Search

Neurofeedback training is a closed-loop neuromodulatory technique in which real-time feedback of brain activity and connectivity is provided to the participant for the purpose of volitional neural control. Through practice and reinforcement, such learning has been shown to facilitate measurable changes in brain function and behavior.In this review, we examine how neurofeedback, coupled with motor imagery training, has the potential to improve or normalize motor function in neurological diseases such as Parkinson disease and chronic stroke. We will also explore neurofeedback in the context of brain-machine interfaces (BMIs), discussing both noninvasive and invasive methods which have been used to power external devices (eg, robot hand orthosis or exoskeleton) in the context of motor neurorehabilitation.The published literature provides mounting high-quality evidence that neurofeedback and BMI control may lead to clinically relevant changes in brain function and behavior.

BACKGROUND: Type 2 diabetes (T2DM) is an established risk factor for developing Parkinson's disease (PD), but its effect on disease progression is not well understood. OBJECTIVE: The aim of this study was to investigate the influence of T2DM on aspects of disease progression in PD. METHODS: We analyzed data from the Tracking Parkinson's study to examine the effects of comorbid T2DM on PD progression and quality of life by comparing symptom severity scores assessing a range of motor and nonmotor symptoms. RESULTS: We identified 167 (8.7%) patients with PD and T2DM (PD + T2DM) and 1763 (91.3%) patients with PD without T2DM (PD). After controlling for confounders, patients with T2DM had more severe motor symptoms, as assessed by Movement Disorder Society Unified Parkinson's Disease Rating Scale, Part III (25.8 [0.9] vs. 22.5 [0.3] P = 0.002), and nonmotor symptoms, as assessed by Non-Motor Symptoms Scale total (38.4 [2.5] vs. 31.8 [0.7] P < 0.001), and were significantly more likely to report loss of independence (odds ratio, 2.08; 95% confidence interval [CI]: 1.34-3.25; P = 0.001) and depression (odds ratio, 1.62; CI: 1.10-2.39; P = 0.015). Furthermore, over time, patients with T2DM had significantly faster motor symptom progression (P = 0.012), developed worse mood symptoms (P = 0.041), and were more likely to develop substantial gait impairment (hazard ratio, 1.55; CI: 1.07-2.23; P = 0.020) and mild cognitive impairment (hazard ratio, 1.7; CI: 1.24-2.51; P = 0.002) compared with the PD group. CONCLUSIONS: In the largest study to date, T2DM is associated with faster disease progression in Parkinson's, highlighting an interaction between these two diseases. Because it is a potentially modifiable metabolic state, with multiple peripheral and central targets for intervention, it may represent a target for alleviating parkinsonian symptoms and slowing progression to disability and dementia. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

BackgroundPatients with Parkinson’s disease (PD) have variable rates of progression. More accurate prediction of progression could improve selection for clinical trials. Although some variance in clinical progression can be predicted by age at onset and phenotype, we hypothesise that this can be further improved by blood biomarkers.ObjectiveTo determine if blood biomarkers (serum neurofilament light (NfL) and genetic status (glucocerebrosidase,GBAand apolipoprotein E (APOE))) are useful in addition to clinical measures for prognostic modelling in PD.MethodsWe evaluated the relationship between serum NfL and baseline and longitudinal clinical measures as well as patients’ genetic (GBAandAPOE) status. We classified patients as having a favourable or an unfavourable outcome based on a previously validated model, and explored how blood biomarkers compared with clinical variables in distinguishing prognostic phenotypes .Results291 patients were assessed in this study. Baseline serum NfL was associated with baseline cognitive status. Nfl predicted a shorter time to dementia, postural instability and death (dementia—HR 2.64; postural instability—HR 1.32; mortality—HR 1.89) whereas APOEe4 status was associated with progression to dementia (dementia—HR 3.12, 95% CI 1.63 to 6.00). NfL levels and genetic variables predicted unfavourable progression to a similar extent as clinical predictors. The combination of clinical, NfL and genetic data produced a stronger prediction of unfavourable outcomes compared with age and gender (area under the curve: 0.74-age/gender vs 0.84-ALL p=0.0103).ConclusionsClinical trials of disease-modifying therapies might usefully stratify patients using clinical, genetic and NfL status at the time of recruitment.

An increase in the efficiency of clinical trial conduct has been successfully demonstrated in the oncology field, by the use of multi-arm, multi-stage trials allowing the evaluation of multiple therapeutic candidates simultaneously, and seamless recruitment to phase 3 for those candidates passing an interim signal of efficacy. Replicating this complex innovative trial design in diseases such as Parkinson’s disease is appealing, but in addition to the challenges associated with any trial assessing a single potentially disease modifying intervention in Parkinson’s disease, a multi-arm platform trial must also specifically consider the heterogeneous nature of the disease, alongside the desire to potentially test multiple treatments with different mechanisms of action. In a multi-arm trial, there is a need to appropriately stratify treatment arms to ensure each are comparable with a shared placebo/standard of care arm; however, in Parkinson’s disease there may be a preference to enrich an arm with a subgroup of patients that may be most likely to respond to a specific treatment approach. The solution to this conundrum lies in having clearly defined criteria for inclusion in each treatment arm as well as an analysis plan that takes account of predefined subgroups of interest, alongside evaluating the impact of each treatment on the broader population of Parkinson’s disease patients. Beyond this, there must be robust processes of treatment selection, and consensus derived measures to confirm target engagement and interim assessments of efficacy, as well as consideration of the infrastructure needed to support recruitment, and the long-term funding and sustainability of the platform. This has to incorporate the diverse priorities of clinicians, triallists, regulatory authorities and above all the views of people with Parkinson’s disease.

Parkinson’s disease (PD) is characterised by the emergence of beta frequency oscillatory synchronisation across the cortico-basal-ganglia circuit. The relationship between the anatomy of this circuit and oscillatory synchronisation within it remains unclear. We address this by combining recordings from human subthalamic nucleus (STN) and internal globus pallidus (GPi) with magnetoencephalography, tractography and computational modelling. Coherence between supplementary motor area and STN within the high (21–30 Hz) but not low (13-21 Hz) beta frequency range correlated with ‘hyperdirect pathway’ fibre densities between these structures. Furthermore, supplementary motor area activity drove STN activity selectively at high beta frequencies suggesting that high beta frequencies propagate from the cortex to the basal ganglia via the hyperdirect pathway. Computational modelling revealed that exaggerated high beta hyperdirect pathway activity can provoke the generation of widespread pathological synchrony at lower beta frequencies. These findings suggest a spectral signature and a pathophysiological role for the hyperdirect pathway in PD., In Parkinson’s disease (PD), beta frequency oscillations are synchronised across the cortico-basal-ganglia circuit. The authors show in human participants that high beta frequencies propagate from the cortex to the basal ganglia via the hyperdirect pathway, indicating a pathophysiological role for this pathway in PD.

Background: Parkinson’s disease severity is typically measured using the Movement Disorder Society Unified Parkinson’s disease rating scale (MDS-UPDRS). While training for this scale exists, users may vary in how they score a patient with the consequence of intra-rater and inter-rater variability. Objective: In this study we explored the consistency of an artificial intelligence platform compared with traditional clinical scoring in the assessment of motor severity in PD. Methods: Twenty-two PD patients underwent simultaneous MDS-UPDRS scoring by two experienced MDS-UPDRS raters and the two sets of accompanying video footage were also scored by an artificial intelligence video analysis platform known as KELVIN. Results: KELVIN was able to produce a summary score for 7 MDS-UPDRS part 3 items with good inter-rater reliability (Intraclass Correlation Coefficient (ICC) 0.80 in the OFF-medication state, ICC 0.73 in the ON-medication state). Clinician scores had exceptionally high levels of inter-rater reliability in both the OFF (0.99) and ON (0.94) medication conditions (possibly reflecting the highly experienced team). There was an ICC of 0.84 in the OFF-medication state and 0.31 in the ON-medication state between the mean Clinician and mean Kelvin scores for the equivalent 7 motor items, possibly due to dyskinesia impacting on the KELVIN scores. Conclusion: We conclude that KELVIN may prove useful in the capture and scoring of multiple items of MDS-UPDRS part 3 with levels of consistency not far short of that achieved by experienced MDS-UPDRS clinical raters, and is worthy of further investigation.

ObjectivesTo 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.MethodsWe 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.ResultsA 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 (ConclusionsWe 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.

Remote and objective assessment of the motor symptoms of Parkinson’s disease is an area of great interest particularly since the COVID-19 crisis emerged. In this paper, we focus on a) the challenges of assessing motor severity via videos and b) the use of emerging video-based Artificial Intelligence (AI)/Machine Learning techniques to quantitate human movement and its potential utility in assessing motor severity in patients with Parkinson’s disease. While we conclude that video-based assessment may be an accessible and useful way of monitoring motor severity of Parkinson’s disease, the potential of video-based AI to diagnose and quantify disease severity in the clinical context is dependent on research with large, diverse samples, and further validation using carefully considered performance standards.

The development of interventions to slow or halt the progression of Parkinson's disease remains a priority for patients and researchers alike. To date, no agents have been shown to have unequivocal evidence of disease-modifying effects in Parkinson's disease. The absence of disease-modifying treatments might relate not only to inadequate approaches for the selection of therapeutic candidates but also to insufficient attention to detail in clinical trial design. Better understanding of Parkinson's disease pathogenesis associated with advances in laboratory models, the use of objective biomarkers of disease progression and target engagement, and a focus on agents known to be safe for human use, alongside the use of precision medicine approaches, should together greatly increase the likelihood for successful identification of disease-modifying treatments for Parkinson's disease.

BackgroundThere are 90 genetic risk variants for Parkinson’s disease (PD) but currently only five nominated loci for PD progression. The biology of PD progression is likely to be of central importance in defining mechanisms that can be used to develop new treatments.MethodsWe studied 6,766 PD patients, over 15,340 visits with a mean follow-up of between 4.2 and 15.7 years and carried out a genome wide survival study for time to motor progression, defined by reaching Hoehn and Yahr stage 3 or greater, cognitive impairment as defined by serial cognitive examination, and death (mortality).FindingsThere was a robust effect of the APOE ε4 allele on mortality and cognitive impairment in PD. We identified three novel loci for mortality and motor progression, and nominated genes based on physical proximity or expression quantitative trait loci data. One locus within the TBXAS1 gene encoding thromboxane A synthase 1 was associated with mortality in PD (HR = 2.04 [95% CI 1.63 to 2.56], p-value = 7.71 x 10-10). Another locus near the SYT10 gene encoding synaptotagmin 10 was associated with mortality just above genome-wide significance (HR=1.36 [95% CI 1.21 to 1.51], p-value=5.31×10-8). A genomic variant associated with the expression of ADORA2A, encoding the A2A adenosine receptor, was associated with motor progression (HR=4.83 [95% CI 2.89 to 8.08], p-value=1.94×10-9). Only the non-Gaucher disease causing GBA PD risk variant E326K, of the known PD risk variants, was associated with progression in PD.InterpretationWe report three novel loci associated with PD progression or mortality. Further work is needed to understand the links between these genomic variants and the underlying disease biology. However, thromboxane synthesis, vesicular peptidergic neurotransmitter release and the A2A adenosine receptor may represent new candidates for disease modification in PD.RESEARCH IN CONTEXTEvidence before this studyWe searched PubMed for articles on Parkinson’s disease (PD) with no language restrictions from database inception up to February 9, 2022. We used the search terms “Parkinson disease AND genetics” and “disease progression OR survival OR mortality OR prognosis OR longitudinal studies”. We also conducted this search with the addition of “genome-wide association study” (GWAS) to focus on these genome-wide analyses. There are now three published large-scale GWASs investigating PD progression, and many candidate variant studies. However, no genome-wide studies have reported on survival/mortality in PD.Added value of this studyTo our knowledge, this is the first GWAS of survival in PD. Our study highlights new loci influencing survival in PD, including TBXAS1 and SYT10. We also conducted GWASs of progression to other clinical milestones, Hoehn and Yahr stage 3 or greater, and cognitive impairment. We show that APOE influences both mortality and cognitive progression in PD, and report an additional locus influencing expression of ADORA2A which affects the rate of motor progression.Implications of all the available evidenceWith the exception of APOE, we report new loci which have not been previously associated with PD progression or for mortality and ageing in the general population. These loci could be investigated in functional studies as potential drug targets to stop or slow progression of PD. In addition, new genetic loci can help to improve our understanding of the biology of PD progression and prediction of progression. Further replication of these loci is also needed in independent, longitudinal PD cohorts.

Making accurate decisions often involves the integration of current and past evidence. Here we examine the neural correlates of conflict and evidence integration during sequential decision making. Female and male human patients implanted with deep-brain stimulation (DBS) electrodes and age- and gender matched healthy controls performed an expanded judgement task, in which they were free to choose how many cues to sample. Behaviourally, we found that while patients sampled numerically more cues, they were less able to integrate evidence and showed suboptimal performance. Using recordings of Magnetoencephalography (MEG) and local field potentials (LFP, in patients) in the subthalamic nucleus (STN), we found that beta oscillations signalled conflict between cues within a sequence. Following cues that differed from previous cues, beta power in the STN and cortex first decreased and then increased. Importantly, the conflict signal in the STN outlasted the cortical one, carrying over to the next cue in the sequence. Furthermore, after a conflict, there was an increase in coherence between the dorsal premotor cortex and subthalamic nucleus in the beta band. These results extend our understanding of cortico-subcortical dynamics of conflict processing, and do so in a context where evidence must be accumulated in discrete steps, much like in real life. Thus, the present work leads to a more nuanced picture of conflict monitoring systems in the brain and potential changes due to disease.Significance StatementDecision-making often involves the integration of multiple pieces of information over time in order to make accurate predictions. We simultaneously recorded whole-head magnetoencephalography and local field potentials from the human subthalamic nucleus in a novel task which required integrating sequentially presented pieces of evidence. Our key finding is prolonged beta oscillations in the subthalamic nucleus, with a concurrent increase in communication with frontal cortex, when presented with conflicting information. These neural effects reflect the behavioural profile of reduced tendency to respond after conflict, as well as relate to suboptimal cue integration in patients, which may be directly linked to clinically reported side-effects of Deep Brain Stimulation such as impaired decision-making and impulsivity.

Parkinson’s disease dementia (PDD) and dementia with Lewy bodies (DLB) are related conditions that are associated with cholinergic system dysfunction. Dysfunction of the nucleus basalis of Meynert (NBM), a basal forebrain structure that provides the dominant source of cortical cholinergic innervation, has been implicated in the pathogenesis of both PDD and DLB. Here we leverage the temporal resolution of magnetoencephalography with the spatial resolution of MRI tractography to explore the intersection of functional and structural connectivity of the NBM in a unique cohort of PDD and DLB patients undergoing deep brain stimulation of this structure. We observe that NBM-cortical structural and functional connectivity correlate within spatially and spectrally segregated networks including: (i) a beta band network to supplementary motor area, where activity in this region was found to drive activity in the NBM; (ii) a delta/theta band network to medial temporal lobe structures encompassing the parahippocampal gyrus; and (iii) a delta/theta band network to visual areas including lingual gyrus. These findings reveal functional networks of the NBM that are likely to subserve important roles in motor control, memory and visual function, respectively. Furthermore, they motivate future studies aimed at disentangling network contribution to disease phenotype., Oswal et al. study the structural and functional connectivity of the nucleus basalis of Meynert (NBM) in patients with PDD and DLB. By integrating NBM recordings, MEG and MRI tractography, they identify frequency-specific pathophysiological networks where functional connectivity is predicted by structural connectivity.

OBJECTIVE Suboptimal lead placement is one of the most common indications for deep brain stimulation (DBS) revision procedures. Confirming lead placement in relation to the visible anatomical target with dedicated stereotactic imaging before terminating the procedure can mitigate this risk. In this study, the authors examined the accuracy, precision, and safety of intraoperative MRI (iMRI) to both guide and verify lead placement during frame-based stereotactic surgery. METHODS A retrospective analysis of 650 consecutive DBS procedures for targeting accuracy, precision, and perioperative complications was performed. Frame-based lead placement took place in an operating room equipped with an MRI machine using stereotactic images to verify lead placement before removing the stereotactic frame. Immediate lead relocation was performed when necessary. Systematic analysis of the targeting error was calculated. RESULTS Verification of 1201 DBS leads with stereotactic MRI was performed in 643 procedures and with stereotactic CT in 7. The mean ± SD of the final targeting error was 0.9 ± 0.3 mm (range 0.1–2.3 mm). Anatomically acceptable lead placement was achieved with a single brain pass for 97% (n = 1164) of leads; immediate intraoperative relocation was performed in 37 leads (3%) to obtain satisfactory anatomical placement. General anesthesia was used in 91% (n = 593) of the procedures. Hemorrhage was noted after 4 procedures (0.6%); 3 patients (0.4% of procedures) presented with transient neurological symptoms, and 1 experienced delayed cognitive decline. Two bleeds coincided with immediate relocation (2 of 37 leads, 5.4%), which contrasts with hemorrhage in 2 (0.2%) of 1164 leads implanted on the first pass (p = 0.0058). Three patients had transient seizures in the postoperative period. The seizures coincided with hemorrhage in 2 of these patients and with immediate lead relocation in the other. There were 21 infections (3.2% of procedures, 1.5% in 3 months) leading to hardware removal. Delayed (> 3 months) retargeting of 6 leads (0.5%) in 4 patients (0.6% of procedures) was performed because of suboptimal stimulation benefit. There were no MRI-related complications, no permanent motor deficits, and no deaths. CONCLUSIONS To the authors’ knowledge, this is the largest series reporting the use of iMRI to guide and verify lead location during DBS surgery. It demonstrates a high level of accuracy, precision, and safety. Significantly higher hemorrhage was encountered when multiple brain passes were required for lead implantation, although none led to permanent deficit. Meticulous audit and calibration can improve precision and maximize safety.

A robust body of evidence from randomized controlled trials has established the efficacy of deep brain stimulation (DBS) in reducing off time and dyskinesias in levodopa-treated patients with Parkinson's disease (PD). These effects go along with improvements in on period motor function, activities of daily living, and quality of life. In addition, subthalamic DBS is effective in controlling drug-refractory PD tremor. Here, we review the available data from long-term observational and controlled follow-up studies in DBS-treated patients to re-examine the persistence of motor and quality of life benefits and evaluate the effects on disease progression, major disability milestones, and survival. Although there is consistent evidence from observational follow-up studies in DBS-treated patients over 5-10 years and beyond showing sustained improvement of motor control, the long-term impact of DBS on overall progression of disability in PD is less clear. Whether DBS reduces or delays the development of later motor and non-motor disability milestones in comparison to best medical management strategies is difficult to answer by uncontrolled observational follow-up, but there are signals from controlled long-term observational studies suggesting that subthalamic DBS may delay some of the late-stage disability milestones including psychosis, falls, and institutionalization, and also slightly prolongs survival compared with matched medically managed patients. These observations could be attributable to the sustained improvements in motor function and reduction in medication-induced side effects, whereas there is no clinical evidence of direct effects of DBS on the underlying disease progression. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Aim: This subanalysis of the OPTIPARK study aimed to confirm the effectiveness and safety of opicapone in patients with Parkinson's disease and motor fluctuations in clinical practice specifically in the UK and to assess the impact of opicapone on treatment costs. Methods: Patients received opicapone added to levodopa for 6 months. Clinical outcomes were assessed at 3 and 6 months and treatment costs at 6 months. Results: Most patients' general condition improved at 3 months, with sustained improvements reported at 6 months. Opicapone improved motor and non-motor symptoms at both timepoints, was generally well tolerated and reduced total treatment costs by GBP 3719. Conclusion: Opicapone added to levodopa resulted in clinical improvements and reduced treatment costs across UK clinical practice.

See Bayram and Litvan (doi:10.1093/brain/awaa287) for a scientific commentary on this article. Patients with diabetes appear to be at increased risk of Parkinson’s disease. In a longitudinal study of approximately 100,000 patients with diabetes, Brauer et al. reveal a lower risk of incident Parkinson’s disease in those treated with GLP-1 mimetics or DPP-4 inhibitors compared to users of other oral antidiabetic drugs., The elevated risk of Parkinson’s disease in patients with diabetes might be mitigated depending on the type of drugs prescribed to treat diabetes. Population data for risk of Parkinson’s disease in users of the newer types of drugs used in diabetes are scarce. We compared the risk of Parkinson’s disease in patients with diabetes exposed to thiazolidinediones (glitazones), glucagon-like peptide-1 (GLP-1) receptor agonists and dipeptidyl peptidase 4 (DPP4) inhibitors, with the risk of Parkinson’s disease of users of any other oral glucose lowering drugs. A population-based, longitudinal, cohort study was conducted using historic primary care data from The Health Improvement Network. Patients with a diagnosis of diabetes and a minimum of two prescriptions for diabetes medications between January 2006 and January 2019 were included in our study. The primary outcome was the first recording of a diagnosis of Parkinson’s disease after the index date, identified from clinical records. We compared the risk of Parkinson’s disease in individuals treated with glitazones or DPP4 inhibitors and/or GLP-1 receptor agonists to individuals treated with other antidiabetic agents using a Cox regression with inverse probability of treatment weighting based on propensity scores. Results were analysed separately for insulin users. Among 100 288 patients [mean age 62.8 years (standard deviation 12.6)], 329 (0.3%) were diagnosed with Parkinson’s disease during the median follow-up of 3.33 years. The incidence of Parkinson’s disease was 8 per 10 000 person-years in 21 175 patients using glitazones, 5 per 10 000 person-years in 36 897 patients using DPP4 inhibitors and 4 per 10 000 person-years in 10 684 using GLP-1 mimetics, 6861 of whom were prescribed GTZ and/or DPP4 inhibitors prior to using GLP-1 mimetics. Compared with the incidence of Parkinson’s disease in the comparison group (10 per 10 000 person-years), adjusted results showed no evidence of any association between the use of glitazones and Parkinson’s disease [incidence rate ratio (IRR) 1.17; 95% confidence interval (CI) 0.76–1.63; P = 0.467], but there was strong evidence of an inverse association between use of DPP4 inhibitors and GLP-1 mimetics and the onset of Parkinson’s disease (IRR 0.64; 95% CI 0.43–0.88; P

Introduction: Preclinical studies suggest a link between cAMP/PKA signalling, phosphodiesterase 4 (PDE4) expression and excessive daytime sleepiness (EDS). Here, we investigated in vivo the association between PDE4 expression and EDS in Parkinson's disease (PD) patients using [ 11 C]rolipram PET and MR imaging. Methods: Eighteen participants, 12 PD and 6 healthy controls, underwent one [ 11 C]rolipram PET and a multi-modal MRI scan. Probabilistic tractography was performed on subjects’ diffusion data to functionally parcellate the striatum according with projections to limbic cortical areas. The severity of EDS was assessed using the Epworth Sleepiness Scale (ESS). To assess PDE4 expression in PD patients with EDS, the PD cohort was divided according to the presence (n = 5) or absence (n = 7) of EDS, defined using validated cut-off of score ≥10 on the ESS as score ≥10 on the ESS. Results: PD patients with EDS showed significantly increased [ 11 C]rolipram volume of distribution (V T ) in the caudate (P = 0.029), hypothalamus (P = 0.013), hippocampus (P = 0.036) and limbic striatum (P = 0.030) compared to patients without EDS. Furthermore, higher ESS scores correlated with increased [ 11 C]rolipram V T in the caudate (r = 0.77; P = 0.003), hypothalamus (r = 0.84; P = 0.001), hippocampus (r = 0.81; P = 0.001) and limbic subdivisions of the striatum (r = 0.80; P = 0.003). Conclusion: Our findings translate into humans preclinical data indicating that EDS is associated with elevated PDE4 in regions regulating sleep. The severity of EDS in PD was associated with elevated PDE4 expression; thus, suggesting a role of PDE4 in the pathophysiology of EDS in PD.

Deep brain stimulation may be an effective therapy for select cases of severe, treatment-refractory Tourette syndrome; however, patient responses are variable, and there are no reliable methods to predict clinical outcomes. The objectives of this retrospective study were to identify the stimulation-dependent structural networks associated with improvements in tics and comorbid obsessive-compulsive behaviour, compare the networks across surgical targets, and determine if connectivity could be used to predict clinical outcomes. Volumes of tissue activated for a large multisite cohort of patients (n = 66) implanted bilaterally in globus pallidus internus (n = 34) or centromedial thalamus (n = 32) were used to generate probabilistic tractography to form a normative structural connectome. The tractography maps were used to identify networks that were correlated with improvement in tics or comorbid obsessive-compulsive behaviour and to predict clinical outcomes across the cohort. The correlated networks were then used to generate ‘reverse’ tractography to parcellate the total volume of stimulation across all patients to identify local regions to target or avoid. The results showed that for globus pallidus internus, connectivity to limbic networks, associative networks, caudate, thalamus, and cerebellum was positively correlated with improvement in tics; the model predicted clinical improvement scores (P = 0.003) and was robust to cross-validation. Regions near the anteromedial pallidum exhibited higher connectivity to the positively correlated networks than posteroventral pallidum, and volume of tissue activated overlap with this map was significantly correlated with tic improvement (P 0.23). For obsessive-compulsive behaviour, both targets showed that connectivity to the prefrontal cortex, orbitofrontal cortex, and cingulate cortex was positively correlated with improvement; however, only the centromedial thalamus maps predicted clinical outcomes across the cohort (P = 0.034), but the model was not robust to cross-validation. Collectively, the results demonstrate that the structural connectivity of the site of stimulation are likely important for mediating symptom improvement, and the networks involved in tic improvement may differ across surgical targets. These networks provide important insight on potential mechanisms and could be used to guide lead placement and stimulation parameter selection, as well as refine targets for neuromodulation therapies for Tourette syndrome.

Functional dependency in basic activities of daily living (ADLs) is a key outcome in Parkinson's disease (PD). We aimed to define dependency in PD, using the original and MDS versions of the Unified Parkinson's Disease Rating Scale (UPDRS).We developed two algorithms to define dependency from items of UPDRS Part 2 and MDS-UPDRS Part 2 relating to basic ADLs (feeding, dressing, hygiene and walking, and getting out of a chair). We validated both algorithms using data from 1110 patients from six community-based PD incidence cohorts, testing concurrent validity, convergent validity, and predictive validity.Our optimal algorithm showed high specificity and moderate to high sensitivity versus SchwabEngland80% (specificity 95% [95% confidence interval (CI) 93-97] and sensitivity 65% [95% CI 55-73] at baseline; 88% [95% CI 85-91] and 85% [95% CI 79-97] respectively at five-years follow-up). Convergent validity was demonstrated by strong associations between dependency defined by the algorithm and cognition (MMSE), quality of life (PDQ39), and impairment (UPDRS part 3) (all p 0.001). Algorithm-defined dependency status also predicted mortality: HR for mortality in those dependent vs independent at baseline was 1.6 (95%CI 1.2-2.1) and in those dependent vs independent at five-years' follow-up was 2.2 (1.6-3.0).We have demonstrated the concurrent validity, convergent validity, and predictive validity of a UPDRS-/MDS-UPDRS-based algorithm to define functional dependency in PD. This can be used for studying dependency in any study where UPDRS or MDS-UPDRS part 2 data have been collected.

In 2011 the European Society for the Study of Tourette Syndrome (ESSTS) published its first European clinical guidelines for the treatment of Tourette Syndrome (TS) with part IV on deep brain stimulation (DBS). Here, we present a revised version of these guidelines with updated recommendations based on the current literature covering the last decade as well as a survey among ESSTS experts. Currently, data from the International Tourette DBS Registry and Database, two meta-analyses, and eight randomized controlled trials (RCTs) are available. Interpretation of outcomes is limited by small sample sizes and short follow-up periods. Compared to open uncontrolled case studies, RCTs report less favorable outcomes with conflicting results. This could be related to several different aspects including methodological issues, but also substantial placebo effects. These guidelines, therefore, not only present currently available data from open and controlled studies, but also include expert knowledge. Although the overall database has increased in size since 2011, definite conclusions regarding the efficacy and tolerability of DBS in TS are still open to debate. Therefore, we continue to consider DBS for TS as an experimental treatment that should be used only in carefully selected, severely affected and otherwise treatment-resistant patients.

Background Long‐term population‐representative data on motor fluctuations and levodopa‐induced dyskinesias in Parkinson's disease is lacking. Methods The Cambridgeshire Parkinson's Incidence from GP to Neurologist (CamPaIGN) cohort comprises incident PD cases followed for up to 13 years (n = 141). Cumulative incidence of motor fluctuations and levodopa‐induced dyskinesias and risk factors were assessed using Kaplan‐Meyer and Cox regression analyses. Results Cumulative incidence of motor fluctuations and levodopa‐induced dyskinesias was 54.3% and 14.5%, respectively, at 5 years and 100% and 55.7%, respectively, at 10 years. Higher baseline UPDRS‐total and SNCA rs356219(A) predicted motor fluctuations, whereas higher baseline Mini‐mental State Examination and GBA mutations predicted levodopa‐induced dyskinesias. Early levodopa use did not predict motor complications. Both early motor fluctuations and levodopa‐induced dyskinesias predicted reduced mortality in older patients (age at diagnosis >70 years). Conclusions Our data support the hypothesis that motor complications are related to the severity of nigrostriatal pathology rather than early levodopa use and indicate that early motor complications do not necessarily confer a negative prognosis. © 2019 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

BackgroundPatients with Parkinson’s disease (PD) have variable disease progression. More accurate prediction of progression could improve clinical trial design. Although some variance in clinical progression can be predicted by age at onset and phenotype, we hypothesise that this can be improved by blood biomarkers.ObjectiveTo determine if serum neurofilament light (NfL) is a useful biomarker for prognostic modelling in PD.MethodsWe evaluated the relationship between serum NfL and baseline and longitudinal clinical measures as well as patients’ genetic (GBA and APOE) status in a large clinical dataset. We classified patients as having a favourable or an unfavourable outcome based on a previously validated model and explored whether serum NfL could distinguish prognostic phenotypes. We compared NfL with baseline candidate predictor variables and studied the combination of clinical, serum and genetic data.ResultsSerum NfL was associated with patients’ cognitive status at baseline. Baseline NfL was associated with the progression of motor and functional impairment and with increased mortality (Survival HR 1.85, CI: 1.03-3.33, p=0.04). Baseline NfL levels predicted unfavourable progression to a similar extent as previously validated clinical predictors (AUC: 0.74 vs 0.78, p=0.22). The combination of clinical, genetic and biomarker data produced a strong predication of unfavourable outcomes as compared to age and gender alone (AUC: 0.71-age/gender vs 0.83-ALL p = 0.0076)ConclusionsBaseline serum NfL provides an objective measure of neurodegeneration in PD patients. Clinical trials of disease-modifying therapies might usefully stratify patients according using clinical, genetic and NfL status at the time of recruitment.