Robust statistical, genetic and functional evidence supports a role for DISC1 in the aetiology of major mental illness. Furthermore, many of its protein-binding partners show evidence for involvement in the pathophysiology of a range of neurodevelopmental and psychiatric disorders. Copy number variants (CNVs) are suspected to play an important causal role in these disorders. In this study, CNV analysis of DISC1 and its binding partners PAFAH1B1, NDE1, NDEL1, FEZ1, MAP1A, CIT and PDE4B in Scottish and Northern Swedish population-based samples was carried out using multiplex amplicon quantification. Here, we report the finding of rare CNVs in DISC1, NDE1 (together with adjacent genes within the 16p13.11 duplication), NDEL1 (including the overlapping MYH10 gene) and CIT. Our findings provide further evidence for involvement of DISC1 and its interaction partners in neuropsychiatric disorders and also for a role of structural variants in the aetiology of these devastating diseases.

Comorbid chronic pain and depression is a challenging dyad of conditions to manage in primary care and reporting has shown to vary by ethnic group. Whether the relationship between depression and chronic pain varies by ethnicity is unclear. This study aims to explore chronic pain and depression reporting across ethnic groups and examine whether this association differs, independently of potential confounding factors.

General cognitive function predicts psychiatric illness across the life course. This study examines the role of pleiotropy in explaining the link between cognitive function and psychiatric disorder.

Alcohol consumption is known to lead to gene expression changes in the brain. After performing weighted gene co-expression network analyses (WGCNA) on genome-wide mRNA and microRNA (miRNA) expression in Nucleus Accumbens (NAc) of subjects with alcohol dependence (AD; N = 18) and of matched controls (N = 18), six mRNA and three miRNA modules significantly correlated with AD were identified (Bonferoni-adj. p≤ 0.05). Cell-type-specific transcriptome analyses revealed two of the mRNA modules to be enriched for neuronal specific marker genes and downregulated in AD, whereas the remaining four mRNA modules were enriched for astrocyte and microglial specific marker genes and upregulated in AD. Gene set enrichment analysis demonstrated that neuronal specific modules were enriched for genes involved in oxidative phosphorylation, mitochondrial dysfunction and MAPK signaling. Glial-specific modules were predominantly enriched for genes involved in processes related to immune functions, i.e. cytokine signaling (all adj. p≤ 0.05). In mRNA and miRNA modules, 461 and 25 candidate hub genes were identified, respectively. In contrast to the expected biological functions of miRNAs, correlation analyses between mRNA and miRNA hub genes revealed a higher number of positive than negative correlations (χ2 test p≤ 0.0001). Integration of hub gene expression with genome-wide genotypic data resulted in 591 mRNA cis-eQTLs and 62 miRNA cis-eQTLs. mRNA cis-eQTLs were significantly enriched for AD diagnosis and AD symptom counts (adj. p = 0.014 and p = 0.024, respectively) in AD GWAS signals in a large, independent genetic sample from the Collaborative Study on Genetics of Alcohol (COGA). In conclusion, our study identified putative gene network hubs coordinating mRNA and miRNA co-expression changes in the NAc of AD subjects, and our genetic (cis-eQTL) analysis provides novel insights into the etiological mechanisms of AD.

Borderline personality disorder (BPD) is a severe psychiatric disorder involving a range of symptoms including marked affective instability and disturbances in interpersonal interactions. Neuroimaging studies are beginning to provide evidence of altered processing in fronto-limbic network deficits in the disorder, however, few studies directly examine structural connections within this circuitry together with their relation to proposed causative processes and clinical features.

Background: Stressful life events (SLEs) and neuroticism are risk factors for major depressive disorder (MDD). However, SLEs and neuroticism are heritable and genetic risk for SLEs is associated with risk for MDD. We sought to investigate the genetic and environmental contributions to SLEs in a family-based sample, and quantify genetic overlap with MDD and neuroticism. Methods: A subset of Generation Scotland: the Scottish Family Health Study (GS), consisting of 9618 individuals with information on MDD, past 6 month SLEs, neuroticism and genome-wide genotype data was used in the present study. We estimated the heritability of SLEs using GCTA software. The environmental contribution to SLEs was assessed by modelling familial, couple and sibling components. Using polygenic risk scores (PRS) and LD score regression (LDSC) we analysed the genetic overlap between MDD, neuroticism and SLEs. Results: Past 6-month life events were positively associated with lifetime MDD status (β=0.21, r 2=1.1%, p=2.5 x 10 -25) and neuroticism (β =0.13, r 2=1.9%, p=1.04 x 10 -37) at the phenotypic level.  Common SNPs explained 8% of the phenotypic variance in personal life events (those directly affecting the individual) (S.E.=0.03, p= 9 x 10 -4). A significant effect of couple environment was detected accounting for 13% (S.E.=0.03, p=0.016) of the phenotypic variation in SLEs. PRS analyses found that reporting more SLEs was associated with a higher polygenic risk for MDD (β =0.05, r 2=0.3%, p=3 x 10 -5), but not a higher polygenic risk for neuroticism. LDSC showed a significant genetic correlation between SLEs and both MDD (r G=0.33, S.E.=0.08 ) and neuroticism (r G=0.15, S.E.=0.07). Conclusions: These findings suggest that SLEs should not be regarded solely as environmental risk factors for MDD as they are partially heritable and this heritability is shared with risk for MDD and neuroticism. Further work is needed to determine the causal direction and source of these associations.

Schizophrenia is a severe mental disorder characterized by numerous subtle changes in brain structure and function. Machine learning allows exploring the utility of combining structural and functional brain magnetic resonance imaging (MRI) measures for diagnostic application, but this approach has been hampered by sample size limitations and lack of differential diagnostic data. Here, we performed a multi-site machine learning analysis to explore brain structural patterns of T1 MRI data in 2668 individuals with schizophrenia, bipolar disorder or attention-deficit/ hyperactivity disorder, and healthy controls. We found reproducible changes of structural parameters in schizophrenia that yielded a classification accuracy of up to 76% and provided discrimination from ADHD, through it lacked specificity against bipolar disorder. The observed changes largely indexed distributed grey matter alterations that could be represented through a combination of several global brain-structural parameters. This multi-site machine learning study identified a brain-structural signature that could reproducibly differentiate schizophrenia patients from controls, but lacked specificity against bipolar disorder. While this currently limits the clinical utility of the identified signature, the present study highlights that the underlying alterations index substantial global grey matter changes in psychotic disorders, reflecting the biological similarity of these conditions, and provide a roadmap for future exploration of brain structural alterations in psychiatric patients.

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10-13) and African ancestries (rs2066702; P = 2.2 × 10-9). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.

Higher scores on the personality trait of neuroticism, the tendency to experience negative emotions, are associated with worse mental and physical health. Studies examining links between neuroticism and health typically operationalize neuroticism by summing the items from a neuroticism scale. However, neuroticism is made up of multiple heterogeneous facets, each contributing to the effect of neuroticism as a whole. A recent study showed that a 12-item neuroticism scale described one broad trait of general neuroticism and two special factors, one characterizing the extent to which people worry and feel vulnerable, and the other characterizing the extent to which people are anxious and tense. This study also found that, although individuals who were higher on general neuroticism lived shorter lives, individuals whose neuroticism was characterized by worry and vulnerability lived longer lives. Here, we examine the genetic contributions to the two special factors of neuroticism-anxiety/tension and worry/vulnerability-and how they contrast with that of general neuroticism. First, we show that, whereas the polygenic load for neuroticism is associated with the genetic risk of coronary artery disease, lower intelligence, lower socioeconomic status (SES), and poorer self-rated health, the genetic variants associated with high levels of anxiety/tension, and high levels of worry/vulnerability are associated with genetic variants linked to higher SES, higher intelligence, better self-rated health, and longer life. Second, we identify genetic variants that are uniquely associated with these protective aspects of neuroticism. Finally, we show that different neurological pathways are linked to each of these neuroticism phenotypes.

Genetic correlations estimated from genome-wide association studies (GWASs) reveal pervasive pleiotropy across a wide variety of phenotypes. We introduce genomic structural equation modelling (genomic SEM): a multivariate method for analysing the joint genetic architecture of complex traits. Genomic SEM synthesizes genetic correlations and single-nucleotide polymorphism heritabilities inferred from GWAS summary statistics of individual traits from samples with varying and unknown degrees of overlap. Genomic SEM can be used to model multivariate genetic associations among phenotypes, identify variants with effects on general dimensions of cross-trait liability, calculate more predictive polygenic scores and identify loci that cause divergence between traits. We demonstrate several applications of genomic SEM, including a joint analysis of summary statistics from five psychiatric traits. We identify 27 independent single-nucleotide polymorphisms not previously identified in the contributing univariate GWASs. Polygenic scores from genomic SEM consistently outperform those from univariate GWASs. Genomic SEM is flexible and open ended, and allows for continuous innovation in multivariate genetic analysis.

The causes of poor respiratory function and COPD are incompletely understood, but it is clear that genes and the environment play a role. As DNA methylation is under both genetic and environmental control, we hypothesised that investigation of differential methylation associated with these phenotypes would permit mechanistic insights, and improve prediction of COPD. We investigated genome-wide differential DNA methylation patterns using the recently released 850 K Illumina EPIC array. This is the largest single population, whole-genome epigenetic study to date.

We examined the association between neuroticism and mortality in a sample of 321,456 people from UK Biobank and explored the influence of self-rated health on this relationship. After adjustment for age and sex, a 1- SD increment in neuroticism was associated with a 6% increase in all-cause mortality (hazard ratio = 1.06, 95% confidence interval = [1.03, 1.09]). After adjustment for other covariates, and, in particular, self-rated health, higher neuroticism was associated with an 8% reduction in all-cause mortality (hazard ratio = 0.92, 95% confidence interval = [0.89, 0.95]), as well as with reductions in mortality from cancer, cardiovascular disease, and respiratory disease, but not external causes. Further analyses revealed that higher neuroticism was associated with lower mortality only in those people with fair or poor self-rated health, and that higher scores on a facet of neuroticism related to worry and vulnerability were associated with lower mortality. Research into associations between personality facets and mortality may elucidate mechanisms underlying neuroticism's covert protection against death.

Cognitive ability is a heritable trait with a polygenic architecture, for which several associated variants have been identified using genotype-based and candidate gene approaches. Haplotype-based analyses are a complementary technique that take phased genotype data into account, and potentially provide greater statistical power to detect lower frequency variants.

Neuroimaging studies have consistently shown functional brain abnormalities in patients with Bipolar Disorder (BD) and Major Depressive Disorder (MDD). However, the extent to which these two disorders are associated with similar or distinct neural changes remains unclear. We conducted a systematic review of functional magnetic resonance imaging studies comparing BD and MDD patients to healthy participants using facial affect processing paradigms. Relevant spatial coordinates from twenty original studies were subjected to quantitative Activation Likelihood Estimation meta-analyses based on 168 BD and 189 MDD patients and 344 healthy controls. We identified common and distinct patterns of neural engagement for BD and MDD within the facial affect processing network. Both disorders were associated with increased engagement of limbic regions. Diagnosis-specific differences were observed in cortical, thalamic and striatal regions. Decreased ventrolateral prefrontal cortical engagement was associated with BD while relative hypoactivation of the sensorimotor cortices was seen in MDD. Increased responsiveness in the thalamus and basal ganglia were associated with BD. These findings were modulated by stimulus valence. These data suggest that whereas limbic overactivation is reported consistently in patients with mood disorders, future research should consider the relevance of a wider network of regions in formulating conceptual models of BD and MDD.

Bipolar disorder is a highly heritable condition. First-degree relatives of affected individuals have a more than a ten-fold increased risk of developing bipolar disorder (BD), and a three-fold risk of developing major depressive disorder (MDD) than the general population. It is unclear however whether differences in brain activation reported in BD and MDD are present before the onset of illness.

Theory of Mind (ToM) or mentalizing is the ability of individuals to determine the intentions and behavior of others. This ability is known to be compromised in schizophrenia and has been shown to fluctuate with symptom severity. Neuropsychological investigations into relatives of individuals with schizophrenia have shown that some relatives also show a deficit in this area of social cognition. In order to address this state and trait issue, we investigated the performance of high-risk relatives of individuals with schizophrenia to those of a matched control group (n = 13) on a blocked design visual joke fMRI paradigm. The task involved looking at two sets of cartoon jokes, one set which required mentalizing abilities to understand the jokes and another set that did not require such abilities. Relatives were divided into two groups based on the presence (HR+, n = 12) or absence (HR-, n = 12) of positive symptoms. The task provided robust activations across the groups in areas previously associated with mentalizing abilities, such as the PFC, precuneus, and temporal lobes. Significant between-group activations were observed in the PFC (primarily BA6, 8, and 9) with the HR- activating significantly greater than the HR+ in these regions. Both a secondary state-specific analysis and a third post hoc analysis further investigating state effects showed significant PFC between-group differences. This study is the first time relatives of individuals with schizophrenia have been imaged using a ToM paradigm, and the results provide evidence of both a state and state-mediated trait effect.

Depression is a polygenic trait that causes extensive periods of disability. Previous genetic studies have identified common risk variants which have progressively increased in number with increasing sample sizes of the respective studies. Here, we conduct a genome-wide association study in 322,580 UK Biobank participants for three depression-related phenotypes: broad depression, probable major depressive disorder (MDD), and International Classification of Diseases (ICD, version 9 or 10)-coded MDD. We identify 17 independent loci that are significantly associated (P < 5 × 10-8) across the three phenotypes. The direction of effect of these loci is consistently replicated in an independent sample, with 14 loci likely representing novel findings. Gene sets are enriched in excitatory neurotransmission, mechanosensory behaviour, post synapse, neuron spine and dendrite functions. Our findings suggest that broad depression is the most tractable UK Biobank phenotype for discovering genes and gene sets that further our understanding of the biological pathways underlying depression.

Major depressive disorder (MDD) is a common illness accompanied by considerable morbidity, mortality, costs, and heightened risk of suicide. We conducted a genome-wide association meta-analysis based in 135,458 cases and 344,901 controls and identified 44 independent and significant loci. The genetic findings were associated with clinical features of major depression and implicated brain regions exhibiting anatomical differences in cases. Targets of antidepressant medications and genes involved in gene splicing were enriched for smaller association signal. We found important relationships of genetic risk for major depression with educational attainment, body mass, and schizophrenia: lower educational attainment and higher body mass were putatively causal, whereas major depression and schizophrenia reflected a partly shared biological etiology. All humans carry lesser or greater numbers of genetic risk factors for major depression. These findings help refine the basis of major depression and imply that a continuous measure of risk underlies the clinical phenotype.

Alcohol use disorder (AUD) is a chronic debilitating disorder with limited treatment options and poorly defined pathophysiology. There are substantial genetic and epigenetic components; however, the underlying mechanisms contributing to AUD remain largely unknown. We conducted the largest DNA methylation epigenome-wide association study (EWAS) analyses currently available for AUD (total N = 625) and employed a top hit replication (N = 4798) using a cross-tissue/cross-phenotypic approach with the goal of identifying novel epigenetic targets relevant to AUD. Results show that a network of differentially methylated regions in glucocorticoid signaling and inflammation-related genes were associated with alcohol use behaviors. A top probe consistently associated across all cohorts was located in the long non-coding RNA growth arrest specific five gene (GAS5) (p < 10-24). GAS5 has been implicated in regulating transcriptional activity of the glucocorticoid receptor and has multiple functions related to apoptosis, immune function and various cancers. Endophenotypic analyses using peripheral cortisol levels and neuroimaging paradigms showed that methylomic variation in GAS5 network-related probes were associated with stress phenotypes. Postmortem brain analyses documented increased GAS5 expression in the amygdala of individuals with AUD. Our data suggest that alcohol use is associated with differential methylation in the glucocorticoid system that might influence stress and inflammatory reactivity and subsequently risk for AUD.

Studies of white matter microstructure in depression typically show alterations in individuals with depression, but they are frequently limited by small sample sizes and the absence of longitudinal measures of depressive symptoms. Depressive symptoms are dynamic, however, and understanding the neurobiology of different trajectories could have important clinical implications.