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

Caregiver Burden in Late-Stage Parkinsonism and Its Associations

Background: Patients in the late stages of parkinsonism are highly dependent on others in their self-care and activities of daily living. However, few studies have assessed the physical, psychological and social consequences of caring for a person with late-stage parkinsonism. Patients and methods: Five hundred and six patients and their caregivers from the Care of Late Stage Parkinsonism (CLaSP) study were included. Patients’ motor and non-motor symptoms were assessed using the UPDRS and Non-motor symptom scale (NMSS), Neuropsychiatric inventory (NPI-12), and caregivers’ health status using the EQ-5D-3 L. Caregiver burden was assessed by the Zarit Burden Interview (ZBI). Results: The majority of caregivers were the spouse or life partner (71.2%), and were living with the patient at home (67%). Approximately half of caregivers reported anxiety/depression and pain/discomfort (45% and 59% respectively). The factors most strongly associated with caregiver burden were patients’ neuropsychiatric features on the total NPI score (r = 0.38, p < 0.0001), total NMSS score (r = 0.28, p < 0.0001), caring for male patients and patients living at home. Being the spouse, the hours per day assisting and supervising the patient as well as caregivers’ EQ-5D mood and pain scores were also associated with higher ZBI scores (all p < 0.001). Conclusion: The care of patients with late stage parkinsonism is associated with significant caregiver burden, particularly when patients manifest many neuropsychiatric and non-motor features and when caring for a male patient at home

Parkinson disease

Parkinson disease is the second-most common neurodegenerative disorder that affects 2-3% of the population ≥65 years of age. Neuronal loss in the substantia nigra, which causes striatal dopamine deficiency, and intracellular inclusions containing aggregates of α-synuclein are the neuropathological hallmarks of Parkinson disease. Multiple other cell types throughout the central and peripheral autonomic nervous system are also involved, probably from early disease onwards. Although clinical diagnosis relies on the presence of bradykinesia and other cardinal motor features, Parkinson disease is associated with many non-motor symptoms that add to overall disability. The underlying molecular pathogenesis involves multiple pathways and mechanisms: α-synuclein proteostasis, mitochondrial function, oxidative stress, calcium homeostasis, axonal transport and neuroinflammation. Recent research into diagnostic biomarkers has taken advantage of neuroimaging in which several modalities, including PET, single-photon emission CT (SPECT) and novel MRI techniques, have been shown to aid early and differential diagnosis. Treatment of Parkinson disease is anchored on pharmacological substitution of striatal dopamine, in addition to non-dopaminergic approaches to address both motor and non-motor symptoms and deep brain stimulation for those developing intractable L-DOPA-related motor complications. Experimental therapies have tried to restore striatal dopamine by gene-based and cell-based approaches, and most recently, aggregation and cellular transport of α-synuclein have become therapeutic targets. One of the greatest current challenges is to identify markers for prodromal disease stages, which would allow novel disease-modifying therapies to be started earlier

Visual tests predict dementia risk in Parkinson's 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

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

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

Assessing cognitive dysfunction in Parkinson’s: 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 visuoperceptual 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 visuoperceptual tests. Specifically, they were worse at identifying skewed images (P <.0001); at detecting hidden objects (P 5.0039); at identifying objects in peripheral vision (P <.0001); and at detecting biological motion (P 5.0065). 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 defi- cits 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