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

Polygenic Risk for Schizophrenia, Brain Structure, and Environmental Risk in UK Biobank

Schizophrenia is a heritable neurodevelopmental disorder characterized by neuroanatomical changes in the brain but exactly how increased genetic burden for schizophrenia influences brain structure is unknown. Similarly, the impact of environmental risk factors for schizophrenia on brain structure is not fully understood. We investigated how genetic burden for schizophrenia (indexed by a polygenic risk score, PRS-SCZ) was associated with cortical thickness (CT), cortical surface area (SA), cortical volume (CV) and multiple subcortical structures within 18,147 White British ancestry participants from UK Biobank. We also explored whether environmental risk factors for schizophrenia (cannabis use, childhood trauma, low birth weight and Townsend social deprivation index) exacerbated the impact of PRS-SCZ on brain structure. We found that PRS-SCZ was significantly associated with lower CT in the frontal lobe, insula lobe, lateral orbitofrontal cortex, medial orbitofrontal cortex, posterior cingulate cortex and inferior frontal cortex, as well as reduced SA and CV in the supramarginal cortex and superior temporal cortex, but not with differences in subcortical volumes. When models included environmental risk factors as covariates, PRS-SCZ was only associated with lower SA/CV within the supramarginal cortex, superior temporal cortex and inferior frontal cortex. Moreover, no interactions were observed between PRS-SCZ and each of the environmental risk factors on brain structure. Overall, we identified brain structural correlates of PRS-SCZ predominantly within frontal and temporal regions. Some of these associations were independent of environmental risk factors, suggesting that they may represent biomarkers of genetic risk for schizophrenia

The associations between self-reported depression, self-reported chronic inflammatory conditions and cognitive abilities in UK Biobank

Background: Depression and chronic inflammatory medical conditions have been linked to impaired cognitive ability. However despite frequent comorbidity, their combined association with cognitive ability has rarely been examined. Methods: This study examined associations between self-reported depression and chronic inflammatory diseases and their interaction with cognitive performance in 456,748 participants of the UK Biobank, adjusting for sociodemographic and lifestyle factors. Numbers with available data ranged from 94,899 to 453,208 depending on the cognitive test. Results: Self-reported depression was associated with poorer performance compared to controls in several cognitive tests (fully adjusted models, reaction time: B = 6.08, 95% CI = 5.09, 7.07; pairs matching: incidence rate ratio = 1.02, 95% CI = 1.02, 1.03; Trail Making Test B: B = 1.37, 95% CI = 0.88, 1.87; Digit Symbol Substitution Test (DSST): B = −0.35, 95% CI = −0.44, −0.27). Self-reported chronic inflammatory conditions were associated with slower reaction time (B = 3.79, 95% CI = 2.81, 4.78) and lower DSST scores (B = −0.21, 95% CI = −0.30, −0.13). No interaction effects were observed. Discussion: In this large, population-based study we provide evidence of lower cognitive performance in both depression and a comprehensive category of chronic inflammatory conditions. Results are consistent with additive effects of both types of disorder on cognitive ability. Clinicians should be aware of such effects, particularly as cognitive impairment is linked to poorer disease outcomes and quality of life

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

Social engagement after stroke – is it relevant to cognitive function? A cross-sectional analysis of UK Biobank data

Background: Findings from studies in older adult populations suggest that measures of social engagement may be associated with health outcomes, including cognitive function. Plausibly the magnitude and direction of this association may differ in stroke. The disabling nature of stroke increases the likelihood of social isolation and stroke survivors are at high risk of cognitive decline. We assessed the association between social engagement and cognitive function in a sample of stroke survivors. Methods: We included available data from stroke survivors in the UK Biobank (N=8776; age range: 40-72; 57.4% male). In a series of regression models, we assessed cross-sectional associations between proxies of social engagement (frequency of family/friend visits, satisfaction with relationships, loneliness, opportunities to confide in someone, participation in social activities) and performance on domain specific cognitive tasks: reaction time, verbal-numerical reasoning, visual memory and prospective memory. We adjusted for demographics, health-, lifestyle-, and stroke-related factors. Accounting for multiple testing, we set our significance threshold at p<0.003. Results: After adjusting for covariates, we found independent associations between faster reaction times and monthly family visits as compared to no visit (standardised beta=-0.32, 99.7% CI: -0.61 to -0.03, N=4,930); slower reaction times and religious group participation (standardised beta=0.25, 99.7% CI 0.07 to 0.44, N=4,938); and poorer performance on both verbal-numerical reasoning and prospective memory tasks with loneliness (standardised beta=-0.19, 99.7% CI: -0.34 to -0.03, N=2,074; odds ratio=0.66, 99.7% CI: 0.46 to 0.94, N=2,188; respectively). In models where all proxies of social engagement were combined, no associations remained significant. Conclusions: We found limited task-specific associations between cognitive performance and proxies of social engagement, with only loneliness related to two tasks. Further studies are necessary to confirm and improve our understanding of these relationships and investigate the potential to target psychosocial factors to support cognitive function in stroke survivors

Comprehensive Assessment of Sleep Duration, Insomnia and Brain Structure within the UK Biobank Cohort

STUDY OBJECTIVES: To assess for associations between sleeping more than or less than recommended by the National Sleep Foundation (NSF), and self-reported insomnia, with brain structure. METHODS: Data from the UK Biobank cohort were analysed (N between 9K and 32K, dependent on availability, aged 44 to 82 years). Sleep measures included self-reported adherence to NSF guidelines on sleep duration (sleeping between 7 and 9 hours per night), and self-reported difficulty falling or staying asleep (insomnia). Brain structural measures included global and regional cortical or subcortical morphometry (thickness, surface area, volume), global and tract-related white matter microstructure, brain age gap (difference between chronological age and age estimated from brain scan), and total volume of white matter lesions. RESULTS: Longer-than-recommended sleep duration was associated with lower overall grey and white matter volumes, lower global and regional cortical thickness and volume measures, higher brain age gap, higher volume of white matter lesions, higher mean diffusivity globally and in thalamic and association fibers, and lower volume of the hippocampus. Shorter-than-recommended sleep duration was related to higher global and cerebellar white matter volumes, lower global and regional cortical surface areas, and lower fractional anisotropy in projection fibers. Self-reported insomnia was associated with higher global grey and white matter volumes, and with higher volumes of the amygdala, hippocampus and putamen. CONCLUSIONS: Sleeping longer than recommended by the NSF is associated with a wide range of differences in brain structure, potentially indicative of poorer brain health. Sleeping less than recommended is distinctly associated with lower cortical surface areas. Future studies should assess the potential mechanisms of these differences and investigate long sleep duration as a putative marker of brain health

The impact of confounding on the associations of different adiposity measures with the incidence of cardiovascular disease: a cohort study of 296 535 adults of white European descent

Aims: The data regarding the associations of body mass index (BMI) with cardiovascular (CVD) risk, especially for those at the low categories of BMI, are conflicting. The aim of our study was to examine the associations of body composition (assessed by five different measures) with incident CVD outcomes in healthy individuals. Methods and results: A total of 296 535 participants (57.8% women) of white European descent without CVD at baseline from the UK biobank were included. Exposures were five different measures of adiposity. Fatal and non-fatal CVD events were the primary outcome. Low BMI (≤18.5 kg m−2) was associated with higher incidence of CVD and the lowest CVD risk was exhibited at BMI of 22–23 kg m−2 beyond, which the risk of CVD increased. This J-shaped association attenuated substantially in subgroup analyses, when we excluded participants with comorbidities. In contrast, the associations for the remaining adiposity measures were more linear; 1 SD increase in waist circumference was associated with a hazard ratio of 1.16 [95% confidence interval (CI) 1.13–1.19] for women and 1.10 (95% CI 1.08–1.13) for men with similar magnitude of associations for 1 SD increase in waist-to-hip ratio, waist-to-height ratio, and percentage body fat mass. Conclusion: Increasing adiposity has a detrimental association with CVD health in middle-aged men and women. The association of BMI with CVD appears more susceptible to confounding due to pre-existing comorbidities when compared with other adiposity measures. Any public misconception of a potential ‘protective’ effect of fat on CVD risk should be challenged

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

Sleep characteristics modify the association between genetic predisposition to obesity and anthropometric measurements in 119,679 UK Biobank participants

Background - Obesity is a multifactorial condition influenced by genetics, lifestyle and environment. Objective - To investigate whether the association between 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 years, participating on the UK Biobank. Interactions between GPRS-obesity, and sleep characteristics (sleep duration, chronotype, day napping, and shift work) in their effects on BMI and WC were investigated. Results - The GPRS-obesity was associated with BMI (β:0.57 kg.m-2 per standard deviation (SD) increase in GPRS, [95%CI:0.55, 0.60]; P=6.3x10-207) and WC (β:1.21 cm, [1.15, 1.28]; P=4.2x10-289). There were significant interactions between GPRS-obesity and a variety of sleep characteristics in their relationship with BMI (P-interaction <0.05). In participants who slept <7 hrs or >9 hrs daily, the effect of GPRS-obesity on BMI was stronger (β:0.60 [0.54, 0.65] and 0.73 [0.49, 0.97] kg.m-2 per SD increase in GPRS, respectively) than in normal length sleepers (7-9 hours; β:0.52 [0.49, 0.55] kg.m-2 per SD). A similar pattern was observed for shiftworkers (β:0.68 [0.59, 0.77] versus 0.54 [0.51, 0.58] kg.m-2 for non-shiftworkers) and for night-shiftworkers (β:0.69 [0.56, 0.82] versus 0.55 [0.51, 0.58] kg.m-2 for non-night- shiftworkers), for those taking naps during the day (β:0.65 [0.52, 0.78] versus 0.51 [0.48, 0.55] kg.m-2 for those who never/rarely had naps) and for those with a self-reported evening chronotype (β:0.72 [0.61, 0.82] versus β:0.52 [0.47, 0.57] kg.m-2 for morning chronotype). Similar findings were obtained using WC as the outcome. Conclusions – This study shows that the association between genetic risk for obesity and phenotypic adiposity measures is exacerbated by adverse sleeping characteristics