Anxiety disorders are one of the most common, debilitating and costly classes of psychiatric disorders worldwide. Twin studies estimate heritability of anxiety disorders to be between 30%-60%, depending on specific disorder, age, and level of impairment. Although individual anxiety disorders are considered clinically distinct, they share much of their phenotypic and genetic variance, potentially reflecting an underlying liability distribution. The UK Biobank has collected symptom and disorder level anxiety data on 157,366 individuals across the UK who have contributed their genetic data. We used this dataset to investigate genome-wide associations, SNP based heritability, and genetic correlations in four anxiety phenotypes. These reflect population level current anxiety symptoms as a quantitative phenotype, and three case control phenotypes; severe current anxiety symptoms, probable lifetime generalised anxiety disorder and self-reported lifetime diagnosis of any anxiety disorder. Probable lifetime generalised anxiety disorder and selfreported lifetime diagnosis of any anxiety disorder were meta-analysed with a comparable genome-wide association study of anxiety. Genetic analyses included unrelated Caucasian individuals of Western European ancestry. Estimates of SNP heritability from common variants ranged between 4% (for population level anxiety symptoms) and 32% (for probable generalised anxiety disorder), and all four UK Biobank anxiety phenotypes are highly genetically correlated. Three genome-wide significant loci were found to be associated with anxiety. Both rs3807866 located in the TMEM106B protein coding region on chromosome 7, and rs2996471 located in the NTRK2 protein coding region on chromosome 9, were associated with self-report of any lifetime anxiety diagnosis. An additional non characterised region on chromosome 9 was associated with both self report of any lifetime anxiety diagnosis (rs10809485), and severe anxiety symptoms (rs17189482). Meta-analysis with a comparable genome-wide association study of anxiety did not result in additional findings. This represents the largest genetic study of anxiety to date-however larger sample sizes will be required to further examine the common genetic architecture underlying anxiety. .

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Anxiety disorders are one of the most common, debilitating and costly classes of psychiatric disorders worldwide. Twin studies estimate heritability of anxiety disorders to be between 30% -60%, depending on specific disorder, age, and level of impairment. Although individual anxiety disorders are considered clinically distinct, they share much of their phenotypic and genetic variance, potentially reflecting an underlying liability distribution.

1Depression is more frequent among individuals exposed to traumatic events. 2 Both trauma exposure and depression are heritable. However, the relationship 3 between these traits, including the role of genetic risk factors, is complex and poorly 4 understood. When modelling trauma exposure as an environmental influence on 5 depression, both gene-environment correlations and gene-environment interactions 6 have been observed. The UK Biobank concurrently assessed Major Depressive 7 Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 8 genotyped individuals of European ancestry. We contrasted genetic influences on 9 MDD between individuals reporting and not reporting trauma exposure (final sample 10 size range: 24,094-92,957). The SNP-based heritability of MDD was greater in 11 participants reporting trauma exposure (24%) than in individuals not reporting trauma 12 exposure (12%), taking into account the strong, positive genetic correlation observed 13 between MDD and reported trauma exposure. The genetic correlation between MDD 14and waist circumference was only significant in individuals reporting trauma 15 exposure (r g = 0.24, p = 1.8x10-7 versus r g = -0.05, p = 0.39 in individuals not 16 reporting trauma exposure, difference p = 2.3x10 -4 ). Our results suggest that the 17 genetic contribution to MDD is greater when additional risk factors are present, and 18 that a complex relationship exists between reported trauma exposure, body 19 composition, and MDD. 20 21

Major depressive disorder and the anxiety disorders are highly prevalent, disabling and moderately heritable. Depression and anxiety are also highly comorbid and have a strong genetic correlation ( r g ≈ 1). Cognitive behavioural therapy is a leading evidence-based treatment but has variable outcomes. Currently, there are no strong predictors of outcome. Therapygenetics research aims to identify genetic predictors of prognosis following therapy. We performed genome-wide association meta-analyses of symptoms following cognitive behavioural therapy in adults with anxiety disorders ( n = 972), adults with major depressive disorder ( n = 832) and children with anxiety disorders ( n = 920; meta-analysis n = 2724). We estimated the variance in therapy outcomes that could be explained by common genetic variants ( h 2 SNP ) and polygenic scoring was used to examine genetic associations between therapy outcomes and psychopathology, personality and learning. No single nucleotide polymorphisms were strongly associated with treatment outcomes. No significant estimate of h 2 SNP could be obtained, suggesting the heritability of therapy outcome is smaller than our analysis was powered to detect. Polygenic scoring failed to detect genetic overlap between therapy outcome and psychopathology, personality or learning. This study is the largest therapygenetics study to date. Results are consistent with previous, similarly powered genome-wide association studies of complex traits.

Background This study aimed to develop, validate and compare the performance of models predicting post-treatment outcomes for depressed adults based on pre-treatment data. Methods Individual patient data from all six eligible randomised controlled trials were used to develop (k = 3, n = 1722) and test (k = 3, n = 918) nine models. Predictors included depressive and anxiety symptoms, social support, life events and alcohol use. Weighted sum scores were developed using coefficient weights derived from network centrality statistics (models 1–3) and factor loadings from a confirmatory factor analysis (model 4). Unweighted sum score models were tested using elastic net regularised (ENR) and ordinary least squares (OLS) regression (models 5 and 6). Individual items were then included in ENR and OLS (models 7 and 8). All models were compared to one another and to a null model (mean post-baseline Beck Depression Inventory Second Edition (BDI-II) score in the training data: model 9). Primary outcome: BDI-II scores at 3–4 months. Results Models 1–7 all outperformed the null model and model 8. Model performance was very similar across models 1–6, meaning that differential weights applied to the baseline sum scores had little impact. Conclusions Any of the modelling techniques (models 1–7) could be used to inform prognostic predictions for depressed adults with differences in the proportions of patients reaching remission based on the predicted severity of depressive symptoms post-treatment. However, the majority of variance in prognosis remained unexplained. It may be necessary to include a broader range of biopsychosocial variables to better adjudicate between competing models, and to derive models with greater clinical utility for treatment-seeking adults with depression.

Background Anxiety and depressive disorders can be classified under a bidimensional model, where depression and generalized anxiety disorder are represented by distress and the other anxiety disorders, by fear. The phenotypic structure of this model has been validated, but twin studies only show partial evidence for genetic and environmental distinctions between distress and fear. Moreover, the effects of genetic variants are mostly shared between anxiety and depression, but the genome‐wide genetic distinction between distress and fear remains unexplored. This study aimed to examine the degree of common genetic variation overlap between distress and fear, and their associations with the psychosocial risk factors of loneliness and social isolation. Methods We used genome‐wide data from 157,366 individuals in the UK Biobank who answered a mental health questionnaire. Results Genetic correlations indicated that depression and generalized anxiety had a substantial genetic overlap, and that they were genetically partially distinct from fear disorders. Associations with loneliness, but not social isolation, showed that loneliness was more strongly associated with both distress disorders than with fear. Conclusions Our findings shed light on genetic and environmental mechanisms that are common and unique to distress and fear and contribute to current knowledge on individuals’ susceptibility to anxiety and depression.

Background. Anxiety and depressive disorders can be classified under a bi-dimensional model, where depression and generalized anxiety disorder are represented by distress and the other anxiety disorders, by fear. The phenotypic structure of this model has been validated, but twin studies only show partial evidence for genetic and environmental distinctions between distress and fear. Moreover, the effects of genetic variants are mostly shared between anxiety and depression, but the genome-wide genetic distinction between distress and fear remain unexplored. This study aimed to examine the degree of common genetic variation overlap between distress and fear, and their associations with the psychosocial risk factors of loneliness and social isolation. Methods. We used genome-wide data from 157,366 individuals in the UK Biobank who answered a mental health questionnaire. Results. Genetic correlations indicated that depression and generalized anxiety had a substantial genetic overlap, and that they were genetically partially distinct from fear disorders. Associations with loneliness, but not social isolation, showed that loneliness was more strongly associated with both distress disorders than with fear. Conclusions. Our findings shed light on genetic and environmental mechanisms that are common and unique to distress and fear and contribute to current knowledge on individuals’ susceptibility to anxiety and depression.