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Objective biomarkers for Parkinson’s Disease (PD) could aid early and specific diagnosis, effective monitoring of disease progression, and improved design and interpretation of clinical trials. Although alpha-synuclein remains a biomarker candidate of interest, the multifactorial and heterogenous nature of PD highlights the need for a PD biomarker panel. Ideal biomarker candidates include markers that are detectable in easily accessible samples, (ideally blood) and that reflect the underlying pathological process of PD. In the present study, we explored the diagnostic and prognostic PD biomarker potential of the SIMOA neurology 4-plex-A biomarker panel, which included neurofilament light (NFL), glial fibrillary acid protein (GFAP), tau and ubiquitin C-terminal hydrolase L1 (UCHL-1). We initially performed a serum vs plasma comparative study to determine the most suitable blood-based matrix for the measurement of these proteins in a multiplexed assay. The levels of NFL and GFAP in plasma and serum were highly correlated (Spearman rho-0.923, p  < 0.0001 and rho = 0.825, p  < 0.001 respectively). In contrast, the levels of tau were significantly higher in plasma compared to serum samples ( p  < 0.0001) with no correlation between sample type (Spearman p  > 0.05). The neurology 4-plex-A panel, along with plasma alpha-synuclein was then assessed in a cross-sectional cohort of 29 PD patients and 30 controls. Plasma NFL levels positively correlated with both GFAP and alpha-synuclein levels (rho = 0.721, p  < 0.0001 and rho = 0.390, p  < 0.05 respectively). As diagnostic biomarkers, the control and PD groups did not differ in their mean NFL, GFAP, tau or UCHL-1 plasma levels (t test p  > 0.05). As disease state biomarkers, motor severity (MDS-UPDRS III) correlated with increased NFL (rho = 0.646, p  < 0.0001), GFAP (rho = 0.450, p  < 0.05) and alpha-synuclein levels (rho = 0.406, p  < 0.05), while motor stage (Hoehn and Yahr) correlated with increased NFL (rho = 0.455, p  < 0.05) and GFAP (rho = 0.549, p  < 0.01) but not alpha-synuclein levels ( p  > 0.05). In conclusion, plasma was determined to be most suitable blood-based matrix for multiplexing the neurology 4-plex-A panel. Given their correlation with motor features of PD, NFL and GFAP appear to be promising disease state biomarker candidates and further longitudinal validation of these two proteins as blood-based biomarkers for PD progression is warranted.

Freezing of gait (FOG) is a disabling motor symptom experienced by a large proportion of patients with Parkinson’s disease (PD). While it is known that FOG contributes to lower health-related quality of life (HRQoL), previous studies have not accounted for other important factors when measuring the specific impact of this symptom. The aim of this study was to examine FOG and HRQoL while controlling for other factors that are known to impact patient well-being, including cognition, motor severity, sleep disturbance and mood. Two hundred and three patients with idiopathic PD (86 with FOG) were included in the study. All patients were between Hoehn and Yahr stages I–III. A forced entry multiple regression model evaluating the relative contribution of all symptoms was conducted, controlling for time since diagnosis and current dopaminergic treatment. Entering all significantly correlated variables into the regression model accounted for the majority of variance exploring HRQoL. Self-reported sleep–wake disturbances, depressive and anxious symptoms and FOG were individually significant predictors. FOG accounted for the highest amount of unique variance. While sleep–wake disturbance and mood have a significant negative impact on HRQoL in PD, the emergence of FOG represents the most substantial predictor among patients in the earlier clinical stages of disease. This finding presumably reflects the disabling loss of independence and fear of injury associated with FOG and underlines the importance of efforts to reduce this common symptom.

Background Depression is common in older people and is associated with underlying brain change increasing the risk of dementia. Sleep disturbance is frequently reported by those with lifetime depression, however whether circadian misalignment also exists is unclear. We aimed to examine circadian rhythms and sleep associations in older patients with and without lifetime depression. Methods Thirty-four older people meeting DSM-IV criteria for lifetime major depression (mean age = 63.9 years), and 30 healthy controls (mean age = 65.7 years) were recruited. Participants underwent 2-weeks of actigraphy followed by a 3-night protocol including dim light melatonin onset (DLMO) assessment and overnight polysomnography (PSG) for sleep architecture. DLMO and phase angle of entrainment were computed. Results Compared to controls, participants with depression had a significantly longer phase angle of entrainment (6.82 h ± 1.45 vs. 5.87 h ± 1.60, p  = 0.02, Cohens-d = 0.62). A small to moderate yet non-significant difference in DLMO times, with earlier DLMO (34 ± 27 min) observed in depression (20:36 ± 1:48 vs. 21:10 ± 1:48, p  = 0.22, Cohens-d = 0.32). Individuals with depression had longer sleep latency and latency to rapid eye movement sleep than controls (all p  < 0.05). Conclusion Circadian advancement and alterations to the timing of sleep and REM onset are evident in older people with lifetime major depression, despite having only mild residual symptoms. Further research examining the prognostic significance of these changes is warranted as well as chronotherapeutic treatment studies.

Freezing of gait is a devastating symptom of Parkinson's disease (PD) that is exacerbated by the processing of cognitive information whilst walking. To date, no studies have explored the neural correlates associated with increases in cognitive load whilst performing a motor task in patients with freezing. In this experiment, 14 PD patients with and 15 PD patients without freezing of gait underwent 3T fMRI while performing a virtual reality gait task. Directions to walk and stop were presented on the viewing screen as either direct cues or as more cognitively indirect pre-learned cues. Both groups showed a consistent pattern of BOLD response within the Cognitive Control Network during performance of the paradigm. However, a between group comparison revealed that those PD patients with freezing of gait were less able to recruit the bilateral anterior insula, ventral striatum and the pre-supplementary motor area, as well as the left subthalamic nucleus when responding to indirect cognitive cues whilst maintaining a motor output. These results suggest that PD patients with freezing of gait are unable to properly recruit specific cortical and subcortical regions within the Cognitive Control Network during the performance of simultaneous motor and cognitive functions.

Background Recent consensus research criteria have identified a ‘psychiatric onset’ form of prodromal dementia with Lewy bodies (DLB) characterised by prominent late-onset psychiatric symptoms. Although recognised as important to raise the index of diagnostic suspicion, evidence regarding this cohort was deemed too limited to impose formal criteria. We reviewed the published literature on psychiatric-onset DLB to identify key clinical characteristics and evidence gaps to progress our understanding of this entity. Methods Medline, PubMed and Embase were searched for relevant articles containing longitudinal follow-up of patients initially presenting with a psychiatric illness who subsequently developed DLB according to the diagnostic criteria available at the time. Results Two cohort studies (18 and 21 patients) along with 12 case series (13 cases) were identified totalling 52 patients (63% female). Initial psychiatric presentation occurred at a mean of 63 years (range 53–88), with depression being the most frequently reported psychiatric presentation (88%). Psychotic presentations were less common on presentation (11%) but became more prevalent throughout the prodromal period before the diagnosis of DLB (83%). Relapses of the psychiatric disease were common occurring in 94% (32/34) of patients. Parkinsonism, cognitive fluctuations, visual hallucinations, and REM sleep behaviour disorder were uncommonly reported at initial presentation (3.8%). Conclusions Psychiatric-onset DLB is characterized by a female predominant relapsing–remitting psychiatric illness presenting with affective symptoms but later developing psychotic features prior to the onset of DLB. Additional prospective studies including other neurodegenerative cohorts with harmonised assessments are required to inform definitive diagnostic criteria for this condition.

Evidence indicates that dopaminergic medication in Parkinson's disease may impair certain aspects of cognitive function, such as reversal learning. We used functional magnetic resonance imaging in patients with mild Parkinson's disease to investigate the neural site at which L-DOPA acts during reversal learning. Patients were scanned both ON and OFF their normal dopamine-enhancing L-DOPA medication during the performance of a probabilistic reversal learning task. We demonstrate that L-DOPA modulated reversal-related activity in the nucleus accumbens, but not in the dorsal striatum or the prefrontal cortex. These data concur with evidence from studies with experimental animals and indicate an important role for the human nucleus accumbens in the dopaminergic modulation of reversal learning.

There is a growing appreciation of the wide range of sleep–wake disturbances that occur frequently in Parkinson’s disease. These are known to be associated with a range of motor and non-motor symptoms and significantly impact not only on the quality of life of the patient, but also on their bed partner. The underlying causes for fragmented sleep and daytime somnolence are no doubt multifactorial but there is clear evidence for circadian disruption in Parkinson’s disease. This appears to be occurring not only as a result of the neuropathological changes that occur across a distributed neural network, but even down to the cellular level. Such observations indicate that circadian changes may in fact be a driver of neurodegeneration, as well as a cause for some of the sleep–wake symptoms observed in Parkinson’s disease. Thus, efforts are now required to evaluate approaches including the prescription of precision medicine to modulate photoreceptor activation ratios that reflect daylight inputs to the circadian pacemaker, the use of small molecules to target clock genes, the manipulation of orexin pathways that could help restore the circadian system, to offer novel symptomatic and novel disease modifying strategies.

The selection of appropriate outcome measures is fundamental to the design of any successful clinical trial. Although dementia with Lewy bodies (DLB) is one of the most common neurodegenerative conditions, assessment of therapeutic benefit in clinical trials often relies on tools developed for other conditions, such as Alzheimer’s or Parkinson’s disease. These may not be sufficiently valid or sensitive to treatment changes in DLB, decreasing their utility. In this review, we discuss the limitations and strengths of selected available tools used to measure DLB-associated outcomes in clinical trials and highlight the potential roles for more specific objective measures. We emphasize that the existing outcome measures require validation in the DLB population and that DLB-specific outcomes need to be developed. Finally, we highlight how the selection of outcome measures may vary between symptomatic and disease-modifying therapy trials.

Identifying biological factors which contribute to the clinical progression of heterogeneous motor and non-motor phenotypes in Parkinson’s disease may help to better understand the disease process. Several lipid-related genetic risk factors for Parkinson’s disease have been identified, and the serum lipid signature of Parkinson’s disease patients is significantly distinguishable from controls. However, the extent to which lipid profiles are associated with clinical outcomes remains unclear. Untargeted high-performance liquid chromatography-tandem mass spectrometry identified >900 serum lipids in Parkinson’s disease subjects at baseline ( n  = 122), and the potential for machine learning models using these lipids to predict motor and non-motor clinical scores after 2 years ( n  = 67) was assessed. Machine learning models performed best when baseline serum lipids were used to predict the 2-year future Unified Parkinson’s disease rating scale part three (UPDRS III) and Geriatric Depression Scale scores (both normalised root mean square error = 0.7). Feature analysis of machine learning models indicated that species of lysophosphatidylethanolamine, phosphatidylcholine, platelet-activating factor, sphingomyelin, diacylglycerol and triacylglycerol were top predictors of both motor and non-motor scores. Serum lipids were overall more important predictors of clinical outcomes than subject sex, age and mutation status of the Parkinson’s disease risk gene LRRK2 . Furthermore, lipids were found to better predict clinical scales than a panel of 27 serum cytokines previously measured in this cohort (The Michael J. Fox Foundation LRRK2 Clinical Cohort Consortium). These results suggest that lipid changes may be associated with clinical phenotypes in Parkinson’s disease.