Higher adiposity and mental health: causal inference using Mendelian randomization.

Higher adiposity is an established risk factor for psychiatric diseases including depression and anxiety. The associations between adiposity and depression may be explained by the metabolic consequences and/or by the psychosocial impact of higher adiposity. We performed one- and two- sample Mendelian randomization (MR) in up to 145 668 European participants from the UK Biobank to test for a causal effect of higher adiposity on 10 well-validated mental health and well-being outcomes derived using the Mental Health Questionnaire (MHQ). We used three sets of adiposity genetic instruments: (a) a set of 72 BMI genetic variants, (b) a set of 36 favourable adiposity variants and (c) a set of 38 unfavourable adiposity variants. We additionally tested causal relationships (1) in men and women separately, (2) in a subset of individuals not taking antidepressants and (3) in non-linear MR models. Two-sample MR provided evidence that a genetically determined one standard deviation (1-SD) higher BMI (4.6 kg/m2) was associated with higher odds of current depression [OR: 1.50, 95%CI: 1.15, 1.95] and lower well-being [ß: -0.15, 95%CI: -0.26, -0.04]. Findings were similar when using the metabolically favourable and unfavourable adiposity variants, with higher adiposity associated with higher odds of depression and lower well-being scores. Our study provides further evidence that higher BMI causes higher odds of depression and lowers well-being. Using genetics to separate out metabolic and psychosocial effects, our study suggests that in the absence of adverse metabolic effects higher adiposity remains causal to depression and lowers well-being.

Body mass index and inflammation in depression and treatment-resistant depression: a Mendelian randomisation study.

BACKGROUND: Major depressive disorder (MDD) has a significant impact on global burden of disease. Complications in clinical management can occur when response to pharmacological modalities is considered inadequate and symptoms persist (treatment-resistant depression (TRD)). We aim to investigate inflammation, proxied by C-reactive protein (CRP) levels, and body mass index (BMI) as putative causal risk factors for depression and subsequent treatment resistance, leveraging genetic information to avoid confounding via Mendelian randomisation (MR). METHODS: We used the European UK Biobank subcohort ([Formula: see text]), the mental health questionnaire (MHQ) and clinical records. For treatment resistance, a previously curated phenotype based on general practitioner (GP) records and prescription data was employed. We applied univariable and multivariable MR models to genetically predict the exposures and assess their causal contribution to a range of depression outcomes. We used a range of univariable, multivariable and mediation MR models techniques to address our research question with maximum rigour. In addition, we developed a novel statistical procedure to apply pleiotropy-robust multivariable MR to one sample data and employed a Bayesian bootstrap procedure to accurately quantify estimate uncertainty in mediation analysis which outperforms standard approaches in sparse binary outcomes. Given the flexibility of the one-sample design, we evaluated age and sex as moderators of the effects. RESULTS: In univariable MR models, genetically predicted BMI was positively associated with depression outcomes, including MDD ([Formula: see text] ([Formula: see text] CI): 0.133(0.072, 0.205)) and TRD (0.347(0.002, 0.682)), with a larger magnitude in females and with age acting as a moderator of the effect of BMI on severity of depression (0.22(0.050, 0.389)). Multivariable MR analyses suggested an independent causal effect of BMI on TRD not through CRP (0.395(0.004, 0.732)). Our mediation analyses suggested that the effect of CRP on severity of depression was partly mediated by BMI. Individuals with TRD ([Formula: see text]) observationally had higher CRP and BMI compared with individuals with MDD alone and healthy controls. DISCUSSION: Our work supports the assertion that BMI exerts a causal effect on a range of clinical and questionnaire-based depression phenotypes, with the effect being stronger in females and in younger individuals. We show that this effect is independent of inflammation proxied by CRP levels as the effects of CRP do not persist when jointly estimated with BMI. This is consistent with previous evidence suggesting that overweight contributed to depression even in the absence of any metabolic consequences. It appears that BMI exerts an effect on TRD that persists when we account for BMI influencing MDD.

Effects of physical activity and sedentary time on depression, anxiety and well-being: a bidirectional Mendelian randomisation study.

BACKGROUND: Mental health conditions represent one of the major groups of non-transmissible diseases. Physical activity (PA) and sedentary time (ST) have been shown to affect mental health outcomes in opposite directions. In this study, we use accelerometery-derived measures of PA and ST from the UK Biobank (UKB) and depression, anxiety and well-being data from the UKB mental health questionnaire as well as published summary statistics to explore the causal associations between these phenotypes. METHODS: We used MRlap to test if objectively measured PA and ST associate with mental health outcomes using UKB data and summary statistics from published genome-wide association studies. We also tested for bidirectional associations. We performed sex stratified as well as sensitivity analyses. RESULTS: Genetically instrumented higher PA was associated with lower odds of depression (OR = 0.92; 95% CI: 0.88, 0.97) and depression severity (beta = - 0.11; 95% CI: - 0.18, - 0.04), Genetically instrumented higher ST was associated higher odds of anxiety (OR = 2.59; 95% CI: 1.10, 4.60). PA was associated with higher well-being (beta = 0.11, 95% CI: 0.04; 0.18) and ST with lower well-being (beta = - 0.18; 95% CI: - 0.32, - 0.03). Similar findings were observed when stratifying by sex. There was evidence for a bidirectional relationship, with higher genetic liability to depression associated with lower PA (beta = - 0.25, 95% CI: - 0.42; - 0.08) and higher well-being associated with higher PA (beta = 0.15; 95% CI: 0.05, 0.25). CONCLUSIONS: We have demonstrated the bidirectional effects of both PA and ST on a range of mental health outcomes using objectively measured predictors and MR methods for causal inference. Our findings support a causal role for PA and ST in the development of mental health problems and in affecting well-being.

Mendelian randomisation study of body composition and depression in people of East Asian ancestry highlights potential setting-specific causality.

BACKGROUND: Extensive evidence links higher body mass index (BMI) to higher odds of depression in people of European ancestry. However, our understanding of the relationship across different settings and ancestries is limited. Here, we test the relationship between body composition and depression in people of East Asian ancestry. METHODS: Multiple Mendelian randomisation (MR) methods were used to test the relationship between (a) BMI and (b) waist-hip ratio (WHR) with depression. Firstly, we performed two-sample MR using genetic summary statistics from a recent genome-wide association study (GWAS) of depression (with 15,771 cases and 178,777 controls) in people of East Asian ancestry. We selected 838 single nucleotide polymorphisms (SNPs) correlated with BMI and 263 SNPs correlated with WHR as genetic instrumental variables to estimate the causal effect of BMI and WHR on depression using the inverse-variance weighted (IVW) method. We repeated these analyses stratifying by home location status: China versus UK or USA. Secondly, we performed one-sample MR in the China Kadoorie Biobank (CKB) in 100,377 participants. This allowed us to test the relationship separately in (a) males and females and (b) urban and rural dwellers. We also examined (c) the linearity of the BMI-depression relationship. RESULTS: Both MR analyses provided evidence that higher BMI was associated with lower odds of depression. For example, a genetically-instrumented 1-SD higher BMI in the CKB was associated with lower odds of depressive symptoms [OR: 0.77, 95% CI: 0.63, 0.95]. There was evidence of differences according to place of residence. Using the IVW method, higher BMI was associated with lower odds of depression in people of East Asian ancestry living in China but there was no evidence for an association in people of East Asian ancestry living in the USA or UK. Furthermore, higher genetic BMI was associated with differential effects in urban and rural dwellers within China. CONCLUSIONS: This study provides the first MR evidence for an inverse relationship between BMI and depression in people of East Asian ancestry. This contrasts with previous findings in European populations and therefore the public health response to obesity and depression is likely to need to differ based on sociocultural factors for example, ancestry and place of residence. This highlights the importance of setting-specific causality when using genetic causal inference approaches and data from diverse populations to test hypotheses. This is especially important when the relationship tested is not purely biological and may involve sociocultural factors.

Using Mendelian Randomisation methods to understand whether diurnal preference is causally related to mental health.

Late diurnal preference has been linked to poorer mental health outcomes, but the understanding of the causal role of diurnal preference on mental health and wellbeing is currently limited. Late diurnal preference is often associated with circadian misalignment (a mismatch between the timing of the endogenous circadian system and behavioural rhythms), so that evening people live more frequently against their internal clock. This study aims to quantify the causal contribution of diurnal preference on mental health outcomes, including anxiety, depression and general wellbeing and test the hypothesis that more misaligned individuals have poorer mental health and wellbeing using an actigraphy-based measure of circadian misalignment. Multiple Mendelian Randomisation (MR) approaches were used to test causal pathways between diurnal preference and seven well-validated mental health and wellbeing outcomes in up to 451,025 individuals. In addition, observational analyses tested the association between a novel, objective measure of behavioural misalignment (Composite Phase Deviation, CPD) and seven mental health and wellbeing outcomes. Using genetic instruments identified in the largest GWAS for diurnal preference, we provide robust evidence that early diurnal preference is protective for depression and improves wellbeing. For example, using one-sample MR, a twofold higher genetic liability of morningness was associated with lower odds of depressive symptoms (OR: 0.92, 95% CI: 0.88, 0.97). It is possible that behavioural factors including circadian misalignment may contribute in the chronotype depression relationship, but further work is needed to confirm these findings.

The genetics of falling susceptibility and identification of causal risk factors.

Falls represent a huge health and economic burden. Whilst many factors are associated with fall risk (e.g. obesity and physical inactivity) there is limited evidence for the causal role of these risk factors. Here, we used hospital and general practitioner records in UK Biobank, deriving a balance specific fall phenotype in 20,789 cases and 180,658 controls, performed a Genome Wide Association Study (GWAS) and used Mendelian Randomisation (MR) to test causal pathways. GWAS indicated a small but significant SNP-based heritability (4.4%), identifying one variant (rs429358) in APOE at genome-wide significance (P < 5e-8). MR provided evidence for a causal role of higher BMI on higher fall risk even in the absence of adverse metabolic consequences. Depression and neuroticism predicted higher risk of falling, whilst higher hand grip strength and physical activity were protective. Our findings suggest promoting lower BMI, higher physical activity as well as psychological health is likely to reduce falls.

BMI and well-being in people of East Asian and European ancestry: a Mendelian randomisation study.

Previous studies have linked higher body mass index (BMI) to lower subjective well-being in adult European ancestry populations. However, our understanding of these relationships across different populations is limited. Here, we investigated the association between BMI and well-being in people of (a) East Asian and (b) European ancestry in the China Kadoorie Biobank (CKB) and UK Biobank (UKB), respectively. Mendelian randomisation (MR) methods were used to test the relationship between BMI with (a) health satisfaction and (b) life satisfaction. One-sample MR enabled us to test effects in men and women separately and to test the role of cultural contexts by stratifying our analyses by urban and rural home location in both China and the UK. Further, we implemented a control function method to test the linearity of the BMI-well-being relationship. We found evidence of different associations between BMI and well-being in individuals of East Asian versus European ancestry. For example, a genetically instrumented higher BMI tentatively associated with higher health satisfaction in people of East Asian ancestry, especially in females (ß: 0.041, 95% CI: 0.002, 0.081). In contrast, there was a robust inverse association between higher genetically instrumented BMI and health satisfaction in all European ancestry UKB participants (ß: -0.183, 95% CI: -0.200, -0.165, Pdifference < 1.00E-15). We also showed the importance of considering non-linear relationships in the MR framework by providing evidence of non-linear relationships between BMI and health and life satisfaction. Overall, our study suggests potential setting-specific causality in the relationship between BMI and subjective well-being, with robust differences observed between East Asians and Europeans when considering very similar outcomes. We highlight the importance of (a) considering potential non-linear relationships in causal analyses and (b) testing causal relationships in different populations, as the casual nature of relationships, especially relationships influenced by social processes, may be setting-specific.

A Case of Internet Gaming Disorder: When #Play Apart Together Takes a Dark Turn.

Background: The Diagnostic and Statistical Manual of Mental Disorders (DSM-5) places internet Gaming disorder (IGD) in its research appendix as a potential new behavioral addiction diagnosis that requires further investigation. As part of the media campaign #HealthyAtHome, recommendation to relieve stress and anxiety during COVID-19, the World Health Organization (WHO) advocated for the playing of video games. The encouragement and expansion of playing video games may have led to the unintentional consequence of increasing the prevalence of IGD as IGD has been postulated to be a maladaptive response to stress. Case: A 34 year old male presented to his primary care physician with decline in work function, increased depression, and anxiety. Before the COVID-19 pandemic he estimated that he spent 2 h a day playing games and socialized with friends weekly; however at the time of presentation, his social interactions were through online gaming only and he was playing games 14 h per day. The patient began paroxetine and bupropion, with good result, though declined concomitant psychotherapy. Discussion: Internet Gaming Disorder is a potential new behavioral addiction that is likely to increase in prevalence over the continuing course of the COVID-19 pandemic. While initial studies show promising effects of medication and psychosocial interventions, further study on standardized diagnostic criteria and effectiveness of treatment modalities is needed.

Simulated distributions from negative experiments highlight the importance of the body mass index distribution in explaining depression-body mass index genetic risk score interactions.

BACKGROUND: Depression and obesity are complex global health problems. Recent studies suggest that a genetic predisposition to obesity might be accentuated in people with depression, but these analyses are prone to bias. Here, we tested the hypothesis that depression accentuates genetic susceptibility to obesity and applied negative control experiments to test whether any observed interactions were real or driven by confounding and statistical biases. METHODS: We used data from up to 378 000 Europeans in UK Biobank, a 73 variant body mass index (BMI) genetic risk score, two depression measures [depression symptoms (DS), major depression (MD)] and an antidepressant usage variable available. We tested whether (i) depression and (ii) antidepressant treatment accentuated genetic susceptibility to obesity. Finally, we performed negative control experiments by sampling individuals at random so that they had BMI distributions identical to depression cases and controls. RESULTS: Depression was associated with an accentuation of an individual's genetic risk of obesity with evidence of interactions for both DS and MD (Pinteraction = 7 × 10-4 and 7 × 10-5 respectively). Antidepressant usage within DS cases accentuated genetic obesity risk (Pinteraction = 9 × 10-4), but not for MD (Pinteraction = 0.13). Negative control experiments suggested that the observed interactions for MD (empirical-P = 0.067) may be driven by statistical biases or confounding factors but were not possible with the larger DS groups. Antidepressant usage interaction also appears to be driven by statistical artefacts (empirical-P = 0.510 using MD and 0.162 using DS). CONCLUSION: We have highlighted the importance of running negative experiments to confirm putative interactions in gene-environment studies. We provide some tentative evidence that depression accentuates an individual's genetic susceptibility to higher BMI but demonstrated that the BMI distributions within cases and controls might drive these interactions.