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.

Streptococcal infections are probably a significant environmental trigger for narcolepsy.

The levels of several hormones fluctuate according to the light and dark cycle and are also affected by sleep, feeding, and general behavior. The regulation and metabolism of several hormones are influenced by interactions between the effects of sleep and the intrinsic circadian system; growth hormone, melatonin, cortisol, leptin, and ghrelin levels are highly correlated with sleep and circadian rhythmicity. There are also endogenous circadian mechanisms that serve to regulate glucose metabolism and similar rhythms pertaining to lipid metabolism, regulated through the actions of various clock genes. Sleep disturbance, which negatively impacts hormonal rhythms and metabolism, is also associated with obesity, insulin insensitivity, diabetes, hormonal imbalance, and appetite dysregulation. Circadian disruption, typically induced by shift work, may negatively impact health due to impaired glucose and lipid homeostasis, reversed melatonin and cortisol rhythms, and loss of clock gene rhythmicity.

Objective (HLA typing, MSLT, and sleep studies) more than subjective (sleepiness and sleep paralysis) features predicted low concentration of CSF hypocretin-1 in patients with narcolepsy without cataplexy.

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