Randomized trial of inosine for urate elevation in amyotrophic lateral sclerosis.

INTRODUCTION/AIMS: Higher urate levels are associated with improved ALS survival in retrospective studies, however whether raising urate levels confers a survival advantage is unknown. In the Safety of Urate Elevation in Amyotrophic Lateral Sclerosis (SURE-ALS) trial, inosine raised serum urate and was safe and well-tolerated. The SURE-ALS2 trial was designed to assess longer term safety. Functional outcomes and a smartphone application were also explored. METHODS: Participants were randomized 2:1 to inosine (n = 14) or placebo (n = 9) for 20 weeks, titrated to serum urate of 7-8 mg/dL. Primary outcomes were safety and tolerability. Functional outcomes were measured with the Amyotrophic Lateral Sclerosis Functional Rating Scale Revised (ALSFRS-R). Mobility and ALSFRS-R were also assessed by a smartphone application. RESULTS: During inosine treatment, mean urate ranged 5.68-6.82 mg/dL. Treatment-emergent adverse event (TEAE) incidence was similar between groups (p > .10). Renal TEAEs occurred in three (21%) and hypertension in one (7%) of participants randomized to inosine. Inosine was tolerated in 71% of participants versus placebo 67%. Two participants (14%) in the inosine group experienced TEAEs deemed related to treatment (nephrolithiasis); one was a severe adverse event. Mean ALSFRS-R decline did not differ between groups (p = .69). Change in measured home time was similar between groups. Digital and in-clinic ALSFRS-R correlated well. DISCUSSION: Inosine met pre-specified criteria for safety and tolerability. A functional benefit was not demonstrated in this trial designed for safety and tolerability. Findings suggested potential utility for a smartphone application in ALS clinical and research settings.

Development and Validation of the Pediatric Hypersomnolence Survey.

BACKGROUND AND OBJECTIVES: Narcolepsy and idiopathic hypersomnia usually begin in early adolescence, but diagnostic delays ranging from 5 to 10 years are common, affecting disease burden. To improve early identification of these treatable conditions, we developed and validated the Pediatric Hypersomnolence Survey (PHS). METHODS: Content was developed through literature review, patient focus groups, interviews with experts in the field, and field testing. We then validated the 14-item self-reported survey across 3 hospitals and web recruitment from patient groups. In the validation phase, we recruited a total of 331 participants (patients with narcolepsy type 1 [n = 64], narcolepsy type 2 [n = 34], idiopathic hypersomnia [n = 36], and other sleep disorders [n = 97] and healthy controls [n = 100], ages 8-18 years) to complete the survey. We assessed a range of psychometric properties, including discriminant diagnostic validity for CNS disorders of hypersomnolence using receiver operating characteristic curve analysis and reliability across a 1-week period. RESULTS: Confirmatory factor analysis indicated a 4-domain solution with good reliability expressed by satisfactory omega values. Across groups, the PHS total score showed appropriate positive correlations with other validated surveys of sleepiness (r = 0.65-0.78, p < 0.001) and negative correlations with multiple sleep latency test measures (mean sleep latency: r = -0.27, p = 0.006; number of sleep-onset REM periods: r = 0.26, p = 0.007). Compared to controls and patients with other sleep disorders, the area under the curve for participants with narcolepsy or idiopathic hypersomnia was 0.87 (standard error 0.02, 95% CI 0.83-0.91) with high sensitivity (81.3, 95% CI 73.7%-87.5%) and specificity (81.2%, 95 CI 75.1%-86.4%). Test-retest reliability was r = 0.87. DISCUSSION: The PHS is a valid and reliable tool for clinicians to identify pediatric patients with narcolepsy and idiopathic hypersomnia. Implemented in clinical practice, the PHS will potentially decrease diagnostic delays and time to treatment, ultimately reducing disease burden for these debilitating conditions. CLASSIFICATION OF EVIDENCE: This study provides Class III evidence that the PHS accurately identifies patients with central disorders of hypersomnolence.

Stability of nocturnal wake and sleep stages defines central nervous system disorders of hypersomnolence.

STUDY OBJECTIVES: We determine if young people with narcolepsy type 1 (NT1), narcolepsy type 2 (NT2), and idiopathic hypersomnia (IH) have distinct nocturnal sleep stability phenotypes compared to subjectively sleepy controls. METHODS: Participants were 5- to 21-year old and drug-naïve or drug free: NT1 (n = 46), NT2 (n = 12), IH (n = 18), and subjectively sleepy controls (n = 48). We compared the following sleep stability measures from polysomnogram recording between each hypersomnolence disorder to subjectively sleepy controls: number of wake and sleep stage bouts, Kaplan-Meier survival curves for wake and sleep stages, and median bout durations. RESULTS: Compared to the subjectively sleepy control group, NT1 participants had more bouts of wake and all sleep stages (p ≤ .005) except stage N3. NT1 participants had worse survival of nocturnal wake, stage N2, and rapid eye movement (REM) bouts (p < .005). In the first 8 hours of sleep, NT1 participants had longer stage N1 bouts but shorter REM (all ps < .004). IH participants had a similar number of bouts but better survival of stage N2 bouts (p = .001), and shorter stage N3 bouts in the first 8 hours of sleep (p = .003). In contrast, NT2 participants showed better stage N1 bout survival (p = .006) and longer stage N1 bouts (p = .02). CONCLUSIONS: NT1, NT2, and IH have unique sleep physiology compared to subjectively sleepy controls, with only NT1 demonstrating clear nocturnal wake and sleep instability. Overall, sleep stability measures may aid in diagnoses and management of these central nervous system disorders of hypersomnolence.

Defining disrupted nighttime sleep and assessing its diagnostic utility for pediatric narcolepsy type 1.

STUDY OBJECTIVES: Disrupted nighttime sleep (DNS) is a core narcolepsy symptom of unconsolidated sleep resulting from hypocretin neuron loss. In this study, we define a DNS objective measure and evaluate its diagnostic utility for pediatric narcolepsy type 1 (NT1). METHODS: This was a retrospective, multisite, cross-sectional study of polysomnograms (PSGs) in 316 patients, ages 6-18 years (n = 150 NT1, n = 22 narcolepsy type 2, n = 27 idiopathic hypersomnia, and n = 117 subjectively sleepy subjects). We assessed sleep continuity PSG measures for (1) their associations with subjective and objective daytime sleepiness, daytime sleep onset REM periods (SOREMPs), self-reported disrupted nocturnal sleep and CSF hypocretin levels and (2) their predictive value for NT1 diagnosis. We then combined the best performing DNS measure with nocturnal SOREMP (nSOREMP) to assess the added value to the logistic regression model and the predictive accuracy for NT1 compared with nSOREMP alone. RESULTS: The Wake/N1 Index (the number of transitions from any sleep stage to wake or NREM stage 1 normalized by total sleep time) was associated with objective daytime sleepiness, daytime SOREMPs, self-reported disrupted sleep, and CSF hypocretin levels (p's < 0.003) and held highest area under the receiver operator characteristic curves (AUC) for NT1 diagnosis. When combined with nSOREMP, the DNS index had greater accuracy for diagnosing NT1 (AUC = 0.91 [0.02]) than nSOREMP alone (AUC = 0.84 [0.02], likelihood ratio [LR] test p < 0.0001). CONCLUSIONS: The Wake/N1 Index is an objective DNS measure that can quantify DNS severity in pediatric NT1. The Wake/N1 Index in combination with or without nSOREMP is a useful sleep biomarker that improves recognition of pediatric NT1 using only the nocturnal PSG.

Listening to the Patient Voice in Narcolepsy: Diagnostic Delay, Disease Burden, and Treatment Efficacy.

STUDY OBJECTIVES: Describe common symptoms, comorbidities, functional limitations, and treatment responsiveness among patients with narcolepsy. Investigate the effect of pediatric onset of narcolepsy symptoms on time to diagnosis of narcolepsy and presence of comorbid depression. METHODS: Cross-sectional survey of 1,699 people in the United States with self-reported diagnosis of narcolepsy. We utilized mixed-methods data analyses to report study findings. RESULTS: Most participants reported receiving a diagnosis of narcolepsy more than 1 y after symptom onset. We found that the strongest predictor of this delayed diagnosis was pediatric onset of symptoms (odds ratio = 2.4, p < 0.0005). Depression was the most common comorbidity but we detected no association with pediatric onset of narcolepsy symptoms. Overall, participants reported that fatigue and cognitive difficulties were their most burdensome symptoms in addition to sleepiness and cataplexy. The majority of participants reported residual daytime fatigue and/or sleepiness despite treatment. Most participants reported they could not perform at work or school as well as they would like because of narcolepsy symptoms. CONCLUSIONS: This study provides unique insight into the narcolepsy disease experience. The study quantifies the problem of diagnostic delay for narcolepsy patients in the United States and highlights that symptoms are more likely to be missed if they develop before 18 y of age. These results suggest that narcolepsy awareness efforts should be aimed at parents, pediatric health care providers, school professionals, and children/adolescents themselves. Disease burden is high because of problems with fatigue, cognition, and persistence of residual symptoms despite treatment.

Impaired memory consolidation in children with obstructive sleep disordered breathing.

Memory consolidation is stabilized and even enhanced by sleep (and particularly by 12-15 Hz sleep spindles in NREM stage 2 sleep) in healthy children but it is unclear what happens to these processes when sleep is disturbed by obstructive sleep disordered breathing. This cross-sectional study investigates differences in declarative memory consolidation among children with primary snoring (PS) and obstructive sleep apnea (OSA) compared to controls. We further investigate whether memory consolidation group differences are associated with NREM stage 2 (N2) sigma (12-15 Hz) or NREM slow oscillation (0.5-1 Hz) spectral power bands. In this study, we trained and tested participants on a spatial declarative memory task with cued recall. Retest occurred after a period of daytime wake (Wake) or a night of sleep (Sleep) with in-lab polysomnography. 36 participants ages 5-9 years completed the protocol: 14 with OSA as defined by respiratory disturbance index (RDI) > 1/hour, 12 with primary snoring (PS) and 10 controls. OSA participants had poorer overall memory consolidation than controls across Wake and Sleep conditions [OSA: mean = -18.7% (5.8), controls: mean = 1.9% (7.2), t = -2.20, P = 0.04]. In contrast, PS participants and controls had comparable memory consolidation across conditions (t = 0.41; P = 0.38). We did not detect a main effect for condition (Sleep, Wake) or group x condition interaction on memory consolidation. OSA participants had lower N2 sigma power than PS (P = 0.03) and controls (P = 0.004) and N2 sigma power inversely correlated with percentage of time snoring on the study night (r = -0.33, P<0.05). Across all participants, N2 sigma power modestly correlated with memory consolidation in both Sleep (r = 0.37, P = 0.03) and Wake conditions (r = 0.44, P = 0.009). Further observed variable path analysis showed that N2 sigma power mediated the relationship between group and mean memory consolidation across Sleep and Wake states [Bindirect = 6.76(3.5), z = 2.03, P = 0.04]. NREM slow oscillation power did not correlate with memory consolidation. All results retained significance after controlling for age and BMI. In sum, participants with mild OSA had impaired memory consolidation and results were mediated by N2 sigma power. These results suggest that N2 sigma power could serve as biomarker of risk for cognitive dysfunction in children with sleep disordered breathing.

"Look who's talking!" Gaze Patterns for Implicit and Explicit Audio-Visual Speech Synchrony Detection in Children With High-Functioning Autism.

Conversation requires integration of information from faces and voices to fully understand the speaker's message. To detect auditory-visual asynchrony of speech, listeners must integrate visual movements of the face, particularly the mouth, with auditory speech information. Individuals with autism spectrum disorder may be less successful at such multisensory integration, despite their demonstrated preference for looking at the mouth region of a speaker. We showed participants (individuals with and without high-functioning autism (HFA) aged 8-19) a split-screen video of two identical individuals speaking side by side. Only one of the speakers was in synchrony with the corresponding audio track and synchrony switched between the two speakers every few seconds. Participants were asked to watch the video without further instructions (implicit condition) or to specifically watch the in-synch speaker (explicit condition). We recorded which part of the screen and face their eyes targeted. Both groups looked at the in-synch video significantly more with explicit instructions. However, participants with HFA looked at the in-synch video less than typically developing (TD) peers and did not increase their gaze time as much as TD participants in the explicit task. Importantly, the HFA group looked significantly less at the mouth than their TD peers, and significantly more at non-face regions of the image. There were no between-group differences for eye-directed gaze. Overall, individuals with HFA spend less time looking at the crucially important mouth region of the face during auditory-visual speech integration, which is maladaptive gaze behavior for this type of task.