«Duermo todo el día para demostrarle al mundo que lucho por mis sueños» / “I sleep all day to show the world that I fight for my dreams”

Se presenta el caso clínico de un paciente que asocia tres trastornos de sueño diferentes: narcolepsia, apnea obstructiva del sueño (AOS) y trastorno de conducta del sueño REM. El objetivo es resaltar la importancia de la narcolepsia, una patología infradiagnosticada y que a veces puede quedar enmascarada por otros trastornos de sueño. En este caso, el paciente es diagnosticado inicialmente de AOS, pero dado que persiste con hipersomnolencia diurna debemos descartar otras causas. (AU)

We report a clinical case of a patient who presents three different sleep disorders, namely, narcolepsy, obstructive sleep apnea (OSA), and REM sleep behavior disorder. The objective of this study is to highlight the importance of narcolepsy, which is an underdiagnosed pathology that can sometimes be masked by other sleep disorders. In this case, the patient is initially diagnosed with OSA, but, due to the persistence of excessive daytime sleepiness, we have to rule out other causes. (AU)

Case report: narcolepsy type 2 due to temporal lobe glioma.

RATIONALE: The orexin projection system includes the lateral hypothalamus, reticular activating structure, and ventrolateral preoptic nucleus, and this system is related to the pathogenesis of narcolepsy. Here, we report a case of narcolepsy type 2 caused by hippocampal glioma of the right temporal lobe. PATIENT CONCERNS: A 44-year-old male farmer complained of excessive daytime sleepiness (EDS) over the past 3 months and more. INTERVENTIONS: The lesion of the right anteromedial temporal lobe was removed and its pathological examination was carried out. OUTCOMES: General examination showed no abnormalities of his heart, lungs, or abdomen. Neurological examination showed no positive sign. The blood routine and biochemical examination were normal. He scored 7 on the Pittsburg sleep quality index, 16 on the Epworth sleepiness scale, 52 on the self-rating anxiety scale, and 48 on the self-rating depression scale. The multiple sleep latency test data showed 2 periods of sleep-onset rapid eyes movement period across 4 successive tests; the average sleep latency was under 8 minutes, and the rapid eyes movement latency was under 7 minutes. Lesion of glioma in hippocampus area of the right anteromedial temporal lobe was confirmed through magnetic resonance imaging, magnetic resonance spectroscopy, and histological examination. After surgical removal of the glioma from the hippocampus area of the right anteromedial temporal lobe, the patient's EDS symptoms disappeared immediately. He scored 3 on the Epworth sleepiness scale. During our follow-up three months later, he remained well with no complications. DIAGNOSIS: We diagnosed the patient with narcolepsy type 2 according to the 3rd Edition of International Classification of Sleep Disorders (ICSD-3). CONCLUSION: The patient suffered from EDS and was diagnosed with narcolepsy type 2. The narcolepsy type 2 was linked to glioma of the hippocampus area. The hippocampus might be another part of regulating the sleep-arousal pathway, and the glioma secretion might interact with the orexin projection system.

Medical specialty visits and diagnoses received by Saudi patients prior to a diagnosis of narcolepsy.

PURPOSE: Narcolepsy is an uncommon neurological disorder characterized by excessive daytime sleepiness (EDS) and multiple other symptoms. Due to the under-recognition of narcolepsy symptoms, patients are often misdiagnosed. This study aimed to assess the types of specialties visited and the diagnoses received by Saudi patients prior to their narcolepsy diagnosis. METHODS: The study included 55 consecutive patients with type-1 and type-2 narcolepsy who attended the narcolepsy clinic between August 2017 and December 2017. Narcolepsy was diagnosed according to the International Classification of Sleep Disorders-third edition criteria. We evaluated sociodemographic data, the specialties visited, and diagnoses and treatments received prior to visiting a sleep specialist. RESULTS: The mean diagnostic delay was 9.1 ± 8.4 years (1-43 years). Multiple linear regression analysis identified early onset as the only predictor of a delayed diagnosis (ß coefficient = - 0.262, p = 0.03). EDS was the main symptom that prompted patients to seek medical consultation, and only one patient had been (1.8%) referred with the diagnosis of narcolepsy. In the study group, 82% of the patients were misdiagnosed with a mental or neurological disorder or were thought to be afflicted by "envy," "evil eye," or "black magic" before receiving a correct diagnosis. No significant differences were detected between patients with narcolepsy type-1 and narcolepsy type-2. CONCLUSIONS: Delays in diagnosing narcolepsy remain a major problem for Saudi patients with this disorder. We found that Saudi patients with narcolepsy had visited several medical specialists and faith healers and were misdiagnosed prior to visiting a sleep specialist.

Changes in quality of life in individuals with narcolepsy type 1 after the H1N1-influenza epidemic and vaccination campaign in Norway: a two-year prospective cohort study.

OBJECTIVE: Cross-sectional studies show a lower health-related quality of life (HRQoL) in individuals with narcolepsy. We aimed to describe changes in HRQoL after two years of multidisciplinary follow-up in a cohort of mainly post-H1N1 vaccination narcolepsy type-1 (NT1) patients in Norway. METHODS: Prospective-cohort study. Narcolepsy diagnosis was based on the International Classification of Sleep Disorders (third edition). Psychiatric comorbidity was assessed using the Achenbach System of Empirically Based Assessment (ASEBA). HRQoL was evaluated with the Pediatric Quality of Life Inventory (PedsQL™ Generic Core Scales 4.0) at baseline and follow-up. Mean follow-up time was 20.7 (2.7) months. RESULTS: Thirty one patients (18 females) with NT1, mean age 14.6 (SD = 4.8) years answered questionnaires at baseline and follow-up. On a group level, the PedsQL Total Health Summary score significantly improved by a mean of 5.9 (95%CI = 0.4, 11.9), p = 0.038; this was mainly driven by improvements in the Physical Health Summary score by 9.8 (3.0, 16.5) points, p = 0.006 and the School Functioning Scale score by 7.5 (1.0, 13.9) points p = 0.025. The Total ASEBA score was correlated with PedsQL Total Health Summary score at baseline, but not with changes in HRQoL. Sodium oxybate (Xyrem®) treatment at follow up was positively associated with changes in PedsQL Total Health Summary score, after adjusting for age and gender, p = 0.027. CONCLUSION: HRQoL in NT1 patients improved after two years of follow-up. The use of sodium oxybate (Xyrem®) at follow-up was associated with increases in HRQoL. Psychiatric comorbidity was correlated with HRQoL at baseline but did not predict changes in HRQoL at follow-up.

Exploring the clinical features of narcolepsy type 1 versus narcolepsy type 2 from European Narcolepsy Network database with machine learning.

Narcolepsy is a rare life-long disease that exists in two forms, narcolepsy type-1 (NT1) or type-2 (NT2), but only NT1 is accepted as clearly defined entity. Both types of narcolepsies belong to the group of central hypersomnias (CH), a spectrum of poorly defined diseases with excessive daytime sleepiness as a core feature. Due to the considerable overlap of symptoms and the rarity of the diseases, it is difficult to identify distinct phenotypes of CH. Machine learning (ML) can help to identify phenotypes as it learns to recognize clinical features invisible for humans. Here we apply ML to data from the huge European Narcolepsy Network (EU-NN) that contains hundreds of mixed features of narcolepsy making it difficult to analyze with classical statistics. Stochastic gradient boosting, a supervised learning model with built-in feature selection, results in high performances in testing set. While cataplexy features are recognized as the most influential predictors, machine find additional features, e.g. mean rapid-eye-movement sleep latency of multiple sleep latency test contributes to classify NT1 and NT2 as confirmed by classical statistical analysis. Our results suggest ML can identify features of CH on machine scale from complex databases, thus providing 'ideas' and promising candidates for future diagnostic classifications.

Neurocognition, sleep, and PET findings in type 2 vs type 1 narcolepsy.

OBJECTIVE: To analyze differences in functional brain images collected in patients with type 2 and type 1 narcolepsy compared to normal controls and the relationship among brain images, objective neuropsychologic tests, and sleep findings. METHODS: Data collection included comprehensive clinical investigation, study of sleep/wake with actigraphy, polysomnography, Multiple Sleep Latency Test, human leukocyte antigen typing, 18F-fluorodeoxyglucose PET, and cognitive tests obtained from 29 patients with type 2 narcolepsy, 104 patients with type 1 narcolepsy, and 26 sex- and age-matched normal control individuals. Conners' Continuous Performance Test (CPT II) and Wisconsin Card-Sorting Task were performed simultaneously with the FDG-PET examination. After analyses of variance, data between patients with type 1 and type 2 narcolepsy were compared by post hoc analysis, and correlation between functional brain imaging findings and results of neurocognitive tests was obtained. RESULTS: All patients with narcolepsy presented with at least 2 sleep-onset REM periods (SOREMP) and subjective sleepiness. Patients with type 2 narcolepsy compared to patients with type 1 narcolepsy had significantly less SOREMP, longer mean sleep latencies, and lower body mass indexes, apnea-hypopnea indexes, and frequency of human leukocyte antigen DQ-Beta1*0602. In patients with type 2 narcolepsy, FDG-PET studies showed significantly less hypermetabolism in the fusiform gyrus, striatum, hippocampus, thalamus, basal ganglia, and cerebellum than in patients with type 1 narcolepsy, and significantly less hypometabolism in the regions of frontal lobe, posterior cingulum, angular gyrus, and part of the parietal lobe; these changes were associated with fewer errors on the CPT. CONCLUSION: Young patients with type 2 narcolepsy have fewer clinical impairments and less distinct brain functional abnormalities than patients with type 1 narcolepsy, who are significantly more affected.

Diagnostic value of sleep stage dissociation as visualized on a 2-dimensional sleep state space in human narcolepsy.

BACKGROUND: Type 1 narcolepsy (NT1) is characterized by symptoms believed to represent Rapid Eye Movement (REM) sleep stage dissociations, occurrences where features of wake and REM sleep are intermingled, resulting in a mixed state. We hypothesized that sleep stage dissociations can be objectively detected through the analysis of nocturnal Polysomnography (PSG) data, and that those affecting REM sleep can be used as a diagnostic feature for narcolepsy. NEW METHOD: A Linear Discriminant Analysis (LDA) model using 38 features extracted from EOG, EMG and EEG was used in control subjects to select features differentiating wake, stage N1, N2, N3 and REM sleep. Sleep stage differentiation was next represented in a 2D projection. Features characteristic of sleep stage differences were estimated from the residual sleep stage probability in the 2D space. Using this model we evaluated PSG data from NT1 and non-narcoleptic subjects. An LDA classifier was used to determine the best separation plane. COMPARISON WITH EXISTING METHODS: This method replicates the specificity/sensitivity from the training set to the validation set better than many other methods. RESULTS: Eight prominent features could differentiate narcolepsy and controls in the validation dataset. Using a composite measure and a specificity cut off 95% in the training dataset, sensitivity was 43%. Specificity/sensitivity was 94%/38% in the validation set. Using hypersomnia subjects, specificity/sensitivity was 84%/15%. Analyzing treated narcoleptics the specificity/sensitivity was 94%/10%. CONCLUSION: Sleep stage dissociation can be used for the diagnosis of narcolepsy. However the use of some medications and presence of undiagnosed hypersomnolence patients impacts the result.

Novel method for evaluation of eye movements in patients with narcolepsy.

BACKGROUND: Narcolepsy causes abnormalities in the control of wake-sleep, non-rapid-eye-movement (non-REM) sleep and REM sleep, which includes specific eye movements (EMs). In this study, we aim to evaluate EM characteristics in narcolepsy as compared to controls using an automated detector. METHODS: We developed a data-driven method to detect EMs during sleep based on two EOG signals recorded as part of a polysomnography (PSG). The method was optimized using the manually scored hypnograms from 36 control subjects. The detector was applied on a clinical sample with subjects suspected for central hypersomnias. Based on PSG, multiple sleep latency test and cerebrospinal fluid hypocretin-1 measures, they were divided into clinical controls (N = 20), narcolepsy type 2 (NT2, N = 19), and narcolepsy type 1 (NT1, N = 28). We investigated the distribution of EMs across sleep stages and cycles. RESULTS: NT1 patients had significantly less EMs during wake, N1, and N2 sleep and more EMs during REM sleep compared to clinical controls, and significantly less EMs during wake and N1 sleep compared to NT2 patients. Furthermore, NT1 patients showed less EMs during NREM sleep in the first sleep cycle and more EMs during NREM sleep in the second sleep cycle compared to clinical controls and NT2 patients. CONCLUSIONS: NT1 patients show an altered distribution of EMs across sleep stages and cycles compared to NT2 patients and clinical controls, suggesting that EMs are directly or indirectly controlled by the hypocretinergic system. A data-driven EM detector may contribute to the evaluation of narcolepsy and other disorders involving the control of EMs.

French consensus. Type 1 and type 2 Narcolepsy: Investigations and follow-up.

In the new international classification of sleep disorders (ICSD-3), narcolepsy is differentiated into two distinct pathologies: type 1 narcolepsy (NT1) and type 2 narcolepsy (NT2). NT1 is characterised by periods of an irrepressible need to sleep, cataplexy (a sudden loss of muscle tone triggered by emotion) and in some cases the presence of symptoms such as hypnagogic hallucinations, sleep paralysis and disturbed night-time sleep. Its physiopathology is based on the loss of hypocretin neurons in the hypothalamus, seemingly connected to an auto-immune process. By definition, cataplexy is absent and the hypocretin levels in the CSF are normal in NT2. Confirming the diagnosis requires polysomnography and multiple sleep latency tests. The choice of further investigations is based on the presence or absence of typical cataplexy. Further investigations include HLA typing, lumbar puncture to measure the hypocretin level in the CSF, or even brain imagery in the case of narcolepsy suspected to be secondary to an underlying pathology. In this consensus we propose recommendations for the work-up to be carried out during diagnosis and follow-up for patients suffering from narcolepsy.

Benefits and risk of sodium oxybate in idiopathic hypersomnia versus narcolepsy type 1: a chart review.

BACKGROUND: Few stimulants have been evaluated for the treatment of idiopathic hypersomnia (IH). Sodium oxybate (indicated in narcolepsy type 1, NT1) has not been tested in IH patients. OBJECTIVE: The aim of this study is to retrospectively evaluate the benefit/risk ratio of sodium oxybate in IH versus NT1 using a chart review. METHODS: We reviewed the files of 46 patients with IH (35.7 ± 12.6 years old, 78% women) and 47 patients with NT1 (44.1 ± 18 years old, 47% women) and evaluated the benefits of sodium oxybate using the Epworth sleepiness scale (ESS) and a four-point scale assessing the global benefit, sleep inertia, sleepiness, sleep duration, and sleep onset latency. The spontaneously reported side effects were collected. RESULTS: Sodium oxybate was prescribed at a lower dose in IH than in NT1 (4.3 ± 2.2 vs. 6.6 ± 2.8 g/night, p <0.0001) patients after having tried more (3.2 ± 1.4 vs. 2.2 ± 1, p <0.0001) stimulants, but it produced a similar ESS change (-3.5 ± 4.5 vs. -3.2 ± 4.2 points) in the IH and NT1 groups. Severe morning inertia was improved in 24/34 (71%) patients with IH. During the follow-up period (15.8 months in IH vs. 35 months in NT1 groups), 53% IH and 68% NT1 patients dropped out. The side effects were as frequent in the IH group as in the NT1 group (67% vs. 52%), but nausea (40% vs. 13%) and dizziness (34.3% vs. 4.3%) were more frequent in the IH group. CONCLUSION: The benefit/risk ratio of sodium oxybate in IH- was similar to NT1-associated sleepiness, with additional benefits on severe morning inertia, despite using smaller doses in more refractory patients.

Narcolepsy with and without cataplexy, idiopathic hypersomnia with and without long sleep time: a cluster analysis.

BACKGROUND: The successive editions of the International Classification of Sleep Disorders (ICSD) reflect the evolution of the concepts of various sleep disorders. This is particularly the case for central disorders of hypersomnolence, with continuous changes in terminology and divisions of narcolepsy, idiopathic hypersomnia, and recurrent hypersomnia. According to the ICSD 2nd Edition (ICSD-2), narcolepsy with cataplexy (NwithC), narcolepsy without cataplexy (Nw/oC), idiopathic hypersomnia with long sleep time (IHwithLST), and idiopathic hypersomnia without long sleep time (IHw/oLST) are four, well-defined hypersomnias of central origin. However, in the absence of biological markers, doubts have been raised as to the relevance of a division of idiopathic hypersomnia into two forms, and it is not yet clear whether Nw/oC and IHw/oLST are two distinct entities. With this in mind, it was decided to empirically review the ICSD-2 classification by using a hierarchical cluster analysis to see whether this division has some relevance, even though the terms "with long sleep time" and "without long sleep time" are inappropriate. RESULTS: The cluster analysis differentiated three main clusters: Cluster 1, "combined monosymptomatic hypersomnia/narcolepsy type 2" (people initially diagnosed with IHw/oLST and Nw/oC); Cluster 2 "polysymptomatic hypersomnia" (people initially diagnosed with IHwithLST); and Cluster 3, narcolepsy type 1 (people initially diagnosed with NwithC). CONCLUSIONS: Cluster analysis confirmed that narcolepsy type 1 and polysymptomatic hypersomnia are independent sleep disorders. People who were initially diagnosed with Nw/oC and IHw/oLST formed a single cluster, referred to as "combined monosymptomatic hypersomnia/narcolepsy type 2."

Process and outcome for international reliability in sleep scoring.

OBJECTIVES: The aim was to evaluate the inter-rater reliability in scoring sleep stages in two sleep labs in Berlin Germany and Beijing China. METHODS: The subjects consist of polysomnography (PSGs) from 15 subjects in a German sleep laboratory, with 7 mild to moderate sleep apnea hypopnea syndrome (SAHS) patients and 8 healthy controls, and PSGs from 15 narcolepsy patients in a Chinese sleep laboratory. Five experienced technologists including two Chinese and three Germans without common training scored the PSGs following the 2007 AASM manual except the EEG signals included only two EEG leads (C3/A2 and C4/A1). Differences in inter-scorer agreement were analyzed based on epoch-by-epoch comparison by means of Cohen's κ, and quantitative sleep parameters by means of intra-class correlation coefficients. RESULTS: Inter-laboratory epoch-by-epoch agreement comparison between scorers from the two countries yielded a moderate agreement with a mean κ value of 0.57 for controls, 0.58 for SAHS, and 0.54 for narcolepsy. When compared with controls, the inter-scoring agreement is higher for wake and N3 stage scoring in SAHS and N1 and N3 scoring in narcolepsy (p < 0.05). The only sleep stage with lower scoring agreement in both SAHS (κ 0.69 vs. 0.79, p = 0.034) and narcolepsy (0.66 vs 0.79, p = 0.022) was stage REM. Inter-laboratory comparisons showed that the most common combinations of deviating scorings were N1 and N2, N2 and N3, and N1 and wake. A 6.5 % deviating scoring rate of wake and REM and a 13.4 % deviating scoring rate of N1 and REM indicated that inter-laboratory scoring in narcolepsy was about twice as in SAHS and controls confused. This was further confirmed by agreement analysis of quantitative parameters using intra-class correlation coefficients ICC(2,1) indicating REM sleep scoring agreement was lower in narcolepsy than in controls (p < 0.05). CONCLUSION: Low REM stage scoring agreement exists for narcoleptics and SAHS, indicating the necessity to study sleep stage scoring agreement for a specific sleep disorder. Intensive training is needed for the scoring of sleep in international multiple center studies to improve the scoring agreement.

Usefulness of genetic characterization of narcolepsy and hypersomnia on phenotype definition: a study in Portuguese patients.

INTRODUCTION: The determination of human leukocyte antigen (HLA) class II genotype is widely used to confirm the diagnosis of narcolepsy with or without cataplexy. The HLA genotyping is reliable, easy to perform and reassures the clinician. It is also less invasive than other methodologies and is in accordance with the autoimmune hypothesis for the origin of narcolepsy. AIM. To assess the usefulness of genetic markers (HLA) in the differential diagnosis between different sleep disorders and their relevance in the context of our population. SUBJECTS AND METHODS: We analyzed a cohort of 113 patients with episodes of daytime sleepiness, 38 patients were classified as narcolepsy with cataplexy, 13 as narcolepsy and 62 as hypersomnia/idiopathic hypersomnia. A control population of 206 reportedly healthy individuals from the same geographic origin was used. RESULTS: The HLA-DQB1*06:02 allele frequency was overrepresented in patients with narcolepsy and narcolepsy with cataplexy (46% and 71% respectively vs. 16% in control population), with a value of p = 4.53-13 for narcolepsy with cataplexy. The HLA-DQB1*02 frequency was increased in the population with hypersomnia when compared with the control population (55% vs. 34%; p = 0.004). CONCLUSIONS: Genetic characterization has the potential to enhance the ability to carry out differential diagnosis among diverse excessive daytime sleepiness phenotypes, corresponding to diverse entities with different biological mechanisms.

TITLE: Utilidad de la caracterizacion genetica de la narcolepsia y la hipersomnia en la definicion del fenotipo: estudio en pacientes portugueses.Introduccion. La determinacion del genotipo de los antigenos leucocitarios humanos (HLA) de clase II es un metodo muy difundido para confirmar el diagnostico de la narcolepsia, con y sin cataplejia. El genotipado del HLA es fiable, sencillo y proporciona seguridad al medico. Tambien es menos invasivo que otros metodos y entronca con la hipotesis autoinmunitaria sobre el origen de la narcolepsia. Objetivo. Evaluar la utilidad de los marcadores geneticos (HLA) en el diagnostico diferencial de diferentes trastornos del sueño y su relevancia en el contexto de nuestra poblacion. Sujetos y metodos. Se analizo una cohorte de 113 pacientes con episodios de somnolencia diurna, 38 de los cuales fueron clasificados como afectados por narcolepsia con cataplejia, 13 con narcolepsia y 62 con hipersomnia/hipersomnia idiopatica. La poblacion de control estaba integrada por 206 individuos sanos del mismo origen geografico. Resultados. La frecuencia del alelo HLA-DQB1*06:02 era superior a la habitual en los pacientes con narcolepsia y narcolepsia con cataplejia (46% y 71%, respectivamente, frente al 16% en la poblacion control), con un valor de p = 4,53­13 en el caso de la narcolepsia con cataplejia. La frecuencia del alelo HLA-DQB1*02 era mas elevada en la poblacion con hipersomnia en comparacion con la poblacion control (55% frente a 34%; p = 0,004). Conclusiones. La caracterizacion genetica tiene posibilidades de mejorar el diagnostico diferencial entre varios fenotipos de somnolencia diurna excesiva, que corresponden a diversas entidades con diferentes mecanismos biologicos.

[Hypersomnia: diagnosis, classification and treatment]. / Las hipersomnias: diagnóstico, clasificación y tratamiento.

Hypersomnia or excessive daytime sleepiness is common in neurological practice and may have different etiologies. Hypersomnia may be defined as sleepiness at an inappropriate time or in an inappropriate situation. It is important to consider that hypersomnia is at times referred to as tiredness or fatigue. A detailed clinical history is essential to reach an accurate diagnosis. A correct diagnosis is necessary to initiate the appropriate treatment considering the negative social and occupational consequences of hypersomnia. Excessive daytime sleepiness syndromes include primary sleep disorders like narcolepsy and hypersomnia secondary to several neurological and psychiatric disorders and also as an adverse effect of numerous drugs.

Episodios paroxísticos no epilépticos: concepto y clasificación / Non-epileptic paroxysmal episodes: concept and classification

Los episodios paroxísticos no epilépticos son episodios desaparición brusca e inesperada con recuperación espontánea a la normalidad. Por sus características pueden ser confundidos con crisis epilépticas lo que lleva a errores terapéuticos. Son muy frecuentes en la infancia y adolescencia por lo que los planteamientos de diagnóstico diferencial entre amigos son un problema habitual para el pediatra. La manera más práctica de clasificarlos es según los mecanismos de producción y la semiología clínica preferente. Podemos diferenciar 6 grupos: secundarios a hipoxia/anoxia cerebral, relacionados con el sueño, trastornos motores paroxísticos, trastornos psicológicos o psiquiátricos paroxísticos, migrañas y síndromes relacionados y otro grupo de misceláneas. En general corresponden a patologías benignas, autolimitadas y con recuperación espontánea, pero que pueden ser confundidas con patología grave a otros niveles: neurológico, cardiológico, digestivo, etc. La mayoría de ellos tiene una edad típica de presentación que puede facilitar su diagnóstico: espasmos de sollozo en época de lactante, etc (AU)

Paroxysmal episodes other tan epilepsy are sudden and unexpected events with spontaneous recuperation. They may be confused with epilepsy seizures, fact that makes therapeutic mistakes. These mistakes are very frequent in child-hood and adolescence and it is necessary to have a good differential diagnosis. The best classification of paroxysmal episodes other than epilepsy is based on the mechanism of production and the clinical aspects. We can differentiate between 6 groups: secondary of movement, paroxysmal psychiatric disorders, migraine relation syndromes and miscellaneous. They are benign process, limited and with spontaneous recuperation, but they get confused with serious illness. The most of this episodes have a typical age of presentation: breath holdings spells during the lactation, etc (AU)

A rare form of narcolepsy (HLA-DR2-) shows possible association with (functionally relevant) alpha-interferon gene polymorphisms.

Narcolepsy is a neuropsychiatric disease caused by complex disturbance of sleep regulation. The main symptoms comprise daytime sleepiness and cataplexy. Although the aetiology remains unclear so far, narcolepsy is genetically characterized by strong linkage to the human leukocyte antigen complex as more than 90% of the patients are typed HLA-DR2+. Recently, it has become apparent that the orexin (hypocretin) neurotransmitter system plays a key role in the pathogenesis of the disease. Canine narcolepsy is caused by mutations in the orexin receptor 2 gene, and narcoleptic patients show specifically decreased cerebrospinal fluid orexin levels. Decreased promotor activity of the prepro-orexin gene is caused by binding of alpha-interferon in vitro. To investigate the possible role of IFNA gene polymorphisms in the pathogenesis of narcolepsy, we have genotyped two single nucleotide polymorphisms in IFNA genes as well as a neighbouring microsatellite. No association was evident in the prevalent DR2+ group. Yet, the IFNA10 single nucleotide polymorphisms and the IFNA microsatellite are associated with the DR2- patient group. Thus, the pathogenetic role of interferons needs to be defined in DR2- narcolepsy.