Jul 2026· European Journal of Psychotraumatology· Vol 17 1, pp.
2692768
· 0 citations· 40 references
Medicine
TL;DR
Genetic evidence linking composite CM liability with selected sleep-related phenotypes, particularly self-reported DS, insomnia symptoms, and DN is provided, providing suggestive genetic evidence linking composite CM liability with selected sleep-related phenotypes.
Abstract
Background: Childhood maltreatment (CM) is associated with sleep disturbance, but observational findings may be affected by confounding, shared familial liability, and reverse-direction explanations. We conducted bidirectional two-sample Mendelian randomization (MR) to examine genetic evidence linking composite CM liability with six sleep-related phenotypes.Methods: Genetic instruments for CM were obtained from a large European-ancestry multi-cohort GWAS meta-analysis. CM was defined as a composite phenotype encompassing multiple abuse and neglect subtypes and ascertainment modes. Summary statistics for chronotype, daytime sleepiness (DS), insomnia symptoms, sleep apnea (SA), daytime napping (DN), and sleep duration (SD) were derived from large European-ancestry GWASs. Inverse-variance weighted MR was the primary method, with weighted median and MR-Egger sensitivity analyses. Benjamini-Hochberg correction was applied and reported as P(BH).Results: In forward MR, genetically proxied CM was associated with higher DS (OR = 1.04, 95% CI 1.01-1.07; P(BH) = 0.030), insomnia symptoms (OR = 1.08, 95% CI 1.01-1.15; P(BH) = 0.030), and DN (β = 0.07, 95% CI 0.03-0.09; P(BH) = 0.002). Little evidence was observed for chronotype, SA, or SD. In exploratory reverse-direction MR, genetic liability to DN (β = 0.16, 95% CI 0.05-0.27; P(BH) = 0.012) and insomnia symptoms (β = 0.21, 95% CI 0.07-0.35; P(BH) = 0.012) was associated with CM liability.Conclusions: This study provides suggestive genetic evidence linking composite CM liability with selected sleep-related phenotypes, particularly self-reported DS, insomnia symptoms, and DN. Reverse-direction findings may reflect shared genetic liability, gene-environment correlation, reporting-related mechanisms, or broader familial pathways rather than temporal effects of adult sleep traits on CM. Given modest effects and uneven sensitivity support, findings should be interpreted cautiously.
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
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.
Marta H Hernandez, Camille Lassale, A. Camps-Vilaró et al.· Journal of Sleep Research· 0 citations
Background Premenstrual disorder (PMD) and postpartum depression (PPD) have a strong phenotypic link and echo women’s hormone fluctuations. Yet, the extent to which they may be cross-inherited remains poorly understood. Methods Using the nationwide cohort of 907,841 women who born 1950-2007 and gave birth during 2001-2021 in Sweden, we estimated the cumulative incidence functions-based heritability and genetic correlation for PMD and PPD. We also analyzed genome-wide association study (GWAS) summary statistics from the largest European-ancestry cohorts for PMD (17,511 cases and 54,786 controls) and PPD (16,145 cases and 46,609 controls) using linkage disequilibrium score regression (LDSC). Fixed-effect cross-trait meta-analysis and imputed transcriptome-wide association analyses (TWAS) were conducted to identify shared loci and gene-tissue associations. Results The register-based heritability was 0.35 (95% CI: 0.29-0.41) for PMD and 0.31 (95% CI: 0.23-0.37) for PPD, with a positive genetic correlation between these disorders (rg = 0.47, 95% CI: 0.25–0.69). LDSC also showed a positive genetic correlation between PMD and PPD (rg = 0.66, SE = 0.10, P = 1.014×10−10), indicating sizable shared heritable influences. Cross-trait meta-analysis identified two novel genome-wide significant loci jointly associated with PMD and PPD, mapping to an intronic region of PCDH9 and the 3’ untranslated region of KCTD16. The KCTD16 locus implicates GABAB–mediated inhibitory signaling in both disorders. Consistent with this, TWAS revealed a hippocampus regulatory signal for KCTD16, with no detectable trend effects in other brain regions or peripheral tissues. Beyond the lead loci, TWAS suggested that the shared risk variants may partially act through genetically regulated gene expression across brain, endocrine and immune-related tissues. Conclusions Together, these findings provide the first evidence for sizable genetic overlap between PMD and PPD and highlight novel and convergent biological mechanisms underlying the abnormal brain response of some women to gonadal hormone fluctuations.
Susu Qu, Kejia Hu, J. Guintivano et al.· Research Square· 0 citations
This study aimed to investigate the genetic causality between cataract (senile and other types) and psychiatric disorders using Mendelian randomization (MR). We performed a bidirectional 2-sample MR analysis using genome-wide association studies summary data. Primary analysis employed inverse-variance weighted, MR-Egger, weighted median, and weighted mode methods. Sensitivity analyses included Cochran Q, MR-pleiotropy residual sum and outlier, MR-Egger intercept, and leave-one-out tests to assess heterogeneity and pleiotropy. Forward MR analysis revealed a suggestive causal effect of other cataract on anxiety (inverse-variance weighted odds ratio [OR] = 0.99, 95% confidence interval: 0.98–1.00, P = .043), though unsupported by other methods. MR-Egger and weighted median suggested potential associations between other cataract and bipolar disorder (P < .05). No significant links were found between senile cataract and psychiatric disorders. Reverse MR analysis showed no consistent causal effects, except for anxiety disorder on other cataract (MR-Egger OR = 8.04, P = .040; weighted median OR = 2.99, P = .047). Sensitivity analyses confirmed robustness despite heterogeneity. This study provides evidence of a potential causal relationship between other cataract and anxiety, though findings were method-dependent. No significant associations were observed for senile cataract or most psychiatric disorders.
Postpartum depression (PPD) is a common mental health disorder after childbirth. Although microbiome research in PPD has mainly focused on the gut, the role of skin microbiota remains unclear. We used Mendelian randomization (MR) to assess potential causal associations between skin microbiota and PPD. A bidirectional 2-sample MR analysis used genome-wide association study (GWAS) summary statistics. Genetic instruments for skin microbial features were obtained from a published skin microbiota GWAS, and PPD data were derived from 67,205 mothers (7604 cases, 59,601 controls). Instruments were selected at P <1 × 10−5, linkage disequilibrium-clumped, harmonized, and filtered for weak instruments (F statistic <10). Because this microbiome threshold is exploratory, Benjamini-Hochberg false discovery rate correction was applied within taxonomic levels. The inverse-variance weighted method was primary, complemented by weighted median and mode-based methods. Heterogeneity, pleiotropy, and outliers were assessed using Cochran Q, MR-Egger intercept, and MR-PRESSO. Three skin microbial taxa showed nominal associations with PPD. Higher genetically predicted Acinetobacter on the dorsal forearm (dry skin; 9 single nucleotide polymorphisms [SNPs]; mean F = 22.12) and Proteobacteria in the antecubital fossa (moist skin; 6 SNPs; mean F = 23.44) were associated with increased PPD risk, whereas Betaproteobacteria in the antecubital fossa (11 SNPs; mean F = 21.54) was associated with decreased risk. Associations were directionally consistent, with no substantial heterogeneity or horizontal pleiotropy. After multiple-testing assessment, the findings were exploratory rather than definitive. Reverse MR did not support an effect of PPD on the identified skin microbiota. This MR study provides exploratory genetic evidence linking specific skin microbial features to PPD risk. The findings extend microbiota-related hypotheses beyond the gut microbiome but require validation in larger microbiome GWAS datasets, longitudinal cohorts, and mechanistic studies before clinical or causal conclusions are drawn.