Prognostic factors for the progression of Parkinson's disease: a systematic review

Impulse control behaviors and apathy commonly co-occur in de novo Parkinson's disease and predict the incidence of levodopa-induced dyskinesia

OBJECTIVE

Impulse control behaviors (ICBs) and apathy are believed to represent opposite motivational expressions of the same behavioral spectrum involving hypo- and hyperdopaminergic status, but this has been recently debated. Our study aims to estimate the co-occurrence of ICBs and apathy in early Parkinson's disease (PD) and to determine whether this complex neuropsychiatric condition is an important marker of PD prognoses.

METHODS

Neuropsychiatric symptoms, clinical data, neuroimaging results, and demographic data from de novo PD patients were obtained from the Parkinson's Progression Markers Initiative, a prospective, multicenter, observational cohort. The clinical characteristics of ICBs co-occurring with apathy and their prevalence were analyzed. We compared the prognoses of the different groups during the 8-year follow-up. Multivariate Cox regression analysis was conducted to predict the development of levodopa-induced dyskinesia (LID) using baseline neuropsychiatric symptoms.

RESULTS

A total of 422 PD patients and 195 healthy controls (HCs) were included. In brief, 87 (20.6 %) de novo PD patients and 37 (19.0 %) HCs had ICBs at baseline. Among them, 23 (26.4 %) de novo PD patients and 3 (8.1 %) HCs had clinical symptoms of both ICBs and apathy. The ICBs and apathy group had more severe non-motor symptoms than the isolated ICBs group. Cox regression analysis demonstrated that the co-occurrence of ICBs and apathy was a risk factor for LID development (HR 2.229, 95 % CI 1.209 to 4.110, p = 0.010).

CONCLUSIONS

Co-occurrence of ICBs and apathy is common in patients with early PD and may help to identify the risk of LID development.

Associations between baseline cognitive status and motor outcomes after treadmill training in people with Parkinson's disease: a pilot study

PURPOSE

To determine the effect of baseline cognition on gait outcomes after a treadmill training program for people with Parkinson's disease (PD).

METHODS

This pilot clinical trial involved people with PD who were classified as having no cognitive impairment (PD-NCI) or mild cognitive impairment (PD-MCI). Baseline executive function and memory were assessed. The intervention was a 10-week gait training program (twice-weekly treadmill sessions), with structured speed and distance progression and verbal cues for gait quality. Response to intervention was assessed by gait speed measured after week 2 (short-term) and week 10 (long-term).

RESULTS

Participants (n = 19; 12 PD-NCI, 7 PD-MCI) had a mean (standard deviation) age of 66.5 (6.3) years, disease duration of 8.8 (6.3) years, and MDS-UPDRS III score of 21.3 (10.7). Gait speed increased at short-term and long-term assessments. The response did not differ between PD-NCI and PD-MCI groups; however, better baseline memory performance and milder PD motor severity were independently associated with greater improvements in gait speed in unadjusted and adjusted models.

CONCLUSIONS

These findings suggest that memory impairments and more severe motor involvement can influence the response to gait rehabilitation in PD and highlight the need for treatments optimized for people with greater cognitive and motor impairment.IMPLICATIONS FOR REHABILITATIONCognitive deficits in Parkinson's disease (PD) could impact motor learning and gait rehabilitation, yet little is known about the effects of cognitive impairments on the response to rehabilitation in people with PD.This study demonstrates that the response to gait rehabilitation did not differ between people with PD who had no cognitive impairment and those with mild cognitive impairment.Across all participants, better baseline memory was associated with greater improvements in gait speed.Rehabilitation professionals should be mindful of PD severity, as those with more substantial memory and motor impairments may require additional dosing or support to maximize gait training benefits.

The simultaneous presence of demoralization, apathy, and depression has a detrimental impact on both cognitive function and motor symptoms in Parkinson's disease patients

Objective

Parkinson's disease (PD) is marked not only by motor symptoms but also by neuropsychiatric manifestations, including demoralization, apathy, and depression. Understanding the clinical distribution and characteristics of these co-occurring symptoms is crucial for improving quality of life of PD patients.

Methods

This study enrolled 195 Chinese PD patients from Xinhua Hospital affiliated to Shanghai Jiao Tong University School of Medicine. The study involved analyzing the clinical characteristics related to the simultaneous presence of demoralization, apathy, and depression in PD patients. Linear regression was employed to elucidate the linear trend between the quantity of negative neuropsychiatric symptoms and cognitive function, as well as motor symptoms and motor complications. SPSS mediation models were utilized to investigate whether the severity of cognitive function mediated the connection between multiple negative neuropsychiatric symptoms and motor symptoms.

Results

Among PD patients, a notable 57.5% experience the presence of multiple concurrent negative neuropsychiatric symptoms. Our investigation unveiled a correlation where patients with more negative neuropsychiatric symptoms displayed heightened cognitive impairment (P=0.048) and more severe motor symptoms (P=0.024), following a linear trend with increasing symptom numbers. Additionally, cognitive impairment played a partial mediating role in the impact of multiple negative neuropsychiatric symptoms on motor symptoms (β=0.747; 95% bootstrap confidence interval: 0.195 to 1.532).

Conclusions

The co-occurrence of these negative neuropsychiatric symptoms has the potential to worsen cognitive function and motor symptoms in PD patients. Moreover, cognitive impairment was identified as playing a partial mediating role in the relationship between multiple negative neuropsychiatric symptoms and motor symptoms.

Piperine improves levodopa availability in the 6-OHDA-lesioned rat model of Parkinson's disease by suppressing gut bacterial tyrosine decarboxylase

AIM

Tyrosine decarboxylase (TDC) presented in the gut-associated strain Enterococcus faecalis can convert levodopa (L-dopa) into dopamine (DA), and its increased abundance would potentially minimize the availability and efficacy of L-dopa. However, the known human decarboxylase inhibitors are ineffective in this bacteria-mediated conversion. This study aims to investigate the inhibition of piperine (PIP) on L-dopa bacterial metabolism and evaluates the synergistic effect of PIP combined with L-dopa on Parkinson's disease (PD).

METHODS

Metagenomics sequencing was adopted to determine the regulation of PIP on rat intestinal microbiota structure, especially on the relative abundance of E. faecalis. Then, the inhibitory effects of PIP on L-dopa conversion and TDC expression of E. faecalis were tested in vitro. We examined the synergetic effect of the combination of L-dopa and PIP on 6-hydroxydopamine (6-OHDA)-lesioned rats and tested the regulations of L-dopa bioavailability and brain DA level by pharmacokinetics study and MALDI-MS imaging. Finally, we evaluated the microbiota-dependent improvement effect of PIP on L-dopa availability using pseudo-germ-free and E. faecalis-transplanted rats.

RESULTS

We found that PIP combined with L-dopa could better ameliorate the move disorders of 6-OHDA-lesioned rats by remarkably improving L-dopa availability and brain DA level than L-dopa alone, which was associated with the effect of PIP on suppressing the bacterial decarboxylation of L-dopa via effectively downregulating the abnormal high abundances of E. faecalis and TDC in 6-OHDA-lesioned rats.

CONCLUSION

Oral administration of L-dopa combined with PIP can improve L-dopa availability and brain DA level in 6-OHDA-lesioned rats by suppressing intestinal bacterial TDC.

Association of physical activity with the risk of Parkinson's disease in depressive disorder: A nationwide longitudinal cohort study

Regular physical activity (PA) has been suggested as effective disease preventable strategies for Parkinson's disease (PD). Depression often precedes PD but whether PA also would reduce the risk of PD in patients with depression has not been known. The aim of study is to examine the association of regular PA with risk of PD among patients with depressive disorder. A total of 1,342,282 patients with depressive disorder were identified from a nationwide health screening cohort from 2010 to 2016. The exposure was changes in pattern of regular PA between pre-and post-diagnosis of depressive disorder, categorized as four groups; 1) no PA, 2) increased PA, 3) decreased PA, and 4) maintaining PA. The outcome was risk of incident PD, calculated using multivariate adjusted Cox proportional hazards regressions according to the PA categorization. Total of 8901 PD cases (0.66%) were developed during 5.3 years of follow-up period. Maintaining PA group was associated with the lowest risk of PD (adjusted hazard ratio [aHR] 0.89, 95% CI 0.83-0.97) among all other PA groups with depressive disorder (with no PA group as reference). Otherwise, decreased PA group significantly increased the risk of PD (aHR 1.10, 95% CI 1.03-1.16). Those who maintained PA before and after diagnosis of depressive disorder were associated with lower risk of incident PD.

Motor progression phenotypes in early-stage Parkinson's Disease: A clinical prediction model and the role of glymphatic system imaging biomarkers

BACKGROUND

Substantial heterogeneity of motor symptoms in Parkinson's disease (PD) poses a challenge to disease prediction.

OBJECTIVES

The aim of this study was to construct a nomogram model that can distinguish different longitudinal trajectories of motor symptom changes in early-stage PD patients.

METHODS

Data on 90 patients with 5-years of follow-up were collected from the Parkinson's Progression Marker Initiative (PPMI) cohort. We used a latent class mixed modeling (LCMM) to identify distinct progression patterns of motor symptoms, and backward stepwise logistic regression with baseline information was conducted to identify the potential predictors for motor trajectory and to develop a nomogram. The performance of the nomogram model was then evaluated using the optimism-corrected C-index for internal validation, the area under the curve (AUC) of the receiver operating characteristic (ROC) curve for discrimination, the calibration curve for predictive accuracy, and decision curve analysis (DCA) for its clinical value.

RESULTS

We identified two trajectories for motor progression patterns. The first, Class 1 (Motor deteriorated group), was characterized by sustained, continuously worsening motor symptoms, and the second, Class 2 (Motor stable group), had stable motor symptoms throughout the follow-up period. The best combination of 7 baseline variables was identified and assembled into the nomogram: Scopa-AUT [odds ratio (OR), 1.11; p = 0.091], Letter number sequencing (LNS) (OR, 0.76; p = 0.068), the asymmetry index of putamen (OR, 0.95; p = 0.034), mean caudate uptake (OR, 0.14; p = 0.086), CSF pTau/α-synuclein (OR, 0.00; p = 0.011), CSF tTau/Aβ (OR, 25434806; p = 0.025), and the index for diffusion tensor image analysis along the perivascular space (ALPS-index) (OR, 0.02; p = 0.030). The nomogram achieved good discrimination, with an original AUC of 0.901 (95% CI, 0.813-0.989), and the bias-corrected concordance index (C-index) with 1,000 bootstraps was 0.834. The calibration curve and DCA also suggested both the high accuracy and clinical usefulness of the nomogram, respectively.

CONCLUSIONS

This study proposes an effective nomogram to predict different motor progression patterns in early-stage PD. Furthermore, the imaging biomarker indicating glymphatic function could be an independent predictive factor for PD motor progression.

Determinants of Dual-task Gait Speed in Older Adults with and without Parkinson's Disease

Mobility difficulties for people with Parkinson's disease (PwPD) are more pronounced when they perform a simultaneous cognitive task while walking. Although it is known that neurodegeneration results in widespread motor and brain impairments, few studies have comprehensively examined possible physical and mental determinants of dual task walking in PwPD. In this cross-sectional study, we aimed to investigate if and how muscle strength (sit-to-stand 30-sec test), cognition (mini-mental state examination) and functionality (timed up and go test) affect walking performance (10-meter walking test) with and without arithmetic dual task from older adults with and without Parkinson's disease. Walking speed was reduced by 16% and 11% with arithmetic dual task for PwPD (from 1.07±0.28 to 0.91±0.29 m.s-1, p<0.001) and older adults (from 1.32±0.28 to 1.16±0.26 m.s-1, p=0.002) compared to essential walking. The cognitive state was similar among the groups, but it was only associated with the dual-task walking speed in PwPD. In PwPD, lower limb strength was the better predictor of speed, whereas mobility was more related to it in older adults. Therefore, future exercise interventions aiming to improve walking in PwPD should consider these findings to maximize their effectiveness.

Time Taken for and Causes of a Decline to Hoehn and Yahr Stage 5 in Patients with Parkinson's Disease

Objective Prediction of time until and causes of becoming bedridden may help patients with Parkinson's disease (PD) plan their productive lives. This study assessed the relationship between the age at the PD onset and time taken to reach Hoehn and Yahr stage (HY) 5 as well as the causes of motor decline to HY5 in Japanese patients with PD. Patients We enrolled patients with PD who visited our institute between April 2015 and December 2020, met the UK brain bank criteria, had medical records from the early PD stage, and had had HY5 for over three months. The relationship between the age at the PD onset and the disease duration was evaluated. Data on the possible causes of motor decline to HY5 were obtained from patients, caregivers or medical records. Results In total, 123 patients with PD (mean age at the PD onset was 69.3 years old; 80 women and 43 men) were included. The age at the PD onset was significantly and negatively correlated with the time until the decline to HY5. Among the 123 patients, 49 reported that the natural course of PD caused the decline to HY5. Possible events that accelerated the motor decline to HY5 included traumatic injury, pneumonia, and other medical or social conditions that might have resulted in reduced daily activities. Conclusion The time until the decline to HY5 can be estimated based on the age at the PD onset. In addition to natural PD progression, medical or social conditions that reduce physical activity may accelerate motor decline to HY5.

Tinetti balance performance is associated with mortality in older adults with late-onset Parkinson's disease: a longitudinal study

BACKGROUND

Parkinson's disease (PD) is associated with a 3-fold mortality risk, which is closely related to advancing age. Evidence is lacking regarding the factors associated with the risks of mortality or nursing-home (NH) admission, in elderly patients with PD. We aimed at identifying the clinical characteristics associated with these outcomes, in older community-dwelling patients with late-onset PD.

METHODS

Retrospective, observational analysis of data from geriatric day hospital patients. Motor assessment included Unified Parkinson Disease Rating Scale (UPDRS) part III score, Tinetti Performance Oriented Mobility Assessment (POMA) balance and gait tests, and gait speed. Levodopa equivalent dose, comorbidity, cognitive performance, Activities of Daily Living performance were examined. Cox proportional hazards models were performed to identify the factors associated with mortality and NH admission rate (maximum follow-up time = 5 years).

RESULTS

We included 98 patients, mean age 79.4 (SD = 5.3) of whom 18 (18.3%) died and 19 (19.4%) were admitted into NH, over a median follow-up of 4 years. In multivariate Cox models, poor balance on the Tinetti POMA scale (HR = 0.82 95%CI (0.66-0.96), p = .023) and older age (HR = 1.12 95%CI (1.01-1.25), p = .044) were the only variables significantly associated with increased mortality risk. A Tinetti balance score below 11/16 was associated with a 6.7 hazard for mortality (p = .006). No specific factor was associated with NH admissions.

CONCLUSIONS

Age and the Tinetti POMA score were the only factors independently associated with mortality. The Tinetti POMA scale should be considered for balance assessment and as a screening tool for the most at-risk individuals, in this population.

Onset of Postural Instability in Parkinson's Disease Depends on Age rather than Disease Duration

Background

Postural instability and falls are considered a major factor of impaired quality of life in patients with advanced Parkinson's disease (PD). The knowledge of the time at which postural instability occurs will help to provide the evidence required to introduce fall-prevention strategies at the right time in PD.

Objective

To investigate whether postural instability of patients with different age at disease onset is associated with age or with disease duration of PD.

Methods

Patients diagnosed with sporadic PD between 1991 and 2017 and postural instability (according to the International Parkinson and Movement Disorder Society Unified Parkinson's Disease Rating Scale (MDS-UPDRS) part III, item 3.12 postural instability) were included, with strict inclusion criteria including regular follow-ups, agreement on data use, and exclusion of comorbidities affecting the free stand.

Results

Applying these strict inclusion criteria, we included 106 patients. Those younger than 50 years at PD onset took significantly longer to develop postural instability (n = 23 patients, median: 18.4 years) compared with patients with later onset of PD (50-70 years, n = 66, median: 14.2 years, p < 0.001; and >70 years, n = 17, median: 5.7 years, p < 0.001, Kruskal-Wallis test followed by Dunn's multiple comparisons test). There was no association between total MDS-UPDRS III (as a measure of motor symptom severity) at onset of postural instability.

Conclusions

In PD, postural instability is primarily associated with the age of the patient and not with disease duration.

Short chain fatty acids-producing and mucin-degrading intestinal bacteria predict the progression of early Parkinson's disease

To elucidate the relevance of gut dysbiosis in Parkinson’s disease (PD) in disease progression, we made random forest models to predict the progression of PD in two years by gut microbiota in 165 PD patients. The area under the receiver operating characteristic curves (AUROCs) of gut microbiota-based models for Hoehn & Yahr (HY) stages 1 and 2 were 0.799 and 0.705, respectively. Similarly, gut microbiota predicted the progression of Movement Disorder Society-Unified Parkinson’s Disease Rating Scale (MDS-UPDRS) III scores in an early stage of PD with AUROC = 0.728. Decreases of short-chain fatty acid-producing genera, Fusicatenibacter, Faecalibacterium, and Blautia, as well as an increase of mucin-degrading genus Akkermansia, predicted accelerated disease progression. The four genera remained unchanged in two years in PD, indicating that the taxonomic changes were not the consequences of disease progression. PD patients with marked gut dysbiosis may thus be destined to progress faster than those without gut dysbiosis.

Foot Trajectory Features in Gait of Parkinson’s Disease Patients

Parkinson’s disease (PD) is a progressive neurological disorder characterized by movement disorders, such as gait instability. This study investigated whether certain spatial features of foot trajectory are characteristic of patients with PD. The foot trajectory of patients with mild and advanced PD in on-state and healthy older and young individuals was estimated from acceleration and angular velocity measured by inertial measurement units placed on the subject’s shanks, just above the ankles. We selected six spatial variables in the foot trajectory: forward and vertical displacements from heel strike to toe-off, maximum clearance, and change in supporting leg (F1 to F3 and V1 to V3, respectively). Healthy young individuals had the greatest F2 and F3 values, followed by healthy older individuals, and then mild PD patients. Conversely, the vertical displacements of mild PD patients were larger than the healthy older individuals. Still, those of healthy older individuals were smaller than the healthy young individuals except for V3. All six displacements of the advanced PD patients were smaller than the mild PD patients. To investigate features in foot trajectories in detail, a principal components analysis and soft-margin kernel support vector machine was used in machine learning. The accuracy in distinguishing between mild PD patients and healthy older individuals and between mild and advanced PD patients was 96.3 and 84.2%, respectively. The vertical and forward displacements in the foot trajectory was the main contributor. These results reveal that large vertical displacements and small forward ones characterize mild and advanced PD patients, respectively.

Prediction of Quality of Life in Patients With Parkinson’s Disease With and Without Excessive Daytime Sleepiness: A Longitudinal Study

Objective

There is a lack of longitudinal studies that directly compare the quality of life (QoL) and investigate the impact of clinical factors on QoL across different excessive daytime sleepiness (EDS) statuses in Parkinson’s disease (PD); therefore, we aimed to compare QoL and reveal the potential heterogeneous predictors of QoL between patients with PD with and without EDS.

Methods

We collected clinical data among 306 patients with PD over 2 years. EDS was assessed by the Epworth Sleepiness Scale and QoL was measured with the 39-item Parkinson’s Disease Questionnaire.

Results

We found that at both baseline and follow-up, patients with PD with EDS had poorer QoL and suffered more non-motor symptoms including depression and clinical probable rapid eye movement sleep behavior disorder (cpRBD). The generalized linear mixed model analysis indicated that the major predictors of QoL in PD with EDS were the akinetic-rigid type, disease duration, and total levodopa equivalent dose, while in PD without EDS, the primary determinants of QoL were Hoehn and Yahr, Mini-Mental State Examination (MMSE), and cpRBD.

Conclusion

Patients with PD with EDS presented with poorer QoL. Besides, the baseline predictors of future QoL differed between patients with PD with and without EDS. These findings remind clinicians to target specific clinical factors when attempting to improve QoL among patients with PD.

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.

Molecular Features of Parkinson's Disease in Patient-Derived Midbrain Dopaminergic Neurons

BACKGROUND

Despite intense efforts to develop an objective diagnostic test for Parkinson's disease, there is still no consensus on biomarkers that can accurately diagnose the disease.

OBJECTIVE

Identification of biomarkers for idiopathic Parkinson's disease (PD) may enable accurate diagnosis of the disease. We tried to find molecular and cellular differences in dopaminergic (DA) neurons derived from healthy subjects and idiopathic PD patients with or without rest tremor at onset.

METHODS

We measured the expression of genes controlling dopamine synthesis, sequestration, and catabolism as well as the levels of corresponding metabolites and reactive oxygen species in midbrain DA neurons differentiated from induced pluripotent stem cells (iPSCs) of healthy subjects and PD patients with or without rest tremor.

RESULTS

Significant differences in DA-related gene expression, metabolites, and oxidative stress were found between midbrain DA neurons derived from healthy subjects and patients with PD. DA neurons derived from PD patients with or without rest tremor at onset exhibited significant differences in the levels of some of these transcripts, metabolites, and oxidative stress.

CONCLUSION

The unique combination of these quantifiable molecular and cellular traits in iPSC-derived midbrain DA neurons can distinguish healthy subjects from idiopathic PD patients and segregate PD patients with or without rest tremor at onset. The strategy may be used to develop an objective diagnostic test for PD.

Prognostication in neurology

Prognosticating is central to primary palliative care in neurology. Many neurologic diseases carry a high burden of troubling symptoms, and many individuals consider health states due to neurologic disease worse than death. Many patients and families report high levels of need for information at all disease stages, including information about prognosis. There are many barriers to communicating prognosis including prognostic uncertainty, lack of training and experience, fear of destroying hope, and not enough time. Developing the right mindset, tools, and skills can improve one's ability to formulate and communicate prognosis. Prognosticating is subject to many biases which can dramatically affect the quality of patient care; it is important for providers to recognize and reduce them. Patients and surrogates often do not hear what they are told, and even when they hear correctly, they form their own opinions. With practice and self-reflection, one can improve their prognostic skills, help patients and families create honest roadmaps of the future, and deliver high-quality person-centered care.

Prognostic imaging variables for recurrent laryngeal and hypopharyngeal carcinoma treated with primary chemoradiotherapy: A systematic review and meta-analysis

Background

In this systematic review, we aim to identify prognostic imaging variables of recurrent laryngeal or hypopharyngeal carcinoma after chemoradiotherapy.

Methods

A systematic search was performed in PubMed and EMBASE (1990–2020). The crude data and effect estimates were extracted for each imaging variable. The level of evidence of each variable was assessed and pooled risk ratios (RRs) were calculated.

Results

Twenty‐two articles were included in this review, 17 on computed tomography (CT) and 5 on magnetic resonance imaging (MRI) variables. We found strong evidence for the prognostic value of tumor volume at various cut‐off points (pooled RRs ranging from 2.09 to 3.03). Anterior commissure involvement (pooled RR 2.19), posterior commissure involvement (pooled RR 2.44), subglottic extension (pooled RR 2.25), and arytenoid cartilage extension (pooled RR 2.10) were also strong prognostic factors.

Conclusion

Pretreatment tumor volume and involvement of several subsites are prognostic factors for recurrent laryngeal or hypopharyngeal carcinoma after chemoradiotherapy.

The reporting of observational studies of drug effectiveness and safety: recommendations to extend existing guidelines

INTRODUCTION

The use of observational data to assess drug effectiveness and safety can provide relevant information, much of which may not be feasible to obtain through randomized clinical trials. Because observational studies provide critical drug safety and effectiveness information that influences drug policy and prescribing practices, transparent, consistent, and accurate reporting of these studies is critical.

AREAS COVERED

We provide recommendations to extend existing reporting guidelines, covering the main components of primary research studies (methods, results, discussion).

EXPERT OPINION

Our recommendations include extending drug safety and effectiveness guidelines to include explicit checklist items on: study registration, causal diagrams, rationale for measures of effect, comprehensive assessment of bias, comprehensive data cleaning steps, drug equivalents, subject-level drug data visualization, sex and gender-based analyses and results, patient-oriented outcomes, and patient involvement in research.

Quality of life and non-motor symptoms in Parkinson's disease patients with subthreshold depression

BACKGROUND

The role of subthreshold depression (subD) in Parkinson's Disease (PD) is not clear. The present study aimed to compare the quality of life (QoL) in PD patients with subD vs patients with no depressive disorder (nonD). Factors related to subD were identified.

MATERIAL AND METHODS

PD patients and controls recruited from the COPPADIS cohort were included. SubD was defined as Judd criteria. The 39-item Parkinson's disease Questionnaire (PDQ-39) and the EUROHIS-QOL 8-item index (EUROHIS-QOL8) were used to assess QoL.

RESULTS

The frequency of depressive symptoms was higher in PD patients (n = 694) than in controls (n = 207) (p < 0.0001): major depression, 16.1% vs 7.8%; minor depression, 16.7% vs 7.3%; subD, 17.4% vs 5.8%. Both health-related QoL (PDQ-39; 18.1 ± 12.8 vs 11.6 ± 10; p < 0.0001) and global QoL (EUROHIS-QOL8; 3.7 ± 0.5 vs 4 ± 0.5; p < 0.0001) were significantly worse in subD (n = 120) than nonD (n = 348) PD patients. Non-motor Symptoms Scale (NMSS) total score was higher in subD patients (45.9 ± 32 vs 29.1 ± 25.8;p < 0.0001). Non-motor symptoms burden (NMSS;OR = 1.019;95%CI 1.011-1.028; p < 0.0001), neuropsychiatric symptoms (NPI; OR = 1.091; 95%CI 1.045-1.139; p < 0.0001), impulse control behaviors (QUIP-RS; OR = 1.035; 95%CI 1.007-1063; p = 0.013), quality of sleep (PDSS; OR = 0.991; 95%CI 0.983-0.999; p = 0.042), and fatigue (VAFS-physical; OR = 1.185; 95%CI 1.086-1.293; p < 0.0001; VAFS-mental; OR = 1.164; 95%CI 1.058-1.280; p = 0.0001) were related to subD after adjustment to age, disease duration, daily equivalent levodopa dose, motor status (UPDRS-III), and living alone.

CONCLUSIONS

SubD is a frequent problem in patients with PD and is more prevalent in these patients than in controls. QoL is worse and non-motor symptoms burden is greater in subD PD patients.

Seven Solutions for Neuroprotection in Parkinson's Disease

Parkinson's disease (PD) is a neurodegenerative disorder characterized by loss of dopaminergic neurons in the substantia nigra and accumulation of iron and alpha-synuclein; it follows a characteristic pattern throughout the nervous system. Despite decades of successful preclinical neuroprotective studies, no drug has then shown efficacy in clinical trials. Considering this dilemma, we have reviewed and organized solutions of varying importance that can be exclusive or additive, and we outline approaches to help generate successful development of neuroprotective drugs for PD: (1) select patients in which the targeted mechanism is involved in the pathological process associated with the monitoring of target engagement, (2) combine treatments that target multiple pathways, (3) establish earliest interventions and develop better prodromal biomarkers, (4) adopt rigorous methodology and specific disease-relevant designs for disease-modifying clinical trials, (5) customize drug with better brain biodistribution, (6) prioritize repurposed drugs as a first line approach, and (7) adapt preclinical models to the targeted mechanisms with translational biomarkers to increase their predictive value. © 2020 International Parkinson and Movement Disorder Society.

Predicting Progression in Parkinson's Disease Using Baseline and 1-Year Change Measures

BACKGROUND

Improved prediction of Parkinson's disease (PD) progression is needed to support clinical decision-making and to accelerate research trials.

OBJECTIVES

To examine whether baseline measures and their 1-year change predict longer-term progression in early PD.

METHODS

Parkinson's Progression Markers Initiative study data were used. Participants had disease duration ≤2 years, abnormal dopamine transporter (DAT) imaging, and were untreated with PD medications. Baseline and 1-year change in clinical, cerebrospinal fluid (CSF), and imaging measures were evaluated as candidate predictors of longer-term (up to 5 years) change in Movement Disorders Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) score and DAT specific binding ratios (SBR) using linear mixed-effects models.

RESULTS

Among 413 PD participants, median follow-up was 5 years. Change in MDS-UPDRS from year-2 to last follow-up was associated with disease duration (β= 0.351; 95% CI = 0.146, 0.555), male gender (β= 3.090; 95% CI = 0.310, 5.869), and baseline (β= -0.199; 95% CI = -0.315, -0.082) and 1-year change (β= 0.540; 95% CI = 0.423, 0.658) in MDS-UPDRS; predictors in the model accounted for 17.6% of the variance in outcome. Predictors of percent change in mean SBR from year-2 to last follow-up included baseline rapid eye movement sleep behavior disorder score (β= -0.6229; 95% CI = -1.2910, 0.0452), baseline (β= 7.232; 95% CI = 2.268, 12.195) and 1-year change (β= 45.918; 95% CI = 35.994,55.843) in mean striatum SBR, and 1-year change in autonomic symptom score (β= -0.325;95% CI = -0.695, 0.045); predictors in the model accounted for 44.1% of the variance.

CONCLUSIONS

Baseline clinical, CSF, and imaging measures in early PD predicted change in MDS-UPDRS and dopamine-transporter binding, but the predictive value of the models was low. Adding the short-term change of possible predictors improved the predictive value, especially for modeling change in dopamine-transporter binding.

Effect of Cognitive Disability and Ambulation Status on Functioning in Moderate-to-Advanced Parkinson Disease

Background: As the disease progresses to moderate to advanced stages, people with Parkinson's disease (PwP) are likely to have various degrees of disability due to the motor and non-motor symptoms, such as ambulatory difficulty and cognitive impairment. The objective of this study was to investigate the impact of cognition and ambulation status on the functioning and disability of PwP using the World Health Orgnaization Disability Assessment Schedule 2.0 (WHODAS 2.0).

Materials and Methods: A group of 10,581 PwP with Hoehn and Yahr Staging 3 and above were collected from a database of disability evaluation and functional assessment using the Taiwan Data Bank of Persons with Disability between July 2012 and October 2018. WHODAS 2.0 was administered and all PwP were grouped based on their ambulatory status, which was assessed by 3-m back and forth walk and cognitive ability, assessed by WHODAS 2.0 first domain with cut-off level at 58.

Results: Non-ambulation and cognitive disability contributed independently to disability in all aspects of WHODAS 2.0 survey, including self-care, getting along with others, performing life activities and participation in society. Compared to ambulation status, cognitive disability had a greater negative impact on functioning in all aspects.

Conclusion: Cognitive disability was associated with greater disability in moderate to advanced PwP than non-ambulatory status. The results of this study may indicate that cognition preservation is essential to ameliorate functional impairment and disability in moderate to advanced PwP.

Prognostic factors of Rapid symptoms progression in patients with newly diagnosed parkinson's disease

Tracking symptoms progression in the early stages of Parkinson's disease (PD) is a laborious endeavor as the disease can be expressed with vastly different phenotypes, forcing clinicians to follow a multi-parametric approach in patient evaluation, looking for not only motor symptomatology but also non-motor complications, including cognitive decline, sleep problems and mood disturbances. Being neurodegenerative in nature, PD is expected to inflict a continuous degradation in patients' condition over time. The rate of symptoms progression, however, is found to be even more chaotic than the vastly different phenotypes that can be expressed in the initial stages of PD. In this work, an analysis of baseline PD characteristics is performed using machine learning techniques, to identify prognostic factors for early rapid progression of PD symptoms. Using open data from the Parkinson's Progression Markers Initiative (PPMI) study, an extensive set of baseline patient evaluation outcomes is examined to isolate determinants of rapid progression within the first two and four years of PD. The rate of symptoms progression is estimated by tracking the change of the Movement Disorder Society-Unified Parkinson's Disease Rating Scale (MDS-UPDRS) total score over the corresponding follow-up period. Patients are ranked according to their progression rates and those who expressed the highest rates of MDS-UPDRS total score increase per year of follow-up period are assigned into the rapid progression class, using 5- and 10-quantiles partition. Classification performance against the rapid progression class was evaluated in a per quantile partition analysis scheme and in quantile-independent approach, respectively. The results shown a more accurate patient discrimination with quantile partitioning, however, a much more compact subset of baseline factors is extracted in the latter, making a more suitable for actual interventions in practice. Classification accuracy improved in all cases when using the longer 4-year follow-up period to estimate PD progression, suggesting that a prolonged patient evaluation can provide better outcomes in identifying rapid progression phenotype. Non-motor symptoms are found to be the main determinants of rapid symptoms progression in both follow-up periods, with autonomic dysfunction, mood impairment, anxiety, REM sleep behavior disorders, cognitive decline and memory impairment being alarming signs at baseline evaluation, along with rigidity symptoms, certain laboratory blood test results and genetic mutations.

Pathological Influences on Clinical Heterogeneity in Lewy Body Diseases

PD, PD with dementia, and dementia with Lewy bodies are clinical syndromes characterized by the neuropathological accumulation of alpha-synuclein in the CNS that represent a clinicopathological spectrum known as Lewy body disorders. These clinical entities have marked heterogeneity of motor and nonmotor symptoms with highly variable disease progression. The biological basis for this clinical heterogeneity remains poorly understood. Previous attempts to subtype patients within the spectrum of Lewy body disorders have centered on clinical features, but converging evidence from studies of neuropathology and ante mortem biomarkers, including CSF, neuroimaging, and genetic studies, suggest that Alzheimer's disease beta-amyloid and tau copathology strongly influence clinical heterogeneity and prognosis in Lewy body disorders. Here, we review previous clinical biomarker and autopsy studies of Lewy body disorders and propose that Alzheimer's disease copathology is one of several likely pathological contributors to clinical heterogeneity of Lewy body disorders, and that such pathology can be assessed in vivo. Future work integrating harmonized assessments and genetics in PD, PD with dementia, and dementia with Lewy bodies patients followed to autopsy will be critical to further refine the classification of Lewy body disorders into biologically distinct endophenotypes. This approach will help facilitate clinical trial design for both symptomatic and disease-modifying therapies to target more homogenous subsets of Lewy body disorders patients with similar prognosis and underlying biology. © 2019 International Parkinson and Movement Disorder Society.

Sex differences in Parkinson's disease presentation and progression

INTRODUCTION

Females have a reduced risk of Parkinson's disease (PD). However, it is unclear if sex is a prognostic factor. We aimed to examine differences in presentation, physician- and patient-reported PD outcomes, and progression by sex in a large clinical cohort.

METHODS

This study was a secondary analysis of a cohort of PD patients seen at a tertiary care center. Sociodemographic and clinical characteristics, treatment, care timing, and outcomes were examined by sex. Sex differences in progression of impairment, disability, and health-related quality of life (HRQoL) were tested with five-year piecewise linear mixed-effects models. A mediation analysis assessed drivers of sex differences.

RESULTS

The study included 914 males and 549 females. Females had significantly less social support, more psychological distress, and worse self-reported (but not physician-reported) disability and HRQoL at initial PD care visits, compared to males. Addressing anxiety symptoms may attenuate this difference. PD progression sex differences were minimal.

CONCLUSION

PD progression does not differ by sex, yet patient-reported measures of disease severity are worse in females than males. To attenuate this sex difference in disease experience, psychological distress screening and management, particularly targeting females, should be implemented as part of PD clinical care.

Deep Brain Stimulation for Freezing of Gait in Parkinson's Disease With Early Motor Complications

BACKGROUND

Effects of DBS on freezing of gait and other axial signs in PD patients are unclear.

OBJECTIVE

Secondary analysis to assess whether DBS affects these symptoms within a large randomized controlled trial comparing DBS of the STN combined with best medical treatment and best medical treatment alone in patients with early motor complications (EARLYSTIM-trial).

METHODS

One hundred twenty-four patients were randomized in the stimulation group and 127 patients in the best medical treatment group. Presence of freezing of gait was assessed in the worst condition based on item-14 of the UPDRS-II at baseline and follow-up. The posture, instability, and gait-difficulty subscore of the UPDRS-III, and a gait test including quantification of freezing of gait and number of steps, were performed in both medication-off and medication-on conditions.

RESULTS

Fifty-two percent in both groups had freezing of gait at baseline based on UPDRS-II. This proportion decreased in the stimulation group to 34%, but did not change in the best medical treatment group at 24 months (P = 0.018). The steps needed to complete the gait test decreased in the stimulation group and was superior to the best medical treatment group (P = 0.016). The axial signs improved in the stimulation group compared to the best medical treatment group (P < 0.01) in both medication-off and medication-on conditions.

CONCLUSIONS

Within the first 2 years of DBS, freezing of gait and other axial signs improved in the medication-off condition compared to best medical treatment in these patients. © 2019 International Parkinson and Movement Disorder Society.

Rate of Progression in Activity and Participation Outcomes in Exercisers with Parkinson's Disease: A Five-Year Prospective Longitudinal Study

Background

Rates of progression of motor symptoms and physical performance show declines between 2% and 7% annually in community samples with Parkinson's disease (PD). However, the effects of ongoing exercise behaviors on progression rates have not been considered.

Objective

The primary purpose of this prospective, longitudinal study was to examine the annual rates of progression in activity and participation measures over five years in community-based exercisers with PD.

Methods

A cohort of 55 regular exercisers with idiopathic PD was assessed at baseline and 1, 2, and 5 years. Regular exercise was defined as scores of 4-5 on the Stages for Readiness to Exercise Scale and a self-reported average of at least 60 minutes of exercise/week within six months of each testing session. Unadjusted and adjusted annual progression rates for activity and participation measures were calculated with a standardized equation of change from baseline. A linear mixed model with covariates of age at PD diagnosis and PD subtype was used to determine adjusted change scores.

Results

Annual progression rates for unadjusted and adjusted variables were similar, and none exceeded 1.7% across time points for this group of exercisers with PD. Older age at PD diagnosis significantly contributed to faster progression of walking and balance functions. A nonlinear trajectory of the PD progression was demonstrated across most activity and participation outcomes.

Conclusions

Annual progression rates demonstrated by this sample of exercisers were lower than those previously reported for motor decline in general samples with PD. Assessing activity and participation outcomes longitudinally at interim time points was important for understanding the trajectory of change over time. The lower rates of progression in this study warrant further investigation into the long-term effects of exercise in PD.

Associations Between Cognitive Functions and Physical Frailty in Patients With Parkinson's Disease

Background: Parkinson’s disease (PD) is a neurodegenerative disease manifested by both motor and non-motor dysfunctions and co-existence of cognitive impairment and physical frailty is common. Given that research in this area is limited, a better understanding of associated factors with physical frailty could provide a focused screening method and facilitate early intervention in PD.

Methods: Seventy-six patients with idiopathic PD were recruited and Fried’s criteria of physical frailty were used to group all participants. Comprehensive cognitive tests and clinical characteristics were measured, and univariate and multivariate analysis was performed to explore the relationship between clinical factors or neuropsychological functions.

Results: Twenty-nine patients with PD (38%) exhibited physical frailty. Compared to PD patients without frailty, PD patients with frailty were older in age and demonstrated worse disease severity and poorer cognitive functions, including attention, executive function, memory, speech and language, and visuospatial function (p < 0.05). Further, stepwise logistic regression analysis revealed that disease severity by the Unified Parkinson’s Disease Rating Scale (UPDRS) total score (OR: 1.065; 95% CI: 1.033–1.099) and executive function (OR: 0.724; 95% CI: 0.581–0.877) were independent risk factors for predicting physical frailty (p = 0.003 and 0.002). The best cut-off points are 46 in UPDRS (sensitivity: 62.1%; specificity: 91.5%).

Conclusions: Executive function impairment is an independent risk factor for the development of physical frailty with disease progression. Awareness of such comorbidity might provide a screening tool to facilitate investigation in their underlying etiology and early intervention for frailty prevention.

Wearable technological platform for multidomain diagnostic and exercise interventions in Parkinson's disease

Physical activity and exercise have become a central component of medical management of chronic illness, particular for the elderly who suffer from neurodegenerative disorders that impair their cognition and mobility. This chapter summarizes our recent research showing that a new generation of wearable technology can be adopted as diagnostic and rehabilitation tools for people living with Parkinson's disease. For example, wearable device-enabled 6-min walking test can be automated to eliminate human supervision and many other technical factors that confound the results with conventional testing. With reduced cost and increased test standardization, the technology can be adopted for population-based screening of cardiovascular fitness and gait rehabilitation training efficacy associated with many medical conditions. The Ambulosono platform for multidomain exercise intervention, in particular, has the potential to deliver lasting clinical benefits in slowing PD progression. The platform, through the integration of brisk walking with behavioral shaping strategies such as contingency reinforcement, anticipatory motor control and musical motivational stimulation, creates a home exercise regime that can transform monotonous walking into a pleasurable daily activity and habit.

Social role functioning in Parkinson's disease: A mixed-methods systematic review

OBJECTIVES

Parkinson's disease (PD) is a progressive neurodegenerative disease that often impedes activities of daily living (ADL) and social functioning. Impairment in these areas can alter social roles by interfering with employment status, household management, friendships, and other relationships. Understanding how PD affects social functioning can help clinicians choose management strategies that mitigate these changes.

METHODS

We conducted a mixed-methods systematic review of existing literature on social roles and social functioning in PD. A tailored search strategy in five databases identified 51 full-text reports that fulfilled the inclusion criteria and passed the quality appraisal. We aggregated and analyzed the results from these studies and then created a narrative summary.

RESULTS

Our review demonstrates how PD causes many people to withdraw from their accustomed social roles and experience deficits in corresponding activities. We describe how PD symptoms (eg, tremor, facial masking, and neuropsychiatric symptoms) interfere with relationships (eg, couple, friends, and family) and precipitate earlier departure from the workforce. Additionally, several studies demonstrated that conventional PD therapy has little positive effect on social role functioning.

CONCLUSIONS

Our report presents critical insight into how PD affects social functioning and gives direction to future studies and interventions (eg, couple counseling and recreational activities).

Predicting motor, cognitive & functional impairment in Parkinson's

OBJECTIVE

We recently demonstrated that 998 features derived from a simple 7-minute smartphone test could distinguish between controls, people with Parkinson's and people with idiopathic Rapid Eye Movement sleep behavior disorder, with mean sensitivity/specificity values of 84.6-91.9%. Here, we investigate whether the same smartphone features can be used to predict future clinically relevant outcomes in early Parkinson's.

METHODS

A total of 237 participants with Parkinson's (mean (SD) disease duration 3.5 (2.2) years) in the Oxford Discovery cohort performed smartphone tests in clinic and at home. Each test assessed voice, balance, gait, reaction time, dexterity, rest, and postural tremor. In addition, standard motor, cognitive and functional assessments and questionnaires were administered in clinic. Machine learning algorithms were trained to predict the onset of clinical outcomes provided at the next 18-month follow-up visit using baseline smartphone recordings alone. The accuracy of model predictions was assessed using 10-fold and subject-wise cross validation schemes.

RESULTS

Baseline smartphone tests predicted the new onset of falls, freezing, postural instability, cognitive impairment, and functional impairment at 18 months. For all outcome predictions AUC values were greater than 0.90 for 10-fold cross validation using all smartphone features. Using only the 30 most salient features, AUC values greater than 0.75 were obtained.

INTERPRETATION

We demonstrate the ability to predict key future clinical outcomes using a simple smartphone test. This work has the potential to introduce individualized predictions to routine care, helping to target interventions to those most likely to benefit, with the aim of improving their outcome.

Parkinson's progression prediction using machine learning and serum cytokines

The heterogeneous nature of Parkinson’s disease (PD) symptoms and variability in their progression complicates patient treatment and interpretation of clinical trials. Consequently, there is much interest in developing models that can predict PD progression. In this study we have used serum samples from a clinically well characterized longitudinally followed Michael J Fox Foundation cohort of PD patients with and without the common leucine-rich repeat kinase 2 (LRRK2) G2019S mutation. We have measured 27 inflammatory cytokines and chemokines in serum at baseline and after 1 year to investigate cytokine stability. We then used the baseline measurements in conjunction with machine learning models to predict longitudinal clinical outcomes after 2 years follow up. Using the normalized root mean square error (NRMSE) as a measure of performance, the best prediction models were for the motor symptom severity scales, with NRMSE of 0.1123 for the Hoehn and Yahr scale and 0.1193 for the unified Parkinson’s disease rating scale part three (UPDRS III). For each model, the top variables contributing to prediction were identified, with the chemokines macrophage inflammatory protein one alpha (MIP1α), and monocyte chemoattractant protein one (MCP1) making the biggest peripheral contribution to prediction of Hoehn and Yahr and UPDRS III, respectively. These results provide information on the longitudinal assessment of peripheral inflammatory cytokines in PD and give evidence that peripheral cytokines may have utility for aiding prediction of PD progression using machine learning models.

Destroyed non-dopaminergic pathways in the early stage of Parkinson's disease assessed by posturography

BACKGROUND

The early stage of Parkinson's disease (PD) (Hoehn-Yahr (HY) I-II stages) is characterized by a negative pull test, which clinically excludes postural instability. Previous studies with dynamic posturography detected balance disturbances even at the onset of the disease but the age dependency or prediction of dyskinesia with dynamic posturography are not known.

OBJECTIVE/HYPOTHESIS

We hypothesized that the postural instability evoked by dynamic posturography was part of the early stage of PD. Furthermore, we studied how we can provoke dyskinesia.

METHODS

Postural instability with static and dynamic posturography (passing balls with different weights around the body) was studied in 45 patients with PD in their HY I, II stages. They were compared with 35 age-matched healthy controls. Eighteen patients with dyskinesia were involved in the study. Fourteen patients were followed for two years.

RESULTS

The pathway and velocity of the movement assessed by static and the dynamic posturography were significantly higher in the group >65 years than that of age-matched healthy controls, while the group ≤65 years showed a significant increment only in the antero-posterior sway during dynamic posturography. The imbalance of patients with dyskinesia was significantly (p < 0.05) provoked by dynamic posturography compared to patients with PD without dyskinesia. The results were independent of age.

CONCLUSION

Postural instability is part of the early symptoms of PD. Non-dopaminergic pathways may be involved in the early stage of PD.

Use of Magnetic Resonance Imaging and Artificial Intelligence in Studies of Diagnosis of Parkinson's Disease

Parkinson's disease (PD) is a common neurodegenerative disorder. It has a delitescent onset and a slow progress. The clinical manifestations of PD in patients are highly heterogeneous. Thus, PD diagnosis process is complex and mainly depends on the professional knowledge and experience of the physician. Magnetic resonance imaging (MRI) could detect the small changes in the brain of PD patients, and quantitative analysis of brain MRI may improve the clinical diagnosis efficiency. However, due to the complexity of clinical courses in PD and the high dimensionality in multimodal MRI data, traditional mathematical analysis could not effectively extract the huge information in them. Up to now, the accuracy of PD diagnosis in large sample size is still unsatisfying. As artificial intelligence (AI) is becoming more mature, varieties of statistical models and machine learning (ML) algorithms have been used for quantitative imaging data analysis to explore a diagnostic result. This review aims to state an overview of existing research recently that used statistical ML/AI methods to perform quantitative analysis of MR image data for the study of PD diagnosis. First we review the recent research in three subareas: diagnosis, differential diagnosis, and subtyping of PD. Then we described the overall workflow from MR image to classification result. Finally, we summarized a critical assessment of the current research and provide some recommendations for likely future research developments and trends.

CSF and blood biomarkers for Parkinson's disease

In the management of Parkinson's disease, reliable diagnostic and prognostic biomarkers are urgently needed. The diagnosis of Parkinson's disease mostly relies on clinical symptoms, which hampers the detection of the earliest phases of the disease-the time at which treatment with forthcoming disease-modifying drugs could have the greatest therapeutic effect. Reliable prognostic markers could help in predicting the response to treatments. Evidence suggests potential diagnostic and prognostic value of CSF and blood biomarkers closely reflecting the pathophysiology of Parkinson's disease, such as α-synuclein species, lysosomal enzymes, markers of amyloid and tau pathology, and neurofilament light chain. A combination of multiple CSF biomarkers has emerged as an accurate diagnostic and prognostic model. With respect to early diagnosis, the measurement of CSF α-synuclein aggregates is providing encouraging preliminary results. Blood α-synuclein species and neurofilament light chain are also under investigation because they would provide a non-invasive tool, both for early and differential diagnosis of Parkinson's disease versus atypical parkinsonian disorders, and for disease monitoring. In view of adopting CSF and blood biomarkers for improving Parkinson's disease diagnostic and prognostic accuracy, further validation in large independent cohorts is needed.

The Diagnostic Scope of Sensor-Based Gait Analysis in Atypical Parkinsonism: Further Observations

Background: Differentiating idiopathic Parkinson's disease (IPD) from atypical Parkinsonian disorders (APD) is challenging, especially in early disease stages. Postural instability and gait difficulty (PIGD) are substantial motor impairments of IPD and APD. Clinical evidence implies that patients with APD have larger PIGD impairment than IPD patients. Sensor-based gait analysis as instrumented bedside test revealed more gait deficits in APD compared to IPD. However, the diagnostic value of instrumented bedside tests compared to clinical assessments in differentiating APD from IPD patients have not been evaluated so far.

Objective: The objectives were (a) to evaluate whether sensor-based gait parameters provide additional information to validated clinical scores in differentiating APD from matched IPD patients, and (b) to investigate if objective, instrumented gait assessments have comparable discriminative power to clinical scores.

Methods: In a previous study we have recorded instrumented gait parameters in patients with APD (Multiple System Atrophy and Progressive Supranuclear Palsy). Here, we compared gait parameters to those of retrospectively pairwise disease duration-, age-, and gender-matched IPD patients in order to address this new research questions. To this aim, the PIGD score was calculated as sum of the MDS-UPDRS-3-items “gait,” “postural stability,” “arising from chair,” and “posture.” Gait characteristics were evaluated in standardized gait tests using an instrumented, sensor-based gait analysis system. Machine learning algorithms were used to extract spatio-temporal gait parameters. Receiver Operating Characteristic analysis was performed in order to detect the discriminative power of the instrumented vs. the clinical bedside tests in differentiating IPD from APD.

Results: Sensor-based stride length, gait velocity, toe off angle, and parameters representing gait variability significantly differed between IPD and APD groups. ROC analysis revealed a high Area Under the Curve (AUC) for PIGD score (0.919), and UPDRS-3 (0.848). Particularly, the objective parameters stance time variability (0.841), swing time variability (0.834), stride time variability (0.821), and stride length variability (0.804) reached high AUC's as well.

Conclusions: PIGD symptoms showed high discriminative power in differentiating IPD from APD supporting gait disorders as substantial diagnostic target. Sensor-based gait variability parameters provide metric, objective added value, and serve as complementary outcomes supporting clinical diagnostics and long-term home-monitoring concepts.

Responsiveness to Change of the Montreal Cognitive Assessment, Mini-Mental State Examination, and SCOPA-Cog in Non-Demented Patients with Parkinson's Disease

BACKGROUND

Clinical monitoring of patients with Parkinson's disease (PD) for cognitive decline is an important element of care. The Montreal Cognitive Assessment (MoCA) has been proposed to be a sensitive tool for assessing cognitive impairment in PD. The aim of our study was to compare the responsiveness of the MoCA to decline in cognition to the responsiveness of the Mini Mental State Examination (MMSE) and the Scales for Outcomes of Parkinson's disease-cognition (SCOPA-Cog).

METHODS

PD patients without dementia were enrolled at 6 North American movement disorders centers between 2008 and 2011. Participants received annual evaluations including the MoCA, MMSE, and SCOPA-Cog followed by formal neuropsychological testing. The gold standard for change in cognition was defined as the change on the neuropsychological test scores over the annual assessments. The Reliable Change Method was used to provide an estimate of the probability that a given difference score would be obtained by chance. The sensitivity of the MoCA, MMSE, and SCOPA-Cog to change was quantified using receiver operating characteristics (ROC) curves.

RESULTS

One hundred seventeen patients were included in the analysis. Participants were followed at mean intervals of 11 ± 2 months for a median of 2 (maximum 5) visits. According to the reliable change index, 56 intervals of cognitive testing showed a decline in global cognition. ROC analysis of change in MoCA, MMSE, and SCOPA-Cog global scores compared to gold standard testing found an area under the curve (AUC) of 0.55 (95% CI 0.48-0.62), 0.56 (0.48-0.63), and 0.63 (0.55-0.70) respectively. There were no significant differences in the AUCs across the tests. The sensitivity of the MoCA, MMSE, and SCOPA-Cog to change at various thresholds for decline in scores reached a maximum of 71% for a cut-off of 1 point change on the SCOPA-Cog.

CONCLUSION

Using neuropsychological testing as a gold standard comparator, the performance of the MoCA, MMSE, and SCOPA-Cog for detecting decline in non-demented PD patients over a 1-year interval is poor. This has implications for clinical practice; stable scores may not be taken as reassurance of the absence of cognitive decline.

Brain imaging of locomotion in neurological conditions

Impaired locomotion is a frequent and major source of disability in patients with neurological conditions. Different neuroimaging methods have been used to understand the brain substrates of locomotion in various neurological diseases (mainly in Parkinson's disease) during actual walking, and while resting (using mental imagery of gait, or brain-behavior correlation analyses). These studies, using structural (i.e., MRI) or functional (i.e., functional MRI or functional near infra-red spectroscopy) brain imaging, electrophysiology (i.e., EEG), non-invasive brain stimulation (i.e., transcranial magnetic stimulation, or transcranial direct current stimulation) or molecular imaging methods (i.e., PET, or SPECT) reveal extended brain networks involving both grey and white matters in key cortical (i.e., prefrontal cortex) and subcortical (basal ganglia and cerebellum) regions associated with locomotion. However, the specific roles of the various pathophysiological mechanisms encountered in each neurological condition on the phenotype of gait disorders still remains unclear. After reviewing the results of individual brain imaging techniques across the common neurological conditions, such as Parkinson's disease, dementia, stroke, or multiple sclerosis, we will discuss how the development of new imaging techniques and computational analyses that integrate multivariate correlations in "large enough datasets" might help to understand how individual pathophysiological mechanisms express clinically as an abnormal gait. Finally, we will explore how these new analytic methods could drive our rehabilitative strategies.

Beyond Dopamine: GABA, Glutamate, and the Axial Symptoms of Parkinson Disease

Introduction: The axial symptoms of Parkinson disease (PD) include difficulties with balance, posture, speech, swallowing, and locomotion with freezing of gait, as well as axial rigidity. These axial symptoms impact negatively on quality of life for many patients, yet remain poorly understood. Dopaminergic treatments typically have little effect on the axial symptoms of PD, suggesting that disruptions in other neurotransmitter systems beyond the dopamine system may underlie these symptoms. The purpose of the present study was to examine the relationship between the axial symptoms of PD and GABA and glutamate levels quantified with magnetic resonance spectroscopy.

Methods: The participant group included 20 patients with PD and 17 healthy control participants. Water-scaled GABA and Glx (glutamate + glutamine) concentrations were derived from GABA-edited MEGA-PRESS spectra acquired from the left basal ganglia and prefrontal cortex, and additional water-scaled Glx concentrations were acquired from standard PRESS spectra acquired from the pons. Spectra were analyzed with LCModel. The axial symptoms of PD were evaluated from subscales of the Unified Parkinson's Disease rating scale (MDS-UPDRS).

Results: PD patients demonstrated significantly higher GABA levels in the basal ganglia, which correlated with the degree of gait disturbance. Basal ganglia Glx levels and prefrontal GABA and Glx levels did not differ significantly between patient and control groups, but within the PD group prefrontal Glx levels correlated negatively with difficulties turning in bed. Results from an exploratory subgroup analysis indicate that the associations between GABA, Glx, and axial symptoms scores are typically more prominent in akinetic-rigid patients than in tremor-dominant patients.

Conclusion: Alterations in GABAergic and glutamatergic neurotransmission may contribute to some of the axial symptoms of PD.