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Immune dysregulation has been observed in individuals with sleep disturbance, with HLA molecules play a crucial role in the immune response. This study aimed to investigate the associations between HLA alleles and sleep behaviours, considering several environmental factors. Data were sourced from the UK Biobank. Logistic regression analyses were performed to explore the associations between 359 HLA alleles and 4 sleep behaviours, including chronotype (n = 204,636), insomnia (n = 227,553), snoring (n = 214,350) and daytime dozing (n = 227,197). Furthermore, gene‐environmental interaction studies (GEIS) were conducted to evaluate the interactions of HLA alleles with environmental factors on sleep behaviours. This study analysed a total sample and subgroups stratified by sex to elucidate the impact of HLA alleles on sleep behaviours. Our findings revealed several associations between specific HLA alleles and sleep behaviours. Notably, HLA‐A*23:01 was associated with evening chronotype in the total sample (OR = 0.918, 95%CI: 0.872–0.965), while HLA‐A*32:01 was associated with evening chronotype in males (OR = 1.089, 95%CI: 1.037–1.144). Furthermore, GEIS identified multiple sets of interactions associated with sleep behaviours. For example, the interaction of HLA‐DPA1*01:04 with alcohol consumption was associated with daytime dozing in the total sample (OR = 1.993, 95%CI: 1.351–2.941), while the interaction of HLA‐DQB1*05:04 with ever suffered mental distress preventing usual activities was associated with insomnia in males (OR = 0.409, 95%CI: 0.254–0.658). Our findings highlight the involvement of HLA in sleep regulation and underscore the potential interactions between HLA alleles and environmental factors in modulating susceptibility to sleep behaviours. [ABSTRACT FROM AUTHOR]

The objectives of this study were to investigate the interaction of mitochondrial DNA (mtDNA) and lifestyle factors in the development of psychiatric disorders and to gain greater insight into their pathogenesis and comorbidity. We analyzed data from approximately 150,000 individuals from the UK Biobank. Mitochondrial gene-by-environment interaction studies (mtGEIS) were performed to assess the relationships between mtDNA and psychiatric disorders, such as anxiety, depression, and self-harm. These disorders were defined using diagnostic and severity indicators derived from the General Anxiety Disorder (GAD-7) and Patient Health Questionnaire (PHQ-9). Smoking and drinking behaviors were characterized based on UK Biobank criteria. For the mtGEIS, logistic and linear regression models from PLINK 2.0 were employed, accounting for covariates like age, sex, PC1-10, Townsend Deprivation Index (TDI), and educational attainment. We also conducted sex-stratified analyses to detect any gender-specific effects. Our findings highlighted significant associations between mtDNA and three psychiatric disorders. Moreover, the interplay between mtDNA and lifestyle factors showed significant associations with psychiatric disorders (all P values < 0.05). Specifically, two mutant loci, T5004C ( B Anx _ self = − 0.0026 , B Dep _ self = − 0.0024 , B Self − harm = − 0.0018) and G9123A ( B Anx _ self = − 0.0030 , B Dep _ self = − 0.0024 , B Self − harm = − 0.0017), were found to reduce the risk of three disorders after interacting with alcohol. Sex-specific differences were also observed. In summary, the expression of mitochondrial genes could be modulated by lifestyle factors like smoking and drinking, potentially affecting psychiatric disorders. These habits might influence mitochondrial respiratory chain activity and the replication and transcriptional regulation of mitochondrial genes, culminating in changes in mitochondrial functionality and subsequently psychiatric disorders. [ABSTRACT FROM AUTHOR]

Background: Allostatic load (AL) is an objective measure of the biological components of chronic stress within clinical practice, potentially influencing depression, anxiety, and suicide. This study investigates the association between AL and these mental disorders., Methods: In this cohort study of 333,017 adults, participants without prior diagnoses of depression, anxiety, or suicide were observed from March 13, 2006, to October 31, 2022. AL was estimated using 10 biomarkers reflecting metabolic, cardiovascular, and inflammatory dysregulation. Diagnoses were based on the International Classification of Diseases 10th Revision (ICD-10). We performed Cox proportional hazards models to assess the relationship between AL and these mental disorders. Additionally, we conducted subgroup analyses for sex, age, and Townsend Deprivation Index (TDI), along with sensitivity analyses., Results: The median follow-up period was 12.99 years. Over the follow-up period, 13,441 (4.04%) participants developed depression, 13,903 (4.17%) developed anxiety and 796 (0.24%) committed suicide. In fully adjusted model, individuals with high AL had an increased risk of depression (HR = 1.389, P = 8.38 ×10 -27 ), anxiety (HR = 1.304, P = 5.82 ×10 -19 ) and suicide (HR = 1.433, P = 4.46 ×10 -3 ). Women and younger individuals with high AL were vulnerable to depression and anxiety, while moderate AL levels were significantly associated with suicide in men and younger participants. Moreover, individuals with middle and high AL had an elevated risk of comorbid depression and anxiety., Conclusions: High AL is positively associated with increased risks of depression, anxiety, and suicide, highlighting its potential as a predictive tool in mental health., (Copyright © 2024. Published by Elsevier Inc.)

Purpose: Previous studies have demonstrated the link between micronutrients and mental health. However, it remains uncertain whether this connection is causal. We aim to investigate the potential causal effects of micronutrients on mental health based on linkage disequilibrium score (LDSC) regression and Mendelian randomization (MR) analysis., Methods: Utilizing publicly available genome-wide association study (GWAS) summary datasets, we performed LDSC and MR analysis to identify candidate micronutrients with potential causal effects on mental health. Single nucleotide polymorphisms (SNPs) significantly linked with candidate micronutrients with a genome-wide significance level ( p < 5 × 10 -8 ) were selected as instrumental variables (IVs). To estimate the causal effect of candidate micronutrients on mental health, we employed inverse variance weighted (IVW) regression. Additionally, two sensitivity analyses, MR-Egger and weighted median, were performed to validate our results., Results: We found evidence supporting significant causal associations between micronutrients and mental health. LDSC detected several candidate micronutrients, including serum iron (genetic correlation = -0.134, p = 0.032) and vitamin C (genetic correlation = -0.335, p < 0.001) for attention-deficit/hyperactivity disorder (ADHD), iron-binding capacity (genetic correlation = 0.210, p = 0.037) for Alzheimer's disease (AD), and vitamin B12 (genetic correlation = -0.178, p = 0.044) for major depressive disorder (MDD). Further MR analysis suggested a potential causal relationship between vitamin B12 and MDD (b = -0.139, p = 0.009). There was no significant heterogeneity or pleiotropy, indicating the validity of the findings., Conclusion: In this study, we identified underlying causal relationships between micronutrients and mental health. Notably, more research is necessary to clarify the underlying biological mechanisms by which micronutrients affect mental health.

Objectives: To assess whether there is a bidirectional causal relationship between the composition of gut microbiota and rheumatoid arthritis (RA), and to identify specific pathogenic bacterial taxa via the Mendelian randomisation (MR) analysis., Methods: We acquired single nucleotide polymorphisms (SNPs) associated with the composition of gut microbiota (n=18,340) and with RA (n=331,313) from publicly available genome-wide association studies (GWAS). The genome-wide threshold was 1 × 10-5 in the forward MR analysis and was 5 × 10-8 in the reverse MR analysis. Inverse variance weighted (IVW) was the main method to analyse causality, and MR results were verified by several sensitivity analyses including weighted median, MR Egger, and MR Pleiotropy Residual Sum and Outlier (PRESSO)., Results: The IVW method suggested that eight taxa were positively correlated with RA, including: MollicutesRF9 (pIVW <0.01), Alphaproteobacteria (pIVW <0.01), Betaproteobacteria (p IVW =0.04), Bacteroidaceae (pIVW <0.01), Adlercreutzia (pIVW <0.01), Bacteroides (pIVW <0.01), Butyricimonas (p IVW =0.03) and Holdemanella (pIVW =0.03). Six bacterial taxa were negatively correlated with RA, including Desulfovibrionales (pIVW = 0.01), Methanobacteriales (pIVW <0.01), Methanobacteria (PIVW <0.01), Desulfovibrionaceae (pIVW <0.01), Methanobacteriaceae (pIVW <0.01) and Butyrivibrio (pIVW =0.02). Heterogeneity (p>0.05) and pleiotropy (p>0.05) analysis confirmed the robustness of the MR results., Conclusions: We identified some specific bacterial taxa that were causally associated with the risk of RA, providing new insights into prevention and diagnosis of RA.