Free-water imaging of the cholinergic basal forebrain and pedunculopontine nucleus in Parkinson's disease.

Free-water imaging can predict and monitor dopamine system degeneration in people with Parkinson's disease. It can also enhance the sensitivity of traditional diffusion tensor imaging (DTI) metrics for indexing neurodegeneration. However, these tools are yet to be applied to investigate cholinergic system degeneration in Parkinson's disease, which involves both the pedunculopontine nucleus and cholinergic basal forebrain. Free-water imaging, free-water-corrected DTI and volumetry were used to extract structural metrics from the cholinergic basal forebrain and pedunculopontine nucleus in 99 people with Parkinson's disease and 46 age-matched controls. Cognitive ability was tracked over 4.5 years. Pearson's partial correlations revealed that free-water-corrected DTI metrics in the pedunculopontine nucleus were associated with performance on cognitive tasks that required participants to make rapid choices (behavioural flexibility). Volumetric, free-water content and DTI metrics in the cholinergic basal forebrain were elevated in a sub-group of people with Parkinson's disease with evidence of cognitive impairment, and linear mixed modelling revealed that these metrics were differently associated with current and future changes to cognition. Free water and free-water-corrected DTI can index cholinergic degeneration that could enable stratification of patients in clinical trials of cholinergic interventions for cognitive decline. In addition, degeneration of the pedunculopontine nucleus impairs behavioural flexibility in Parkinson's disease, which may explain this region's role in increased risk of falls.

Progression of atypical parkinsonian syndromes: PROSPECT-M-UK study implications for clinical trials.

The advent of clinical trials of disease-modifying agents for neurodegenerative disease highlights the need for evidence-based end point selection. Here we report the longitudinal PROSPECT-M-UK study of progressive supranuclear palsy (PSP), corticobasal syndrome (CBS), multiple system atrophy (MSA) and related disorders, to compare candidate clinical trial end points. In this multicentre UK study, participants were assessed with serial questionnaires, motor examination, neuropsychiatric and MRI assessments at baseline, 6 and 12 months. Participants were classified by diagnosis at baseline and study end, into Richardson syndrome, PSP-subcortical (PSP-parkinsonism and progressive gait freezing subtypes), PSP-cortical (PSP-frontal, PSP-speech and language and PSP-CBS subtypes), MSA-parkinsonism, MSA-cerebellar, CBS with and without evidence of Alzheimer's disease pathology and indeterminate syndromes. We calculated annual rate of change, with linear mixed modelling and sample sizes for clinical trials of disease-modifying agents, according to group and assessment type. Two hundred forty-three people were recruited [117 PSP, 68 CBS, 42 MSA and 16 indeterminate; 138 (56.8%) male; age at recruitment 68.7 ± 8.61 years]. One hundred and fifty-nine completed the 6-month assessment (82 PSP, 27 CBS, 40 MSA and 10 indeterminate) and 153 completed the 12-month assessment (80 PSP, 29 CBS, 35 MSA and nine indeterminate). Questionnaire, motor examination, neuropsychiatric and neuroimaging measures declined in all groups, with differences in longitudinal change between groups. Neuroimaging metrics would enable lower sample sizes to achieve equivalent power for clinical trials than cognitive and functional measures, often achieving N < 100 required for 1-year two-arm trials (with 80% power to detect 50% slowing). However, optimal outcome measures were disease-specific. In conclusion, phenotypic variance within PSP, CBS and MSA is a major challenge to clinical trial design. Our findings provide an evidence base for selection of clinical trial end points, from potential functional, cognitive, clinical or neuroimaging measures of disease progression.

Delirium is more common and associated with worse outcomes in Parkinson's disease compared to older adult controls: results of two prospective longitudinal cohort studies.

BACKGROUND: Inpatient prevalence of Parkinson's disease (PD) delirium varies widely across the literature. Delirium in general older populations is associated with adverse outcomes, such as increased mortality, dementia, and institutionalisation. However, to date there are no comprehensive prospective studies in PD delirium. This study aimed to determine delirium prevalence in hospitalised PD participants and the association with adverse outcomes, compared to a control group of older adults without PD. METHODS: Participants were hospitalised inpatients from the 'Defining Delirium and its Impact in Parkinson's Disease' and the 'Delirium and Cognitive Impact in Dementia' studies comprising 121 PD participants and 199 older adult controls. Delirium was diagnosed prospectively using the Diagnostic and Statistical Manual of Mental Disorders 5th Edition criteria. Outcomes were determined by medical note reviews and/or home visits 12 months post hospital discharge. RESULTS: Delirium was identified in 66.9% of PD participants compared to 38.7% of controls (p < 0.001). In PD participants only, delirium was associated with a significantly higher risk of mortality (HR = 3.3 (95% confidence interval [CI] = 1.3-8.6), p = 0.014) and institutionalisation (OR = 10.7 (95% CI = 2.1-54.6), p = 0.004) 12 months post-discharge, compared to older adult controls. However, delirium was associated with an increased risk of developing dementia 12 months post-discharge in both PD participants (OR = 6.1 (95% CI = 1.3-29.5), p = 0.024) and in controls (OR = 13.4 (95% CI = 2.5-72.6), p = 0.003). CONCLUSION: Delirium is common in hospitalised PD patients, affecting two thirds of patients, and is associated with increased mortality, institutionalisation, and dementia. Further research is essential to understand how to accurately identify, prevent and manage delirium in people with PD who are in hospital.

Network connectivity and structural correlates of survival in progressive supranuclear palsy and corticobasal syndrome.

There is a pressing need to understand the factors that predict prognosis in progressive supranuclear palsy (PSP) and corticobasal syndrome (CBS), with high heterogeneity over the poor average survival. We test the hypothesis that the magnitude and distribution of connectivity changes in PSP and CBS predict the rate of progression and survival time, using datasets from the Cambridge Centre for Parkinson-plus and the UK National PSP Research Network (PROSPECT-MR). Resting-state functional MRI images were available from 146 participants with PSP, 82 participants with CBS, and 90 healthy controls. Large-scale networks were identified through independent component analyses, with correlations taken between component time series. Independent component analysis was also used to select between-network connectivity components to compare with baseline clinical severity, longitudinal rate of change in severity, and survival. Transdiagnostic survival predictors were identified using partial least squares regression for Cox models, with connectivity compared to patients' demographics, structural imaging, and clinical scores using five-fold cross-validation. In PSP and CBS, between-network connectivity components were identified that differed from controls, were associated with disease severity, and were related to survival and rate of change in clinical severity. A transdiagnostic component predicted survival beyond demographic and motion metrics but with lower accuracy than an optimal model that included the clinical and structural imaging measures. Cortical atrophy enhanced the connectivity changes that were most predictive of survival. Between-network connectivity is associated with variability in prognosis in PSP and CBS but does not improve predictive accuracy beyond clinical and structural imaging metrics.

Documentation and diagnosis of delirium in Parkinson's disease.

OBJECTIVE: To assess the accuracy of documentation of the symptoms and diagnosis of delirium in medical notes of inpatients with Parkinson's disease (PD). METHODS: The DETERMINE-PD pilot study assessed PD inpatients over 4-months. Delirium prevalence was classified prospectively using a standardized assessment at a single visit on the basis of Diagnostic and Statistical Manual of Mental Disorders 5th Edition (DSM-5) criteria. Incident delirium was diagnosed retrospectively using detailed clinical vignettes and validated consensus method. Inpatient medical notes and discharge summaries of those with delirium were reviewed for documentation of symptoms, diagnosis and follow-up. RESULTS: Forty-four PD patients consented to take part in the study, accounting for 53 admissions. We identified 30 cases (56.6%) of delirium during the participants' stay in hospital. Of those with delirium identified by the research team, delirium symptoms were documented in the clinical notes of 72.3%; 37.9% had a delirium diagnosis documented. Older patients were more likely to have delirium (p = 0.027) and have this diagnosis documented (p = 0.034). Time from documentation of symptoms to diagnosis ranged from <24 h to 7 days (mean 1.6 ± 4.4 days). Hypoactive delirium was significantly less likely to have been identified and formally diagnosed (63% of not documented were hypoactive vs. 37% hyperactive, mixed or unclear, p = 0.016). Only 11.5% of discharge summaries included diagnosis of delirium. CONCLUSION: Delirium in PD is common. Documentation of symptoms of delirium was common; however, fails to lead to a documentation of diagnosis in over half of admissions with delirium and was even less commonly communicated in the Primary Care discharge summaries. This highlights the need for increased education about delirium symptomatology and diagnosis in PD.

Neurofilament light levels predict clinical progression and death in multiple system atrophy.

Disease-modifying treatments are currently being trialled in multiple system atrophy. Approaches based solely on clinical measures are challenged by heterogeneity of phenotype and pathogenic complexity. Neurofilament light chain protein has been explored as a reliable biomarker in several neurodegenerative disorders but data on multiple system atrophy have been limited. Therefore, neurofilament light chain is not yet routinely used as an outcome measure in multiple system atrophy. We aimed to comprehensively investigate the role and dynamics of neurofilament light chain in multiple system atrophy combined with cross-sectional and longitudinal clinical and imaging scales and for subject trial selection. In this cohort study, we recruited cross-sectional and longitudinal cases in a multicentre European set-up. Plasma and CSF neurofilament light chain concentrations were measured at baseline from 212 multiple system atrophy cases, annually for a mean period of 2 years in 44 multiple system atrophy patients in conjunction with clinical, neuropsychological and MRI brain assessments. Baseline neurofilament light chain characteristics were compared between groups. Cox regression was used to assess survival; receiver operating characteristic analysis to assess the ability of neurofilament light chain to distinguish between multiple system atrophy patients and healthy controls. Multivariate linear mixed-effects models were used to analyse longitudinal neurofilament light chain changes and correlated with clinical and imaging parameters. Polynomial models were used to determine the differential trajectories of neurofilament light chain in multiple system atrophy. We estimated sample sizes for trials aiming to decrease neurofilament light chain levels. We show that in multiple system atrophy, baseline plasma neurofilament light chain levels were better predictors of clinical progression, survival and degree of brain atrophy than the neurofilament light chain rate of change. Comparative analysis of multiple system atrophy progression over the course of disease, using plasma neurofilament light chain and clinical rating scales, indicated that neurofilament light chain levels rise as the motor symptoms progress, followed by deceleration in advanced stages. Sample size prediction suggested that significantly lower trial participant numbers would be needed to demonstrate treatment effects when incorporating plasma neurofilament light chain values into multiple system atrophy clinical trials in comparison to clinical measures alone. In conclusion, neurofilament light chain correlates with clinical disease severity, progression and prognosis in multiple system atrophy. Combined with clinical and imaging analysis, neurofilament light chain can inform patient stratification and serve as a reliable biomarker of treatment response in future multiple system atrophy trials of putative disease-modifying agents.

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.

Gait-Related Metabolic Covariance Networks at Rest in Parkinson's Disease.

BACKGROUND: Gait impairments are characteristic motor manifestations and significant predictors of poor quality of life in Parkinson's disease (PD). Neuroimaging biomarkers for gait impairments in PD could facilitate effective interventions to improve these symptoms and are highly warranted. OBJECTIVE: The aim of this study was to identify neural networks of discrete gait impairments in PD. METHODS: Fifty-five participants with early-stage PD and 20 age-matched healthy volunteers underwent quantitative gait assessment deriving 12 discrete spatiotemporal gait characteristics and [18 F]-2-fluoro-2-deoxyglucose-positron emission tomography measuring resting cerebral glucose metabolism. A multivariate spatial covariance approach was used to identify metabolic brain networks that were related to discrete gait characteristics in PD. RESULTS: In PD, we identified two metabolic gait-related covariance networks. The first correlated with mean step velocity and mean step length (pace gait network), which involved relatively increased and decreased metabolism in frontal cortices, including the dorsolateral prefrontal and orbital frontal, insula, supplementary motor area, ventrolateral thalamus, cerebellum, and cuneus. The second correlated with swing time variability and step time variability (temporal variability gait network), which included relatively increased and decreased metabolism in sensorimotor, superior parietal cortex, basal ganglia, insula, hippocampus, red nucleus, and mediodorsal thalamus. Expression of both networks was significantly elevated in participants with PD relative to healthy volunteers and were not related to levodopa dosage or motor severity. CONCLUSIONS: We have identified two novel gait-related brain networks of altered glucose metabolism at rest. These gait networks could serve as a potential neuroimaging biomarker of gait impairments in PD and facilitate development of therapeutic strategies for these disabling symptoms. © 2022 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Factors Influencing Habitual Physical Activity in Parkinson's Disease: Considering the Psychosocial State and Wellbeing of People with Parkinson's and Their Carers.

Participating in habitual physical activity (HPA) may slow onset of dependency and disability for people with Parkinson's disease (PwP). While cognitive and physical determinants of HPA are well understood, psychosocial influences are not. This pilot study aimed to identify psychosocial factors associated with HPA to guide future intervention development. Sixty-four PwP participated in this study; forty had carer informants. PwP participants wore a tri-axial accelerometer on the lower back continuously for seven days at two timepoints (18 months apart), measuring volume, pattern and variability of HPA. Linear mixed effects analysis identified relationships between demographic, clinical and psychosocial data and HPA from baseline to 18 months. Key results in PwP with carers indicated that carer anxiety and depression were associated with increased HPA volume (p < 0.01), while poorer carer self-care was associated with reduced volume of HPA over 18 months (p < 0.01). Greater carer strain was associated with taking longer walking bouts after 18 months (p < 0.01). Greater carer depression was associated with lower variability of HPA cross-sectionally (p = 0.009). This pilot study provides preliminary novel evidence that psychosocial outcomes from PwP's carers may impact HPA in Parkinson's disease. Interventions to improve HPA could target both PwP and carers and consider approaches that also support psychosocial wellbeing.

Spatial Covariance of Cholinergic Muscarinic M1 /M4 Receptors in Parkinson's Disease.

BACKGROUND: Parkinson's disease (PD) is associated with cholinergic dysfunction, although the role of M1 and M4 receptors remains unclear. OBJECTIVE: To investigate spatial covariance patterns of cholinergic muscarinic M1 /M4 receptors in PD and their relationship with cognition and motor symptoms. METHODS: Some 19 PD and 24 older adult controls underwent 123 I-iodo-quinuclidinyl-benzilate (QNB) (M1 /M4 receptor) and 99m Tc-exametazime (perfusion) single-photon emission computed tomography (SPECT) scanning. We implemented voxel principal components analysis, producing a series of images representing patterns of intercorrelated voxels across individuals. Linear regression analyses derived specific M1 /M4 spatial covariance patterns associated with PD. RESULTS: A cholinergic M1 /M4 pattern that converged onto key hubs of the default, auditory-visual, salience, and sensorimotor networks fully discriminated PD patients from controls (F1,41  = 135.4, P < 0.001). In PD, we derived M1 /M4 patterns that correlated with global cognition (r = -0.62, P = 0.008) and motor severity (r = 0.53, P = 0.02). Both patterns emerged with a shared topography implicating the basal forebrain as well as visual, frontal executive, and salience circuits. Further, we found a M1 /M4 pattern that predicted global cognitive decline (r = 0.46, P = 0.04) comprising relative decreased binding within default and frontal executive networks. CONCLUSIONS: Cholinergic muscarinic M1 /M4 modulation within key brain networks were apparent in PD. Cognition and motor severity were associated with a similar topography, inferring both phenotypes possibly rely on related cholinergic mechanisms. Relative decreased M1 /M4 binding within default and frontal executive networks could be an indicator of future cognitive decline. © 2021 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Cholinergic Basal Forebrain Volumes Predict Gait Decline in Parkinson's Disease.

BACKGROUND: Gait disturbance is an early, disabling feature of Parkinson's disease (PD) that is typically refractory to dopaminergic medication. The cortical cholinergic system, originating in the nucleus basalis of Meynert of the basal forebrain, has been implicated. However, it is not known if degeneration in this region relates to a worsening of disease-specific gait impairment. OBJECTIVE: To evaluate associations between sub-regional cholinergic basal forebrain volumes and longitudinal progression of gait impairment in PD. METHODS: 99 PD participants and 47 control participants completed gait assessments via an instrumented walkway during 2 minutes of continuous walking, at baseline and for up to 3 years, from which 16 spatiotemporal characteristics were derived. Sub-regional cholinergic basal forebrain volumes were measured at baseline via MRI and a regional map derived from post-mortem histology. Univariate analyses evaluated cross-sectional associations between sub-regional volumes and gait. Linear mixed-effects models assessed whether volumes predicted longitudinal gait changes. RESULTS: There were no cross-sectional, age-independent relationships between sub-regional volumes and gait. However, nucleus basalis of Meynert volumes predicted longitudinal gait changes unique to PD. Specifically, smaller nucleus basalis of Meynert volume predicted increasing step time variability (P = 0.019) and shortening swing time (P = 0.015); smaller posterior nucleus portions predicted shortening step length (P = 0.007) and increasing step time variability (P = 0.041). CONCLUSIONS: This is the first study to demonstrate that degeneration of the cortical cholinergic system predicts longitudinal progression of gait impairments in PD. Measures of this degeneration may therefore provide a novel biomarker for identifying future mobility loss and falls. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Genome-Wide Association Studies of Cognitive and Motor Progression in Parkinson's Disease.

BACKGROUND: There are currently no treatments that stop or slow the progression of Parkinson's disease (PD). Case-control genome-wide association studies have identified variants associated with disease risk, but not progression. The objective of the current study was to identify genetic variants associated with PD progression. METHODS: We analyzed 3 large longitudinal cohorts: Tracking Parkinson's, Oxford Discovery, and the Parkinson's Progression Markers Initiative. We included clinical data for 3364 patients with 12,144 observations (mean follow-up 4.2 years). We used a new method in PD, following a similar approach in Huntington's disease, in which we combined multiple assessments using a principal components analysis to derive scores for composite, motor, and cognitive progression. These scores were analyzed in linear regression in genome-wide association studies. We also performed a targeted analysis of the 90 PD risk loci from the latest case-control meta-analysis. RESULTS: There was no overlap between variants associated with PD risk, from case-control studies, and PD age at onset versus PD progression. The APOE ε4 tagging variant, rs429358, was significantly associated with composite and cognitive progression in PD. Conditional analysis revealed several independent signals in the APOE locus for cognitive progression. No single variants were associated with motor progression. However, in gene-based analysis, ATP8B2, a phospholipid transporter related to vesicle formation, was nominally associated with motor progression (P = 5.3 × 10-6 ). CONCLUSIONS: We provide early evidence that this new method in PD improves measurement of symptom progression. We show that the APOE ε4 allele drives progressive cognitive impairment in PD. Replication of this method and results in independent cohorts are needed. © 2020 The Authors. Movement Disorders published by Wiley Periodicals LLC on behalf of International Parkinson and Movement Disorder Society.

Fluctuating cognition in the Lewy body dementias.

Fluctuating cognition is a core diagnostic feature of dementia with Lewy bodies and is also a key clinical feature of Parkinson's disease dementia. These dementias share common pathological features and are referred to as Lewy body dementias. Whilst highly prevalent in Lewy body dementia, with up to 90% of patients experiencing the symptom at some point in the disease trajectory, clinical identification of fluctuating cognition is often challenging. Furthermore, its underlying pathophysiological processes remain unclear. However, neuroimaging and neurophysiological techniques have recently provided insight into potential drivers of the phenomenon. In this update, we review data pertaining to clinical features and underlying mechanisms of fluctuating cognition in Lewy body dementia. We collate evidence for different proposed aetiologies: fluctuating cognition as an attentional disorder, as a consequence of loss of cholinergic drive, as a manifestation of failure in neuronal efficiency and synchrony, and as a disorder of sleep/arousal. We also review data relating to putative mechanisms that have received less attention to date. Increased understanding of fluctuating cognition may help to illuminate pathophysiological mechanisms in cognitive processing in Lewy body dementia, guide future research, and facilitate the design of targeted therapeutic approaches.

Genetic analysis of Mendelian mutations in a large UK population-based Parkinson's disease study.

Our objective was to define the prevalence and clinical features of genetic Parkinson's disease in a large UK population-based cohort, the largest multicentre prospective clinico-genetic incident study in the world. We collected demographic data, Movement Disorder Society Unified Parkinson's Disease Rating Scale scores, and Montreal Cognitive Assessment scores. We analysed mutations in PRKN (parkin), PINK1, LRRK2 and SNCA in relation to age at symptom onset, family history and clinical features. Of the 2262 participants recruited to the Tracking Parkinson's study, 424 had young-onset Parkinson's disease (age at onset ≤ 50) and 1799 had late onset Parkinson's disease. A range of methods were used to genotype 2005 patients: 302 young-onset patients were fully genotyped with multiplex ligation-dependent probe amplification and either Sanger and/or exome sequencing; and 1701 late-onset patients were genotyped with the LRRK2 'Kompetitive' allele-specific polymerase chain reaction assay and/or exome sequencing (two patients had missing age at onset). We identified 29 (1.4%) patients carrying pathogenic mutations. Eighteen patients carried the G2019S or R1441C mutations in LRRK2, and one patient carried a heterozygous duplication in SNCA. In PRKN, we identified patients carrying deletions of exons 1, 4 and 5, and P113Xfs, R275W, G430D and R33X. In PINK1, two patients carried deletions in exon 1 and 5, and the W90Xfs point mutation. Eighteen per cent of patients with age at onset ≤30 and 7.4% of patients from large dominant families carried pathogenic Mendelian gene mutations. Of all young-onset patients, 10 (3.3%) carried biallelic mutations in PRKN or PINK1. Across the whole cohort, 18 patients (0.9%) carried pathogenic LRRK2 mutations and one (0.05%) carried an SNCA duplication. There is a significant burden of LRRK2 G2019S in patients with both apparently sporadic and familial disease. In young-onset patients, dominant and recessive mutations were equally common. There were no differences in clinical features between LRRK2 carriers and non-carriers. However, we did find that PRKN and PINK1 mutation carriers have distinctive clinical features compared to young-onset non-carriers, with more postural symptoms at diagnosis and less cognitive impairment, after adjusting for age and disease duration. This supports the idea that there is a distinct clinical profile of PRKN and PINK1-related Parkinson's disease. We estimate that there are approaching 1000 patients with a known genetic aetiology in the UK Parkinson's disease population. A small but significant number of patients carry causal variants in LRRK2, SNCA, PRKN and PINK1 that could potentially be targeted by new therapies, such as LRRK2 inhibitors.

Identifying delirium in Parkinson disease: A pilot study.

INTRODUCTION: People with Parkinson disease (PD) may be at increased risk of delirium and associated adverse outcomes. Delirium is an acute neuropsychiatric syndrome defined by confusion and inattention and is common in older adults. Previous studies may have underestimated the prevalence of delirium in PD because of overlapping symptoms, lack of awareness, and poorly defined criteria. We aimed to identify the prevalence and incidence of delirium in inpatients with PD. MEASUREMENTS: Participants were inpatients with PD admitted over a 4-month period. Delirium prevalence was classified using a standardised assessment at a single visit on the basis of the Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM-5) criteria. To capture remaining time in hospital, incident delirium was diagnosed using detailed clinical vignettes and a validated consensus method. RESULTS: Forty-four PD patients consented to take part in the study, accounting for 53 admissions. Delirium prevalence was 34.0% (n = 18); reviewing participants over the duration of their hospital stay identified 30 (56.6%) incident delirium cases. The admitting team screened 24.5% for delirium, and delirium was documented in eight (14.8%) patients' medical notes. Patients with delirium were significantly older, had higher frailty scores, and had a longer hospital stay (P < .05 for all). CONCLUSIONS: Delirium is common in PD inpatients at admission and incidence increases during hospital stay, but delirium is commonly missed. Our results highlight the importance of screening for delirium throughout patients' stay in hospital. Future studies should consider frequent evaluation over the duration of hospital stay to identify emergent delirium during the admission.

Pro-Saccades Predict Cognitive Decline in Parkinson's Disease: ICICLE-PD.

BACKGROUND: Cumulative dementia incidence in Parkinson's disease (PD) is significant, with major personal and socioeconomic impacts on individuals with PD and their carers. Early identification of dementia risk is vital to ensuring optimal intervention. Saccadic deficits often distinguish neurodegenerative disorders and cognitive impairment, but their ability to predict cognitive decline in PD has yet to be determined. The aims of this study were to (1) evaluate baseline (6.4 ± 6.1 months since PD diagnosis) differences in pro-saccadic metrics between those with early PD and healthy age-matched adults; and (2) assess the ability of baseline pro-saccades to predict subsequent cognitive decline over 4.5 years. METHODS: One hundred and forty-one PD and 90 age-matched participants recruited at diagnosis underwent saccadometric assessment of pro-saccades at baseline and had cognition assessed at baseline, 18, 36, and 54 months. Pro-saccadic characteristics included latency, duration, amplitude, peak, and average velocity. Cognitive assessment included executive function, attention, fluctuating attention, and memory. Linear mixed-effects models examined pro-saccadic metrics as predictors of cognitive decline over 54 months. RESULTS: Pro-saccades were significantly impaired at baseline in PD compared with controls. Pro-saccadic characteristics of latency, duration, peak, and average velocity predicted decline in global cognition, executive function, attention, and memory over 54 months in PD. In addition, only reduction in global cognition and attention were predicted by pro-saccadic metrics in age-matched adults, indicating that PD findings were not purely age related. CONCLUSIONS: Saccadic characteristics are impaired in early PD and are predictive of cognitive decline in several domains. Assessment of saccades may provide a useful non-invasive biomarker for long-term PD cognitive decline in early disease. © 2019 International Parkinson and Movement Disorder Society.

Risk of Parkinson's disease dementia related to level I MDS PD-MCI.

BACKGROUND: The International Parkinson and Movement Disorders Society criteria for mild cognitive impairment in PD need validation. The objectives of this present study were to evaluate prognostic validity of level I (abbreviated) International Parkinson and Movement Disorders Society mild cognitive impairment in PD criteria for development of PD dementia and compared them with level II (comprehensive) criteria. METHODS: We analyzed data from 8 international studies (1045 patients) from our consortium that included baseline data on demographics, motor signs, depression, detailed neuropsychological testing, and longitudinal follow-up for conversion to Parkinson's disease dementia. Survival analysis evaluated their contribution to the hazard of Parkinson's disease dementia. RESULTS: Level I mild cognitive impairment in PD, increasing age, male sex, and severity of PD motor signs independently increased the hazard of Parkinson's disease dementia. Level I and level II mild cognitive impairment in PD classification had similar discriminative ability with respect to the time to Parkinson's disease dementia. CONCLUSIONS: Level I mild cognitive impairment in PD classification independently contributes to the hazard of Parkinson's disease dementia. This finding supports the prognostic validity of the abbreviated mild cognitive impairment in PD criteria. © 2019 International Parkinson and Movement Disorder Society.

Features of GBA-associated Parkinson's disease at presentation in the UK Tracking Parkinson's study.

OBJECTIVES: To examine the influence of the glucocerebrosidase (GBA) mutation carrier state on age at onset of Parkinson's disease (PD), the motor phenotype and cognitive function at baseline assessment in a large cohort of UK patients. We also analysed the prevalence of mood and behavioural problems that may confound the assessment of cognitive function. METHODS: We prospectively recruited patients with PD in the Tracking Parkinson's study. We fully sequenced the GBA gene in all recently diagnosed patients (≤3.5 years). We examined cognitive (Montreal Cognitive Assessment) and motor (Movement Disorder Society Unified Parkinson's Disease Rating Scale part 3) function at a baseline assessment, at an average of 1.3 years after diagnosis. We used logistic regression to determine predictors of PD with mild cognitive impairment and PD with dementia. RESULTS: We studied 1893 patients with PD: 48 (2.5%) were heterozygous carriers for known Gaucher's disease (GD) causing pathogenic mutations; 117 (6.2%) had non-synonymous variants, previously associated with PD, and 28 (1.5%) patients carried variants of unknown significance in the GBA gene. L444P was the most common pathogenic GBA mutation. Patients with pathogenic GBA mutations were on average 5 years younger at disease onset compared with non-carriers (P=0.02). PD patients with GD-causing mutations did not have an increased family risk of PD. Patients with GBA mutations were more likely to present with the postural instability gait difficulty phenotype compared with non-carriers (P=0.02). Patients carrying pathogenic mutations in GBA had more advanced Hoehn and Yahr stage after adjustment for age and disease duration compared with non-carriers (P=0.005). There were no differences in cognitive function between GBA mutation carriers and non-carriers at this early disease stage. CONCLUSIONS: Our study confirms the influence of GBA mutations on the age of onset, disease severity and motor phenotype in patients with PD. Cognition did not differ between GBA mutation carriers and non-carriers at baseline, implying that cognitive impairment/dementia, reported in other studies at a later disease stage, is not present in recently diagnosed cases. This offers an important window of opportunity for potential disease-modifying therapy that may protect against the development of dementia in GBA-PD. CLINICAL TRIAL REGISTRATION: NCT02881099; Results.

Developing and validating Parkinson's disease subtypes and their motor and cognitive progression.

OBJECTIVES: To use a data-driven approach to determine the existence and natural history of subtypes of Parkinson's disease (PD) using two large independent cohorts of patients newly diagnosed with this condition. METHODS: 1601 and 944 patients with idiopathic PD, from Tracking Parkinson's and Discovery cohorts, respectively, were evaluated in motor, cognitive and non-motor domains at the baseline assessment. Patients were recently diagnosed at entry (within 3.5 years of diagnosis) and were followed up every 18 months. We used a factor analysis followed by a k-means cluster analysis, while prognosis was measured using random slope and intercept models. RESULTS: We identified four clusters: (1)  fast motor progression with symmetrical motor disease, poor olfaction, cognition and postural hypotension; (2) mild motor and non-motor disease with intermediate motor progression; (3) severe motor disease, poor psychological well-being and  poor sleep with an intermediate motor progression; (4) slow motor progression with tremor-dominant, unilateral disease. Clusters were moderately to substantially stable across the two cohorts (kappa 0.58). Cluster 1 had the fastest motor progression in Tracking Parkinson's at 3.2 (95% CI 2.8 to 3.6) UPDRS III points per year while cluster 4 had the slowest at 0.6 (0.1-1.1). In Tracking Parkinson's, cluster 2 had the largest response to levodopa 36.3% and cluster 4 the lowest 28.8%. CONCLUSIONS: We have found four novel clusters that replicated well across two independent early PD cohorts and were associated with levodopa response and motor progression rates. This has potential implications for better understanding disease pathophysiology and the relevance of patient stratification in future clinical trials.