OBJECTIVE AND BACKGROUND: Health-related quality of life (HRQoL) is reduced in narcolepsy type 1 (NT1), but proper information on HRQoL in narcolepsy type 2 (NT2) and idiopathic hypersomnia (IH) is lacking. This study examines HRQoL of NT1, NT2, IH, and healthy controls (HC) and assesses the HRQoL associates in these diseases. PATIENTS AND METHODS: 117 adults (64 NT1, 22 NT2, 31 IH; 61.5 % women; 38.3 ± 12.0 years; 71.8 % treated) and 41 HC (53.7 % women; 35.9 ± 9.6 years) completed questionnaires assessing sleepiness, fatigue, symptoms severity, sleep inertia, depressive and anxiety symptoms, HRQoL, and underwent a semi-structured interview. Data were analyzed using the Mann-Whitney and Kruskal-Wallis tests, Spearman's correlation coefficient, and regression analysis. RESULTS: HRQoL of NT1, NT2, and IH, separately, was poorer compared to HC (p < 0.001). According to the 36-Item Short Form Health Survey, the mental HRQoL was more impaired in NT2 and IH than NT1 (p < 0.05) in association with more pronounced depressive symptoms (p < 0.01; p < 0.05, respectively) and sleep inertia (p < 0.01; p < 0.01, respectively). Psychiatric disorders were more prevalent in NT2 and IH versus NT1 (p < 0.05). CONCLUSION: HRQoL is reduced in NT1, NT2, and IH, with this reduction being more pronounced in NT2 and IH. Poor mental HRQoL of NT2 and IH was associated both with the severity of depressive symptoms and more intense sleep inertia.

• MeSH
• Depression psychology   MeSH
• Adult MeSH
• Idiopathic Hypersomnia * psychology   MeSH
• Quality of Life * psychology   MeSH
• Middle Aged MeSH
• Humans MeSH
• Narcolepsy * psychology   MeSH
• Surveys and Questionnaires MeSH
• Severity of Illness Index MeSH
• Fatigue psychology   MeSH
• Anxiety psychology   MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Female MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH

STUDY OBJECTIVES: Microbial antigens can elicit an immune response leading to the production of autoantibodies cross-reacting with autoantigens. Still, their clinical significance in human sera in the context of brain diseases is unclear. Therefore, assessment of natural autoantibodies reacting with their neuropeptides may elucidate the autoimmune etiology of central hypersomnias. The study aims to determine whether serum autoantibody levels differ in patients with different types of central hypersomnias (narcolepsy type 1 and 2, NT1 and NT2; idiopathic hypersomnia, IH) and healthy controls and if the differences could suggest the participation of autoantibodies in disease pathogenesis. METHODS: Sera from 91 patients with NT1, 27 with NT2, 46 with IH, and 50 healthy controls were examined for autoantibodies against assorted neuropeptides. Participants were screened using questionnaires related to sleep disorders, quality of life, and mental health conditions. In addition, serum biochemical parameters and biomarkers of microbial penetration through the intestinal wall were determined. RESULTS: A higher prevalence of autoantibodies against neuropeptides was observed only for alpha-melanocytes-stimulating hormone (α-MSH) and neuropeptide glutamic acid-isoleucine (NEI), which differed slightly among diagnoses. Patients with both types of narcolepsy exhibited signs of microbial translocation through the gut barrier. According to the questionnaires, patients diagnosed with NT2 or IH had subjectively worse life quality than patients with NT1. Patients displayed significantly lower levels of bilirubin and creatinine and slightly higher alkaline phosphatase values than healthy controls. CONCLUSIONS: Overall, serum anti-neuronal antibodies prevalence is rare, suggesting that their participation in the pathophysiology of concerned sleep disorders is insignificant. Moreover, their levels vary slightly between diagnoses indicating no major diagnostic significance.

• Keywords
• Autoantibodies, Hypersomnia, Immunity, Narcolepsy, Neuropeptides, Sleepiness,
• MeSH
• Autoantibodies MeSH
• Quality of Life MeSH
• Humans MeSH
• Narcolepsy * epidemiology   MeSH
• Neuropeptides * MeSH
• Disorders of Excessive Somnolence * epidemiology   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• Autoantibodies MeSH
• Neuropeptides * MeSH

In recent years, there has been an increased interest in elucidating the influence of the gut microbiota on sleep physiology. The gut microbiota affects the central nervous system by modulating neuronal pathways through the neuroendocrine and immune system, the hypothalamus-pituitary-adrenal axis, and various metabolic pathways. The gut microbiota can also influence circadian rhythms. In this study, we observed the gut microbiota composition of patients suffering from narcolepsy type 1, narcolepsy type 2, and idiopathic hypersomnia. We did not observe any changes in the alpha diversity of the gut microbiota among patient groups and healthy controls. We observed changes in beta diversity in accordance with Jaccard dissimilarities between the control group and groups of patients suffering from narcolepsy type 1 and idiopathic hypersomnia. Our results indicate that both these patient groups differ from controls relative to the presence of rare bacterial taxa. However, after adjustment for various confounding factors such as BMI, age, and gender, there were no statistical differences among the groups. This indicates that the divergence in beta diversity in the narcolepsy type 1 and idiopathic hypersomnia groups did not arise due to sleep disturbances. This study implies that using metabolomics and proteomics approaches to study the role of microbiota in sleep disorders might prove beneficial.

• Keywords
• Central disorders of hypersomnolence, Gut microbiota, Idiopathic hypersomnia, Microbiota-gut-brain axis, Narcolepsy type 1, Narcolepsy type 2, Sleep,
• MeSH
• Idiopathic Hypersomnia * MeSH
• Humans MeSH
• Narcolepsy * MeSH
• Disorders of Excessive Somnolence * MeSH
• Sleep Wake Disorders * MeSH
• Sleep MeSH
• Gastrointestinal Microbiome * MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH

Narcolepsy type 1 (NT1) is caused by a loss of hypocretin/orexin transmission. Risk factors include pandemic 2009 H1N1 influenza A infection and immunization with Pandemrix®. Here, we dissect disease mechanisms and interactions with environmental triggers in a multi-ethnic sample of 6,073 cases and 84,856 controls. We fine-mapped GWAS signals within HLA (DQ0602, DQB1*03:01 and DPB1*04:02) and discovered seven novel associations (CD207, NAB1, IKZF4-ERBB3, CTSC, DENND1B, SIRPG, PRF1). Significant signals at TRA and DQB1*06:02 loci were found in 245 vaccination-related cases, who also shared polygenic risk. T cell receptor associations in NT1 modulated TRAJ*24, TRAJ*28 and TRBV*4-2 chain-usage. Partitioned heritability and immune cell enrichment analyses found genetic signals to be driven by dendritic and helper T cells. Lastly comorbidity analysis using data from FinnGen, suggests shared effects between NT1 and other autoimmune diseases. NT1 genetic variants shape autoimmunity and response to environmental triggers, including influenza A infection and immunization with Pandemrix®.

• MeSH
• Autoimmunity genetics   MeSH
• Autoimmune Diseases * epidemiology   genetics   MeSH
• Influenza, Human * epidemiology   genetics   MeSH
• Humans MeSH
• Narcolepsy * chemically induced   genetics   MeSH
• Influenza Vaccines * adverse effects   MeSH
• Influenza A Virus, H1N1 Subtype * genetics   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Research Support, N.I.H., Extramural MeSH
• Names of Substances
• Influenza Vaccines * MeSH

Fatigue, depression, and sleep inertia are frequently underdiagnosed manifestations in narcolepsy and idiopathic hypersomnia. Our cross-sectional study design included diagnostic interview accompanied by assessment instruments and aimed to explore how these factors influence disease severity as well as to elucidate any sex predisposition. One hundred and forty-eight subjects (female 63%) were divided into narcolepsy type 1 (NT1; n = 87, female = 61%), narcolepsy type 2 (NT2; n = 22, female = 59%), and idiopathic hypersomnia (IH; n = 39, female = 69%). All subjects completed a set of questionnaires: Epworth Sleepiness Scale (ESS), Hospital Anxiety and Depression Scales (HADS), Fatigue Severity Scale (FSS), and Sleep Inertia Questionnaire (SIQ). In narcoleptic subjects, questionnaire data were correlated with the Narcolepsy Severity Scale (NSS), and in subjects with idiopathic hypersomnia, with the Idiopathic Hypersomnia Severity Scale (IHSS). The highest correlation in narcoleptic subjects was found between NSS and ESS (r = 0.658; p < 0.0001), as well as FSS (r = 0.506; p < 0.0001), while in subjects with idiopathic hypersomnia, the most prominent positive correlations were found between IHSS and SIQ (r = 0.894; p < 0.0001), FSS (r = 0.812; p < 0.0001), HADS depression scale (r = 0.649; p = 0.0005), and HADS anxiety scale (r = 0.528; p < 0.0001). ESS showed an analogic correlation with disease severity (r = 0.606; p < 0.0001). HADS anxiety and depression scores were higher in females (p < 0.05 and p < 0.01), with similar results for FSS and SIQ scales (p < 0.05 for both), and a trend toward higher ESS values in females (p = 0.057). Our study illustrates that more attention should be focused on pathophysiological mechanisms and associations of fatigue, depression, as well as sleep inertia in these diseases; they influence the course of both illnesses, particularly in women.

• Keywords
• depression, disease severity, excessive daytime sleepiness, fatigue, idiopathic hypersomnia, narcolepsy type 1 and 2, sex differences, sleep inertia,
• Publication type
• Journal Article MeSH

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.

• MeSH
• Idiopathic Hypersomnia * diagnosis   MeSH
• Cataplexy * diagnosis   MeSH
• Humans MeSH
• Adolescent MeSH
• Narcolepsy * diagnosis   drug therapy   MeSH
• Disorders of Excessive Somnolence * diagnosis   epidemiology   MeSH
• Cluster Analysis MeSH
• Check Tag
• Humans MeSH
• Adolescent MeSH
• Publication type
• Journal Article MeSH
• Observational Study MeSH
• Research Support, Non-U.S. Gov't MeSH

PURPOSE: Narcolepsy type-1 (NT1) is a rare chronic neurological sleep disorder with excessive daytime sleepiness (EDS) as usual first and cataplexy as pathognomonic symptom. Shortening the NT1 diagnostic delay is the key to reduce disease burden and related low quality of life. Here we investigated the changes of diagnostic delay over the diagnostic years (1990-2018) and the factors associated with the delay in Europe. PATIENTS AND METHODS: We analyzed 580 NT1 patients (male: 325, female: 255) from 12 European countries using the European Narcolepsy Network database. We combined machine learning and linear mixed-effect regression to identify factors associated with the delay. RESULTS: The mean age at EDS onset and diagnosis of our patients was 20.9±11.8 (mean ± standard deviation) and 30.5±14.9 years old, respectively. Their mean and median diagnostic delay was 9.7±11.5 and 5.3 (interquartile range: 1.7-13.2 years) years, respectively. We did not find significant differences in the diagnostic delay over years in either the whole dataset or in individual countries, although the delay showed significant differences in various countries. The number of patients with short (≤2-year) and long (≥13-year) diagnostic delay equally increased over decades, suggesting that subgroups of NT1 patients with variable disease progression may co-exist. Younger age at cataplexy onset, longer interval between EDS and cataplexy onsets, lower cataplexy frequency, shorter duration of irresistible daytime sleep, lower daytime REM sleep propensity, and being female are associated with longer diagnostic delay. CONCLUSION: Our findings contrast the results of previous studies reporting shorter delay over time which is confounded by calendar year, because they characterized the changes in diagnostic delay over the symptom onset year. Our study indicates that new strategies such as increasing media attention/awareness and developing new biomarkers are needed to better detect EDS, cataplexy, and changes of nocturnal sleep in narcolepsy, in order to shorten the diagnostic interval.

• Keywords
• cataplexy, diagnostic delay, machine learning, misdiagnosis, symptom onset,
• Publication type
• Journal Article MeSH

Idiopathic hypersomnia was first described in 1976 under two forms: polysymptomatic, characterized by excessive daytime sleepiness, long and unrefreshing naps, nocturnal sleep of abnormally long duration and signs of sleep drunkenness upon awakening; monosymptomatic, manifested by excessive daytime sleepiness only. Yet, after 45 years, this sleep disorder is still poorly delineated and diagnostic criteria produced by successive International Classifications of Sleep Disorders are far from satisfactory. The first part of this review is a historical account of the successive names and descriptions of idiopathic hypersomnia: monosymptomatic and polysymptomatic idiopathic hypersomnia in 1976; central nervous system idiopathic hypersomnia in 1979; idiopathic hypersomnia in 1990; idiopathic hypersomnia with and without long sleep time in 2005; idiopathic hypersomnia again in 2014; and, within the last few years, the proposal of separating idiopathic hypersomnia into a well-defined subtype, idiopathic hypersomnia with long sleep duration, and a more heterogeneous subtype combining idiopathic hypersomnia without long sleep duration and narcolepsy type 2. The second part is a critical review of both current ICSD-3 diagnostic criteria and clinical features, scales and questionnaires, electrophysiological and circadian control tests, research techniques, currently used to diagnose idiopathic hypersomnia. The third part proposes a diagnostic evaluation of idiopathic hypersomnia, in the absence of biologic markers and of robust electrophysiological diagnostic criteria.

• Keywords
• central disorders of hypersomnolence, idiopathic hypersomnia, idiopathic hypersomnia with long sleep duration, idiopathic hypersomnia with long sleep time, idiopathic hypersomnia without long sleep duration, idiopathic hypersomnia without long sleep time, narcolepsy, narcolepsy type 1 and narcolepsy type 2,
• Publication type
• Journal Article MeSH
• Review MeSH

BACKGROUND: There are limited data available on regional differences in the diagnosis and management of narcolepsy. In order to better understand worldwide trends in clinical assessment and management of narcolepsy, a survey of health-care providers was conducted by the World Sleep Society Narcolepsy task force. METHODS: A total of 146 surveys that included items on the diagnosis and management of narcolepsy were completed by practitioners representing 37 countries. RESULTS: Most of the participants were from Europe, North America, Oceania, Asia and Latin America. A consistent approach to applying the diagnostic criteria of Narcolepsy was documented with the exception of measurement of CSF hypocretin-1, which has limited availability. While the majority of practitioners (58%) reported not using the test, 1% indicated always evaluating CSF hypocretin-1 levels. There was much variability in the availability of currently recommended medications such as sodium oxybate and pitolisant; modafinil and antidepressants were the most commonly used medications. Amphetamines were unavailable in some countries. CONCLUSION: The results of the study highlight clinical and therapeutic realities confronted by worldwide physicians in the management of narcolepsy. While the diagnostic criteria of narcolepsy rely in part on the quantification of CSF hypocretin-1, few physicians reported having incorporated this test into their routine assessment of the condition. Regional differences in the management of narcolepsy appeared to be related to geographic availability and expense of the therapeutic agents.

• Keywords
• CSF hypocretin-1, HLA DQB1∗0602, MSLT, Narcolepsy type-1, Narcolepsy type-2, Narcolepsy—pharmacotherapy,
• MeSH
• Humans MeSH
• Narcolepsy * diagnosis   drug therapy   MeSH
• Orexins MeSH
• Patient Care MeSH
• Polysomnography MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Asia MeSH
• Europe MeSH
• North America MeSH
• Names of Substances
• Orexins MeSH

Increased incidence rates of narcolepsy type-1 (NT1) have been reported worldwide after the 2009-2010 H1N1 influenza pandemic (pH1N1). While some European countries found an association between the NT1 incidence increase and the H1N1 vaccination Pandemrix, reports from Asian countries suggested the H1N1 virus itself to be linked to the increased NT1 incidence. Using robust data-driven modeling approaches, that is, locally estimated scatterplot smoothing methods, we analyzed the number of de novo NT1 cases (n = 508) in the last two decades using the European Narcolepsy Network database. We confirmed the peak of NT1 incidence in 2010, that is, 2.54-fold (95% confidence interval [CI]: [2.11, 3.19]) increase in NT1 onset following 2009-2010 pH1N1. This peak in 2010 was found in both childhood NT1 (2.75-fold increase, 95% CI: [1.95, 4.69]) and adulthood NT1 (2.43-fold increase, 95% CI: [2.05, 2.97]). In addition, we identified a new peak in 2013 that is age-specific for children/adolescents (i.e. 2.09-fold increase, 95% CI: [1.52, 3.32]). Most of these children/adolescents were HLA DQB1*06:02 positive and showed a subacute disease onset consistent with an immune-mediated type of narcolepsy. The new 2013 incidence peak is likely not related to Pandemrix as it was not used after 2010. Our results suggest that the increased NT1 incidence after 2009-2010 pH1N1 is not unique and our study provides an opportunity to develop new hypotheses, for example, considering other (influenza) viruses or epidemiological events to further investigate the pathophysiology of immune-mediated narcolepsy.

• Keywords
• H1N1 influenza, childhood narcolepsy, narcolepsy,
• MeSH
• Influenza, Human * epidemiology   prevention & control   MeSH
• Child MeSH
• Adult MeSH
• Incidence MeSH
• Humans MeSH
• Adolescent MeSH
• Narcolepsy * epidemiology   etiology   MeSH
• Vaccination MeSH
• Influenza Vaccines * MeSH
• Influenza A Virus, H1N1 Subtype * MeSH
• Check Tag
• Child MeSH
• Adult MeSH
• Humans MeSH
• Adolescent MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Geographicals
• Asia MeSH
• Europe MeSH
• Names of Substances
• Influenza Vaccines * MeSH