Consistent effects of the genetics of happiness across the lifespan and ancestries in multiple cohorts.

Happiness is a fundamental human affective trait, but its biological basis is not well understood. Using a novel approach, we construct LDpred-inf polygenic scores of a general happiness measure in 2 cohorts: the Adolescent Brain Cognitive Development (ABCD) cohort (N = 15,924, age range 9.23-11.8 years), the Add Health cohort (N = 9129, age range 24.5-34.7) to determine associations with several well-being and happiness measures. Additionally, we investigated associations between genetic scores for happiness and brain structure in ABCD (N = 9626, age range (8.9-11) and UK Biobank (N = 16,957, age range 45-83). We detected significant (p.FDR < 0.05) associations between higher genetic scores vs. several well-being measures (best r2 = 0.019) in children of multiple ancestries in ABCD and small yet significant correlations with a happiness measure in European participants in Add Health (r2 = 0.004). Additionally, we show significant associations between lower genetic scores for happiness with smaller structural brain phenotypes in a white British subsample of UK Biobank and a white sub-sample group of ABCD. We demonstrate that the genetic basis for general happiness level appears to have a consistent effect on happiness and wellbeing measures throughout the lifespan, across multiple ancestral backgrounds, and multiple brain structures.

Polygenic risk of major depressive disorder as a risk factor for venous thromboembolism.

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are associated with an increased risk of cardiovascular diseases, including venous thromboembolism (VTE). The reasons for this are complex and include obesity, smoking, and use of hormones and psychotropic medications. Genetic studies have increasingly provided evidence of the shared genetic risk of psychiatric and cardiometabolic illnesses. This study aimed to determine whether a genetic predisposition to MDD, BD, or SCZ is associated with an increased risk of VTE. Genetic correlations using the largest genome-wide genetic meta-analyses summary statistics for MDD, BD, and SCZ (Psychiatric Genetics Consortium) and a recent genome-wide genetic meta-analysis of VTE (INVENT Consortium) demonstrated a positive association between VTE and MDD but not BD or SCZ. The same summary statistics were used to construct polygenic risk scores for MDD, BD, and SCZ in UK Biobank participants of self-reported White British ancestry. These were assessed for impact on self-reported VTE risk (10 786 cases, 285 124 controls), using logistic regression, in sex-specific and sex-combined analyses. We identified significant positive associations between polygenic risk for MDD and the risk of VTE in men, women, and sex-combined analyses, independent of the known risk factors. Secondary analyses demonstrated that this association was not driven by those with lifetime experience of mental illness. Meta-analyses of individual data from 6 additional independent cohorts replicated the sex-combined association. This report provides evidence for shared biological mechanisms leading to MDD and VTE and suggests that, in the absence of genetic data, a family history of MDD might be considered when assessing the risk of VTE.

Testing for associations between HbA1c levels, polygenic risk and brain health in UK Biobank (N = 39 283).

AIM: To investigate whether continuous HbA1c levels and HbA1c-polygenic risk scores (HbA1c-PRS) are significantly associated with worse brain health independent of type 2 diabetes (T2D) diagnosis (vs. not), by examining brain structure and cognitive test score phenotypes. METHODS: Using UK Biobank data (n = 39 283), we tested whether HbA1c levels and/or HbA1c-PRS were associated with cognitive test scores and brain imaging phenotypes. We adjusted for confounders of age, sex, Townsend deprivation score, level of education, genotyping chip, eight genetic principal components, smoking, alcohol intake frequency, cholesterol medication, body mass index, T2D and apolipoprotein (APOE) e4 dosage. RESULTS: We found an association between higher HbA1c levels and poorer performance on symbol digit substitution scores (standardized beta [ß] = -0.022, P = .001) in the fully adjusted model. We also found an association between higher HbA1c levels and worse brain MRI phenotypes of grey matter (GM; fully-adjusted ß = -0.026, P < .001), whole brain volume (ß = -0.072, P = .0113) and a general factor of frontal lobe GM (ß = -0.022, P < .001) in partially and fully adjusted models. HbA1c-PRS were significantly associated with GM volume in the fully adjusted model (ß = -0.010, P = .0113); however, when adjusted for HbA1c levels, the association was not significant. CONCLUSIONS: Our findings suggest that measured HbA1c is associated with poorer cognitive health, and that HbA1c-PRS do not add significant information to this.

Genetic architecture of DCC and influence on psychological, psychiatric and cardiometabolic traits in multiple ancestry groups in UK Biobank.

BACKGROUND: People with severe mental illness have a higher risk of cardiometabolic disease than the general population. Traditionally attributed to sociodemographic, behavioural factors and medication effects, recent genetic studies have provided evidence of shared biological mechanisms underlying mental illness and cardiometabolic disease. We aimed to determine whether signals in the DCC locus, implicated in psychiatric and cardiometabolic traits, were shared or distinct. METHODS: In UK Biobank, we systematically assessed genetic variation in the DCC locus for association with metabolic, cardiovascular and psychiatric-related traits in unrelated "white British" participants (N = 402,837). Logistic or linear regression were applied assuming an additive genetic model and adjusting for age, sex, genotyping chip and population structure. Bonferroni correction for the number of independent variants was applied. Conditional analyses (including lead variants as covariates) and trans-ancestry analyses were used to investigate linkage disequilibrium between signals. RESULTS: Significant associations were observed between DCC variants and smoking, anhedonia, body mass index (BMI), neuroticism and mood instability. Conditional analyses and linkage disequilibrium structure suggested signals for smoking and BMI were distinct from each other and the mood traits, whilst individual mood traits were inter-related in a complex manner. LIMITATIONS: Restricting analyses in non-"white British" individuals to the phenotypes significant in the "white British" sample is not ideal, but the smaller samples sizes restricted the phenotypes possible to analyse. CONCLUSIONS: Genetic variation in the DCC locus had distinct effects on BMI, smoking and mood traits, and therefore is unlikely to contribute to shared mechanisms underpinning mental and cardiometabolic traits.

Subjective and objective sleep and circadian parameters as predictors of depression-related outcomes: A machine learning approach in UK Biobank.

BACKGROUND: Sleep and circadian disruption are associated with depression onset and severity, but it is unclear which features (e.g., sleep duration, chronotype) are important and whether they can identify individuals showing poorer outcomes. METHODS: Within a subset of the UK Biobank with actigraphy and mental health data (n = 64,353), penalised regression identified the most useful of 51 sleep/rest-activity predictors of depression-related outcomes; including case-control (Major Depression (MD) vs. controls; postnatal depression vs. controls) and within-case comparisons (severe vs. moderate MD; early vs. later onset, atypical vs. typical symptoms; comorbid anxiety; suicidality). Best models (of lasso, ridge, and elastic net) were selected based on Area Under the Curve (AUC). RESULTS: For MD vs. controls (n(MD) = 24,229; n(control) = 40,124), lasso AUC was 0.68, 95 % confidence interval (CI) 0.67-0.69. Discrimination was reasonable for atypical vs. typical symptoms (n(atypical) = 958; n(typical) = 18,722; ridge: AUC 0.74, 95 % CI 0.71-0.77) but poor for remaining models (AUCs 0.59-0.67). Key predictors across most models included: difficulty getting up, insomnia symptoms, snoring, actigraphy-measured daytime inactivity and lower morning activity (~8 am). In a distinct subset (n = 310,718), the number of these factors shown was associated with all depression outcomes. LIMITATIONS: Analyses were cross-sectional and in middle-/older aged adults: comparison with longitudinal investigations and younger cohorts is necessary. DISCUSSION: Sleep and circadian measures alone provided poor to moderate discrimination of depression outcomes, but several characteristics were identified that may be clinically useful. Future work should assess these features alongside broader sociodemographic, lifestyle and genetic features.

Cognitive Function in People With Familial Risk of Depression.

Importance: Cognitive impairment in depression is poorly understood. Family history of depression is a potentially useful risk marker for cognitive impairment, facilitating early identification and targeted intervention in those at highest risk, even if they do not themselves have depression. Several research cohorts have emerged recently that enable findings to be compared according to varying depths of family history phenotyping, in some cases also with genetic data, across the life span. Objective: To investigate associations between familial risk of depression and cognitive performance in 4 independent cohorts with varied depth of assessment, using both family history and genetic risk measures. Design, Setting, and Participants: This study used data from the Three Generations at High and Low Risk of Depression Followed Longitudinally (TGS) family study (data collected from 1982 to 2015) and 3 large population cohorts, including the Adolescent Brain Cognitive Development (ABCD) study (data collected from 2016 to 2021), National Longitudinal Study of Adolescent to Adult Health (Add Health; data collected from 1994 to 2018), and UK Biobank (data collected from 2006 to 2022). Children and adults with or without familial risk of depression were included. Cross-sectional analyses were conducted from March to June 2022. Exposures: Family history (across 1 or 2 prior generations) and polygenic risk of depression. Main Outcomes and Measures: Neurocognitive tests at follow-up. Regression models were adjusted for confounders and corrected for multiple comparisons. Results: A total of 57 308 participants were studied, including 87 from TGS (42 [48%] female; mean [SD] age, 19.7 [6.6] years), 10 258 from ABCD (4899 [48%] female; mean [SD] age, 12.0 [0.7] years), 1064 from Add Health (584 [49%] female; mean [SD] age, 37.8 [1.9] years), and 45 899 from UK Biobank (23 605 [51%] female; mean [SD] age, 64.0 [7.7] years). In the younger cohorts (TGS, ABCD, and Add Health), family history of depression was primarily associated with lower performance in the memory domain, and there were indications that this may be partly associated with educational and socioeconomic factors. In the older UK Biobank cohort, there were associations with processing speed, attention, and executive function, with little evidence of education or socioeconomic influences. These associations were evident even in participants who had never been depressed themselves. Effect sizes between familial risk of depression and neurocognitive test performance were largest in TGS; the largest standardized mean differences in primary analyses were -0.55 (95% CI, -1.49 to 0.38) in TGS, -0.09 (95% CI, -0.15 to -0.03) in ABCD, -0.16 (95% CI, -0.31 to -0.01) in Add Health, and -0.10 (95% CI, -0.13 to -0.06) in UK Biobank. Results were generally similar in the polygenic risk score analyses. In UK Biobank, several tasks showed statistically significant associations in the polygenic risk score analysis that were not evident in the family history models. Conclusions and Relevance: In this study, whether assessed by family history or genetic data, depression in prior generations was associated with lower cognitive performance in offspring. There are opportunities to generate hypotheses about how this arises through genetic and environmental determinants, moderators of brain development and brain aging, and potentially modifiable social and lifestyle factors across the life span.

Investigating the potential impact of PCSK9-inhibitors on mood disorders using eQTL-based Mendelian randomization.

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.

Associations between three diet quality indices, genetic risk and body composition: A prospective cohort study.

BACKGROUND & AIMS: Diet and genetic predisposition to adiposity are independent predictors of body composition, yet few cohort studies have examined the association between overall diet quality indices, genetic risk and body composition. This study examined the prospective association of three diet quality indices and a polygenic risk score (PRS) with trunk fat mass, total fat mass, lean mass and bone mineral content. METHODS: Adults from UK Biobank cohort were included. Dietary intake was assessed using the Oxford WebQ and three diet quality indices calculated: Recommended Food Score (RFS); Mediterranean Diet Score (MDS); Healthy Diet Indicator (HDI). Bioimpedance data were available for trunk fat, total fat and lean mass (kg). Trunk fat mass (kg), total fat mass (kg) and lean mass (kg) were assessed using bioelectrical impedance (BIA) in 17,478 adults. Bone mineral content (g) was available from dual energy x-ray absorptiometry (DXA) scans in 11,887 participants. Linear regression analyses, adjusted for demographic and lifestyle confounders, were used to estimate prospective associations between each diet quality index and body composition outcomes. A PRS created from 97 adiposity-related single nucleotide polymorphisms was used to examine interaction effects. RESULTS: A total of 17,478 adults (M = 55.9, SD 7.5 years) were followed up for up to 10 years. RFS, HDI and MDS were inversely associated with trunk fat (RFS: B -0.29; 95% CI: -0.33, -0.25; HDI: -0.23; -0.27, -0.19; MDS: -0.22; -0.26, -0.18), total fat (RFS: B -0.49; 95% CI: -0.56, -0.42; HDI: -0.38; -0.45, -0.32; MDS: -0.38; -0.44, -0.32) and lean (RFS: B -0.10; 95% CI: -0.14, -0.06; HDI: -0.07; -0.11, -0.03; MDS: -0.07; -0.11, -0.04) mass. Diet quality was positively associated with bone mineral content (RFS: B 8.23; 95% CI: 2.14, 14.3; HDI: 6.77; 1.00, 12.5). There was evidence of non-linear associations between diet quality (RFS and HDI only) and trunk fat (p < 0.01) and total fat mass (p < 0.05). There was limited evidence PRS was associated with body composition, with interaction effects of PRS and HDI (p-interaction = 0.039) and MDS (p-interaction = 0.031) on total fat mass. CONCLUSION: Higher diet quality was associated with lower trunk fat, total fat and lean mass, regardless of the diet quality index examined (RFS, HDI or MDS), while higher diet quality (RFS and HDI only) was associated with higher bone mineral content. The benefit of higher diet quality on reducing total fat mass was most evident in individuals with higher generic risk of adiposity. These findings underscore the importance of a high-quality diet for maintaining optimal body composition, particularly in individuals with genetic pre-disposition to adiposity.

Quantifying bias in psychological and physical health in the UK Biobank imaging sub-sample.

UK Biobank is a prospective cohort study of around half-a-million general population participants, recruited between 2006 and 2010, with baseline studies at recruitment and multiple assessments since. From 2014 to date, magnetic resonance imaging (MRI) has been pursued in a participant sub-sample, with the aim to scan around n = 100k. This sub-sample is studied widely and therefore understanding its relative characteristics is important for future reports. We aimed to quantify psychological and physical health in the UK Biobank imaging sub-sample, compared with the rest of the cohort. We used t-tests and χ2 for continuous/categorical variables, respectively, to estimate average differences on a range of cognitive, mental and physical health phenotypes. We contrasted baseline values of participants who attended imaging (versus had not), and compared their values at the imaging visit versus baseline values of participants who were not scanned. We also tested the hypothesis that the associations of established risk factors with worse cognition would be underestimated in the (hypothesized) healthier imaging group compared with the full cohort. We tested these interactions using linear regression models. On a range of cognitive, mental health, cardiometabolic, inflammatory and neurological phenotypes, we found that 47 920 participants who were scanned by January 2021 showed consistent statistically significant 'healthy' bias compared with the ∼450 000 who were not scanned. These effect sizes were small to moderate based on Cohen's d/Cramer's V metrics (range = 0.02 to -0.21 for Townsend, the largest effect size). We found evidence of interaction, where stratified analysis demonstrated that associations of established cognitive risk factors were smaller in the imaging sub-sample compared with the full cohort. Of the ∼100 000 participants who ultimately will undergo MRI assessment within UK Biobank, the first ∼50 000 showed some 'healthy' bias on a range of metrics at baseline. Those differences largely remained at the subsequent (first) imaging visit, and we provide evidence that testing associations in the imaging sub-sample alone could lead to potential underestimation of exposure/outcome estimates.

Genetic analysis of the PCSK9 locus in psychological, psychiatric, metabolic and cardiovascular traits in UK Biobank.

The association between severe mental illness (SMI) and cardiovascular and metabolic disease (CMD) is poorly understood. PCSK9 is expressed in systems critical to both SMI and CMD and influences lipid homeostasis and brain function. We systematically investigated relationships between genetic variation within the PCSK9 locus and risk for both CMD and SMI. UK Biobank recruited ~500,000 volunteers and assessed a wide range of SMI and CMD phenotypes. We used genetic data from white British ancestry individuals of UK Biobank. Genetic association analyses were conducted in PLINK, with statistical significance defined by the number of independent SNPs. Conditional analyses and linkage disequilibrium assessed the independence of SNPs and the presence of multiple signals. Two genetic risk scores of lipid-lowering alleles were calculated and used as proxies for putative lipid-lowering effects of PCSK9. PCSK9 variants were associated with central adiposity, venous thrombosis embolism, systolic blood pressure, mood instability, and neuroticism (all p < 1.16 × 10-4). No secondary signals were identified. Conditional analyses and high linkage disequilibrium (r2 = 0.98) indicated that mood instability and central obesity may share a genetic signal. Genetic risk scores suggested that the lipid-lowering effects of PCSK9 may be causal for greater mood instability and higher neuroticism. This is the first study to implicate the PCSK9 locus in mood-disorder symptoms and related traits, as well as the shared pathology of SMI and CMD. PCSK9 effects on mood may occur via lipid-lowering mechanisms. Further work is needed to understand whether repurposing PCSK9-targeting therapies might improve SMI symptoms and prevent CMD.

Dietary patterns, genetic risk, and incidence of obesity: Application of reduced rank regression in 11,735 adults from the UK Biobank study.

Few studies have derived dietary patterns based on intake of discretionary foods and beverages and examined associations with genetic risk and obesity. We examined associations between dietary patterns based on discretionary foods, saturated fatty acids (SFA), and fiber, with a polygenetic risk score (PRS) for obesity and risk of overall obesity, central obesity and high body fat (BF) up to 9.7 years later. Data from 11,735 adults from the UK Biobank cohort study were used. Dietary patterns were derived from 24-h dietary assessments using reduced rank regression (response variables: discretionary foods and beverages [%E]; SFA [%E]; fiber density [g/MJ]). Cox proportional hazard models were used to investigate associations between dietary patterns and incident overall obesity, central obesity and high BF, with interactions by PRS. Three dietary patterns (DP) were identified. DP1, correlated positively with discretionary foods and SFA, inversely with fiber, was associated with higher risk of central obesity (hazard ratio: 1.08; 95% confidence interval: 1.02, 1.14). DP2, correlated positively with discretionary foods and fiber, inversely with SFA, was not associated with obesity incidence. DP3, correlated positively with SFA and fiber, inversely with discretionary foods, was associated with lower risk of central obesity (hazard ratio: 0.92; 95% confidence interval: 0.87, 0.98). There was limited evidence of interactions with PRS. A dietary pattern high in high-SFA and low-fiber discretionary foods and beverages was associated with higher risk of obesity, independent of genetic predisposition.

Prediabetes blunts DPP4 genetic control of postprandial glycaemia and insulin secretion.

AIMS/HYPOTHESIS: Imbalances in glucose metabolism are hallmarks of clinically silent prediabetes (defined as impaired fasting glucose and/or impaired glucose tolerance) representing dysmetabolism trajectories leading to type 2 diabetes. CD26/dipeptidyl peptidase 4 (DPP4) is a clinically proven molecular target of diabetes-controlling drugs but the DPP4 gene control of dysglycaemia is not proven. METHODS: We dissected the genetic control of post-OGTT and insulin release responses by the DPP4 gene in a Portuguese population-based cohort of mainly European ancestry that comprised individuals with normoglycaemia and prediabetes, and in mouse experimental models of Dpp4 deficiency and hyperenergetic diet. RESULTS: In individuals with normoglycaemia, DPP4 single-nucleotide variants governed glycaemic excursions (rs4664446, p=1.63x10-7) and C-peptide release responses (rs2300757, p=6.86x10-5) upon OGTT. Association with blood glucose levels was stronger at 30 min OGTT, but a higher association with the genetic control of insulin secretion was detected in later phases of the post-OGTT response, suggesting that the DPP4 gene directly senses glucose challenges. Accordingly, in mice fed a normal chow diet but not a high-fat diet, we found that, under OGTT, expression of Dpp4 is strongly downregulated at 30 min in the mouse liver. Strikingly, no genetic association was found in prediabetic individuals, indicating that post-OGTT control by DPP4 is abrogated in prediabetes. Furthermore, Dpp4 KO mice provided concordant evidence that Dpp4 modulates post-OGTT C-peptide release in normoglycaemic but not dysmetabolic states. CONCLUSIONS/INTERPRETATION: These results showed the DPP4 gene as a strong determinant of post-OGTT levels via glucose-sensing mechanisms that are abrogated in prediabetes. We propose that impairments in DPP4 control of post-OGTT insulin responses are part of molecular mechanisms underlying early metabolic disturbances associated with type 2 diabetes.

Association between polygenic risk for Alzheimer's disease, brain structure and cognitive abilities in UK Biobank.

Previous studies testing associations between polygenic risk for late-onset Alzheimer's disease (LOAD-PGR) and brain magnetic resonance imaging (MRI) measures have been limited by small samples and inconsistent consideration of potential confounders. This study investigates whether higher LOAD-PGR is associated with differences in structural brain imaging and cognitive values in a relatively large sample of non-demented, generally healthy adults (UK Biobank). Summary statistics were used to create PGR scores for n = 32,790 participants using LDpred. Outcomes included 12 structural MRI volumes and 6 concurrent cognitive measures. Models were adjusted for age, sex, body mass index, genotyping chip, 8 genetic principal components, lifetime smoking, apolipoprotein (APOE) e4 genotype and socioeconomic deprivation. We tested for statistical interactions between APOE e4 allele dose and LOAD-PGR vs. all outcomes. In fully adjusted models, LOAD-PGR was associated with worse fluid intelligence (standardised beta [ß] = -0.080 per LOAD-PGR standard deviation, p = 0.002), matrix completion (ß = -0.102, p = 0.003), smaller left hippocampal total (ß = -0.118, p = 0.002) and body (ß = -0.069, p = 0.002) volumes, but not other hippocampal subdivisions. There were no significant APOE x LOAD-PGR score interactions for any outcomes in fully adjusted models. This is the largest study to date investigating LOAD-PGR and non-demented structural brain MRI and cognition phenotypes. LOAD-PGR was associated with smaller hippocampal volumes and aspects of cognitive ability in healthy adults and could supplement APOE status in risk stratification of cognitive impairment/LOAD.

Unhealthy Lifestyle, Genetics and Risk of Cardiovascular Disease and Mortality in 76,958 Individuals from the UK Biobank Cohort Study.

To examine associations of unhealthy lifestyle and genetics with risk of all-cause mortality, cardiovascular disease (CVD) mortality, myocardial infarction (MI) and stroke. We used data on 76,958 adults from the UK Biobank prospective cohort study. Favourable lifestyle included no overweight/obesity, not smoking, physical activity, not sedentary, healthy diet and adequate sleep. A Polygenic Risk Score (PRS) was derived using 300 CVD-related single nucleotide polymorphisms. Cox proportional hazard ratios (HR) were used to model effects of lifestyle and PRS on risk of CVD and all-cause mortality, stroke and MI. New CVD (n = 364) and all-cause (n = 2408) deaths, and stroke (n = 748) and MI (n = 1140) events were observed during a 7.8 year mean follow-up. An unfavourable lifestyle (0-1 healthy behaviours) was associated with higher risk of all-cause mortality (HR: 2.06; 95% CI: 1.73, 2.45), CVD mortality (HR: 2.48; 95% CI: 1.64, 3.76), MI (HR: 2.12; 95% CI: 1.65, 2.72) and stroke (HR:1.74; 95% CI: 1.25, 2.43) compared to a favourable lifestyle (≥4 healthy behaviours). PRS was associated with MI (HR: 1.35; 95% CI: 1.27, 1.43). There was evidence of a lifestyle-genetics interaction for stroke (p = 0.017). Unfavourable lifestyle behaviours predicted higher risk of all-cause mortality, CVD mortality, MI and stroke, independent of genetic risk.

Genetic Variation in the ASTN2 Locus in Cardiovascular, Metabolic and Psychiatric Traits: Evidence for Pleiotropy Rather Than Shared Biology.

BACKGROUND: The link between cardiometabolic and psychiatric illness has long been attributed to human behaviour, however recent research highlights shared biological mechanisms. The ASTN2 locus has been previously implicated in psychiatric and cardiometabolic traits, therefore this study aimed to systematically investigate the genetic architecture of ASTN2 in relation to a wide range of relevant traits. METHODS: Baseline questionnaire, assessment and genetic data of 402111 unrelated white British ancestry individuals from the UK Biobank was analysed. Genetic association analyses were conducted using PLINK 1.07, assuming an additive genetic model and adjusting for age, sex, genotyping chip, and population structure. Conditional analyses and linkage disequilibrium assessment were used to determine whether cardiometabolic and psychiatric signals were independent. RESULTS: Associations between genetic variants in the ASTN2 locus and blood pressure, total and central obesity, neuroticism, anhedonia and mood instability were identified. All analyses support the independence of the cardiometabolic traits from the psychiatric traits. In silico analyses provide support for the central obesity signal acting through ASTN2, however most of the other signals are likely acting through other genes in the locus. CONCLUSIONS: Our systematic analysis demonstrates that ASTN2 has pleiotropic effects on cardiometabolic and psychiatric traits, rather than contributing to shared pathology.

Discovery Genome-Wide Association Study of Body Composition in 4,386 Adults From the UK Biobank's Pilot Imaging Enhancement Study.

Body composition (fat, skeletal muscle and bone mass) is an important determinant of overall health and risk of endocrine disorders such as type 2 diabetes and osteoporosis. Although diet and physical activity are strongly implicated, body composition is also heritable. We conducted a discovery genome-wide association study on 31 phenotypes from the three-compartment body composition model (fat, lean and bone mass) in a set of 4 386 individuals (n = 2 109 males, n = 2 294 females) from the UK Biobank pilot imaging enhancement program that underwent a dual energy X-ray absorptiometry (DXA) scan for assessment of body composition and genetic screening. From 6 137 607 imputed single nucleotide polymorphisms (SNPs) we identified 17 body composition loci (P<5.0 x 10-8). GWAS from the combined dataset identified four statistically significant SNPs (rs7592270, rs145972737, rs13212044, rs77772562). In sex-stratified GWAS, 10 male specific SNPs across all traits were identified and five female specific SNPs. Of the 17 SNPs, six were in or close to a gene where there was a plausible functional connection. Three SNPs (rs7592270, rs77772562 and rs7552312) were correlated with obesity phenotypes, one SNP (rs2236705) with lean phenotypes and two with bone mass phenotypes (rs112098641 and rs113380185). These results highlight candidate genes and biological pathways related to body composition, including glucose metabolism and estrogen regulation, that are of interest to replicate in future studies.

Testing for Interactions Between APOE and Klotho Genotypes on Cognitive, Dementia, and Brain Imaging Metrics in UK Biobank.

Recent research suggests genetic variation in the Klotho locus may modify the association between APOE ɛ4 and cognitive impairment. We tested for associations and interactions between these genotypes versus risk of dementia, cognitive abilities, and brain structure in older UK Biobank participants. Klotho status was indexed with rs9536314 heterozygosity (versus not), in unrelated people with versus without APOE ɛ4 genotype, corrected for various confounders. APOE ɛ4 associated with increased risk of dementia, worse cognitive abilities, and brain structure. Klotho was associated with better reasoning. There were no interactions; potentially suggesting an age- and pathology-dependent Klotho effect.

Phenotypic and genetic associations between anhedonia and brain structure in UK Biobank.

Anhedonia is a core symptom of multiple psychiatric disorders and has been associated with alterations in brain structure. Genome-wide association studies suggest that anhedonia is heritable, with a polygenic architecture, but few studies have explored the association between genetic loading for anhedonia-indexed by polygenic risk scores for anhedonia (PRS-anhedonia)-and structural brain imaging phenotypes. Here, we investigated how anhedonia and PRS-anhedonia were associated with brain structure within the UK Biobank cohort. Brain measures (including total grey/white matter volumes, subcortical volumes, cortical thickness (CT) and white matter integrity) were analysed using linear mixed models in relation to anhedonia and PRS-anhedonia in 19,592 participants (9225 males; mean age = 62.6 years, SD = 7.44). We found that state anhedonia was significantly associated with reduced total grey matter volume (GMV); increased total white matter volume (WMV); smaller volumes in thalamus and nucleus accumbens; reduced CT within the paracentral cortex, the opercular part of inferior frontal gyrus, precentral cortex, insula and rostral anterior cingulate cortex; and poorer integrity of many white matter tracts. PRS-anhedonia was associated with reduced total GMV; increased total WMV; reduced white matter integrity; and reduced CT within the parahippocampal cortex, superior temporal gyrus and insula. Overall, both state anhedonia and PRS-anhedonia were associated with individual differences in multiple brain structures, including within reward-related circuits. These associations may represent vulnerability markers for psychopathology relevant to a range of psychiatric disorders.