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Saccade alterations are potential early signs of Alzheimer's disease. However, uncertainty persists in how early and reliably automated saccade recording systems detect impairments. This multicenter pathophysiological case-control transversal study explored saccade execution in carefully diagnosed amnestic mild cognitive impairment patients fulfilling research criteria for prodromal Alzheimer's disease (n = 29), as compared to both aged-matched mild Alzheimer's disease patients (n = 23) and controls (n = 27). Auto-coded saccades from horizontal (gap) vertical (step) stimulus elicited pro-saccades, and anti-saccade (gap) tasks were compared across the 3 groups. Mild cognitive impairment patients committed significantly more anti-saccade errors compared to controls (46.9 versus 24.3%, p < 0.001). Conventional analyses of the auto-coded stimulus elicited saccades parameters did not distinguish the amnestic mild cognitive impairment from controls or the mild Alzheimer's disease group. However, an offline analysis of manually coded saccade latencies, using resampling statistics did reveal subtle differences among the groups. Analysis of the manually coded data revealed that the mild Alzheimer's disease group had a reliably larger self-corrected error-rate than in amnestic mild cognitive impairment and controls (p = 0.003). Analysis of the manually coded saccade latencies, using more sensitive lognormal bootstrap analysis revealed a continuum, from amnestic mild cognitive impairment to mild Alzheimer's disease, of an increased severity of impaired inhibition of stimulus elicited saccades and correct voluntary saccade initiation. Anti-saccade error rates and psychometric measures of executive and several other cognitive functions were moderately and negatively correlated. Overall, inhibitory impairments in stimulus elicited saccades, characteristic of Alzheimer's disease, may be detected early in presumed prodromal patients using a simple, automated anti-saccade task.

BackgroundBackground: Late-stage parkinsonism and Parkinson's disease (PD) are insufficiently studied population. Although neuropsychiatric symptoms (eg, psychosis, depression, anxiety, behavioral problems) are frequently present, their prevalence and clinical predictors remain unknown. Objective Objective: To determine the prevalence and predictors of neuropsychiatric symptoms in late-stage PD. Methods Methods: We conducted a multinational study of patients with PD with ≥7 years disease duration and either a Hoehn and Yahr stage ≥4 or a Schwab and England score ≤ 50% in the on stage. Neuropsychiatric symptoms were assessed through interviews with carers using the Neuropsychiatric Inventory, with a frequency × severity score ≥ 4, indicating clinically relevant symptoms. The determinants analyzed were demographic characteristics, medication, and motor and nonmotor symptoms. Univariate and multivariate logistic analyses were performed on predictors of clinically relevant neuropsychiatric symptoms. Results Results: A total of 625 patients were recruited in whom the Neuropsychiatric Inventory could be completed. In 92.2% (576/625) of the patients, at least 1 neuropsychiatric symptom was present, and 75.5% (472/625) had ≥1 clinically relevant symptom. The most common clinically relevant symptoms were apathy (n = 242; 38.9%), depression (n = 213; 34.5%), and anxiety (n = 148; 23.8%). The multivariate analysis revealed unique sets of predictors for each symptom, particularly the presence of other neuropsychiatric features, cognitive impairment, daytime sleepiness. Conclusion Conclusion:Neuropsychiatric symptoms are common in late-stage PD. The strongest predictors are the presence of other neuropsychiatric symptoms. Clinicians involved in the care for patients with late-stage PD should be aware of these symptoms in this specific disease group and proactively explore other psychiatric comorbidities once a neuropsychiatric symptom is recognized.

AK5-Abs should be systematically considered in aged patients with subacute anterograde amnesia. Recognition of this disorder is important to develop new treatment strategies to prevent irreversible limbic damage.

Multiple system atrophy (MSA) is a rare and fatal neurodegenerative disorder that is characterized by a variable combination of parkinsonism, cerebellar impairment, and autonomic dysfunction. Some symptomatic treatments are available while neuroprotection or disease-modification remain unmet treatment needs. The pathologic hallmark is the accumulation of aggregated alpha-synuclein (α-syn) in oligodendrocytes forming glial cytoplasmic inclusions, which qualifies MSA as synucleinopathy together with Parkinson's disease and dementia with Lewy bodies. Despite progress in our understanding of the pathogenesis of MSA, the origin of α-syn aggregates in oligodendrocytes is still a matter of an ongoing debate. We critically review here studies published in the field over the past 5 years dealing with pathogenesis, genetics, clinical signs, biomarker for improving diagnostic accuracy, and treatment development.

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Disease-modifying treatments are currently being trialed in multiple system atrophy (MSA). 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 in multiple system atrophy have been limited. Therefore, neurofilament light chain is not yet routinely used as an outcome measure in MSA. 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 multicentre European set-up. Plasma and cerebrospinal fluid 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; ROC 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 NfL 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 NfL 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.