Narcolepsy Type Research Articles

Serum N-Glycan Profiling of Patients with Narcolepsy Type 1 Using LC-MS/MS.

The neurological condition known as narcolepsy type 1 (NT1) is an uncommon condition marked by extreme daytime sleepiness, cataplexy, sleep paralysis, hallucinations, disrupted nocturnal sleep, and low or undetectable levels of orexin in the CSF fluid. NT1 has been hypothesized to be an immunological disorder; its treatment is currently only symptomatic, and misdiagnosis is not uncommon. This study compares the N-glycome of NT1 patients with healthy controls in search of potential glycan biomarkers using LC-MS/MS. A total of 121 candidate N-glycans were identified, 55 of which were isomeric N-glycan structures and 65 were not. Seventeen N-glycan biomarker candidates showed significant differences between the NT1 and control cohorts. All of the candidate glycan biomarkers were isomeric except HexNAc6Hex7Fuc0NeuAc1 (6701) and HexNAc6Hex7Fuc1NeuAc2 (6712). Therefore, with isomeric and nonisomeric structures, a total of 20 candidate N-glycan biomarkers are reported in this study, and interestingly, all are either sialylated or sialylated-fucosylated and upregulated in NT1 relative to the control. The distribution levels of all the identified N-glycans show that the sialylated glycan type is the most abundant in NT1 and is majorly disialylated, although the trisialylated subtype is three-fold higher in NT1 compared to the healthy control. The first isomers of HexNAc5Hex6Fuc0NeuAc3 (5603), HexNAc6Hex7Fuc0NeuAc2 (6702), and HexNAc6Hex7Fuc1NeuAc4 (6714) expressed a high level of fold changes (FC) of 1.62, 2.19, and 2.98, respectively. These results suggest a different N-glycome profile of NT1 and a relationship between sialylated glycan isomers in NT1 disease development or progression. The revelation of N-glycan expression alterations in this study may improve NT1 diagnostic methods, understanding of NT1 pathology, and the development of new targeted therapeutics.

Constructing a cataplexy face prediction model for narcolepsy type 1 based on ResNet-18

Objective: To establish a prediction model for the identifying of cataplexy facial features based on clinical shooting videos by using a deep learning image recognition network ResNet-18. Methods: A cross-sectional study. Twenty-five narcolepsy type 1 patients who were first diagnosed and never received treatment and 25 healthy controls recruited by advertisement in the Second Affiliated Hospital of Nanchang University from 2020 to 2023.After image preprocessing, a total of 1 180 images were obtained, including 583 cataplexy faces and 597 normal faces.90% were selected as the training set and validation set, and then expanded the data by 5 times.80% of the expanded data set was extracted as the training set and 20% as the validation set, that is, the number of the training set was (583+597)×0.9×0.8×5=4 248, the number of the validation set was (583+597)×0.9×0.2×5=1 062. The data sets for training and validation were used train parameters to establish the model and were trained through the five-fold cross-validation method, to establish the ResNet-18 cataplexy face recognition model via transfer learning.10% (118 images) of the original non-amplified images were extracted as the test set. The test set data did not participate in data enhancement and model training, and was only used to evaluate the final performance of the model. Finally, ResNet-18 was compared with VGG-16, ResNet-34 and Inception V3 deep learning models, and the receiver operating characteristic curve was used to evaluate the value of ResNet-18 image recognition network in cataplexy face recognition. Results: Among 25 patients with narcolepsy type 1, 15 were males and 10 were females, aged [M (Q1, Q3)] of 14.0(11.0, 20.5) years.Among 25 healthy controls, 14 were males and 11 were females, with a median age of 16.0(14.4, 23.0) years.The overall accuracy of ResNet-18 image recognition network in the test set was 90.9%, the sensitivity was 96.4% and the specificity was 85.2%. The area under the ROC curve was 0.99(95%CI:0.96-1.00). The ResNet-18 model parameter amount was 11.69 M, the floating point operation amount was 1 824.03 M, and the single image recognition time was 5.9 ms. Conclusions: The cataplexy face prediction model built based on the deep learning image recognition network ResNet-18 has a high accuracy in identifying cataplexy faces.

The electroretinography to identify biomarkers of idiopathic hypersomnia and narcolepsy type 1.

Hypersomnia spectrum disorders are underdiagnosed and poorly treated due to their heterogeneity and absence of biomarkers. The electroretinography has been proposed as a proxy of central dysfunction and has proved to be valuable to differentiate certain psychiatric disorders. Hypersomnolence is a shared core feature in central hypersomnia and psychiatric disorders. We therefore aimed to identify biomarkers by studying the electroretinography profile in patients with narcolepsy type 1, idiopathic hypersomnia and in controls. Cone, rod and retinal ganglion cells electrical activity were recorded with flash-electroretinography in non-dilated eye of 31 patients with idiopathic hypersomnia (women 84%, 26.6 ± 5.9 years), 19 patients with narcolepsy type 1 (women 63%, 36.6 ± 12.7 years) and 43 controls (women 58%, 30.6 ± 9.3 years). Reduced cone a-wave amplitude (p = 0.039) and prolonged cone (p = 0.022) and rod b-wave (p = 0.009) latencies were observed in patients with narcolepsy type 1 as compared with controls, while prolonged photopic negative response-wave latency (retinal ganglion cells activity) was observed in patients with idiopathic hypersomnia as compared with controls (p = 0.033). The rod and cone b-wave latency clearly distinguished narcolepsy type 1 from idiopathic hypersomnia and controls (area under the curve > 0.70), and the photopic negative response-wave latency distinguished idiopathic hypersomnia and narcolepsy type 1 from controls with an area under the curve > 0.68. This first original study shows electroretinography anomalies observed in patients with hypersomnia. Narcolepsy type 1 is associated with impaired cone and rod responses, whereas idiopathic hypersomnia is associated with impaired retinal ganglion cells response, suggesting different phototransduction alterations in both hypersomnias. Although these results need to be confirmed with a larger sample size, the electroretinography may be a promising tool for clinicians to differentiate hypersomnia subtypes.

Narcolepsy and rapid eye movement sleep.

Since the first description of narcolepsy at the end of the 19th Century, great progress has been made. The disease is nowadays distinguished as narcolepsy type 1 and type 2. In the 1960s, the discovery of rapid eye movement sleep at sleep onset led to improved understanding of core sleep-related disease symptoms of the disease (excessive daytime sleepiness with early occurrence of rapid eye movement sleep, sleep-related hallucinations, sleep paralysis, rapid eye movement parasomnia), as possible dysregulation of rapid eye movement sleep, and cataplexy resembling an intrusion of rapid eye movement atonia during wake. The relevance of non-sleep-related symptoms, such as obesity, precocious puberty, psychiatric and cardiovascular morbidities, has subsequently been recognized. The diagnostic tools have been improved, but sleep-onset rapid eye movement periods on polysomnography and Multiple Sleep Latency Test remain key criteria. The pathogenic mechanisms of narcolepsy type 1 have been partly elucidated after the discovery of strong HLA class II association and orexin/hypocretin deficiency, a neurotransmitter that is involved in altered rapid eye movement sleep regulation. Conversely, the causes of narcolepsy type 2, where cataplexy and orexin deficiency are absent, remain unknown. Symptomatic medications to treat patients with narcolepsy have been developed, and management has been codified with guidelines, until the recent promising orexin-receptor agonists. The present review retraces the steps of the research on narcolepsy that linked the features of the disease with rapid eye movement sleep abnormality, and those that do not appear associated with rapid eye movement sleep.

Pediatric Narcolepsy Type 1: A State-of-the-Art Review

Narcolepsy is a chronic central disorder of hypersomnolence most frequently arising during childhood/adolescence. This review article examined the literature concerning the etiology, prevalence, clinical course, and treatment of children with type 1 narcolepsy (NT1). Core symptoms of pediatric NT1 include excessive daytime sleepiness (EDS) and cataplexy, together with disrupted night sleep, sleep paralysis, and hypnagogic and hypnopompic hallucinations that can also occur. This disease frequently presents several comorbidities, such as obesity and precocious puberty, conditions ranging from psychological distress to psychiatric disorders, and cognitive aspects that further worsen the clinical picture. NT1 impairs the quality of life of children, thus calling for an early diagnosis and adequate treatment. To date, pharmacological treatments have been registered for childhood NT1 and can improve symptoms. Non-pharmacological approaches are also essential to improve patients’ well-being, ranging from behavioral treatments (e.g., planned napping) to psychosocial interventions (e.g., school programs). Multidisciplinary treatment management and early diagnosis are key factors in order to allow for adequate quality of life and development in children with NT1.

Impaired cognition in narcolepsy: clinical and neurobiological perspectives.

In addition to well-known symptoms such as sleepiness and cataplexy, many people with narcolepsy have impaired cognition, reporting inattention, poor memory, and other concerns. Unfortunately, research on cognition in narcolepsy has been limited. Strong evidence demonstrates difficulties with sustained attention, but evidence for executive dysfunction and impaired memory is mixed. Animal research provides some insights into how loss of the orexin neurons in narcolepsy type 1 may give rise to impaired cognition via dysfunction of the prefrontal cortex, and cholinergic and monoaminergic systems. This paper reviews some of these clinical and preclinical findings, provides a neurobiological framework to understand these deficits, and highlights some of the many key unanswered questions.

Evaluating routine blood and cerebrospinal fluid samples in narcolepsy patients

Cerebrospinal fluid hypocretin-1 is proven to be a precise diagnostic marker of narcolepsy Type 1 (NT1). However other characteristics of cerebrospinal fluid and blood parameters have not yet been described. The objective of this study was to evaluate the differences in routine blood and cerebrospinal fluid analyses between NT1 patients and patients suspected of hypersomnia. We collected retrospectively all measures of cerebrospinal fluid hypocretin-1 between 2019 and 2022. This yielded 612 patients out of which 146 were diagnosed with NT1 and the rest (466 patients) were used as a control group. We selected the most relevant routine samples from both blood, plasma and cerebrospinal fluid and compared the two groups. The only significantly different analytes were plasma lactate dehydrogenase and cerebrospinal fluid hypocretin-1. No other differences were found between the groups including thyroid markers, markers of neuroendocrine function, inflammatory markers in blood or cerebrospinal fluid, markers of permeability of the blood brain barrier or metabolic markers in blood samples. We found no significant differences in routine blood or cerebrospinal fluid components, neuroendocrine function, neuroinflammation and metabolic markers. The results reflect that the hypocretin system does not seem to play a chronic major role in regulation of these markers. None of the parameters routinely measured in blood in these patients could differentiate between NT1 and non-NT1 disorders besides CSF-hcrt-1.

High-resolution HLA sequencing and hypocretin receptor 2 autoantibodies in narcolepsy type 1 and type 2.

Narcolepsy is a sleep disorder caused by an apparent degeneration of orexin/hypocretin neurons in the lateral hypothalamic area and a subsequent decrease in orexin/hypocretin levels in the cerebrospinal fluid. Narcolepsy is classified into type 1 (NT1) and type 2 (NT2). While genetic associations in the human leukocyte antigen (HLA) region and candidate autoantibodies have been investigated in NT1 to imply an autoimmune origin, less is known about the pathogenesis in NT2. Twenty-six NT1 and 15 NT2 patients were included, together with control groups of 24 idiopathic hypersomnia (IH) patients and 778 general population participants. High-resolution sequencing was used to determine the alleles, the extended haplotypes, and the genotypes of HLA-DRB3, -DRB4, -DRB5, -DRB1, -DQA1, -DQB1, -DPA1, and -DPB1. Radiobinding assay was used to determine autoantibodies against hypocretin receptor 2 (anti-HCRTR2 autoantibodies). NT1 was associated with HLA-DRB5*01:01:01, -DRB1*15:01:01, -DQA1*01:02:01, -DQB1*06:02:01, -DRB5*01:01:01, -DRB1*15:01:01, -DQA1*01:02:01, -DQB1*06:02:01 (odds ratio [OR]: 9.15; p=8.31×10-4) and HLA-DRB5*01:01:01, -DRB1*15:01:01, -DQA1*01:02:01, -DQB1*06:02:01, -DRB4*01:03:01, -DRB1*04:01:01, -DQA1*03:02//03:03:01, -DQB1*03:01:01 (OR: 23.61; p=1.58×10-4) genotypes. Lower orexin/hypocretin levels were reported in the NT2 subgroup (n=5) that was associated with the extended HLA-DQB1*06:02:01 haplotype (p=.001). Anti-HCRTR2 autoantibody levels were not different between study groups (p=.8524). We confirmed the previous association of NT1 with HLA-DQB1*06:02:01 extended genotypes. A subgroup of NT2 patients with intermediate orexin/hypocretin levels and association with HLA-DQB1*06:02:01 was identified, indicating a possible overlap between the two distinct narcolepsy subtypes, NT1 and NT2. Low anti-HCRTR2 autoantibody levels suggest that these receptors might not function as autoimmune targets in either NT1 or NT2.

The value of using ELISA to detect orexin-A in cerebrospinal fluid in the diagnosis of narcolepsy.

Orexin in cerebrospinal fluid (CSF) is a neuropeptide synthesized by a cluster of neurons in the lateral hypothalamus. It mainly functions to maintain arousal, regulate feeding, and participate in reward mechanisms. Radioimmunoassay (RIA) and enzyme-linked immunosorbent assay (ELISA) can detect CSF orexin. At present, RIA is widely used but is limited by various conditions, which is not conducive to its widespread development. We aimed to determine whether ELISA can replace RIA in detecting orexin in CSF. We investigated the results of 20 patients with central disorders of hypersomnolence, including 11 with narcolepsy type 1, 2 with narcolepsy type 2, 5 with idiopathic hypersomnia, and 2 with other causes of somnolence. RIA and ELISA were used to detect CSF orexin, and P values <.05 were considered to be significant. In the narcolepsy and non-narcolepsy type 1 groups, there was no correlation between the RIA and ELISA results (P > .05). In the narcolepsy type 1 group, the ELISA and RIA results were significantly different (P < .05), but this was not observed in the non-narcolepsy type 1 group (P > .05). The accuracy of ELISA to detect CSF orexin was lower than that of RIA (P < .05). ELISA cannot replace RIA in the measurement of CSF orexin, and RIA is recommended as the first choice when narcolepsy is suspected.

Navigating narcolepsy: exploring coping strategies and their association with quality of life in patients with narcolepsy type 1

Narcolepsy type 1 (NT1) is a chronic neurological disorder characterized by symptoms such as excessive daytime sleepiness, sudden sleep episodes, disrupted nocturnal sleep, cataplexy, sleep paralysis, and hypnagogic hallucinations, which significantly impact the overall well-being and quality of life of individuals. While psychological factors have gained attention, there is limited research on the coping strategies employed by patients with NT1 and their association with quality of life. This study aimed to compare coping strategies in patients with NT1 and controls, as well as assess the relationship between coping strategies and quality of life in patients with NT1. A total of 122 individuals diagnosed with NT1 and 138 controls were enrolled in this cross-sectional study. Participants completed questionnaires assessing coping strategies and health-related quality of life. A Mann–Whitney U test was conducted to compare the use of different coping strategies by patients with NT1 and controls. Spearman's rho correlation was performed to examine the association between coping strategies and quality of life in the NT1 group. Results showed that patients with NT1 exhibited differences in the use of coping strategies compared to controls. They reported lower use of active coping, planning, instrumental, and emotional social support, and higher use of behavioral and mental disengagement. Denial and behavioral disengagement were significantly and negatively associated with quality of life. Identifying coping strategies and their association with quality of life may aid in the development of tailored interventions aimed at improving the adoption of effective coping strategies and reducing the use of maladaptive coping strategies.

Development and validation of a machine learning model for prediction of comorbid major depression disorder among narcolepsy type 1

BackgroundMajor depression disorder (MDD) forms a common psychiatric comorbidity among patients with narcolepsy type 1 (NT1), yet its impact on patients with NT1 is often overlooked by neurologists. Currently, there is a lack of effective methods for accurately predicting MDD in patients with NT1. ObjectiveThis study utilized machine learning (ML) algorithms to identify critical variables and developed the prediction model for predicting MDD in patients with NT1. MethodsThe study included 267 NT1 patients from four sleep centers. The diagnosis of comorbid MDD was based on Diagnostic and Statistical Manual of Mental Disorders fifth edition (DSM-5). ML models, including six full models and six compact models, were developed using a training set. The performance of these models was compared in the testing set, and the optimal model was evaluated in the testing set. Various evaluation metrics, such as Area under the receiver operating curve (AUC), precision-recall (PR) curve and calibration curve were employed to assess and compare the performance of the ML models. Model interpretability was demonstrated using SHAP. ResultIn the testing set, the logistic regression (LG) model demonstrated superior performance compared to other ML models based on evaluation metrics such as AUC, PR curve, and calibration curve. The top eight features used in the LG model, ranked by feature importance, included social impact scale (SIS) score, narcolepsy severity scale (NSS) score, total sleep time, body mass index (BMI), education years, age of onset, sleep efficiency, sleep latency. ConclusionThe study yielded a straightforward and practical ML model for the early identification of MDD in patients with NT1. A web-based tool for clinical applications was developed, which deserves further verification in diverse clinical settings.

Executive function performance in children and adolescent patients with narcolepsy type 1

ObjectiveThe executive function profile in patients with narcolepsy type 1 (NT1) has been mentioned; however, limited research exists on children and adolescent patients with NT1.This study aims to assess executive function in children and adolescent patients with NT1 in China, examine potential influencing factors and evaluate the short-term treatment effect on executive function. Methods53 NT1 patients (36 males, age 12.2 ± 3.4 years) and 37 healthy controls (23 males, age 12.2 ± 2.5 years) underwent self-reported measures assessing subjective sleepiness, depression, anxiety and sleep quality. A comprehensive neuropsychological test was administered to assess executive function domains, including processing speed, inhibitory control, cognitive flexibility and working memory. These assessments were repeated in NT1 patients after three-day regular drug treatment. ResultsNT1 patients exhibited higher levels of excessive daytime sleepiness, depression, anxiety, and poor sleep quality compared to healthy controls. Patients showed impaired processing speed, inhibitory control and cognitive flexibility (p < 0.05), whereas working memory was unaffected (p > 0.05). Regression analysis revealed that parameters from sleep monitoring, such as sleep efficiency and sleep latency, were correlated with executive function performance after controlling for age, gender, and education years. The short-term treatment led to improvements in inhibitory control, cognitive flexibility, and working memory. ConclusionThe findings showed that executive function was impaired among children and adolescent patients with NT1, which was associated with objective sleep parameters. Furthermore, this study emphasizes the necessity of neuropsychological assessments and early interventions among children and adolescent NT1 patients.

Microglia Density and Its Association With Disease Duration, Severity, and Orexin Levels in Patients With Narcolepsy Type 1.

Narcolepsy type 1 (NT1) is due to the loss of hypothalamic neurons that produce orexin (ORX), by a suspected immune-mediated process. Rare postmortem studies are available and failed to detect any inflammation in the hypothalamic region, but these brains were collected years after the first symptoms. In vivo studies close to disease onset are lacking. We aimed to explore microglia density in the hypothalamus and thalamus in NT1 compared with controls using [18F]DPA-714 PET and to study in NT1 the relationships between microglia density in the hypothalamus and in other regions of interest (ROIs) with disease duration, severity, and ORX levels. Patients with NT1 and controls underwent a standardized clinical evaluation and [18F]DPA-714 PET imaging using a radiolabeled ligand specific to the 18 kDa translocator protein (TSPO). TSPO genotyping determined receptor affinity. Images were processed on peripheral module interface using standard uptake value (SUV) on ROIs: hypothalamus, thalamus, frontal area, cerebellum, and the whole brain. SUV ratios (SUVr) were calculated by normalizing SUV with cerebellum uptake. A total of 41 patients with NT1 (21 adults, 20 children, 10 with recent disease onset <1 year) and 35 controls were included, with no significant difference between groups for [18F]DPA-714 binding (SUV/SUVr) in the hypothalamus and thalamus. Unexpectedly, significantly lower SUVr in the whole brain was found in NT1 compared with controls (0.97 ± 0.06 vs 1.08 ± 0.22, p = 0.04). The same finding between NT1 and controls in the whole brain was observed in those with high or mixed TSPO affinity (p = 0.03 and p = 0.04). Similar trend was observed in the frontal area in NT1 (0.96 ± 0.09 vs 1.09 ± 0.25, p = 0.05). In NT1, no association was found between SUVr in different ROIs and age, disease duration, severity, or ORX levels. We found no evidence of in vivo increased microglia density in NT1 compared with controls, even close to disease onset, and even unexpectedly a decrease in the whole brain of these patients. These findings do not support the presence of neuroinflammation in the destruction process of ORX neurons. ClinicalTrials.org NCT03754348.

Atypical isolated cataplexy: two case reports and a mini-review

ABSTRACT Cataplexy is the sudden loss of muscle tone often provoked by emotion such as laughter or excitement. Cataplexy is one of the essential diagnostic features of Narcolepsy type 1 (NT1). We describe two cases of isolated cataplexy with different outcomes, highlighting the diagnostic and prognostic challenges. There is conflicting literature as to whether it is a legitimate standalone diagnosis or an early warning sign of narcolepsy. Our cases do not fit with current diagnostic criteria for narcolepsy, yet still share some clinical or laboratory features. These ambiguous cases question what the mechanistic relationship between narcolepsy and cataplexy may be.

Identifying time-resolved features of nocturnal sleep characteristics of narcolepsy using machine learning.

The differential diagnosis of narcolepsy type 1, a rare, chronic, central disorder of hypersomnolence, is challenging due to overlapping symptoms with other hypersomnolence disorders. While recent years have seen significant growth in our understanding of nocturnal polysomnography narcolepsy type 1 features, there remains a need for improving methods to differentiate narcolepsy type 1 nighttime sleep features from those of individuals without narcolepsy type 1. We aimed to develop a machine learning framework for identifying sleep features to discriminate narcolepsy type 1 from clinical controls, narcolepsy type 2 and idiopathic hypersomnia. The population included polysomnography data from 350 drug-free individuals (114 narcolepsy type 1, 90 narcolepsy type 2, 105 idiopathic hypersomnia, and 41 clinical controls) collected at the National Reference Centers for Narcolepsy in Montpelier, France. Several sets of nocturnal sleep features were explored, as well as the value of time-resolving sleep architecture by analysing sleep per quarter-night. Several patterns of nighttime sleep evolution emerged that differed between narcolepsy type 1, clinical controls, narcolepsy type 2 and idiopathic hypersomnia, with increased nighttime instability observed in patients with narcolepsy type 1. Using machine learning models, we identified rapid eye movement sleep onset as the best single polysomnography feature to distinguish narcolepsy type 1 from controls, narcolepsy type 2 and idiopathic hypersomnia. By combining multiple feature sets capturing different aspects of sleep across quarter-night periods, we were able to further improve between-group discrimination and could identify the most discriminative sleep features. Our results highlight salient polysomnography features and the relevance of assessing their time-dependent changes during sleep that could aid diagnosis and measure the impact of novel therapeutics in future clinical trials.

Single cell transcriptomics of cerebrospinal fluid cells from patients with recent-onset narcolepsy

Narcolepsy is a rare cause of hypersomnolence and may be associated or not with cataplexy, i.e. sudden muscle weakness. These forms are designated narcolepsy-type 1 (NT1) and -type 2 (NT2), respectively. Notable characteristics of narcolepsy are that most patients carry the HLA-DQB1*06:02 allele and NT1-patients have strongly decreased levels of hypocretin-1 (synonym orexin-A) in the cerebrospinal fluid (CSF). The pathogenesis of narcolepsy is still not completely understood but the strong HLA-bias and increased frequencies of CD4+ T cells reactive to hypocretin in the peripheral blood suggest autoimmune processes in the hypothalamus. Here we analyzed the transcriptomes of CSF-cells from twelve NT1 and two NT2 patients by single cell RNAseq (scRNAseq). As controls, we used CSF cells from patients with multiple sclerosis, radiologically isolated syndrome, and idiopathic intracranial hypertension. From 27,255 CSF cells, we identified 20 clusters of different cell types and found significant differences in three CD4+ T cell and one monocyte clusters between narcolepsy and multiple sclerosis patients. Over 1000 genes were differentially regulated between patients with NT1 and other diseases. Surprisingly, the most strongly upregulated genes in narcolepsy patients as compared to controls were coding for the genome-encoded MTRNR2L12 and MTRNR2L8 peptides, which are homologous to the mitochondria-encoded HUMANIN peptide that is known playing a role in other neurological diseases including Alzheimer's disease.

Effectiveness and optimization of low-sodium oxybate in participants with narcolepsy switching from a high-sodium oxybate: data from the Substitution of Equal Grams of Uninterrupted Xyrem to Xywav study.

Low-sodium oxybate (LXB; calcium, magnesium, potassium, and sodium oxybates; Xywav) contains the same active moiety as high-sodium oxybates (SXBs; SXB [Xyrem] and fixed-dose SXB [Lumryz]), with 92% less sodium, and is approved in the United States for treatment of cataplexy or excessive daytime sleepiness in patients 7 years of age and older with narcolepsy, and idiopathic hypersomnia in adults. Patients with narcolepsy have increased cardiovascular risk relative to people without narcolepsy. LXB's lower sodium content is recognized by the United States Food and Drug Administration in the narcolepsy population as clinically meaningful in reducing cardiovascular morbidity compared with SXBs. The Substitution of Equal Grams of Uninterrupted Xyrem to Xywav study (NCT04794491) examined the transition experience of patients with narcolepsy switching from SXB to LXB. Eligible participants were aged 18-80 years with narcolepsy type 1 or 2 on a stable SXB dose/regimen. After 2 weeks, participants transitioned gram-per-gram to LXB for 6 weeks, with opportunity for subsequent titration. Assessments included the Epworth Sleepiness Scale, Patient Global Impression of change, Ease of Switching Medication Scale, and Forced Preference Questionnaire. The study enrolled 62 participants at baseline; 60 transitioned to LXB and 54 completed the study. At baseline and end of the LXB intervention/early discontinuation, respectively, mean total doses were 8.0 and 8.0 g/night; mean Epworth Sleepiness Scale scores were 9.4 and 8.8. Most participants reported improvement (45%) or no change (48%) in narcolepsy symptoms on the Patient Global Impression of change, reported the transition to LXB was "easy" (easy, extremely easy, not difficult at all; 93%) on the Ease of Switching Medication Scale, and preferred LXB compared with SXB (79%) on the Forced Preference Questionnaire, most commonly due to the lower sodium content. Most participants switched from SXB to LXB with minimal modifications of dose/regimen and reported the transition process was easy. Effectiveness of oxybate treatment was maintained on LXB, and most participants preferred LXB to SXB. No new safety or tolerability issues were identified. Registry: ClinicalTrials.gov; Name: An Interventional Safety Switch Study (Segue Study) of XYWAV in Narcolepsy; URL: https://classic.clinicaltrials.gov/ct2/show/NCT04794491; Identifier: NCT04794491. Macfadden W, Leary EB, Fuller DS, Kirby MT, Roy A. Effectiveness and optimization of low-sodium oxybate in participants with narcolepsy switching from a high-sodium oxybate: data from the Substitution of Equal Grams of Uninterrupted Xyrem to Xywav study. J Clin Sleep Med. 2024;20(9):1467-1477.

0637 Composite Response with Once-Nightly Sodium Oxybate: Symptom Improvement in Participants with Narcolepsy Type 1

0637 Composite Response with Once-Nightly Sodium Oxybate: Symptom Improvement in Participants with Narcolepsy Type 1

1142 Atypical Cataplexy and Post LP Headaches in POTS with Features of Narcolepsy Type I

1142 Atypical Cataplexy and Post LP Headaches in POTS with Features of Narcolepsy Type I

0664 Development of a Novel Patient-Reported Outcome Measure of Functional Impacts for Narcolepsy Types 1 and 2

0664 Development of a Novel Patient-Reported Outcome Measure of Functional Impacts for Narcolepsy Types 1 and 2