Joey Ward

Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci

Neuroticism is a personality trait of fundamental importance for psychological well-being and public health. It is strongly associated with major depressive disorder (MDD) and several other psychiatric conditions. Although neuroticism is heritable, attempts to identify the alleles involved in previous studies have been limited by relatively small sample sizes. Here we report a combined meta-analysis of genome-wide association study (GWAS) of neuroticism that includes 91 370 participants from the UK Biobank cohort, 6659 participants from the Generation Scotland: Scottish Family Health Study (GS:SFHS) and 8687 participants from a QIMR (Queensland Institute of Medical Research) Berghofer Medical Research Institute (QIMR) cohort. All participants were assessed using the same neuroticism instrument, the Eysenck Personality Questionnaire-Revised (EPQ-R-S) Short Form’s Neuroticism scale. We found a single-nucleotide polymorphism-based heritability estimate for neuroticism of ∼15% (s.e.=0.7%). Meta-analysis identified nine novel loci associated with neuroticism. The strongest evidence for association was at a locus on chromosome 8 (P=1.5 × 10−15) spanning 4 Mb and containing at least 36 genes. Other associated loci included interesting candidate genes on chromosome 1 (GRIK3 (glutamate receptor ionotropic kainate 3)), chromosome 4 (KLHL2 (Kelch-like protein 2)), chromosome 17 (CRHR1 (corticotropin-releasing hormone receptor 1) and MAPT (microtubule-associated protein Tau)) and on chromosome 18 (CELF4 (CUGBP elav-like family member 4)). We found no evidence for genetic differences in the common allelic architecture of neuroticism by sex. By comparing our findings with those of the Psychiatric Genetics Consortia, we identified a strong genetic correlation between neuroticism and MDD and a less strong but significant genetic correlation with schizophrenia, although not with bipolar disorder. Polygenic risk scores derived from the primary UK Biobank sample captured ∼1% of the variance in neuroticism in the GS:SFHS and QIMR samples, although most of the genome-wide significant alleles identified within a UK Biobank-only GWAS of neuroticism were not independently replicated within these cohorts. The identification of nine novel neuroticism-associated loci will drive forward future work on the neurobiology of neuroticism and related phenotypes.

Prevalence and correlates of cognitive impairment in euthymic adults with bipolar disorder: A systematic review

BACKGROUND Previous reviews have identified medium-large group differences in cognitive performance in adults with bipolar disorder (BD) compared to healthy peers, but the proportion with clinically relevant cognitive impairment has not yet been established. This review aimed to quantify the prevalence of cognitive impairment in euthymic adults with BD, and to describe sociodemographic, clinical and other factors that are significantly associated with cognitive impairment. METHODS Systematic literature review. The population was euthymic community-dwelling adults with BD, aged 18-70 years, and recruited consecutively or randomly. The outcome was cognitive impairment, relative to healthy population norms. Electronic databases and reference lists of relevant articles were searched, and authors were contacted. Original cross-sectional studies published in peer-reviewed English-language journals from January 1994 to February 2015 were included. Methodological bias and reporting bias were assessed using standard tools. A narrative synthesis is presented together with tables and forest plots. RESULTS Thirty articles were included, of which 15 contributed prevalence data. At the 5th percentile impairment threshold, prevalence ranges were: executive function 5.3-57.7%; attention/working memory 9.6-51.9%; speed/reaction time 23.3-44.2%; verbal memory 8.2-42.1%; visual memory 11.5-32.9%. More severe or longstanding illness and antipsychotic medication were associated with greater cognitive impairment. LIMITATIONS The synthesis was limited by heterogeneity in cognitive measures and impairment thresholds, precluding meta-analysis. CONCLUSIONS Cognitive impairment affects a substantial proportion of euthymic adults with BD. Future research with more consistent measurement and reporting will facilitate an improved understanding of cognitive impairment burden in BD.

Cannabis use and risk of schizophrenia: a Mendelian randomization study.

Cannabis use is observationally associated with an increased risk of schizophrenia, but whether the relationship is causal is not known. Using a genetic approach, we took 10 independent genetic variants previously identified to associate with cannabis use in 32 330 individuals to determine the nature of the association between cannabis use and risk of schizophrenia. Genetic variants were employed as instruments to recapitulate a randomized controlled trial involving two groups (cannabis users vs nonusers) to estimate the causal effect of cannabis use on risk of schizophrenia in 34 241 cases and 45 604 controls from predominantly European descent. Genetically-derived estimates were compared with a meta-analysis of observational studies reporting ever use of cannabis and risk of schizophrenia or related disorders. Based on the genetic approach, use of cannabis was associated with increased risk of schizophrenia (odds ratio (OR) of schizophrenia for users vs nonusers of cannabis: 1.37; 95% confidence interval (CI), 1.09–1.67; P-value=0.007). The corresponding estimate from observational analysis was 1.43 (95% CI, 1.19–1.67; P-value for heterogeneity =0.76). The genetic markers did not show evidence of pleiotropic effects and accounting for tobacco exposure did not alter the association (OR of schizophrenia for users vs nonusers of cannabis, adjusted for ever vs never smoker: 1.41; 95% CI, 1.09–1.83). This adds to the substantial evidence base that has previously identified cannabis use to associate with increased risk of schizophrenia, by suggesting that the relationship is causal. Such robust evidence may inform public health messages about cannabis use, especially regarding its potential mental health consequences.

Association of Body Mass Index With Cardiometabolic Disease in the UK Biobank: A Mendelian Randomization Study

Importance Higher body mass index (BMI) is a risk factor for cardiometabolic disease; however, the underlying causal associations remain unclear. Objectives To use UK Biobank data to report causal estimates of the association between BMI and cardiometabolic disease outcomes and traits, such as pulse rate, using mendelian randomization. Design, Setting, and Participants Cross-sectional baseline data from a population-based cohort study including 119 859 UK Biobank participants with complete phenotypic (medical and sociodemographic) and genetic data. Participants attended 1 of 22 assessment centers across the United Kingdom between 2006 and 2010. The present study was conducted from May 1 to July 11, 2016. Main Outcomes and Measures Prevalence of hypertension, coronary heart disease, and type 2 diabetes were determined at assessment, based on self-report. Blood pressure was measured clinically. Participants self-reported sociodemographic information pertaining to relevant confounders. A polygenic risk score comprising 93 single-nucleotide polymorphisms associated with BMI from previous genome-wide association studies was constructed, and the genetic risk score was applied to derive causal estimates using a mendelian randomization approach. Results Of the 119 859 individuals included in the study, 56 816 (47.4%) were men; mean (SD) age was 56.87 (7.93) years. Mendelian randomization analysis showed significant positive associations between genetically instrumented higher BMI and risk of hypertension (odds ratio [OR] per 1-SD higher BMI, 1.64; 95% CI, 1.48-1.83; P = 1.1 × 10−19), coronary heart disease (OR, 1.35; 95% CI, 1.09-1.69; P = .007) and type 2 diabetes (OR, 2.53; 95% CI, 2.04-3.13; P = 1.5 × 10−17), as well as systolic blood pressure (&bgr; = 1.65 mm Hg; 95% CI, 0.78-2.52 mm Hg; P = 2.0 × 10−04) and diastolic blood pressure (&bgr;  = 1.37 mm Hg; 95% CI, 0.88-1.85 mm Hg; P = 3.6 × 10−08). These associations were independent of age, sex, Townsend deprivation scores, alcohol intake, and smoking history. Conclusions and Relevance The results of this study add to the burgeoning evidence of an association between higher BMI and increased risk of cardiometabolic diseases. This finding has relevance for public health policies in many countries with increasing obesity levels.

Erratum: Genome-wide analysis of over 106 000 individuals identifies 9 neuroticism-associated loci

Correction to: Molecular Psychiatry 21, 749–757; doi:10.1038/mp.2016.49 The GWAS of neuroticism conducted within the Queensland Institute of Medical Research (QIMR) Berghofer Medical Research Institute cohort did not include covariates of age, sex, genotyping batch and 10 principal components. Adding these covariates does not substantially change the pattern of results within the meta-analysis, but P-values for the nine reported loci have changed slightly (please see revised Figure 2, Table 2A and Table 2B).

Association of disrupted circadian rhythmicity with mood disorders, subjective wellbeing, and cognitive function: a cross-sectional study of 91 105 participants from the UK Biobank

BACKGROUND Disruption of sleep and circadian rhythmicity is a core feature of mood disorders and might be associated with increased susceptibility to such disorders. Previous studies in this area have used subjective reports of activity and sleep patterns, but the availability of accelerometer-based data from UK Biobank participants permits the derivation and analysis of new, objectively ascertained circadian rhythmicity parameters. We examined associations between objectively assessed circadian rhythmicity and mental health and wellbeing phenotypes, including lifetime history of mood disorder. METHODS UK residents aged 37-73 years were recruited into the UK Biobank general population cohort from 2006 to 2010. We used data from a subset of participants whose activity levels were recorded by wearing a wrist-worn accelerometer for 7 days. From these data, we derived a circadian relative amplitude variable, which is a measure of the extent to which circadian rhythmicity of rest-activity cycles is disrupted. In the same sample, we examined cross-sectional associations between low relative amplitude and mood disorder, wellbeing, and cognitive variables using a series of regression models. Our final model adjusted for age and season at the time that accelerometry started, sex, ethnic origin, Townsend deprivation score, smoking status, alcohol intake, educational attainment, overall mean acceleration recorded by accelerometry, body-mass index, and a binary measure of childhood trauma. FINDINGS We included 91 105 participants with accelerometery data collected between 2013 and 2015 in our analyses. A one-quintile reduction in relative amplitude was associated with increased risk of lifetime major depressive disorder (odds ratio [OR] 1·06, 95% CI 1·04-1·08) and lifetime bipolar disorder (1·11, 1·03-1·20), as well as with greater mood instability (1·02, 1·01-1·04), higher neuroticism scores (incident rate ratio 1·01, 1·01-1·02), more subjective loneliness (OR 1·09, 1·07-1·11), lower happiness (0·91, 0·90-0·93), lower health satisfaction (0·90, 0·89-0·91), and slower reaction times (linear regression coefficient 1·75, 1·05-2·45). These associations were independent of demographic, lifestyle, education, and overall activity confounders. INTERPRETATION Circadian disruption is reliably associated with various adverse mental health and wellbeing outcomes, including major depressive disorder and bipolar disorder. Lower relative amplitude might be linked to increased susceptibility to mood disorders. FUNDING Lister Institute of Preventive Medicine.

Sleep characteristics modify the association of genetic predisposition with obesity and anthropometric measurements in 119,679 UK Biobank participants.

Background: Obesity is a multifactorial condition influenced by genetics, lifestyle, and environment.Objective: We investigated whether the association of a validated genetic profile risk score for obesity (GPRS-obesity) with body mass index (BMI) and waist circumference (WC) was modified by sleep characteristics.Design: This study included cross-sectional data from 119,859 white European adults, aged 37-73 y, participating in the UK Biobank. Interactions of GPRS-obesity and sleep characteristics (sleep duration, chronotype, day napping, and shift work) with their effects on BMI and WC were investigated. Results: β Values are expressed as the change in BMI (in kg/m2) or WC per 1-SD increase in GPRS-obesity. The GPRS-obesity was associated with BMI (β: 0.57; 95% CI: 0.55, 0.60; P = 6.3 × 10-207) and WC (1.21 cm; 95% CI: 1.15, 1.28 cm; P = 4.2 × 10-289). There were significant interactions of GPRS-obesity and a variety of sleep characteristics with their relation with BMI (P-interaction < 0.05). In participants who slept <7 or >9 h daily, the effect of GPRS-obesity on BMI was stronger (β: 0.60; 95% CI: 0.54, 0.65 and β: 0.73; 95% CI: 0.49, 0.97, respectively) than in normal-length sleepers (7-9 h; β: 0.52; 95% CI: 0.49, 0.55). A similar pattern was observed for shift workers (β: 0.68; 95% CI: 0.59, 0.77 compared with β: 0.54; 95% CI: 0.51, 0.58 for non-shift workers) and for night-shift workers (β: 0.69; 95% CI: 0.56, 0.82 compared with β: 0.55; 95% CI: 0.51, 0.58 for non-night-shift workers), for those taking naps during the day (β: 0.65; 95% CI: 0.52, 0.78 compared with β: 0.51; 95% CI: 0.48, 0.55 for those who never or rarely had naps), and for those with a self-reported evening chronotype (β: 0.72; 95% CI: 0.61, 0.82 compared with β: 0.52; 95% CI: 0.47, 0.57 for morning chronotype). Similar findings were obtained by using WC as the outcome.Conclusion: This study shows that the association between genetic risk for obesity and phenotypic adiposity measures is exacerbated by adverse sleeping characteristics.

Genome-wide analysis of self-reported risk-taking behaviour and cross-disorder genetic correlations in the UK Biobank cohort

Risk-taking behaviour is a key component of several psychiatric disorders and could influence lifestyle choices such as smoking, alcohol use, and diet. As a phenotype, risk-taking behaviour therefore fits within a Research Domain Criteria (RDoC) approach, whereby identifying genetic determinants of this trait has the potential to improve our understanding across different psychiatric disorders. Here we report a genome-wide association study in 116,255 UK Biobank participants who responded yes/no to the question “Would you consider yourself a risk taker?” Risk takers (compared with controls) were more likely to be men, smokers, and have a history of psychiatric disorder. Genetic loci associated with risk-taking behaviour were identified on chromosomes 3 (rs13084531) and 6 (rs9379971). The effects of both lead SNPs were comparable between men and women. The chromosome 3 locus highlights CADM2, previously implicated in cognitive and executive functions, but the chromosome 6 locus is challenging to interpret due to the complexity of the HLA region. Risk-taking behaviour shared significant genetic risk with schizophrenia, bipolar disorder, attention-deficit hyperactivity disorder, and post-traumatic stress disorder, as well as with smoking and total obesity. Despite being based on only a single question, this study furthers our understanding of the biology of risk-taking behaviour, a trait that has a major impact on a range of common physical and mental health disorders.

Adverse metabolic and mental health outcomes associated with shiftwork in a population-based study of 277,168 workers in UK biobank*

Abstract Background: Reported associations between shiftwork and health have largely been based on occupation-specific, or single sex studies that might not be generalizable to the entire working population. The objective of this study was to investigate whether shiftwork was independently associated with obesity, diabetes, poor sleep, and well-being in a large, UK general population cohort. Methods: Participants of the UK Biobank study who were employed at the time of assessment were included. Exposure variables were self-reported shiftwork (any shiftwork and night shiftwork); and outcomes were objectively measured obesity, inflammation and physical activity and self-reported lifestyle, sleep and well-being variables, including mental health. Results: Shiftwork was reported by 17% of the 277,168 employed participants. Shiftworkers were more likely to be male, socioeconomically deprived and smokers, and to have higher levels of physical activity. Univariately, and following adjustment for lifestyle and work-related confounders, shiftworkers were more likely to be obese, depressed, to report disturbed sleep, and to have neurotic traits. Conclusions: Shiftwork was independently associated with multiple indicators of poor health and wellbeing, despite higher physical activity, and even in shiftworkers that did not work nights. Shiftwork is an emerging social factor that contributes to disease in the urban environment across the working population. Key messages Studies have linked shiftwork to obesity and diabetes in nurses and industry workers, but little is known about the implications of shiftwork for the general workforce In this large cross sectional study of UK workers, shiftwork was associated with obesity, depression and sleep disturbance, despite higher levels of physical activity. Shiftwork was associated with multiple indicators of compromised health and wellbeing and were more likely to report neurotic traits and evening preference

Seasonality of depressive symptoms in women but not in men: a cross-sectional study in the UK Biobank cohort

BACKGROUND We examined whether seasonal variations in depressive symptoms occurred independently of demographic and lifestyle factors, and were related to change in day length and/or outdoor temperature. METHODS In a cross-sectional analysis of >150,000 participants of the UK Biobank cohort, we used the cosinor method to assess evidence of seasonality of a total depressive symptoms score and of low mood, anhedonia, tenseness and tiredness scores in women and men. Associations of depressive symptoms with day length and mean outdoor temperature were then examined. RESULTS Seasonality of total depressive symptom scores, anhedonia and tiredness scores was observed in women but not men, with peaks in winter. In women, increased day length was associated with reduced reporting of low mood and anhedonia, but with increased reporting of tiredness, independent of demographic and lifestyle factors. Associations with day length were not independent of the average outdoor temperature preceding assessment. LIMITATIONS This was a cross-sectional investigation - longitudinal studies of within-subject seasonal variation in mood are necessary. Outcome measures relied on self-report and measured only a subset of depressive symptoms. CONCLUSION This large, population-based study provides evidence of seasonal variation in depressive symptoms in women. Shorter days were associated with increased feelings of low mood and anhedonia in women. Clinicians should be aware of these population-level sex differences in seasonal mood variations in order to aid recognition and treatment of depression and subclinical depressive symptoms.