Background:Alterations in perivascular fluid dynamics have been implicated in Parkinson's disease (PD) and metabolic disorders such as type 2 diabetes mellitus (T2DM). However, the relative contributions of neurodegenerative and metabolic conditions to functional perivascular water diffusivity versus structural neurofluid markers remain to be elucidated. Objectives:To investigate the differences in perivascular water diffusivity and structural neurofluid markers using diffusion tensor image-analysis along the perivascular space (DTI-ALPS), perivascular space (PVS) burden, and choroid plexus volume (CPV) in PD and T2DM. Methods:Consecutive patients with de novo PD and disease controls were included. Subjects were classified into four groups according to PD and T2DM status and matched for age and sex. The ALPS-index was derived from DTI, whereas PVS burden and CPV were quantified on three-dimensional T1-weighted images and normalized to intracranial volume. Results:A total of 127 subjects were included. The ALPS-index differed significantly among the four groups (P < 0.001), with both PD groups demonstrating significantly lower values than control groups, irrespective of T2DM status. Within the PD cohort, longer disease duration and older age were independently associated with lower ALPS-index values. CPV also differed significantly across groups (P = 0.006) with higher values observed only in controls with T2DM, while PVS burden did not differ significantly. Conclusions:In early-stage PD, impaired perivascular diffusivity was associated primarily with neurodegeneration, and no significant additive effect of T2DM was detected. Conversely, the increase in normalized CPV associated with T2DM was observed only in controls and not in PD, suggesting that metabolic and neurodegenerative conditions may differentially influence neurofluid markers.
Objectives:Understanding normal gait characteristics is fundamental for characterizing disease-specific gait alterations. This study aimed to evaluate age-related differences in gait across various task conditions and identify data-driven gait profiles based on dual-task vulnerability in healthy Korean adults. Methods:A cross-sectional gait assessment was conducted using GAITRite® under four conditions: preferred speed, serial sevens subtraction, cell phone use, and backward walking. Gait parameters were categorized into five domains: pace, variability, rhythm, asymmetry, and postural control. Participants were stratified into younger (<60 years) and older adults (≥60 years). Latent profile analysis (LPA) was performed using the dual-task cost variables to identify data-driven gait profiles. Results:Ninety-eight healthy adults (aged 23-87 years) were analyzed. Age-related differences were most pronounced during cell phone use, which was supported by significant age × task interaction effects across the pace, variability, rhythm, and postural control domains (pfdr < 0.05). LPA identified three profiles: Pace-Preserved (Pa-P), Asymmetry-Dominant (Asym-D), and Postural control-Dominant (Pc-D). Younger adults were evenly distributed across the profiles, whereas older adults were predominantly classified into the Asym-D and Pc-D profiles. The Asym-D profile, characterized by the highest mean age, exhibited numerically lower cognitive scores, particularly in the visuospatial domain. Conclusions:Regardless of chronological age groups and data-driven profiles, dual-task gait interference was most pronounced in the cognitive-motor dual-task condition. Data-driven profiling also identified a subgroup characterized by gait asymmetry, older age, and lower cognitive scores, suggesting a potentially distinct cognitive-motor pattern that warrants longitudinal investigation. These preliminary reference values provide a valuable foundation for the identification of pathological gait patterns in clinical populations.
Objective:To quantify key disease milestones, particularly loss of ambulation and survival, and to describe the VPS13A variant spectrum and clinical heterogeneity in patients with chorea-acanthocytosis (ChA). Methods:We conducted a cross-sectional study of 34 ChA patients from 24 unrelated families. Whole-exome sequencing identified VPS13A variants in all probands. Clinical and paraclinical data were collected through neurological evaluations and electronic medical records. Patients were classified as either surviving (ambulatory or non-ambulatory) or deceased. Results:Twenty-one VPS13A variants were identified, including 12 novel variants. Median current age and disease duration were 38.5 (IQR, 34-43) and 8 (IQR, 4-12.25) years, respectively. Loss of ambulation occurred in 26.5% of patients after a median of 10 years (range, 5-16) from onset. Kaplan-Meier analysis estimated a median time to loss of ambulation of 16.0 years (95% CI, 8.8-23.2), with estimated ambulation probabilities of 87% at 6 years and 38% at 16 years. Seven patients died after a median disease duration of 10 years (range, 3-17). The median survival time was not reached during follow-up; the estimated restricted mean survival time was 16.7 years (95% CI, 14.1-19.3). Compulsions co-occurred with obsessions in all cases and were associated with higher rates of suicidal ideation, while insomnia was more frequent in patients without compulsions. Suicide and sepsis were the leading causes of death. Conclusions:This study defines the natural history of ChA, providing prognostic data on ambulation and survival. The discovery of novel VPS13A variants highlights genetic heterogeneity and supports further investigation into disease mechanisms and therapeutic targets.
Objective Cognitive impairment is a major nonmotor manifestation of Parkinson’s disease (PD), and mood disorders, including depression and anxiety, are being increasingly recognized as potentially modifiable contributors to cognitive decline. However, studies simultaneously evaluating the individual and combined effects of depression and anxiety on specific cognitive domains in PD remain limited.Methods One hundred forty-nine patients with early- to mid-stage PD were stratified by depression (Beck Depression Inventory≥14) and anxiety (Beck Anxiety Inventory≥8) status. Cognitive performance was evaluated using the Seoul Neuropsychological Screening Battery. Group differences were analyzed using analyses of covariance, adjusting for education, Hoehn and Yahr stage, and Movement Disorder Society-sponsored revision of the Unified Parkinson’s Disease Rating Scale motor scores, followed by Bonferroni correction for multiple testing.Results After adjustment for covariates, depression was associated with impaired verbal recognition memory (p=0.009), although this association did not survive Bonferroni correction. Conversely, anxiety-related deficits in immediate visual recall (p= 0.006) and inhibitory executive control (p=0.016) remained robustly significant even after rigorous correction. Patients with comorbid depression and anxiety exhibited the most pervasive cognitive impairment, including statistically significant deficits in both visual memory and frontal executive function (all adjusted p<0.05).Conclusion Depression and anxiety exert distinct yet additive detrimental effects on cognition in patients with early PD. While anxiety and comorbid symptoms show robust associations with visuospatial and executive deficits, the impact of isolated depression appears less statistically stable under conservative thresholds. These findings underscore the importance of early neuropsychiatric screening and targeted intervention, which may be associated with the maintenance of cognitive health in patients with PD.
Objective Pathological α-synuclein aggregation is a key finding in synucleinopathies, including Parkinson’s disease (PD), dementia with Lewy bodies, and multiple system atrophy. The real-time quaking-induced conversion (RT-QuIC) assay using cerebrospinal fluid (CSF) can sensitively detect pathological α-synuclein aggregates and is supported by a strong biological rationale. However, the invasive nature of CSF collection limits its clinical utility. A blood-based RT-QuIC assay is therefore of growing interest; although evidence remains limited, it has shown good performance in distinguishing patients with PD from healthy controls (HCs). In this study we investigated pathological α-synuclein aggregates in the neuron-derived extracellular vesicles (nEVs) isolated from serum samples of patients with synucleinopathies and HCs.Methods Serum samples were collected from patients diagnosed with synucleinopathies and HCs without neurological disorders. Total extracellular vesicles (EVs) were isolated from serum using an ExoQuick kit, after which nEVs were isolated via L1-cell adhesion molecule immunocapture. The identity of the nEVs was confirmed by transmission electron microscopy (TEM), nanoparticle tracking analysis (NTA), and western blotting. Pathological α-synuclein aggregates in EVs were assessed by western blotting, dot blotting, and RT-QuIC assays.Results The concentration and abundance of EVs were comparable between the PD and HC groups. TEM and NTA confirmed EV morphology and size distribution, and western blotting validated the neuronal quality of the nEVs. Compared with those from HCs, nEVs from patients with synucleinopathies showed higher levels of phosphorylated or aggregated α-synuclein. Optimized RT-QuIC conditions using nEV enabled preliminary discrimination of synucleinopathy from HC with nEVs, with distinct kinetic profiles observed between groups.Conclusion Serum-derived nEVs represent a promising, minimally invasive seed source for RT-QuIC assays, offering robust diagnostic performance for the detection of synucleinopathies and potential applicability in broader clinical settings.
Sleep disturbances are highly prevalent and clinically significant nonmotor features of Parkinson's disease (PD). Although in-laboratory polysomnography remains the gold standard method for investigating these disturbances, its limited scalability and ecological validity constrain longitudinal and real-world assessments. Recent advances in digital health technologies have introduced a broad spectrum of portable, wearable, and contactless tools for sleep monitoring. In this scoping review, we systematically map the landscape of digital sleep technologies in PD by using a tiered framework based on technical maturity and clinical validation (Tiers 1-4); moreover, we further classify them by signal modality and sleep symptom domain. Through a systematic review of the literature, we identified 19 studies (Tiers 2-4) that applied digital biomarkers to assess sleep disturbances in PD, including REM sleep behavior disorder, nocturnal immobility, insomnia, circadian rhythm disturbances, excessive daytime sleepiness, and sleep-related respiratory and movement disorders. We additionally contextualize these findings against the rapid expansion of multimodal and AI-driven Tier 3-4 platforms in the general population. Despite this technological progress, a major translational gap persists in PD, which is characterized by limited disease-specific validation, small cohort sizes, and insufficient multimodal benchmarking. Multimodal systems leveraging machine learning offer a promising direction by enabling the more precise characterization of complex and overlapping sleep phenotypes. Emerging contactless systems further expand the potential for continuous, low-burden monitoring, although their clinical validity remains to be established. Future development of digital sleep biomarkers in PD will require prospective validation against established standards and the integration of multimodal data to enable scalable, longitudinal phenotyping and clinical trial applications.
OBJECTIVE:Obstacle crossing during walking poses a major risk of falling among individuals with Parkinson's disease (PD), particularly those with cognitive impairment. Although cognitive decline worsens gait, its specific effects on gait performance and cortical activation during obstacle walking remain unclear. The dynamic interaction between brain activity and gait across different walking phases is especially understudied in PD patients with mild cognitive impairment (PD-MCI) compared with those without cognitive impairment (PD-non-MCI). METHODS:Nineteen PD-non-MCI and fifteen PD-MCI participants performed obstacle walking, and functional near-infrared spectroscopy was used to measure activation in the prefrontal cortex (PFC), supplementary motor area (SMA), and premotor cortex (PMC). Gait parameters (speed, cadence, stride length, and stride time) and obstacle crossing metrics (crossing speed, stride length, stride time, and step width) were analyzed across early (5-20 s) and late (20-40 s) phases. Generalized estimating equations were used to examine group, phase, and interaction effects. Brain-gait associations were assessed using Spearman's correlations. RESULTS:PD-MCI participants exhibited poorer obstacle walking performance than PD-non-MCI participants, but no significant phase-related behavioral change was observed. Both groups showed higher PFC, SMA, and PMC activation during the early phase, reflecting greater neural engagement at task onset. However, SMA and PMC activation decreased more steeply across phases in the PD-MCI group. In PD-MCI patients, obstacle walking performance correlated negatively with early-phase PMC and late-phase PFC activation. CONCLUSION:PD-MCI participants had poorer gait and greater cortical activation, indicating increased neural effort and reduced efficiency. These. RESULTS:highlight altered brain-gait coupling in PD-MCI patients and emphasize the need for interventions that increase neural efficiency during complex walking.
OBJECTIVE:Vestibulo-ocular reflex (VOR) impairment has been reported in Parkinson's disease (PD). However, its clinical implications, particularly with respect to cognition, remain unclear. We investigated canal-specific VOR changes and their associations with cognitive function, motor symptoms, gaits, and dopamine transporter (DAT) uptake in de novo PD patients. METHODS:We prospectively enrolled 127 patients with de novo PD who underwent video head-impulse tests (video-HITs), comprehensive neuropsychological assessments, gait analysis, and 18F-N-(3-fluoropropyl)-2β-carbon ethoxy-3β-(4-iodophenyl) nortropane positron emission tomography. Associations between VOR gains and the clinical characteristics of PD were evaluated using general linear models adjusted for age, sex, and education level. Cognitive analyses were performed after the patients were stratified into PD with normal cognition (PD-NC) and PD with mild cognitive impairment (PD-MCI) groups. Partial correlation analyses were performed to assess the relationships between VOR gains and regional DAT uptake. RESULTS:Decreased VOR gain in at least one canal was observed in 22 patients (17.32%). Horizontal canal (HC) gain was positively associated with the Korean version of Montreal Cognitive Assessment score (p=0.040), and anterior canal (AC) gain was negatively associated with the base of support (p=0.018). The patterns of association between VOR gains and neuropsychological measures differed between the PD-NC and PD-MCI groups. In addition, VOR-cognition relationships were canal-specific: HC gain was positively related to visuospatial function, whereas AC and posterior canal gains were negatively related to language and frontal-executive functions. DAT uptake in the locus coeruleus was positively correlated with HC gain (p=0.020). CONCLUSION:VOR integrity is associated with cognitive and gait function in patients with PD. Video-HITs may serve as potential biomarkers for disease monitoring in PD patients.
