Disease (PD) subjects with the prototypical p.A53T SNCA mutation, comparing them to 36 matched Healthy Controls (HCs) and 36 idiopathic PD (iPD) cases. We furthermore assessed the CSF profile of 7 asymptomatic carriers of this mutation. There was no significant difference between the 3 groups of A53T-PD, HC and iPD in total alpha synuclein (a-syn) levels, beta-amyloid 1-42, total-Tau and p-Tau, although A53T-PD subjects tended to have slightly lower beta-amyloid 1-42, total-Tau and especially total a-syn levels. All A53T-PD cases had a positive CSF a-syn Seeding Amplification Assay (SAA). Four out of 7 asymptomatic carriers also had a positive SAA, in 3 without motor symptoms or signs and absence of clear prodromal manifestations. Conversion to motoric manifestations has occurred in one out of these 3 subjects, 8 years after SAA positivity, while one other subject only has hyposmia 8 years later. Overall, these results indicate that at least in early stages of PD, CSF Alzheimer's Disease profiles are not significantly different in A53T-PD compared to HCs or iPD, while the CSF a-syn SAA is universally positive in this group. Furthermore, the assay may be positive in asymptomatic carriers at a time with no prodromal manifestations and many years before motor disease onset, opening a window into very early stages of disease pathobiology and opportunities for early therapeutic intervention.

Background: Problematic Internet use (PIU) has been scarcely investigated in Parkinson's disease (PD). Objectives: To estimate the prevalence of PIU symptoms in PD using a specific screening instrument and to explore the clinical characteristics of these individuals. Methods: Two-stage observational study in a Movement Disorders clinic. In Evaluation 1, participants with PD were screened by the Brazilian Portuguese Nine-Item Problematic Internet Use Questionnaire-Short Form (BR-PIUQ-SF-9). In Evaluation 2, screening-positive participants underwent an exploratory assessment of Internet use. Results: 16.7% of participants with PD were positive for the BR-PIUQ-SF-9. The median Internet use time among these positive-screened participants was 5.5 hours per day. Most of them had impulsive-compulsive behaviors, and somatic concern, anxiety, and depressive mood were common psychiatric symptoms. Conclusions: Approximately one in six participants screened positive for PIU symptoms. Impulsive-compulsive behaviors and depressive symptoms were frequent among those undergoing subsequent exploratory assessment.

Background: Parkinsons disease (PD) has a prolonged prodromal phase, but minimally invasive molecular biomarkers distinguishing manifest PD from prodromal synucleinopathy remain insufficiently characterized. Isolated REM sleep behavior disorder (iRBD) represents a high-risk prodromal condition and provides an opportunity to investigate early blood-based transcriptional alterations. Objective: To identify peripheral blood transcriptomic signatures distinguishing healthy controls (HC), individuals with iRBD, and patients with PD, and to explore whether longitudinal iRBD samples exhibit movement toward a PD-like transcriptional state. Methods: Peripheral blood RNA-seq data were analyzed using harmonized metadata, DESeq2 differential-expression analysis, internally validated machine-learning models, PD-like projection, and integrated biomarker-panel prioritization. Independent baseline samples were used for cross-sectional differential-expression and machine-learning analyses. iRBD follow-up and post-conversion observations were excluded from baseline model development and reserved for exploratory longitudinal analyses. Results: Baseline analyses included 71 independent samples: 20 HC, 31 iRBD, and 20 PD. An additional 19 iRBD follow-up observations, including three post-conversion observations, were available for exploratory analyses. Differential-expression analysis identified 170 FDR-significant genes in PD versus HC and 85 in PD versus iRBD, compared with one FDR-significant gene in iRBD versus HC. Internal machine-learning validation showed stronger discrimination of manifest PD, with a best ROC-AUC of 0.883 for HC versus PD and 0.889 for iRBD versus PD. Discrimination between HC and iRBD was weak, with a best ROC-AUC of 0.584. PD-like projection scores were lowest in HC, highest in PD, and heterogeneous among baseline iRBD samples. Follow-up iRBD samples showed an exploratory upward shift in the mean PD-like projection score. Integrated prioritization produced a 24-gene PD candidate panel and a 24-gene exploratory iRBD panel, with genes in each panel supported by machine-learning feature-stability evidence and differential expression analysis. Conclusions: Manifest PD was associated with a distinct peripheral blood transcriptional signature, whereas iRBD-associated alterations were substantially weaker and more heterogeneous. The prioritized panels represent candidates for independent technical and external validation and should not yet be interpreted as clinically validated diagnostic or prognostic tests.

Abstract Background. Parkinson's disease (PD) is a progressive neurodegenerative disorder of increasing prevalence, with diagnostic accuracy of approximately 26% in early symptomatic patients. There is a need for accurate, non-invasive biomarkers to aid in disease diagnosis. Methods. This proof-of-concept study enrolled 90 participants (PD n = 30, other movement disorders [OM] n = 30, healthy controls [HC] n = 30) at a single institution. Participants completed two 10-minute eye-tracking sessions using the SaccadeDX 250 Hz binocular system. A two-level cascade classifier was fitted using elastic-net feature selection followed by logistic regression on the selected features, validated by 10-fold cross-validation. The cascade distinguished HC from movement disorders (Level 1) and PD from OM (Level 2), with the objective of establishing clinical validity that an eye-tracking signal correlates reliably with PD diagnosis. Results. Level 1 achieved an area under the curve (AUC) of 0.818 (95% CI: 0.71, 0.91), with a sensitivity of 83% and specificity of 63%. Level 2 achieved an AUC of 0.670 (95% CI: 0.52, 0.80), with a sensitivity of 68% and specificity of 63%. End-to-end PD detection achieved an AUC of 0.866 and an accuracy of 83.5%, meeting the prospectively specified accuracy threshold and the proof-of-concept AUC benchmark. Five adverse events were recorded (three cases of dizziness, one of nausea, and one of dry eyes); one participant withdrew from the study. Conclusions. Clinical validity is established: a reproducible eye-tracking signal for PD is detectable using a two-level cascade classifier. A multi-center confirmatory study is warranted before assessment of clinical utility.

Background: Mutations in leucine-rich repeat kinase 2 (LRRK2) are the most common genetic risk factor for Parkinson's disease (PD). G2019S, the most common pathogenic variant, has been linked to milder motor symptoms, but the effects of other LRRK2 variants on disease trajectory remain incompletely characterized. R1441G, the second most common pathogenic variant, co-occurs with the PD risk variant M1646T on a shared haplotype. Whether this haplotype confers a distinct rate of motor progression has not been established. Methods: We analyzed up to 12 years of longitudinal data from 603 participants in the Parkinson's Progression Markers Initiative (PPMI) with PD and available whole-genome sequencing data: 394 sporadic PD, 169 G2019S carriers, 20 R1441G+M1646T carriers, and 20 M1646T carriers. Motor symptom progression (MDS-UPDRS III) was assessed using linear mixed-effects models with genotype-by-time interactions, adjusted for age at onset, disease duration at baseline, sex, race, baseline score, and levodopa equivalent daily dose. Results: R1441G+M1646T carriers exhibited 76% slower progression in OFF-state MDS-UPDRS III than sporadic PD (0.50 vs. 2.04 points/year; {beta}=-1.54 [95% CI: -2.48, -0.60]; p=0.001). G2019S carriers exhibited 26% slower progression (1.52 points/year; {beta}=-0.52 [-0.99, -0.06]; p=0.03). M1646T carriers did not differ from sporadic PD (p=0.60). Slower progression in R1441G+M1646T carriers was characterized by attenuated bradykinesia (64% slower; p=0.008), axial decline (76% slower; p=0.002), and a lack of orofacial symptom progression (p<0.001). R1441G+M1646T carriers also exhibited 55% slower self-reported motor decline (MDS-UPDRS II; p=0.04) Conclusions: R1441G+M1646T carriers exhibit substantially slower motor progression than sporadic PD while M1646T carriers do not.

Background: Levodopa is time-critical in hospitalized Parkinson disease. Whether dosing fidelity depends on care setting or documented access status is unclear. Objectives: To quantify levodopa dosing fidelity, test ICU exposure with clustering-aware methods, and test whether documented access type is associated with delayed or omitted dosing. Methods: Retrospective cohort study using MIMIC-IV (2011-2022). Adults with Parkinson disease and [&ge;]1 scheduled levodopa dose contributed 1,665 admissions and 39,322 doses. ICU exposure was tested with a patient-clustered GEE model. Among ICU-exposed doses, access type (normal, tube feeding, parenteral nutrition, NPO) was modeled in one fully adjusted model and tested for specificity, restricted to the ICU, against an active-comparator medication (statins). Results: Of 39,322 doses, 79.8% were on time by the primary 60-minute definition; a symmetric {+/-}15-minute definition classified 68.8% as mistimed. ICU exposure was not associated with delayed or omitted dosing after clustering (patient-clustered OR, 0.87; 95% CI, 0.74-1.01). Among ICU-exposed doses, NPO was associated with delayed or omitted dosing (adjusted OR, 1.89; 95% CI, 1.36-2.62) and tube feeding with lower odds (adjusted OR, 0.62; 95% CI, 0.42-0.92; P < .001). The comparator medication showed a directionally consistent but inconclusive interaction (OR, 1.27-1.28; 92 patients). A route-order association was not observed among immediate-release formulations (OR, 0.72; 4 patients). Conclusions: ICU admission alone was not associated with dosing unreliability after clustering. Among ICU-exposed doses, access type, not a single pooled category, was associated with dosing reliability; a comparator-medication check, valid only in the ICU, was directionally consistent but inconclusive.

BackgroundThe relationship between essential tremor (ET) and Parkinsons disease (PD) remains controversial. Beyond viewing ET as a discrete risk factor for PD, recent frameworks propose that an ET phenotype may represent a clinical presentation of prodromal PD (pPD), consistent with the current reconceptualization of ET as a syndrome. Whether co-occurring subtle motor signs alter pPD probability in ET remains unknown. MethodsUsing the MDS research criteria, we calculated pPD probability in a large cohort of ET patients with and without subtle motor signs (rest tremor, hypomimia, isolated rigidity, reduced arm swing, altered repetitive movements, global slowing). Multivariable regression was used to identify independent predictors of pPD probability. ResultsAmong 599 ET patients (median disease duration: 12 years), only 6 (1.0%) met criteria for probable pPD. Although ET patients with subtle motor signs exhibited higher continuous pPD probability scores than those without, the frequency of possible or probable pPD did not differ significantly between groups. In multivariable regression, neither ET nor individual subtle motor signs, but hypomimia, were independent predictors of pPD probability, which was primarily driven by older age and male sex. ConclusionsLong-standing ET, whether isolated or accompanied by subtle motor signs, is not associated with pPD, with the possible exception of co-occurring hypomimia.

LRRK2 is implicated in Parkinson's disease (PD) microbiome-gut-brain axis. We compared plasma lipopolysaccharide-binding protein (LBP) and soluble CD14 (sCD14), markers of gut permeability and endotoxin exposure, in PD patients with/without LRRK2 p.G2385R and/or p.R1628P, and controls, and examined their associations with systemic inflammation and clinical severity. Neither marker differed between groups. Across PD patients, LBP correlated with higher IL-6, TNF- and worse motor function, while sCD14 correlated with higher IL-6, CCL5 and worse constipation. These findings highlight the clinical relevance of endotoxin-related immune signaling in PD, without LRRK2 risk variant-specific associations and identify LBP as an emerging marker of inflammatory burden.

Blood-based (BB) biomarker investigations in Parkinson disease (PD) and in mild traumatic brain injury (mTBI) have substantially grown over the past decade. High risks for PD in young post-mTBI veterans have been inferred from medical record data using actuarial modeling. However, potential utility of BB biomarkers to quantify risks vs. no risk for PD in young post-mTBI veterans has not been established. Previously we reported post-mTBI veterans performed significantly below the standardized normative scores for their age and education level on specific domains of executive functioning, on par with senior aged individuals with early-stage PD. Here, we examined serum brain-derived neurotropic factor (BDNF), ubiquitin C-terminal hydrolase-L1 (UCH-L1), glial fibrillary acidic protein (GFAP), and S100 calcium-binding protein {beta} (S100B) in association with executive functioning outcomes in search of a bio-cognitive model suitable to differentiate risk from no risk for prodromal PD. A reference range of bio-cognitive cut-points were derived from Area Under the Curve (AUC) sensitivity and specificity methods. Our data revealed two bio-cognitive signatures with reference range cut-points when GFAP was paired with cognitive flexibility / attention scores, and when S100B was paired with categorical / semantic verbal memory scores. Both bio-cognitive signatures revealed prodromal PD risk vs.no-risk parameters that remained relevant for differentiating young veterans who had encountered a past mTBI and those who had not experienced a mTBI. Subjects with early-stage PD who had withstood a mTBI up to 10- to 40-years earlier were also differentiated from those who had no mTBI history. These results indicate the predictive utility of expanding the biomarker field to include reference ranges, cut-points, and specific cognitive domains to estimate risks for PD in a clinic setting. These preliminary data also add value in establishing a quantifiable bio-cognitive risk signature to identify prodromal PD risks in young adults prior to obvious cognitive and motor decline. While encouraging, these data require further follow-up with a larger sample size in a longitudinal design to validate these findings.

Background: Motor complications, such as motor fluctuations and Levodopa-induced dyskinesias (LID), significantly impair quality of life in persons with Parkinson's disease (PD) on long-term Levodopa treatment. Predicting their onset is crucial for tailored patient care. Objectives: To develop and evaluate machine learning (ML) models to forecast the onset of new motor fluctuations and LID in PD patients within three years from baseline assessment, and to assess how training cohort composition influences performance. Methods: A comprehensive ML workflow with repeated Nested Grid Search Cross-Validation was applied to real-world clinical data from a multicentric cohort of 247 PD patients. ML models were rigorously evaluated on the clinically relevant subgroup free of motor complications at baseline. SHAP analysis provided model explainability. Results: Models achieved moderate predictive power for both LID (SVC: MCC 0.28 {+/-} 0.14) and motor fluctuations (Voting MCC = 0.32 {+/-} 0.18). For LID prediction, the strongest predictors were the Levodopa Equivalent Daily Dose (LEDD), baseline motor fluctuations, and duration of Levodopa therapy, with risk increasing significantly above a LEDD threshold of 300-400 mg. A critical ablation study revealed that excluding patients with pre-existing complications caused a collapse in model sensitivity, highlighting their essential role in defining the upper bound of predicted risk. Conclusions: The model-based risk assessment is consistent with established clinical factors. Inclusion of the full spectrum of disease severity, including patients with pre-existing motor complications, in the training set is essential for achieving a robust probabilistic risk scale and reliable model calibration for new-onset prediction.

Background: Pathogenic variants in GCH1 have been associated with Parkinson's disease (PD), but the clinical phenotype and longitudinal disease course of GCH1-associated PD remain incompletely characterized. Objectives: To characterize the genetic spectrum, clinical phenotype, and longitudinal progression of GCH1-associated PD across multiple populations. Methods: Whole-genome sequencing (WGS) and clinical exome sequencing (CES) data from the Global Parkinson Genetics Program (GP2) were analyzed together with unpublished and published GCH1-associated PD patients. Variant pathogenicity was classified according to ACMG criteria. Demographic, clinical, and longitudinal features were compared between GCH1 P/LP variant carriers and non-carrier PD patients; individuals with known pathogenic variants in PD-associated genes were excluded from both groups. Results: In the GP2 cohort (PD, n=22,825; controls, n=4,453), 16 pathogenic or likely pathogenic (P/LP) GCH1 variants were identified in 58 individuals, including 54 PD patients, one control, and three individuals with other neurodegenerative phenotypes (two with progressive supranuclear palsy and one with dementia with Lewy bodies). In the pooled-ancestry WGS analysis, GCH1 P/LP variants were enriched in PD patients versus controls (0.267% vs 0.023%; OR=11.854; 95% CI=1.620-86.699; p=0.0006). Variant frequencies in PD patients ranged from 0.121% to 0.714% across ancestries. In the CES cohort, P/LP variants were identified in 0.201% of PD patients. After integrating GP2 with additional unpublished and published datasets, 119 GCH1-associated PD patients were analyzed. Compared with noncarriers, carriers of P/LP GCH1 variants had an earlier age at onset (mean [SD], 53.7 [14.8] vs 59.2 [11.7] years; P < .001), lower levodopa equivalent daily dose requirements (mean [SD , 467.5 [331.7] vs 680.3 [466.4] mg/d; P < .001), and a higher frequency of a family history of Parkinson disease (47.6% vs 19.9%; P < .001). Adjusted Cox models showed significant delayed progression to motor fluctuations (HR=0.32, 95% CI=0.16-0.62) and levodopa-induced dyskinesias (HR=0.51, 95% CI=0.30-0.87). Conclusion: GCH1 pathogenic variants were associated with a clinically distinct phenotype characterized by earlier disease onset and slower progression of motor complications. These findings suggest that GCH1 genetic variants may serve as genetic biomarkers for patient stratification and prognosis in PD.

Background: Non-motor symptoms, including sleep and cognitive dysfunction, are major contributors to reduced quality of life in people with Parkinsons disease (PwPD). Dance has been proposed as a promising intervention to improve quality of life in PwPD. Previously, we reported longitudinal trajectories of global cognition following community-based dance; however, little is known about its long-term influence on sleep-related non-motor symptoms and their relationship with global cognitive performance. Objective: We examined the six-year trajectories of sleep and overall non-motor symptom severity among PwPD participating in weekly community-based dance classes compared to a sedentary Reference group. As a secondary objective, we evaluated their association with global cognitive performance as a functional outcome. Methods: This longitudinal observational study followed PwPD engaged in community dance participation as well as a matched sedentary control group from the Parkinsons Progression Markers Initiative database over six years. Generalized estimating equations (GEE) were used to model group-level trends, with sensitivity analyses conducted to assess the robustness of the findings. Results: Non-motor outcomes showed that insomnia worsened significantly within the Reference group (p = .003) but improved among dancers (p = .005), with daytime sleepiness remaining stable across both groups. When sleep was used as a predictor of cognition, global cognitive performance trended to improve in the Dance group (p = .078) and declined mid-period in the Reference group (p = .014). In addition, overall non-motor symptom severity worsened in the Reference group (p = .011) but remained stable in the Dance group. Constipation also worsened significantly in the Reference group (p = .012) compared to the Dance group. Conclusion: The present study demonstrates that community-based dance may support select non-motor symptoms, including insomnia, and cognitive resilience in PwPD. Findings reinforce dance as a valuable, real-world, non-pharmacological approach to slow functional decline in PD.

Background The global burden of Parkinson's disease (PD) has increased substantially over recent decades, driven by population ageing and rising age-standardized prevalence. In Africa, accurate estimates remain limited due to a lack of recent, methodologically robust population-based studies. Objectives To determine the current age-standardized and sex-specific prevalence rates of PD in Nigeria. Methods We conducted a 2-stage, cross-sectional population-based door-to-door survey among adults aged [&ge;]18 years in two densely populated urban local government areas in Lagos State, Nigeria, between April 1, 2024 and January 31, 2025. The first stage involved a household census and screening for parkinsonism using a standardized screening tool. The second stage consisted of in-person clinical assessment and diagnostic confirmation by physicians using established clinical diagnostic criteria. Crude and age-standardized prevalence rates (to the World Health Organization World Standard and European Standard Populations) were calculated. Results 31,009 individuals (52.7% female) from 13,222 households were surveyed, and 70 persons were diagnosed with PD. The crude prevalence ratio was 225.7 per 100,000, with higher prevalence in males (53/14658, 361.6) than females (17/16,351, 104.0). The age-standardized prevalence rate (95% confidence interval) was 193 per 100,000 (150 -- 245) (females: 86 (50 -- 137); males: 277 (207 -- 362)), and increased with advancing age. The diagnostic gap (previously undiagnosed) was 60.0% (42/70). Treatment gap (never treated) was 44/70 (62.9%). Conclusions The age-standardized prevalence of PD is higher than previously reported in sub-Saharan Africa. These findings provide contemporary data to inform updated estimates of disease burden and support health systems planning.

Importance Alzheimer disease (AD) is frequently accompanied by co-pathologies such as Lewy bodies, intracellular protein aggregates consisting of misfolded -synuclein, ubiquitin and several other proteins. These aggregated proteins contribute to the pathological and clinical heterogeneity of AD and are associated with a more rapid progression. Cerebrospinal fluid (CSF) measurement of aggregated -synuclein or skin biopsy histochemistry are the current biomarkers for Lewy body pathology in individuals with Parkinson's disease and related synucleinopathies but are invasive, not easily scalable for large studies or practical in clinical practice. Neuron-derived extracellular vesicles (nEVs) provide a feasible and tolerable alternative to detect Lewy body pathology. nEVs exit across the blood-brain barrier and deliver neuron-derived proteins into the systemic circulation, offering direct access to brain-level protein concentrations from peripheral blood, not afforded by conventional plasma biomarkers. Objective To use nEVs extracted from plasma to measure brain-derived -synuclein levels as a clinical biomarker of Lewy body pathology and synucleinopathy across clinically and pathologically characterized cohorts. Design, Setting, and Participants This multicohort observational study evaluated plasma nEV-derived -synuclein levels in 1,304 individuals, including 794 (61%) individuals without dementia, 469 (36%) individuals with AD, and 41 (3%) individuals with PD across four cohorts. Postmortem validation was performed from autopsy data in 127 individuals, including 96 (76%) individuals without, and 31 (24%) with, Lewy body pathology. Cerebrospinal fluid (CSF) -synuclein seed amplification assay data were available in a small subset of 54 (4.1%) of the group. Amyloid positron emission tomography (PET) data were available in 901(69.1%) of the total group. Exposure Clinical diagnosis, AD biomarker positivity, Lewy body pathology, CSF -synuclein seed assay status, and amyloid PET positivity. Main Outcomes and Measures Plasma nEV-derived -synuclein levels normalized to CD9 and assessed in relation to clinical diagnosis, AD biomarker status, neuropathologically confirmed Lewy body pathology, CSF seed assay results, and amyloid PET positivity. Results Compared with controls, plasma -synuclein levels from nEVs were significantly elevated among individuals with PD (controls mean 0.51, SD=0.24 vs PD mean=0.69, SD=0.23, P=8.66*10-). nEV-derived -synuclein levels were also significantly higher in P-tau181 and P-tau217 positive individuals with and without cognitive impairment compared to P-tau negative individuals. Elevated nEV-derived -synuclein levels were subsequently validated in individuals with postmortem Lewy body pathology (28.6% higher mean levels, P=0.02). Among 54 individuals with CSF -synuclein seed amplification assay, 8 (15%) were positive and showed a 18.2% increase in mean nEV -synuclein levels compared to individuals with negative -synuclein seed amplification. nEV-derived -synuclein levels were also significantly elevated in amyloid PET positive individuals with and without dementia (5.8% higher mean levels, P=8.50E-03) and clinical AD (9.3% higher mean levels, P=6.38E-12). Conclusions and Relevance Plasma -synuclein levels from nEVs likely reflect underlying synuclein pathology in the brain and have potential as a blood-based biomarker for detecting Lewy body pathology in PD and in AD and related dementias. nEVs cross the blood-brain barrier and carry neuron-derived cargo directly into the bloodstream, thus providing a unique window into brain -synuclein levels that is not accessible through conventional plasma biomarkers.

Background: Freezing of gait (FOG) is a disabling and often underrecognized feature of Parkinsons disease (PD). Objective gait analysis may improve characterization of this motor symptom. Objective: To compare quantitative 3D gait parameters in PD with FOG (PDF) and PD without FOG (PDNF) in a routine clinical cohort. Methods: We retrospectively analyzed a sequential sample of 180 patients with PD referred for motion analysis between 2020 and 2024. All patients underwent 3D motion capture in the off-medication state. Eighteen gait outcomes spanning pace, rhythm, postural control, variability, and asymmetry domains were derived from steady-state walking tasks. FOG status was determined using physician documentation and Movement Disorder Society Unified Parkinsons Disease Rating Scale (MDS-UPDRS) items. Group differences between PDF (n=99) and PDNF (n=81) were evaluated using independent samples t-tests, with outcomes adjusted for disease duration and corrected for multiple comparisons. A secondary analysis among PDF compared those in Hoehn and Yahr (H&Y) stage [&ge;]III to those in H&Y [&le;]II. Results: PDF had longer disease duration, higher OFF MDS-UPDRS III scores, and higher Hoehn and Yahr stage than PDNF but were similar in age and sex. After adjusting for disease duration and multiplicity, PDF demonstrated reduced step length, stride length, and forward velocity, and greater cadence variability, while most postural control, and asymmetry measures were comparable between groups. Among PDF, advanced H&Y stage was associated with impaired pace and rhythm, similar to previous reports among PD in general. Conclusion: In this large, sequential, clinically referred cohort, FOG was associated with more advanced PD and specific impairments in pace and gait variability. These findings support comprehensive 3D gait analysis as an objective tool to better delineate FOG-related gait abnormalities and identify features that may predict FOG, informing targeted interventions.

Background. Cognitive impairment in Parkinson's disease (PD) is highly prevalent and heterogeneous. Assessing multiple cognitive domains is challenging and risks redundancy. This study evaluated whether a discriminant analysis approach could optimize the selection of specific tasks and measures for identifying attention and memory deficits in PD. Methods. Thirty PD patients and 25 cognitively unimpaired (CU) controls completed four experimental tasks: two assessing attention (flanker and spatial Stroop), one for recognition memory, one for working memory (n-back). Following group-level difference analyses, a discriminant analysis was performed to identify which tasks, and performance metrics possessed the highest sensitivity for distinguishing PD patients from CU individuals. Results. At the group level, PD patients exhibited significantly worse conflict costs in both attention tasks and lower sensitivity scores (d') in the recognition memory task compared to CU controls. The discriminant analysis revealed that time-based measures from the spatial Stroop task and the sensitivity score from the recognition memory task provided the highest discriminating power to differentiate between the two groups. Conclusion. These findings suggest that cognitive deficits in PD can be identified with high diagnostic accuracy using a targeted subset of metrics, eliminating the need for extensive and redundant neuropsychological testing batteries for attention and memory, without needing an extensive number of cognitive tasks for attention and memory.

By utilizing a targeted genetic assay within a Fox Insight cohort (N = 1,987), this research establishes a hybrid, transparent, and interpretable predictive framework. Initial modeling via Firth penalized logistic regression discovered enrichment regarding the GBA N370S locus (OR = 0.01, FDR < .001), highlighting the critical role of epidemiological evaluation in enriched, human study populations. Advanced ensemble learning methods, refined through a meta-learner gradient boosting machine, attained an out-of-sample AUC of 0.929 on 15% of the analysis dataset partitioned via random sampling and strictly held-out from model training. Both global, visual machine learning explanations and local-Shapley interpretations provide transparency into the models and individual predictions representative of practical, collaborative human-artificial intelligence efforts, offering a solution that supports classification while remaining accessible and economical.

The heterogenous clinical and pathophysiological presentation of idiopathic Parkinson's Disease (iPD) suggests the existence of underlying distinct biological subtypes. A better definition of PD subtypes is crucial for the development of target disease modifier approaches. Using data from the Parkinson ' s Precision Medicine Initiative (PPMI) cohort, we aimed to identify distinct biological subtypes of iPD through data-driven cluster analysis leveraging currently available biomarker data. We included n=225 de novo iPD subjects. Individuals with known genetic forms of PD were excluded. A total of 22 biomarkers reflecting different biological pathways (neurodegeneration, proteinopathy, neuroinflammation, mitochondrial impairment, and lipid metabolism/autophagy-lysosomal dysfunction) and measured in cerebrospinal fluid (CSF), whole blood, serum, plasma, or urine were selected. Hierarchical clustering was performed using ward.D2 method and Gower dissimilarity. Clinical-demographic characteristics of the identified clusters were compared at baseline and 5-year follow-up. We identified three clusters: Cluster I (''Mitochondrial-Predominant'' subtype); Cluster II (''Cryptic'' subtype); Cluster III (''Mixed Pathology'' subtype). The ''Mitochondrial-Predominant'' and ''Mixed Pathology'' subtypes showed higher levels of CSF mitochondrial DNA deletions and ND1 compared to the ''Cryptic'' subtype. The ''Mixed Pathology'' subtype was also characterized by higher levels of serum NfL, CSF p-tau, CSF GFAP, CSF YKL-40, and lower levels of plasma total ceramide, glucosylceramide, and sphingomyelin compared to the other subtypes. In the ''Cryptic'' subtype no clear dominant biological profile was detected. Clinically, subjects belonging to the ''Mixed Pathology'' subtype were older and predominantly male. No differences in 5-year clinical progression were found between clusters. While most of the previous research has performed a biological characterization of the clinical subtypes of PD, with our work we propose a biology-driven clustering in a large cohort if subjects with iPD. We identified three biological subtypes. The ''Mitochondrial-Predominant'' subtype was characterized by alterations exclusively of biomarkers reflecting mitochondrial dysfunction. The ''Mixed Pathology'' subtype, in contrast, was characterized by biomarker alterations across all explored pathological pathways. Finally, the ''Cryptic'' subtype included subjects whose biomarker signature did not indicate predominant alterations in any of the explored pathways. The clusters did not differ in terms of baseline clinical-demographic characteristics, except for age and sex. No difference in mid-term clinical progression was observed between subtypes.

Background. The VPS35 p.D620N variant causes autosomal dominant Parkinson's disease (PD) and has been shown to activate the LRRK2 kinase pathway, resulting in increased Rab substrate phosphorylation in peripheral immune cells and elevated urinary bis(monoacylglycero)phosphate (BMP) levels. Recently, a VPS35 variant of unknown significance (c.959C>T; p.A320V) was described in two late-onset sporadic PD patients. Methods. We ascertained a family from the Canary Islands in which six siblings were chronically exposed to high doses of pesticides. Three siblings developed levodopa-responsive, akinetic-rigid PD, while the other three remained unaffected. Whole-exome sequencing was performed in the three affected siblings. The frequency of the resulting candidate variant was assessed in 23,327 PD patients and 9,235 controls from four independent cohorts. Members of this pedigree and unrelated controls were assessed for LRRK2 kinase activity in monocytes and neutrophils and BMP levels in urine. Results. The three affected siblings were all heterozygous for p.A320V, whereas the three unaffected siblings did not carry the variant. In the combined PD case-control cohort, p.A320V was identified in six patients and one control. However, unlike p.D620N, heterozygous carrier status for p.A320V was not associated with increased LRRK2 kinase activity or elevated urine BMP levels. Conclusions. While VPS35 p.A320V co-segregated with PD in this family, it did not exhibit the characteristic LRRK2-associated biomarker signature observed in VPS35 p.D620N carriers. It is possible that p.A320V exerts a subtle effect on VPS35 function that was not captured by the assays performed and that chronic pesticide exposure contributed to disease penetrance in this pedigree.