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Objective: It is hypothesized that narcolepsy type 1 (NT1) develops in genetically susceptible people who encounter environmental triggers leading to immune-mediated hypocretin-1 deficiency. The pathophysiologies of narcolepsy type 2 (NT2) and idiopathic hypersomnia (IH) remain unknown. The main aim of this study was to collect all reported immunological events before onset of a central disorder of hypersomnolence., Methods: Medical records of 290 people with NT1, and 115 with NT2 or IH were retrospectively reviewed to extract infection and influenza vaccination history. Prevalence, distribution of immunological events, and time until hypersomnolence onset were compared between NT1 and the combined group of NT2 and IH., Results: Immunological events were frequently reported before hypersomnolence disorder onset across groups. Flu and H1N1 influenza vaccination were more common in NT1, and Epstein-Barr virus and other respiratory and non-respiratory infections in NT2 and IH. Distributions of events were comparable between NT2 and IH. Rapid symptom onset within one month of infection was frequent across groups, especially after flu infection in NT1. Hypersomnolence disorder progression after an immunological event was reported in ten individuals., Conclusions: Our findings suggest a variety of immunological triggers potentially related to NT1, including H1N1 influenza infection or vaccination, infection with other flu types, and other respiratory and non-respiratory infections. Frequent reports of immunological events (other than those reported in NT1) immediately prior to the development of NT2 and IH support the specificity of triggers for NT1, and open important new research avenues into possible underlying immunological mechanisms in NT2 and IH., Competing Interests: Declaration of competing interest The authors declare the following financial interests/personal relationships which may be considered as potential competing interests: Lammers GJ reports a relationship with Alkermes plc that includes: consulting or advisory. Lammers GJ reports a relationship with Takeda Pharmaceutical Company Limited that includes: consulting or advisory. Lammers GJ reports a relationship with Bioprojet that includes: consulting or advisory. Lammers GJ reports a relationship with Jazz Pharmaceuticals plc that includes: consulting or advisory. Fronczek R reports a relationship with Takeda Pharmaceutical Company Limited that includes: consulting or advisory. Fronczek R reports a relationship with Bioprojet that includes: consulting or advisory, funding grants, and speaking and lecture fees. Fronczek R reports a relationship with Jazz Pharmaceuticals plc that includes: funding grants. Khatami R reports a relationship with Neuraxpharm that includes: consulting or advisory. Khatami R reports a relationship with Idorsia Pharmaceuticals Ltd that includes: consulting or advisory. If there are other authors, they declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 The Authors. Published by Elsevier B.V. All rights reserved.)

Study Objectives: To review the Maintenance of Wakefulness Test (MWT) as assessment of daytime sleepiness in the evaluation of treatment effects and driving fitness in central disorders of hypersomnolence (CDH)., Methods: We performed a scoping review of studies using the MWT in patients with CDH (i.e. narcolepsy types 1 and 2, and idiopathic hypersomnia). N = 20 articles were included, comprising 683 patients and 129 controls. MWT effect sizes were compared to the Clinical Global Impression (GCI) scale and the Epworth Sleepiness Scale (ESS). MWT sleep latency was correlated to objective driving performances. The role of motivation was evaluated by comparing MWTs of treatment studies (low motivation) to driving fitness studies (high motivation to stay awake). Healthy controls were compared to norm values., Results: MWT and CGI were both impacted by the same treatment; however, the MWT has higher effect sizes and was more sensitive to measure these effects. The MWT correlated fairly to moderately (ρ = -0.26 to -0.56; p ≤ .05) to objective driving performance. Motivation played a major role on MWT sleep latencies (d = 0.76 to 1.43; p ≤ .001). Current norm values may not be valid, as sleep latency may be impacted by age., Conclusions: The MWTs applicability to measure treatment effects in CDH was confirmed, but age-adjusted norm values are needed. For a more complete evaluation of EDS it should be combined with subjective measures. Its reliability for driving fitness evaluation is insufficient, and motivation plays a major role. To predict or monitor driving performance in CDH, valid and easy methods should be developed., (© The Author(s) 2022. Published by Oxford University Press on behalf of Sleep Research Society. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Background and Objectives: Recent studies fueled doubts as to whether all currently defined central disorders of hypersomnolence are stable entities, especially narcolepsy type 2 and idiopathic hypersomnia. New reliable biomarkers are needed, and the question arises of whether current diagnostic criteria of hypersomnolence disorders should be reassessed. The main aim of this data-driven observational study was to see whether data-driven algorithms would segregate narcolepsy type 1 and identify more reliable subgrouping of individuals without cataplexy with new clinical biomarkers., Methods: We used agglomerative hierarchical clustering, an unsupervised machine learning algorithm, to identify distinct hypersomnolence clusters in the large-scale European Narcolepsy Network database. We included 97 variables, covering all aspects of central hypersomnolence disorders such as symptoms, demographics, objective and subjective sleep measures, and laboratory biomarkers. We specifically focused on subgrouping of patients without cataplexy. The number of clusters was chosen to be the minimal number for which patients without cataplexy were put in distinct groups., Results: We included 1,078 unmedicated adolescents and adults. Seven clusters were identified, of which 4 clusters included predominantly individuals with cataplexy. The 2 most distinct clusters consisted of 158 and 157 patients, were dominated by those without cataplexy, and among other variables, significantly differed in presence of sleep drunkenness, subjective difficulty awakening, and weekend-week sleep length difference. Patients formally diagnosed as having narcolepsy type 2 and idiopathic hypersomnia were evenly mixed in these 2 clusters., Discussion: Using a data-driven approach in the largest study on central disorders of hypersomnolence to date, our study identified distinct patient subgroups within the central disorders of hypersomnolence population. Our results contest inclusion of sleep-onset REM periods in diagnostic criteria for people without cataplexy and provide promising new variables for reliable diagnostic categories that better resemble different patient phenotypes. Cluster-guided classification will result in a more solid hypersomnolence classification system that is less vulnerable to instability of single features., (Copyright © 2022 The Author(s). Published by Wolters Kluwer Health, Inc. on behalf of the American Academy of Neurology.)

The classification of the central disorders of hypersomnolence has undergone multiple iterations in an attempt to capture biologically meaningful disease entities in the absence of known pathophysiology. Accumulating data suggests that further refinements may be necessary. At the 7th International Symposium on Narcolepsy, a group of clinician-scientists evaluated data in support of keeping or changing classifications, and as a result suggest several changes. First, idiopathic hypersomnia with long sleep durations appears to be an identifiable and meaningful disease subtype. Second, idiopathic hypersomnia without long sleep time and narcolepsy without cataplexy share substantial phenotypic overlap and cannot reliably be distinguished with current testing, and so combining them into a single disease entity seems warranted at present. Moving forward, it is critical to phenotype patients across a wide variety of clinical and biological features, to aid in future refinements of disease classification., (© Sleep Research Society 2020. Published by Oxford University Press on behalf of the Sleep Research Society.)

Study Objectives: Sleep state misperception is common in various sleep disorders, especially in chronic insomnia with a prevalence ranging between 9-50%. Most prior studies used nocturnal polysomnography (PSG) for the identification of sleep state misperception during nighttime. Our objective was to assess sleep state misperception during daytime in people with sleep disorders with excessive daytime sleepiness (EDS)., Methods: In this prospective observational study, we assessed the occurrence of, and factors influencing sleep state misperception in consecutive patients undergoing a routine multiple sleep latency test (MSLT) in a tertiary sleep-wake centre included between 2014 and 2017. Mixed models were applied to assess the influence of patients' clinical data on sleep state perception., Results: People with narcolepsy type 1 (NT1, n = 33) and type 2 (NT2, n = 14), idiopathic hypersomnia (IH, n = 56), obstructive sleep apnea (OSA, n = 31) and insufficient sleep syndrome (ISS, n = 31) were included. The prevalence of both classical and reverse sleep state misperception did not differ between the sleep disorders (mean 25%, range 8-37%) after correction for sleep stage, sleep onset latency and age. Longer sleep onset latency and reaching only non-rapid eye movement (REM) sleep stage 1 were significant predictors for classical sleep state misperception., Conclusions: Sleep state misperception is common in people with NT1 and NT2, IH, OSA, and ISS. Classical sleep state misperception is more frequent in patients with longer sleep onset latencies who only reach non-REM sleep stage 1 during a nap., (Copyright © 2020 Elsevier B.V. All rights reserved.)