The Swiss Narcolepsy Network (SNaNe)

The central disorders of hypersomnolence (CDH) manifest with daytime sleepiness, often accompanied by cognitive symptoms. Objective tests characterizing cognitive dysfunction may have diagnostic utility. Further, because some people with CDH report worsening cognition upon awakening, cognitive testing before and after napping may provide additional diagnostic information. Patients with CDH with idiopathic hypersomnia (n = 76), narcolepsy type 1 (n = 19), narcolepsy type 2 (n = 22), and self-reported excessive daytime sleepiness not meeting current diagnostic criteria (n = 76) and nonsleepy controls (n = 33) underwent testing with the Psychomotor Vigilance Test (PVT), a 10-minute reaction-time test. A subset of participants underwent repeat testing during a Multiple Sleep Latency Test, before and immediately after naps 2 and 4. Most PVT metrics were significantly better in controls than in patients with CDH. Minimal group differences in PVT performance were observed by CDH diagnosis. PVT performance was weakly correlated to Epworth Sleepiness Scale and Multiple Sleep Latency Test mean sleep latency in the CDH group. Before and after naps, PVT metrics were minimally different for controls, while PVT performance generally worsened following naps in the CDH group, with significant worsening compared with controls for nap 2 mean, median, lapses, and fastest 10% of responses and nap 4 lapses and slowest 10% of responses. Change in performance did not differ based on CDH diagnostic group for any metric on either nap. The PVT, at baseline and following a short nap, may provide adjunctive diagnostic utility in separating individuals with CDH from controls. Trotti LM, Saini P, Bremer E, etal. The Psychomotor Vigilance Test as a measure of alertness and sleep inertia in people with central disorders of hypersomnolence. J Clin Sleep Med. 2022;18(5):1395-1403.

Central disorders of hypersomnolence (CDoH), including the primary hypersomnolence disorders of narcolepsy type 1 (NT1), narcolepsy type 2 (NT2), idiopathic hypersomnia (IH), and Kleine-Levin syndrome (KLS), as well as secondary hypersomnolence disorders, represent an underdiagnosed and under-treated population. Continuing advancements in understanding and treating CDoH rely on an understanding of the patient and caregiver experience. To address this need, a community-led, patient-owned online research study was launched by the nonprofit organizations Sleep Consortium and Global Genes, using the RARE-X research platform. An expert working group of stakeholders with expertise in hypersomnolence disorders, including clinicians, therapy developers, and patient advocates, was convened to identify key patient- and caregiver-reported clinical outcome measures essential for evaluating CDoH symptoms and impacts. These clinical outcome measures have been implemented as part of an online direct-to-patient study. The measures chosen by the Sleep Consortium Expert Working Group are presented here with the hope of supporting the standardization of clinical outcome assessments being used in CDoH research, especially for primary hypersomnolence disorders.

Central disorders of hypersomnolence - A narrative review on current and potential biomarkers.

Background and ObjectivesRecent 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.MethodsWe 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.ResultsWe 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.DiscussionUsing 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.

Introduction Narcolepsy and other central disorders of hypersomnolence are conditions that often present challenging diagnostic and management dilemmas for clinicians. Inspired by the example of the Oncology Tumor Board system, we established a multidisciplinary board to aid in managing these complex sleep disorders with the specific goals of enhancing patient care while also offering additional educational opportunities for trainees. Here we present our initial experience with this Hypersomnia Board. Methods Beginning in early 2022, clinical practitioners from various disciplines relevant to the care of hypersomnia patients were recruited for board participation. Participants represent sleep medicine, psychiatry, neurology, clinical psychology, and pharmacy. Board meetings are held virtually once a month. Cases are selected for presentation from the participants’ respective clinics and are presented by the treating physicians. Outcomes of the discussion including any recommended changes to the management plan are documented in the patient’s medical record. Results To date, 14 hypersomnia cases have been presented to the board for discussion. Clinical dilemmas prompting board discussion have included refractory daytime sleepiness despite standard therapies, uncertainty related to a previous narcolepsy diagnosis, confounding mental health issues, or medication side effects. Etiology of hypersomnia was thought to be narcolepsy type 1 in 6/14 patients, NT2 in 4/14, idiopathic hypersomnia in 2/14, and obstructive sleep apnea (primary or co-morbid) in 6/14. Comorbid mental illness was common in the cases discussed (PTSD in 5/14, depression in 7/14, both in 2/14), as was concomitant OSA. Board discussion led to recommendations for medication changes in 4/14 and to other interventions (such as earlier referral to mental health specialists) or additional diagnostic testing in the remainder of patients. Clinicians involved including trainees have reported satisfaction with the opportunity to better collaborate on management of these complex cases and the added exposure to challenging hypersomnia cases. Conclusion The management of complex and relatively rare sleep disorders such as narcolepsy and other central disorders of hypersomnolence often requires multidisciplinary input, which our Hypersomnia Board has been able to facilitate. Further research is needed to assess the impact on patient-centered outcomes and on improving access to coordinated care for these disorders. Support (if any) None

The goals of this article are to describe the clinical approach to and management of patients with central disorders of hypersomnolence, and to understand and differentiate available diagnostic tools. Updated clinical practice guidelines for the treatment of central disorders of hypersomnolence and narcolepsy specifically highlight new treatment options. Approval for a lower-sodium oxybate formulation that contains 92% less sodium than the standard sodium oxybate for the treatment of narcolepsy and idiopathic hypersomnia adds to the number of medications available for these disorders, allowing for a more tailored management of symptoms. Central disorders of hypersomnolence are characterized by excessive daytime sleepiness that impacts daily functions. These disorders can be differentiated by obtaining a detailed clinical sleep history and by a thoughtful interpretation of sleep diagnostic testing. Tailoring treatment approaches to meet the needs of individuals and accounting for medical and psychiatric comorbidities may improve quality of life.

The international Swiss Primary Hypersomnolence and Narcolepsy Cohort Study (iSPHYNCS) is a multicentre study aimed at identifying novel biomarkers for central disorders of hypersomnolence (CDH). We analysed questionnaires and metadata to uncover distinct clusters of participants and explore phenotypic variability within CDH. Data were collected from 227 patients with CDH and 33 healthy controls. Participants completed validated clinical questionnaires and study-specific questions addressing CDH-related symptoms such as excessive daytime sleepiness, fatigue, cataplexy, disrupted sleep, and sleep paralysis. Demographic metadata (age, gender, BMI) were included. After excluding participants with missing over 30% of data (n = 40), missing values were imputed using a multiple random forest algorithm. A robust clustering pipeline was employed: (1) random sampling of 60% of the dataset, (2) dimensionality reduction via UMAP, (3) K-means clustering, and (4) consensus clustering across 500 iterations. Post hoc analysis was performed to identify biomarkers in data not used for clustering. We identified four distinct clusters. One predominantly comprised healthy controls, while another primarily contained individuals with narcolepsy type 1 (NT1). Two clusters represented predominantly the narcolepsy borderland group (NBL), with one distinctly characterised by higher symptom severity and psychiatric comorbidities. The clustering pipeline produced reproducible results, with the NT1 and healthy control clusters serving as internal validation. The differentiation between the two NBL clusters aligns with prior studies, suggesting a possible NBL subtype marked by increased fatigue and psychiatric comorbidities. These findings emphasise the phenotypic heterogeneity of CDH and the potential for cluster-based approaches in management. Trial Registration: ClinicalTrials.gov identifier: NCT04330963.

Background and purposeThe diagnosis of sleep–wake disorders (SWDs) is challenging because of the existence of only few accurate biomarkers and the frequent coexistence of multiple SWDs and/or other comorbidities. The aim of this study was to assess in a large cohort of well‐characterized SWD patients the potential of a data‐driven approach for the identification of SWDs.MethodsWe included 6958 patients from the Bernese Sleep Registry and 300 variables/biomarkers including questionnaires, results of polysomnography/vigilance tests, and final clinical diagnoses. A pipeline, based on machine learning, was created to extract and cluster the clinical data. Our analysis was performed on three cohorts: patients with central disorders of hypersomnolence (CDHs), a full cohort of patients with SWDs, and a clean cohort without coexisting SWDs.ResultsA first analysis focused on the cohort of patients with CDHs and revealed four patient clusters: two clusters for narcolepsy type 1 (NT1) but not for narcolepsy type 2 or idiopathic hypersomnia. In the full cohort of SWDs, nine clusters were found: four contained patients with obstructive and central sleep apnea syndrome, one with NT1, and four with intermixed SWDs. In the cohort of patients without coexisting SWDs, an additional cluster of patients with chronic insomnia disorder was identified.ConclusionsThis study confirms the existence of clear clusters of NT1 in CDHs, but mainly intermixed groups in the full spectrum of SWDs, with the exception of sleep apnea syndromes and NT1. New biomarkers are needed for better phenotyping and diagnosis of SWDs.

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).

ObjectiveTo evaluate the reliability of actigraphy to distinguish the features of estimated daytime and nighttime sleep between patients with central disorders of hypersomnolence and healthy controls. MethodsThirty-nine drug-naïve patients with Narcolepsy Type 1, twenty-four drug-naïve patients with Idiopathic Hypersomnia, and thirty age- and sex- matched healthy controls underwent seven days of actigraphic and self-report monitoring of sleep/wake behavior. The following variables were examined: estimated time in bed (eTIB), estimated total sleep time, estimated sleep latency (eSOL), estimated sleep efficiency, estimated wake after sleep onset, number of estimated awakenings (eAwk), number of estimated awakenings longer than 5 minutes, estimated sleep motor activity (eSMA), number of estimated naps, mean duration of the longest estimated nap (eNapD), and daytime motor activity. ResultsAll actigraphic parameters significantly differentiated the three groups, except eTIB and eSOL. A discriminant score computed combining actigraphic parameters from nighttime (eSMA, eAwk) and daytime (eNapD) periods showed a wide area under the curve (0.935) and a good balance between positive (95%) and negative predictive (87%) values in Narcolepsy Type 1 cases. ConclusionActigraphy provided a reliable objective measurement of sleep quality and daytime napping behavior able to distinguish central disorders of hypersomnolence and in particular Narcolepsy Type 1. The nycthemeral profile, combined with a careful clinical evaluation, may be an ecological information, useful to track disease course.

HLA Subtype Distribution in Central Disorders of Hypersomnolence and Relationship of HLA Typing with Clinical and Electrophysiological Findings in Patients with Excessive Daytime Sleepiness - Turkish Journal of Sleep Medicine

Overview of Central Disorders of Hypersomnolence

Narcolepsy and the Hypersomnias

An autoimmune-mediated process in the pathophysiology of narcolepsy type 1 (NT1) is highly suspicious, if this pathomechanism is transferable to other types of central disorders of hypersomnolence (CDH), is still controversial. The association of NT1 with HLA class II system implicates a T-cell-mediated autoimmunity, in which helper CD4+ T-cells and cytotoxic CD8+ T-cells may be pathogenic. This study aimed to identify specific immune profiles in peripheral blood (PB) and cerebrospinal fluid (CSF) in different types of CDH. Forty-three people with polysomnographically confirmed CDH (24 idiopathic hypersomnia [IH], 12 NT1, and 7 NT2) were compared with 24 healthy controls (HC). PB and CSF were analyzed with multiparameter flow cytometry to distinguish between subclasses of peripheral and intrathecal immune cells and specific surface markers of T-cells. The overall proportion of helper CD4+ T-cells and cytotoxic CD8+ T-cells in PB and CSF did not differ between the patients and HC. Activated HLA-DR+ CD4+ T-cells and HLA-DR+ CD8+ T-cells in PB and CSF both in NT1, NT2 and IH were significantly increased compared with HC. A significant correlation of HLA-DR+ CD4+- and HLA-DR+ CD8+ T-cells with higher amounts of excessive daytime sleepiness was found in the NT1 and IH groups, indicating an association of activated T-cells in the central nervous system with an increase in sleepiness. These findings provide further evidence of a T-cell-mediated autoimmunity not only in NT1, but also in NT2 and IH. Moreover, the identification of activated cytotoxic CD8+ T-cells further supports the evidence of T-cell-mediated neuronal damage, which has previously been suggested in NT1.

The diagnosis of narcolepsy type 1 (NT1) currently requires the multiple sleep latency test (MSLT), or a nocturnal sleep-onset REM period (SOREMP) combined with typical cataplexy, or alternatively the determination of CSF hypocretin-1 (CSF-hcrt-1) deficiency. We evaluated the 24-hour polysomnography (PSG) recordings in adult and pediatric patients as an alternative diagnostic tool. Patients of any age, referred to the narcolepsy center of a university hospital for suspected central disorder of hypersomnolence (CDH), were consecutively recruited between 2013 and 2022. Participants underwent 2 days (day1-night1-day2-night2) of continuous dynamic PSG followed by MSLT. When consent was given, CSF-hcrt-1 was measured. The accuracy of 24-hour PSG variables from night1 and day2 (index test) was assessed with receiver operating characteristic (ROC) curve analysis in identifying NT1 based on current criteria (applied to night2-PSG, MSLT, and CSF-hcrt1). The markers with area under the curve (AUC) ≥0.75 were then tested in adults and children, separately, and to diagnose NT1 and narcolepsy type 2 (NT2) in different scenarios. Eight hundred seven patients (30.1% pediatric, 52.4% male) were included, and 709 had CSF-hcrt-1 measured. According to the standard criteria, 322 were diagnosed with NT1 (mean age 26.7 ± 17.1 years, 40.4% pediatric, 54.0% male) and 484 with non-NT1 (mean age 32.7 ± 16.5 years, 23.3% pediatric, 51.3% male), encompassing 31 with NT2, 163 with idiopathic hypersomnia, and 281 with other diagnoses. Detecting SOREMP ≥1 during daytime resulted in AUC = 0.84 (95% CI 0.82-0.87), with 84.4% sensitivity and 84.5% specificity for NT1. Performance was superior to all nighttime-PSG measures (p < 0.001) including nighttime-SOREMP (AUC = 0.77, 95% CI 0.74-0.80; sensitivity = 62.1%, specificity = 91.7%) and did not differ from 24-hour SOREMP ≥1 (AUC = 0.85, 95% CI 0.82-0.87; sensitivity = 89.7%, specificity = 80.2%). The combination of daytime-SOREMP ≥1 with cataplexy showed AUC = 0.89 (95% CI 0.86-0.91) for NT1, superior to the combination of nighttime-SOREMP with cataplexy (AUC = 0.78, 95% CI 0.76-0.81, p < 0.001) and similar to MSLT criteria for narcolepsy (AUC = 0.90, 95% CI 0.88-0.92, p = 0.36). Performances were similar in adults and children. Daytime-SOREMP ≥1 identified NT1 and NT2 combined within all CDH with a sensitivity of 80.8% and specificity of 88.0%. The detection of daytime-SOREMP during dynamic 24-hour PSG is more accurate than nighttime-SOREMP for diagnosing narcolepsy and, combined with cataplexy, is comparable with MSLT criteria for the identification of NT1. These results offer the prospect of 24-hour PSG diagnostics for NT1 in the home setting. This study provides Class II evidence that daytime SOREMP during a 24-hour PSG accurately distinguishes NT1 in patients with a clinical history of possible cataplexy from those who do not have NT1.