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Objective: This study aimed to identify candidate loci and genes related to sleep disturbances in depressed individuals and clarify the co-occurrence of sleep disturbances and depression from the genetic perspective., Methods: The study subjects (including 58,256 self-reported depressed individuals and 6,576 participants with PHQ-9 score ≥ 10, respectively) were collected from the UK Biobank, which were determined based on the Patient Health Questionnaire (PHQ-9) and self-reported depression status, respectively. Sleep related traits included chronotype, insomnia, snoring and daytime dozing. Genome-wide association studies (GWASs) of sleep related traits in depressed individuals were conducted by PLINK 2.0 adjusting age, sex, Townsend deprivation index and 10 principal components as covariates. The CAUSALdb database was used to explore the mental traits associated with the candidate genes identified by the GWAS., Results: GWAS detected 15 loci significantly associated with chronotype in the subjects with self-reported depression, such as rs12736689 at RNASEL (P = 1.00 × 10 - 09 ), rs509476 at RGS16 (P = 1.58 × 10 - 09 ) and rs1006751 at RFX4 (P = 1.54 × 10 - 08 ). 9 candidate loci were identified in the subjects with PHQ-9 ≥ 10, of which 2 loci were associated with insomnia such as rs115379847 at EVC2 (P = 3.50 × 10 - 08 ), and 7 loci were associated with daytime dozing, such as rs140876133 at SMYD3 (P = 3.88 × 10 - 08 ) and rs139156969 at ROBO2 (P = 3.58 × 10 - 08 ). Multiple identified genes, such as RNASEL, RGS16, RFX4 and ROBO2 were reported to be associated with chronotype, depression or cognition in previous studies., Conclusion: Our study identified several candidate genes related to sleep disturbances in depressed individuals, which provided new clues for understanding the biological mechanism underlying the co-occurrence of depression and sleep disorders., (© 2024. The Author(s).)

Immune dysregulation has been widely observed in patients with psychiatric disorders. This study aims to examine the association between HLA alleles and depression and anxiety. Using data from the UK Biobank, we performed regression analyses to assess the association of 359 HLA alleles with depression and anxiety, as determined by Patient Health Questionnaire (PHQ) score (n = 120,033), self-reported depression (n = 121,685), general anxiety disorder (GAD-7) score (n = 120,590), and self-reported anxiety (n = 108,310). Subsequently, we conducted gene environmental interaction study (GEIS) to evaluate the potential effects of interactions between HLA alleles and environmental factors on the risk of depression and anxiety. Sex stratification was implemented in all analysis. Our study identified two significant HLA alleles associated with self-reported depression, including HLA-C*07:01 (β = -0.015, p = 5.54 × 10 -5 ) and HLA-B*08:01 (β = -0.015, p = 7.78 × 10 -5 ). Additionally, we identified four significant HLA alleles associated with anxiety score, such as HLA-DRB1*07:01 (β = 0.084, p = 9.28 × 10 -5 ) and HLA-B*57:01 (β = 0.139, p = 1.22 × 10 -4 ). GEIS revealed that certain HLA alleles interacted with environmental factors to influence mental health outcomes. For instance, HLA-A*02:07 × cigarette smoking was associated with depression score (β = 0.976, p = 1.88 × 10 -6 ). Moreover, sex stratification analysis revealed significant sex-based differences in the interaction effects of certain HLA alleles with environmental factors. Our findings indicate the considerable impact of HLA alleles on the risks of depression and anxiety, providing valuable insights into the functional relevance of immune dysfunction in these conditions., (© 2023 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Background Depression has been linked to an increased risk of cardiovascular and respiratory diseases; however, its impact on cardiac and lung function remains unclear, especially when accounting for potential gene–environment interactions. Methods We developed a novel polygenic and gene–environment interaction risk score (PGIRS) integrating the major genetic effect and gene–environment interaction effect of depression-associated loci. The single nucleotide polymorphisms (SNPs) demonstrating major genetic effect or environmental interaction effect were obtained from genome-wide SNP association and SNP-environment interaction analyses of depression. We then calculated the depression PGIRS for non-depressed individuals, using smoking and alcohol consumption as environmental factors. Using linear regression analysis, we assessed the associations of PGIRS and conventional polygenic risk score (PRS) with lung function (N  = 42 886) and cardiac function (N  = 1791) in the subjects with or without exposing to smoking and alcohol drinking. Results We detected significant associations of depression PGIRS with cardiac and lung function, contrary to conventional depression PRS. Among smokers, forced vital capacity exhibited a negative association with PGIRS (β  = −0.037, FDR = 1.00 × 10−8), contrasting with no significant association with PRS (β  = −0.002, FDR = 0.943). In drinkers, we observed a positive association between cardiac index with PGIRS (β  = 0.088, FDR = 0.010), whereas no such association was found with PRS (β  = 0.040, FDR = 0.265). Notably, in individuals who both smoked and drank, forced expiratory volume in 1-second demonstrated a negative association with PGIRS (β  = −0.042, FDR = 6.30 × 10−9), but not with PRS (β  = −0.003, FDR = 0.857). Conclusions Our findings underscore the profound impact of depression on cardiac and lung function, highlighting the enhanced efficacy of considering gene–environment interactions in PRS-based studies. [ABSTRACT FROM AUTHOR]