AUTHOR=Defillo Archie , Grassi Massimiliano , Daccò Silvia , Martin Jennifer L. , Guadagni Veronica TITLE=Clinical association between current depressive symptoms and odds ratio product in US sleep centers JOURNAL=Frontiers in Sleep VOLUME=Volume 4 - 2025 YEAR=2025 URL=https://www.frontiersin.org/journals/sleep/articles/10.3389/frsle.2025.1635704 DOI=10.3389/frsle.2025.1635704 ISSN=2813-2890 ABSTRACT=IntroductionThe Odds Ratio Product (ORP) is a validated EEG-based measure of sleep depth, more sensitive than traditional metrics. While it has been studied in healthy individuals and those with sleep–wake disorders, its relevance in psychiatric conditions remains unclear. This study examined ORP during sleep and its association with depressive symptoms in a large cohort referred to multiple U.S. sleep centers.MethodsWe retrospectively analyzed data from 829 adults (48.85% female; mean age 43.49 ± 13.74 years) enrolled in two multicenter studies. Each participant completed the Patient Health Questionnaire-9 (PHQ-9) and underwent overnight polysomnography (PSG), with ORP calculated from central EEG channels. Mean and standard deviation ORP values were derived for the full night and Wake, stages 1, 2, 3, and REM sleep. Associations between ORP metrics and depression severity (PHQ-9 total and PHQ-9 ≥10) were tested using linear and logistic regressions, adjusting for age and sex. Model fit was assessed with the Akaike Information Criterion (significance level α = 0.05).ResultsFixed-effects models outperformed mixed-effects models. Mean ORP during the full night and light sleep (stages 1 + 2) showed a significant U-shaped association with depression, indicating both high and low ORP values relate to greater depressive burden. In stage 3, higher mean ORP was linearly associated with more severe symptoms. Lower ORP variability across the night also correlated with higher depression scores.ConclusionsORP shows potential as a non-invasive biomarker for depressive symptoms, with distinct associations depending on sleep depth. Integrating ORP into clinical PSG analyses could improve detection of depression-related sleep patterns.