Orexin-A measurement in narcolepsy : A stability study and a comparison of LC-MS/MS and immunoassays

Background: Orexin-A and-B are neuropeptides involved in sleep-wake regulation. In human narcolepsy type 1, this cycle is disrupted due to loss of orexin-producing neurons in the hypothalamus. Cerebrospinal fluid (CSF) orexin-A measurement is used in the diagnosis of narcolepsy type 1. Currently available immunoassays may lack specificity for accurate orexin quantification. We developed and validated a liquid chromatography mass spectrometry assay (LC-MS/MS) for CSF orexin-A and B. Methods: We used CSF samples from narcolepsy type 1 (n = 22) and type 2 (n = 6) and non-narcoleptic controls (n = 44). Stable isotope-labeled orexin-A and-B internal standards were added to samples before solid-phase extraction and quantification by LC-MS/MS. The samples were also assayed by commercial radioimmunoassay (RIA, n = 42) and enzymatic immunoassay (EIA, n = 72) kits. Stability of orexins in CSF was studied for 12 months. Results: Our assay has a good sensitivity (10 pmol/L = 35 pg/mL) and a wide linear range (35-3500 pg/mL). Added orexin-A and-B were stable in CSF for 12 and 3 months, respectively, when frozen. The median orexin-A concentration in CSF from narcolepsy type 1 patients was <35 pg/mL (range <35-131 pg/mL), which was lower than that in CSF from control individuals (98 pg/mL, range <35-424 pg/mL). Orexin-A concentrations determined using our LC-MS/MS assay were five times lower than those measured with a commercial RIA. Orexin-B concentrations were undetectable Conclusions: Orexin-A concentrations measured by our LC-MS/MS assay were lower in narcolepsy type 1 patients as compared to controls. RIA yielded on average higher concentrations than LC-MS/MS.Peer reviewe

Pandemic influenza vaccine & narcolepsy: Simulations on the potential impact of bias

Several studies have identified an association between PandemrixTM, an AS03 adjuvanted pandemic influenza A(H1N1) vaccine, and narcolepsy, a rare and under-diagnosed sleep disorder with a median onset-to-diagnosis interval of ten years. This paper reviews potential sources of bias in published studies and aims to provide, through simulation, methodological recommendations for assessment of vaccine safety signals. Our simulation study showed that in the absence of an association between the vaccine and the outcome, presence of detection bias and differential exposure misclassification could account for elevated risk estimates. These may play a major role, particularly in alert situations when observation times are limited and the disease has a long latency period. Estimates from the case-control design were less inflated than those from the cohort design when these biases were present. Overall, these simulations provide useful insights for the design and interpretation of future studies

The predictive value of the CTA Vasospasm Score on delayed cerebral ischaemia and functional outcome after aneurysmal subarachnoid hemorrhage

Background and purpose: Delayed cerebral ischaemia (DCI) is a severe complication of aneurysmal subarachnoid hemorrhage that can significantly impact clinical outcome. Cerebral vasospasm is part of the pathophysiology of DCI and therefore a computed tomography angiography (CTA) Vasospasm Score was developed and an exploration was carried out of whether this score predicts DCI and subsequent poor outcome after aneurysmal subarachnoid hemorrhage. Methods: The CTA Vasospasm Score sums the degree of angiographic cerebral vasospasm of 17 intradural arterial segments. The score ranges from 0 to 34 with a higher score reflecting more severe vasospasm. Outcome measures were cerebral infarction due to DCI (CI-DCI), radiological and clinical DCI, and unfavorable functional outcome defined as a modified Rankin Scale >2 at 6 months. Receiver operating characteristic analyses were used to assess predictive value and to determine optimal cut-off scores. Inter-rater reliability was evaluated by Cohen's kappa coefficient. Results: This study included 59 patients. CI-DCI occurred in eight patients (14%), DCI in 14 patients (24%) and unfavorable outcome in 12 patients (20%). Median CTA Vasospasm Scores were higher in patients with (CI-)DCI and poor outcome. Receiver operating characteristic analysis revealed the highest area under the curve on day 5: CI-DCI 0.89 (95% confidence interval [CI] 0.79–0.99), DCI 0.68 (95% CI 0.50–0.87) and functional outcome 0.74 (95% CI 0.57–0.91). Cohen's kappa between the two raters was moderate to substantial (0.57–0.63). Conclusions: This study demonstrates that the CTA Vasospasm Score on day 5 can reliably identify patients with a high risk of developing (CI-)DCI and unfavorable outcome

Diagnosis of central disorders of hypersomnolence: A reappraisal by European experts

Summary 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)Peer reviewe

Data-Driven Phenotyping of Central Disorders of Hypersomnolence With Unsupervised Clustering.

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 whether current diagnostic criteria of hypersomnolence disorders should be reassessed. The main aim of this data-driven observational study was to see if 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 1078 unmedicated adolescents and adults. Seven clusters were identified, of which four clusters included predominantly individuals with cataplexy. The two most distinct clusters consisted of 158 and 157 patients respectively, were dominated by those without cataplexy and, amongst other variables, significantly differed in presence of sleep drunkenness, subjective difficulty awakening and weekend-week sleep length difference. Patients formally diagnosed as narcolepsy type 2 and idiopathic hypersomnia were evenly mixed in these two 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 rapid eye moment periods (SOREMPs) 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

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.</p

Narcolepsy and adjuvanted pandemic influenza A (H1N1) 2009 vaccines – Multi-country assessment

Background: In 2010, a safety signal was detected for narcolepsy following vaccination with Pandemrix, an AS03-adjuvanted monovalent pandemic H1N1 influenza (pH1N1) vaccine. To further assess a possible association and inform policy on future use of adjuvants, we conducted a multi-country study of narcolepsy and adjuvanted pH1N1 vaccines. Methods: We used electronic health databases to conduct a dynamic retrospective cohort study to assess narcolepsy incidence rates (IR) before and during pH1N1 virus circulation, and after pH1N1 vaccination campaigns in Canada, Denmark, Spain, Sweden, Taiwan, the Netherlands, and the United Kingdom. Using a case-control study design, we evaluated the risk of narcolepsy following AS03- and MF59-adjuvanted pH1N1 vaccines in Argentina, Canada, Spain, Switzerland, Taiwan, and the Netherlands. In the Netherlands, we also conducted a case-coverage study in children born between 2004 and 2009. Results: No changes in narcolepsy IRs were observed in any periods in single study sites except Sweden and Taiwan; in Taiwan incidence increased after wild-type pH1N1 virus circulation and in Sweden (a previously identified signaling country), incidence increased after the start of pH1N1 vaccination. No association was observed for Arepanrix-AS03 or Focetria-MF59 adjuvanted pH1N1 vaccines and narcolepsy in children or adults in the case-control study nor for children born between 2004 and 2009 in the Netherlands case-coverage study for Pandemrix-AS03. Conclusions: Other than elevated narcolepsy IRs in the period after vaccination campaigns in Sweden, we did not find an association between AS03- or MF59-adjuvanted pH1N1 vaccines and narcolepsy in children or adults in the sites studied, although power to evaluate the AS03-adjuvanted Pandemrix brand vaccine was limited in our study

Narcolepsy Type 1: Should We Only Target Hypocretin Receptor 2?

Nearly 25 years have passed since the ground-breaking discovery that hypocretin deficiency underlies human narcolepsy with cataplexy. Over time, it has become increasingly evident that hypocretin deficiency goes beyond the conventional core symptoms, or pentad, traditionally associated with narcolepsy. The emergence of hypocretin receptor 2 agonists presents an exciting opportunity, prompting us to explore the role of receptor 2 in the complete spectrum of NT1 symptoms. In this review, several clinical manifestations beyond the core symptoms will be discussed. We will outline what is currently known about the involvement of hypocretin receptors to reflect on what we expect with current knowledge from treatment with specific receptor agonists