Journal of Parkinson’s Disease

IntroductionMotor complications are major determinants of disability in Parkinsons disease (PD), yet clinician-rated motor complication severity does not fully explain variability in health-related quality of life (HRQoL). Research questionTo examine the contribution of illness perceptions and cognitive-behavioural responses to HRQoL alongside motor complication severity in people with PD. MethodsThis multi-centre, cross-sectional study recruited 58 people with idiopathic PD (median age 68 years; 55.2% male; 48.3% from minoritised ethnic backgrounds; Hoehn & Yahr stage 2-3). All underwent assessment of motor complications (Movement Disorder Society-Unified Parkinsons Disease Rating Scale; MDS-UPDRS Part IV) and HRQoL (Parkinsons Disease Questionnaire-39 Summary Index; PDQ-39 SI). Illness perceptions were measured with Illness Perception Questionnaire-Revised (IPQ-R) Part 2, and cognitive-behavioural responses with Cognitive and Behavioural Responses Questionnaire (CBRQ). Regression models were adjusted for age, sex, disease duration, motor severity (MDS-UPDRS Part III), levodopa equivalent daily dose (LEDD), anxiety, depression, and cognitive function. A subset (n=47) completed 7-day Parkinsons KinetiGraph monitoring. ResultsDemographic and clinical covariates explained 77.3% of variance in HRQoL (R{superscript 2}=0.773). Adding motor complication severity explained a significant additional 3.7% ({Delta}R{superscript 2}=0.037, P=0.004). Subsequent inclusion of illness consequences (IPQ-R) and catastrophising (CBRQ) explained a further 4.1% ({Delta}R{superscript 2}=0.041, P=0.004), yielding a final adjusted R{superscript 2} of 0.815. In the fully adjusted model, catastrophising (B=0.797, P=0.027) and perceived consequences (B=0.767, P=0.013) remained independently associated with HRQoL. ConclusionHRQoL in PD appears to depend not only on motor complication severity, but also on patients interpretations and responses. Clinicians should assess both to guide holistic care and support adaptive coping.

Background: Gait variability is a hallmark of Parkinson's disease (PD) and has been linked to cognitive deficits and fall risk. Rapid eye movement sleep behavior disorder (RBD) is a strong predictor of synucleinopathies, yet evidence for gait changes in RBD is inconsistent. Performing a dual task increases gait variability, an effect that can be quantified using a cost function. Objective: Determine the degree to which dual task cost differs between control, RBD, and PD participants at baseline, and between RBD converters versus non-converters at follow-up. Methods: 46 RBD, 23 control, and 14 PD participants completed standardized gait analysis at baseline. Parameters chosen for analysis included enhanced gait variability index (eGVI), functional ambulation performance (FAP), velocity, step length, cadence, base of support, and double support time. Medical records were surveilled for 3 years following participant enrollment, determining that 6 RBD participants converted to PD or dementia. Baseline gait indices and dual task costs were compared between control, RBD, and PD groups at enrollment, and between RBD stable and RBD converters at follow-up. Results: The PD group had greater eGVI, as well as greater dual task cost for FAP, cadence, width, and double support time. No differences in gait variability were identified between RBD and control groups at baseline. Compared to the stable group, RBD converters had greater dual task cost for FAP, velocity, cadence, and double support time. Conclusions: Increased gait variability during dual task may identify RBD patients at imminent risk of phenoconversion.

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.

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.

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

BackgroundEffective screening for Parkinson disease (PD) is important for both symptomatic treatment and recruitment into intervention trials. We recently developed a toolkit to quantify PD risk. Here, we examined the PREDIGT models diagnostic performance when deployed at home. MethodsWe contacted 613 subjects following outpatient clinic encounters. Between 2022-2024, 305 participants (range, 40-85 years) were recruited: 93 with typical PD; 66 had other neurological diseases (OND); 146 were neurologically healthy. Two versions of the toolkit were completed: First, an original, 69-item-long questionnaire paired with a 40-scent smell test; thereafter, a simplified, 11-item-long questionnaire and a newly developed, 8-scent smell test. PREDIGT summary scores were calculated for each subject to examine diagnostic classifications. Area-under-the-ROC-curve, sensitivity, specificity, and likelihood ratios were used to evaluate performances and to determine clinically relevant thresholds. ResultsIn both versions, PD patients had higher questionnaire scores and lower smell test scores than neurologically healthy controls (p<0.001); scores for OND subjects ranked at intermediate levels. The simplified questionnaire outperformed the original version in diagnostic accuracy. The abbreviated smell test performed as well as the 40-item version in identifying hyposmia. At a value of 22.94 (range 0-100) for the threshold that separates PD subjects from other participants, the simplified PREDIGT summary score showed a sensitivity of 0.98, a specificity of 0.83, and revealed positive and negative likelihood ratios of 5.88 and 0.02, respectively. InterpretationOur study reveals that unsupervised screening for typical PD can be effectively carried out at home using an 11-item questionnaire and 8-scent smell test.

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.

Abstract/SummaryO_ST_ABSBackgroundC_ST_ABSCerebrospinal fluid (CSF) -synuclein seed amplification assay (SAA) has emerged as a diagnostic biomarker for Parkinsons disease (PD) and has been linked to differences in disease severity and progression. However, whether SAA status predicts responsiveness to levodopa remains unknown. We investigated the longitudinal association between SAA status, levodopa responsiveness, dopaminergic denervation, and motor complications in sporadic PD. MethodsIn this longitudinal analysis, PD participants from the Parkinsons Progression Markers Initiative (PPMI) cohort with CSF SAA testing who initiated levodopa treatment were included. SAA- and SAA+ patients were matched on sex, age, and disease duration at treatment initiation. Motor severity was assessed using MDS-UPDRS Part III, with proportional and absolute responsiveness derived from ON and OFF medication states. Motor complications were assessed using MDS-UPDRS Part IV, and dopaminergic dysfunction was quantified using caudate DAT-SPECT. Linear mixed-effects models examined longitudinal differences as a function of SAA status. FindingsIn this analysis, 40 SAA- patients were compared to 183 matched SAA+ patients. SAA+ patients showed a slower rate of ON-state motor progression than SAA- patients (0.87 vs 3.47 points/year; p = 0.01). Consistently, proportional levodopa responsiveness increased over time in SAA+ patients while declining in SAA- patients (p = 0.036). These differences were accompanied by lower caudate DAT binding at treatment initiation in SAA- patients (p = 0.002) and faster dopaminergic decline over time (p = 0.008). Although SAA+ patients had fewer motor complications at treatment initiation, their progression was similar. InterpretationCSF -synuclein SAA status is associated with divergent levodopa response in PD, with SAA+ patients showing sustained and progressively greater motor benefit, while SAA- patients show declining responsiveness. Faster dopaminergic denervation in SAA- patients may underlie this difference. SAA status captures clinically relevant heterogeneity that may inform patient stratification and therapeutic decision-making.

Importance: The real-world prevalence and the clinical determinants associated with cognitive impairment in diverse patients with Parkinson disease (PD) have been understudied. Objective: To determine the prevalence of cognitive impairment in a diverse PD cohort and explore associations with vascular, motor, and nonmotor factors. Design, setting and participants: Case-only analysis of diverse patients with PD recruited to the East London Parkinson disease project (July 2022 to July 2025) at the Royal London Hospital, a tertiary referral center. Of 237 patients with cognitive status defined by expert, multi-disciplinary, clinical consensus, 223 remained after excluding atypical or secondary parkinsonism, other dementias, and study withdrawal. Exposures: Observational study (no experimental intervention); exposures included vascular risk factors, motor and nonmotor clinical features. Main Outcome(s) and Measure(s): The main outcome was cognitive impairment (PDCI), defined as mild cognitive impairment (PDMCI) or dementia (PDD) by expert clinical consensus based on clinical, imaging, and cognitive screening. Results: Among 223 participants with a median disease duration of 4.0 (1.0-9.0) years, 112 (50.2%) had PDCI, including 62 (27.8%) with PDD and 50 (22.4%) with PDMCI. South Asian ethnicity was associated with PDCI in univariate analysis (OR, 2.30; 95% CI, 1.32-4.00, P = .003) and the association strengthened after adjusting for age, gender, years of education, disease duration and depression scores (OR, 3.60; 95% CI, 1.68-7.69, P < .001). PDCI was associated with increased odds of smoking (OR, 3.62; 95% CI, 1.56-8.41, P = .003) in the adjusted model. Increased odds were also associated with motor severity (Movement Disorders Society Unified Parkinson Disease Rating Scale Part III; OR per point increase 1.07; 95% CI, 1.04-1.10; P < .001), and daytime somnolence score (Epworth Sleepiness Scale; OR per point increase, 1.08; 95% CI, 1.01-1.16; P = .03). Conclusions and Relevance: In this multi-ethnic study of PD using gold-standard expert multidisciplinary consensus, cognitive impairment was common and more prevalent among South Asian individuals. Smoking, greater motor severity, and higher daytime somnolence were associated with increased odds of cognitive impairment.

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: 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.

We investigated whether people with Parkinson's disease who are dual GBA1+LRRK2 carriers have a milder, LRRK2-like phenotype as previously reported. This was accomplished by comparing clinical features and alpha-synuclein seed amplification assay (SAA) positivity rates between dual GBA1+LRRK2-PD(n=13), GBA1-PD(n=169) and LRRK2-PD(n=175) carriers in a cross-sectional retrospective study of Parkinson's Progression Markers Initiative (PPMI) data. Our results show that GBA1+LRRK2-PD rate(83%) is closer to GBA1-PD rate(87%) rather than LRRK2-PD rate (62%mp-value>0.05). GBA1+LRRK2-PD have both non-motor and motor phenotypic similarity of GBA1-PD(p-value>0.05). This small PPMI cohort indicates that dual GBA1+LRRK2-PD carriers' SAA positivity and phenotype are aligned with GBA1-PD.

Importance: Dementia is a common and disabling complication of Parkinson's disease (PD). Blood-based biomarkers that identify individuals at higher risk of future dementia could improve prognostication and trial stratification. Objective: To determine whether blood-based proteins are associated with future risk of dementia in PD. Design, Setting, and Participants: Prospective longitudinal cohort study with discovery and replication analyses in the Oxford Parkinson's Disease Centre (OPDC) Discovery cohort and the Parkinson's Progression Markers Initiative (PPMI). A total of 1,335 participants with PD and 431 healthy controls, with serum, plasma, or cerebrospinal fluid proteomic data and follow-up of up to 12 years, were included. Main Outcomes and Measures: Incident dementia, defined using a composite of MoCA scores, MDS-UPDRS items, and clinician diagnosis. Associations between baseline protein levels and time to dementia were evaluated. Results: Among 1,335 participants with PD, 168 developed incident dementia across cohorts (OPDC Discovery [serum], n = 108; PPMI Project 293 [plasma], n = 23; PPMI Project 181 [CSF], n = 37). In the OPDC cohort, GFAP was the only protein (of 5,408 tested) significantly associated with incident dementia (HR = 2.43; 95% CI: 1.79-3.30; p-adjust =1.35 x 10-4). Higher GFAP tertiles were associated with greater cumulative dementia incidence. Findings were replicated in the PPMI plasma project (HR = 2.42; 95% CI: 1.12-5.22; p = 0.024) but not in the CSF project (HR = 0.96; 95% CI: 0.66-1.39; p = 0.82). Higher baseline GFAP was significantly associated with lower baseline cognitive performance and greater longitudinal cognitive decline but no significant association with motor progression. In both cohorts, GFAP levels increased over time but showed no group-level differences. Conclusions and Relevance: Circulating GFAP is a robust and reproducible predictor of future dementia in PD, detectable early in the disease course. While the lack of differential longitudinal trajectories between PD patients with and without dementia suggests that GFAP does not act as a dynamic marker of cognitive decline, its relative stability supports its role as an early indicator of underlying biological vulnerability or subclinical pathology. These findings support serum GFAP as a promising, accessible biomarker for early dementia risk stratification.

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.

Background: Lysosomal dysfunction plays a crucial role in the pathogenesis of Parkinson's disease (PD), particularly among GBA1 mutation carriers. Beyond GBA1, genes such as TMEM175, SCARB2, and CTSB identified in genome-wide association studies (GWAS) are also implicated in lysosomal pathways contributing to PD risk, although their functional effects in patients remain unclear. Proteins encoded by these lysosome-related genes have been explored as potential therapeutic targets in experimental models. Biomarker profiles, including clinical measures, alpha-synuclein seeding activity, lysosomal proteins, and sphingolipids, may facilitate patient stratification and support therapeutic monitoring in future clinical trials. Aim: The aim of this study is to investigate the impact of genetic variants of three lysosomal-related genes (TMEM175, SCARB2, and CTSB) on biomarker profiles in PD with and without GBA1 variants. Cross-sectional data from two German cohorts: the Tuebingen Parkinson Cohort (TUEPAC) and the DESCRIBE PD cohort of the German Center for Neurodegenerative Diseases were used as explorative cohorts, and data from Accelerating Medicines Partnership Parkinson's Disease (AMP-PD) were used as a validation cohort. The ultimate goal is to provide new data for patient stratification based on genetics, which might serve as a readout for target engagement and treatment efficiency assessment. Methods: Three cohorts were analyzed: TUEPAC, DESCRIBE PD, and AMP-PD. TUEPAC and DESCRIBE PD were combined into a single German discovery cohort (TUEPAC-DESCRIBE-PD), while AMP-PD served as an independent validation cohort. Within each cohort, for subgroup analyses, PD patients were classified as the overall PD cohort (PDall), and further stratified by GBA1 mutation status into PD patients without GBA1 mutations (PDGBA1_wildtype), and PD patients carrying GBA1 mutations (PDGBA1). We evaluated cognitive and motor function, as well as depression using the Montreal Cognitive Assessment (MoCA), Unified Parkinson Disease Rating Scale-part III (UPDRS III), and Beck Depression Inventory-II(BDI-II) scales. Analyzed biomarkers included CSF -syn seeding activity using seed amplification assay (SAA), CSF lysosomal protein levels of lysosomal integral membrane protein 2 (LIMP2), also known as SCARB2, cathepsin B (CTSB) and lysosome-associated membrane protein 2 (LAMP2), blood-based enzyme activity of the lysosomal glucocerebrosidase (GCase), and CSF sphingolipid profiles. PD patients carrying risk alleles in TMEM175, SCARB2, and CTSB were compared to non-carriers. Results: Genotype-phenotype correlation analysis in TUEPAC-DESCRIBE-PD and AMP-PD revealed: (1) In PDall, the TMEM175 p.M393T risk variant was nominally associated with decreased cognitive function when adjusted for GBA1 mutation status in TUEPAC-DESCRIBE-PD; this association could not be replicated, although a similar trend was observed in the slightly smaller, but multicentric AMP-PD cohort; TMEM175 p.M393T was not significantly associated with BDI-II or UPDRS-III scores in either cohort. (2) In PDGBA1_wildtype, GCase activity was significantly lower in PD patients with SCARB2 rs6812193 risk allele in TUEPAC-DESCRIBE-PD, while a similar but non-significant trend was observed in AMP-PD; (3) In PDall, CSF levels of CTSB were nominally lower in carriers of CTSB rs1293298 risk allele compared to carriers of CTSB rs1293298 protective allele in TUEPAC-DESCRIBE-PD; in PDGBA1_wildtype, LAMP2 was significantly lower in carriers of CTSB rs1293298 risk allele compared to carriers of CTSB rs1293298 protective allele in TUEPAC-DESCRIBE-PD; (4) In PDall, TMEM175 p.M393T risk allele was nominally associated with altered sphingolipid profiles across both TUEPAC-DESCRIBE-PD and AMP-PD cohorts. Conclusion: These findings demonstrate that genetic variants in lysosomal-related genes (TMEM175, SCARB2, and CTSB) have a functional impact on biomarker profiles in PD patients. Integrating genetic characterization with biochemical profiling provides a framework for patient stratification and may serve as a translational strategy to monitor target engagement and evaluate treatment efficacy in future clinical trials.

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.

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.

Purpose: The purpose of this study was to identify subgroups of talkers with Parkinsons disease (PD) with shared tongue, lip, and jaw articulatory amplitude behaviors. The study also sought to identify demographic and clinical features that can distinguish the identified kinematic subgroups. Methods: 53 talkers with PD and 54 controls participated. Articulatory amplitudes of the tongue, lip, and jaw were measured during a paragraph reading task using three-dimensional electromagnetic articulography. Amplitude performance profiles of the tongue, lip, and jaw were established for each talker with PD by referencing their performance to that of controls. These profiles were submitted to a hierarchical cluster analysis to identify kinematic-based subgroups. Amplitude performances were compared across subgroups to determine between-group patterns. Demographic and clinical features (e.g., age, sex, disease duration, selected perceptual speech characteristics, dysarthria severity) were compared across the identified kinematic subgroups. Results: Four main kinematic subgroups with differing amplitude performance profiles were identified. One subgroup exhibited normal to mildly exaggerated or mildly reduced amplitudes and was labeled preclinical subgroup (n = 16). Three subgroups exhibited pronounced amplitude reductions of either the tongue (n = 10), the tongue and lips (n = 12), or the tongue, lips, and jaw (n = 10). In addition, there were five talkers with PD whose performance profiles did not align with the identified four subgroups. Their performance was characterized by either pronounced amplitude exaggerations or mildly reduced jaw and lip amplitudes and exaggerated tongue amplitudes. None of the demographic or clinical features differed significantly between the main four subgroups. Conclusion: Findings suggest that the extent to which hypokinesia manifests within the articulatory subsystem can vary in talkers with PD. Longitudinal studies are needed to determine if these subgroups represent different stages of disease progression or distinctly different manifestations of the disease within the articulatory subsystem.

BackgroundPhenoconversion to Parkinsons disease (PD) or dementia with Lewy bodies (DLB) currently relies on established clinical diagnostic criteria. Availability of in vivo biomarkers--CSF -synuclein seed amplification assay (CSFaSynSAA) and dopamine transporter (DAT) imaging--offer the opportunity to investigate congruency between clinical phenoconversion and biologically defined disease. MethodsWe analyzed Parkinso[n]s Progression Markers Initiative participants who phenoconverted to PD, DLB, multiple system atrophy (MSA), Alzheimers disease (AD) or other dementias from prodromal and non-manifesting genetic carrier (NMC) groups and controls. Site investigators determined phenoconversion based on established diagnostic criteria. All phenoconverters with [&ge;]1 annual follow-up visit, with available biomarkers and persistent clinically defined diagnosis at last observation were included. Neuronal alpha-Synuclein Disease Integrated Staging System (NSD-ISS) staging was applied. ResultsAmong 121 phenoconverters, 103 had evaluable CSFaSynSAA and DAT data and were included in analysis: 92 PD, 7 DLB, 2 MSA, 2 AD/other dementias. Phenoconversion annual rates varied widely across groups: iRBD 7.9%, hyposmia 4.2%, GBA1 0.3%, LRRK2 1.3%, LRRK2+GBA1 0.9%, and controls 0.5%. Median time from baseline to phenoconversion ranged from 13-14 months in iRBD and hyposmia to 36-85 months in NMCs. The expected biomarker profile (CSFaSynSAA+/DAT+) for clinically-diagnosed synucleinopathy occurred in 74 (71.8%) participants. Biological alignment (CSFaSynSAA+/DAT+) was present in 87% hyposmics and 72% iRBD phenoconverters. CSFaSynSAA negativity was high among LRRK2 phenoconverters (67%), who also were more likely to have a preserved sense of smell (83%). Phenoconversion occurred later than onset of functional impairment: 15/47 (31.9%) iRBDs and 7/38 (18.4%) hyposmics were already NSD-ISS stage [&ge;]4 at time of phenoconversion. ConclusionsClinical phenoconversion did not necessarily align with biological evidence of synucleinopathy or dopaminergic loss and can be delayed compared to onset of meaningful functional impairment. Longitudinal follow up on converters without biological evidence of PD is required to confirm conversion diagnosis and evaluate for a later occurrence of biomarker positivity.

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.