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Chronic pain is highly prevalent worldwide and represents a significant socioeconomic and public health burden. Several aspects of chronic pain, for example back pain and a severity-related phenotype 'chronic pain grade', have been shown previously to be complex heritable traits with a polygenic component. Additional pain-related phenotypes capturing aspects of an individual's overall sensitivity to experiencing and reporting chronic pain have also been suggested as a focus for investigation. We made use of a measure of the number of sites of chronic pain in individuals within the UK general population. This measure, termed Multisite Chronic Pain (MCP), is a complex trait and its genetic architecture has not previously been investigated. To address this, we carried out a large-scale genome-wide association study (GWAS) of MCP in ~380,000 UK Biobank participants. Our findings were consistent with MCP having a significant polygenic component, with a Single Nucleotide Polymorphism (SNP) heritability of 10.2%. In total 76 independent lead SNPs at 39 risk loci were associated with MCP. Additional gene-level association analyses identified neurogenesis, synaptic plasticity, nervous system development, cell-cycle progression and apoptosis genes as enriched for genetic association with MCP. Genetic correlations were observed between MCP and a range of psychiatric, autoimmune and anthropometric traits, including major depressive disorder (MDD), asthma and Body Mass Index (BMI). Furthermore, in Mendelian randomisation (MR) analyses a causal effect of MCP on MDD was observed. Additionally, a polygenic risk score (PRS) for MCP was found to significantly predict chronic widespread pain (pain all over the body), indicating the existence of genetic variants contributing to both of these pain phenotypes. Overall, our findings support the proposition that chronic pain involves a strong nervous system component with implications for our understanding of the physiology of chronic pain. These discoveries may also inform the future development of novel treatment approaches.

UK Biobank is a well-characterised cohort of over 500 000 participants including genetics, environmental data and imaging. An online mental health questionnaire was designed for UK Biobank participants to expand its potential. Describe the development, implementation and results of this questionnaire. An expert working group designed the questionnaire, using established measures where possible, and consulting a patient group. Operational criteria were agreed for defining likely disorder and risk states, including lifetime depression, mania/hypomania, generalised anxiety disorder, unusual experiences and self-harm, and current post-traumatic stress and hazardous/harmful alcohol use. A total of 157 366 completed online questionnaires were available by August 2017. Participants were aged 45-82 (53% were ≥65 years) and 57% women. Comparison of self-reported diagnosed mental disorder with a contemporary study shows a similar prevalence, despite respondents being of higher average socioeconomic status. Lifetime depression was a common finding, with 24% (37 434) of participants meeting criteria and current hazardous/harmful alcohol use criteria were met by 21% (32 602), whereas other criteria were met by less than 8% of the participants. There was extensive comorbidity among the syndromes. Mental disorders were associated with a high neuroticism score, adverse life events and long-term illness; addiction and bipolar affective disorder in particular were associated with measures of deprivation. The UK Biobank questionnaire represents a very large mental health survey in itself, and the results presented here show high face validity, although caution is needed because of selection bias. Built into UK Biobank, these data intersect with other health data to offer unparalleled potential for crosscutting biomedical research involving mental health.

Chronic pain is highly prevalent worldwide and imparts a significant socioeconomic and public health burden. Factors influencing susceptibility to, and mechanisms of, chronic pain development, are not fully understood, but sex is thought to play a significant role, and chronic pain is more prevalent in women than in men. To investigate sex differences in chronic pain, we carried out a sex-stratified genome-wide association study of Multisite Chronic Pain (MCP), a derived chronic pain phenotype, in UK Biobank on 178,556 men and 209,093 women, as well as investigating sex-specific genetic correlations with a range of psychiatric, autoimmune and anthropometric phenotypes and the relationship between sex-specific polygenic risk scores for MCP and chronic widespread pain. We also assessed whether MCP-associated genes showed expression pattern enrichment across tissues. A total of 123 SNPs at five independent loci were significantly associated with MCP in men. In women, a total of 286 genome-wide significant SNPs at ten independent loci were discovered. Meta-analysis of sex-stratified GWAS outputs revealed a further 87 independent associated SNPs. Gene-level analyses revealed sex-specific MCP associations, with 31 genes significantly associated in females, 37 genes associated in males, and a single gene, DCC , associated in both sexes. We found evidence for sex-specific pleiotropy and risk for MCP was found to be associated with chronic widespread pain in a sex-differential manner. Male and female MCP were highly genetically correlated, but at an r g of significantly less than 1 (0.92). All 37 male MCP-associated genes and all but one of 31 female MCP-associated genes were found to be expressed in the dorsal root ganglion, and there was a degree of enrichment for expression in sex-specific tissues. Overall, the findings indicate that sex differences in chronic pain exist at the SNP, gene and transcript abundance level, and highlight possible sex-specific pleiotropy for MCP. Results support the proposition of a strong central nervous-system component to chronic pain in both sexes, additionally highlighting a potential role for the DRG and nociception.

ObjectivesTo examine associations of three diet quality indices and a polygenic risk score with incidence of all-cause mortality, cardiovascular disease (CVD) mortality, myocardial infarction (MI) and stroke.DesignProspective cohort study.SettingUK Biobank, UK.Participants77 004 men and women (40–70 years) recruited between 2006 and 2010.Main outcome measuresA polygenic risk score was created from 300 single nucleotide polymorphisms associated with CVD. Cox proportional HRs were used to estimate independent effects of diet quality and genetic risk on all-cause mortality, CVD mortality, MI and stroke risk. Dietary intake (Oxford WebQ) was used to calculate Recommended Food Score (RFS), Healthy Diet Indicator (HDI) and Mediterranean Diet Score (MDS).ResultsNew all-cause (n=2409) and CVD (n=364) deaths and MI (n=1141) and stroke (n=748) events were identified during mean follow-ups of 7.9 and 7.8 years, respectively. The adjusted HR associated with one-point higher RFS for all-cause mortality was 0.96 (95% CI: 0.94 to 0.98), CVD mortality was 0.94 (95% CI: 0.90 to 0.98), MI was 0.97 (95% CI: 0.95 to 1.00) and stroke was 0.94 (95% CI: 0.91 to 0.98). The adjusted HR for all-cause mortality associated with one-point higher HDI and MDS was 0.97 (95% CI: 0.93 to 0.99) and 0.95 (95% CI: 0.91 to 0.98), respectively. The adjusted HR associated with one-point higher MDS for stroke was 0.93 (95% CI: 0.87 to 1.00). There was little evidence of associations between HDI and risk of CVD mortality, MI or stroke. There was evidence of an interaction between diet quality and genetic risk score for MI.ConclusionHigher diet quality predicted lower risk of all-cause mortality, independent of genetic risk. Higher RFS was also associated with lower risk of CVD mortality and MI. These findings demonstrate the benefit of following a healthy diet, regardless of genetic risk.

Systemic inflammation has been linked with mood disorder and cognitive impairment. The extent of this relationship remains uncertain, with the effects of serum inflammatory biomarkers compared to genetic predisposition toward inflammation yet to be clearly established. We investigated the magnitude of associations between C-reactive protein (CRP) measures, lifetime history of bipolar disorder or major depression, and cognitive function (reaction time and visuospatial memory) in 84,268 UK Biobank participants. CRP was measured in serum and a polygenic risk score for CRP was calculated, based on a published genome-wide association study. Multiple regression models adjusted for sociodemographic and clinical confounders. Increased serum CRP was significantly associated with mood disorder history (Kruskal-Wallis H = 196.06, p < 0.001, η2 = 0.002) but increased polygenic risk for CRP was not (F = 0.668, p = 0.648, η2 < 0.001). Compared to the lowest quintile, the highest serum CRP quintile was significantly associated with both negative and positive differences in cognitive performance (fully adjusted models: reaction time B = -0.030, 95% CI = -0.052, -0.008; visuospatial memory B = 0.066, 95% CI = 0.042, 0.089). More severe mood disorder categories were significantly associated with worse cognitive performance and this was not moderated by serum or genetic CRP level. In this large cohort study, we found that measured inflammation was associated with mood disorder history, but genetic predisposition to inflammation was not. The association between mood disorder and worse cognitive performance was very small and did not vary by CRP level. The inconsistent relationship between CRP measures and cognitive performance warrants further study.

Background Associations of anxiety disorder and depression with coronary artery disease (CAD) are heterogeneous between populations. This study investigated how genetic susceptibility to CAD alters these associations with incident CAD, comparing and combining anxiety disorder and depression. Methods This is a prospective cohort study using UK Biobank. Diagnoses of anxiety disorder and depression were ascertained through linked hospital admission data. Incident CAD was ascertained through hospital admission and death certificate data after baseline. CAD polygenic risk score (PRS CAD ) was obtained from CARDIoGRAMplus4 and categorised into low, intermediate, and high. Cox proportional hazard models were used to examine associations between anxiety disorder and depression and CAD. Results Both anxiety disorder (HR 2.31, 95% CI 1.92–2.78) and depression (HR 2.15, 95% CI 1.90–2.24) were associated with CAD after adjusting for sociodemographic confounders. There was an addictive interaction between depression and PRS CAD (RERI 0.97, 95% CI 0.12–1.81) such that the association between depression and CAD was strongest among those with a high PRS CAD whilst there was no such evidence for anxiety disorder. Anxiety disorder only (HR 1.68, 95% 1.16–2.44), depression only (HR 2.13, 95% CI 1.72–2.64), and concomitant anxiety disorder and depression (HR 3.85, 95% CI 2.48–5.98) were associated with CAD even among people with a low PRS CAD . Adjusting for potential mediators attenuated all these associations across PRS categories. Conclusions CAD genetic susceptibility might partly contribute to the clustering of depression and CAD but does not provide a full explanation, nor does it explain the association between anxiety disorder and CAD. Therefore, other mechanisms should be explored.

Prescription of PCSK9-inhibitors has increased in recent years but not much is known about its off-target effects. PCSK9 -expression is evident in non-hepatic tissues, notably the brain, and genetic variation in the PCSK9 locus has recently been shown to be associated with mood disorder-related traits. We investigated whether PCSK9 inhibition, proxied by a genetic reduction in expression of PCSK9 mRNA, might have a causal adverse effect on mood disorder-related traits. We used genetic variants in the PCSK9 locus associated with reduced PCSK9 expression (eQTLs) in the European population from GTEx v8 and examined the effect on PCSK9 protein levels and three mood disorder-related traits (major depressive disorder, mood instability, and neuroticism), using summary statistics from the largest European ancestry genome-wide association studies. We conducted summary-based Mendelian randomization analyses to estimate the causal effects, and attempted replication using data from eQTLGen, Brain-eMETA, and the CAGE consortium. We found that genetically reduced PCSK9 gene-expression levels were significantly associated with reduced PCSK9 protein levels but not with increased risk of mood disorder-related traits. Further investigation of nearby genes demonstrated that reduced USP24 gene-expression levels was significantly associated with increased risk of mood instability (p-value range = 5.2x10 -5 –0.03), and neuroticism score (p-value range = 2.9x10 -5 –0.02), but not with PCSK9 protein levels. Our results suggest that genetic variation in this region acts on mood disorders through a PCSK9-independent pathway, and therefore PCSK9-inhibitors are unlikely to have an adverse impact on mood disorder-related traits.

There are currently no reliable approaches for correctly identifying which patients with major depressive disorder (MDD) will respond well to antidepressant therapy. However, recent genetic advances suggest that Polygenic Risk Scores (PRS) could allow MDD patients to be stratified for antidepressant response. We used PRS for MDD and PRS for neuroticism as putative predictors of antidepressant response within three treatment cohorts: The Genome-based Therapeutic Drugs for Depression (GENDEP) cohort, and 2 sub-cohorts from the Pharmacogenomics Research Network Antidepressant Medication Pharmacogenomics Study PRGN-AMPS (total patient number = 760). Results across cohorts were combined via meta-analysis within a random effects model. Overall, PRS for MDD and neuroticism did not significantly predict antidepressant response but there was a consistent direction of effect, whereby greater genetic loading for both MDD (best MDD result, p < 5*10-5 MDD-PRS at 4 weeks, β = -0.019, S.E = 0.008, p = 0.01) and neuroticism (best neuroticism result, p < 0.1 neuroticism-PRS at 8 weeks, β = -0.017, S.E = 0.008, p = 0.03) were associated with less favourable response. We conclude that the PRS approach may offer some promise for treatment stratification in MDD and should now be assessed within larger clinical cohorts.

Prescription of PCSK9-inhibitors has increased in recent years but not much is known about its off-target effects. PCSK9-expression is evident in non-hepatic tissues, notably the brain, and genetic variation in the PCSK9 locus has recently been shown to be associated with mood disorder-related traits. We investigated whether PCSK9 inhibition, proxied by a genetic reduction in expression of PCSK9 mRNA, might have a causal adverse effect on mood disorder-related traits. We used genetic variants in the PCSK9 locus associated with reduced PCSK9 expression (eQTLs) in the European population from GTEx v8 and examined the effect on PCSK9 protein levels and three mood disorder-related traits (major depressive disorder, mood instability, and neuroticism), using summary statistics from the largest European ancestry genome-wide association studies. We conducted summary-based Mendelian randomization analyses to estimate the causal effects, and attempted replication using data from eQTLGen, Brain-eMETA, and the CAGE consortium. We found that genetically reduced PCSK9 gene-expression levels were significantly associated with reduced PCSK9 protein levels but not with increased risk of mood disorder-related traits. Further investigation of nearby genes demonstrated that reduced USP24 gene-expression levels was significantly associated with increased risk of mood instability (p-value range = 5.2x10-5-0.03), and neuroticism score (p-value range = 2.9x10-5-0.02), but not with PCSK9 protein levels. Our results suggest that genetic variation in this region acts on mood disorders through a PCSK9-independent pathway, and therefore PCSK9-inhibitors are unlikely to have an adverse impact on mood disorder-related traits.

Background Obesity and central obesity are multifactorial conditions with genetic and non-genetic (lifestyle and environmental) contributions. There is incomplete understanding of whether lifestyle modifies the translation from respective genetic risks into phenotypic obesity and central obesity, and to what extent genetic predisposition to obesity and central obesity is mediated via lifestyle factors. Methods This is a cross-sectional study of 201,466 (out of approximately 502,000) European participants from UK Biobank and tested for interactions and mediation role of lifestyle factors (diet quality; physical activity levels; total energy intake; sleep duration, and smoking and alcohol intake) between genetic risk for obesity and central obesity. BMI-PRS and WHR-PRS are exposures and obesity and central obesity are outcomes. Results Overall, 42.8% of the association between genetic predisposition to obesity and phenotypic obesity was explained by lifestyle: 0.9% by mediation and 41.9% by effect modification. A significant difference between men and women was found in central obesity; the figures were 42.1% (association explained by lifestyle), 1.4% (by mediation), and 40.7% (by modification) in women and 69.6% (association explained by lifestyle), 3.0% (by mediation), and 66.6% (by modification) in men. Conclusions A substantial proportion of the association between genetic predisposition to obesity/central obesity and phenotypic obesity/central obesity was explained by lifestyles. Future studies with repeated measures of obesity and lifestyle would be needed to clarify causation.