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Smoking and alcohol consumption were associated with the development of depression and anxiety. 3′UTR APA quantitative trait loci (3'aQTLs) have been associated with multiple health states and conditions. Our aim is to evaluate the interactive effects of 3'aQTLs-alcohol consumption/tobacco smoking on the risk of anxiety and depression. The 3'aQTL data of 13 brain regions were extracted from the large-scale 3'aQTL atlas. The phenotype data (frequency of cigarette smoking and alcohol drinking, anxiety score, self-reported anxiety, depression score and self-reported depression) of 90,399–103,011 adults aged 40–69 years living in the UK and contributing to the UK Biobank during 2006–2010, were obtained from the UK Biobank cohort. The frequency of cigarette smoking and alcohol drinking of each subject were defined by the amount of smoking and alcohol drinking of self-reported, respectively. The continuous alcohol consumption/smoking terms were further categorized in tertiles. 3'aQTL-by-environmental interaction analysis was then performed to evaluate the associations of gene-smoking/alcohol consumption interactions with anxiety and depression using generalized linear model (GLM) of PLINK 2.0 with an additive mode of inheritance. Furthermore, GLM was also used to explore the relationship between alcohol consumption/smoking with hazard of anxiety/depression stratified by allele for the significant genotyped SNPs that modified the alcohol consumption/smoking-anxiety/depression association. The interaction analysis identified several candidate 3'aQTLs-alcohol consumption interactions, such as rs7602638 located in PPP3R1 (β = 0.08, P = 6.50 × 10−6) for anxiety score; rs10925518 located in RYR2 (OR = 0.95, P = 3.06 × 10−5) for self-reported depression. Interestingly, we also observed that the interactions between TMOD1 (β = 0.18, P = 3.30 × 10−8 for anxiety score; β = 0.17, P = 1.42 × 10−6 for depression score), ZNF407 (β = 0.17, P = 2.11 × 10−6 for anxiety score; β = 0.15, P = 4.26 × 10−5 for depression score) and alcohol consumption was not only associated with anxiety, but related to depression. Besides, we found that relationship between alcohol consumption and hazard of anxiety/depression was significantly different for different SNPs genotypes, such as rs34505550 in TMOD1 (AA: OR = 1.03, P = 1.79 × 10−6; AG: OR = 1.00, P = 0.94; GG: OR = 1.00, P = 0.21) for self-reported anxiety. The identified 3'aQTLs-alcohol consumption/smoking interactions were associated with depression and anxiety, and its potential biological mechanisms need to be further revealed. Our study identified important interactions between candidate 3'aQTL and alcohol consumption/smoking on depression and anxiety, and found that the 3'aQTL may modify the associations between consumption/smoking with depression and anxiety. These findings may help to further explore the pathogenesis of depression and anxiety. • Interaction between rs7602638 located in PPP3R1 and alcohol consumption was positively associated with anxiety score. • Interaction between rs10925518 in RYR2 and alcohol consumption was negatively correlated with self-reported depression. • Interactions between TMOD1, NLRP1, ZNF407 and alcohol consumption were positively associated with anxiety and depression. [ABSTRACT FROM AUTHOR]

Disrupted brain structures and several life environmental factors have been shown to influence depression and anxiety, but their interactions with anxiety and depression remain elusive. Genome‐wide association study datasets of 15 brain structure longitudinal changes (N = 15,640) were obtained from the published study. Genotype and phenotype‐related data of depression, anxiety, and life environmental factors (including smoking, alcohol drinking, coffee intake, maternal smoking, physical activity, vitamin D, insomnia, sleep duration, and family satisfaction) were collected from UK Biobank. We calculated the polygenic risk scores (PRS) of 15 brain structure changes and then conducted linear regression analyses to explore the interactions of brain structure changes and life environmental factors on depression and anxiety using 15 brain structure change‐related PRS, life environmental factors and interactions of them as instrumental variables, and depression score or anxiety score as outcomes. Sex stratification in all analyses was performed to reveal sex‐specific differences in the interactions. We found 14 shared interactions related to both depression and anxiety in total sample, such as alcohol drinking × cerebellum white matter 3 (WM; beta = −.003, p =.018 for depression; beta = −003, p =.008 for anxiety) and maternal smoking × nucleus accumbens 2 (beta =.088, p =.002 for depression; beta =.070, p =.008 for anxiety). We also observed sex‐specific differences in the interactions, for instance, alcohol drinking × cerebellum WM 3 was negatively associated with depression and anxiety in males (beta = −.004, p =.020 for depression; beta = −.005, p =.002 for anxiety). Our study results reveal the important interactions between brain structure changes and several life environmental factors on depression and anxiety, which may help to explore the pathogenesis of depression and anxiety. [ABSTRACT FROM AUTHOR]

Psychiatric disorders and neuroticism are closely associated with central nervous system, whose proper functioning depends on efficient protein renewal. This study aims to systematically analyze the association between anxiety / depression / neuroticism and each of the 439 proteins. 47,536 pQTLs of 439 proteins in brain, plasma and cerebrospinal fluid (CSF) were collected from recent genome-wide association study. Polygenic risk scores (PRS) of the 439 proteins were then calculated using the UK Biobank cohort, including 120,729 subjects of neuroticism, 255,354 subjects of anxiety and 316,513 subjects of depression. Pearson correlation analyses were performed to evaluate the correlation between each protein and each of the mental traits by using calculated PRSs as the instrumental variables of protein. In general population, six correlations were identified in plasma and CSF such as plasma protease C1 inhibitor (C1-INH) with neuroticism score (r = − 0.011, P = 2.56 × 10− 9) in plasma, C1-INH with neuroticism score (r = -0.010, P = 3.09 × 10− 8) in CSF, and ERBB1 with self-reported depression (r = − 0.012, P = 4.65 × 10− 5) in CSF. C1-INH and ERBB1 may induce neuroticism and depression by affecting brain function and synaptic development. Gender subgroup analyses found that BST1 was correlated with neuroticism score in male CSF (r = − 0.011, P = 1.80 × 10− 5), while CNTN2 was correlated with depression score in female brain (r = − 0.013, P = 6.43 × 10− 4). BST1 and CNTN2 may be involved in nervous system metabolism and brain health. Six common candidate proteins were associated with all three traits (P < 0.05) and were confirmed in relevant proteomic studies, such as C1-INH in plasma, CNTN2 and MSP in the brain. Our results provide novel clues for revealing the roles of proteins in the development of anxiety, depression and neuroticism. [ABSTRACT FROM AUTHOR]

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]

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. [ABSTRACT FROM AUTHOR]

Background: Psychiatric disorders have great health hazards and the exact pathogeny remains elusive now. We aim to explore the potential interaction effects of mitochondrial function and human behavior on the risks of anxiety and depression.Methods: The genome-wide association study (GWAS) data of mitochondrial function (N = 383,476-982,072) were obtained from published studies. Individual level genotype and phenotype data of anxiety, depression and behavioral factors (including drinking, smoking and physical activity) were all from the UK Biobank (N = 84,805-85,164). We first calculated the polygenic risk scores (PRS) of mitochondrial function as the instrumental variables, and then constructed linear regression analyses to systematically explore the potential interaction effects of mitochondrial function and human behavior on anxiety and depression.Results: In total samples, we observed mitochondrial heteroplasmy (MtHz) vs. Drinking (PGAD-7 = 6.49 × 10-3; PPHQ-9 = 1.89 × 10-3) was positively associated with both anxiety and depression. In males, MtHz vs. Drinking (PMale = 3.46 × 10-5) was positively correlated with depression. In females, blood mitochondrial DNA copy number (mtDNA-CN) vs. Drinking (PFemale = 8.63 × 10-3) was negatively related to anxiety. Furthermore, we identified additional 6 suggestive interaction effects (P < 0.05) for anxiety and depression.Limitations: Considering all subjects were from UK Biobank, it should be careful to extrapolate our findings to other populations with different genetic background.Conclusions: Our results suggest the significant impacts of mitochondrial function and human behavior interactions on the development of anxiety and depression, providing new clues for clarifying the pathogenesis of anxiety and depression. [ABSTRACT FROM AUTHOR]

Comparing with the general population, the pain in depression patients has more complex biological mechanism. We aim to explore the etiological mechanism of pain in depression patients from the perspective of genetics. Utilizing the UK Biobank samples with self-reported depression status or PHQ score ≥10, we conducted genome-wide association studies (GWAS) of seven pain traits (N = 1,133–58,349). Additionally, we used FUSION pipeline to perform proteome-wide association study (PWAS) and transcriptome-wide association study (TWAS) by integrating GWAS summary data with two different proteome reference weights (ROS/MAP and Banner) and Rnaseq gene expression reference weights, respectively. GWAS identified 3 significant genes associated with different pain traits in depression patients, including TRIOBP (P GWAS = 4.48 × 10−8) for stomach or abdominal pain, SLC9A9(P GWAS = 2.77 × 10−8) for multisite chronic pain (MCP) and ADGRF1 (P GWAS = 1.51 × 10−8) for neck or shoulder pain. In addition, PWAS and TWAS analysis also identified multiple candidate genes associated with different pain traits in depression patients, such as TPRG1L (P PWAS-Banner = 3.38 × 10−2) and SIRPA (P PWAS-Banner = 3.65 × 10−2) for MCP, etc. Notably, when comparing the results of PWAS and TWAS analysis, we found overlapping candidate genes in these pain traits, such as GSTM3 (P PWAS - Banner = 3.38 × 10−2, P TWAS = 6.92 × 10−3) in the stomach or abdominal pain phenotype, ATG7 (P PWAS - Rosmap = 3.15 × 10−2, P TWAS = 2.98 × 10−2) in the MCP, etc. We identified multiple novel candidate genes for pain traits in depression patients from different perspectives of genetics, which provided novel clues for understanding the genetic mechanisms underlying the pain in depression patients. [ABSTRACT FROM AUTHOR]

The effects of gene-by-environment (G×E) interactions on complex diseases are significant, especially the superimposed effects of multiple environmental factors. However, research on the multi-environments-gene interactions of anxiety, depression, and self-harm is still limited. This study included white individuals (N = 66,041–74,482) from the UK Biobank. We fitted all environmental factors to a single environmental score (ES), and the estimated ES was used to calculate the multiplicative interaction effects between ES and genome-wide SNPs. Heritability was stratified by minor allele frequency (MAF) and linkage disequilibrium (LD). Our research found 10 loci with significant interaction effects, such as rs114830993 (PRICKLE2, P = 2.30 × 10−8), rs151323364 (ASTN2, P = 2.71 × 10−10) and rs536631793 (SYN3, P = 4.09 × 10−8). In addition, we found that G×E heritability has a significant contribution to the depression of Patient Health Questionnaire-9 (PHQ-9) scores (h2 G×E (female) = 6.1%, h2 G×E (male) = 8.7%). Our research supported the important influence of multi-environments-gene interactions on anxiety, depression, and self-harm and provided clues for the prevention and etiological research of them. [ABSTRACT FROM AUTHOR]

Cumulative evidence shows that gut microbiome can influence brain function and behavior via the inflammatory processes. However, the role of interaction between gut dysbiosis and C-reactive protein (CRP) in the development of anxiety and depression remains to be elucidated. In this study, a total of 3321 independent single nucleotide polymorphism (SNP) loci associated with gut microbiome were driven from genome-wide association study (GWAS). Using individual level genotype data from UK Biobank, we then calculated the polygenetic risk scoring (PRS) of 114 gut microbiome related traits. Moreover, regression analysis was conducted to evaluate the possible effect of interaction between gut microbiome and CRP on the risks of Patient Health Questionnaire-9 (PHQ-9) (N = 113,693) and Generalized Anxiety Disorder-7 (GAD-7) (N = 114,219). At last, 11 candidate CRP × gut microbiome interaction with suggestive significance was detected for PHQ-9 score, such as F_Ruminococcaceae (β = − 0.009, P = 2.2 × 10–3), G_Akkermansia (β = − 0.008, P = 7.60 × 10–3), F_Acidaminococcaceae (β = 0.008, P = 1.22 × 10–2), G_Holdemanella (β = − 0.007, P = 1.39 × 10–2) and O_Lactobacillales (β = 0.006, P = 1.79× 10–2). 16 candidate CRP × gut microbiome interaction with suggestive significance was detected for GAD-7 score, such as O_Bacteroidales (β = 0.010, P = 4.00× 10–4), O_Selenomonadales (β = − 0.010, P = 1.20 × 10–3), O_Clostridiales (β = 0.009, P = 2.70 × 10–3) and G_Holdemanella (β = − 0.008, P = 4.20 × 10–3). Our results support the significant effect of interaction between CRP and gut microbiome on the risks of anxiety and depression, and identified several candidate gut microbiomes for them. [ABSTRACT FROM AUTHOR]