Maternal Childhood Adversity and Infant Epigenetic Aging: Moderation by Restless Sleep During Pregnancy.

Maternal exposure to childhood adversity is associated with detrimental health outcomes throughout the lifespan and may have implications for offspring. Evidence links maternal adverse childhood experiences (ACEs) to detrimental birth outcomes, yet the impact on the infant's epigenome is unclear. Moreover, maternal sleep habits during pregnancy may influence this association. Here, we explore whether restless sleep during pregnancy moderates the association between exposure to maternal childhood adversity and infant epigenetic age acceleration in 332 mother-infant dyads (56% female; 39% Black; 25% Hispanic). During the 2nd trimester, mothers self-reported childhood adversity and past-week restless sleep; DNA methylation from umbilical vein endothelial cells was used to estimate five epigenetic clocks. Multivariable linear regression was used to test study hypotheses. Despite no evidence of main effects, there was evidence of an interaction between maternal ACEs and restless sleep in predicting infant epigenetic age acceleration using the EPIC Gestational Age clock. Only infants whose mothers reported exposure to both ACEs and restless sleep demonstrated accelerated epigenetic aging. Results provide preliminary evidence that maternal childhood adversity and sleep may influence the infant epigenome.

Gene‒environment interaction effect of hypothalamic‒pituitary‒adrenal axis gene polymorphisms and job stress on the risk of sleep disturbances.

Background: Studies have shown that chronic exposure to job stress may increase the risk of sleep disturbances and that hypothalamic‒pituitary‒adrenal (HPA) axis gene polymorphisms may play an important role in the psychopathologic mechanisms of sleep disturbances. However, the interactions among job stress, gene polymorphisms and sleep disturbances have not been examined from the perspective of the HPA axis. This study aimed to know whether job stress is a risk factor for sleep disturbances and to further explore the effect of the HPA axis gene × job stress interaction on sleep disturbances among railway workers. Methods: In this cross-sectional study, 671 participants (363 males and 308 females) from the China Railway Fuzhou Branch were included. Sleep disturbances were evaluated with the Pittsburgh Sleep Quality Index (PSQI), and job stress was measured with the Effort-Reward Imbalance scale (ERI). Generalized multivariate dimensionality reduction (GMDR) models were used to assess gene‒environment interactions. Results: We found a significant positive correlation between job stress and sleep disturbances (P < 0.01). The FKBP5 rs1360780-T and rs4713916-A alleles and the CRHR1 rs110402-G allele were associated with increased sleep disturbance risk, with adjusted ORs (95% CIs) of 1.75 [1.38-2.22], 1.68 [1.30-2.18] and 1.43 [1.09-1.87], respectively. However, the FKBP5 rs9470080-T allele was a protective factor against sleep disturbances, with an OR (95% CI) of 0.65 [0.51-0.83]. GMDR analysis indicated that under job stress, individuals with the FKBP5 rs1368780-CT, rs4713916-GG, and rs9470080-CT genotypes and the CRHR1 rs110402-AA genotype had the greatest risk of sleep disturbances. Conclusions: Individuals carrying risk alleles who experience job stress may be at increased risk of sleep disturbances. These findings may provide new insights into stress-related sleep disturbances in occupational populations.

Shared genetic architecture and causal relationship between sleep behaviors and lifespan.

Poor sleep health is associated with a wide array of increased risk for cardiovascular, metabolic and mental health problems as well as all-cause mortality in observational studies, suggesting potential links between sleep health and lifespan. However, it has yet to be determined whether sleep health is genetically or/and causally associated with lifespan. In this study, we firstly studied the genome-wide genetic association between four sleep behaviors (short sleep duration, long sleep duration, insomnia, and sleep chronotype) and lifespan using GWAS summary statistics, and both sleep duration time and insomnia were negatively correlated with lifespan. Then, two-sample Mendelian randomization (MR) and multivariable MR analyses were applied to explore the causal effects between sleep behaviors and lifespan. We found that genetically predicted short sleep duration was causally and negatively associated with lifespan in univariable and multivariable MR analyses, and this effect was partially mediated by coronary artery disease (CAD), type 2 diabetes (T2D) and depression. In contrast, we found that insomnia had no causal effects on lifespan. Our results further confirmed the negative effects of short sleep duration on lifespan and suggested that extension of sleep may benefit the physical health of individuals with sleep loss. Further attention should be given to such public health issues.

Causal associations between leisure sedentary behaviors and sleep status with frailty: insight from Mendelian randomization study.

BACKGROUND: Observational studies have suggested that sedentary behaviors and sleep status are associated with frailty. However, it remains unclear whether these associations are causal. METHODS: Using summary statistics from genome-wide association studies, we evaluated the causal effect of modifiable risk factors, including leisure sedentary behaviors and sleep status on the frailty index (FI) using two-sample univariable and multivariable Mendelian randomization (MR) analyses. Genetic correlations were tested between the correlated traits. RESULTS: We identified potential causal associations between the time spent watching television (ß = 0.26, 95% confidence interval [CI]: 0.21-0.31, P = 3.98e-25), sleep duration (ß = -0.18, 95%CI: -0.26, -0.10; P = 6.04e-06), and daytime napping (ß = 0.29, 95%CI: 0.18-0.41, P = 2.68e-07) and the FI based on the inverse-variance-weighted method. The estimates were consistent across robust and multivariate MR analyses. Linkage disequilibrium score regression detected a genetic correlation between the time spent watching television (Rg = 0.43, P = 6.46e-48), sleep duration (Rg = -0.20, P = 5.29e-10), and daytime napping (Rg = 0.25, P = 3.34e-21) and the FI. CONCLUSIONS: Genetic predispositions to time spent watching television and daytime napping were positively associated with the FI, while sleep duration was negatively associated with the FI. Our findings offer key insights into factors influencing biological aging and suggest areas for interventions to promote healthy aging and slow down the aging process.

Neuropsychiatric disorders, chronotype and sleep: A narrative review of GWAS findings and the application of Mendelian randomization to investigate causal relationships.

Genome-wide association studies (GWAS) have been important for characterizing the genetic component and enhancing our understanding of the biological aetiology of both neuropsychiatric disorders and sleep-related phenotypes such as chronotype, which is our preference for morning or evening time. Mendelian randomization (MR) is a post-GWAS analysis that is used to infer causal relationships between potential risk factors and outcomes. MR uses genetic variants as instrumental variants for exposures to study the effect on outcomes. This review details the main results from GWAS of neuropsychiatric disorders and sleep-related phenotypes, and the application of MR to investigate their bidirectional relationship. The main results from MR studies of neuropsychiatric disorders and sleep-related phenotypes are summarized. These MR studies have identified 37 causal relationships between neuropsychiatric disorders and sleep-related phenotypes. MR studies identified evidence of a causal role for five neuropsychiatric disorders and symptoms (attention deficit hyperactivity disorder, bipolar disorder, depressive symptoms, major depressive disorder and schizophrenia) on sleep-related phenotypes and evidence of a causal role for five sleep-related phenotypes (daytime napping, insomnia, morning person, long sleep duration and sleep duration) on risk for neuropsychiatric disorders. These MR results show a bidirectional relationship between neuropsychiatric disorders and sleep-related phenotypes and identify potential risk factors for follow-up studies.

Association of sleep traits with myopia in children and adolescents: A meta-analysis and Mendelian randomization study.

PURPOSE: The association between sleep and myopia in children and adolescents has been reported, yet it remains controversial and inconclusive. This study aimed to investigate the influence of different sleep traits on the risk of myopia using meta-analytical and Mendelian randomization (MR) techniques. METHODS: The literature search was performed in August 31, 2023 based on PubMed, Embase, Web of Science, and Cochrane library. The meta-analysis of observational studies reporting the relationship between sleep and myopia was conducted. MR analyses were carried out to assess the causal impact of genetic pre-disposition for sleep traits on myopia. RESULTS: The results of the meta-analysis indicated a significant association between the risk of myopia and both short sleep duration [odds ratio (OR) = 1.23, 95% confidence interval (CI) = 1.08-1.42, P = 0.003] and long sleep duration (OR = 0.75, 95% CI = 0.66-0.86, P < 0.001). MR analyses revealed no significant causal associations of genetically determined sleep traits with myopia, including chronotype, sleep duration, short sleep duration and long sleep duration (all P > 0.05). CONCLUSIONS: No evidence was found to support a causal relationship between sleep traits and myopia. While sleep may not independently predict the risk of myopia, the potential impact of sleep on the occurrence and development of myopia cannot be disregarded.

Exome sequencing identifies genes associated with sleep-related traits.

Sleep is vital for human health and has a moderate heritability. Previous genome-wide association studies have limitations in capturing the role of rare genetic variants in sleep-related traits. Here we conducted a large-scale exome-wide association study of eight sleep-related traits (sleep duration, insomnia symptoms, chronotype, daytime sleepiness, daytime napping, ease of getting up in the morning, snoring and sleep apnoea) among 450,000 participants from UK Biobank. We identified 22 new genes associated with chronotype (ADGRL4, COL6A3, CLK4 and KRTAP3-3), daytime sleepiness (ST3GAL1 and ANKRD12), daytime napping (PLEKHM1, ANKRD12 and ZBTB21), snoring (WDR59) and sleep apnoea (13 genes). Notably, 20 of these genes were confirmed to be significantly associated with sleep disorders in the FinnGen cohort. Enrichment analysis revealed that these discovered genes were enriched in circadian rhythm and central nervous system neurons. Phenotypic association analysis showed that ANKRD12 was associated with cognition and inflammatory traits. Our results demonstrate the value of large-scale whole-exome analysis in understanding the genetic architecture of sleep-related traits and potential biological mechanisms.

Adaptive changes in BMAL2 with increased locomotion associated with the evolution of unihemispheric slow-wave sleep in mammals.

Marine mammals, especially cetaceans, have evolved a very special form of sleep characterized by unihemispheric slow-wave sleep (USWS) and a negligible amount or complete absence of rapid-eye-movement sleep; however, the underlying genetic mechanisms remain unclear. Here, we detected unique, significant selection signatures in basic helix-loop-helix ARNT like 2 (BMAL2; also called ARNTL2), a key circadian regulator, in marine mammal lineages, and identified two nonsynonymous amino acid substitutions (K204E and K346Q) in the important PER-ARNT-SIM domain of cetacean BMAL2 via sequence comparison with other mammals. In vitro assays revealed that these cetacean-specific mutations specifically enhanced the response to E-box-like enhancer and consequently promoted the transcriptional activation of PER2, which is closely linked to sleep regulation. The increased PER2 expression, which was further confirmed both in vitro and in vivo, is beneficial for allowing cetaceans to maintain continuous movement and alertness during sleep. Concordantly, the locomotor activities of zebrafish overexpressing the cetacean-specific mutant bmal2 were significantly higher than the zebrafish overexpressing the wild-type gene. Subsequently, transcriptome analyses revealed that cetacean-specific mutations caused the upregulation of arousal-related genes and the downregulation of several sleep-promoting genes, which is consistent with the need to maintain hemispheric arousal during USWS. Our findings suggest a potential close relationship between adaptive changes in BMAL2 and the remarkable adaptation of USWS and may provide novel insights into the genetic basis of the evolution of animal sleep.

Associations between sleep-behavioral traits and healthspan: A one-sample Mendelian randomization study based on 388,909 participants of the UK-Biobank.

BACKGROUND: Although the association between sleep behavior and morbidity and mortality risk has been reported before, there is still uncertainty whether the observed associations are causal or confounding. Therefore, we investigated the causal relationships between sleep-behavioral traits and terminated healthspan risk using Mendelian randomization (MR). METHODS: We conducted a one-sample MR analysis to evaluate causality between six sleep-behavioral traits (sleep duration, chronotype/morningness, napping, sleeplessness/insomnia, and getting up from bed) and risk of healthspan termination among 388, 909 UK Biobank (UKB) participants. Instrumental variables for sleep behaviors (N = 590) were obtained from recent genome-wide association studies (GWAS). We defined healthspan based on eight predominant health-terminating events associated with longevity (congestive heart failure, myocardial infarction, chronic obstructive pulmonary disease, stroke, dementia, diabetes, cancer, and death). We further constructed a sleep score and a weighted genetic risk score to increase the predictive ability of the sleep-behavioral traits. Cox regression models and Inverse Probability Treatment Weighting (IPTW) were implemented, followed by MR to assess causation. We used inverse-variance-weighted MR to estimate causal effects, and weighted-median and MR-egger for sensitivity analysis to test the pleiotropic effects. RESULTS: In IPTW, we observed a decreased risk of terminated healthspan for healthy sleep behaviors such as 'sleep duration 7-8h/d' (Hazard ratio, HR = 0.93; 95 % confidence interval, CI: 0.92-0.96; P < 0.001); 'morningness' (HR = 0.95; 95%CI: 0.93-0.98; P < 0.01); 'napping' (HR = 0.93; 95%CI: 0.91-0.94; P < 0.001); 'easy getting up from bed' (HR = 0.91; 95%CI: 0.88-0.93; P < 0.001); and, 'never/rarely experience sleeplessness/insomnia' (HR = 0.94; 95%CI: 0.92-0.96; P < 0.001). MR results further indicated causal associations between healthy sleep duration (OR = 0.98; 95%CI: 0.97-1.00; P = 0.036) and insomnia (OR = 1.02; 95%CI: 1.01-1.03; P < 0.001) with terminated healthspan. MR-egger did not suggest any potential pleiotropy. CONCLUSION: This study supports abnormal sleep duration and insomnia as potential causal risk factors for terminated healthspan. Thus, healthy sleep behavior is valuable for the extension of healthspan, and well-designed and tailored sleep health interventions are warranted.

Single-cell transcriptomics reveals that glial cells integrate homeostatic and circadian processes to drive sleep-wake cycles.

The sleep-wake cycle is determined by circadian and sleep homeostatic processes. However, the molecular impact of these processes and their interaction in different brain cell populations are unknown. To fill this gap, we profiled the single-cell transcriptome of adult Drosophila brains across the sleep-wake cycle and four circadian times. We show cell type-specific transcriptomic changes, with glia displaying the largest variation. Glia are also among the few cell types whose gene expression correlates with both sleep homeostat and circadian clock. The sleep-wake cycle and sleep drive level affect the expression of clock gene regulators in glia, and disrupting clock genes specifically in glia impairs homeostatic sleep rebound after sleep deprivation. These findings provide a comprehensive view of the effects of sleep homeostatic and circadian processes on distinct cell types in an entire animal brain and reveal glia as an interaction site of these two processes to determine sleep-wake dynamics.

Genome-wide association in Drosophila identifies a role for Piezo and Proc-R in sleep latency.

Sleep latency, the amount of time that it takes an individual to fall asleep, is a key indicator of sleep need. Sleep latency varies considerably both among and within species and is heritable, but lacks a comprehensive description of its underlying genetic network. Here we conduct a genome-wide association study of sleep latency. Using previously collected sleep and activity data on a wild-derived population of flies, we calculate sleep latency, confirming significant, heritable genetic variation for this complex trait. We identify 520 polymorphisms in 248 genes contributing to variability in sleep latency. Tests of mutations in 23 candidate genes and additional putative pan-neuronal knockdown of 9 of them implicated CG44153, Piezo, Proc-R and Rbp6 in sleep latency. Two large-effect mutations in the genes Proc-R and Piezo were further confirmed via genetic rescue. This work greatly enhances our understanding of the genetic factors that influence variation in sleep latency.

Causal association between sleep traits and autoimmune arthritis: Evidence from a bidirectional Mendelian randomization study.

OBJECTIVE: To explore whether there is a genetic causal relationship between sleep traits and the risk of autoimmune arthritis (AA). METHODS: Univariable and multivariable Mendelian randomization was employed using genome-wide association studies data to assess sleep traits' associations with AAs, including rheumatoid arthritis (RA), ankylosing spondylitis, and psoriatic arthritis. The inverse-variance weighted method served as the primary analysis, supplemented by the CAUSE method to improve power and mitigate false positives. Mediation Mendelian randomization was used to quantify direct and indirect effects. RESULTS: Significant associations were shown between insomnia symptoms and increased risk of overall RA (odds ratio = 2.75, 95% confidence interval 1.45-5.22) and seronegative RA (odds ratio = 6.95, 95% confidence interval 2.47-19.56). CAUSE results revealed an association of insomnia symptoms with overall RA and seronegative RA, as well as the sleep duration with overall RA. After the adjustment for body mass index, alcohol status, smoking status, and physical activity levels, multivariable analyses revealed that genetic predisposition to insomnia symptoms and prolonged sleep duration showed independent negative associations with the risk of overall RA and seropositive RA. In the reversed multivariable analyses, a borderline negative association was shown in the overall RA-sleep duration and a positive association of seropositive RA with the risk of insomnia symptoms. CONCLUSION: This study demonstrated a potential bidirectional causal relationship that genetic predisposition to insomnia symptoms and shorter sleep duration was associated with the risk of AA, especially RA. Genetic predisposition to RA was also associated with decreased sleep duration, as well as increased insomnia symptom risk.

Genetics of sleep medication purchases suggests causality from sleep problems to psychiatric traits.

STUDY OBJECTIVES: Over 10% of the population in Europe and in the United States use sleep medication to manage sleep problems. Our objective was to elucidate genetic risk factors and clinical correlates that contribute to sleep medication purchase and estimate the comorbid impact of sleep problems. METHODS: We performed epidemiological analysis for psychiatric diagnoses, and genetic association studies of sleep medication purchase in 797 714 individuals from FinnGen Release 7 (N = 311 892) and from the UK Biobank (N = 485 822). Post-association analyses included genetic correlation, co-localization, Mendelian randomization (MR), and polygenic risk estimation. RESULTS: In a GWAS we identified 27 genetic loci significantly associated with sleep medication, located in genes associated with sleep; AUTS2, CACNA1C, MEIS1, KIRREL3, PAX8, GABRA2, psychiatric traits; CACNA1C, HIST1H2BD, NUDT12. TOPAZ1 and TSNARE1. Co-localization and expression analysis emphasized effects on the KPNA2, GABRA2, and CACNA1C expression in the brain. Sleep medications use was epidemiologically related to psychiatric traits in FinnGen (OR [95% (CI)] = 3.86 [3.78 to 3.94], p < 2 × 10-16), and the association was accentuated by genetic correlation and MR; depression (rg = 0.55 (0.027), p = 2.86 × 10-89, p MR = 4.5 × 10-5), schizophrenia (rg = 0.25 (0.026), p = 2.52 × 10-21, p MR = 2 × 10-4), and anxiety (rg = 0.44 (0.047), p = 2.88 × 10-27, p MR = 8.6 × 10-12). CONCLUSIONS: These results demonstrate the genetics behind sleep problems and the association between sleep problems and psychiatric traits. Our results highlight the scientific basis for sleep management in treating the impact of psychiatric diseases.

Associations Between Sleep Traits and Social Isolation: Observational and Bidirectional Mendelian Randomization Study.

Social isolation has been found associated with multiple sleep traits in conventional observational studies. However, whether this association is causal and if so, its direction is uncertain. We analyzed the association between social isolation and multiple sleep traits in 30 430 participants from the Guangzhou Biobank Cohort Study. In bidirectional Mendelian randomization, we used 6, 17, and 11 single nucleotide polymorphisms associated with attendance at sports club/gym, religious group, and pub/social club from the UK Biobank (n = 452 302), respectively, and 152 single nucleotide polymorphisms associated with insomnia from the combination of UK Biobank and 23andme (n = 1 331 010). Observationally in the Guangzhou Biobank Cohort Study, insomnia (yes/no) (beta = 0.12, 95% confidence interval (CI) 0.10-0.16) and poor sleep quality (yes/no) (beta = 0.12, CI: 0.08-0.15), but not sleep duration and chronotype, were associated with a higher social isolation score (severe social isolation). In bidirectional MR, genetically predicted insomnia decreases the odds of attendance at sports club/gym (beta = 0.98, CI: 0.98-0.99) and religious groups (beta = 0.99, CI: 0.98-0.99), but not pub/social club. However, these 3 types of social activity were not associated with insomnia. Our results support the causal effects of insomnia on social activity. Further clinical investigations into the utility of insomnia treatment in alleviating social isolation are needed.

Sleep patterns according to genetically determined ethnicity in the population of São Paulo, Brazil.

Sleep is a behavior expressed differently for each individual. However, studies have shown that some ethnic groups express common sleep patterns, which can be observed in different ethnic groups. Previous studies have shown the existence of sleep disparities in populations of different ethnicities. Most of these studies have considered self-reported ethnicity and assessed sleep subjectively. Therefore, the aim of this study was to evaluate sleep disparities in different ethnic groups based on an analysis of genetic ancestry and the use of objective sleep evaluation. To do this, we used data from the São Paulo Epidemiologic Sleep Study (EPISONO), which was undertaken in Brazil, a country that is known for its ethnic/racial diversity. All individuals completed a series of questionnaires, underwent full polysomnography and had their blood collected for DNA extraction. After genotyping and identifying samples with high-quality DNA suitable for genetic analysis, 31 ancestry-informative markers (AIMs) were selected. These markers exhibited substantial allelic frequency differences, enabling the characterization of the three primary founding populations of modern Brazil - Europeans, West-Africans, and Native Americans. Through this analysis, the genetic contribution of each of these ancestral groups was identified in respect of each participant. Based on this, a latent class cluster analysis (LCCA) was performed to define the three clusters that best classified the sample according to ethnic group: African (n = 255), Caucasian (n = 668) and Native American (n = 83). Applying the adjusted model for the confounding variables (age, socio-economic class and sex), statistically significant differences in sleep variables between ethnicities were found. Africans had higher sleep latency compared to the other groups (ß = 4.46, CI = 1.18 to 7.74 and ß = 7.83, CI = 3.50 to 12.15), while Caucasians had longer total sleep time (ß = -16.47, CI = -29.94 to -2.99) and better sleep efficiency (ß = -2.19, CI = -4.35 to -0.02) compared to Africans. Regarding the respiratory arousals index (ß = -1.11, IC = -2.07 to -0.16) and periodic leg movements index (ß = -7.48, CI = -12.08 to -2.88), both were higher among Caucasians compared to Africans. We were able to conclude that genetic ancestry might modulate sleep structure and the occurrence of sleep disorders.

DAYWAKE implicates novel roles for circulating lipid-binding proteins as extracerebral regulators of daytime wake-sleep behavior.

Sleep during the midday, commonly referred to as siesta, is a common trait of animals that mainly sleep during the night. Work using Drosophila led to the identification of the daywake (dyw) gene, found to have anti-siesta activity. Herein, we show that the DYW protein undergoes signal peptide-dependent secretion, is present in the circulatory system, and accumulates in multiple organs, but, surprisingly, it is not detected in the brain where wake-sleep centers are located. The abundance of DYW in adult flies is regulated by age, sex, temperature, and the splicing efficiency of a nearby thermosensitive intron. We suggest that DYW regulates daytime wake-sleep balance in an indirect, extracerebral manner, via a multi-organ network that interfaces with the circulatory system.

Analysis of epigenetic clocks links yoga, sleep, education, reduced meat intake, coffee, and a SOCS2 gene variant to slower epigenetic aging.

DNA methylation (DNAm) clocks hold promise for measuring biological age, useful for guiding clinical interventions and forensic identification. This study compared the commonly used DNAm clocks, using DNA methylation and SNP data generated from nearly 1000 human blood or buccal swab samples. We evaluated different preprocessing methods for age estimation, investigated the association of epigenetic age acceleration (EAA) with various lifestyle and sociodemographic factors, and undertook a series of novel genome-wide association analyses for different EAA measures to find associated genetic variants. Our results highlighted the Skin&Blood clock with ssNoob normalization as the most accurate predictor of chronological age. We provided novel evidence for an association between the practice of yoga and a reduction in the pace of aging (DunedinPACE). Increased sleep and physical activity were associated with lower mortality risk score (MRS) in our dataset. University degree, vegetable consumption, and coffee intake were associated with reduced levels of epigenetic aging, whereas smoking, higher BMI, meat consumption, and manual occupation correlated well with faster epigenetic aging, with FitAge, GrimAge, and DunedinPACE clocks showing the most robust associations. In addition, we found a novel association signal for SOCS2 rs73218878 (p = 2.87 × 10-8) and accelerated GrimAge. Our study emphasizes the importance of an optimized DNAm analysis workflow for accurate estimation of epigenetic age, which may influence downstream analyses. The results support the influence of genetic background on EAA. The associated SOCS2 is a member of the suppressor of cytokine signaling family known for its role in human longevity. The reported association between various risk factors and EAA has practical implications for the development of health programs to improve quality of life and reduce premature mortality associated with age-related diseases.

Multivariate genome-wide association study of sleep health demonstrates unity and diversity.

There has been a recent push to focus sleep research less on disordered sleep and more on the dimensional sleep health. Sleep health incorporates several dimensions of sleep: chronotype, efficiency, daytime alertness, duration, regularity, and satisfaction with sleep. A previous study demonstrated sleep health domains correlate only moderately with each other at the genomic level (|rGs| = 0.11-0.51) and show unique relationships with psychiatric domains (controlling for shared variances, duration, alertness, and non-insomnia independently related to a factor for internalizing psychopathology). Of the domains assessed, circadian preference was the least genetically correlated with all other facets of sleep health. This pattern is important because it suggests sleep health should be considered a multifaceted construct rather than a unitary construct. Prior genome-wide association studies (GWASs) have vastly increased our knowledge of the biological underpinnings of specific sleep traits but have only focused on univariate analyses. We present the first multivariate GWAS of sleep and circadian health (multivariate circadian preference, efficiency, and alertness factors, and three single-indicator factors of insomnia, duration, and regularity) using genomic structural equation modeling. We replicated loci found in prior sleep GWASs, but also discovered "novel" loci for each factor and found little evidence for genomic heterogeneity. While we saw overlapping genomic enrichment in subcortical brain regions and shared associations with external traits, much of the genetic architecture (loci, mapped genes, and enriched pathways) was diverse among sleep domains. These results confirm sleep health as a family of correlated but genetically distinct domains, which has important health implications.