BackgroundSleep duration may be an important regulator of body weight and metabolism. An association between short habitual sleep time and increased body mass index (BMI) has been reported in large population samples. The potential role of metabolic hormones in this association is unknown.Methods and FindingsStudy participants were 1,024 volunteers from the Wisconsin Sleep Cohort Study, a population-based longitudinal study of sleep disorders. Participants underwent nocturnal polysomnography and reported on their sleep habits through questionnaires and sleep diaries. Following polysomnography, morning, fasted blood samples were evaluated for serum leptin and ghrelin (two key opposing hormones in appetite regulation), adiponectin, insulin, glucose, and lipid profile. Relationships among these measures, BMI, and sleep duration (habitual and immediately prior to blood sampling) were examined using multiple variable regressions with control for confounding factors.A U-shaped curvilinear association between sleep duration and BMI was observed. In persons sleeping less than 8 h (74.4% of the sample), increased BMI was proportional to decreased sleep. Short sleep was associated with low leptin (p for slope = 0.01), with a predicted 15.5% lower leptin for habitual sleep of 5 h versus 8 h, and high ghrelin (p for slope = 0.008), with a predicted 14.9% higher ghrelin for nocturnal (polysomnographic) sleep of 5 h versus 8 h, independent of BMI.ConclusionParticipants with short sleep had reduced leptin and elevated ghrelin. These differences in leptin and ghrelin are likely to increase appetite, possibly explaining the increased BMI observed with short sleep duration. In Western societies, where chronic sleep restriction is common and food is widely available, changes in appetite regulatory hormones with sleep curtailment may contribute to obesity.

Narcolepsy is a disabling sleep disorder affecting humans and animals. It is characterized by daytime sleepiness, cataplexy, and striking transitions from wakefulness into rapid eye movement (REM) sleep. In this study, we used positional cloning to identify an autosomal recessive mutation responsible for this sleep disorder in a well-established canine model. We have determined that canine narcolepsy is caused by disruption of the hypocretin (orexin) receptor 2 gene (Hcrtr2). This result identifies hypocretins as major sleep-modulating neurotransmitters and opens novel potential therapeutic approaches for narcoleptic patients.

A single nucleotide polymorphism located in the 3' flanking region of the human CLOCK gene was investigated as a predictor of diurnal preference in a population-based random sample of 410 normal adults. Morningness-eveningness preferences were determined using the 19-item Home-Ostberg questionnaire. Subjects carrying one of the two CLOCK alleles, 3111C, had a significantly lower mean Horne-Ostberg score. The distribution of scores was clearly shifted toward eveningness for these subjects. The score difference was independent of age, sex and ethnic heritage, thus making population stratification effects unlikely to explain this difference. These subjects had a substantial 10- to 44-minute delay in preferred timing for activity or sleep episodes. We suggest that the identified polymorphism or another tightly linked polymorphism within the CLOCK gene or its regulatory elements may be responsible for the finding.

Analysis of sleep for the diagnosis of sleep disorders such as Type-1 Narcolepsy (T1N) currently requires visual inspection of polysomnography records by trained scoring technicians. Here, we used neural networks in approximately 3,000 normal and abnormal sleep recordings to automate sleep stage scoring, producing a hypnodensity graph—a probability distribution conveying more information than classical hypnograms. Accuracy of sleep stage scoring was validated in 70 subjects assessed by six scorers. The best model performed better than any individual scorer (87% versus consensus). It also reliably scores sleep down to 5 s instead of 30 s scoring epochs. A T1N marker based on unusual sleep stage overlaps achieved a specificity of 96% and a sensitivity of 91%, validated in independent datasets. Addition of HLA-DQB1*06:02 typing increased specificity to 99%. Our method can reduce time spent in sleep clinics and automates T1N diagnosis. It also opens the possibility of diagnosing T1N using home sleep studies.