Motor subtype in Parkinson's disease: Different disorders or different stages of disease?

Replication and reliability of Parkinson's disease clinical subtypes

BACKGROUND

We recently identified three distinct Parkinson's disease subtypes: "motor only" (predominant motor deficits with intact cognition and psychiatric function); "psychiatric & motor" (prominent psychiatric symptoms and moderate motor deficits); "cognitive & motor" (cognitive and motor deficits).

OBJECTIVE

We used an independent cohort to replicate and assess reliability of these Parkinson's disease subtypes.

METHODS

We tested our original subtype classification with an independent cohort (N = 100) of Parkinson's disease participants without dementia and the same comprehensive evaluations assessing motor, cognitive, and psychiatric function. Next, we combined the original (N = 162) and replication (N = 100) datasets to test the classification model with the full combined dataset (N = 262). We also generated 10 random split-half samples of the combined dataset to establish the reliability of the subtype classifications. Latent class analyses were applied to the replication, combined, and split-half samples to determine subtype classification.

RESULTS

First, LCA supported the three-class solution - Motor Only, Psychiatric & Motor, and Cognitive & Motor- in the replication sample. Next, using the larger, combined sample, LCA again supported the three subtype groups, with the emergence of a potential fourth group defined by more severe motor deficits. Finally, split-half analyses showed that the three-class model also had the best fit in 13/20 (65%) split-half samples; two-class and four-class solutions provided the best model fit in five (25%) and two (10%) split-half replications, respectively.

CONCLUSIONS

These results support the reproducibility and reliability of the Parkinson's disease behavioral subtypes of motor only, psychiatric & motor, and cognitive & motor groups.

Progression subtypes in Parkinson's disease identified by a data-driven multi cohort analysis

The progression of Parkinson's disease (PD) is heterogeneous across patients, affecting counseling and inflating the number of patients needed to test potential neuroprotective treatments. Moreover, disease subtypes might require different therapies. This work uses a data-driven approach to investigate how observed heterogeneity in PD can be explained by the existence of distinct PD progression subtypes. To derive stable PD progression subtypes in an unbiased manner, we analyzed multimodal longitudinal data from three large PD cohorts and performed extensive cross-cohort validation. A latent time joint mixed-effects model (LTJMM) was used to align patients on a common disease timescale. Progression subtypes were identified by variational deep embedding with recurrence (VaDER). In each cohort, we identified a fast-progressing and a slow-progressing subtype, reflected by different patterns of motor and non-motor symptoms progression, survival rates, treatment response, features extracted from DaTSCAN imaging and digital gait assessments, education, and Alzheimer's disease pathology. Progression subtypes could be predicted with ROC-AUC up to 0.79 for individual patients when a one-year observation period was used for model training. Simulations demonstrated that enriching clinical trials with fast-progressing patients based on these predictions can reduce the required cohort size by 43%. Our results show that heterogeneity in PD can be explained by two distinct subtypes of PD progression that are stable across cohorts. These subtypes align with the brain-first vs. body-first concept, which potentially provides a biological explanation for subtype differences. Our predictive models will enable clinical trials with significantly lower sample sizes by enriching fast-progressing patients.

Neuromelanin-sensitive magnetic resonance imaging: Possibilities and promises as an imaging biomarker for Parkinson's disease

Parkinson's disease (PD) is an age-related progressive neurodegenerative disorder characterized by both motor and non-motor symptoms resulting from the death of dopaminergic neurons in the substantia nigra pars compacta (SNpc) and noradrenergic neurons in the locus coeruleus (LC). The current diagnosis of PD primarily relies on motor symptoms, often leading to diagnoses in advanced stages, where a significant portion of SNpc dopamine neurons has already succumbed. Therefore, the identification of imaging biomarkers for early-stage PD diagnosis and disease progression monitoring is imperative. Recent studies propose that neuromelanin-sensitive magnetic resonance imaging (NM-MRI) holds promise as an imaging biomarker. In this review, we summarize the latest findings concerning NM-MRI characteristics at various stages in patients with PD and those with atypical parkinsonism. In conclusion, alterations in neuromelanin within the LC are associated with non-motor symptoms and prove to be a reliable imaging biomarker in the prodromal phase of PD. Furthermore, NM-MRI demonstrates efficacy in differentiating progressive supranuclear palsy (PSP) from PD and multiple system atrophy with predominant parkinsonism. The spatial patterns of changes in the SNpc can be indicative of PD progression and aid in distinguishing between PSP and synucleinopathies. We recommend that patients with PD and individuals at risk for PD undergo regular NM-MRI examinations. This technology holds the potential for widespread use in PD diagnosis.

A comprehensive multivariate analysis of the center of pressure during quiet standing in patients with Parkinson's disease

BACKGROUND

We hypothesized that postural instability observed in individuals with Parkinson's disease (PD) can be classified as distinct subtypes based on comprehensive analyses of various evaluated parameters obtained from time-series of center of pressure (CoP) data during quiet standing. The aim of this study was to characterize the postural control patterns in PD patients by performing an exploratory factor analysis and subsequent cluster analysis using CoP time-series data during quiet standing.

METHODS

127 PD patients, 47 aged 65 years or older healthy older adults, and 71 healthy young adults participated in this study. Subjects maintain quiet standing for 30 s on a force platform and 23 variables were calculated from the measured CoP time-series data. Exploratory factor analysis and cluster analysis with a Gaussian mixture model using factors were performed on each variable to classify subgroups based on differences in characteristics of postural instability in PD.

RESULTS

The factor analysis identified five factors (magnitude of sway, medio-lateral frequency, anterio-posterior frequency, component of high frequency, and closed-loop control). Based on the five extracted factors, six distinct subtypes were identified, which can be considered as subtypes of distinct manifestations of postural disorders in PD patients. Factor loading scores for the clinical classifications (younger, older, and PD severity) overlapped, but the cluster classification scores were clearly separated.

CONCLUSIONS

The cluster categorization clearly identifies symptom-dependent differences in the characteristics of the CoP, suggesting that the detected clusters can be regarded as subtypes of distinct manifestations of postural disorders in patients with PD.

Plasma extracellular vesicle synaptic proteins as biomarkers of clinical progression in patients with Parkinson's disease

Synaptic dysfunction plays a key role in Parkinson's disease (PD), and plasma extracellular vesicle (EV) synaptic proteins are emerging as biomarkers for neurodegenerative diseases. Assessment of plasma EV synaptic proteins for their efficacy as biomarkers in PD and their relationship with disease progression was conducted. In total, 144 participants were enrolled, including 101 people with PD (PwP) and 43 healthy controls (HCs). The changes in plasma EV synaptic protein levels between baseline and 1-year follow-up did not differ significantly in both PwP and HCs. In PwP, the changes in plasma EV synaptic protein levels were significantly associated with the changes in Unified Parkinson's Disease Rating Scale (UPDRS)-II and III scores. Moreover, PwP with elevated levels (first quartile) of any one plasma EV synaptic proteins (synaptosome-associated protein 25, growth-associated protein 43 or synaptotagmin-1) had significantly greater disease progression in UPDRS-II score and the postural instability and gait disturbance subscore in UPDRS-III than did the other PwP after adjustment for age, sex, and disease duration. The promising potential of plasma EV synaptic proteins as clinical biomarkers of disease progression in PD was suggested. However, a longer follow-up period is warranted to confirm their role as prognostic biomarkers.

Time-resolved quantification of fine hand movements as a proxy for evaluating bradykinesia-induced motor dysfunction

Bradykinesia is a behavioral manifestation that contributes to functional dependencies in later life. However, the current state of bradykinesia indexing primarily relies on subjective, time-averaged categorizations of motor deficits, which often yield poor reliability. Herein, we used time-resolved analyses of accelerometer recordings during standardized movements, data-driven factor analyses, and linear mixed effects models (LMEs) to quantitatively characterize general, task- and therapy-specific indices of motor impairment in people with Parkinson's disease (PwP) currently undergoing treatment for bradykinesia. Our results demonstrate that single-trial, accelerometer-based features of finger-tapping and rotational hand movements were significantly modulated by divergent therapeutic regimens. Further, these features corresponded well to current gold standards for symptom monitoring, with more precise predictive capacities of bradykinesia-specific declines achieved when considering kinematic features from diverse movement types together, rather than in isolation. Herein, we report data-driven, sample-specific kinematic profiles of diverse movement types along a continuous spectrum of motor impairment, which importantly, preserves the temporal scale for which biomechanical fluctuations in motor deficits evolve in humans. Therefore, this approach may prove useful for tracking bradykinesia-induced motor decline in aging populations the future.

Plasma GFAP as a prognostic biomarker of motor subtype in early Parkinson's disease

Parkinson's disease (PD) is a heterogeneous movement disorder with different motor subtypes including tremor dominant (TD), indeterminate and postural instability, and gait disturbance (PIGD) motor subtypes. Plasma glial fibrillary acidic protein (GFAP) was elevated in PD patients and may be regarded as a biomarker for motor and cognitive progression. Here we explore if there was an association between plasma GFAP and different motor subtypes and whether baseline plasma GFAP level can predict motor subtype conversion. Patients with PD classified as TD, PIGD or indeterminate subtypes underwent neurological evaluation at baseline and 2 years follow-up. Plasma GFAP in PD patients and controls were measured using an ultrasensitive single molecule array. The study enrolled 184 PD patients and 95 control subjects. Plasma GFAP levels were significantly higher in the PIGD group compared to the TD group at 2-year follow-up. Finally, 45% of TD patients at baseline had a subtype shift and 85% of PIGD patients at baseline remained as PIGD subtypes at 2 years follow-up. Baseline plasma GFAP levels were significantly higher in TD patients converted to PIGD than non-converters in the baseline TD group. Higher baseline plasma GFAP levels were significantly associated with the TD motor subtype conversion (OR = 1.283, P = 0.033) and lower baseline plasma GFAP levels in PIGD patients were likely to shift to TD and indeterminate subtype (OR = 0.551, P = 0.021) after adjusting for confounders. Plasma GFAP may serve as a clinical utility biomarker in differentiating motor subtypes and predicting baseline motor subtypes conversion in PD patients.

Brain network centrality and connectivity are associated with clinical subtypes and disease progression in Parkinson's disease

To investigate brain network centrality and connectivity alterations in different Parkinson's disease (PD) clinical subtypes using resting-state functional magnetic resonance imaging (RS-fMRI), and to explore the correlation between baseline connectivity changes and the clinical progression. Ninety-two PD patients were enrolled at baseline, alongside 38 age- and sex-matched healthy controls. Of these, 85 PD patients underwent longitudinal assessments with a mean of 2.75 ± 0.59 years. Two-step cluster analysis integrating comprehensive motor and non-motor manifestations was performed to define PD subtypes. Degree centrality (DC) and secondary seed-based functional connectivity (FC) were applied to identify brain network centrality and connectivity changes among groups. Regression analysis was used to explore the correlation between baseline connectivity changes and clinical progression. Cluster analysis identified two main PD subtypes: mild PD and moderate PD. Two different subtypes within the mild PD were further identified: mild motor-predominant PD and mild-diffuse PD. Accordingly, the disrupted DC and seed-based FC in the left inferior frontal orbital gyrus and left superior occipital gyrus were severe in moderate PD. The DC and seed-based FC alterations in the right gyrus rectus and right postcentral gyrus were more severe in mild-diffuse PD than in mild motor-predominant PD. Moreover, disrupted DC were associated with clinical manifestations at baseline in patients with PD and predicted motor aspects progression over time. Our study suggested that brain network centrality and connectivity changes were different among PD subtypes. RS-fMRI holds promise to provide an objective assessment of subtype-related connectivity changes and predict disease progression in PD.

Free water imaging unravels unique patterns of longitudinal structural brain changes in Parkinson's disease subtypes

Background

Research shows that individuals with Parkinson's disease (PD) who have a postural instability and gait difficulties (PIGD) subtype have a faster disease progression compared to those with a tremor dominant (TD) subtype. Nevertheless, our understanding of the structural brain changes contributing to these clinical differences remains limited, primarily because many brain imaging techniques are only capable of detecting changes in the later stages of the disease.

Objective

Free water (FW) has emerged as a robust progression marker in several studies, showing increased values in the posterior substantia nigra that predict symptom worsening. Here, we examined longitudinal FW changes in TD and PIGD across multiple brain regions.

Methods

Participants were TD and PIGD enrolled in the Parkinson's Progression Marker Initiative (PPMI) study who underwent diffusion MRI at baseline and 2 years later. FW changes were quantified for regions of interest (ROI) within the basal ganglia, thalamus, brainstem, and cerebellum.

Results

Baseline FW in all ROIs did not differ between groups. Over 2 years, PIGD had a greater percentage increase in FW in the putamen, globus pallidus, and cerebellar lobule V. A logistic regression model incorporating percent change in motor scores and FW in these brain regions achieved 91.4% accuracy in discriminating TD and PIGD, surpassing models based solely on clinical measures (74.3%) or imaging (76.1%).

Conclusion

The results further suggest the use of FW to study disease progression in PD and provide insight into the differential course of brain changes in early-stage PD subtypes.

Predicting Ambulatory Capacity in Parkinson's Disease to Analyze Progression, Biomarkers, and Trial Design

BACKGROUND

In Parkinson's disease (PD), gait and balance is impaired, relatively resistant to available treatment and associated with falls and disability. Predictive models of ambulatory progression could enhance understanding of gait/balance disturbances and aid in trial design.

OBJECTIVES

To predict trajectories of ambulatory abilities from baseline clinical data in early PD, relate trajectories to clinical milestones, compare biomarkers, and evaluate trajectories for enrichment of clinical trials.

METHODS

Data from two multicenter, longitudinal, observational studies were used for model training (Tracking Parkinson's, n = 1598) and external testing (Parkinson's Progression Markers Initiative, n = 407). Models were trained and validated to predict individuals as having a "Progressive" or "Stable" trajectory based on changes of ambulatory capacity scores from the Movement Disorders Society Unified Parkinson's Disease Rating Scale parts II and III. Survival analyses compared time-to-clinical milestones and trial outcomes between predicted trajectories.

RESULTS

On external evaluation, a support vector machine model predicted Progressive trajectories using baseline clinical data with an accuracy, weighted-F1 (proportionally weighted harmonic mean of precision and sensitivity), and sensitivity/specificity of 0.735, 0.799, and 0.688/0.739, respectively. Over 4 years, the predicted Progressive trajectory was more likely to experience impaired balance, loss of independence, impaired function and cognition. Baseline dopamine transporter imaging and select biomarkers of neurodegeneration were significantly different between predicted trajectory groups. For an 18-month, randomized (1:1) clinical trial, sample size savings up to 30% were possible when enrollment was enriched for the Progressive trajectory versus no enrichment.

CONCLUSIONS

It is possible to predict ambulatory abilities from clinical data that are associated with meaningful outcomes in people with early PD. © 2023 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Resting-state functional magnetic resonance imaging study comparing tremor-dominant and postural instability/gait difficulty subtypes of Parkinson's disease

PURPOSE

The symptom-specific intrinsic neural mechanisms underlying Parkinson's disease (PD) subtypes (tremor dominant [TD] and postural instability gait difficulty [PIGD]) remain unclarified. We examined spontaneous brain activity patterns in TD and PIGD.

MATERIAL AND METHODS

We included 49 patients with PD (21 with TD/28 with PIGD) and 32 healthy controls (HCs) in this study. We conducted analysis of variance and post-hoc analyses of the amplitude of low-frequency fluctuation (ALFF) and regional homogeneity (ReHo) values of the three groups, with age, sex, and gray matter volume as covariates, and a relationship analysis of the ALFF and ReHo values with clinical variables.

RESULTS

In comparison with HCs, PIGD PD patients had increased ALFF values in the right middle occipital gyrus and left superior occipital gyrus and decreased values primarily in the bilateral inferior frontal gyrus (triangular part). TD PD patients had lower ALFF values in the right inferior frontal gyrus (triangular part) and left insula. In comparison to TD PD patients, PIGD PD patients had higher ALFF values in the left middle occipital gyrus and left superior occipital gyrus. In contrast to HCs, TD PD patients demonstrated a reduction of ReHo values in the left middle temporal gyrus, and PIGD patients showed a decrease of ReHo values in the left inferior temporal gyrus.

CONCLUSION

ALFF values increased in the occipital gyrus of the PIGD PD patients, thus providing evidence of a compensatory mechanism of altered motor function in comparison with the TD PD patients.

Unlocking potential: low frequency subthalamic nucleus stimulation enhances executive function in Parkinson's disease patients with postural instability/gait disturbance

Postural instability/gait disturbance (PIGD) is very common in advanced Parkinson's disease, and associated with cognitive dysfunction. Research suggests that low frequency (5-12 Hz) subthalamic nucleus-deep brain stimulation (STN-DBS) could improve cognition in patients with Parkinson's disease (PD). However, the clinical effectiveness of low frequency stimulation in PIGD patients has not been explored. This study was designed in a double-blinded randomized cross-over manner, aimed to verify the effect of low frequency STN-DBS on cognition of PIGD patients. Twenty-nine PIGD patients with STN-DBS were tested for cognitive at off (no stimulation), low frequency (5 Hz), and high frequency (130 Hz) stimulation. Neuropsychological tests included the Stroop Color-Word Test (SCWT), Verbal fluency test, Symbol Digital Switch Test, Digital Span Test, and Benton Judgment of Line Orientation test. For conflict resolution of executive function, low frequency stimulation significantly decreased the completion time of SCWT-C (p = 0.001) and Stroop interference effect (p < 0.001) compared to high frequency stimulation. However, no significant differences among stimulation states were found for other cognitive tests. Here we show, low frequency STN-DBS improved conflict resolution of executive function compared to high frequency. Our results demonstrated the possibility of expanding the treatment coverage of DBS to cognitive function in PIGD, which will facilitate integration of low frequency stimulation into future DBS programming.

Parkinson's disease progression: Increasing expression of an invariant common core subnetwork

Notable success has been achieved in the study of neurodegenerative conditions using reduction techniques such as principal component analysis (PCA) and sparse inverse covariance estimation (SICE) in positron emission tomography (PET) data despite their widely differing approach. In a recent study of SICE applied to metabolic scans from Parkinson's disease (PD) patients, we showed that by using PCA to prespecify disease-related partition layers, we were able to optimize maps of functional metabolic connectivity within the relevant networks. Here, we show the potential of SICE, enhanced by disease-specific subnetwork partitions, to identify key regional hubs and their connections, and track their associations in PD patients with increasing disease duration. This approach enabled the identification of a core zone that included elements of the striatum, pons, cerebellar vermis, and parietal cortex and provided a deeper understanding of progressive changes in their connectivity. This subnetwork constituted a robust invariant disease feature that was unrelated to phenotype. Mean expression levels for this subnetwork increased steadily in a group of 70 PD patients spanning a range of symptom durations between 1 and 21 years. The findings were confirmed in a validation sample of 69 patients with up to 32 years of symptoms. The common core elements represent possible targets for disease modification, while their connections to external regions may be better suited for symptomatic treatment.

DBS-evoked cortical responses index optimal contact orientations and motor outcomes in Parkinson's disease

Although subthalamic deep brain stimulation (DBS) is a highly-effective treatment for alleviating motor dysfunction in patients with Parkinson's disease (PD), clinicians currently lack reliable neurophysiological correlates of clinical outcomes for optimizing DBS parameter settings, which may contribute to treatment inefficacies. One parameter that could aid DBS efficacy is the orientation of current administered, albeit the precise mechanisms underlying optimal contact orientations and associated clinical benefits are not well understood. Herein, 24 PD patients received monopolar stimulation of the left STN during magnetoencephalography and standardized movement protocols to interrogate the directional specificity of STN-DBS current administration on accelerometer metrics of fine hand movements. Our findings demonstrate that optimal contact orientations elicit larger DBS-evoked cortical responses in the ipsilateral sensorimotor cortex, and importantly, are differentially predictive of smoother movement profiles in a contact-dependent manner. Moreover, we summarize traditional evaluations of clinical efficacy (e.g., therapeutic windows, side effects) for a comprehensive review of optimal/non-optimal STN-DBS contact settings. Together, these data suggest that DBS-evoked cortical responses and quantitative movement outcomes may provide clinical insight for characterizing the optimal DBS parameters necessary for alleviating motor symptoms in patients with PD in the future.

Cytokine profiles of plasma extracellular vesicles as progression biomarkers in Parkinson's disease

BACKGROUND

Inflammation contributes substantially to the pathogenesis of Parkinson's disease (PD). Plasma extracellular vesicle (EV)-derived cytokines are emerging biomarkers of inflammation. We conducted a longitudinal study of the plasma EV-derived cytokine profiles of people with PD (PwP).

METHODS

A total of 101 people with mild to moderate PD and 45 healthy controls (HCs) were recruited, and they completed motor assessments (Unified Parkinson Disease Rating Scale [UPDRS]) and cognitive tests at baseline and 1-year follow-up. We isolated the participants' plasma EVs and analyzed their levels of cytokines, including interleukin (IL)-1β, IL-6, IL-10, tumor necrosis factor (TNF)-α, and transforming growth factor (TGF)-β.

RESULTS

We noted no significant changes in the plasma EV-derived cytokine profiles of the PwPs and HCs between baseline and the 1-year follow-up. Among the PwP, changes in plasma EV-derived IL-1β, TNF-α and IL-6 levels were significantly associated with changes in the severity of postural instability and gait disturbance (PIGD) and cognition. Baseline plasma EV-derived IL-1β, TNF-α, IL-6, and IL-10 levels were significantly associated with the severity of PIGD and cognitive symptoms at follow-up, and PwP with elevated IL-1β and IL-6 levels exhibited significant progression of PIGD over the study period.

CONCLUSION

These results suggested the role of inflammation in PD progression. In addition, baseline levels of plasma EV-derived proinflammatory cytokines can be used to predict the progression of PIGD, the most severe motor symptom of PD. Additional studies with longer follow-up periods are necessary, and plasma EV-derived cytokines may serve as effective biomarkers of PD progression.

Abnormal cerebellum connectivity patterns related to motor subtypes of Parkinson's disease

Cerebellar dysfunction may substantially contribute to the clinical symptoms of Parkinson's disease (PD). The role of cerebellar subregions in tremors and gait disturbances in PD remains unknown. To investigate alterations in cerebellar subregion volumes and functional connectivity (FC), as well as FC between the dentate nucleus (DN) and ventral lateral posterior nucleus (VLp) of the thalamus, which are potentially involved in different PD motor subtypes. We conducted morphometric and resting-state functional connectivity analyses in various cerebellar subregions in 22 tremor-dominant (TD)-PD and 35 postural instability gait difficulty dominant (PIGD)-PD patients and 38 sex- and age-matched healthy controls (HCs). The volume and FC alterations in various cerebellar subregions and the neural correlates of these changes with the clinical severity scores were investigated. The PIGD-PD group showed greater FC between the right motor cerebellum (CBMm) and left postcentral gyrus than the HC group, and a higher FC was associated with less severe PIGD symptoms. In contrast, the TD-PD group had decreased FC between the right DN and left VLp compared with the PIGD-PD and HC groups, and lower FC was associated with worse TD symptoms. Furthermore, the PIGD-PD group had higher FC between the left DN and left inferior temporal gyrus than the TD-PD group. Morphometric analysis revealed that the TD-PD group showed a significantly higher volume of left CBMm than the HC group. Our findings point to differential alteration patterns in cerebellar subregions and offer a new perspective on the pathophysiology of motor subtypes of PD.

The definition of precision medicine in neurodegenerative disorders and the one disease-many diseases tension

Precision medicine is a patient-centered approach that aims to translate new knowledge to optimize the type and timing of interventions for the greatest benefit to individual patients. There is considerable interest in applying this approach to treatments designed to slow or halt the progression of neurodegenerative diseases. Indeed, effective disease-modifying treatment (DMT) remains the greatest unmet therapeutic need in this field. In contrast to the enormous progress in oncology, precision medicine in the field of neurodegeneration faces multiple challenges. These are related to major limitations in our understanding of many aspects of the diseases. A critical barrier to advances in this field is the question of whether the common sporadic neurodegenerative diseases (of the elderly) are single uniform disorders (particularly related to their pathogenesis) or whether they represent a collection of related but still very distinct disease states. In this chapter, we briefly touch on lessons from other fields of medicine that might be applied to the development of precision medicine for DMT in neurodegenerative diseases. We discuss why DMT trials may have failed to date, and particularly the importance of appreciating the multifaceted nature of disease heterogeneity and how this has and will impact on these efforts. We conclude with comments on how we can move from this complex disease heterogeneity to the successful application of precision medicine principles in DMT for neurodegenerative diseases.

Plasma extracellular vesicle tau, β-amyloid, and α-synuclein and the progression of Parkinson's disease: a follow-up study

Background

Plasma extracellular vesicle (EV) contents are promising biomarkers of Parkinson's disease (PD). The pathognomonic proteins of PD, including α-synuclein, tau, and β-amyloid, are altered in people with PD (PwP) and are associated with clinical presentation in previous cross-sectional studies. However, the dynamic changes in these plasma EV proteins in PwP and their correlation with clinical progression remain unclear.

Objective

We investigated the dynamic changes in plasma EV α-synuclein, tau, and β-amyloid and their correlation with/prediction of clinical progression in PwP.

Design

A cohort study.

Methods

In total, 103 PwP and 37 healthy controls (HCs) completed baseline assessment and 1-year follow-up. Clinical assessments included Unified Parkinson's Disease Rating Scale (UPDRS) parts II and III, Mini-Mental State Examination (MMSE), and Montreal Cognitive Assessment (MoCA). Plasma EVs were isolated, and immunomagnetic reduction-based immunoassay was used to assess α-synuclein, tau, and β-amyloid 1-42 (Aβ1-42) levels within the EVs.

Results

Compared with HCs, significant differences were noted in the annual changes in all three EV pathognomonic proteins in PwP. Although the absolute changes in plasma EV pathognomonic proteins did not significantly correlate with clinical changes, PwP with elevated baseline plasma EV tau (upper-half) levels demonstrated significantly greater decline in motor and cognition, and increased plasma EV α-synuclein levels were associated with postural instability and the gait disturbance motor subtype. For PwP with elevated levels of all three biomarkers, clinical deterioration was significant, as indicated by UPDRS-II scores, postural instability and gait disturbance subscores of UPDRS-III, and MMSE score.

Conclusion

The combination of plasma EV α-synuclein, tau, and Aβ1-42 may identify PwP with a high risk of deterioration. Our findings can elucidate the interaction between these pathognomonic proteins, and they may serve as treatment response markers and can be applied in treatment approaches for disease modification.

The severity of corneal nerve loss differentiates motor subtypes in patients with Parkinson's disease

Background

Parkinson's disease (PD) is a heterogeneous movement disorder with patients manifesting with either tremor-dominant (TD) or postural instability and gait disturbance (PIGD) motor subtypes. Small nerve fiber damage occurs in patients with PD and may predict motor progression, but it is not known whether it differs between patients with different motor subtypes.

Objective

The aim of this study was to explore whether there was an association between the extent of corneal nerve loss and different motor subtypes.

Methods

Patients with PD classified as TD, PIGD, or mixed subtype underwent detailed clinical and neurological evaluation and corneal confocal microscopy (CCM). Corneal nerve fiber density (CNFD), corneal nerve branch density (CNBD), and corneal nerve fiber length (CNFL) were compared between groups, and the association between corneal nerve fiber loss and motor subtypes was investigated.

Results

Of the 73 patients studied, 29 (40%) had TD, 34 (46%) had PIGD, and 10 (14%) had a mixed subtype. CNFD (no./mm², 24.09 ± 4.58 versus 28.66 ± 4.27; p < 0.001), CNBD (no./mm², 28.22 ± 11.11 versus 37.37 ± 12.76; p = 0.015), and CNFL (mm/mm², 13.11 ± 2.79 versus 16.17 ± 2.37; p < 0.001) were significantly lower in the PIGD group compared with the TD group. Multivariate logistic regression showed that higher CNFD (OR = 1.265, p = 0.019) and CNFL (OR = 1.7060, p = 0.003) were significantly associated with the TD motor subtype. The receiver operating characteristic (ROC) analysis demonstrated that combined corneal nerve metrics showed excellent discrimination between TD and PIGD, with an area under the curve (AUC) of 0.832.

Conclusion

Greater corneal nerve loss occurs in patients with PIGD compared with TD, and patients with a higher CNFD or CNFL were more likely to have the TD subtype. CCM may have clinical utility in differentiating different motor subtypes in PD.

Mild cognitive impairment is associated with poor gait performance in patients with Parkinson’s disease

Cognitive impairment may be commonly accompanied by gait disturbance in patients with Parkinson’s disease (PD). However, it is still controversial whether gait disturbance is associated with mild cognitive impairment (MCI) and which cognitive function has a more important effect on specific gait parameter. Our objective was to investigate the association of gait parameters with MCI and the correlation between performance on comprehensive neuropsychological tests and gait parameters in PD patients. We enrolled 257 patients with de novo PD (111 PD-normal cognition and 146 PD-MCI). All patients underwent comprehensive neuropsychological tests and gait evaluation using the GAITRite system. We used logistic regression analysis and partial correlation to identify the association between gait parameters and MCI and correlations between neuropsychological performance and gait parameters. Gait velocity (odds ratio [OR] = 0.98, 95% confidence interval [CI] = 0.97−0.99) and stride length (OR = 0.98; 95% CI = 0.97−0.99) were associated with MCI in patients with PD. Specifically, gait velocity, stride length, and double support ratio were only associated with attention and frontal-executive function performance in patients with PD. Our findings provide insight into the relationship between gait disturbance and MCI in patients with PD. Furthermore, the evaluation of gait disturbance is necessary for PD patients with cognitive impairment.

Cerebro-cerebellar motor networks in clinical subtypes of Parkinson’s disease

Parkinson’s disease (PD) patients can be classified in tremor-dominant (TD) and postural-instability-and-gait-disorder (PIGD) motor subtypes. PIGD represents a more aggressive form of the disease that TD patients have a potentiality of converting into. This study investigated functional alterations within the cerebro-cerebellar system in PD-TD and PD-PIGD patients using stepwise functional connectivity (SFC) analysis and identified neuroimaging features that predict TD to PIGD conversion. Thirty-two PD-TD, 26 PD-PIGD patients and 60 healthy controls performed clinical/cognitive evaluations and resting-state functional MRI (fMRI). Four-year clinical follow-up data were available for 28 PD-TD patients, who were classified in 10 converters (cTD-PD) and 18 non-converters (ncTD-PD) to PIGD. The cerebellar seed-region was identified using a fMRI motor task. SFC analysis, characterizing regions that connect brain areas to the cerebellar seed at different levels of link-step distances, evaluated similar and divergent alterations in PD-TD and PD-PIGD. The discriminatory power of clinical data and/or SFC in distinguishing cPD-TD from ncPD-TD patients was assessed using ROC curve analysis. Compared to PD-TD, PD-PIGD patients showed decreased SFC in temporal lobe and occipital lobes and increased SFC in cerebellar cortex and ponto-medullary junction. Considering the subtype-conversion analysis, cPD-TD patients were characterized by increased SFC in temporal and occipital lobes and in cerebellum and ponto-medullary junction relative to ncPD-TD group. Combining clinical and SFC data, ROC curves provided the highest classification power to identify conversion to PIGD. These findings provide novel insights into the pathophysiology underlying different PD motor phenotypes and a potential tool for early characterization of PD-TD patients at risk of conversion to PIGD.

Olfactory dysfunction and striatal dopamine transporter binding in motor subtypes of Parkinson's disease

BACKGROUND

Olfactory dysfunction is one of the earliest non-motor symptoms (NMS) in Parkinson's disease (PD). There are contradictory results regarding the association of olfactory dysfunction and dopamine uptake in striatal nuclei among PD patients. It has been suggested that different motor subtypes of PD vary in the disease pathophysiology and progression. Thus, we hypothesized that there might be different associations between olfactory dysfunction and striatal dopaminergic neuronal loss among three motor subtypes of PD, namely, indeterminate, postural instability and gait difficulty (PIGD), and tremor-dominant (TD).

METHODS

We recruited 162 healthy controls (HCs) and 464 drug-naïve PD patients from PPMI who underwent common PD scaling tests. Striatal binding ratios (SBRs) of DaTSCAN images in caudate and putamen nuclei were calculated. To assess the olfactory function, the University of Pennsylvania Smell Identification Test (UPSIT) was carried out.

RESULTS

The UPSIT score was significantly correlated with MDS-UPDRS part I (p value: 0.002, correlation coefficient: - 0.160), MDS-UPDRS part III (p value: 0.000, correlation coefficient: - 0.248), and SBR score in right (p value: 0.000, correlation coefficient: 0.240) and left caudate (p value: 0.000, correlation coefficient: 0.221) and right (p value: 0.000, correlation coefficient: 0.323) and left putamen (p value: 0.000, correlation coefficient: 0.335) nucleus in TD subtype. There were no significant correlations in HC, PIGD, and indeterminate subjects.

CONCLUSION

The olfactory dysfunction was correlated with dopamine transporter activity in striatal nuclei only in the TD subtype. Therefore, the olfactory dysfunction in PIGD and indeterminate subtype may not be a predictive factor for the future decrease in dopamine uptake.

Early Parkinson's Disease Phenotypes Tailored by Personality, Behavior, and Motor Symptoms

BACKGROUND

Previous studies described a parkinsonian personality characterized as rigid, introverted, and cautious; however, little is known about personality traits in de novo Parkinson's disease (PD) patients and their relationships with motor and neuropsychiatric symptoms.

OBJECTIVE

To investigate personality in de novo PD and explore its relationship with PD symptoms.

METHODS

Using Cloninger's biosocial model, we assessed personality in 193 de novo PD patients. Motor and non-motor symptoms were measured using several validated scales. Cluster analysis was conducted to investigate the interrelationship of personality traits, motor, and non-motor symptoms.

RESULTS

PD patients showed low novelty seeking, high harm avoidance, and normal reward dependence and persistence scores. Harm avoidance was positively correlated with the severity of depression, anxiety, and apathy (rs = [0.435, 0.676], p < 0.001) and negatively correlated with quality of life (rs = -0.492, p < 0.001). Novelty seeking, reward dependence, and persistence were negatively correlated with apathy (rs = [-0.274, -0.375], p < 0.001). Classification of patients according to personality and PD symptoms revealed 3 distinct clusters: i) neuropsychiatric phenotype (with high harm avoidance and low novelty seeking, hypodopaminergic neuropsychiatric symptoms and higher impulsivity), ii) motor phenotype (with low novelty seeking and higher motor severity), iii) benign phenotype (with low harm avoidance and high novelty seeking, reward dependence, and persistence traits clustered with lower symptoms severity and low impulsivity).

CONCLUSION

Personality in early PD patients allows us to recognize 3 patients' phenotypes. Identification of such subgroups may help to better understand their natural history. Their longitudinal follow-up will allow confirming whether some personality features might influence disease evolution and treatment.

Depression in Patients with Parkinson's Disease: Current Understanding of its Neurobiology and Implications for Treatment

Depression is one of the most frequent and burdensome non-motor symptoms in Parkinson’s disease (PD), across all stages. Even when its severity is mild, PD depression has a great impact on quality of life for these patients and their caregivers. Accordingly, accurate diagnosis, supported by validated scales, identification of risk factors, and recognition of motor and non-motor symptoms comorbid to depression are critical to understanding the neurobiology of depression, which in turn determines the effectiveness of dopaminergic drugs, antidepressants and non-pharmacological interventions. Recent advances using in vivo functional and structural imaging demonstrate that PD depression is underpinned by dysfunction of limbic networks and monoaminergic systems, depending on the stage of PD and its associated symptoms, including apathy, anxiety, rapid eye movement sleep behavior disorder (RBD), cognitive impairment and dementia. In particular, the evolution of serotonergic, noradrenergic, and dopaminergic dysfunction and abnormalities of limbic circuits across time, involving the anterior cingulate and orbitofrontal cortices, amygdala, thalamus and ventral striatum, help to delineate the variable expression of depression in patients with prodromal, early and advanced PD. Evidence is accumulating to support the use of dual serotonin and noradrenaline reuptake inhibitors (desipramine, nortriptyline, venlafaxine) in patients with PD and moderate to severe depression, while selective serotonin reuptake inhibitors, repetitive transcranial magnetic stimulation and cognitive behavioral therapy may also be considered. In all patients, recent findings advocate that optimization of dopamine replacement therapy and evaluation of deep brain stimulation of the subthalamic nucleus to improve motor symptoms represents an important first step, in addition to physical activity. Overall, this review indicates that increasing understanding of neurobiological changes help to implement a roadmap of tailored interventions for patients with PD and depression, depending on the stage and comorbid symptoms underlying PD subtypes and their prognosis.

Immersive Technology for Cognitive-Motor Training in Parkinson’s Disease

Background: Parkinson’s disease (PD) is a neurodegenerative disease in which the progressive loss of dopaminergic neurons (DA) leads to initially sporadic and eventually widespread damage of the nervous system resulting in significant musculoskeletal and cognitive deterioration. Loss of motor function alongside increasing cognitive impairment is part of the natural disease progression. Gait is often considered an automatic activity; however, walking is the result of a delicate balance of multiple systems which maintain the body’s center of mass over an ever-changing base of support. It is a complex motor behavior that requires components of attention and memory to prevent falls and injury. In addition, evidence points to the critical role of salient visual information to gait adaptability. There is a growing understanding that treatment for PD needs to address movement as it occurs naturally and walking needs to be practiced in more complex environments than traditional therapy has provided.

The emerging postural instability phenotype in idiopathic Parkinson disease

Identification of individuals at high risk for rapid progression of motor and cognitive signs in Parkinson disease (PD) is clinically significant. Postural instability and gait dysfunction (PIGD) are associated with greater motor and cognitive deterioration. We examined the relationship between baseline clinical factors and the development of postural instability using 5-year longitudinal de-novo idiopathic data (n = 301) from the Parkinson’s Progressive Markers Initiative (PPMI). Logistic regression analysis revealed baseline features associated with future postural instability, and we designated this cohort the emerging postural instability (ePI) phenotype. We evaluated the resulting ePI phenotype rating scale validity in two held-out populations which showed a significantly higher risk of postural instability. Emerging PI phenotype was identified before onset of postural instability in 289 of 301 paired comparisons, with a median progression time of 972 days. Baseline cognitive performance was similar but declined more rapidly in ePI phenotype. We provide an ePI phenotype rating scale (ePIRS) for evaluation of individual risk at baseline for progression to postural instability.

Cognitive control in Parkinson's disease

Cognitive control is the ability to act according to plan. Problems with cognitive control are a primary symptom and a major decrement of quality of life in Parkinson's disease (PD). Individuals with PD have problems with seemingly different controlled processes (e.g., task switching, impulsivity, gait disturbance, apathetic motivation). We review how these varied processes all rely upon disease-related alteration of common neural substrates, particularly due to dopaminergic imbalance. A comprehensive understanding of the neural systems underlying cognitive control will hopefully lead to more concise and reliable explanations of distributed deficits. However, high levels of clinical heterogeneity and medication-invariant control deficiencies suggest the need for increasingly detailed elaboration of the neural systems underlying control in PD.

Parkinson's Disease Subtyping Using Clinical Features and Biomarkers: Literature Review and Preliminary Study of Subtype Clustering

The second most common progressive neurodegenerative disorder, Parkinson’s disease (PD), is characterized by a broad spectrum of symptoms that are associated with its progression. Several studies have attempted to classify PD according to its clinical manifestations and establish objective biomarkers for early diagnosis and for predicting the prognosis of the disease. Recent comprehensive research on the classification of PD using clinical phenotypes has included factors such as dominance, severity, and prognosis of motor and non-motor symptoms and biomarkers. Additionally, neuroimaging studies have attempted to reveal the pathological substrate for motor symptoms. Genetic and transcriptomic studies have contributed to our understanding of the underlying molecular pathogenic mechanisms and provided a basis for classifying PD. Moreover, an understanding of the heterogeneity of clinical manifestations in PD is required for a personalized medicine approach. Herein, we discuss the possible subtypes of PD based on clinical features, neuroimaging, and biomarkers for developing personalized medicine for PD. In addition, we conduct a preliminary clustering using gait features for subtyping PD. We believe that subtyping may facilitate the development of therapeutic strategies for PD.

Long-Term Cognitive Decline Related to the Motor Phenotype in Parkinson's Disease

BACKGROUND

Parkinson's disease (PD) is associated with various non-motor symptoms, including cognitive deterioration.

OBJECTIVE

Here, we used data from the DEMPARK/LANDSCAPE cohort to describe the association between progression of cognitive profiles and the PD motor phenotypes: postural instability and gait disorder (PIGD), tremor-dominant (TR-D), and not-determined (ND).

METHODS

Demographic, clinical, and neuropsychological six-year longitudinal data of 711 PD-patients were included (age: M = 67.57; 67.4% males). We computed z-transformed composite scores for a priori defined cognitive domains. Analyses were controlled for age, gender, education, and disease duration. To minimize missing data and drop-outs, three-year follow-up data of 442 PD-patients was assessed with regard to the specific role of motor phenotype on cognitive decline using linear mixed modelling (age: M = 66.10; 68.6% males).

RESULTS

Our study showed that in the course of the disease motor symptoms increased while MMSE and PANDA remained stable in all subgroups. After three-year follow-up, significant decline of overall cognitive performance for PIGD-patients were present and we found differences for motor phenotypes in attention (β= -0.08, SE = 0.003, p < 0.006) and memory functions showing that PIGD-patients deteriorate per months by -0.006 compared to the ND-group (SE = 0.003, p = 0.046). Furthermore, PIGD-patients experienced more often difficulties in daily living.

CONCLUSION

Over a period of three years, we identified distinct neuropsychological progression patterns with respect to different PD motor phenotypes, with early executive deficits yielding to a more amnestic profile in the later course. Here, in particular PIGD-patients worsened over time compared to TR-D and ND-patients, highlighting the greater risk of dementia for this motor phenotype.

Efficacy of C-Mill gait training for improving walking adaptability in early and middle stages of Parkinson's disease

BACKGROUND

Walking adaptability is an obvious manifestation of Parkinson's disease (PD). Augmented reality technologies such as interactive walkways may improve walking adaptability in patients with Parkinson's Disease (PWP).

RESEARCH QUESTION

How effective is C-Mill gait adaptability training in the early and middle stages of PD for improving walking adaptability in motor subtypes of the disease?

METHODS

Fifty-two patients with early- or middle-stage PD were divided into two groups according to motor subtype (postural instability/gait disorder [PIGD] and non-PIGD) and received 7 days of training (0.5 h every day, 2 h after medication) on an augmented reality treadmill with built-in visual targets and obstacles. Functional assessments were performed before and after intervention, including posture control and walking, C-gait assessment, and participant experience. The Parkinson Disease Quality of Life questionnaire was administered at 3-month follow-up.

RESULTS

Both the PIGD (n = 29) and non-PIGD (n = 23) groups showed improved tandem walking, obstacle avoidance, and overall score in C-gait assessment and Timed Up and Go test after C-Mill training. However, there were no differences between the two groups. The PIGD group showed improvement in visually guided stepping and Speed adaptations, whereas the non-PIGD group did not improve. The non-PIGD group reported they could complete the training with less exertion after the intervention and at the 3-month follow-up, these patients reported improvement in quality of life.

SIGNIFICANCE

C-Mill gait adaptation training in the early and middle stages of PD improves walking adaptability in both motor subtypes. Cue strategies are the probable mechanism and may decrease fall risk after training. There was no difference between the groups in the improvements of perceived exertion and quality of life at follow-up. Although PIGD patients showed statistic improvements in visually guided stepping compared with non-PIGD patients, but the difference was not likely to be clinically meaningful. Specific effects of C-mill training for different types of PD were not observed in our study.

Parkinson's Disease Motor Subtypes Change with the Progression of the Disease: Results from the COPPADIS Cohort at 2-Year Follow-Up

BACKGROUND

Motor phenotype (MP) can be associated with a different prognosis in Parkinson's disease (PD), but it is not fixed and can change over time.

OBJECTIVE

Our aim was to analyze how the MP changed over time and to identify factors associated with the changes in PD patients from a multicenter Spanish PD cohort.

METHODS

PD patients who were recruited from January-2016 to November-2017 (baseline visit; V0) and evaluated again at a 2-year±30 days follow-up (V2) from 35 centers of Spain from the COPPADIS cohort, were included in this study.MP was calculated at both visits based on Jankovic classification in TD (tremor dominant), IND (indeterminate), or PIGD (postural instability and gait difficulty). Sociodemographic and clinical data were collected, including serum biomarkers.

RESULTS

Five hundred eleven patients (62.57±8.59 years old; 59.2%males) were included in the study. At V0, MP was: 47.4%(242/511) TD; 36.6%(187/511) PIGD; 16%(82/511) IND. Up to 38%(194/511) of the patients changed their phenotype from V0 to V2, being the most frequent from TD to IND (8.4%) and from TD to PIGD (6.7%). A worse cognitive status (OR = 0.966) and less autonomy for activities of daily living (OR  =  0.937) at V0 and a greater increase in the globalNMS burden (OR  =  1.011) from V0 to V2 were associated with changing from TD to another phenotype after 2-year follow-up.

CONCLUSION

The MP in PD can change over time. With disease progression, the percentage of cases with non-tremoric MP increases. PD patients who changed from TD to postural instability and gait difficulty increased NMS burden significantly.

Profiling the most elderly parkinson's disease patients: Does age or disease duration matter?

BACKGROUND

Despite our ageing populations, elderly patients are underrepresented in clinical research, and ageing research is often separate from that of Parkinson's disease (PD). To our knowledge, no previous study has focused on the most elderly ('old-old', age ≥ 85 years) patients with PD to reveal how age directly influences PD clinical progression.

OBJECTIVE

We compared the clinical characteristics and pharmacological profiles, including complications of levodopa treatment, disease progression, disabilities, and comorbidities of the old-old with those of comparable younger ('young-old', age 60-75 years) PD patients. In addition, within the old-old group, we compared those with a short disease duration (< 10 years at the time of diagnosis) to those with a long disease duration ≥10 years to investigate whether prognosis was related to disease progression or aging.

METHODS

This single-centre, case-control study compared 60 old-old to 92 young-old PD patients, matched for disease duration. Patients in the old-old group were also divided equally (30:30) into two subgroups (short and long disease duration) with the same mean age. We compared the groups based on several clinical measures using a conditional logistic regression.

RESULTS

By study design, there were no differences between age groups when comparing disease duration, however, the proportion of men decreased with age (p = 0.002). At a comparable length of PD duration of 10 years, the old-old PD patients predominantly had significantly greater postural instability and gait disturbance (p = 0.006), higher motor scope of the Unified Parkinson's Disease Rating Scale (UPDRS-III, p<0.0001), and more advanced Hoehn & Yahr (H&Y) stage (p<0.0001). The Non-Motor Symptoms Questionnaire (NMSQuest) score was also significantly higher among the old-old (p<0.0001) compared to the young-old patients. Moreover, the distribution of NMS also differed between ages, with features of gastrointestinal problems (p<0.0001), urinary problems (p = 0.004), sleep disturbances and fatigue (p = 0.032), and cognitive impairment (p<0.0001) significantly more common in the old-old group, whereas sexual problems (p = 0.012), depression, and anxiety (p = 0.032) were more common in the young-old. No differences were found in visual hallucinations, cerebrovascular disease, and miscellaneous domains. While young-old PD patients received higher levodopa equivalent daily doses (p<0.0001) and developed a significant greater rate of dyskinesia (p = 0.002), no significant difference was observed in the rate of wearing-off (p = 0.378). Old-old patients also had greater disability, as measured by the Schwab and England scale (p<0.0001) and had greater milestone frequency specifically for dementia (p<0.0001), wheelchair placement (p<0.0001), nursing home placement (p = 0.019), and hospitalisation in the past 1 year (p = 0.05). Neither recurrent falls (p = 0.443) nor visual hallucinations (p = 0.607) were documented significantly more often in the old-old patients.

CONCLUSIONS

Age and disease duration were independently associated with clinical presentation, course, and progression of PD. Age was the main predictor, but disease duration also had a strong effect, suggesting that factors of the ageing process beyond the disease process itself cause PD in the most elderly to be more severe.

Wilful pathogens provoke a gut feeling in Parkinson’s disease

Parkinson’s disease is the second most common neurological disorder marked by characteristic poverty and dysfunction in movement. There are many mechanisms and factors which have been postulated to be associated with the neurodegenerative pathway(s) resulting in distinctive loss of neurons in the substantia nigra. Subsequently, the neuropathology is more widespread and exhibited in other areas of the brain, and enteric nervous system. Aggregates of misfolded α-synuclein or Lewy bodies are the hallmark of the illness and appear to be central in the whole cascade of cell destruction. There are many processes implicated in neuronal destruction including: oxidative stress, excitotoxicity, mitochondrial dysfunction, an imbalance in protein homeostasis and neuroinflammation. Interesting, inflammation induced by pathogens (including, bacteria and viruses) has been associated in the pathogenesis of the disease. Bacteria such as Helicobacter pylori and Helicobacter suis appear to colonise the gut, and elicit systemic immune responses, which is them transmitted via the gut-axis to the brain, where cytotoxic cytokines induce neuroinflammation and cell death. This conforms to the bottom–top hypothesis proposed by Braak. The gut is also implicated in two other theories postulated in the development and progression of the disorder, namely, the top–down and the threshold. There is a possibility that these theories may be inter-linked and operate together to certain degree. Ultimately specific trigger factors or conditions may govern the occurrences of these processes in genetically predisposed individuals. Nevertheless, the importance of pathogen-related gut infections cannot be overlooked, since it can result in dysbiosis of gut microbes, which may orchestrate α-synuclein pathology and eventually cell destruction.

Serum Neurofilament Light Chain as a Marker of Progression in Parkinson's Disease: Long-Term Observation and Implications of Clinical Subtypes

BACKGROUND

Biochemical and clinical biomarkers correlate with progression rate and disease severity in Parkinson's disease (PD) but are not sufficiently studied in late PD.

OBJECTIVE

To examine how serum neurofilament light chain (S-NfL) alone or combined with clinical classifications predicts PD outcome in later disease stages.

METHODS

Eighty-five patients with 7.9±5.1 years of PD duration were included in an observational cohort. Clinical scores were obtained at two separate examinations 8.2±2.0 years apart. S-NfL levels were determined with single molecule array (SiMoA). Five predefined disease progression milestones were assessed. After affirming combination potential of S-NfL and either of two clinical classifications, three combined models were constructed based on these factors and age at onset in different combinations.

RESULTS

S-NfL levels showed significant hazard ratios for four out of five disease progression milestones: walking-aid usage (HR 3.5; 95% CI 1.4-8.5), nursing home living (5.1; 2.1-12.5), motor end-stage (6.2; 2.1-17.8), and death (4.1; 1.7-9.7). Higher S-NfL levels were associated with lower ability in activities of daily living and poorer cognition at baseline and/or at follow-up. Combined models showed significantly improved area under receiver operating characteristic curves (0.77-0.91) compared to S-NfL levels alone (0.68-0.71) for predicting the five disease milestones.

CONCLUSION

S-NfL levels stratified patients according to their likelihood to reach clinically relevant progression milestones during this long-term observational study. S-NfL alone reflected motor and social outcomes in later stages of PD. Combining S-NfL with clinical factors was possible and exploratory combined models improved prognostic accuracy.

Stability of MDS-UPDRS Motor Subtypes Over Three Years in Early Parkinson's Disease

Background: Various classifications have been proposed to subtype Parkinson's disease (PD) based on their motor phenotypes. However, the stability of these subtypes has not been properly evaluated.

Objective: The goal of this study was to understand the distribution of PD motor subtypes, their stability over time, and baseline factors that predicted subtype stability.

Methods: Participants (n = 170) from two prospective cohorts were included: the Early PD Longitudinal Singapore (PALS) study and the National Neuroscience Institute Movement Disorders Database. Early PD patients were classified into tremor-dominant (TD), postural instability and gait difficulty (PIGD), and indeterminate subtypes according to the Movement Disorder Society's Unified PD Rating Scale (MDS-UPDRS) criteria and clinically evaluated for three consecutive years.

Results: At baseline, 60.6% patients were TD, 12.4% patients were indeterminate, and 27.1% patients were PIGD subtypes (p < 0.05). After 3 years, only 62% of patients in TD and 50% of patients in PIGD subtypes remained stable. The mean levodopa equivalent daily dose (LEDD) was higher in the PIGD subtype (276.92 ± 232.91 mg; p = 0.01). Lower LEDD [p < 0.05, odds ratio (OR) 0.99, 95% confidence interval (CI): 0.98–0.99] and higher TD/PIGD ratios (p < 0.05, OR 1.77, 95% CI: 1.29–2.43) were independent predictors of stability of TD subtype with an area under the curve (AUC) of 0.787 (95%CI: 0.669–0.876), sensitivity = 57.8%, and specificity = 89.7%.

Conclusion: Only 50–62% of PD motor subtypes as defined by MDS-UPDRS remained stable over 3 years. TD/PIGD ratio and baseline LEDD were independent predictors for TD subtype stability over 3 years.

Features of "ET plus" correlate with age and tremor duration: "ET plus" may be a disease stage rather than a subtype of essential tremor

BACKGROUND

Essential tremor (ET) is characterized by considerable clinical heterogeneity. In 2018, the term "ET plus" was introduced to mark a potential stratification point for dividing ET into subtypes - ET vs ET plus (i.e., ET cases with neurological features other than action tremor). However, as ET progresses, patients often develop increasingly severe tremor, spread of tremor, tremor under different activation conditions, and other features. Given this situation, ET plus may represent a disease stage rather than a disease classification or subtype. In theory, if the defining characteristics of a disease subtype fluctuate with age or disease duration, it raises the distinct possibility the "subtype" is a disease stage.

METHODS

A cohort of 241 prospectively enrolled ET cases underwent a detailed motor and cognitive assessment in which the features of ET plus including cerebellar signs (intention tremor, tandem gait difficulty), rest tremor, dystonia, and cognitive performance were evaluated. We determined whether these features of ET plus correlated with action tremor duration and age.

RESULTS

We demonstrated that numerous ET plus features were significantly correlated with both age and action tremor duration (numerous p values < 0.05). The same relationships were observed in a series of sensitivity analyses.

CONCLUSION

We observed that the component parts of ET plus are highly age- and stage-dependent. These features are yearly-changing features conditional on a demographic and disease stage variable. These data support the notion that ET plus may represent a disease stage rather than a distinct disease subtype or disease classification.

Clinical classification systems and long-term outcome in mid- and late-stage Parkinson's disease

Parkinson’s disease shows a heterogeneous course and different clinical subtyping systems have been described. To compare the capabilities of two clinical classification systems, motor-phenotypes, and a simplified clinical motor-nonmotor subtyping system, a cohort was included at mean 7.9 ± 5.3 years of disease duration, classified using both clinical systems, and reexamined and reclassified at the end of an observation period. Time-points were retrospectively extracted for five major disease milestones: death, dementia, Hoehn and Yahr stage 5, nursing home living, and walking aid use. Eighty-nine patients were observed for 8.1 ± 2.7 years after inclusion. Dementia developed in 32.9% of the patients and 36.0–67.4% reached the other milestones. Motor-phenotypes were unable to stratify risks during this period, but the worst compared with the more favorable groups in the motor-nonmotor system conveyed hazard ratios between 2.6 and 63.6 for all milestones. A clear separation of risks for dying, living at the nursing home, and reaching motor end-stage was also shown when using only postural instability and gait disorder symptoms, without weighing them against the severity of the tremor. At reexamination, 29.4% and 64.7% of patients had changed classification groups in the motor-phenotype and motor-nonmotor systems, respectively. The motor-nonmotor system thus stratified risks of reaching crucial outcomes in mid–late Parkinson’s disease far better than the well-studied motor-phenotypes. Removing the tremor aspect of motor-phenotypes clearly improved this system, however. Classifications in both systems became unstable over time. The simplification of the motor-nonmotor system was easily applicable and showed potential as a prognostic marker during a large part of Parkinson’s disease.

Distinct progression patterns across Parkinson disease clinical subtypes

OBJECTIVE

To examine specific symptom progression patterns and possible disease staging in Parkinson disease clinical subtypes.

METHODS

We recently identified Parkinson disease clinical subtypes based on comprehensive behavioral evaluations, "Motor Only," "Psychiatric & Motor," and "Cognitive & Motor," which differed in dementia and mortality rates. Parkinson disease participants ("Motor Only": n = 61, "Psychiatric & Motor": n = 17, "Cognitive & Motor": n = 70) and controls (n = 55) completed longitudinal, comprehensive motor, cognitive, and psychiatric evaluations (average follow-up = 4.6 years). Hierarchical linear modeling examined group differences in symptom progression. A three-way interaction among time, group, and symptom duration (or baseline age, separately) was incorporated to examine disease stages.

RESULTS

All three subtypes increased in motor dysfunction compared to controls. The "Motor Only" subtype did not show significant cognitive or psychiatric changes compared to the other two subtypes. The "Cognitive & Motor" subtype's cognitive dysfunction at baseline further declined compared to the other two subtypes, while also increasing in psychiatric symptoms. The "Psychiatric & Motor" subtype's elevated psychiatric symptoms at baseline remained steady or improved over time, with mild, steady decline in cognition. The pattern of behavioral changes and analyses for disease staging yielded no evidence for sequential disease stages.

INTERPRETATION

Parkinson disease clinical subtypes progress in clear, temporally distinct patterns from one another, particularly in cognitive and psychiatric features. This highlights the importance of comprehensive clinical examinations as the order of symptom presentation impacts clinical prognosis.

Discovery of Parkinson's disease states and disease progression modelling: a longitudinal data study using machine learning

BACKGROUND

Parkinson's disease is heterogeneous in symptom presentation and progression. Increased understanding of both aspects can enable better patient management and improve clinical trial design. Previous approaches to modelling Parkinson's disease progression assumed static progression trajectories within subgroups and have not adequately accounted for complex medication effects. Our objective was to develop a statistical progression model of Parkinson's disease that accounts for intra-individual and inter-individual variability and medication effects.

METHODS

In this longitudinal data study, data were collected for up to 7-years on 423 patients with early Parkinson's disease and 196 healthy controls from the Parkinson's Progression Markers Initiative (PPMI) longitudinal observational study. A contrastive latent variable model was applied followed by a novel personalised input-output hidden Markov model to define disease states. Clinical significance of the states was assessed using statistical tests on seven key motor or cognitive outcomes (mild cognitive impairment, dementia, dyskinesia, presence of motor fluctuations, functional impairment from motor fluctuations, Hoehn and Yahr score, and death) not used in the learning phase. The results were validated in an independent sample of 610 patients with Parkinson's disease from the National Institute of Neurological Disorders and Stroke Parkinson's Disease Biomarker Program (PDBP).

FINDINGS

PPMI data were download July 25, 2018, medication information was downloaded on Sept 24, 2018, and PDBP data were downloaded between June 15 and June 24, 2020. The model discovered eight disease states, which are primarily differentiated by functional impairment, tremor, bradykinesia, and neuropsychiatric measures. State 8, the terminal state, had the highest prevalence of key clinical outcomes including 18 (95%) of 19 recorded instances of dementia. At study outset 4 (1%) of 333 patients were in state 8 and 138 (41%) of 333 patients reached stage 8 by year 5. However, the ranking of the starting state did not match the ranking of reaching state 8 within 5 years. Overall, patients starting in state 5 had the shortest time to terminal state (median 2·75 [95% CI 1·75-4·25] years).

INTERPRETATION

We developed a statistical progression model of early Parkinson's disease that accounts for intra-individual and inter-individual variability and medication effects. Our predictive model discovered non-sequential, overlapping disease progression trajectories, supporting the use of non-deterministic disease progression models, and suggesting static subtype assignment might be ineffective at capturing the full spectrum of Parkinson's disease progression.

FUNDING

Michael J Fox Foundation.

Lateralization of Motor Signs Affects Symptom Progression in Parkinson Disease

Background: Asymmetry of motor signs is a cardinal feature of Parkinson disease which may impact phenotypic expression.

Objective: To investigate the relationship between lateralization of motor signs and symptom progression and severity during longitudinal observation for up to 4 years in a naturalistic study.

Methods: We analyzed data prospectively collected during the NINDS Parkinson Disease Biomarker Project (PDBP). We defined the Movement Disorder Society Revision of the Unified Parkinson Disease Rating Scale (MDS-UPDRS) part II as the primary measure of symptom progression. Left side predominant subjects were those whose lateralized motor scores on the MDS-UPDRS part III were ≥2 points higher on the left side than on the right side of the body. Multiple regression models (controlled for age, gender, education years, ethnicity, levodopa equivalent daily dose (LEDD) at baseline, and years with PD) were used to estimate the rate of symptom progression comparing left predominant (LPD) with non-left predominant (NLPD) subjects. A sensitivity analysis was performed using the same multiple regression models in the subgroups of low (0–26) or high (>27) MDS-UPDRS II score at baseline to determine if PD severity influenced the results.

Results: We included 390 participants, 177 LPD and 213 NLPD. We found that MDS-UPDRS part II progression from baseline to 48 months was faster in LPD compared to NLPD (0.6 points per year faster in LPD, p = 0.05). Additionally, the LPD group was statistically significantly worse at baseline and at 48 months in several subparts of the MDS-UPDRS and the Parkinson's Disease Questionnaire-39 (PDQ-39) mobility score. Significantly slower progression (difference of −0.8, p = 0.01) and lower score at 48 months (difference of −3.8, p = 0.003) was seen for NLPD vs. LPD in the group with lower baseline MDS-UPDRS part II score.

Conclusion: Left side lateralization was associated with faster symptom progression and worse outcomes in multiple clinical domains in our cohort. Clinicians should consider using motor predominance in their counseling regarding prognosis.

Mild and marked executive dysfunction and falls in people with Parkinson's disease

BACKGROUND

Executive dysfunction and risk of falling are hallmarks of Parkinson's disease (PD). However, it is unclear how executive dysfunction predisposes people with PD to falling.

OBJECTIVES

To: (i) identify sensorimotor, balance, and cardiovascular risk factors for falls that discriminate between those with normal executive function and those with mild and marked executive dysfunction in people with PD and (ii) determine whether mild and marked executive dysfunction are significant risk factors for falls when adjusting for PD duration and severity and freezing of gait (FOG).

METHODS

Using the Frontal Assessment Battery, 243 participants were classified into normal executive function (n = 87), mild executive dysfunction (n = 100), and marked executive dysfunction (n = 56) groups. Participants were asked if they had episodes of FOG in the last month and were assessed with the Movement Disorders Society - Unified Parkinson's Disease Rating Scale (MDS-UPDRS), the Hoehn and Yahr Scale, the physiological profile assessment, and tests of orthostatic hypotension, coordinated stability, and gait and were then followed-up prospectively for falls for 32-52 weeks.

RESULTS

Several PD-specific (elevated Hoehn and Yahr stage, higher MDS-UPDRS scale scores, a history of FOG, Postural Instability and Gait Difficulty subtype, and longer PD duration), sensorimotor (poor vision, knee extension weakness, slow simple reaction time), and balance (greater postural sway and poor controlled leaning balance) factors discriminated among the normal executive function and mild and marked executive dysfunction groups. Fall rates (mean ± SD) differed significantly among the groups (normal executive function: 1.0 ± 1.7; mild executive dysfunction: 2.8 ± 5.2; marked executive dysfunction: 4.7 ± 7.3) with the presence of both mild and marked executive dysfunction identified as significant risk factors for falls when adjusting for three measures of PD severity (Hoehn and Yahr scale scores, disease duration, and FOG).

CONCLUSIONS

Several PD-specific, sensorimotor, and balance factors differed significantly among the normal, mild, and marked executive dysfunction groups and both mild and marked executive dysfunction were identified as independent risk factors for falls in people with PD.

The inconsistency and instability of Parkinson's disease motor subtypes

INTRODUCTION

Tremor-dominant (TD), indeterminate/mixed (ID/M) and postural instability gait difficulty/akinetic-rigid (PIGD/AR) are commonly used subtypes to categorize Parkinson's disease (PD) patients based on their most prominent motor signs. Three different algorithms to determine these motor subtypes are used. Here, we examined if PD subtypes are consistent among algorithms and if subtype stability over time depends on the applied algorithm.

METHODS

Using a large longitudinal PD database, we applied 3 published algorithms of PD motor subtype classification in two sets of analyses: 1) cross-sectional analysis in 1185 patients, determining the prevalence of subtypes in 5-year intervals of disease duration; 2) longitudinal analysis of 178 patients, comparing subtypes of individual patients at baseline (within 5 years of diagnosis) and at follow-up ≥ 5 years after baseline.

RESULTS

Cross-sectionally, prevalence of subtypes varied widely among the 3 algorithms: 5-32% TD, 9-31% ID/M, and 59-75% PIGD/AR. For all 3 algorithms, cross-sectional analysis showed a marked decline of TD prevalence with disease duration and a corresponding increase in PIGD/AR prevalence, driven by increasing gait/balance scores over time. Longitudinally, only 15-36% of baseline TD patients were still categorized as TD at 6.2 ± 1.0 years of follow-up. In 15-39% of baseline TD patients, the subtype changed to ID/M, and 46-50% changed to PIGD/AR. This shift was observed using all 3 algorithms.

CONCLUSION

PD motor subtypes determined by different established algorithms are inconsistent and unstable over time. Lack of subtype fidelity should be considered when interpreting biomarker-subtype correlation and highlights the need for better definition of PD subtypes.

Predicting the longitudinal changes of levodopa dose requirements in Parkinson's disease using item response theory assessment of real-world Unified Parkinson's Disease Rating Scale

Item response theory (IRT) has been recently adopted to successfully characterize the progression of Parkinson's disease using serial Unified Parkinson's Disease Rating Scale (UPDRS) measurements. However, it has yet to be applied in predicting the longitudinal changes of levodopa dose requirements in the real‐world setting. Here we use IRT to extract two latent variables that represent tremor and non‐tremor‐related symptoms from baseline assessments of UPDRS Part III scores. We show that relative magnitudes of the two latent variables are strong predictors of the progressive increase of levodopa equivalent dose (LED). Retrospectively collected item‐level UPDRS Part III scores and longitudinal records of prescribed medication doses of 128 patients with de novo PD extracted from the electronic medical records were used for model building. Supplementary analysis based on a subset of 36 patients with at least three serial assessments of UPDRS Part III scores suggested that the two latent variables progress at significantly different rates. A web application was developed to facilitate the use of our model in making individualized predictions of future LED and disease progression.

Genome-Wide Association Study Meta-Analysis for Parkinson Disease Motor Subtypes

OBJECTIVE

To discover genetic determinants of Parkinson disease (PD) motor subtypes, including tremor dominant (TD) and postural instability/gait difficulty (PIGD) forms.

METHODS

In 3,212 PD cases of European ancestry, we performed a genome-wide association study (GWAS) examining 2 complementary outcome traits derived from the Unified Parkinson's Disease Rating Scale, including dichotomous motor subtype (TD vs PIGD) or a continuous tremor/PIGD score ratio. Logistic or linear regression models were adjusted for sex, age at onset, disease duration, and 5 ancestry principal components, followed by meta-analysis.

RESULTS

Among 71 established PD risk variants, we detected multiple suggestive associations with PD motor subtype, including GPNMB (rs199351, p subtype = 0.01, p ratio = 0.03), SH3GL2 (rs10756907, p subtype = 0.02, p ratio = 0.01), HIP1R (rs10847864, p subtype = 0.02), RIT2 (rs12456492, p subtype = 0.02), and FBRSL1 (rs11610045, p subtype = 0.02). A PD genetic risk score integrating all 71 PD risk variants was also associated with subtype ratio (p = 0.026, ß = -0.04, 95% confidence interval = -0.07-0). Based on top results of our GWAS, we identify a novel suggestive association at the STK32B locus (rs2301857, p ratio = 6.6 × 10-7), which harbors an independent risk allele for essential tremor.

CONCLUSIONS

Multiple PD risk alleles may also modify clinical manifestations to influence PD motor subtype. The discovery of a novel variant at STK32B suggests a possible overlap between genetic risk for essential tremor and tremor-dominant PD.

Consistency and Stability of Motor Subtype Classifications in Patients With de novo Parkinson's Disease

Objective

Patients with Parkinson’s disease (PD) are commonly classified into subtypes based on motor symptoms. The aims of the present study were to determine the consistency between PD motor subtypes, to assess the stability of PD motor subtypes over time, and to explore the variables influencing PD motor subtype stability.

Methods

This study was part of a longitudinal study of de novo PD patients at a single center. Based on three different motor subtype classification systems proposed by Jankovic, Schiess, and Kang, patients were respectively categorized as tremor-dominant/indeterminate/postural instability and gait difficulty (TD/indeterminate/PIGD), TD_S/mixed_S/akinetic-rigid_S (ARS), or TD_K/mixed_K/AR_K at baseline evaluation and then re-assessed 1 month later. Demographic and clinical characteristics were recorded at each evaluation. The consistency between subtypes at baseline evaluation was assessed using Cohen’s kappa coefficient (κ). Additional variables were compared between PD subtype groups using the two-sample t-test, Mann–Whitney U-test or Chi-squared test.

Results

Of 283 newly diagnosed, untreated PD patients, 79 were followed up at 1 month. There was fair agreement between the Jankovic, Schiess, and Kang classification systems (κ_S = 0.383 ± 0.044, κ_K = 0.360 ± 0.042, κ_SK = 0.368 ± 0.038). Among the three classification systems, the Schiess classification was the most stable and the Jankovic classification was the most unstable. The non-motor symptoms questionnaire (NMSQuest) scores differed significantly between PD patients with stable and unstable subtypes based on the Jankovic classification (p = 0.008), and patients with a consistent subtype had more severe NMSQuest scores than patients with an inconsistent subtype.

Conclusion

Fair consistency was observed between the Jankovic, Schiess, and Kang classification systems. For the first time, non-motor symptoms (NMSs) scores were found to influence the stability of the TD/indeterminate/PIGD classification. Our findings support combining NMSs with motor symptoms to increase the effectiveness of PD subtypes.

Clinical Phenotypes of Parkinson's Disease Associate with Distinct Gut Microbiota and Metabolome Enterotypes

Parkinson’s disease (PD) is a clinically heterogenic disorder characterized by distinct clinical entities. Most studies on motor deficits dichotomize PD into tremor dominant (TD) or non-tremor dominant (non-TD) with akinetic-rigid features (AR). Different pathophysiological mechanisms may affect the onset of motor manifestations. Recent studies have suggested that gut microbes may be involved in PD pathogenesis. The aim of this study was to investigate the gut microbiota and metabolome composition in PD patients in relation to TD and non-TD phenotypes. In order to address this issue, gut microbiota and the metabolome structure of PD patients were determined from faecal samples using 16S next generation sequencing and gas chromatography–mass spectrometry approaches. The results showed a reduction in the relative abundance of Lachnospiraceae, Blautia, Coprococcus, Lachnospira, and an increase in Enterobacteriaceae, Escherichia and Serratia linked to non-TD subtypes. Moreover, the levels of important molecules (i.e., nicotinic acid, cadaverine, glucuronic acid) were altered in relation to the severity of phenotype. We hypothesize that the microbiota/metabolome enterotypes associated to non-TD subtypes may favor the development of gut inflammatory environment and gastrointestinal dysfunctions and therefore a more severe α-synucleinopathy. This study adds important information to PD pathogenesis and emphasizes the potential pathophysiological link between gut microbiota/metabolites and PD motor subtypes.

Corneal confocal microscopy detects small fibre neurodegeneration in Parkinson's disease using automated analysis

We studied the utility of corneal confocal microscopy (CCM) in detecting a reduction in corneal nerve parameters in a large cohort of patients with Parkinson’s disease (PD) compared to controls using a fully automated potentially scalable method of analysis. We also assessed if CCM parameters are related to the severity and sub-type of PD. 98 participants with PD and 26 healthy controls underwent CCM with automated corneal nerve quantification, MDS-UPDRS III, Hoehn and Yahr scale, Montreal Cognitive Assessment, Parkinson’s Disease Questionnaire-39 and PD subtype assessment. Corneal nerve fibre density (mean difference: − 5.00 no/mm², 95% confidence interval (CI) [− 7.89, − 2.12], p = 0.001), corneal nerve branch density (mean difference: − 10.71 no/mm², 95% CI [− 16.93, − 4.48], p = 0.003), corneal total branch density (mean difference: − 14.75 no/mm², 95% CI [− 23.58, − 5.92], p = 0.002), and corneal nerve fibre length (mean difference: − 2.57 mm/mm², 95% CI [− 4.02, − 1.12], p = 0.001) were significantly lower in PD participants compared to controls. There was no correlation between corneal nerve parameters and duration, severity or subtype of PD, cognitive function or quality of life. CCM with automated corneal nerve analysis identifies nerve fibre damage and may act as a biomarker for neurodegeneration in PD.