Genome-wide determinants of mortality and motor progression in Parkinson's disease.

There are 90 independent genome-wide significant 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. We studied 6766 PD patients, over 15,340 visits with a mean follow-up of between 4.2 and 15.7 years and carried out genome-wide survival studies for time to a motor progression endpoint, defined by reaching Hoehn and Yahr stage 3 or greater, and death (mortality). There was a robust effect of the APOE ε4 allele on mortality in PD. We also identified a locus within the TBXAS1 gene encoding thromboxane A synthase 1 associated with mortality in PD. We also report 4 independent loci associated with motor progression in or near MORN1, ASNS, PDE5A, and XPO1. Only the non-Gaucher disease causing GBA1 PD risk variant E326K, of the known PD risk variants, was associated with mortality in PD. Further work is needed to understand the links between these genomic variants and the underlying disease biology. However, these may represent new candidates for disease modification in PD.

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.

Predicting cognitive decline using neuropsychiatric symptoms in prodromal Lewy body dementia: A longitudinal study.

INTRODUCTION: Neuropsychiatric symptoms (NPS) in Lewy body dementias (LBD) occur frequently and early in disease progression. Such symptoms are associated with worse quality of life, caregiver burden and functional limitations. Limited evidence exists, however, outlining the longitudinal relationship between NPS and cognitive decline in prodromal LBD. METHODS: 123 participants were derived from three cohort studies. Patients with mild cognitive impairment (MCI) relating to probable dementia with Lewy bodies (MCI-LB, n = 67) and Parkinson's disease (PD-MCI, n = 56) completed comprehensive cognitive and neuropsychiatric assessment and were followed up longitudinally. Linear regression and mixed effects models assessed the relationship between baseline NPS and cognition at baseline and over time. RESULTS: In MCI-LB, overall NPS burden was associated with declines over time in executive function (p = 0.026) and processing speed (p = 0.028) and baseline aberrant motor behaviour was associated with declines in attention (p < 0.025). Anxiety was significantly associated with poorer visuospatial functioning (p = 0.016) at baseline and poorer attention both at baseline (p = 0.017) and across time points (p = 0.024). In PD-MCI, psychosis was associated with poorer executive functioning at baseline (p = 0.008) and across time points (p = 0.002) but had no association with changes longitudinally. CONCLUSIONS: Core neuropsychiatric components of LBD are not strongly associated with cognition in prodromal disease. This may suggest that neuropathological mechanisms underlying NPS may not be the same as those underlying cognitive impairment. Non-core NPS, however, may be more directly associated with cognitive change. Future studies utilising neuroimaging techniques are needed to explore the neuropathological basis of NPS in prodromal LBD.

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.

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.

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.

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.

Level I PD-MCI Using Global Cognitive Tests and the Risk for Parkinson's Disease Dementia.

Background: The criteria for PD-MCI allow the use of global cognitive tests. Their predictive value for conversion from PD-MCI to PDD, especially compared to comprehensive neuropsychological assessment, is unknown. Methods: The MDS PD-MCI Study Group combined four datasets containing global cognitive tests as well as a comprehensive neuropsychological assessment to define PD-MCI (n = 467). Risk for developing PDD was examined using a Cox model. Global cognitive tests were compared to neuropsychological test batteries (Level I&II) in determining risk for PDD. Results: PD-MCI based on a global cognitive test (MMSE or MoCA) increases the hazard for developing PDD (respectively HR = 2.57, P = 0.001; HR = 4.14, P = <0.001). The C-statistics for MMSE (0.72) and MoCA (0.70) were lower than those based on neuropsychological tests (Level I = 0.82; Level II = 0.81). Sensitivity, specificity and diagnostic accuracy balance was best in Level II. Conclusion: MMSE and MoCA predict conversion to PDD. However, Level II neuropsychological assessment seems the preferred assessment for PD-MCI.

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.

Evaluation of Bedside Tests of Attention and Arousal Assessing Delirium in Parkinson's Disease, Dementia, and Older Adults.

BACKGROUND: Delirium is a serious acute neuropsychiatric condition associated with altered attention and arousal. OBJECTIVE: To evaluate simple bedside tests for attention and arousal to detect delirium in those with and without Parkinson's disease (PD) and dementia. METHODS: Participants from two prospective delirium studies were pooled comprising 30 with PD without cognitive impairment, 24 with Lewy body cognitive impairment (PD dementia or dementia with Lewy bodies), 16 with another dementia and 179 PD and dementia-free older adults. Participants completed standardised delirium assessments including tests of attention: digit span, Memorial Delirium Assessment Scale (MDAS) attention and months of the year backwards; and arousal: Glasgow Coma Scale (GSC), Observational Scale of Level of Arousal (OSLA), Modified Richmond Agitation Scale and MDAS consciousness. Delirium was diagnosed using the DSM-5 criteria. RESULTS: On their first admission, 21.7%participants had prevalent delirium. Arousal measures accurately detected delirium in all participants (p < 0.01 for all), but only selected attention measures detected delirium in PD and dementia. In PD and dementia-free older adults, impaired digit span and OSLA were the optimal tests to detect delirium (area under the curve [AUC] = 0.838, p < 0.001) while in PD and dementia the optimal tests were MDAS attention and GCS (AUC=0.90 and 0.84, respectively, p < 0.001 for both). CONCLUSION: Simple bedside tests of attention and arousal at a single visit could accurately detect delirium in PD, dementia and PD and dementia-free older adults; however, the optimal tests differed between groups. Combined attention and arousal scores increased accuracy, which could have clinical utility to aid the identification of delirium neurodegenerative disorders.

Altered network stability in progressive supranuclear palsy.

The clinical syndromes of Progressive Supranuclear Palsy (PSP) may be mediated by abnormal temporal dynamics of brain networks, due to the impact of atrophy, synapse loss and neurotransmitter deficits. We tested the hypothesis that alterations in signal complexity in neural networks influence short-latency state transitions. Ninety-four participants with PSP and 64 healthy controls were recruited from two independent cohorts. All participants underwent clinical and neuropsychological testing and resting-state functional MRI. Network dynamics were assessed using hidden Markov models and neural signal complexity measured in terms of multiscale entropy. In both cohorts, PSP increased the proportion of time in networks associated with higher cognitive functions. This effect correlated with clinical severity as measured by the PSP-rating-scale, and with reduced neural signal complexity. Regional atrophy influenced abnormal brain-state occupancy, but abnormal network topology and dynamics were not restricted to areas of atrophy. Our findings show that the pathology of PSP causes clinically relevant changes in neural temporal dynamics, leading to a greater proportion of time in inefficient brain-states.

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.

Which Neuropsychological Tests? Predicting Cognitive Decline and Dementia in Parkinson's Disease in the ICICLE-PD Cohort.

BACKGROUND: Cognitive impairment is common in Parkinson's disease (PD), with 80% cumulatively developing dementia (PDD). OBJECTIVE: We sought to identify tests that are sensitive to change over time above normal ageing so as to refine the neuropsychological tests predictive of PDD. METHODS: Participants with newly diagnosed PD (n = 211) and age-matched controls (n = 99) completed a range of clinical and neuropsychological tests as part of the ICICLE-PD study at 18-month intervals over 72 months. Impairments on tests were determined using control means (<1-2SD) and median scores. Mild cognitive impairment (PD-MCI) was classified using 1-2SD below normative values. Linear mixed effects modelling assessed cognitive decline, while Cox regression identified baseline predictors of PDD. RESULTS: At 72 months, 46 (cumulative probability 33.9%) participants had developed PDD; these participants declined at a faster rate in tests of global cognition, verbal fluency, memory and attention (p < 0.05) compared to those who remained dementia-free. Impaired baseline global cognition, visual memory and attention using median cut-offs were the best predictors of early PDD (area under the curve [AUC] = 0.88, p < 0.001) compared to control-generated cut-offs (AUC = 0.76-0.84,p < 0.001) and PD-MCI (AUC = 0.64-0.81, p < 0.001). Impaired global cognition and semantic fluency were the most useful brief tests employable in a clinical setting (AUC = 0.79, p < 0.001). CONCLUSION: Verbal fluency, attention and memory were sensitive to change in early PDD and may be suitable tests to measure therapeutic response in future interventions. Impaired global cognition, attention and visual memory were the most accurate predictors for developing a PDD. Future studies could consider adopting these tests for patient clinical trial stratification.

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.