Beta-triggered adaptive deep brain stimulation during reaching movement in Parkinson's disease.

Subthalamic nucleus (STN) beta-triggered adaptive deep brain stimulation (ADBS) has been shown to provide clinical improvement comparable to conventional continuous DBS (CDBS) with less energy delivered to the brain and less stimulation induced side effects. However, several questions remain unanswered. First, there is a normal physiological reduction of STN beta band power just prior to and during voluntary movement. ADBS systems will therefore reduce or cease stimulation during movement in people with Parkinson's disease and could therefore compromise motor performance compared to CDBS. Second, beta power was smoothed and estimated over a time period of 400 ms in most previous ADBS studies, but a shorter smoothing period could have the advantage of being more sensitive to changes in beta power, which could enhance motor performance. In this study, we addressed these two questions by evaluating the effectiveness of STN beta-triggered ADBS using a standard 400 ms and a shorter 200 ms smoothing window during reaching movements. Results from 13 people with Parkinson's disease showed that reducing the smoothing window for quantifying beta did lead to shortened beta burst durations by increasing the number of beta bursts shorter than 200 ms and more frequent switching on/off of the stimulator but had no behavioural effects. Both ADBS and CDBS improved motor performance to an equivalent extent compared to no DBS. Secondary analysis revealed that there were independent effects of a decrease in beta power and an increase in gamma power in predicting faster movement speed, while a decrease in beta event related desynchronization (ERD) predicted quicker movement initiation. CDBS suppressed both beta and gamma more than ADBS, whereas beta ERD was reduced to a similar level during CDBS and ADBS compared with no DBS, which together explained the achieved similar performance improvement in reaching movements during CDBS and ADBS. In addition, ADBS significantly improved tremor compared with no DBS but was not as effective as CDBS. These results suggest that STN beta-triggered ADBS is effective in improving motor performance during reaching movements in people with Parkinson's disease, and that shortening of the smoothing window does not result in any additional behavioural benefit. When developing ADBS systems for Parkinson's disease, it might not be necessary to track very fast beta dynamics; combining beta, gamma, and information from motor decoding might be more beneficial with additional biomarkers needed for optimal treatment of tremor.

The aperiodic exponent of subthalamic field potentials reflects excitation/inhibition balance in Parkinsonism.

Periodic features of neural time-series data, such as local field potentials (LFPs), are often quantified using power spectra. While the aperiodic exponent of spectra is typically disregarded, it is nevertheless modulated in a physiologically relevant manner and was recently hypothesised to reflect excitation/inhibition (E/I) balance in neuronal populations. Here, we used a cross-species in vivo electrophysiological approach to test the E/I hypothesis in the context of experimental and idiopathic Parkinsonism. We demonstrate in dopamine-depleted rats that aperiodic exponents and power at 30-100 Hz in subthalamic nucleus (STN) LFPs reflect defined changes in basal ganglia network activity; higher aperiodic exponents tally with lower levels of STN neuron firing and a balance tipped towards inhibition. Using STN-LFPs recorded from awake Parkinson's patients, we show that higher exponents accompany dopaminergic medication and deep brain stimulation (DBS) of STN, consistent with untreated Parkinson's manifesting as reduced inhibition and hyperactivity of STN. These results suggest that the aperiodic exponent of STN-LFPs in Parkinsonism reflects E/I balance and might be a candidate biomarker for adaptive DBS.

Computer vision quantification of whole-body Parkinsonian bradykinesia using a large multi-site population.

Parkinson's disease (PD) is a common neurological disorder, with bradykinesia being one of its cardinal features. Objective quantification of bradykinesia using computer vision has the potential to standardise decision-making, for patient treatment and clinical trials, while facilitating remote assessment. We utilised a dataset of part-3 MDS-UPDRS motor assessments, collected at four independent clinical and one research sites on two continents, to build computer-vision-based models capable of inferring the correct severity rating robustly and consistently across all identifiable subgroups of patients. These results contrast with previous work limited by small sample sizes and small numbers of sites. Our bradykinesia estimation corresponded well with clinician ratings (interclass correlation 0.74). This agreement was consistent across four clinical sites. This result demonstrates how such technology can be successfully deployed into existing clinical workflows, with consumer-grade smartphone or tablet devices, adding minimal equipment cost and time.

Evoked resonant neural activity in subthalamic local field potentials reflects basal ganglia network dynamics.

Evoked resonant neural activity (ERNA) is induced by subthalamic deep brain stimulation (DBS) and was recently suggested as a marker of lead placement and contact selection in Parkinson's disease. Yet, its underlying mechanisms and how it is modulated by stimulation parameters are unclear. Here, we recorded local field potentials from 27 Parkinson's disease patients, while leads were externalised to scrutinise the ERNA. First, we show that ERNA in the time series waveform and spectrogram likely represent the same activity, which was contested before. Second, our results show that the ERNA has fast and slow dynamics during stimulation, consistent with the synaptic failure hypothesis. Third, we show that ERNA parameters are modulated by different DBS frequencies, intensities, medication states and stimulation modes (continuous DBS vs. adaptive DBS). These results suggest the ERNA might prove useful as a predictor of the best DBS frequency and lowest effective intensity in addition to contact selection. Changes with levodopa and DBS mode suggest that the ERNA may indicate the state of the cortico-basal ganglia circuit making it a putative biomarker to track clinical state in adaptive DBS.

Subthalamic Nucleus Stimulation-Induced Local Field Potential Changes in Dystonia.

BACKGROUND: Subthalamic nucleus (STN) stimulation is an effective treatment for Parkinson's disease and induced local field potential (LFP) changes that have been linked with clinical improvement. STN stimulation has also been used in dystonia although the internal globus pallidus is the standard target where theta power has been suggested as a physiomarker for adaptive stimulation. OBJECTIVE: We aimed to explore if enhanced theta power was also present in STN and if stimulation-induced spectral changes that were previously reported for Parkinson's disease would occur in dystonia. METHODS: We recorded LFPs from 7 patients (12 hemispheres) with isolated craniocervical dystonia whose electrodes were placed such that inferior, middle, and superior contacts covered STN, zona incerta, and thalamus. RESULTS: We did not observe prominent theta power in STN at rest. STN stimulation induced similar spectral changes in dystonia as in Parkinson's disease, such as broadband power suppression, evoked resonant neural activity (ERNA), finely-tuned gamma oscillations, and an increase in aperiodic exponents in STN-LFPs. Both power suppression and ERNA localize to STN. Based on this, single-pulse STN stimulation elicits evoked neural activities with largest amplitudes in STN, which are relayed to the zona incerta and thalamus with changing characteristics as the distance from STN increases. CONCLUSIONS: Our results show that STN stimulation-induced spectral changes are a nondisease-specific response to high-frequency stimulation, which can serve as placement markers for STN. This broadens the scope of STN stimulation and makes it an option for other disorders with excessive oscillatory peaks in STN. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Genetics of validated Parkinson's disease subtypes in the Oxford Discovery and Tracking Parkinson's cohorts.

OBJECTIVES: To explore the genetics of four Parkinson's disease (PD) subtypes that have been previously described in two large cohorts of patients with recently diagnosed PD. These subtypes came from a data-driven cluster analysis of phenotypic variables. METHODS: We looked at the frequency of genetic mutations in glucocerebrosidase (GBA) and leucine-rich repeat kinase 2 against our subtypes. Then we calculated Genetic Risk Scores (GRS) for PD, multiple system atrophy, progressive supranuclear palsy, Lewy body dementia, and Alzheimer's disease. These GRSs were regressed against the probability of belonging to a subtype in the two independent cohorts and we calculated q-values as an adjustment for multiple testing across four subtypes. We also carried out a Genome-Wide Association Study (GWAS) of belonging to a subtype. RESULTS: A severe disease subtype had the highest rates of patients carrying GBA mutations while the mild disease subtype had the lowest rates (p=0.009). Using the GRS, we found a severe disease subtype had a reduced genetic risk of PD (p=0.004 and q=0.015). In our GWAS no individual variants met genome wide significance (<5×10e-8) although four variants require further follow-up, meeting a threshold of <1×10e-6. CONCLUSIONS: We have found that four previously defined PD subtypes have different genetic determinants which will help to inform future studies looking at underlying disease mechanisms and pathogenesis in these different subtypes of disease.

A Clinically Interpretable Computer-Vision Based Method for Quantifying Gait in Parkinson's Disease.

Gait is a core motor function and is impaired in numerous neurological diseases, including Parkinson's disease (PD). Treatment changes in PD are frequently driven by gait assessments in the clinic, commonly rated as part of the Movement Disorder Society (MDS) Unified PD Rating Scale (UPDRS) assessment (item 3.10). We proposed and evaluated a novel approach for estimating severity of gait impairment in Parkinson's disease using a computer vision-based methodology. The system we developed can be used to obtain an estimate for a rating to catch potential errors, or to gain an initial rating in the absence of a trained clinician-for example, during remote home assessments. Videos (n=729) were collected as part of routine MDS-UPDRS gait assessments of Parkinson's patients, and a deep learning library was used to extract body key-point coordinates for each frame. Data were recorded at five clinical sites using commercially available mobile phones or tablets, and had an associated severity rating from a trained clinician. Six features were calculated from time-series signals of the extracted key-points. These features characterized key aspects of the movement including speed (step frequency, estimated using a novel Gamma-Poisson Bayesian model), arm swing, postural control and smoothness (or roughness) of movement. An ordinal random forest classification model (with one class for each of the possible ratings) was trained and evaluated using 10-fold cross validation. Step frequency point estimates from the Bayesian model were highly correlated with manually labelled step frequencies of 606 video clips showing patients walking towards or away from the camera (Pearson's r=0.80, p<0.001). Our classifier achieved a balanced accuracy of 50% (chance = 25%). Estimated UPDRS ratings were within one of the clinicians' ratings in 95% of cases. There was a significant correlation between clinician labels and model estimates (Spearman's ρ=0.52, p<0.001). We show how the interpretability of the feature values could be used by clinicians to support their decision-making and provide insight into the model's objective UPDRS rating estimation. The severity of gait impairment in Parkinson's disease can be estimated using a single patient video, recorded using a consumer mobile device and within standard clinical settings; i.e., videos were recorded in various hospital hallways and offices rather than gait laboratories. This approach can support clinicians during routine assessments by providing an objective rating (or second opinion), and has the potential to be used for remote home assessments, which would allow for more frequent monitoring.

Per-oral image guided gastrojejunostomy insertion for levodopa-carbidopa intestinal gel in Parkinson's disease is safe and may be advantageous.

BACKGROUND: Procedural aspects and complications of gastrojejunostomy insertion are important considerations in the use of levodopa-carbidopa intestinal gel therapy (LCIG) and may limit uptake. We describe our experience of using per-oral image guided gastrojejunostomy (PIG-J) which avoids the need for endoscopy and routine sedation in percutaneous endoscopic gastrojejunostomy (PEG-J) and allows more secure tube placement than radiologically inserted gastrojejunostomy techniques. METHODS: We describe a case series of 32 patients undergoing PIG-J insertion for LCIG therapy in a single centre. Under local anaesthetic, a fluoroscopy-guided gastric puncture allows access for the guidewire which is then used to pull through the gastrostomy tube allowing for secure fixation, followed by placement of the gastrojejunal extension. RESULTS: Between December 2015 to April 2020, 32/34 patients referred for PIG-J underwent this procedure successfully, 2 cases unsuccessful due to technical considerations. One patient developed delirium following successful implantation. Ten patients (31%) required a replacement tube due to blockage or displacement within the first 12 months of placement, including 2 patients who needed more than one replacement. Minor complications occurred in 10 other patients (31%), including infection (9 patients); a small haematoma not requiring intervention who later developed an infection (1 patient); and peri-stomal acid leakage (1 patient). CONCLUSION: In summary, PIG-J insertion is safe with a similar complication rate to traditional PEG-J, well tolerated and effective for use in LCIG administration. This may widen access to LCIG for PD patients who may not be suitable or unable to tolerate PEG-J.

Neurophysiological Correlates of Trait Impulsivity in Parkinson's Disease.

BACKGROUND: Impulsivity is common in people with Parkinson's disease (PD), with many developing impulsive compulsive behavior disorders (ICB). Its pathophysiological basis remains unclear. OBJECTIVES: We aimed to investigate local field potential (LFP) markers of trait impulsivity in PD and their relationship to ICB. METHODS: We recorded subthalamic nucleus (STN) LFPs in 23 PD patients undergoing deep brain stimulation implantation. Presence and severity of ICB were assessed by clinical interview and the Questionnaire for Impulsive-Compulsive Disorders in PD-Rating Scale (QUIP-RS), whereas trait impulsivity was estimated with the Barratt Impulsivity Scale (BIS-11). Recordings were obtained during the off dopaminergic states and the power spectrum of the subthalamic activity was analyzed using Fourier transform-based techniques. Assessment of each electrode contact localization was done to determine the topography of the oscillatory activity recorded. RESULTS: Patients with (n = 6) and without (n = 17) ICB had similar LFP spectra. A multiple regression model including QUIP-RS, BIS-11, and Unified PD Rating Scale-III scores as regressors showed a significant positive correlation between 8-13 Hz power and BIS-11 score. The correlation was mainly driven by the motor factor of the BIS-11, and was irrespective of the presence or absence of active ICB. Electrode contact pairs with the highest α power, which also correlated most strongly with BIS-11, tended to be more ventral than contact pairs with the highest beta power, which localize to the dorsolateral motor STN. CONCLUSIONS: Our data suggest a link between α power and trait impulsivity in PD, irrespective of the presence and severity of ICB. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Closed-Loop Deep Brain Stimulation for Essential Tremor Based on Thalamic Local Field Potentials.

BACKGROUND: High-frequency thalamic stimulation is an effective therapy for essential tremor, which mainly affects voluntary movements and/or sustained postures. However, continuous stimulation may deliver unnecessary current to the brain due to the intermittent nature of the tremor. OBJECTIVE: We proposed to close the loop of thalamic stimulation by detecting tremor-provoking movement states using local field potentials recorded from the same electrodes implanted for stimulation, so that the stimulation is only delivered when necessary. METHODS: Eight patients with essential tremor participated in this study. Patient-specific support vector machine classifiers were first trained using data recorded while the patient performed tremor-provoking movements. Then, the trained models were applied in real-time to detect these movements and triggered the delivery of stimulation. RESULTS: Using the proposed method, stimulation was switched on for 80.37 ± 7.06% of the time when tremor-evoking movements were present. In comparison, the stimulation was switched on for 12.71 ± 7.06% of the time when the patients were at rest and tremor-free. Compared with continuous stimulation, a similar amount of tremor suppression was achieved while only delivering 36.62 ± 13.49% of the energy used in continuous stimulation. CONCLUSIONS: The results suggest that responsive thalamic stimulation for essential tremor based on tremor-provoking movement detection can be achieved without any requirement for external sensors or additional electrocorticography strips. Further research is required to investigate whether the decoding model is stable across time and generalizable to the variety of activities patients may engage with in everyday life. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Postoperative Externalization of Deep Brain Stimulation Leads Does Not Increase Infection Risk.

OBJECTIVES: Externalization of deep brain stimulation (DBS) leads is performed to allow electrophysiological recording from implanted electrodes as well as assessment of clinical response to trial stimulation before implantable pulse generator (IPG) insertion. Hypothetically, lead externalization provides a route for inoculation and subsequent infection of hardware, though this has not been established definitively in the literature. We sought to determine if lead externalization affects the risk of infection in DBS surgery. MATERIALS AND METHODS: We present our center's experience of lead externalization and surgical site infection (SSI) in DBS surgery for movement disorders. Patients were divided into two cohorts: one in which leads were not externalized and IPGs were implanted at the time of electrode insertion, and one in which leads were externalized for six days while patients underwent electrophysiological recording from DBS electrodes for research. We compare baseline characteristics of these two cohorts and their SSI rates. RESULTS: Infective complications were experienced by 3/82 (3.7%) patients overall with one (1.2%) requiring complete hardware removal. These occurred in 1/36 (2.7%) in the externalized cohort and 2/46 (4.3%) in the nonexternalized cohort. The incidence of infection between the two cohorts was not significantly different (p = 1, two-tailed Fisher's exact test). This lack of significant difference persisted when baseline variation between the cohorts in age, hardware manufacturer, and indication for DBS were corrected by excluding patients implanted for dystonia, none of whom underwent externalization. We present and discuss in detail each of the three cases of infection. CONCLUSIONS: Our data suggest that externalization of leads does not increase the risk of infective complications in DBS surgery. Lead externalization is a safe procedure which can provide a substrate for unique neurophysiological studies to advance knowledge and therapy of disorders treated with DBS.

Closed-loop DBS triggered by real-time movement and tremor decoding based on thalamic LFPs for essential tremor.

High frequency Deep Brain Stimulation (DBS) targeting the motor thalamus is an effective therapy for essential tremor (ET). However, since tremor mainly affects periods of voluntary movements and sustained postures in ET, conventional continuous stimulation may deliver unnecessary current to the brain. Here we tried to decode movement states based on local field potentials (LFPs) recorded from motor thalamus and zona incerta in real-time to trigger the switching on and off of DBS in three patients with ET. Patient-specific models were first identified using thalamic LFPs recorded while the patient performed movements that tended to trigger tremor in everyday life. During the real-time test, LFPs were continuously recorded to decode movements and tremor, and the detection triggered stimulation. Results show that voluntary movements can be detected with a mean sensitivity ranging from 76.8% to 88.6% and a false positive rate ranging from 16.0% to 23.1% Postural tremor was detected with similar accuracy. The closed-loop DBS triggered by tremor detection suppressed intention tremor by 90.5% with a false positive rate of 20.3%.Clinical Relevance- This is the first study on closed-loop DBS triggered by real-time movement and tremor decoding based solely on thalamic LFPs. The results suggest that responsive DBS based on movement and tremor detection can be achieved without any requirement for external sensors or additional electrocorticography strips.

Dopamine and reward hypersensitivity in Parkinson's disease with impulse control disorder.

Impulse control disorders in Parkinson's disease are common neuropsychiatric complications associated with dopamine replacement therapy. Some patients treated with dopamine agonists develop pathological behaviours, such as gambling, compulsive eating, shopping, or disinhibited sexual behaviours, which can have a severe impact on their lives and that of their families. In this study we investigated whether hypersensitivity to reward might contribute to these pathological behaviours and how this is influenced by dopaminergic medication. We asked participants to shift their gaze to a visual target as quickly as possible, in order to obtain reward. Critically, the reward incentive on offer varied over trials. Motivational effects were indexed by pupillometry and saccadic velocity, and patients were tested ON and OFF dopaminergic medication, allowing us to measure the effect of dopaminergic medication changes on reward sensitivity. Twenty-three Parkinson's disease patients with a history of impulse control disorders were compared to 26 patients without such behaviours, and 31 elderly healthy controls. Intriguingly, behavioural apathy was reported alongside impulsivity in the majority of patients with impulse control disorders. Individuals with impulse control disorders also exhibited heightened sensitivity to exogenous monetary rewards cues both ON and OFF (overnight withdrawal) dopamine medication, as indexed by pupillary dilation in anticipation of reward. Being OFF dopaminergic medication overnight did not modulate pupillary reward sensitivity in impulse control disorder patients, whereas in control patients reward sensitivity was significantly reduced when OFF dopamine. These effects were independent of cognitive impairment or total levodopa equivalent dose. Although dopamine agonist dose did modulate pupillary responses to reward, the pattern of results was replicated even when patients with impulse control disorders on dopamine agonists were excluded from the analysis. The findings suggest that hypersensitivity to rewards might be a contributing factor to the development of impulse control disorders in Parkinson's disease. However, there was no difference in reward sensitivity between patient groups when ON dopamine medication, suggesting that impulse control disorders may not emerge simply because of a direct effect of dopaminergic drug level on reward sensitivity. The pupillary reward sensitivity measure described here provides a means to differentiate, using a physiological measure, Parkinson's disease patients with impulse control disorder from those who do not experience such symptoms. Moreover, follow-up of control patients indicated that increased pupillary modulation by reward can be predictive of the risk of future emergence of impulse control disorders and may thereby provide the potential for early identification of patients who are more likely to develop these symptoms.

Spectrum of impulse control behaviours in Parkinson's disease: pathophysiology and management.

Impulse control behaviours (ICBs) are a range of behaviours linked by their reward-based, repetitive natures. They can be precipitated in Parkinson's disease (PD) by dopamine replacement therapy, often with detrimental consequences for patients and caregivers. While now a well-recognised non-motor feature of treated PD, much remains unknown about the influence of risk factors, pathophysiological mechanisms, vulnerability factors for specific types of behaviour and the optimal management strategies. Imaging studies have identified structural and functional changes in striatal and prefrontal brain regions, among others. Gene association studies indicate a role for genetic predisposition to PD-ICB. Clinical observational studies have identified potential modifiable and non-modifiable risk factors. Psychological studies shed light on the neurocognitive domains implicated in PD-ICBs and identify psychosocial determinants that may perpetuate the cycle of impulsive and harm-avoidance behaviours. Based on these results, a range of pharmacological and non-pharmacological management strategies have been trialled in PD-ICBs with varying success. The purpose of this review is to update clinicians on the evidence around the pathophysiology of PD-ICB. We aim to translate our findings into an interpretable biopsychosocial model that can be applied to the clinical assessment and management of individual cases of PD-ICB.

Continuous Real-World Gait Monitoring in Idiopathic REM Sleep Behavior Disorder.

BACKGROUND: Patients with REM sleep behavior disorder (RBD) have a high risk of developing PD, and thus can be used to study prodromal biomarkers. RBD has been associated with changes in gait; quantifying these changes using wearable technology is promising; however, most data are obtained in clinical settings precluding pragmatic application. OBJECTIVE: We aimed to investigate if wearable-based, real-world gait monitoring can detect early gait changes and discriminate individuals with RBD from controls, and explore relationships between real-world gait and clinical characteristics. METHODS: 63 individuals with RBD (66±10 years) and 34 controls recruited in the Oxford Parkinson's Disease Centre Discovery Study were assessed. Data were collected using a wearable device positioned on the lower back for 7 days. Real-world gait was quantified in terms of its Macrostructure (volume, pattern and variability (S2)) and Microstructure (14 characteristics). The value of Macro and Micro gait in discriminating RBD from controls was explored using ANCOVA and ROC analysis, and correlation analysis was performed between gait and clinical characteristics. RESULTS: Significant differences were found in discrete Micro characteristics in RBD with reduced gait velocity, variability and rhythm (p≤0.023). These characteristics significantly discriminated RBD (AUC≥0.620), with swing time as the single strongest discriminator (AUC=0.652). Longer walking bouts discriminated best between the groups for Macro and Micro outcomes (p≤0.036). CONCLUSIONS: Our results suggest that real-world gait monitoring may have utility as "risk" clinical marker in RBD participants. Real-world gait assessment is low-cost and could serve as a pragmatic screening tool to identify gait impairment in RBD.

Blood biomarkers with Parkinson's disease clusters and prognosis: The oxford discovery cohort.

BACKGROUND: Predicting prognosis in Parkinson's disease (PD) has important implications for individual prognostication and clinical trials design and targeting novel treatments. Blood biomarkers could help in this endeavor. METHODS: We identified 4 blood biomarkers that might predict prognosis: apolipoprotein A1, C-reactive protein, uric acid and vitamin D. These biomarkers were measured in baseline serum from 624 Parkinson's disease subjects (median disease duration, 1.0 years; interquartile range, 0.5-2.0) from the Oxford Discovery prospective cohort. We compared these biomarkers against PD subtypes derived from clinical features in the baseline cohort using data-driven approaches. We used multilevel models with MDS-UPDRS parts I, II, and III and Montreal Cognitive Assessment as outcomes to test whether the biomarkers predicted subsequent progression in motor and nonmotor domains. We compared the biomarkers against age of PD onset and age at diagnosis. The q value, a false-discovery rate alternative to P values, was calculated as an adjustment for multiple comparisons. RESULTS: Apolipoprotein A1 and C-reactive protein levels differed across our PD subtypes, with severe motor disease phenotype, poor psychological well-being, and poor sleep subtype having reduced apolipoprotein A1 and higher C-reactive protein levels. Reduced apolipoprotein A1, higher C-reactive protein, and reduced vitamin D were associated with worse baseline activities of daily living (MDS-UPDRS II). CONCLUSION: Baseline clinical subtyping identified a pro-inflammatory biomarker profile significantly associated with a severe motor/nonmotor disease phenotype, lending biological validity to subtyping approaches. No blood biomarker predicted motor or nonmotor prognosis. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

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.

Impulse control disorders in Parkinson disease and RBD: A longitudinal study of severity.

OBJECTIVE: To describe the prevalence, natural history, and risk factors for impulse control behaviors (ICBs) among people with Parkinson disease (PD), those with REM sleep behavior disorder (RBD), and controls. METHODS: Participants with early PD (within 3.5 years of diagnosis), those with RBD, and controls were clinically phenotyped and screened for ICBs longitudinally (with the Questionnaire for Impulsivity in Parkinson's Disease). ICB-positive individuals were invited for a semistructured interview, repeated 1 year later. The severity of the ICB was assessed with the Parkinson's Impulse Control Scale. Multiple imputation and regression models were used to estimate ICB prevalence and associations. RESULTS: Data from 921 cases of PD at baseline, 768 cases at 18 months, and 531 cases at 36 months were included, with 21% to 25% screening positive for ICBs at each visit. Interviews of ICB screen-positive individuals revealed that 10% met formal criteria for impulse control disorders (ICD), while 33% had subsyndromal ICD (ICB symptoms without reaching the formal diagnostic criteria for ICD). When these data were combined through the use of multiple imputation, the prevalence of PD-ICB was estimated at 19.1% (95% confidence interval 10.1-28.2). On follow-up, 24% of cases of subsyndromal ICD had developed full symptoms of an ICD. PD-ICD was associated with dopamine agonist use, motor complications, and apathy but not PD-RBD. ICD prevalence in the RBD group (1%) was similar to that in controls (0.7%). CONCLUSIONS: ICBs occur in 19.1% of patients with early PD, many persisting or worsening over time. RBD is not associated with increased ICD risk. Psychosocial drivers, including mood and support networks, affect severity.