Optimising classification of Parkinson's disease based on motor, olfactory, neuropsychiatric and sleep features.

Olfactory loss, motor impairment, anxiety/depression, and REM-sleep behaviour disorder (RBD) are prodromal Parkinson's disease (PD) features. PD risk prediction models typically dichotomize test results and apply likelihood ratios (LRs) to scores above and below cut-offs. We investigate whether LRs for specific test values could enhance classification between PD and controls. PD patient data on smell (UPSIT), possible RBD (RBD Screening Questionnaire), and anxiety/depression (LADS) were taken from the Tracking Parkinson's study (n = 1046). For motor impairment (BRAIN test) in PD cases, published data were supplemented (n = 87). Control data (HADS for anxiety/depression) were taken from the PREDICT-PD pilot study (n = 1314). UPSIT, RBDSQ, and anxiety/depression data were analysed using logistic regression to determine which items were associated with PD. Gaussian distributions were fitted to BRAIN test scores. LRs were calculated from logistic regression models or score distributions. False-positive rates (FPRs) for specified detection rates (DRs) were calculated. Sixteen odours were associated with PD; LRs for this set ranged from 0.005 to 5511. Six RBDSQ and seven anxiety/depression questions were associated with PD; LRs ranged from 0.35 to 69 and from 0.002 to 402, respectively. BRAIN test LRs ranged from 0.16 to 1311. For a 70% DR, the FPR was 2.4% for the 16 odours, 4.6% for anxiety/depression, 16.0% for the BRAIN test, and 20.0% for the RBDSQ. Specific selections of (prodromal) PD marker features rather than dichotomized marker test results optimize PD classification. Such optimized classification models could improve the ability of algorithms to detect prodromal PD; however, prospective studies are needed to investigate their value for PD-prediction models.

Advance Care Planning and Care Coordination for People With Parkinson's Disease and Their Family Caregivers-Study Protocol for a Multicentre, Randomized Controlled Trial.

Background: Parkinson's disease (PD) is a progressive neurodegenerative disease with motor- and non-motor symptoms. When the disease progresses, symptom burden increases. Consequently, additional care demands develop, the complexity of treatment increases, and the patient's quality of life is progressively threatened. To address these challenges, there is growing awareness of the potential benefits of palliative care for people with PD. This includes communication about end-of-life issues, such as Advance Care Planning (ACP), which helps to elicit patient's needs and preferences on issues related to future treatment and care. In this study, we will assess the impact and feasibility of a nurse-led palliative care intervention for people with PD across diverse European care settings. Methods: The intervention will be evaluated in a multicentre, open-label randomized controlled trial, with a parallel group design in seven European countries (Austria, Estonia, Germany, Greece, Italy, Sweden and United Kingdom). The "PD_Pal intervention" comprises (1) several consultations with a trained nurse who will perform ACP conversations and support care coordination and (2) use of a patient-directed "Parkinson Support Plan-workbook". The primary endpoint is defined as the percentage of participants with documented ACP-decisions assessed at 6 months after baseline (t1). Secondary endpoints include patients' and family caregivers' quality of life, perceived care coordination, patients' symptom burden, and cost-effectiveness. In parallel, we will perform a process evaluation, to understand the feasibility of the intervention. Assessments are scheduled at baseline (t0), 6 months (t1), and 12 months (t2). Statistical analysis will be performed by means of Mantel-Haenszel methods and multilevel logistic regression models, correcting for multiple testing. Discussion: This study will contribute to the current knowledge gap on the application of palliative care interventions for people with Parkinson's disease aimed at ameliorating quality of life and managing end-of-life perspectives. Studying the impact and feasibility of the intervention in seven European countries, each with their own cultural and organisational characteristics, will allow us to create a broad perspective on palliative care interventions for people with Parkinson's disease across settings. Clinical Trial Registration:www.trialregister.nl, NL8180.

Digital health technology for non-motor symptoms in people with Parkinson's disease: Futile or future?

INTRODUCTION: There is an ongoing digital revolution in the field of Parkinson's disease (PD) for the objective measurement of motor aspects, to be used in clinical trials and possibly support therapeutic choices. The focus of remote technologies is now also slowly shifting towards the broad but more "hidden" spectrum of non-motor symptoms (NMS). METHODS: A narrative review of digital health technologies for measuring NMS in people with PD was conducted. These digital technologies were defined as assessment tools for NMS offered remotely in the form of a wearable, downloadable as a mobile app, or any other objective measurement of NMS in PD that did not require a hospital visit and could be performed remotely. Searches were performed using peer-reviewed literature indexed databases (MEDLINE, Embase, PsycINFO, Cochrane Database of Systematic Reviews, Cochrane CENTRAL Register of Controlled Trials), as well as Google and Google Scholar. RESULTS: Eighteen studies deploying digital health technology in PD were identified, for example for the measurement of sleep disorders, cognitive dysfunction and orthostatic hypotension. In addition, we describe promising developments in other conditions that could be translated for use in PD. CONCLUSION: Unlike motor symptoms, non-motor features of PD are difficult to measure directly using remote digital technologies. Nonetheless, it is currently possible to reliably measure several NMS and further digital technology developments are underway to offer further capture of often under-reported and under-recognised NMS.

Improving estimation of Parkinson's disease risk-the enhanced PREDICT-PD algorithm.

We previously reported a basic algorithm to identify the risk of Parkinson's disease (PD) using published data on risk factors and prodromal features. Using this algorithm, the PREDICT-PD study identified individuals at increased risk of PD and used tapping speed, hyposmia and REM sleep behaviour disorder (RBD) as "intermediate" markers of prodromal PD in the absence of sufficient incident cases. We have now developed and tested an enhanced algorithm which incorporates the intermediate markers into the risk model. Risk estimates were compared using the enhanced and the basic algorithm in members of the PREDICT-PD pilot cohort. The enhanced PREDICT-PD algorithm yielded a much greater range of risk estimates than the basic algorithm (93-609-fold difference between the 10th and 90th centiles vs 10-13-fold respectively). There was a greater increase in the risk of PD with increasing risk scores for the enhanced algorithm than for the basic algorithm (hazard ratios per one standard deviation increase in log risk of 2.75 [95% CI 1.68-4.50; p < 0.001] versus 1.47 [95% CI 0.86-2.51; p = 0.16] respectively). Estimates from the enhanced algorithm also correlated more closely with subclinical striatal DaT-SPECT dopamine depletion (R2 = 0.164, p = 0.005 vs R2 = 0.043, p = 0.17). Incorporating the previous intermediate markers of prodromal PD and using likelihood ratios improved the accuracy of the PREDICT-PD prediction algorithm.

Sequence of clinical and neurodegeneration events in Parkinson's disease progression.

Dementia is one of the most debilitating aspects of Parkinson's disease. There are no validated biomarkers that can track Parkinson's disease progression, nor accurately identify patients who will develop dementia and when. Understanding the sequence of observable changes in Parkinson's disease in people at elevated risk for developing dementia could provide an integrated biomarker for identifying and managing individuals who will develop Parkinson's dementia. We aimed to estimate the sequence of clinical and neurodegeneration events, and variability in this sequence, using data-driven statistical modelling in two separate Parkinson's cohorts, focusing on patients at elevated risk for dementia due to their age at symptom onset. We updated a novel version of an event-based model that has only recently been extended to cope naturally with clinical data, enabling its application in Parkinson's disease for the first time. The observational cohorts included healthy control subjects and patients with Parkinson's disease, of whom those diagnosed at age 65 or older were classified as having high risk of dementia. The model estimates that Parkinson's progression in patients at elevated risk for dementia starts with classic prodromal features of Parkinson's disease (olfaction, sleep), followed by early deficits in visual cognition and increased brain iron content, followed later by a less certain ordering of neurodegeneration in the substantia nigra and cortex, neuropsychological cognitive deficits, retinal thinning in dopamine layers, and further deficits in visual cognition. Importantly, we also characterize variation in the sequence. We found consistent, cross-validated results within cohorts, and agreement between cohorts on the subset of features available in both cohorts. Our sequencing results add powerful support to the increasing body of evidence suggesting that visual processing specifically is affected early in patients with Parkinson's disease at elevated risk of dementia. This opens a route to earlier and more precise detection, as well as a more detailed understanding of the pathological mechanisms underpinning Parkinson's dementia.

Testing Shortened Versions of Smell Tests to Screen for Hyposmia in Parkinson's Disease.

BACKGROUND: Hyposmia is an early feature in neurodegenerative diseases, most notably Parkinson's disease (PD). Using abbreviated smell tests could provide a cost-effective means for large-scale hyposmia screening. It is unclear whether short smell tests can effectively detect hyposmia in patient populations. OBJECTIVES: To test the ability of short smell combinations to "prescreen" for probable hyposmia in people with PD and target administration of more extensive tests, such as the University of Pennsylvania Smell Identification Test. METHODS: We assessed the screening performance of a short 4-smell combination previously derived from use of the 40-item University of Pennsylvania Smell Identification Test in healthy older people and its ability to detect hyposmia in a large cohort of PD patients. RESULTS: The novel 4-smell combination included menthol, clove, onion, and orange and had a sensitivity of 87.1% (95% confidence interval, 84.9%-89.2%) and specificity of 69.7% (63.3%-75.5%) for detecting hyposmia in patients with PD. A different (also novel) 4-item combination developed using a data-driven approach in PD patients only achieved 81.3% (78.2%-84.4%) sensitivity for equivalent specificity. CONCLUSIONS: A short 4-smell combination derived from a healthy population demonstrated high sensitivity to detect those with hyposmia and PD.

Visual tests predict dementia risk in Parkinson disease.

OBJECTIVE: To assess the role of visual measures and retinal volume to predict the risk of Parkinson disease (PD) dementia. METHODS: In this cohort study, we collected visual, cognitive, and motor data in people with PD. Participants underwent ophthalmic examination, retinal imaging using optical coherence tomography, and visual assessment including acuity and contrast sensitivity and high-level visuoperception measures of skew tolerance and biological motion. We assessed the risk of PD dementia using a recently described algorithm that combines age at onset, sex, depression, motor scores, and baseline cognition. RESULTS: One hundred forty-six people were included in the study (112 with PD and 34 age-matched controls). The mean disease duration was 4.1 (±2·5) years. None of these participants had dementia. Higher risk of dementia was associated with poorer performance in visual measures (acuity: ρ = 0.29, p = 0.0024; contrast sensitivity: ρ = -0.37, p < 0.0001; skew tolerance: ρ = -0.25, p = 0.0073; and biological motion: ρ = -0.26, p = 0.0054). In addition, higher risk of PD dementia was associated with thinner retinal structure in layers containing dopaminergic cells, measured as ganglion cell layer (GCL) and inner plexiform layer (IPL) thinning (ρ = -0.29, p = 0.0021; ρ = -0.33, p = 0.00044). These relationships were not seen for the retinal nerve fiber layer that does not contain dopaminergic cells and were not seen in unaffected controls. CONCLUSION: Visual measures and retinal structure in dopaminergic layers were related to risk of PD dementia. Our findings suggest that visual measures and retinal GCL and IPL volumes may be useful to predict the risk of dementia in PD.

Screening performance of abbreviated versions of the UPSIT smell test.

BACKGROUND: Hyposmia can develop with age and in neurodegenerative conditions, including Parkinson's disease (PD). The University of Pennsylvania Smell Identification Test (UPSIT) is a 40-item smell test widely used for assessing hyposmia. However, in a number of situations, such as identifying hyposmic individuals in large populations, shorter tests are preferable. METHODS: We assessed the ability of shorter UPSIT subsets to detect hyposmia in 891 healthy participants from the PREDICT-PD study. Shorter subsets included Versions A and B of the 4-item Pocket Smell Test (PST) and 12-item Brief Smell Identification Test (BSIT). Using a data-driven approach, we evaluated screening performances of 23,231,378 combinations of 1-7 smell items from the full UPSIT to derive "winning" subsets, and validated findings separately in another 191 healthy individuals. We then compared discriminatory UPSIT smells between PREDICT-PD participants and 40 PD patients, and assessed the performance of "winning" subsets containing discriminatory smells in PD patients. RESULTS: PST Versions A and B achieved sensitivity/specificity of 76.8%/64.9% and 86.6%/45.9%, respectively, while BSIT Versions A and B achieved 83.1%/79.5% and 96.5%/51.8%. From the data-driven analysis, 2 "winning" 7-item subsets surpassed the screening performance of 12-item BSITs (validation sensitivity/specificity of 88.2%/85.4% and 100%/53.5%), while a "winning" 4-item subset had higher sensitivity than PST-A, -B, and even BSIT-A (validation sensitivity 91.2%). Interestingly, several discriminatory smells featured within "winning" subsets, and demonstrated high-screening performances for identifying hyposmic PD patients. CONCLUSION: Using abbreviated smell tests could provide a cost-effective means of large-scale hyposmia screening, allowing more targeted UPSIT administration in general and PD-related settings.

Can neuroimaging predict dementia in Parkinson's disease?

Dementia in Parkinson's disease affects 50% of patients within 10 years of diagnosis but there is wide variation in severity and timing. Thus, robust neuroimaging prediction of cognitive involvement in Parkinson's disease is important: (i) to identify at-risk individuals for clinical trials of potential new treatments; (ii) to provide reliable prognostic information for individuals and populations; and (iii) to shed light on the pathophysiological processes underpinning Parkinson's disease dementia. To date, neuroimaging has not made major contributions to predicting cognitive involvement in Parkinson's disease. This is perhaps unsurprising considering conventional methods rely on macroscopic measures of topographically distributed neurodegeneration, a relatively late event in Parkinson's dementia. However, new technologies are now emerging that could provide important insights through detection of other potentially relevant processes. For example, novel MRI approaches can quantify magnetic susceptibility as a surrogate for tissue iron content, and increasingly powerful mathematical approaches can characterize the topology of brain networks at the systems level. Here, we present an up-to-date overview of the growing role of neuroimaging in predicting dementia in Parkinson's disease. We discuss the most relevant findings to date, and consider the potential of emerging technologies to detect the earliest signs of cognitive involvement in Parkinson's disease.

Mild Cognitive Impairment in Parkinson's Disease-What Is It?

PURPOSE OF REVIEW: Mild cognitive impairment is a common feature of Parkinson's disease, even at the earliest disease stages, but there is variation in the nature and severity of cognitive involvement and in the risk of conversion to Parkinson's disease dementia. This review aims to summarise current understanding of mild cognitive impairment in Parkinson's disease. We consider the presentation, rate of conversion to dementia, underlying pathophysiology and potential biomarkers of mild cognitive impairment in Parkinson's disease. Finally, we discuss challenges and controversies of mild cognitive impairment in Parkinson's disease. RECENT FINDINGS: Large-scale longitudinal studies have shown that cognitive involvement is important and common in Parkinson's disease and can present early in the disease course. Recent criteria for mild cognitive impairment in Parkinson's provide the basis for further study of cognitive decline and for the progression of different cognitive phenotypes and risk of conversion to dementia. Improved understanding of the underlying pathology and progression of cognitive change are likely to lead to opportunities for early intervention for this important aspect of Parkinson's disease.

Assessing cognitive dysfunction in Parkinson's disease: An online tool to detect visuo-perceptual deficits.

BACKGROUND: People with Parkinson's disease (PD) who develop visuo-perceptual deficits are at higher risk of dementia, but we lack tests that detect subtle visuo-perceptual deficits and can be performed by untrained personnel. Hallucinations are associated with cognitive impairment and typically involve perception of complex objects. Changes in object perception may therefore be a sensitive marker of visuo-perceptual deficits in PD. OBJECTIVE: We developed an online platform to test visuo-perceptual function. We hypothesised that (1) visuo-perceptual deficits in PD could be detected using online tests, (2) object perception would be preferentially affected, and (3) these deficits would be caused by changes in perception rather than response bias. METHODS: We assessed 91 people with PD and 275 controls. Performance was compared using classical frequentist statistics. We then fitted a hierarchical Bayesian signal detection theory model to a subset of tasks. RESULTS: People with PD were worse than controls at object recognition, showing no deficits in other visuo-perceptual tests. Specifically, they were worse at identifying skewed images (P < .0001); at detecting hidden objects (P = .0039); at identifying objects in peripheral vision (P < .0001); and at detecting biological motion (P = .0065). In contrast, people with PD were not worse at mental rotation or subjective size perception. Using signal detection modelling, we found this effect was driven by change in perceptual sensitivity rather than response bias. CONCLUSIONS: Online tests can detect visuo-perceptual deficits in people with PD, with object recognition particularly affected. Ultimately, visuo-perceptual tests may be developed to identify at-risk patients for clinical trials to slow PD dementia. © 2018 The Authors. Movement Disorders published by Wiley Periodicals, Inc. on behalf of International Parkinson and Movement Disorder Society.

Current concepts and controversies in the pathogenesis of Parkinson's disease dementia and Dementia with Lewy Bodies.

Parkinson's disease dementia (PDD) and dementia with Lewy bodies (DLB) are relentlessly progressive neurodegenerative disorders that are likely to represent two ends of a disease spectrum. It is well established that both are characterised pathologically by widespread cortical Lewy body deposition. However, until recently, the pathophysiological mechanisms leading to neuronal damage were not known. It was also not understood why some cells are particularly vulnerable in PDD/DLB, nor why some individuals show more aggressive and rapid dementia than others. Recent studies using animal and cell models as well as human post-mortem analyses have provided important insights into these questions. Here, we review recent developments in the pathophysiology in PDD/DLB. Specifically, we examine the role of pathological proteins other than α-synuclein, consider particular morphological and physiological features that confer vulnerabilities on some neurons rather than others, and finally examine genetic factors that may explain some of the heterogeneity between individuals with PDD/DLB.

Visual dysfunction in Parkinson's disease.

Patients with Parkinson's disease have a number of specific visual disturbances. These include changes in colour vision and contrast sensitivity and difficulties with complex visual tasks such as mental rotation and emotion recognition. We review changes in visual function at each stage of visual processing from retinal deficits, including contrast sensitivity and colour vision deficits to higher cortical processing impairments such as object and motion processing and neglect. We consider changes in visual function in patients with common Parkinson's disease-associated genetic mutations including GBA and LRRK2 . We discuss the association between visual deficits and clinical features of Parkinson's disease such as rapid eye movement sleep behavioural disorder and the postural instability and gait disorder phenotype. We review the link between abnormal visual function and visual hallucinations, considering current models for mechanisms of visual hallucinations. Finally, we discuss the role of visuo-perceptual testing as a biomarker of disease and predictor of dementia in Parkinson's disease.

Accuracy of screening instruments for detection of neuropsychiatric syndromes in Parkinson's disease.

Parkinson's disease includes neuropsychiatric manifestations, such as depression, anxiety, apathy, psychosis, and impulse control disorders, which often are unreported by patients and caregivers or undetected by doctors. Given their substantial impact on patients and caregivers as well as the existence of effective therapies for some of these disorders, screening for neuropsychiatric symptoms is important. Instruments for screening have a particular methodology for validation, and their performance is expressed in terms of accuracy compared with formal diagnostic criteria. The present study reviews the attributes of the screening instruments applied for detection of the aforementioned major neuropsychiatric symptoms in Parkinson's disease. A quasi-systematic review (including predefined selection criteria, but not evaluating the quality of the reviewed studies) was carried out on the basis of previous systematic reviews (commissioned by the American Academy of Neurology and the Movement Disorder Society) and made current by conducting a literature search (2005-2014). For depression, 11 scales and questionnaires were shown to be valid for Parkinson's disease screening. The recently developed Parkinson Anxiety Scale and the Geriatric Anxiety Inventory demonstrate satisfactory properties as screening instruments for anxiety, and the Lille Apathy Rating Scale for detection of apathy. No scale adequately screens for psychosis, so a specific psychosis instrument should be developed. The Questionnaire for Impulsive-Compulsive Disorders in Parkinson's Disease (Questionnaire and Rating Scale) are valid for comprehensive screening of impulse control disorders, and the Parkinson's Disease-Sexual Addiction Screening Test for hypersexuality specifically.

Imaging psychogenic movement disorders.

The neurobiological basis of psychogenic movement disorders (PMDs) has been elusive, and they remain difficult to treat. In the last few years, functional neuroimaging studies have provided insight into their pathophysiology and neural correlates. Here, we review the various methodological approaches that have been used in both clinical and research practice to address neural correlates of functional disorders. We then review the dominant hypotheses generated from the literature on psychogenic paralysis. Overall, these studies emphasize abnormalities in the prefrontal and anterior cingulate cortices. Recently, functional neuroimaging has been used to specifically examine PMDs. These studies have addressed a major point of controversy: whether higher frontal brain areas are directly responsible for inhibiting motor areas or whether they reflect modulation by attentional and/or emotional processes. In addition to elucidating the mechanism and cause, recent work has also explored the lack of agency that characterizes PMDs. We describe the results and implications of the results of these imaging studies and discuss possible interpretations.

The functional neuroimaging correlates of psychogenic versus organic dystonia.

The neurobiological basis of psychogenic movement disorders remains poorly understood and the management of these conditions difficult. Functional neuroimaging studies have provided some insight into the pathophysiology of disorders implicating particularly the prefrontal cortex, but there are no studies on psychogenic dystonia, and comparisons with findings in organic counterparts are rare. To understand the pathophysiology of these disorders better, we compared the similarities and differences in functional neuroimaging of patients with psychogenic dystonia and genetically determined dystonia, and tested hypotheses on the role of the prefrontal cortex in functional neurological disorders. Patients with psychogenic (n = 6) or organic (n = 5, DYT1 gene mutation positive) dystonia of the right leg, and matched healthy control subjects (n = 6) underwent positron emission tomography of regional cerebral blood flow. Participants were studied during rest, during fixed posturing of the right leg and during paced ankle movements. Continuous surface electromyography and footplate manometry monitored task performance. Averaging regional cerebral blood flow across all tasks, the organic dystonia group showed abnormal increases in the primary motor cortex and thalamus compared with controls, with decreases in the cerebellum. In contrast, the psychogenic dystonia group showed the opposite pattern, with abnormally increased blood flow in the cerebellum and basal ganglia, with decreases in the primary motor cortex. Comparing organic dystonia with psychogenic dystonia revealed significantly greater regional blood flow in the primary motor cortex, whereas psychogenic dystonia was associated with significantly greater blood flow in the cerebellum and basal ganglia (all P < 0.05, family-wise whole-brain corrected). Group × task interactions were also examined. During movement, compared with rest, there was abnormal activation in the right dorsolateral prefrontal cortex that was common to both organic and psychogenic dystonia groups (compared with control subjects, P < 0.05, family-wise small-volume correction). These data show a cortical-subcortical differentiation between organic and psychogenic dystonia in terms of regional blood flow, both at rest and during active motor tasks. The pathological prefrontal cortical activation was confirmed in, but was not specific to, psychogenic dystonia. This suggests that psychogenic and organic dystonia have different cortical and subcortical pathophysiology, while a derangement in mechanisms of motor attention may be a feature of both conditions.

Parkin disease: a phenotypic study of a large case series.

Mutations in the parkin gene, PARK2, are a common cause of parkinsonism in familial as well as isolated cases with an age of onset <40 years and should be considered in the diagnostic work up of young-onset parkinsonism. We report a detailed clinical evaluation of a personal series of 24 patients with mutations in the parkin gene. The clinical presentation of most cases was broadly comparable to that of previous descriptions of autosomal recessive early-onset or juvenile parkinsonism and young-onset Parkinson's disease and also had similarities with phenotypes of dopa-responsive dystonia. However, our only case with consanguineous parents had an age of onset of 54 years. We report three new phenotypes at presentation: cervical dystonia; autonomic dysfunction and peripheral neuropathy; and pure exercise-induced dystonia. We emphasize a number of clinical features that can be seen in parkin disease: focal dystonia; early instability; freezing; festination or retropulsion; concurrent autonomic failure; dramatic response to anticholinergics; early or atypical L-dopa-induced dyskinesias; exquisite sensitivity to small doses of L-dopa; and recurrent psychosis, even taking L-dopa alone. We also report behavioural disorder prior to the onset of parkinsonism. Some relatives carrying a single parkin mutation without extrapyramidal symptoms or signs also had psychiatric symptoms that might be related to their carrier status.