Genetic risk for insomnia is associated with objective sleep measures in young and healthy good sleepers.

Insomnia disorder (ID) is the second most common neuropsychiatric disorder. Its socioeconomic burden is enormous while diagnosis and treatment are difficult. A novel approach that reveals associations between insomnia genetic propensity and sleep phenotypes in youth may help understand the core of the disease isolated from comorbidities and pave the way for new treatments. We obtained quantitative nocturnal sleep electroencephalogram (EEG) features in 456 participants (18-31y, 49 women). Sleep EEG was recorded during a baseline night following at least 7 days of regular sleep times. We then assessed daytime sleep onset latency in a subsample of N = 359 men exposed to manipulations affecting sleep pressure. We sampled saliva or blood for polygenic risk score (PRS) determination. The PRS for ID was computed based on genome-wide common single nucleotide polymorphism assessments. Participants also completed a battery of behavioral and cognitive tests. The analyses revealed that the PRS for ID was negatively associated with cumulated EEG power in the delta (0.5-4 Hz) and theta (4-8 Hz) bands across rapid eye movement (REM) and non-REM sleep (p ≤ .0026; β ≥ -0.13) controlling for age, sex and BMI. The PRS for ID was also negatively associated with daytime likelihood of falling asleep (β = -0.19, p = .0009). Other explorations for associations with non-baseline-nights, cognitive measures, and mood did not yield significant results. These results propose that the need or the ability to fall asleep and to generate slow brain activity during sleep may constitute the core sleep-related risk factors for developing ID.

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Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.

Déclaration de conflit d'intérêts

Declaration of Competing Interest C. Berthomier and M. Brandewinder have ownership and directorship of Physip and are employees of Physip who owns ASEEGA. This had no impact on study design and data analyses and interpretations. E. Koshmanova, V. Muto, D. Chylinski, C. Mouraux, M. Reyt, M. Grinard, P. Talwar, E. Lambot, N. Mortazavi, C. Degueldre, A. Luxen, E. Salmon, M. Georges, F. Collette, P. Maquet, E.Van Someren, and G. Vandewalle declare no conflict of interest.