SPECTRUM OF NARCOLEPSY AND ITS SYMPTOMS

$0P50FY2000NSNIH

Stanford University, Stanford CA

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Abstract

The overall goal of the epidemiology study proposed here is to provide population-based knowledge on the occurrence and correlates of narcolepsy-related symptoms and polygraphic signs as a foundation for characterizing and refining the working definition of human narcolepsy. We propose the collection of new data from participants enrolled in the Wisconsin Sleep Cohort Study, a longitudinal epidemiology study of the natural history of sleep disorders. This will be established by: a) administering a narcolepsy-related symptom questionnaire to a sample of 5000 middle-aged men and women; b) on a subsample of 820, conducting multiple-sleep latency tests (MSLTs) designed to detect episodes of sleep-onset rapid eye movement sleep periods (SOREMPs); and c) HLA typing to determine DQP1 positivity These new data will be added to extensive subjective and objective data on a sample of 1400, including baseline and follow-up polysomnography, experimental MSLTs, and other tests collected previously and currently as part of the Wisconsin Sleep Cohort Study. The anticipated results will be of direct application to the development of more specific and more sensitive guidelines for diagnosis and treatment of narcolepsy. In addition, the expected new knowledge on the spectrum and correlates of narcolepsy symptoms and signals will provide a foundation for further research on risk factors and adverse health outcomes on narcolepsy. The specific aims are: 1. To determine in the general adult population the distribution and correlates of narcolepsy-related symptoms (cataplexy, sleep paralysis, hypnagogic hallucinations, automatic behavior, excessive daytime sleepiness, and disturbed nocturnal sleep), and polygraphic signs including SOREMPs; 2. To confirm that HLA-DQ polymorphisms in the general population influence nocturnal sleep architecture; 3. To evaluate the influence of HLA susceptibility alleles on narcolepsy-related symptoms and signals, diagnostic groupings, and symptom clusters.

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