Mental health in UK Biobank: development, implementation and results from an online questionnaire completed by 157 366 participants

The genetic basis of major depressive disorder

The genetic dissection of major depressive disorder (MDD) ranks as one of the success stories of psychiatric genetics, with genome-wide association studies (GWAS) identifying 178 genetic risk loci and proposing more than 200 candidate genes. However, the GWAS results derive from the analysis of cohorts in which most cases are diagnosed by minimal phenotyping, a method that has low specificity. I review data indicating that there is a large genetic component unique to MDD that remains inaccessible to minimal phenotyping strategies and that the majority of genetic risk loci identified with minimal phenotyping approaches are unlikely to be MDD risk loci. I show that inventive uses of biobank data, novel imputation methods, combined with more interviewer diagnosed cases, can identify loci that contribute to the episodic severe shifts of mood, and neurovegetative and cognitive changes that are central to MDD. Furthermore, new theories about the nature and causes of MDD, drawing upon advances in neuroscience and psychology, can provide handles on how best to interpret and exploit genetic mapping results.

Associating broad and clinically defined polygenic scores for depression with depression-related phenotypes

Twin studies indicate that 30-40% of the disease liability for depression can be attributed to genetic differences. Here, we assess the explanatory ability of polygenic scores (PGS) based on broad- (PGS_BD) and clinical- (PGS_MDD) depression summary statistics from the UK Biobank in an independent sample of adults (N = 210; 100% European Ancestry) who were extensively phenotyped for depression and related neurocognitive traits (e.g., rumination, emotion regulation, anhedonia, and resting frontal alpha asymmetry). The UK Biobank-derived PGS_BD had small associations with MDD, depression severity, anhedonia, cognitive reappraisal, brooding, and suicidal ideation but only the association with suicidal ideation remained statistically significant after correcting for multiple comparisons. Similarly small associations were observed for the PGS_MDD but none remained significant after correcting for multiple comparisons. These findings provide important initial guidance about the expected effect sizes between current UKB PGSs for depression and depression-related neurocognitive phenotypes.

Adjustment Method of College Students' Mental Health Based on Data Analysis Under the Background of Positive Psychology

Colleges and universities are in an important position to train builders and successors of the socialist cause whilst promoting quality education. Mental health education is an important foundation and condition for comprehensively improving students' overall quality. This research explores adjustment methods for college students' mental health based on virtual reality under the background of positive psychology. It discusses the importance of system requirements analysis in the software development process, analyzes the system's functional requirements, safety requirements, and software and hardware requirements, and uses the Apriori algorithm to explore the influencing factors of college students' mental health. Based on the system engineering method and using the data mining clustering method undertake detailed analysis and research on the mental health of college students, it then designs an anomaly mining algorithm based on clustering to quickly find anomalous data health problems. The interface design of the system is concise and the operation is simple. Users can conveniently input, query, and count information according to the various controls on the interface, which fully embodies human-oriented characteristics. Exploration of the characteristics of students' frequent Internet access ensures the efficiency, accuracy, and comprehensiveness of the evaluation and consultation work, facilitating psychological counseling for teachers and students, and saving paper. By establishing a data mining model, mining the database, and learning about different student groups and their respective characteristics, we discuss our research on student psychology and summarize the mental health status and gender, adaptation and anxiety, introversion, emotionality, and calmness of college students. We also consider the relationship between sex, negative, and courage. Using positive psychology theory, we examine the positive experiences of students and interconnected qualities, to build a mental health practice system. In the experiment, the happiness index evaluation of the virtual reality treatment system group was significant, P = 0.002 < 0.05. Mental health education plays an important role in cultivating the healthy psychology of college students, developing their psychological potential, enhancing their adaptability, and improving their personality. This analysis based on actual data provides a reliable basis for psychological educators to improve the efficiency and effectiveness of school psychological counseling and to facilitate schools in establishing new methods of early prevention and intervention for psychological disorders, enabling institutions to create a healthy atmosphere for college students.

Integrating physical activity into the treatment of depression in adults: A qualitative enquiry

Around 246 million people globally suffer from depression. Physical activity (PA) can reduce the risk of depression by 30% and is recognised as an effective treatment for mild-to-moderate depression (MMD). However, a high proportion of patients with MMD are currently inactive and the implementation of PA as an adherent treatment for MMD is not well understood. This study contributes to a growing body of research exploring how to support people who are experiencing MMD to increase their PA levels (i.e. initiation and maintenance). It investigated which factors individuals with MMD perceived to be important for integrating PA into the treatment of depression in adults. In-depth interviews were carried out with individuals with MMD (N = 6), and data were analysed using thematic analysis. Two main theories of social capital that of Bourdieu and Putnam informed the discussion of findings. The initiation and maintenance of PA were linked to individual factors including health (i.e. nature of depression; comorbidities); abilities and tastes; socioeconomic status (e.g. financial position) and positive encouragement. In addition, maintenance emerged as dependent upon the choice, enjoyment, and meaningfulness of PA itself, and, for those who engaged in group PA, on social capital. PA interventions need to be personalised. This goes beyond a simple exercise prescription based on functional ability, but instead takes into account the needs, desires and capabilities of the whole person. The nature of MMD, the wider physical and socio-economic context and the social capital that is available to the individual also need to be harnessed.

Validation of UK Biobank data for mental health outcomes: A pilot study using secondary care electronic health records

UK Biobank (UKB) is widely employed to investigate mental health disorders and related exposures; however, its applicability and relevance in a clinical setting and the assumptions required have not been sufficiently and systematically investigated. Here, we present the first validation study using secondary care mental health data with linkage to UKB from Oxford - Clinical Record Interactive Search (CRIS) focusing on comparison of demographic information, diagnostic outcome, medication record and cognitive test results, with missing data and the implied bias from both resources depicted. We applied a natural language processing model to extract information embedded in unstructured text from clinical notes and attachments. Using a contingency table we compared the demographic information recorded in UKB and CRIS. We calculated the positive predictive value (PPV, proportion of true positives cases detected) for mental health diagnosis and relevant medication. Amongst the cohort of 854 subjects, PPVs for any mental health diagnosis for dementia, depression, bipolar disorder and schizophrenia were 41.6%, and were 59.5%, 12.5%, 50.0% and 52.6%, respectively. Self-reported medication records in UKB had general PPV of 47.0%, with the prevalence of frequently prescribed medicines to each typical mental health disorder considerably different from the information provided by CRIS. UKB is highly multimodal, but with limited follow-up records, whereas CRIS offers a longitudinal high-resolution clinical picture with more than ten years of observations. The linkage of both datasets will reduce the self-report bias and synergistically augment diverse modalities into a unified resource to facilitate more robust research in mental health.

Group-tailored feedback on online mental health screening for university students: using cluster analysis

BACKGROUND

The method by which mental health screening result reports are given affects the user's health behavior. Lists with the distribution of scores in various mental health areas is difficult for users to understand, and if the results are negative, they may feel more embarrassed than necessary. Therefore, we propose using group-tailored feedback, grouping people of similar mental health types by cluster analysis for comprehensive explanations of multidimensional mental health.

METHODS

This cross-sectional, observational study was conducted using a qualitative approach based on cluster analysis. Data were collected via a developed mental screening website, with depression, anxiety, sleep problems, perfectionism, procrastination, and attention assessed for 2 weeks in January 2020 in Korea. Participants were randomly recruited, and sample size was 174. Total was divided into 25 with severe depression/anxiety (SDA+) and 149 without severe depression/anxiety (SDA-) according to the PHQ-9 and GAD-7 criteria. Cluster analysis was conducted in each group, and an ANOVA was performed to find significant clusters. Thereafter, structured discussion was performed with mental health professionals to define the features of the clusters and construct the feedback content initially. Thirteen expert counselors were interviewed to reconstruct the content and validate the effectiveness of the developed feedback.

RESULTS

SDA- was divided into 3 using the k-means algorithm, which showed the best performance (silhouette score = 0.32, CH score = 91.67) among the clustering methods. Perfectionism and procrastination were significant factors in discretizing the groups. SDA+ subgroups were integrated because only 25 people belonged to this group, and they need professional help rather than self-care. Mental status and treatment recommendations were determined for each group, and group names were assigned to represent their features. The developed feedback was assessed to improve mental health literacy (MHL) through integrative and understandable explanations of multidimensional mental health. Moreover, it appeared that a sense of belonging was induced to reduce reluctance to face the feedback.

CONCLUSIONS

This study suggests group-tailored feedback using cluster analysis, which identifies groups of university students by integrating multidimensions of mental health. These methods can help students increase their interest in mental health and improve MHL to enable timely help.

Child maltreatment and incident mental disorders in middle and older ages: a retrospective UK Biobank cohort study

BACKGROUND

Understanding the mental health consequences of child maltreatment at different life stages is important in accurately quantifying the burden of maltreatment. This study investigated the association between child maltreatment and incident mental disorders in middle and older age as well as the potential mediators and moderators.

METHODS

This is a retrospective cohort study of 56,082 participants from UK Biobank. Child maltreatment was recalled using the Childhood Trauma Screener. Incident mental disorders, including depressive, anxiety and affective disorders, behavioural syndromes, post-traumatic stress disorder (PTSD), schizophrenia, substance abuse, and dementia, after baseline assessment were ascertained through linkage to primary care records.

FINDINGS

There was a dose-response relationship between child maltreatment and mental disorder. Those who experienced three or more maltreatment types had the highest risk of all mental disorders (HR 1.85, 95% CI: 1.67-2.06) followed by those who experienced two (HR 1.48, 95% CI: 1.35-1.63) and then one (HR 1.26, 95% CI: 1.19-2.35). Child maltreatment was most strongly associated with PTSD (HR 1.59, 95% CI: 1.20-2.10 P=0.001). The excess risk was largely unexplained by the included mediators. The association between child maltreatment and all mental disorders were stronger among participants who binge drank (P_interaction=0.003) or had few social visits (P_interaction=0.003).

INTERPRETATION

The mental health consequence of child maltreatment could last decades, even among those who had no recorded mental disorders in early adulthood. In the absence of strong mediators, prevention of child maltreatment remains the priority.

FUNDING

Wellcome Trust Institutional Strategic Support Fund.

A Polygenic Approach to Understanding Resilience to Peer Victimisation

Previous studies suggest an individual’s risk of depression following adversity may be moderated by their genetic liability. No study, however, has examined peer victimisation, an experience repeatedly associated with mental illness. We explore whether the negative mental health outcomes following victimisation can be partly attributed to genetic factors using polygenic scores for depression and wellbeing. Among participants from the Avon Longitudinal Study of Parents and Children (ALSPAC), we show that polygenic scores and peer victimisation are significant independent predictors of depressive symptoms (n=2268) and wellbeing (n=2299) in early adulthood. When testing for interaction effects, our results lead us to conclude that low mental health and wellbeing following peer victimisation is unlikely to be explained by a moderating effect of genetic factors, as indexed by current polygenic scores. Genetic profiling is therefore unlikely to be effective in identifying those more vulnerable to the effects of victimisation at present. The reasons why some go on to experience mental health problems following victimisation, while others remain resilient, requires further exploration, but our results rule out a major influence of current polygenic scores.

CRISPR disruption and UK Biobank analysis of a highly conserved polymorphic enhancer suggests a role in male anxiety and ethanol intake

Excessive alcohol intake is associated with 5.9% of global deaths. However, this figure is especially acute in men such that 7.6% of deaths can be attributed to alcohol intake. Previous studies identified a significant interaction between genotypes of the galanin (GAL) gene with anxiety and alcohol abuse in different male populations but were unable to define a mechanism. To address these issues the current study analysed the human UK Biobank cohort and identified a significant interaction (n = 115,865; p = 0.0007) between allelic variation (GG or CA genotypes) in the highly conserved human GAL5.1 enhancer, alcohol intake (AUDIT questionnaire scores) and anxiety in men. Critically, disruption of GAL5.1 in mice using CRISPR genome editing significantly reduced GAL expression in the amygdala and hypothalamus whilst producing a corresponding reduction in ethanol intake in KO mice. Intriguingly, we also found the evidence of reduced anxiety-like behaviour in male GAL5.1KO animals mirroring that seen in humans from our UK Biobank studies. Using bioinformatic analysis and co-transfection studies we further identified the EGR1 transcription factor, that is co-expressed with GAL in amygdala and hypothalamus, as being important in the protein kinase C (PKC) supported activity of the GG genotype of GAL5.1 but less so in the CA genotype. Our unique study uses a novel combination of human association analysis, CRISPR genome editing in mice, animal behavioural analysis and cell culture studies to identify a highly conserved regulatory mechanism linking anxiety and alcohol intake that might contribute to increased susceptibility to anxiety and alcohol abuse in men.

Polygenic contributions to alcohol use and alcohol use disorders across population-based and clinically ascertained samples

BACKGROUND

Studies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds.

METHODS

We examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes.

RESULTS

In COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47-0.68%, p = 2.0 × 10-8-1.0 × 10-10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10-8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10-6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10-11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10-7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10-16).

CONCLUSIONS

AUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.

Childhood trauma, life-time self-harm, and suicidal behaviour and ideation are associated with polygenic scores for autism

Autistic individuals experience significantly elevated rates of childhood trauma, self-harm and suicidal behaviour and ideation (SSBI). Is this purely the result of negative environmental experiences, or does this interact with genetic predisposition? In this study we investigated if a genetic predisposition for autism is associated with childhood trauma using polygenic scores (PGS) and genetic correlations in the UK Biobank (105,222 < N < 105,638), and tested potential mediators and moderators of the association between autism, childhood trauma and SSBI. Autism PGS were significantly associated with childhood trauma (max R2 = 0.096%, P < 2 × 10-16), self-harm ideation (max R2 = 0.108%, P < 2 × 10-16), and self-harm (max R2 = 0.13%, P < 2 × 10-16). Supporting this, we identified significant genetic correlations between autism and childhood trauma (rg = 0.36 ± 0.05, P = 8.13 × 10-11), self-harm ideation (rg = 0.49 ± 0.05, P = 4.17 × 10-21) and self-harm (rg = 0.48 ± 0.05, P = 4.58 × 10-21), and an over-transmission of PGS for the two SSBI phenotypes from parents to autistic probands. Male sex negatively moderated the effect of autism PGS on childhood trauma (β = -0.023 ± 0.005, P = 6.74 × 10-5). Further, childhood trauma positively moderated the effect of autism PGS on self-harm score (β = 8.37 × 10-3 ± 2.76 × 10-3, P = 2.42 × 10-3) and self-harm ideation (β = 7.47 × 10-3 ± 2.76 × 10-3, P = 6.71 × 10-3). Finally, depressive symptoms, quality and frequency of social interactions, and educational attainment were significant mediators of the effect of autism PGS on SSBI, with the proportion of effect mediated ranging from 0.23 (95% CI: 0.09-0.32) for depression to 0.008 (95% CI: 0.004-0.01) for educational attainment. Our findings identify that a genetic predisposition for autism is associated with adverse life-time outcomes, which represent complex gene-environment interactions, and prioritizes potential mediators and moderators of this shared biology. It is important to identify sources of trauma for autistic individuals in order to reduce their occurrence and impact.

Factors associated with sharing e-mail information and mental health survey participation in large population cohorts

BACKGROUND

People who opt to participate in scientific studies tend to be healthier, wealthier and more educated than the broader population. Although selection bias does not always pose a problem for analysing the relationships between exposures and diseases or other outcomes, it can lead to biased effect size estimates. Biased estimates may weaken the utility of genetic findings because the goal is often to make inferences in a new sample (such as in polygenic risk score analysis).

METHODS

We used data from UK Biobank, Generation Scotland and Partners Biobank and conducted phenotypic and genome-wide association analyses on two phenotypes that reflected mental health data availability: (i) whether participants were contactable by e-mail for follow-up; and (ii) whether participants responded to follow-up surveys of mental health.

RESULTS

In UK Biobank, we identified nine genetic loci associated (P <5 × 10-8) with e-mail contact and 25 loci associated with mental health survey completion. Both phenotypes were positively genetically correlated with higher educational attainment and better health and negatively genetically correlated with psychological distress and schizophrenia. One single nucleotide polymorphism association replicated along with the overall direction of effect of all association results.

CONCLUSIONS

Re-contact availability and follow-up participation can act as further genetic filters for data on mental health phenotypes.

Polygenic overlap and shared genetic loci between loneliness, severe mental disorders, and cardiovascular disease risk factors suggest shared molecular mechanisms

Clinical and epidemiological evidence suggest that loneliness is associated with severe mental disorders (SMDs) and increases the risk of cardiovascular disease (CVD). However, the mechanisms underlying the relationship between loneliness, SMDs, and CVD risk factors remain unknown. Here we explored overlapping genetic architecture and genetic loci shared between SMDs, loneliness, and CVD risk factors. We analyzed large independent genome-wide association study data on schizophrenia (SCZ), bipolar disorder (BD), major depression (MD), loneliness and CVD risk factors using bivariate causal mixture mode (MiXeR), which estimates the total amount of shared variants, and conditional false discovery rate to evaluate overlap in specific loci. We observed substantial genetic overlap between SMDs, loneliness and CVD risk factors, beyond genetic correlation. We identified 149 loci jointly associated with loneliness and SMDs (MD n = 67, SCZ n = 54, and BD n = 28), and 55 distinct loci jointly associated with loneliness and CVD risk factors. A total of 153 novel loneliness loci were found. Most of the shared loci possessed concordant effect directions, suggesting that genetic risk for loneliness may increase the risk of both SMDs and CVD. Functional analyses of the shared loci implicated biological processes related to the brain, metabolic processes, chromatin and immune system. Altogether, the study revealed polygenic overlap between loneliness, SMDs and CVD risk factors, providing new insights into their shared genetic architecture and common genetic mechanisms.

A major role for common genetic variation in anxiety disorders

Anxiety disorders are common, complex psychiatric disorders with twin heritabilities of 30-60%. We conducted a genome-wide association study of Lifetime Anxiety Disorder (n_case = 25 453, n_control = 58 113) and an additional analysis of Current Anxiety Symptoms (n_case = 19 012, n_control = 58 113). The liability scale common variant heritability estimate for Lifetime Anxiety Disorder was 26%, and for Current Anxiety Symptoms was 31%. Five novel genome-wide significant loci were identified including an intergenic region on chromosome 9 that has previously been associated with neuroticism, and a locus overlapping the BDNF receptor gene, NTRK2. Anxiety showed significant positive genetic correlations with depression and insomnia as well as coronary artery disease, mirroring findings from epidemiological studies. We conclude that common genetic variation accounts for a substantive proportion of the genetic architecture underlying anxiety.

Genetic comorbidity between major depression and cardio-metabolic traits, stratified by age at onset of major depression

It is imperative to understand the specific and shared etiologies of major depression and cardio-metabolic disease, as both traits are frequently comorbid and each represents a major burden to society. This study examined whether there is a genetic association between major depression and cardio-metabolic traits and if this association is stratified by age at onset for major depression. Polygenic risk scores analysis and linkage disequilibrium score regression was performed to examine whether differences in shared genetic etiology exist between depression case control status (N cases = 40,940, N controls = 67,532), earlier (N = 15,844), and later onset depression (N = 15,800) with body mass index, coronary artery disease, stroke, and type 2 diabetes in 11 data sets from the Psychiatric Genomics Consortium, Generation Scotland, and UK Biobank. All cardio-metabolic polygenic risk scores were associated with depression status. Significant genetic correlations were found between depression and body mass index, coronary artery disease, and type 2 diabetes. Higher polygenic risk for body mass index, coronary artery disease, and type 2 diabetes was associated with both early and later onset depression, while higher polygenic risk for stroke was associated with later onset depression only. Significant genetic correlations were found between body mass index and later onset depression, and between coronary artery disease and both early and late onset depression. The phenotypic associations between major depression and cardio-metabolic traits may partly reflect their overlapping genetic etiology irrespective of the age depression first presents.

The Genetics of the Mood Disorder Spectrum: Genome-wide Association Analyses of More Than 185,000 Cases and 439,000 Controls

BACKGROUND

Mood disorders (including major depressive disorder and bipolar disorder) affect 10% to 20% of the population. They range from brief, mild episodes to severe, incapacitating conditions that markedly impact lives. Multiple approaches have shown considerable sharing of risk factors across mood disorders despite their diagnostic distinction.

METHODS

To clarify the shared molecular genetic basis of major depressive disorder and bipolar disorder and to highlight disorder-specific associations, we meta-analyzed data from the latest Psychiatric Genomics Consortium genome-wide association studies of major depression (including data from 23andMe) and bipolar disorder, and an additional major depressive disorder cohort from UK Biobank (total: 185,285 cases, 439,741 controls; nonoverlapping N = 609,424).

RESULTS

Seventy-three loci reached genome-wide significance in the meta-analysis, including 15 that are novel for mood disorders. More loci from the Psychiatric Genomics Consortium analysis of major depression than from that for bipolar disorder reached genome-wide significance. Genetic correlations revealed that type 2 bipolar disorder correlates strongly with recurrent and single-episode major depressive disorder. Systems biology analyses highlight both similarities and differences between the mood disorders, particularly in the mouse brain cell types implicated by the expression patterns of associated genes. The mood disorders also differ in their genetic correlation with educational attainment-the relationship is positive in bipolar disorder but negative in major depressive disorder.

CONCLUSIONS

The mood disorders share several genetic associations, and genetic studies of major depressive disorder and bipolar disorder can be combined effectively to enable the discovery of variants not identified by studying either disorder alone. However, we demonstrate several differences between these disorders. Analyzing subtypes of major depressive disorder and bipolar disorder provides evidence for a genetic mood disorders spectrum.

Genome-wide gene-environment analyses of major depressive disorder and reported lifetime traumatic experiences in UK Biobank

Depression is more frequent among individuals exposed to traumatic events. Both trauma exposure and depression are heritable. However, the relationship between these traits, including the role of genetic risk factors, is complex and poorly understood. When modelling trauma exposure as an environmental influence on depression, both gene-environment correlations and gene-environment interactions have been observed. The UK Biobank concurrently assessed Major Depressive Disorder (MDD) and self-reported lifetime exposure to traumatic events in 126,522 genotyped individuals of European ancestry. We contrasted genetic influences on MDD stratified by reported trauma exposure (final sample size range: 24,094-92,957). The SNP-based heritability of MDD with reported trauma exposure (24%) was greater than MDD without reported trauma exposure (12%). Simulations showed that this is not confounded by the strong, positive genetic correlation observed between MDD and reported trauma exposure. We also observed that the genetic correlation between MDD and waist circumference was only significant in individuals reporting trauma exposure (rg = 0.24, p = 1.8 × 10-7 versus rg = -0.05, p = 0.39 in individuals not reporting trauma exposure, difference p = 2.3 × 10-4). Our results suggest that the genetic contribution to MDD is greater when reported trauma is present, and that a complex relationship exists between reported trauma exposure, body composition, and MDD.

Trends in psychiatric diagnoses, medications and psychological therapies in a large Swedish region: a population-based study

BACKGROUND

Health services utilization for mental health disorders is reported to increase sharply in many countries. The aim of this study was to report trends in all aspects of mental health care utilization in a total population sample.

METHODS

Repeated cross-sectional register study of the Stockholm Region (VAL) including both primary and secondary care. Trends in the proportion of adults in the total population of Stockholm Region with a recorded ICD-10 psychiatric diagnosis or psychological therapy during 2007-2017 as well as claims of psychiatric medication from 2011 were calculated.

RESULTS

The proportion of adults utilizing any mental health care increased from 13.2% in 2011 to 16.1% in 2017. In 2017, 49.3% were treated in primary care, 32.2% in secondary care and 18.5% were jointly managed. The increase was most pronounced in younger adults. Women were more likely to receive mental health care than men in all ages. Medication decreased from 71.0 to 67.7%, while psychological therapy increased from 33.1 to 37.6%. The use of psychiatric medication increased with age while psychological therapy decreased. All time trends were statistically significant (p < .0001).

CONCLUSION

Care for mental health disorders has been increasing mainly in primary care and was delivered to one in seven adult individuals in 2017. Interventions are needed to address the growing burden of mental health disorders while avoiding overtreatment.

Genetic aetiology of self-harm ideation and behaviour

Family studies have identified a heritable component to self-harm that is partially independent from comorbid psychiatric disorders. However, the genetic aetiology of broad sense (non-suicidal and suicidal) self-harm has not been characterised on the molecular level. In addition, controversy exists about the degree to which suicidal and non-suicidal self-harm share a common genetic aetiology. In the present study, we conduct genome-wide association studies (GWAS) on lifetime self-harm ideation and self-harm behaviour (i.e. any lifetime self-harm act regardless of suicidal intent) using data from the UK Biobank (n > 156,000). We also perform genome wide gene-based tests and characterize the SNP heritability and genetic correlations between these traits. Finally, we test whether polygenic risk scores (PRS) for self-harm ideation and self-harm behaviour predict suicide attempt, suicide thoughts and non-suicidal self-harm (NSSH) in an independent target sample of 8,703 Australian adults. Our GWAS results identified one genome-wide significant locus associated with each of the two phenotypes. SNP heritability (hsnp2) estimates were ~10%, and both traits were highly genetically correlated (LDSC rg > 0.8). Gene-based tests identified seven genes associated with self-harm ideation and four with self-harm behaviour. Furthermore, in the target sample, PRS for self-harm ideation were significantly associated with suicide thoughts and NSSH, and PRS for self-harm behaviour predicted suicide thoughts and suicide attempt. Follow up regressions identified a shared genetic aetiology between NSSH and suicide thoughts, and between suicide thoughts and suicide attempt. Evidence for shared genetic aetiology between NSSH and suicide attempt was not statistically significant.

Child maltreatment and cardiovascular disease: quantifying mediation pathways using UK Biobank

BACKGROUND

Child maltreatment is associated with cardiovascular disease (CVD), but mediation pathways have not been fully elucidated. The aim of the current study was to determine and quantify the underlying pathways linking child maltreatment and CVD.

METHODS

We conducted a retrospective cohort study using the UK Biobank. The number and types of child maltreatment, including abuse and neglect, were recalled by the participants. Lifestyle, biological, physical, and mental health factors measured at baseline were explored as potential mediators. Incident CVD was ascertained through record linkage after baseline measurement. Age, sex, ethnicity, area-based deprivation, and education level were adjusted for as confounders. Cox proportional hazard models were conducted to test for associations between child maltreatment and incident CVD.

RESULTS

A total of 152,040 participants who completed the child maltreatment assessment were included in the analyses, and one third reported at least one type of child maltreatment. There was a dose-response relationship between the number of maltreatment types and incident CVD. On average, each additional type of child maltreatment was associated with an 11% (95% CI 8-14%, P < 0.0001) increased risk of CVD. The majority (56.2%) of the association was mediated through depressive symptoms, followed by smoking (14.7%), high-density lipoprotein cholesterol (8.7%), and sleep duration (2.4%).

CONCLUSION

Child maltreatment is associated with incident CVD through a combination of mental health, lifestyle, and biological pathways. Therefore, in addition to interventions to reduce the occurrence of child maltreatment, attention should be targeted at promoting healthy lifestyles and preventing, identifying, and treating depression among children and adults who have previously been maltreated.

The genetic and environmental hierarchical structure of anxiety and depression in the UK Biobank

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.

A phenome-wide association and Mendelian Randomisation study of polygenic risk for depression in UK Biobank

Depression is a leading cause of worldwide disability but there remains considerable uncertainty regarding its neural and behavioural associations. Here, using non-overlapping Psychiatric Genomics Consortium (PGC) datasets as a reference, we estimate polygenic risk scores for depression (depression-PRS) in a discovery (N = 10,674) and replication (N = 11,214) imaging sample from UK Biobank. We report 77 traits that are significantly associated with depression-PRS, in both discovery and replication analyses. Mendelian Randomisation analysis supports a potential causal effect of liability to depression on brain white matter microstructure (β: 0.125 to 0.868, p_FDR < 0.043). Several behavioural traits are also associated with depression-PRS (β: 0.014 to 0.180, p_FDR: 0.049 to 1.28 × 10⁻¹⁴) and we find a significant and positive interaction between depression-PRS and adverse environmental exposures on mental health outcomes. This study reveals replicable associations between depression-PRS and white matter microstructure. Our results indicate that white matter microstructure differences may be a causal consequence of liability to depression.

Depression is correlated with many brain-related traits. Here, Shen et al. perform phenome-wide association studies of a depression polygenic risk score (PRS) and find associations with 51 behavioural and 26 neuroimaging traits which are further followed up on using Mendelian randomization and mediation analyses.

Characteristics, comorbidities, and correlates of atypical depression: evidence from the UK Biobank Mental Health Survey

BACKGROUND

Depression is a heterogeneous disorder with multiple aetiological pathways and multiple therapeutic targets. This study aims to determine whether atypical depression (AD) characterized by reversed neurovegetative symptoms is associated with a more pernicious course and a different sociodemographic, lifestyle, and comorbidity profile than nonatypical depression (nonAD).

METHODS

Among 157 366 adults who completed the UK Biobank Mental Health Questionnaire (MHQ), N = 37 434 (24%) met the DSM-5 criteria for probable lifetime major depressive disorder (MDD) based on the Composite International Diagnostic Interview Short Form. Participants reporting both hypersomnia and weight gain were classified as AD cases (N = 2305), and the others as nonAD cases (N = 35 129). Logistic regression analyses were conducted to examine differences between AD and nonAD in depression features, sociodemographic and lifestyle factors, lifetime adversities, psychiatric and physical comorbidities.

RESULTS

Persons with AD experienced an earlier age of depression onset, longer, more severe and recurrent episodes, and higher help-seeking rates than nonAD persons. AD was associated with female gender, unhealthy behaviours (smoking, social isolation, low physical activity), more lifetime deprivation and adversity, higher rates of comorbid psychiatric disorders, obesity, cardiovascular disease (CVD), and metabolic syndrome. Sensitivity analyses comparing AD persons with those having typical neurovegetative symptoms (hyposomnia and weight loss) revealed similar results.

CONCLUSIONS

These findings highlight the clinical and public health significance of AD as a chronic form of depression, associated with high comorbidity and lifetime adversity. Our findings have implications for predicting depression course and comorbidities, guiding research on aetiological mechanisms, planning service use and informing therapeutic approaches.

Harnessing Progress in Psychiatric Genetics to Advance Population Mental Health

Advances in genomics and neuroscience have ushered in unprecedented opportunities to increase our understanding of the biological underpinnings of mental disorders, yet there has been limited progress in translating knowledge on genetic risk factors to reduce the burden of these conditions in the population. We describe the challenges and opportunities afforded by the growth of large-scale population health databases, progress in genomics, and collaborative efforts in epidemiology and neuroscience to develop informed population-wide interventions for mental disorders. Future progress is likely to benefit from the following efforts: expansion of large collaborative studies of mental disorders to include more systematically ascertained multiethnic samples from biobanks and registries, harmonization of phenotypic characterization in registry and population samples to extend clinical diagnosis to transdiagnostic concepts, systematic investigation of the influences of both specific and nonspecific environmental factors that may combine with genetic susceptibility to confer increased risk of specific mental disorders, and implementation of study designs that can inform gene-environment interactions. Such data can ultimately be combined to develop comprehensive models of risks of, interventions for, and outcomes of mental disorders. With its focus on phenotypic characterization, sampling, study designs, and analytic methods, epidemiology will be central to progress in translating genomics to public health.

Minimal phenotyping yields genome-wide association signals of low specificity for major depression

Minimal phenotyping refers to the reliance on the use of a small number of self-reported items for disease case identification, increasingly used in genome-wide association studies (GWAS). Here we report differences in genetic architecture between depression defined by minimal phenotyping and strictly defined major depressive disorder (MDD): the former has a lower genotype-derived heritability that cannot be explained by inclusion of milder cases and a higher proportion of the genome contributing to this shared genetic liability with other conditions than for strictly defined MDD. GWAS based on minimal phenotyping definitions preferentially identifies loci that are not specific to MDD, and, although it generates highly predictive polygenic risk scores, the predictive power can be explained entirely by large sample sizes rather than by specificity for MDD. Our results show that reliance on results from minimal phenotyping may bias views of the genetic architecture of MDD and impede the ability to identify pathways specific to MDD.

Recent Efforts to Dissect the Genetic Basis of Alcohol Use and Abuse

Alcohol use disorder (AUD) is defined by several symptom criteria, which can be dissected further at the genetic level. Over the past several years, our understanding of the genetic factors influencing alcohol use and abuse has progressed tremendously; numerous loci have been implicated in different aspects of alcohol use. Previously known associations with alcohol-metabolizing enzymes (ADH1B, ALDH2) have been replicated definitively. In addition, novel associations with loci containing the genes KLB, GCKR, CRHR1, and CADM2 have been reported. Downstream analyses have leveraged these genetic findings to reveal important relationships between alcohol use behaviors and both physical and mental health. AUD and aspects of alcohol misuse have been shown to overlap strongly with psychiatric disorders, whereas aspects of alcohol consumption have shown stronger links to metabolism. These results demonstrate that the genetic architecture of alcohol consumption only partially overlaps with the genetics of clinically defined AUD. We discuss the limitations of using quantitative measures of alcohol use as proxy measures for AUD, and we outline how future studies will require careful phenotype harmonization to properly capture the genetic liability to AUD.

Classical Human Leukocyte Antigen Alleles and C4 Haplotypes Are Not Significantly Associated With Depression

BACKGROUND

The prevalence of depression is higher in individuals with autoimmune diseases, but the mechanisms underlying the observed comorbidities are unknown. Shared genetic etiology is a plausible explanation for the overlap, and in this study we tested whether genetic variation in the major histocompatibility complex (MHC), which is associated with risk for autoimmune diseases, is also associated with risk for depression.

METHODS

We fine-mapped the classical MHC (chr6: 29.6-33.1 Mb), imputing 216 human leukocyte antigen (HLA) alleles and 4 complement component 4 (C4) haplotypes in studies from the Psychiatric Genomics Consortium Major Depressive Disorder Working Group and the UK Biobank. The total sample size was 45,149 depression cases and 86,698 controls. We tested for association between depression status and imputed MHC variants, applying both a region-wide significance threshold (3.9 × 10-6) and a candidate threshold (1.6 × 10-4).

RESULTS

No HLA alleles or C4 haplotypes were associated with depression at the region-wide threshold. HLA-B*08:01 was associated with modest protection for depression at the candidate threshold for testing in HLA genes in the meta-analysis (odds ratio = 0.98, 95% confidence interval = 0.97-0.99).

CONCLUSIONS

We found no evidence that an increased risk for depression was conferred by HLA alleles, which play a major role in the genetic susceptibility to autoimmune diseases, or C4 haplotypes, which are strongly associated with schizophrenia. These results suggest that any HLA or C4 variants associated with depression either are rare or have very modest effect sizes.

Cannabis use, depression and self-harm: phenotypic and genetic relationships

BACKGROUND AND AIMS

The use of cannabis has previously been linked to both depression and self-harm; however, the role of genetics in this relationship is unclear. This study aimed to estimate the phenotypic and genetic associations between cannabis use and depression and self-harm.

DESIGN

Cross-sectional data collected through UK Biobank were used to test the phenotypic association between cannabis use, depression and self-harm. UK Biobank genetic data were then combined with consortia genome-wide association study summary statistics to further test the genetic relationships between these traits using LD score regression, polygenic risk scoring and Mendelian randomization methods.

SETTING

United Kingdom, with additional international consortia data.

PARTICIPANTS

A total of 126 291 British adults aged between 40 and 70 years, recruited into UK Biobank.

MEASUREMENTS

Phenotypic outcomes were life-time history of cannabis use (including initial and continued cannabis use), depression (including single-episode and recurrent depression) and self-harm. Genome-wide genetic data were used and assessment centre, batch and the first six principal components were included as key covariates when handling genetic data.

FINDINGS

In UK Biobank, cannabis use is associated with an increased likelihood of depression [odds ratio (OR) = 1.64, 95% confidence interval (CI) = 1.59-1.70] and self-harm (OR = 2.85, 95% CI = 2.69-3.01). The strength of this phenotypic association is stronger when more severe trait definitions of cannabis use and depression are considered. Using consortia genome-wide summary statistics, significant genetic correlations are seen between cannabis use and depression [rg = 0.289, standard error (SE) = 0.036]. Polygenic risk scores for cannabis use and depression explain a small but significant proportion of variance in cannabis use, depression and self-harm within a UK Biobank target sample. However, two-sample Mendelian randomization analyses were not significant.

CONCLUSIONS

Cannabis use appeared to be both phenotypically and genetically associated with depression and self-harm. Limitations in statistical power mean that conclusions could not be made on the direction of causality between these traits.

Potential influence of socioeconomic status on genetic correlations between alcohol consumption measures and mental health

BACKGROUND

Frequency and quantity of alcohol consumption are metrics commonly used to measure alcohol consumption behaviors. Epidemiological studies indicate that these alcohol consumption measures are differentially associated with (mental) health outcomes and socioeconomic status (SES). The current study aims to elucidate to what extent genetic risk factors are shared between frequency and quantity of alcohol consumption, and how these alcohol consumption measures are genetically associated with four broad phenotypic categories: (i) SES; (ii) substance use disorders; (iii) other psychiatric disorders; and (iv) psychological/personality traits.

METHODS

Genome-Wide Association analyses were conducted to test genetic associations with alcohol consumption frequency (N = 438 308) and alcohol consumption quantity (N = 307 098 regular alcohol drinkers) within UK Biobank. For the other phenotypes, we used genome-wide association studies summary statistics. Genetic correlations (rg) between the alcohol measures and other phenotypes were estimated using LD score regression.

RESULTS

We found a substantial genetic correlation between the frequency and quantity of alcohol consumption (rg = 0.52). Nevertheless, both measures consistently showed opposite genetic correlations with SES traits, and many substance use, psychiatric, and psychological/personality traits. High alcohol consumption frequency was genetically associated with high SES and low risk of substance use disorders and other psychiatric disorders, whereas the opposite applies for high alcohol consumption quantity.

CONCLUSIONS

Although the frequency and quantity of alcohol consumption show substantial genetic overlap, they consistently show opposite patterns of genetic associations with SES-related phenotypes. Future studies should carefully consider the potential influence of SES on the shared genetic etiology between alcohol and adverse (mental) health outcomes.

Physical activity based classification of serious mental illness group participants in the UK Biobank using ensemble dense neural networks

Serious Mental Illnesses (SMIs) including schizophrenia and bipolar disorder are long term conditions which place major burdens on health and social care services. Locomotor activity is altered in many cases of SMI, and so in the long term wearable activity trackers could potentially aid in the early detection of SMI relapse, allowing early and targeted intervention. To move towards this goal, in this paper we use accelerometer activity tracking data collected from the UK Biobank to classify people as being either in a self-reported SMI group or an age and gender matched control group. Using an ensemble dense neural network algorithm we exploited hourly and average derived features from the wearable activity data and the created model obtained an accuracy of 91.3%.

The Genetic Links to Anxiety and Depression (GLAD) Study: Online recruitment into the largest recontactable study of depression and anxiety

BACKGROUND

Anxiety and depression are common, debilitating and costly. These disorders are influenced by multiple risk factors, from genes to psychological vulnerabilities and environmental stressors, but research is hampered by a lack of sufficiently large comprehensive studies. We are recruiting 40,000 individuals with lifetime depression or anxiety and broad assessment of risks to facilitate future research.

METHODS

The Genetic Links to Anxiety and Depression (GLAD) Study (www.gladstudy.org.uk) recruits individuals with depression or anxiety into the NIHR Mental Health BioResource. Participants invited to join the study (via media campaigns) provide demographic, environmental and genetic data, and consent for medical record linkage and recontact.

RESULTS

Online recruitment was effective; 42,531 participants consented and 27,776 completed the questionnaire by end of July 2019. Participants' questionnaire data identified very high rates of recurrent depression, severe anxiety, and comorbidity. Participants reported high rates of treatment receipt. The age profile of the sample is biased toward young adults, with higher recruitment of females and the more educated, especially at younger ages.

DISCUSSION

This paper describes the study methodology and descriptive data for GLAD, which represents a large, recontactable resource that will enable future research into risks, outcomes, and treatment for anxiety and depression.

Investigating Causality Between Blood Metabolites and Emotional and Behavioral Responses to Traumatic Stress: a Mendelian Randomization Study

To investigate the causal relationship between blood metabolites and traits related to trauma-response, we combined genome-wide and metabolome-wide datasets generated from large-scale cohorts. Five trauma-response traits ascertained in the UK Biobank (52,816 < N < 117,900 individuals) were considered: (i) "Avoided activities/situations because of previous stressful experience" (Avoidance); (ii) "Felt distant from other people" (Distant); (iii) "Felt irritable/had angry outbursts" (Irritable); (iv) "Felt very upset when reminded of stressful experience" (Upset); (v) "Repeated disturbing thoughts of stressful experience". These were investigated with respect to 52 blood metabolites tested in a previous genome-wide-association study (N = 24,925 European-ancestry individuals). Linkage disequilibrium score regression, polygenic risk scoring (PRS), and Mendelian randomization were applied to the datasets. We observed that 14 metabolites were genetically correlated with trauma-response traits (p < 0.05). High-resolution PRS of 4 metabolites (citrate; glycoprotein acetyls; concentration of large very-low-density lipoproteins (VLDL) particles (LVLDLP); total cholesterol in medium particles of VLDL (MVLDLC)) were associated with trauma-response traits (false discovery rate Q < 10%). These genetic associations were partially due to causal relationships (Citrate→Upset β = - 0.058, p = 9.1 × 10^-4; Glycoproteins→Avoidance β = 0.008, p = 0.003; LVLDLP→Distant β = 0.008, p = 0.022; MVLDLC→Avoidance β = 0.019, p = 3 × 10^-4). No reverse associations were observed. In conclusion, our study supports causal relationships between certain blood metabolites and emotional and behavioral responses to traumatic experiences.

Identification of novel common variants associated with chronic pain using conditional false discovery rate analysis with major depressive disorder and assessment of pleiotropic effects of LRFN5

Chronic pain is a complex trait that is moderately heritable and genetically, as well as phenotypically, correlated with major depressive disorder (MDD). Use of the conditional false discovery rate (cFDR) approach, which leverages pleiotropy identified from existing GWAS outputs, has been successful in discovering novel associated variants in related phenotypes. Here, genome-wide association study outputs for both von Korff chronic pain grade and for MDD were used to identify variants meeting a cFDR threshold for each outcome phenotype separately, as well as a conjunctional cFDR (ccFDR) threshold for both phenotypes together. Using a moderately conservative threshold, we identified a total of 11 novel single nucleotide polymorphisms (SNPs), six of which were associated with chronic pain grade and nine of which were associated with MDD. Four SNPs on chromosome 14 were associated with both chronic pain grade and MDD. SNPs associated only with chronic pain grade were located within SLC16A7 on chromosome 12. SNPs associated only with MDD were located either in a gene-dense region on chromosome 1 harbouring LINC01360, LRRIQ3, FPGT and FPGT-TNNI3K, or within/close to LRFN5 on chromosome 14. The SNPs associated with both outcomes were also located within LRFN5. Several of the SNPs on chromosomes 1 and 14 were identified as being associated with expression levels of nearby genes in the brain and central nervous system. Overall, using the cFDR approach, we identified several novel genetic loci associated with chronic pain and we describe likely pleiotropic effects of a recently identified MDD locus on chronic pain.

A polygenic score for body mass index is associated with depressive symptoms via early life stress: Evidence for gene-environment correlation

Increasing childhood obesity rates are associated with not only adverse physical, but also mental health outcomes, including depression. These negative outcomes may be caused and/or exacerbated by the bullying and shaming overweight individuals experience. As body mass index (BMI) can be highly heritable, we hypothesized that a genetic risk for higher BMI, will predict higher early life stress (ELS), which in turn will predict higher depressive symptoms in adulthood. Such a process will reflect an evocative gene-environment correlation (rGE) wherein an individual's genetically influenced phenotype evokes a reaction from the environment that subsequently shapes the individual's health. We modeled genetic risk using a polygenic score of BMI derived from a recent large GWAS meta-analysis. Self-reports were used for the assessment of ELS and depressive symptoms in adulthood. The discovery sample consisted of 524 non-Hispanic Caucasian university students from the Duke Neurogenetics Study (DNS; 278 women, mean age 19.78 ± 1.23 years) and the independent replication sample consisted of 5930 white British individuals from the UK biobank (UKB; 3128 women, mean age 62.66 ± 7.38 years). A significant mediation effect was found in the DNS (indirect effect = 0.207, bootstrapped SE = .10, bootstrapped 95% CI: 0.014 to 0.421), and then replicated in the UKB (indirect effect = 0.04, bootstrapped SE = .01, bootstrapped 95% CI: 0.018 to 0.066). Higher BMI polygenic scores predicted higher ELS, which in turn predicted higher depressive symptoms. Our findings suggest that evocative rGE may contribute to weight-related mental health problems and stress the need for interventions that aim to reduce weight bias, specifically during childhood.

Children of the Twins Early Development Study (CoTEDS): A Children-of-Twins Study

The Children of the Twins Early Development Study (CoTEDS) is a new prospective children-of-twins study in the UK, designed to investigate intergenerational associations across child developmental stages. CoTEDS will enable research on genetic and environmental factors that underpin parent-child associations, with a focus on mental health and cognitive-related traits. Through CoTEDS, we will have a new lens to examine the roles that parents play in influencing child development, as well as the genetic and environmental factors that shape parenting behavior and experiences. Recruitment is ongoing from the sample of approximately 20,000 contactable adult twins who have been enrolled in the Twins Early Development Study (TEDS) since infancy. TEDS twins are invited to register all offspring to CoTEDS at birth, with 554 children registered as of May 2019. By recruiting the second generation of TEDS participants, CoTEDS will include information on adult twins and their offspring from infancy. Parent questionnaire-based data collection is now underway for 1- and 2-year-old CoTEDS infants, with further waves of data collection planned. Current data collection includes the following primary constructs: child mental health, temperament, language and cognitive development; parent mental health and social relationships; parenting behaviors and feelings; and other socioecological factors. Measurement tools have been selected with reference to existing genetically informative cohort studies to ensure overlap in phenotypes measured at corresponding stages of development. This built-in study overlap is intended to enable replication and triangulation of future analyses across samples and research designs. Here, we summarize study protocols and measurement procedures and describe future plans.

Genomics of body fat percentage may contribute to sex bias in anorexia nervosa

Anorexia nervosa (AN) occurs nine times more often in females than in males. Although environmental factors likely play a role, the reasons for this imbalanced sex ratio remain unresolved. AN displays high genetic correlations with anthropometric and metabolic traits. Given sex differences in body composition, we investigated the possible metabolic underpinnings of female propensity for AN. We conducted sex-specific GWAS in a healthy and medication-free subsample of the UK Biobank (n = 155,961), identifying 77 genome-wide significant loci associated with body fat percentage (BF%) and 174 with fat-free mass (FFM). Partitioned heritability analysis showed an enrichment for central nervous tissue-associated genes for BF%, which was more prominent in females than males. Genetic correlations of BF% and FFM with the largest GWAS of AN by the Psychiatric Genomics Consortium were estimated to explore shared genomics. The genetic correlations of BF%male and BF%female with AN differed significantly from each other (p < .0001, δ = -0.17), suggesting that the female preponderance in AN may, in part, be explained by sex-specific anthropometric and metabolic genetic factors increasing liability to AN.

Indicators of mental disorders in UK Biobank-A comparison of approaches

OBJECTIVES

For many research cohorts, it is not practical to provide a "gold-standard" mental health diagnosis. It is therefore important for mental health research that potential alternative measures for ascertaining mental disorder status are understood.

METHODS

Data from UK Biobank in those participants who had completed the online Mental Health Questionnaire (n = 157,363) were used to compare the classification of mental disorder by four methods: symptom-based outcome (self-complete based on diagnostic interviews), self-reported diagnosis, hospital data linkage, and self-report medication.

RESULTS

Participants self-reporting any psychiatric diagnosis had elevated risk of any symptom-based outcome. Cohen's κ between self-reported diagnosis and symptom-based outcome was 0.46 for depression, 0.28 for bipolar affective disorder, and 0.24 for anxiety. There were small numbers of participants uniquely identified by hospital data linkage and medication.

CONCLUSION

Our results confirm that ascertainment of mental disorder diagnosis in large cohorts such as UK Biobank is complex. There may not be one method of classification that is right for all circumstances, but an informed and transparent use of outcome measure(s) to suit each research question will maximise the potential of UK Biobank and other resources for mental health research.

Association of Rare Copy Number Variants With Risk of Depression

IMPORTANCE

The role of large, rare copy number variants (CNVs) in neuropsychiatric disorders is well established, but their association with common psychiatric disorders, such as depression, remains unclear.

OBJECTIVE

To examine the association of a group of 53 CNVs associated with neurodevelopmental disorders and burden of rare CNVs with risk of depression.

DESIGN, SETTING, AND PARTICIPANTS

This case-control study used data from the UK Biobank study sample, which comprised 502 534 individuals living in the United Kingdom. Individuals with autism spectrum disorder, intellectual disability, attention-deficit/hyperactivity disorder, schizophrenia, or bipolar affective disorder diagnoses were excluded. Analyses were further restricted to individuals of European genetic ancestry (n = 407 074). The study was conducted from January 2017 to September 2018.

EXPOSURES

CNV carrier status.

MAIN OUTCOMES AND MEASURES

For the primary outcome, individuals who reported that a physician had told them they had a depression diagnosis were defined as cases. Analyses were repeated using 2 alternative depression definitions: self-reported lifetime depression with current antidepressant prescription at the time of visit 1, and hospital discharge diagnosis of depression.

RESULTS

Copy number variants were identified in 488 366 individuals aged 37 to 73 years. In total, 407 074 individuals with European genetic ancestry (220 201 female [54.1%]; mean [SD] age of 56.9 [8.0] years) were included in the study. Of these individuals, 23 979 (5.9%) had self-reported lifetime depression and 383 095 (94.1%) reported no lifetime depression. The group of 53 neurodevelopmental CNVs was associated with self-reported depression (odds ratio [OR], 1.34; 95% CI, 1.19-1.49, uncorrected P = 1.38 × 10-7), and these results were consistent when using 2 alternative definitions of depression. This association was partially explained by physical health, educational attainment, social deprivation, smoking status, and alcohol consumption. A strong independent association remained between the neurodevelopmental CNVs and depression in analyses that incorporated these other measures (OR, 1.26; 95% CI, 1.11-1.43; P = 2.87 × 10-4). Eight individual CNVs were nominally associated with risk of depression, and 3 of these 8 CNVs (1q21.1 duplication, Prader-Willi syndrome duplication, and 16p11.2 duplication) survived Bonferroni correction for the 53 CNVs tested. After the exclusion of carriers of neurodevelopmental CNVs, no association was found between measures of CNV burden and depression.

CONCLUSIONS AND RELEVANCE

Neurodevelopmental CNVs appear to be associated with depression, extending the spectrum of clinical phenotypes that are associated with CNV carrier status.

When a corrigendum is not sufficient

We present the reasoning behind a retraction noting that even small, honest errors can result in significant changes in findings.

Genetic influences on treatment-seeking for common mental health problems in the UK biobank

The majority of those who experience clinical anxiety and/or depressive symptoms in the population do not receive treatment. Studies investigating inequalities in treatment outcomes rarely consider that individuals respond differently to their experience of the environment. Much of our environment is under genetic influence, via our behaviour, whereby individuals actively select their experiences. If genes influence who seeks and receives treatment, selection bias will confound genomic studies of treatment response. Furthermore, if some individuals are at high genetic risk of needing but not commencing treatment, then greater efforts could be made to engage them. The role of common genetic variation on four lifetime treatment-seeking behaviours (treatment-seeking, treatment-receipt, self-help, self-medication with alcohol/drugs) was examined in participants of the UK Biobank (sample size range: 48,106 - 75,322). Treatment-related behaviours were only modestly heritable in these data. Nonetheless, genetic correlations reveal substantial genetic overlap between lifetime treatment-related behaviours and psychiatric disorders, symptoms and behavioural traits. To our knowledge, this is the first study to examine genetic influences on treatment-related behaviours. Further work is required to determine whether genetic factors could be used alongside clinical, social and demographic factors to identify at risk groups and inform strategies which target early intervention.

Genetic variation in CADM2 as a link between psychological traits and obesity

CADM2 has been associated with a range of behavioural and metabolic traits, including physical activity, risk-taking, educational attainment, alcohol and cannabis use and obesity. Here, we set out to determine whether CADM2 contributes to mechanisms shared between mental and physical health disorders. We assessed genetic variants in the CADM2 locus for association with phenotypes in the UK Biobank, IMPROVE, PROCARDIS and SCARFSHEEP studies, before performing meta-analyses. A wide range of metabolic phenotypes were meta-analysed. Psychological phenotypes analysed in UK Biobank only were major depressive disorder, generalised anxiety disorder, bipolar disorder, neuroticism, mood instability and risk-taking behaviour. In UK Biobank, four, 88 and 172 genetic variants were significantly (p < 1 × 10⁻⁵) associated with neuroticism, mood instability and risk-taking respectively. In meta-analyses of 4 cohorts, we identified 362, 63 and 11 genetic variants significantly (p < 1 × 10⁻⁵) associated with BMI, SBP and CRP respectively. Genetic effects on BMI, CRP and risk-taking were all positively correlated, and were consistently inversely correlated with genetic effects on SBP, mood instability and neuroticism. Conditional analyses suggested an overlap in the signals for physical and psychological traits. Many significant variants had genotype-specific effects on CADM2 expression levels in adult brain and adipose tissues. CADM2 variants influence a wide range of both psychological and metabolic traits, suggesting common biological mechanisms across phenotypes via regulation of CADM2 expression levels in adipose tissue. Functional studies of CADM2 are required to fully understand mechanisms connecting mental and physical health conditions.

Dispositional negativity, cognition, and anxiety disorders: An integrative translational neuroscience framework

When extreme, anxiety can become debilitating. Anxiety disorders, which often first emerge early in development, are common and challenging to treat, yet the underlying mechanisms have only recently begun to come into focus. Here, we review new insights into the nature and biological bases of dispositional negativity, a fundamental dimension of childhood temperament and adult personality and a prominent risk factor for the development of pediatric and adult anxiety disorders. Converging lines of epidemiological, neurobiological, and mechanistic evidence suggest that dispositional negativity increases the likelihood of psychopathology via specific neurocognitive mechanisms, including attentional biases to threat and deficits in executive control. Collectively, these observations provide an integrative translational framework for understanding the development and maintenance of anxiety disorders in adults and youth and set the stage for developing improved intervention strategies.

Uncovering the Genetic Architecture of Major Depression

There have been several recent studies addressing the genetic architecture of depression. This review serves to take stock of what is known now about the genetics of depression, how it has increased our knowledge and understanding of its mechanisms, and how the information and knowledge can be leveraged to improve the care of people affected. We identify four priorities for how the field of MD genetics research may move forward in future years, namely by increasing the sample sizes available for genome-wide association studies (GWASs), greater inclusion of diverse ancestries and low-income countries, the closer integration of psychiatric genetics with electronic medical records, and the development of the neuroscience toolkit for polygenic disorders.

Identification of novel genome-wide associations for suicidality in UK Biobank, genetic correlation with psychiatric disorders and polygenic association with completed suicide

BACKGROUND

Suicide is a major issue for global public health. Suicidality describes a broad spectrum of thoughts and behaviours, some of which are common in the general population. Although suicide results from a complex interaction of multiple social and psychological factors, predisposition to suicidality is at least partly genetic.

METHODS

Ordinal genome-wide association study of suicidality in the UK Biobank cohort comparing: 'no suicidality' controls (N = 83,557); 'thoughts that life was not worth living' (N = 21,063); 'ever contemplated self-harm' (N = 13,038); 'act of deliberate self-harm in the past' (N = 2498); and 'previous suicide attempt' (N = 2666).

OUTCOMES

We identified three novel genome-wide significant loci for suicidality (on chromosomes nine, 11 and 13) and moderate-to-strong genetic correlations between suicidality and a range of psychiatric disorders, most notably depression (r_g 0·81).

INTERPRETATION

These findings provide new information about genetic variants relating to increased risk of suicidal thoughts and behaviours. Future work should assess the extent to which polygenic risk scores for suicidality, in combination with non-genetic risk factors, may be useful for stratified approaches to suicide prevention at a population level. FUND: UKRI Innovation-HDR-UK Fellowship (MR/S003061/1). MRC Mental Health Data Pathfinder Award (MC_PC_17217). MRC Doctoral Training Programme Studentship at the University of Glasgow (MR/K501335/1). MRC Doctoral Training Programme Studentship at the Universities of Glasgow and Edinburgh. UKRI Innovation Fellowship (MR/R024774/1).

Genome-Wide Association Study of Circadian Rhythmicity in 71,500 UK Biobank Participants and Polygenic Association with Mood Instability

BACKGROUND

Circadian rhythms are fundamental to health and are particularly important for mental wellbeing. Disrupted rhythms of rest and activity are recognised as risk factors for major depressive disorder and bipolar disorder.

METHODS

We conducted a genome-wide association study (GWAS) of low relative amplitude (RA), an objective measure of rest-activity cycles derived from the accelerometer data of 71,500 UK Biobank participants. Polygenic risk scores (PRS) for low RA were used to investigate potential associations with psychiatric phenotypes.

OUTCOMES

Two independent genetic loci were associated with low RA, within genomic regions for Neurofascin (NFASC) and Solute Carrier Family 25 Member 17 (SLC25A17). A secondary GWAS of RA as a continuous measure identified a locus within Meis Homeobox 1 (MEIS1). There were no significant genetic correlations between low RA and any of the psychiatric phenotypes assessed. However, PRS for low RA was significantly associated with mood instability across multiple PRS thresholds (at PRS threshold 0·05: OR = 1·02, 95% CI = 1·01-1·02, p = 9·6 × 10-5), and with major depressive disorder (at PRS threshold 0·1: OR = 1·03, 95% CI = 1·01-1·05, p = 0·025) and neuroticism (at PRS threshold 0·5: Beta = 0·02, 95% CI = 0·007-0·04, p = 0·021).

INTERPRETATION

Overall, our findings contribute new knowledge on the complex genetic architecture of circadian rhythmicity and suggest a putative biological link between disrupted circadian function and mood disorder phenotypes, particularly mood instability, but also major depressive disorder and neuroticism.

FUNDING

Medical Research Council (MR/K501335/1).