Jul 2026· Journal of Sleep Research· pp.
e70411
· 0 citations· 28 references
Medicine
TL;DR
Findings indicate that genetically determined short sleep duration and insomnia symptoms are associated with mental and neurological problems, cardiovascular disease and musculoskeletal disorders, suggesting a potentially preventive, causal role of healthy sleeping patterns on chronic disease.
Abstract
Sleep-related and chronotype traits have been shown to impact health in observational studies. To identify whether these associations are potentially causal, we conducted phenome-wide Mendelian randomisation analyses of short sleep, insomnia symptoms, total sleep duration, long sleep, snoring, daytime sleepiness and morning chronotype with a broad range of health-related phenotypes. We assessed the association between the genetic predisposition to these traits and the occurrence of 702 health-related phenotypes, using summary statistics of the largest genome-wide association studies in European individuals. Results that were significant (multiple comparisons: False Discovery Rate) and valid (robust genetic instruments, unaffected by horizontal pleiotropy) were validated using data from the second largest European genome-wide association study. Genetically determined short sleep was associated with increased risks of attention-deficit/hyperactivity disorder and neuroticism, musculoskeletal conditions, asthma and gastroesophageal reflux and lower educational attainment. Genetically determined insomnia symptoms showed associations with increased risk of coronary artery disease, major depression and osteoarticular disease. Genetically determined long sleep was linked to higher risk of iron deficiency anaemia and lower bone mineral density. Genetic predisposition to snoring was associated with more falls, greater body mass and higher low-grade inflammation. Genetically determined morning chronotype was related to higher vitamin D levels and lower risk of irritable bowel syndrome. No associations were found for daytime sleepiness. Overall, these findings indicate that genetically determined short sleep duration and insomnia symptoms are associated with mental and neurological problems, cardiovascular disease and musculoskeletal disorders, suggesting a potentially preventive, causal role of healthy sleeping patterns on chronic disease.
OBJECTIVE
This study applied two-sample Mendelian randomization (MR) to elucidate causal relationships between sleep-related phenotypes and childhood asthma risk.
METHODS
Instrumental variables for daytime napping, sleep disorders, chronotype, and fatigue were selected from European ancestry genome-wide association studies. Causal estimates were primarily derived using inverse-variance weighting (IVW), supplemented by sensitivity analyses including MR-Egger and MR-PRESSO. Instrument validity, heterogeneity, pleiotropy, and directionality were rigorously evaluated.
RESULTS
IVW results demonstrated that genetic susceptibility to daytime napping (OR = 1.76; 95% CI: 1.07-2.88; p < .05), sleep disorders (OR = 1.35; 95% CI: 1.12-1.61; p < .05), and frequent fatigue (OR = 2.94; 95% CI: 1.61-5.38; p < .05) significantly increased asthma risk, whereas morning chronotype was protective (OR = 0.76; 95% CI: 0.61-0.98; p = .015). Sensitivity analyses supported these findings, with no evidence of pleiotropy or reverse causation.
CONCLUSIONS
These results suggest that sleep behaviors causally influence childhood asthma risk and may represent modifiable targets for prevention and management.
Li Yin, Feifei Zhang, Fang Li et al.· Pediatric Allergy and Immuno...· 0 citations
STUDY OBJECTIVES
Since genome-wide association studies (GWAS) of sleep phenotypes have been conducted in differing populations and definitions of sleep phenotypes vary across studies, we investigated associations between several polygenic risk scores (PRSs) and potential sleep definitions among multiethnic cohorts.
METHODS
Using data from four cohorts (HCHS/SOL, ARIC, MESA, BHS, N = 16 895), we considered multiple definitions of short and long sleep, insomnia, and excessive daytime sleepiness (EDS). PRSs were developed based on summary statistics from GWAS in European ancestry individuals from the UK Biobank (UKB) and from GWAS conducted in a multiethnic population from the Million Veteran Program (MVP). Study-specific analyses estimated associations between sleep PRSs and corresponding sleep measures per 1 standard deviation increase in the PRS. Models were adjusted for age, sex, ancestral principal components, and center and race as appropriate. Results were meta-analyzed across studies.
RESULTS
PRSs based on European ancestry UKB GWAS had statistically significant associations with multiple definitions of the corresponding sleep phenotypes. Associations that were most consistent across studies included: short sleep PRS with ≤6 hours (OR = 1.23,p = 1.80x10-7,phet = 0.97); long sleep PRS with ≥9 hours (OR = 1.09,p = 6.76x10-4,phet = 0.77); insomnia PRS with the Women's Health Initiative Insomnia Rating Scale (WHIIRS) ≥10 or a subset of three questions ≥6 in ARIC (OR = 1.17,p = 5.51x10-10,phet = 0.69); and EDS PRS with Epworth Sleepiness Scale (ESS) ≥11 (OR = 1.23,p = 1.83x10-13,phet = 0.83). PRSs based on multi-ancestry MVP GWAS had weaker associations compared to those based on European ancestry only.
CONCLUSIONS
By evaluating several types of sleep PRSs and sleep phenotypes, we were able to highlight which sleep PRS performed well across diverse populations and which sleep definitions better captured genetic underpinnings.
A. Wyss, Michael Brown, Xiang Li et al.· Sleep· 0 citations
Background The relationship between sleep disorders and psychiatric disorders has been extensively studied in epidemiological research. However, whether specific sleep-related traits are associated with psychiatric disorders through potential causal mechanisms remains incompletely understood. Methods This study employed a two-sample Mendelian randomization (MR) analysis method to investigate potential causal associations between six sleep-related traits and eleven psychiatric disorders. MR analyses were performed using inverse variance weighting (IVW), weighted median, and MR-Egger methods. Cochran’s Q test was used to assess heterogeneity, while MR-Egger intercept analysis and MR-PRESSO (Mendelian Randomization Pleiotropy RESidual Sum and Outlie) were applied to evaluate potential horizontal pleiotropy. In addition, a retrospective observational study was conducted using clinical data from the First Affiliated Hospital of Soochow University between November 2023 and December 2025. Logistic regression analysis was performed to assess the association between sleep disorders and psychiatric disorders. Results MR analyses identified potential associations between sleep-related traits and psychiatric disorders. Genetically predicted insomnia was associated with an increased risk of major depressive disorder (OR = 2.22, 95% CI: 1.66–2.97, P < 0.001). In the retrospective clinical cohort, individuals with sleep disorders exhibited a higher prevalence of psychiatric disorders (adjusted OR = 1.71, 95% CI: 1.09–2.69, P = 0.020). The consistency between genetic evidence and clinical observational findings provides complementary support for the clinical relevance of the observed association. Conclusion By integrating MR analyses with retrospective clinical observational data, this study provides genetic and clinical evidence supporting an association between sleep disorders and psychiatric disorders. These findings suggest that sleep disturbances may represent potential modifiable factors associated with mental health outcomes and highlight the importance of sleep-related interventions in psychiatric disease prevention and management.
Xin Wu, Mei Chang, Bingyi Song et al.· Frontiers in Psychiatry· 0 citations
Sleep disturbances are prevalent in schizophrenia and are associated with symptom severity, yet findings remain inconsistent, reflecting unmeasured biological moderators. Chronotype and the BDNF genetic variant influence sleep regulation and schizophrenia-related phenotypes. However, their combined contribution to the sleep quality-symptom severity association remains unexplored. We aimed to characterise sleep quality and chronotype in schizophrenia, examine their associations with symptom severity, and determine whether BDNF Val66Met moderates these relationships. In this cross-sectional study, 217 individuals with schizophrenia were assessed for sleep quality (Pittsburgh Sleep Quality Index), chronotype (Morningness-Eveningness Questionnaire), and symptom severity (Positive and Negative Syndrome Scale) and genotyped for BDNF Val66Met. Multivariate regression evaluated the contributions of sleep quality, chronotype, and Val66Met genotype to symptom severity scores, adjusting for covariates. Plasma BDNF levels were measured in a subset of patients (n = 91). Poor sleep quality was prevalent in schizophrenia (69.12%) and was significantly associated with PANSS total (β = 0.35, P < 0.001), positive (β = 0.24, P < 0.001), negative (β = 0.27, P < 0.001), and general psychopathology scores (β = 0.31, P < 0.001). Schizophrenia patients with poor sleep quality had later illness onset (P = 0.02). Morning chronotype was associated with longer illness duration (P = 0.03) but lower general psychopathology (P = 0.02). BDNF Val66Met showed no association with sleep, chronotype, or symptom severity and did not moderate sleep-symptom relationships. Plasma BDNF levels were higher in poor sleepers (P < 0.001, r = 0.65), independent of Val66Met genotype. Our results showed poor sleep quality is associated with symptom severity in schizophrenia, including later illness onset, independent of chronotype or BDNF Val66Met variant.
Anusree A Kumar, Aisha Shaju, Midhun Sidharthan et al.· Progress in Neuro-psychophar...· 0 citations
Fatigue is a multifactorial condition influenced by environmental, behavioral, genetic, and disease-related factors. While observational studies have identified key contributors like circadian disruption, sleep disturbances, and genetic predisposition, the causal relationships remain unclear. Mendelian randomization (MR) offers a robust approach to overcome limitations of traditional studies and establish causal links between modifiable behavioral preferences and fatigue. This study employed univariate and multivariate MR (MVMR) analyses using publicly available genome-wide association study (GWAS) summary statistics to investigate the potential causal relationships between these behavioral preference factors and the risk of fatigue. We obtained GWAS summary statistics for relevant variables from the Neale Lab and MRC Integrated Epidemiology Unit (MRC-IEU) databases. After systematic screening of multiple domains (internal microenvironment, indoor environment parameters, and natural environment characteristics), the inverse variance weighted (IVW) method served as the primary analysis, complemented by sensitivity analysis (heterogeneity test, pleiotropy analysis, leave-one-out analysis, and MR-PRESSO) to evaluate result robustness. Using GWAS data from 32 traits (1645,048 participants), we identified three significant behavioral preference-related determinants of fatigue: chronotype, ease of getting up in the morning, and time spent outdoors in summer. The MR results demonstrated: Protective effects against fatigue associated with greater ease of getting up in the morning (OR = 0.991, 95%CI 0.987–0.995; P < .001) and longer summer outdoor exposure (OR = 0.996, 95%CI 0.992–1.000; P = .030); Elevated fatigue risk,linked to evening chronotype (OR = 1.003, 95%CI 1.001–1.005; P = .013). MVMR analysis showed that after jointly incorporating variables, the impact of ease of getting up in the morning on fatigue remained significant (OR = 0.987, 95%CI: 0.980–0.995, P = .002). Sensitivity analyses confirmed the robustness of these findings: although significant heterogeneity was detected for ease of getting up in the morning (Cochran’s Q test P < .05), no evidence of horizontal pleiotropy (MR-Egger intercept P > .05) or outlier SNPs (MR-PRESSO) was found, and results were consistent across multiple MR methods. These findings provide genetic evidence supporting causal relationships between modifiable behavioral preference factors and fatigue. Specifically, greater ease of getting up in the morning and longer summer outdoor exposure may reduce fatigue risk, while evening chronotype increases susceptibility.
Tao Luo, Fen Zhang, H. Xue et al.· Medicine· 0 citations
