Anisha Nagpal, Anna Patterson, Ashley Ross, Loran Knol, Sajal Shukla, Adam Bryant Miller, Fiona Baker, Katja M Schmalenberger, Tory A Eisenlohr-Moul
{"title":"Characterizing Nonlinear Heterogeneous Sleep Trajectories across the Menstrual Cycle in a Transdiagnostic Psychiatric Population.","authors":"Anisha Nagpal, Anna Patterson, Ashley Ross, Loran Knol, Sajal Shukla, Adam Bryant Miller, Fiona Baker, Katja M Schmalenberger, Tory A Eisenlohr-Moul","doi":"10.1093/sleep/zsag220","DOIUrl":null,"url":null,"abstract":"<p><strong>Study objectives: </strong>Sleep disturbance is closely linked to affective symptoms and suicidal ideation (SI). These symptoms fluctuate across the menstrual cycle; however, menstrual cycle-related sleep variability remains poorly characterized in psychiatric populations. This study examined how subjective and objective sleep fluctuate across the menstrual cycle in a psychiatric sample, considering individual differences and associations with negative affective and SI symptom trajectories.</p><p><strong>Materials and methods: </strong>A transdiagnostic psychiatric sample recruited for recent suicidality provided intensive daily subjective sleep and symptom ratings (N = 142,M = 26.59,years SD = 5.34) alongside wearable-derived (Oura) objective sleep measures (N = 39) across 1-3 menstrual cycles. Cycle timing was aligned to ovulation and menses using Phase-Aligned Cycle Time Scaling. Generalized additive mixed models quantified average cyclical effects and interindividual heterogeneity. Exploratory smooth mixture modeling (SMM) identified latent subgroups with shared temporal sleep trajectories which were compared to trait-level demographic and clinical characteristics as well as affective, SI, and pain cyclical symptom trajectory subgroups.</p><p><strong>Results: </strong>Most sleep outcomes showed substantial within-person cyclical variability. SMM identified distinct subgroups for Oura-derived sleep efficiency, and for subjective ratings of fatigue, insomnia, sleep quality, and hypersomnia, with patterns including perimenstrual or luteal worsening, as well as no cycle-related variability. Sleep subgroups, especially for subjective ratings, frequently significantly aligned with parallel affective, pain, and SI trajectories, suggesting temporally-coupled vulnerability.</p><p><strong>Conclusions: </strong>Sleep trajectories across the menstrual cycle are heterogeneous and meaningfully coupled with psychiatric symptom patterns. These findings support cycle-aware sleep monitoring and suggest that cyclical sleep disruption may help identify windows of heightened psychiatric risk, motivating replication and personalized intervention approaches.</p>","PeriodicalId":22018,"journal":{"name":"Sleep","volume":" ","pages":""},"PeriodicalIF":4.9000,"publicationDate":"2026-08-20","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Sleep","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1093/sleep/zsag220","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"Medicine","Score":null,"Total":0}
引用次数: 0
Abstract
Study objectives: Sleep disturbance is closely linked to affective symptoms and suicidal ideation (SI). These symptoms fluctuate across the menstrual cycle; however, menstrual cycle-related sleep variability remains poorly characterized in psychiatric populations. This study examined how subjective and objective sleep fluctuate across the menstrual cycle in a psychiatric sample, considering individual differences and associations with negative affective and SI symptom trajectories.
Materials and methods: A transdiagnostic psychiatric sample recruited for recent suicidality provided intensive daily subjective sleep and symptom ratings (N = 142,M = 26.59,years SD = 5.34) alongside wearable-derived (Oura) objective sleep measures (N = 39) across 1-3 menstrual cycles. Cycle timing was aligned to ovulation and menses using Phase-Aligned Cycle Time Scaling. Generalized additive mixed models quantified average cyclical effects and interindividual heterogeneity. Exploratory smooth mixture modeling (SMM) identified latent subgroups with shared temporal sleep trajectories which were compared to trait-level demographic and clinical characteristics as well as affective, SI, and pain cyclical symptom trajectory subgroups.
Results: Most sleep outcomes showed substantial within-person cyclical variability. SMM identified distinct subgroups for Oura-derived sleep efficiency, and for subjective ratings of fatigue, insomnia, sleep quality, and hypersomnia, with patterns including perimenstrual or luteal worsening, as well as no cycle-related variability. Sleep subgroups, especially for subjective ratings, frequently significantly aligned with parallel affective, pain, and SI trajectories, suggesting temporally-coupled vulnerability.
Conclusions: Sleep trajectories across the menstrual cycle are heterogeneous and meaningfully coupled with psychiatric symptom patterns. These findings support cycle-aware sleep monitoring and suggest that cyclical sleep disruption may help identify windows of heightened psychiatric risk, motivating replication and personalized intervention approaches.
期刊介绍:
SLEEP® publishes findings from studies conducted at any level of analysis, including:
Genes
Molecules
Cells
Physiology
Neural systems and circuits
Behavior and cognition
Self-report
SLEEP® publishes articles that use a wide variety of scientific approaches and address a broad range of topics. These may include, but are not limited to:
Basic and neuroscience studies of sleep and circadian mechanisms
In vitro and animal models of sleep, circadian rhythms, and human disorders
Pre-clinical human investigations, including the measurement and manipulation of sleep and circadian rhythms
Studies in clinical or population samples. These may address factors influencing sleep and circadian rhythms (e.g., development and aging, and social and environmental influences) and relationships between sleep, circadian rhythms, health, and disease
Clinical trials, epidemiology studies, implementation, and dissemination research.