GWAS Meta-Analysis Reveals Shared Genes and Biological Pathways between Major Depressive Disorder and Insomnia

Correlation between psychological stress and depressive symptoms among Japanese university students: a cross-sectional analysis

[Purpose] Higher education students face significant environmental changes, placing them at heightened risk of developing depressive symptoms that have been exacerbated by the coronavirus infectious disease pandemic. This study examined the association between psychological stress and depressive symptoms among Japanese university students. [Participants and Methods] We conducted an online and face-to-face questionnaire survey with 145 Japanese university students studying rehabilitation sciences. Depressive symptoms and psychological stress were evaluated using the Self-rating Depression Scale and Stress Response Scale-18, respectively. [Results] Among the participants, 88 had depressive symptoms. Compared to the non-depressive symptom group, the depressive symptom group experienced higher psychological stress and comprised significantly more women and individuals with insomnia. Logistic regression analysis revealed that psychological stress and insomnia were independent predictors of depressive symptoms. [Conclusion] Psychological stress is independently associated with depressive symptoms. The correlation between insomnia, stress, and depressive symptoms requires further investigation. Future research should explore the causal relationship between psychological stress and depressive symptoms and consider the factors that may influence this relationship.

The association between epilepsy and sleep disturbance in US adults: the mediating effect of depression

BACKGROUND

People with epilepsy (PWE) frequently experience sleep disturbances that can severely affect their quality of life. Depression is also a common symptom in the PWE population and can aggravate sleep problems. However, the interplay between epilepsy, depression, and sleep disturbances is not yet fully understood. Our study was designed to investigate the association between epilepsy and sleep disturbances in US adults and to determine whether depressive symptoms play a mediating role in this relationship.

METHODS

We examined data from the National Health and Nutrition Examination Survey (NHANES) spanning January 1, 2015, to March 2020, before the pandemic.A total of 10,093 participants aged ≥ 20 years with complete data on epilepsy and sleep disturbance were included. Weighted multiple logistic regression and mediation analysis were used to explore the associations among depression, epilepsy, and sleep disturbance. Interaction effects of epilepsy with various covariates were also investigated.

RESULTS

Epilepsy was associated with depression and sleep disturbances. Weighted logistic regression analysis revealed a significant association between epilepsy and sleep disturbances (OR = 3.67, 95% CI = 1.68-8.04). Depression partially mediated this relationship, demonstrating a mediation effect of 23.0% (indirect effect = 0.037, P < 0.001). Subgroup analyses revealed variations in the relationship between epilepsy and sleep disturbances among different groups. Furthermore, interaction analyses revealed significant interactions between epilepsy and age (P = 0.049) and hypertension (P = 0.045).

CONCLUSIONS

Our study utilizing NHANES data confirmed that depression partially mediated the association between epilepsy and sleep disturbance. Additionally, we observed differences in this association across demographic groups. Addressing depressive symptoms in PWE may improve their sleep quality, but further research is needed to explore the underlying mechanisms.

Shared genetic mechanisms underlying association between sleep disturbances and depressive symptoms

OBJECTIVES

Polygenic scores (PGS) for sleep disturbances and depressive symptoms in an epidemiological cohort were contrasted. The overlap between genes assigned to variants that compose the PGS predictions was tested to explore the shared genetic bases of sleep problems and depressive symptoms.

METHODS

PGS analysis was performed on the São Paulo Epidemiologic Sleep Study (EPISONO, N = 1042), an adult epidemiological sample. A genome wide association study (GWAS) for depression grounded the PGS calculations for Beck Depression Index (BDI), while insomnia GWAS based the PGS for Insomnia Severity Index (ISI) and Pittsburg Sleep Quality Index (PSQI). Pearson's correlation was applied to contrast PGS and clinical scores. Fisher's Exact and Benjamin-Hochberg tests were used to verify the overlaps between PGS-associated genes and the pathways enriched among their intersections.

RESULTS

All PGS models were significant when individuals were divided as cases or controls according to BDI (R2 = 1.2%, p = 0.00026), PSQI (R2 = 3.3%, p = 0.007) and ISI (R2 = 3.4%, p = 0.021) scales. When clinical scales were used as continuous variables, the PGS models for BDI (R2 = 1.5%, p = 0.0004) and PSQI scores (R2 = 3.3%, p = 0.0057) reached statistical significance. PSQI and BDI scores were correlated, and the same observation was applied to their PGS. Genes assigned to variants that compose the best-fit PGS predictions for sleep quality and depressive symptoms were significantly overlapped. Pathways enriched among the intersect genes are related to synapse function.

CONCLUSIONS

The genetic bases of sleep quality and depressive symptoms are correlated; their implicated genes are significantly overlapped and converge on neural pathways. This data suggests that sleep complaints accompanying depressive symptoms are not secondary issues, but part of the core mental illness.

Potential genetic and epigenetic mechanisms in insomnia: A systematic review

Insomnia is a stress-related sleep disorder conceptualised within a diathesis-stress framework, which it is thought to result from predisposing factors interacting with precipitating stressful events that trigger the development of insomnia. Among predisposing factors genetics and epigenetics may play a role. A systematic review of the current evidence for the genetic and epigenetic basis of insomnia was conducted according to Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) system. A total of 24 studies were collected for twins and family heritability, 55 for genome-wide association studies, 26 about candidate genes for insomnia, and eight for epigenetics. Data showed that insomnia is a complex polygenic stress-related disorder, and it is likely to be caused by a synergy of genetic and environmental factors, with stress-related sleep reactivity being the important trait. Even if few studies have been conducted to date on insomnia, epigenetics may be the framework to understand long-lasting consequences of the interaction between genetic and environmental factors and effects of stress on the brain in insomnia. Interestingly, polygenic risk for insomnia has been causally linked to different mental and medical disorders. Probably, by treating insomnia it would be possible to intervene on the effect of stress on the brain and prevent some medical and mental conditions.

Bidirectional mechanism of comorbidity of depression and insomnia based on synaptic plasticity

Insomnia is one of the most common accompanying symptoms of depression, with both sharing highly overlapping molecular pathways. The same pathological changes can trigger comorbidity of insomnia and depression, which further forms a vicious cycle with the involvement of more mechanisms and disease progression. Thus, understanding the potential interaction mechanisms between insomnia and depression is critical for clinical diagnosis and treatment. Comorbidity genetic factors, the hypothalamic-pituitary-adrenal axis, along with circadian rhythms of cortisol and the brain reward mechanism, are important ways in contributing to the comorbidity occurrence and development. However, owing to lack of pertinent investigational data, intricate molecular mechanisms necessitate further elaboration. Synaptic plasticity is a solid foundation for neural homeostasis. Pathological alterations of depression and insomnia may perturb the production and release of neurotransmitter, dendritic spine remodeling and elimination, which converges and reflects in aberrant synaptic dynamics. Hence, the introduction of synaptic plasticity research route and the construction of a comprehensive model of depression and insomnia comorbidity can provide new ideas for clinical depression insomnia comorbidity treatment plans.

Integrating genetics and transcriptomics to study major depressive disorder: a conceptual framework, bioinformatic approaches, and recent findings

Major depressive disorder (MDD) is a complex and heterogeneous psychiatric syndrome with genetic and environmental influences. In addition to neuroanatomical and circuit-level disturbances, dysregulation of the brain transcriptome is a key phenotypic signature of MDD. Postmortem brain gene expression data are uniquely valuable resources for identifying this signature and key genomic drivers in human depression; however, the scarcity of brain tissue limits our capacity to observe the dynamic transcriptional landscape of MDD. It is therefore crucial to explore and integrate depression and stress transcriptomic data from numerous, complementary perspectives to construct a richer understanding of the pathophysiology of depression. In this review, we discuss multiple approaches for exploring the brain transcriptome reflecting dynamic stages of MDD: predisposition, onset, and illness. We next highlight bioinformatic approaches for hypothesis-free, genome-wide analyses of genomic and transcriptomic data and their integration. Last, we summarize the findings of recent genetic and transcriptomic studies within this conceptual framework.

Shared Genetics and Causality Between Decaffeinated Coffee Consumption and Neuropsychiatric Diseases: A Large-Scale Genome-Wide Cross-Trait Analysis and Mendelian Randomization Analysis

Coffee or caffeine consumption has been associated with neuropsychiatric disorders, implying a shared etiology. However, whether these associations reflect causality remains largely unknown. To understand the genetic structure of the association between decaffeinated coffee consumption (DCC) and neuropsychiatric traits, we examined the genetic correlation, causality, and shared genetic structure between DCC and neuropsychiatric traits using linkage disequilibrium score regression, bidirectional Mendelian randomization (MR), and genome-wide cross-trait meta-analysis in large GWAS Consortia for coffee consumption (N = 329,671) and 13 neuropsychiatric traits (sample size ranges from 36,052 to 500,199). We found strong positive genetic correlations between DCC and lifetime cannabis use (LCU; Rg = 0.48, P = 8.40 × 10^-19), alcohol use disorder identification test (AUDIT) total score (AUDIT_T; Rg = 0.40, P = 4.63 × 10^-13), AUDIT_C score (alcohol consumption component of the AUDIT; Rg = 0.40, P = 5.26 × 10^-11), AUDIT_P score (dependence and hazardous-use component of the AUDIT; Rg = 0.28, P = 1.36 × 10^-05), and strong negative genetic correlations between DCC and neuroticism (Rg = -0.15, P = 7.27 × 10^-05), major depressed diseases (MDD; Rg = -0.15, P = 0.0010), and insomnia (Rg= -0.15, P = 0.0007). In the cross-trait meta-analysis, we identified 6, 5, 1, 1, 2, 31, and 27 shared loci between DCC and Insomnia, LCU, AUDIT_T, AUDIT_C, AUDIT_P, neuroticism, and MDD, respectively, which were mainly enriched in bone marrow, lymph node, cervix, uterine, lung, and thyroid gland tissues, T cell receptor signaling pathway, antigen receptor-mediated signaling pathway, and epigenetic pathways. A large of TWAS-significant associations were identified in tissues that are part of the nervous system, digestive system, and exo-/endocrine system. Our findings further indicated a causal influence of liability to DCC on LCU and low risk of MDD (odds ratio: 0.90, P = 9.06 × 10^-5 and 1.27, P = 7.63 × 10^-4 respectively). We also observed that AUDIT_T and AUDIT_C were causally related to DCC (odds ratio: 1.83 per 1-SD increase in AUDIT_T, P = 1.67 × 10^-05, 1.80 per 1-SD increase in AUDIT_C, P = 5.09 × 10^-04). Meanwhile, insomnia and MDD had a causal negative influence on DCC (OR: 0.91, 95% CI: 0.86-0.95, P = 1.51 × 10^-04 for Insomnia; OR: 0.93, 95% CI: 0.89-0.99, P = 6.02 × 10^-04 for MDD). These findings provided evidence for the shared genetic basis and causality between DCC and neuropsychiatric diseases, and advance our understanding of the shared genetic mechanisms underlying their associations, as well as assisting with making recommendations for clinical works or health education.

The Function and Structure of Precuneus Is Associated With Subjective Sleep Quality in Major Depression

BACKGROUND

Poor sleep quality is related to depression. However, the investigation of the neural basis for poor sleep quality in individuals with major depression (MD) is limited.

METHODS

Resting state functional and structural MRI data were derived from 114 MD individuals and 74 normal controls (NCs). Fractional amplitude of low-frequency fluctuation (fALFF) and gray matter volume (GMV) were used to measure function and structure of the brain. Pittsburgh Sleep Quality Index (PSQI) was performed to evaluate subjective sleep quality. Correlations were carried out to investigate links of PSQI score with brain imaging indices in MD and NCs, separately. We also examined the differences in fALFF and GMV of brain regions related to PSQI score between MD and NCs.

RESULTS

In contrast to NCs, MD individuals had higher PSQI score. The higher PSQI score was associated with lower fALFF and lower GMV in bilateral precuneus in MD individuals. Moreover, the MD individuals exhibited increased fALFF in bilateral precuneus compared with NCs. However, the correlation between subjective sleep quality and neuroimaging parameters was not significant in NCs.

CONCLUSION

The implication of these findings is that the function and structure of precuneus provides a neural basis for subjective poor sleep quality in MD. Understanding this may lead to better intervention of depression and associated sleep complaints.