The clinical diagnosis of synucleinopathies, including Parkinson’s disease (PD), dementia with Lewy bodies (DLB), and multiple system atrophy (MSA), is challenging, especially at an early disease ...stage, due to the heterogeneous and often non-specific clinical manifestations. The discovery of reliable specific markers for synucleinopathies would consequently be of great aid to the diagnosis and management of these disorders. Real-Time Quaking-Induced Conversion (RT-QuIC) is an ultrasensitive technique that has been previously used to detect self-templating amyloidogenic proteins in the cerebrospinal fluid (CSF) and other biospecimens in prion disease and synucleinopathies. Using a wild-type recombinant α-synuclein as a substrate, we applied RT-QuIC to a large cohort of 439 CSF samples from clinically well-characterized, or post-mortem verified patients with parkinsonism or dementia. Of significance, we also studied patients with isolated REM sleep behavior disorder (iRBD) (
n
= 18) and pure autonomic failure (PAF) (
n
= 28), representing clinical syndromes that are often caused by a synucleinopathy, and may precede the appearance of parkinsonism or cognitive decline. The results show that our RT-QuIC assay can accurately detect α-synuclein seeding activity across the spectrum of Lewy Body (LB)-related disorders (LBD), including DLB, PD, iRBD, and PAF, with an overall sensitivity of 95.3%. In contrast, all but two patients with MSA showed no α-synuclein seeding activity in the applied experimental setting. The analysis of the fluorescence response reflecting the amount of α-synuclein seeds revealed no significant differences between the clinical syndromes associated with LB pathology. Finally, the assay demonstrated 98% specificity in a neuropathological cohort of 101 cases lacking LB pathology. In conclusion, α-synuclein RT-QuIC provides an accurate marker of synucleinopathies linked to LB pathology and may have a pivotal role in the early discrimination and management of affected patients. The finding of no α-synuclein seeding activity in MSA seems to support the current view that MSA and LBD are associated with different conformational strains of α-synuclein.
Narcolepsy is a rare, chronic, and disabling central nervous system hypersomnia; two forms can be recognized: narcolepsy type 1 (NT1) and narcolepsy type 2 (NT2). Its etiology is still largely ...unknown, but studies have reported a strong association between NT1 and HLA, as well as a pathogenic association with the deficiency of cerebrospinal hypocretin-1. Thus, the most reliable pathogenic hypothesis is an autoimmune process destroying hypothalamic hypocretin-producing cells. A definitive cure for narcolepsy is not available to date, and although the research in the field is highly promising, up to now, current treatments have aimed to reduce the symptoms by means of different pharmacological approaches. Moreover, overall narcolepsy symptoms management can also benefit from non-pharmacological approaches such as cognitive behavioral therapies (CBTs) and psychosocial interventions to improve the patients’ quality of life in both adult and pediatric-affected individuals as well as the well-being of their families. In this review, we summarize the available therapeutic options for narcolepsy, including the pharmacological, behavioral, and psychosocial interventions.
Summary Narcolepsy is a sleep disorder characterised by loss of hypothalamic hypocretin (orexin) neurons. The prevalence of narcolepsy is about 30 per 100 000 people, and typical age at onset is ...12–16 years. Narcolepsy is strongly associated with the HLA-DQB1*06:02 genotype, and has been thought of as an immune-mediated disease. Other risk genes, such as T-cell-receptor α chain and purinergic receptor subtype 2Y11, are also implicated. Interest in narcolepsy has increased since the epidemiological observations that H1N1 infection and vaccination are potential triggering factors, and an increase in the incidence of narcolepsy after the pandemic AS03 adjuvanted H1N1 vaccination in 2010 from Sweden and Finland supports the immune-mediated pathogenesis. Epidemiological observations from studies in China also suggest a role for H1N1 virus infections as a trigger for narcolepsy. Although the pathological mechanisms are unknown, an H1N1 virus-derived antigen might be the trigger.
The COVID-19 pandemic has produced unprecedented changes in social, work, and leisure activities, which all have had major impact on sleep and psychological well-being. This study documented the ...prevalence of clinical cases of insomnia, anxiety, and depression and selected risk factors (COVID-19, confinement, financial burden, social isolation) during the first wave of the pandemic in 13 countries throughout the world.
International, multi-center, harmonized survey of 22 330 adults (mean age = 41.9 years old, range 18–95; 65.6% women) from the general population in 13 countries and four continents. Participants were invited to complete a standardized web-based survey about sleep and psychological symptoms during the first wave of the COVID-19 pandemic from May to August 2020.
Clinical insomnia symptoms were reported by 36.7% (95% CI, 36.0–37.4) of respondents and 17.4% (95% CI, 16.9–17.9) met criteria for a probable insomnia disorder. There were 25.6% (95% CI, 25.0–26.2) with probable anxiety and 23.1% (95% CI, 22.5–23.6) with probable depression. Rates of insomnia symptoms (>40%) and insomnia disorder (>25%) were significantly higher in women, younger age groups, and in residents of Brazil, Canada, Norway, Poland, USA, and United Kingdom compared to residents from Asian countries (China and Japan, 8% for disorder and 22%–25% for symptoms) (all Ps < 0.01). Proportions of insomnia cases were significantly higher among participants who completed the survey earlier in the first wave of the pandemic relative to those who completed it later. Risks of insomnia were higher among participants who reported having had COVID-19, who reported greater financial burden, were in confinement for a period of four to five weeks, and living alone or with more than five people in same household. These associations remained significant after controlling for age, sex, and psychological symptoms.
Insomnia, anxiety, and depression were very prevalent during the first wave of the COVID-19 pandemic. Public health prevention programs are needed to prevent chronicity and reduce long-term adverse outcomes associated with chronic insomnia and mental health problems.
•High rates of insomnia symptoms (36.7%) and disorder (17.4%) associated with COVID-19.•High rates of anxiety (25.6%) and depression (23.1%) associated with COVID-19.•People in confinement, living alone or with five or more people, at higher risk for insomnia.•Sleep health education needed to prevent chronic insomnia and adverse health consequences.
Coronavirus disease 2019 (COVID-19) seriously affected the whole of Italy. The extreme virulence and the speed of propagation resulted in restrictions and home confinement. This change was ...immediately perceived by people who found themselves exposed to feelings of uncertainty, fear, anger, stress, and a drastic change in the diurnal but above all nocturnal lifestyle. For these reasons, we aimed to study the quality of sleep and its connection to distress levels and to evaluate how lifestyle changed in the Italian population during the lockdown.
By means of an Internet survey we recruited 6,519 adults during the whole of the COVID-19 lockdown (from March 10-1st phase to May 4-2nd phase). We investigated the sociodemographic and COVID-19-related information and assessed sleep quality using the Medical Outcomes Study-sleep scale (MOS-SS) and mental health with the short form of Depression, Anxiety, and Stress Scales-21 Items (DASS-21). Multiple logistic regression model was used to evaluate the multivariate association between the dependent variable (good sleeper vs. poor sleeper) and all the variables that were significant in the univariate analysis.
A total of 3,562 (55.32%) participants reported poor sleep quality according to the MOS-Sleep Index II score. The multiple binary logistic regression results of poor sleepers revealed several risk factors during the outbreak restrictions: female gender, living in Central Italy, having someone close who died because of COVID-19, markedly changed sleep-wake rhythms characterized by earlier or postponed habitual bedtime, earlier habitual awakening time and reduced number of afternoon naps, and extremely severe levels of stress, anxiety, and depression.
This is the first study designed to understand sleep quality and sleep habits during the whole of the lockdown period in the Italian population that provides more than 6,000 participants in a survey developed specifically for the health emergency related to COVID-19. Our study found that more than half of the Italian population had impaired sleep quality and sleep habits due to elevated psychological distress during the COVID-19 lockdown containment measures. A multidisciplinary action should be undertaken in order to plan appropriate responses to the current crisis caused by the lockdown for the COVID-19 outbreak.
The aim of this European initiative is to facilitate a structured discussion to improve the next edition of the International Classification of Sleep Disorders (ICSD), particularly the chapter on ...central disorders of hypersomnolence.
The ultimate goal for a sleep disorders classification is to be based on the underlying neurobiological causes of the disorders with clear implication for treatment or, ideally, prevention and or healing. The current ICSD classification, published in 2014, inevitably has important shortcomings, largely reflecting the lack of knowledge about the precise neurobiological mechanisms underlying the majority of sleep disorders we currently delineate. Despite a clear rationale for the present structure, there remain important limitations that make it difficult to apply in routine clinical practice. Moreover, there are indications that the current structure may even prevent us from gaining relevant new knowledge to better understand certain sleep disorders and their neurobiological causes.
We suggest the creation of a new consistent, complaint driven, hierarchical classification for central disorders of hypersomnolence; containing levels of certainty, and giving diagnostic tests, particularly the MSLT, a weighting based on its specificity and sensitivity in the diagnostic context.
We propose and define three diagnostic categories (with levels of certainty):
1/“Narcolepsy” 2/“Idiopathic hypersomnia”, 3/“Idiopathic excessive sleepiness” (with subtypes).
Analysis of sleep for the diagnosis of sleep disorders such as Type-1 Narcolepsy (T1N) currently requires visual inspection of polysomnography records by trained scoring technicians. Here, we used ...neural networks in approximately 3,000 normal and abnormal sleep recordings to automate sleep stage scoring, producing a hypnodensity graph-a probability distribution conveying more information than classical hypnograms. Accuracy of sleep stage scoring was validated in 70 subjects assessed by six scorers. The best model performed better than any individual scorer (87% versus consensus). It also reliably scores sleep down to 5 s instead of 30 s scoring epochs. A T1N marker based on unusual sleep stage overlaps achieved a specificity of 96% and a sensitivity of 91%, validated in independent datasets. Addition of HLA-DQB1*06:02 typing increased specificity to 99%. Our method can reduce time spent in sleep clinics and automates T1N diagnosis. It also opens the possibility of diagnosing T1N using home sleep studies.
The lack of quantitative criteria for identifying insomnia using actigraphy represents an unresolved limit for the use of actigraphy in a clinical setting. The current study was conducted to evaluate ...the most efficient actigraphic parameter in the assessment of insomnia and to suggest preliminary quantitative actigraphic criteria (QAC).
Performing a retrospective study we recovered 408 actigraphic records from 3 sleep measure databases: 2 regarding insomnia patients (n = 126) and one normal sleepers (n = 282). We compared the 2 samples analyzing the following actigraphic sleep parameters: time in bed (TIB), sleep onset latency (SOL), total sleep time (TST), wake after sleep onset (WASO), sleep efficiency percentage (SE%), number of awakenings longer than 5 minutes (NA > 5) and mean motor activity (MA). Moreover, a linear discriminant function (LDF) was developed to identify and combine the most useful actigraphic sleep parameters to separate insomnia patients from normal sleepers. Using Youden index we calculated the preliminary QAC for each actigraphic sleep parameter and for LDF. Receiver operator characteristic (ROC) curves for classifying the accuracy of QAC were performed.
All sleep parameters recorded by actigraphy significantly differentiated the 2 groups, except TIB. An LDF analysis showed that the most useful combination of actigraphic sleep parameters to assess insomnia was TST, SOL, and NA > 5, which obtained the best ROC and the best balance between positive and negative predictive values compared to any single actigraphic parameter.
Actigraphy provided a satisfactory objective measurement of sleep quality in insomnia patients. The combination of TST, SOL, and NA > 5 proved the best way to assess insomnia using actigraphy. Acknowledging that the lack of a technological standard and some methodological limitations prevent us generalizing our results, we recommend additional studies on larger populations using different actigraph models.
Several studies have confirmed the α-synuclein real-time quaking-induced conversion (RT-QuIC) assay to have high sensitivity and specificity for Parkinson's disease. However, whether the assay can be ...used as a robust, quantitative measure to monitor disease progression, stratify different synucleinopathies and predict disease conversion in patients with idiopathic REM sleep behaviour disorder remains undetermined. The aim of this study was to assess the diagnostic value of CSF α-synuclein RT-QuIC quantitative parameters in regard to disease progression, stratification and conversion in synucleinopathies. We performed α-synuclein RT-QuIC in the CSF samples from 74 Parkinson's disease, 24 multiple system atrophy and 45 idiopathic REM sleep behaviour disorder patients alongside 55 healthy controls, analysing quantitative assay parameters in relation to clinical data. α-Synuclein RT-QuIC showed 89% sensitivity and 96% specificity for Parkinson's disease. There was no correlation between RT-QuIC quantitative parameters and Parkinson's disease clinical scores (e.g. Unified Parkinson's Disease Rating Scale motor), but RT-QuIC positivity and some quantitative parameters (e.g. Vmax) differed across the different phenotype clusters. RT-QuIC parameters also added value alongside standard clinical data in diagnosing Parkinson's disease. The sensitivity in multiple system atrophy was 75%, and CSF samples showed longer T50 and lower Vmax compared to Parkinson's disease. All RT-QuIC parameters correlated with worse clinical progression of multiple system atrophy (e.g. change in Unified Multiple System Atrophy Rating Scale). The overall sensitivity in idiopathic REM sleep behaviour disorder was 64%. In three of the four longitudinally followed idiopathic REM sleep behaviour disorder cohorts, we found around 90% sensitivity, but in one sample (DeNoPa) diagnosing idiopathic REM sleep behaviour disorder earlier from the community cases, this was much lower at 39%. During follow-up, 14 of 45 (31%) idiopathic REM sleep behaviour disorder patients converted to synucleinopathy with 9/14 (64%) of convertors showing baseline RT-QuIC positivity. In summary, our results showed that α-synuclein RT-QuIC adds value in diagnosing Parkinson's disease and may provide a way to distinguish variations within Parkinson's disease phenotype. However, the quantitative parameters did not correlate with disease severity in Parkinson's disease. The assay distinguished multiple system atrophy patients from Parkinson's disease patients and in contrast to Parkinson's disease, the quantitative parameters correlated with disease progression of multiple system atrophy. Our results also provided further evidence for α-synuclein RT-QuIC having potential as an early biomarker detecting synucleinopathy in idiopathic REM sleep behaviour disorder patients prior to conversion. Further analysis of longitudinally followed idiopathic REM sleep behaviour disorder patients is needed to better understand the relationship between α-synuclein RT-QuIC signature and the progression from prodromal to different synucleinopathies.
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