The aim of this study, comprising 88 suicide attempters, was to identify hypothalamic-pituitary-adrenal (HPA) -axis coupled CpG-sites showing methylation shifts linked to severity of the suicide attempt. Candidate methylation loci were further investigated as risk loci for a general psychiatric risk score in two cohorts of adolescents (cohort 1 and 2). The genome-wide methylation pattern was measured in whole blood using the Illumina Infinium Methylation EPIC BeadChip. Subjects were stratified into high-risk and low-risk groups based on the severity of the suicidal behavior. We included CpG sites located within 2000 basepairs away from transcriptional start site of the following HPA-axis coupled genes: corticotropin releasing hormone (CRH), corticotropin releasing hormone binding protein (CRHBP), corticotropin releasing hormone receptor 1 (CRHR1), corticotropin releasing hormone receptor 2 (CRHR2), FK506-binding protein 51 (FKBP5) and the glucocorticoid receptor (NR3C1). The methylation state of two corticotropin releasing hormone (CRH)-associated CpG sites were significantly hypomethylated in the high-risk group of suicide attempters (n = 31) (cg19035496 and cg23409074) (p < 0.001). Adolescent cohort 1 and 2 consisted of 129 and 93 subjects, respectively, and were stratified by the in silico generated DAWBA measurements of a general psychiatric risk score into high-risk group (>~50% risk) or controls. In adolescent cohort 2, cg19035496 was hypermethylated in subjects with a high general psychiatric risk score. Our results show epigenetic changes in the CRH gene related to severity of suicide attempt in adults and a general psychiatric risk score in adolescents.

Job-related stress has been associated with poor health outcomes but little is known about the causal nature of these findings. We employed Mendelian randomisation (MR) approach to investigate the causal effect of neuroticism, education, and physical activity on job satisfaction. Trait-specific genetic risk score (GRS) based on recent genome wide association studies were used as instrumental variables (IV) using the UK Biobank cohort (N = 315,536). Both single variable and multivariable MR analyses were used to determine the effect of each trait on job satisfaction. We observed a clear evidence of a causal association between neuroticism and job satisfaction. In single variable MR, one standard deviation (1 SD) higher genetically determined neuroticism score (4.07 units) was associated with −0.31 units lower job satisfaction (95% confidence interval (CI): −0.38 to −0.24; P = 9.5 × 10 −20). The causal associations remained significant after performing sensitivity analyses by excluding invalid genetic variants from GRS Neuroticism (β(95%CI): −0.28(−0.35 to −0.21); P = 3.4 x 10 −15). Education (0.02; −0.08 to 0.12; 0.67) and physical activity (0.08; −0.34 to 0.50; 0.70) did not show any evidence for causal association with job satisfaction. When genetic instruments for neuroticism, education and physical activity were included together, the association of neuroticism score with job satisfaction was reduced by only −0.01 units, suggesting an independent inverse causal association between neuroticism score (P = 2.7 x 10 −17) and job satisfaction. Our findings show an independent causal association between neuroticism score and job satisfaction. Physically active lifestyle may help to increase job satisfaction despite presence of high neuroticism scores. Our study highlights the importance of considering the confounding effect of negative personality traits for studies on job satisfaction.

Genome-wide association studies have identified a number of single-nucleotide polymorphisms (SNPs) that are associated with psychiatric diseases. Increasing body of evidence suggests a complex connection of SNPs and the transcriptional and epigenetic regulation of gene expression, which is poorly understood. In the current study, we investigated the interplay between genetic risk variants, shifts in methylation and mRNA levels in whole blood from 223 adolescents distinguished by a risk for developing psychiatric disorders. We analyzed 37 SNPs previously associated with psychiatric diseases in relation to genome-wide DNA methylation levels using linear models, with Bonferroni correction and adjusting for cell-type composition. Associations between DNA methylation, mRNA levels and psychiatric disease risk evaluated by the Development and Well-Being Assessment (DAWBA) score were identified by robust linear models, Pearson’s correlations and binary regression models. We detected five SNPs (in HCRTR1, GAD1, HADC3 and FKBP5) that were associated with eight CpG sites, validating five of these SNP–CpG pairs. Three of these CpG sites, that is, cg01089319 (GAD1), cg01089249 (GAD1) and cg24137543 (DIAPH1), manifest in significant gene expression changes and overlap with active regulatory regions in chromatin states of brain tissues. Importantly, methylation levels at cg01089319 were associated with the DAWBA score in the discovery group. These results show how distinct SNPs linked with psychiatric diseases are associated with epigenetic shifts with relevance for gene expression. Our findings give a novel insight on how genetic variants may modulate risks for the development of psychiatric diseases.

ObjectiveTo examine the association between the MTNR1B G risk allele, type 2 diabetes (T2D) and chronotype in the UK Biobank.MethodsData from the baseline investigation of the UK Biobank were utilized (n = 337 083 White British; mean age: 56.9 years; 54% women). MTNR1B rs10830963 was directly genotyped [CC (reference group), CG and GG]. Chronotype was divided into four categories: definitely morning (reference group); more morning than evening; more evening than morning; and definitely evening. Logistic regression analyses were performed to estimate odds ratios and 95% confidence intervals (CIs) for T2D, controlling for age, sex and other confounders.ResultsCarriers of the rs10830963 risk allele had a higher risk of T2D [CG vs. CC: OR (95% CI) 1.10 (1.07, 1.15); GG vs. CC: 1.21 (1.14, 1.29)]. Compared with definitely morning chronotype, participants with definitely evening chronotype exhibited the highest risk of T2D [1.25 (1.17, 1.33)]. Despite a nonsignificant interaction between chronotype and the risk allele [0.98 (0.94, 1.01), P = 0.176 for interaction term], we found that definitely evening chronotype (vs. definitely morning) was linked with a higher risk of T2D amongst CC and CG but not GG carriers. Additionally, we saw that the GG genotype (vs. CC) was associated with a higher risk of T2D across all chronotype categories, except for definitely evening.ConclusionOur findings suggest that the MTNR1B G risk allele and late chronotype increase the risk of T2D. The association between late chronotype and higher risk of T2D appears to vary across MTNR1B rs10830963 genotypes.

Patients with bipolar disorder (BD) show higher frequency of obesity and type 2 diabetes (T2D), but the underlying genetic determinants and molecular pathways are not well studied. Using large publicly available datasets, we (1) conducted a gene-based analysis using MAGMA to identify genes associated with BD and body mass index (BMI) or T2D and investigated their functional enrichment; and (2) performed two meta-analyses between BD and BMI, as well as BD and T2D using Metasoft. Target druggability was assessed using the Drug Gene Interaction Database (DGIdb). We identified 518 and 390 genes significantly associated with BD and BMI or BD and T2D, respectively. A total of 52 and 12 genes, respectively, were significant after multiple testing correction. Pathway analyses conducted on nominally significant targets showed that genes associated with BD and BMI were enriched for the Neuronal cell body Gene Ontology (GO) term (p = 1.0E−04; false discovery rate (FDR) = 0.025) and different pathways, including the Signaling by Hedgehog pathway (p = 4.8E−05, FDR = 0.02), while genes associated with BD and T2D showed no specific enrichment. The meta-analysis between BD and BMI identified 64 relevant single nucleotide polymorphisms (SNPs). While the majority of these were located in intergenic regions or in a locus on chromosome 16 near and in the NPIPL1 and SH2B1 genes (best SNP: rs4788101, p = 2.1E−24), five were located in the ETV5 gene (best SNP: rs1516725, p = 1E−24), which was previously associated with both BD and obesity, and one in the RPGRIP1L gene (rs1477199, p = 5.7E−09), which was also included in the Signaling by Hedgehog pathway. The meta-analysis between BD and T2D identified six significant SNPs, three of which were located in ALAS1 (best SNP: rs352165, p = 3.4E−08). Thirteen SNPs associated with BD and BMI, and one with BD and T2D, were located in genes which are part of the druggable genome. Our results support the hypothesis of shared genetic determinants between BD and BMI and point to genes involved in Hedgehog signaling as promising targets.