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

Narkolepsie typ 1 (NT1), narkolepsie typ 2 (NT2) a idiopatická hypersomnie (IH) mají hlavní symptom centrální hypersomnii (CH). Etiopatofyziologie NT1 je spojena s deficitem hypokretinu autoimunitního původu. Etiopatofyziologie NT2 a IH je neznámá. Jsou pochybnosti o nezávislosti NT2 a IH a o jejich dlouhodobém průběhu. Střevní microbiota má vliv na mozkové funkce a chování buď přímo přes tvorbu mediátorů nebo nepřímo prostřednictvím autoprotilátek proti vybraným neuronům. Lze proto vyslovit hypotézu, že microbiota hraje roli v etiopatofyziologii nemocí s CH a může modifikovat aktuální intenzitu samotné hypersomnie. Nemocní s CH a zdravé kontroly budou klinicky vyšetřeni (včetně dlouhodobého vývoje NT2 a IH). Jejich stolice bude geneticky analyzována s cílem definovat mikrobiom střevní mikrobioty. Bude pátráno po autoprotilátkách. Výsledky budou vzájemně korelovány. Tento výzkum má osvětlit patofyziologii nemocí s CH a také má pomoci v doporučeních nemocným a může otevřít nové směry léčby.; Narcolepsy type 1 (NT1), narcolepsy type 2 (NT2) and idiopathic hypersomnia (IH) have as a main symptom central hypersomnia (CH). The etiopathophysiology of NT1 is related to the hypocretin deficiency of autoimmune origin. The etiopathophysiology of NT2 and IH is unknown. There are doubts on the independence of NT2 and IH and their long-term course. The gut microbiota has an impact on brain functions and behavior either directly by mediators’ production or indirectly via autoantibodies against selected neurons. This evokes the hypothesis that microbiota has a role in etiopathophysiology of diseases with CH and may modify actual intensity of hypersomnia itself. Patients with CH and healthy controls will be clinically examined (including the long-term evolution of NT2 and IH). Their stools will be genetically analyzed in attempt to define the microbiome of the gut microbiota. The autoantibodies will be searched in their blood. The results will be mutually correlated. This research may elucidate the pathophysiology of CH disorders as well as may help to counselling the patients and fina

• Keywords
• autoimmunity, mikrobiom, microbiome, autoprotilátky, autoantibodies, idiopatická hypersomnie, Idiopathic hypersomnia, autoimunita, elderly, extrakce DNA, vysoce výkonné sekvenování (HTS), funkce střevní bariéry, DNA extraction, high throughput sequencing (HTS), stáří, mikrobiota, microbiota, Narkolepsie typ 1 - narkolepsie s kataplexií, narkolepsie typ 2 - narkolepsie bez kataplexie, centrální hypersomnie, vývoj nemoci, Narcolepsy type 1 - narcolepsy with cataplexy, narcolepsy type 2 - narcolepsy without cataplexy, central hypersomnia, intesintal barrier function, disease evolution,

• NML Publication type
• závěrečné zprávy o řešení grantu AZV MZ ČR

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.

• 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

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.

• 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

Cíl: Studie si kladla za cíl ověřit vhodnost použití Škály tíže narkolepsie (Narcolepsy Severity Scale; NSS) jako základního klinického nástroje pro stanovení subjektivní tíže onemocnění u pacientů s narkolepsií typu 1 (NT1) v ČR. Soubor a metodika: Celkem 78 pacientů ze 2 spánkových center s diagnózou NT1 (29 mužů, 49 žen, průměrný věk 36,1 ± 11,7 let, rozmezí 18–71 let, z toho léčených n = 51) vyplnilo škálu NSS sestávající z 15 otázek zaměřených na výskyt, frekvenci a dopad na denní aktivity všech hlavních narkoleptických příznaků. Současně byli instruováni vyplnit Epworthskou škálu spavosti (Epworth Sleepiness Scale; ESS), Škálu tíže únavy (Fatigue Severity Scale; FSS), Škálu hodnocení úzkosti a deprese při hospitalizaci (Hospital Anxiety and Depression Rating Scale; HADS) a zkrácenou verzi Dotazníku kvality života (Quality of Life Questionnaire; SF-36). Výsledky: Škála NSS vykazuje dobrou vnitřní konzistenci dotazníku pomocí koeficientu Cronbachova a, která je pro celou kohortu pacientů s NT1 0,80, pro skupinu léčených pacientů 0,79 a pro skupinu neléčených pacientů 0,82. Keiser-Meyer-Olkinův index pro celou kohortu je 0,73, což potvrzuje dostatečnou strukturální validitu dotazníku. Nebyl zjištěn signifikantní rozdíl ve skóre NSS léčených a neléčených pacientů, nicméně byla potvrzena korelace celkového skóre NSS s ESS (ρ = 0,61; p < 0,0001) a FSS (ρ = 0,4438; p < 0,0001). Závěr: NSS představuje vhodný a snadno aplikovatelný klinický nástroj ke stanovení subjektivní tíže onemocnění, dobře vystihuje hlavní narkoleptické příznaky a hodnotí jejich vliv na denní aktivity.

Aim: The aim of the study was to verify the applicability of the Narcolepsy Severity Scale (NSS) as a basic clinical tool for determining the subjective severity of the disease in patients with narcolepsy type 1 (NT1) in the Czech Republic. Patients and methods: A total of 78 patients from 2 sleep centers with a diagnosis of NT1 (29 men, 49 women, mean age 36.1 ± 11.7 years, range 18–71 years, N = 51 were treated) completed the NSS scale consisting of 15 questions focusing on the occurrence, frequency, and impact on daily activities of all major narcoleptic symptoms. At the same time, they were instructed to complete the Epworth Sleepiness Scale (ESS), the Fatigue Severity Scale (FSS), the Hospital Anxiety and Depression Rating Scale (HADS) and a short version of the Quality of Life Questionnaire (SF-36). Results: The NSS scale shows good internal consistency of the questionnaire using Cronbach‘s a, which is 0.80 for the whole cohort of NT1 patients, 0.79 for the treated group and 0.82 for the untreated group. The Keiser-Meyer-Olkin index for the entire cohort is 0.73, confirming sufficient structural validity of the questionnaire. There was no significant difference in the NSS scores of treated and untreated patients; however, the correlation of the total NSS score with ESS (ρ = 0.61; P < 0.0001) and FSS (ρ = 0.4438; P < 0.0001) was confirmed. Conclusions: The NSS is a convenient and practical clinical tool for determining the subjective severity of the disease, well capturing the main narcoleptic symptoms and assessing their impact on daily activities.

• MeSH
• Adult MeSH
• Quality of Life MeSH
• Middle Aged MeSH
• Humans MeSH
• Narcolepsy * MeSH
• Surveys and Questionnaires MeSH
• Check Tag
• Adult MeSH
• Middle Aged MeSH
• Humans MeSH

Cíl: Srovnání polysomnografických parametrů nočního spánku pacientů mužů s narkolepsií typu 1 ve věku nad 55 let s věkově spárovanými kontrolami. Soubor a metodika: Soubor tvořilo 17 mužů (průměrný věk 66,1 ± 8,3 let) s narkolepsií typu 1, jejichž dříve získané záznamy polysomnografického vyšetření byly porovnány z hlediska základních parametrů makrostruktury spánku a jeho základních poruch s polysomnografickými záznamy věkově spárovaných mužů (průměr 65,0 ± 6,6 let). Výsledky: Pacienti s narkolepsií typu 1 měli oproti kontrolám významně nižší procentuální zastoupení stádia NREM 3 (8 vs. 26 %; p = 0,003) a REM spánku (12 vs. 19 %; p = 0,01) a vyšší zastoupení stádia NREM 1 (17 vs. 10 %; p = 0,01). Zastoupení bdělosti (29 vs. 26 %) a stádia NREM 2 (33 vs. 30 %), průměrná latence usnutí, latence REM spánku, trvání spánku i spánková efektivita (67 ± 14 vs. 72 ± 17 %) se mezi soubory nelišily. Výskyt obstrukčních spánkových apnoí byl srovnatelný (apnoe/hypopnoe index 25 ± 26 vs. 23 ± 18). Index periodických pohybů končetinami ve spánku byl v narkoleptické skupině výrazně vyšší (46 ± 31 vs. 16 ± 22; p = 0,02) a přítomnost poruchy atonie v REM spánku (47 vs. 8 %; p = 0,002) četnější. Závěr: Muži s narkolepsií typu 1 mají signifikantně méně zastoupena stádia NREM 3 a REM, a naopak více stádia NREM 1.

Aim: The aim of this study was to compare polysomnographic parameters of nocturnal sleep in male patients with narcolepsy type 1 aged over 55 years with age-matched controls. Patients and methods: The cohort consisted of 17 men (mean age 66.1 ± 8.3 years) with narcolepsy type 1 whose previously obtained polysomnographic records were compared in terms of basic parameters of sleep macrostructure and its basic disorders with polysomnographic records of age-paired men (mean 65.0 ± 6.6 years). Results: Compared to controls, males with narcolepsy type 1 had a significantly lower percentage of NREM 3 (8 vs. 26%; P = 0.003) and REM sleep stages (12 vs. 19%; P = 0.01) and a higher presentation of NREM 1 stages (17 vs. 10%; P = 0.01). The representation of wakefulness (29 vs. 26%) and NREM 2 stages (33 vs. 30%), mean sleep latency, REM sleep latency, sleep duration, and sleep efficiency (67 ± 14 vs. 72 ± 17%) did not differ between groups. The incidence of obstructive sleep apneas was comparable (apnea-hypopnea index 25 ± 26 vs. 23 ± 18). The index of periodic limb movements during sleep was significantly higher (46 ± 31 vs. 16 ± 22; P = 0.02) and the presence of REM sleep without atonia (47 vs. 8%; P = 0.02) was more frequent in the narcoleptic group. Conclusion: Men with narcolepsy type 1 have significantly less NREM 3 and REM stages and more NREM 1 stages.

• MeSH
• Middle Aged MeSH
• Humans MeSH
• Narcolepsy * physiopathology   pathology   MeSH
• Polysomnography * methods   instrumentation   MeSH
• Sleep Wake Disorders diagnosis   MeSH
• Aged MeSH
• Sleep Stages MeSH
• Statistics as Topic MeSH
• Check Tag
• Middle Aged MeSH
• Humans MeSH
• Male MeSH
• Aged MeSH
• Publication type
• Clinical Study MeSH
• Research Support, Non-U.S. Gov't 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.

• Publication type
• Journal Article 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.

• 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