Biology subjects

Munafo, M. R.

Publications and source records attributed to Munafo, M. R..

At least 19 recordsLinked to original sources

bioRxiv2025

The carbon footprint of science when it fails to self-correct

Science is - in principle - self-correcting, but there is growing evidence that such self-correction can be slow, and that spurious findings continue to drive research activity that is no longer justified. Here we highlight the environmental impact of this failure to self-correct sufficiently rapidly. We identified a non-fraudulent occurrence of irreproducible findings: the literature on the association between genetic variation in the serotonin transporter gene (5-HTTLPR) with anxiety and depression. An initial report in 1996 found evidence for an association, but a study as early as 2005 that was three orders of magnitude larger found no evidence for an association. However, studies investigating this association continue to be published. We isolated 1,183 studies published between 1996 and 2024 that investigated the association and calculated an estimated carbon footprint of these studies. We estimate that the failure to self-correct had a footprint of approximately 30,068 tons of CO2 equivalent. Our aim is to present a case study of the potential carbon footprint of research activity that is no longer justified, when a theory is disproven. We highlight the importance of integrating self-correction mechanisms within research, and embracing the need to discontinue unfruitful lines of enquiry.

scientific communication and education↗

bioRxiv2019

A Bayesian predictive approach for dealing with pseudoreplication

Pseudoreplication occurs when the number of measured values or data points exceeds the number of genuine replicates, and when the statistical analysis treats all data points as independent and thus fully contributing to the result. By artificially inflating the sample size, pseudoreplication contributes to irreproducibility, and it is a pervasive problem in biological research. In some fields, more than half of published experiments have pseudoreplication - making it one of the biggest threats to inferential validity. Researchers may be reluctant to use appropriate statistical methods if their hypothesis is about the pseudoreplicates and not the genuine replicates; for example, when an intervention is applied to pregnant female rodents (genuine replicates) but the hypothesis is about the effect on the multiple offspring (pseudoreplicates). We propose using a Bayesian predictive approach, which enables researchers to make valid inferences about biological entities of interest, even if they are pseudoreplicates, and show the benefits of this approach using two in vivo data sets.

neuroscience↗

bioRxiv2019

Exploration of the role of CHRNA5-A3-B4 genotype in smoking behaviours

Genome-wide association studies have identified associations between variation at rs16969968/rs1051730 in the CHRNA5-A3-B4 gene cluster and smoking related outcomes. Experiments in rodents have described the nicotinic acetylcholine receptors (nAChRs) subunits encoded by this gene cluster and showed a lack of nicotine aversion in nAChRs deficient animal models. We conducted a nicotine challenge and a smoking topography study in humans, hypothesising that: 1. responses to a nicotine challenge would differ according to the rs16969968/rs1051730 genotype and 2. genotype may influence nicotine intake via smoking topography.\n\nWe used linear regressions to examine associations between rs16969968/rs1051730 genotype and subjective (questionnaires) and objective (physiological parameters) responses following acute nicotine exposure in never smokers (hypothesis 1) or cigarette smoking in current smokers (hypothesis 2). There was evidence to suggest nicotine exposure increases blood pressure and heart rate, and negatively affects mood, but insufficient evidence that these effects differ by genotype. Carriers of the minor allele following smoking one cigarette, exhibited reduced cravings (b=-2.46, 95% CI -4.87 to - 0.06, p=0.04) and inhaled less smoke per cigarette (b=-0.24, 95% CI - 0.43 to - 0.06, p=0.01) and per puff (b=-0.18, 95% CI -0.32 to -0.01, p=0.02). These results suggest that we need to carefully consider the translational value of the findings of aversion behaviour in nAChRs rodent models, and that deeper inhalation does not explain the strong association between rs16969968/rs1051730 genotype and objective biomarkers of tobacco exposure.

neuroscience↗

bioRxiv2019

Is disrupted sleep a risk factor for Alzheimers disease? Evidence from a two-sample Mendelian randomization analysis

INTRODUCTIONIt is established that Alzheimers disease (AD) patients experience sleep disruption. However, it remains unknown whether disruption in the quantity, quality or timing of sleep is a risk factor for the onset of AD.\n\nMETHODSMendelian randomization (MR) was used to estimate the causal effect of self-reported and accelerometer-measured sleep parameters (chronotype, duration, fragmentation, insomnia, daytime napping and daytime sleepiness) on AD risk.\n\nRESULTSOverall, there was little evidence that sleep traits affect the risk of AD. There was some evidence to suggest that self-reported daytime napping was associated with lower AD risk (odds ratio [OR]: 0.70, 95% confidence interval [CI]: 0.50 to 0.99). Some other sleep traits (accelerometer-measured eveningness and sleep duration, and self-reported daytime sleepiness) had ORs for AD risk of a similar magnitude to daytime napping, but were less precisely estimated.\n\nDISCUSSONOur findings provide tentative evidence that daytime napping may reduce AD risk. However, findings should be replicated using independent samples.

epidemiology↗

bioRxiv2019

Executive control of positive and negative information and adolescent depressive symptoms: cross-sectional and longitudinal associations in a population-based cohort.

BackgroundLarge population-based studies of neuropsychological factors that characterize or precede depressive symptoms are rare. Most studies use small case-control or cross-sectional designs, which may cause selection bias and cannot test temporality. In a large UK population-based cohort we investigated cross-sectional and longitudinal associations between executive control of positive and negative information and adolescent depressive symptoms. MethodsCohort study of 2315 UK adolescents (ALSPAC) who completed an affective go/no-go task at age 18. Depressive symptoms were assessed with the Clinical Interview Schedule Revised (CIS-R) and short Mood and Feeling Questionnaire (sMFQ) at age 18, and with the sMFQ 15 months later. Analyses were linear multilevel regressions (for cross-sectional associations) and traditional linear regressions (for longitudinal associations), before and after adjustment for confounders. ResultsCross-sectionally, at age 18, there was some evidence that adolescents with more depressive symptoms made more errors in executive control (after adjustments, errors increased by 0.17 of a point per 1 SD increase in sMFQ score, 95% CI 0.08 to 0.25). However, this cross-sectional association was not observed for the CIS-R (.03, 95% CI -.06 to .12). There was no evidence of a difference in executive control errors according to valence. Longitudinally, there was no evidence that reduced executive control was associated with future depressive symptoms. ConclusionsExecutive control of positive and negative information does not appear to be a marker of current or future depressive symptoms in adolescents and would therefore not be a useful target in interventions to prevent adolescent depression. According to our evidence, the affective go/no-go task is also not a good candidate for future neuroimaging studies of adolescent depression.

epidemiology↗

bioRxiv2019

Feedback training can increase detection of happiness in ambiguous facial expressions in children and adults with autism spectrum disorders

Recognition of subtle emotional facial expressions is challenging for some individuals with autism spectrum disorders (ASD). Training that targets recognition of low intensity emotional expressions may therefore be effective as an intervention to improve social-emotional skills. This paper reports the results of two randomised controlled experiments looking at the effect of a training methodology designed to increase the recognition of happy emotion in low intensity happy facial expressions. The first study implements this training with children with autism spectrum disorder (ASD, N = 14) and the second study implements this training with adults with ASD (N = 27). The training paradigm used images from a morph sequence that mixed a happy expression with a mixed-emotion norm expression to create a sequence of varying intensity happy expressions. Participants were asked to say whether or not individual faces from the sequence were happy, to measure their happiness detection threshold. Participants that received active training were given biased feedback to shift their detection threshold, while participants that received control training were given feedback consistent with their baseline threshold. There was some statistical evidence that thresholds in the active training group shifted more than in the control group. This suggests training was successful in increasing the number of expressions that individuals identified as happy. However, there was no evidence that training increased facial expression recognition accuracy, as measured by the Reading the Mind in the Eyes task completed after training (Study 2).

clinical trials↗

bioRxiv2018

Effects of varenicline and cognitive bias modification on neural response to smoking-related cues: a randomised control trial

Drug-related cognitive biases have been positively associated with drug-craving and increased likelihood of relapse. Cognitive bias modification paradigms have been developed to attenuate cognitive biases but there have been few studies that examined neural responses to these paradigms. This study compared neural responses following CBM and explored whether CBM effects were potentiated by varenicline administration. This was a double-blind placebo-controlled study with two between subject factors of drug (varenicline, placebo) and CBM (attend towards smoking cues, train away from smoking cues, control training) that recruited daily ([≥] 10 cigarettes per day) non-treatment seeking smokers. Participants (n = 67, 53% female) were randomised to one-week of drug administration (varenicline or placebo) before attending a study session at which they were randomised to CBM condition, and underwent an fMRI scan were they were presented with smoking and neutral cues. Neural response to smoking (vs. neutral) cues, cognitive bias, craving and mood were assessed. There was no evidence of CBM effects on any outcomes. There was evidence of effects of varenicline on craving, with greater reductions in craving in the week preceding the study session in the varencline group (p = 0.04,{eta} p2 = .06). There was also evidence of a drug by CBM interaction for neural responses (z = 3.78, p <0.001). Compared to placebo, varenicline was associated with greater activation in the right temporal middle gyrus in the CBM control condition, compared to an opposite effect in the CBM \"attend towards\" condition. These data suggest that CBM does not modify cognitive bias, subjective craving and mood, or neural response to smoking cues. There was also no evidence that CBM effects were potentiated by varenicline.

clinical trials↗

bioRxiv2018

What explains the effect of education on cardiovascular disease? Applying Mendelian randomization to identify the consequences of education inequality

Key PointsO_ST_ABSQuestionC_ST_ABSWhat is the role of body mass index, systolic blood pressure and smoking in mediating the effect of education on cardiovascular disease risk?\n\nFindingWe find consistent evidence that body mass index, systolic blood pressure and smoking mediate the effect of education, explaining up to 18%, 27% and 33% respectively. Including all three risk factors in a model together explains around 40% of the effect of education.\n\nMeaningIntervening on body mass index, systolic blood pressure and smoking would lead to reductions in cases of CVD attributable to lower levels of education. Over half of the effect of education on risk of cardiovascular disease is not mediated through these risk factors.\n\nImportanceLower levels of education are causally related to higher cardiovascular risk, but the extent to which this is driven by modifiable risk factors also associated with education is unknown.\n\nObjectiveTo investigate the role of body mass index, systolic blood pressure and smoking in explaining the effect of education on risk of cardiovascular disease outcomes.\n\nDesignMultivariable regression analysis of observational data and Mendelian randomization (MR) analysis of genetic data.\n\nSettingUK Biobank and international genome-wide association study consortia.\n\nParticipantsPredominantly individuals of European ancestry.\n\nMain outcomes and measuresThe effects of education (per 1-standard deviation increase, equivalent to 3.6 years) on coronary heart disease, cardiovascular disease (all subtypes), myocardial infarction and stroke risk (all measured in odds ratio, OR), and the degree to which this is mediated through body mass index, systolic blood pressure and smoking.\n\nResultsEach additional standard deviation of education associated with 13% lower risk of coronary heart disease (OR 0.87, 95% confidence interval [CI] 0.84 to 0.89) in observational analysis and 37% lower risk (OR 0.63, 95% CI 0.60 to 0.67) in Mendelian randomization analysis. As a proportion of the total risk reduction, body mass index mediated 15% (95% CI 13% to 17%) and 18% (95% CI 14% to 23%) in the observational and Mendelian randomization estimates, respectively. Corresponding estimates for systolic blood pressure were 11% (95% CI 9% to 13%) and 21% (95% CI 15% to 27%), and for smoking, 19% (15% to 22%) and 33% (95% CI 17% to 49%). All three risk factors combined mediated 42% (95% CI 36% to 48%) and 36% (95 % CI 16% to 63%) of the effect of education on coronary heart disease in observational and Mendelian randomization respectively. Similar results were obtained when investigating risk of stroke, myocardial infarction and all-cause cardiovascular disease.\n\nConclusions and relevanceBMI, SBP and smoking mediate a substantial proportion of the protective effect of education on risk of cardiovascular outcomes and intervening on these would lead to reductions in cases of CVD attributable to lower levels of education. However, more than half of the protective effect of education remains unexplained and requires further investigation.

epidemiology↗

bioRxiv2018

Epigenetic regulation of PAR4-related platelet activation: mechanistic links between environmental exposure and cardiovascular disease

Protease-activated receptor 4 (PAR4) is a potent thrombin receptor. Epigenetic control of the F2RL3 locus (which encodes for PAR4) via DNA methylation is associated with both smoking and cardiovascular disease. We examined the association between DNA hypomethylation at F2RL3 and risk of cardiovascular disease, focusing on acute myocardial infarction (AMI) (n=853 cases / 2,352 controls). We used in vitro cell models to dissect the role of DNA methylation in regulating expression of F2RL3. We investigated the interplay between F2RL3 DNA methylation and platelet function in human (n=41). Lastly, we used Mendelian randomization to unify observational and functional work by assessing evidence for causal relationships using data from UK Biobank (n=407,141) and CARDIoGRAMplusC4D (n=184,305). Observationally, one standard deviation (SD) decrease in DNA methylation at F2RL3 was associated with a 25% increase in the odds of AMI. In vitro, short-term exposure of cells to cigarette smoke reduced F2RL3 DNA methylation and increased gene expression. Transcriptional assays flagged a role for a CEBP recognition sequence in modulating the enhancer activity of F2RL3 exon 2. Lower DNA methylation at F2RL3 was associated with increased platelet reactivity in human. The estimated casual odds ratio of ischaemic heart disease was 1.03 (95% CI: 1.00, 1.07) per 1 SD decrease in F2RL3 DNA. In conclusion, we show that DNA methylation-dependent platelet activation is part of a complex system of features contributing to cardiovascular health. Tailoring therapeutic intervention to new knowledge of F2RL3/PAR4 function should be explored to ameliorate the detrimental effects of this risk factor on cardiovascular health.\n\nOne sentence summaryDNA methylation-dependent platelet activation is a likely causal contributor to cardiovascular health.

epidemiology↗

bioRxiv2018

Investigating causal relationships between sleep traits and risk of breast cancer: a Mendelian randomization study

ObjectiveTo examine whether sleep traits have a causal effect on risk of breast cancer.\n\nDesignMultivariable regression, one- and two-sample Mendelian randomization.\n\nSettingThe UK Biobank prospective cohort study and the Breast Cancer Association Consortium (BCAC) case-control genome-wide association study.\n\nParticipants156,848 women in the multivariable regression and one-sample Mendelian randomization analysis in UK Biobank (7,784 with a breast cancer diagnosis) and 122,977 breast cancer cases and 105,974 controls from BCAC in the two-sample Mendelian randomization analysis.\n\nExposuresSelf-reported chronotype (morning/evening preference), insomnia symptoms and sleep duration in multivariable regression, and genetic variants robustly associated with these sleep traits.\n\nMain outcome measuresBreast cancer (prevalent and incident cases in UK Biobank, prevalent cases only in BCAC).\n\nResultsIn multivariable regression analysis using data on breast cancer incidence in UK Biobank, morning preference was inversely associated with breast cancer (HR 0.95, 95% CI 0.93, 0.98 per category increase) while there was little evidence for an association with sleep duration and insomnia symptoms. Using 341 single nucleotide polymorphisms (SNPs) associated with chronotype, 91 SNPs associated sleep duration and 57 SNPs associated with insomnia symptoms, one-sample MR analysis in UK Biobank provided some supportive evidence for a protective effect of morning preference on breast cancer risk (HR 0.85, 95% 0.70, 1.03 per category increase) but imprecise estimates for sleep duration and insomnia symptoms. Two-sample MR using data from BCAC supported findings for a protective effect of morning preference (OR 0.88, 95% CI 0.82, 0.93 per category increase) and adverse effect of increased sleep duration (OR 1.19, 95% CI 1.02, 1.39 per hour increase) on breast cancer (both estrogen receptor positive and negative), while there was inconsistent evidence for insomnia symptoms. Results were largely robust to sensitivity analyses accounting for horizontal pleiotropy.\n\nConclusionsWe found consistent evidence for a protective effect of morning preference and suggestive evidence for an adverse effect of sleep duration on breast cancer risk.

epidemiology↗

bioRxiv2018

Bidirectional effects of anxiety and anorexia nervosa: A Mendelian randomization study

ObjectivesTo assess bidirectional effects of anxiety and anorexia nervosa (AN) phenotypes. Design Two-sample Mendelian randomization.\n\nSettingGenome-wide association study (GWAS) summary statistics from the Psychiatric Genomics Consortium (PGC), analysis of the UK Biobank sample, and Anxiety Neuro Genetics Study (ANGST) consortium.\n\nParticipantsEuropean descent participants from the PGC (n = 14,477), UK Biobank (n = 348,219), and ANGST consortium (n = 17,310, and n = 18,186).\n\nMain outcome measuresAN diagnosis, worry, anxiety disorder pathology (case-control and quantitative phenotypes).\n\nResultsWe found evidence of a moderate genetic correlation between worry and AN (Rg = 0.36, SE = 0.05, p < 0.001), and the Mendelian randomization analysis supported a causal influence of worry on AN (OR = 2.14, 95% CI: 1.18 to 3.90, p = 0.01). There was no clear evidence for a causal effect of AN on worry in this study (B = -0.01, 95% CI: -0.03 to 0.02, p = 0.55). There was no robust evidence for a causal influence of anxiety disorders on AN (for case-control anxiety disorder phenotype: OR = 1.02, 95% CI: 0.69, 1.50, p = 0.922; for quantitative anxiety disorder phenotype: OR = 4.26, 95% CI: 0.49, 36.69, p = 0.187). There was no robust evidence for a causal effect of AN on anxiety disorders (for case control anxiety disorder phenotype: OR = 1.00, 95% CI: 0.72, 1.38, p = 0.981; for quantitative anxiety disorder phenotype: B = 0.01, 95% CI: -0.06, 0.6=09, p = 0,761). AN and anxiety disorder phenotypes were not genetically correlated (for case-control anxiety disorder phenotype: Rg = 0.10, se = 0.17, p = .56; for quantitative anxiety disorder phenotype: Rg = 0.12, SE = 0.17, p = 0.47).\n\nConclusionsFindings support a role for worry in AN development, highlighting a potential target of future AN prevention efforts. Mechanisms underlying the association should be a focus of future investigation. The relatively small sample sizes of anxiety disorder and AN GWASs may have limited power to detect causal effects; these associations should be studied further.

epidemiology↗

bioRxiv2018

MR-pheWAS with stratification and interaction: Searching for the causal effects of smoking heaviness identified an effect on facial aging

Mendelian randomization (MR) is an established approach for estimating the causal effect of an environmental exposure on a downstream outcome. The gene x environment (GxE) study design can be used within an MR framework to determine whether MR estimates may be biased if the genetic instrument affects the outcome through pathways other than via the exposure of interest (known as horizontal pleiotropy). MR phenome-wide association studies (MR-pheWAS) search for the effects of an exposure, and a recently published tool (PHESANT) means that it is now possible to do this comprehensively, across thousands of traits in UK Biobank. In this study, we introduce the GxE MR-pheWAS approach, and search for the causal effects of smoking heaviness - stratifying on smoking status (ever versus never) - as an exemplar. If a genetic variant is associated with smoking heaviness (but not smoking initiation), and this variant affects an outcome (at least partially) via tobacco intake, we would expect the effect of the variant on the outcome to differ in ever versus never smokers. If this effect is entirely mediated by tobacco intake, we would expect to see an effect in ever smokers but not never smokers. We used PHESANT to search for the causal effects of smoking heaviness, instrumented by genetic variant rs16969968, among never and ever smokers respectively, in UK Biobank. We ranked results by: 1) strength of effect of rs16969968 among ever smokers, and 2) strength of interaction between ever and never smokers. We replicated previously established causal effects of smoking heaviness, including a detrimental effect on lung function and pulse rate. Novel results included a detrimental effect of heavier smoking on facial aging. We have demonstrated how GxE MR-pheWAS can be used to identify causal effects of an exposure, while simultaneously assessing the extent that results may be biased by horizontal pleiotropy.\n\nAuthor summaryMendelian randomization uses genetic variants associated with an exposure to investigate causality. For instance, a genetic variant that relates to how heavily a person smokes has been used to test whether smoking causally affects health outcomes. Mendelian randomization is biased if the genetic variant also affects the outcome via other pathways. We exploit additional information - that the effect of heavy smoking only occurs in people who actually smoke - to overcome this problem. By testing associations in ever and never smokers separately we can assess whether the genetic variant affects an outcome via smoking or another pathway. If the effect is entirely via smoking heaviness, we would expect to see an effect in ever but not never smokers, and this would suggest that smoking causally influences the outcome. Previous Mendelian randomization studies of smoking heaviness focused on specific outcomes - here we searched for the causal effects of smoking heaviness across over 18,000 traits. We identified previously established effects (e.g. a detrimental effect on lung function) and novel results including a detrimental effect of heavier smoking on facial aging. Our approach can be used to search for the causal effects of other exposures, where the exposure only occurs in known subsets of the population.

epidemiology↗

bioRxiv2018

The effects of age at menarche and first sexual intercourse on reproductive and behavioural outcomes: a Mendelian randomization study

There is substantial variation in the timing of significant reproductive life events such as menarche and first sexual intercourse. Life history theory explains this variation as an adaptive response to the developmental environment. In environments characterized by harsh conditions, adopting a fast life history strategy may increase fitness. In line with this, there is evidence demonstrating that greater childhood adversity is associated with earlier age at menarche. Here we applied Mendelian randomization (MR) methods to investigate whether there is a causal effect of variation in age at menarche and age at first sexual intercourse on outcomes related to reproduction, education and risky behaviour in UK Biobank (N = 114883-181,255). Our results suggest that earlier age at menarche affects some traits that characterize life history strategies including earlier age at first and last birth, decreased educational attainment, and decreased age at leaving education (for example, we found evidence for a 0.26 year decrease in age at first birth per year decrease in age at menarche, 95% confidence interval: -0.34 to -0.17; p < 0.0001). We find no clear evidence of effects of age at menarche on other outcomes, such as risk taking behaviour. Age at first sexual intercourse was also related to many life history outcomes, although there was evidence of horizontal pleiotropy which violates an assumption of MR and results should be treated with caution. Taken together, these results highlight how MR can be applied to test predictions of life history theory and to better understand determinants of health and social behaviour.

evolutionary biology↗

bioRxiv2018

Causal effects of lifetime smoking on risk for depression and schizophrenia: Evidence from a Mendelian randomisation study

BackgroundSmoking prevalence is higher amongst individuals with schizophrenia and depression compared to the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS).\n\nMethodsWe conducted a GWAS of lifetime smoking behaviour (capturing smoking duration, heaviness and cessation) in a sample of 462,690 individuals from the UK Biobank, and validated the findings via two-sample MR analyses of positive control outcomes (e.g., lung cancer). Having established the validity of our instrument, we used bi-directional two-sample Mendelian randomisation to explore its effects on schizophrenia and depression.\n\nOutcomesThere was strong evidence to suggest smoking is a causal risk factor for both schizophrenia (OR = 2.27, 95% CI = 1.67 - 3.08, P < 0.001) and depression (OR = 1.99, 95% CI = 1.71 - 2.32, P < 0.001). We also found some evidence that genetic risk for both schizophrenia and depression cause increased lifetime smoking ({beta} = 0.022, 95% CI = 0.005 - 0.038, P = 0.009; {beta}= 0.091, 95% CI = 0.027 - 0.155, P = 0.005).\n\nInterpretationThese findings suggest that the association between smoking, schizophrenia and depression is due, at least in part, to a causal effect of smoking, providing further evidence for the detrimental consequences of smoking for mental health.\n\nFundingThis work was supported by the Medical Research Council Integrative Epidemiology Unit, the NIHR Biomedical Research Centre, University Hospitals Bristol NHS Foundation Trust and the University of Bristol.\n\nResearch in contextO_ST_ABSEvidence before this studyC_ST_ABSThe association between smoking and mental health (especially schizophrenia and depression) is often assumed to be the result of self-medication (for example, to alleviate symptoms). However, more recent evidence has suggested that smoking might also be a risk factor for schizophrenia and depression. This alternative direction of effect is supported by meta-analyses and previous prospective observational evidence using related individuals to control for genetic and environmental confounding. However, observational evidence cannot completely account for confounding or the possibility of reverse causation. One way to get around these problems is Mendelian randomisation (MR). Previous MR studies of smoking and mental health have not shown an effect of smoking on depression and are inconclusive for the effects of smoking on schizophrenia. However, these studies have only looked at individual aspects of smoking behaviour and some studies required stratifying participants into smokers and non-smokers, reducing power.\n\nAdded value of this studyWe have developed a novel genetic instrument for lifetime smoking exposure which can be used within a two-sample MR framework, using publicly-available GWAS summary statistics. We were therefore able to test the bi-directional association between smoking with schizophrenia and depression to see if the effects are causal. We found strong evidence to suggest that smoking is a causal risk factor for both schizophrenia and depression. There was some evidence to suggest that risk of schizophrenia and depression increases lifetime smoking (consistent with the self-medication hypothesis) but the effects were stronger for depression than schizophrenia.\n\nImplications of all the available evidenceThis study was the first to demonstrate evidence for an effect of lifetime smoking exposure on risk of schizophrenia and depression within a causal inference framework. This emphasises the detrimental public health consequences of smoking, not just for physical health, but also to mental illness.

epidemiology↗

bioRxiv2018

Schizophrenia risk and reproductive success: A Mendelian randomization study.

Schizophrenia is a debilitating and heritable mental disorder associated with lower reproductive success. However, the prevalence of schizophrenia is stable over populations and time, resulting in an evolutionary puzzle: how is schizophrenia maintained in the population given its apparent fitness costs? One possibility is that increased genetic liability for schizophrenia, in the absence of the disorder itself, may confer some reproductive advantage. We assessed the correlation and causal effect of genetic liability for schizophrenia with number of children and age at first birth using data from the Psychiatric Genomics Consortium and UK Biobank. Linkage disequilibrium score regression showed little evidence of genetic correlation between genetic liability for schizophrenia and number of children (rg=0.002, p=0.84) or age at first birth (rg=-0.007, p=0.45). Mendelian randomization indicated no robust evidence of a causal effect of genetic liability for schizophrenia on number of children (mean difference: 0.003 increase in number of children per doubling in the natural log odds ratio of schizophrenia risk, 95% CI: -0.003 to 0.009, p=0.39) or age at first birth (-0.004 years lower age at first birth, 95% CI: -0.043 to 0.034, p=0.82). These results suggest that increased genetic liability for schizophrenia does not confer a reproductive advantage.

evolutionary biology↗

bioRxiv2018

Emotional recognition training modifies neural response to emotional faces but does not improve mood in healthy volunteers with high levels of depressive symptoms

IMPORTANCEDepression is a debilitating and highly prevalent mental health disorder. There is a need for new, effective, and scalable treatments for depression, and cognitive bias modification (CBM) of negative emotional processing biases has been suggested as one possibility. Such treatments may form the basis of digital therapeutics, that could be administered remotely and at low cost, should they prove to be effective.\n\nOBJECTIVESStudy one was designed to determine neural correlates of a recently developed CBM technique for emotion recognition training; specifically, our aim was to compare the effects of training vs placebo on pre-specified regions of interest involved in emotion processing that are known to be sensitive to antidepressant treatment. Study two aimed to investigate efficacy of training on mood measures at 2 and 6-week follow-up and was powered to replicate and extend earlier findings.\n\nDESIGN, SETTING, AND PARTICIPANTSBoth studies were double blind RCTs, in which participants completed five sessions of emotion recognition training or sham training, in the laboratory, over a one-week period. In study one (N=37), following this training, participants completed a novel emotion recognition task whilst undergoing fMRI. In study two (N=190), measures of mood were assessed post training, and at 2-week and 6-week follow-up. Both studies recruited analogue samples of healthy volunteers with high levels of depressive symptoms (BDI-ii > 14).\n\nMAIN OUTCOMES AND MEASURESIn study one, our primary outcome was neural activation in the following pre-specified regions of interest: the bilateral amygdala, the mPFC, bilateral dlPFC, and the occipital cortex. In study two, our primary outcome was depressive symptoms over the last 2 weeks assessed using the BDI-ii at 6-week follow-up. Secondary outcomes included depressive symptoms measured using the HAM-D, and positive and negative affect assessed using the PANAS.\n\nRESULTSIn both studies, CBM resulted in a change in emotion recognition bias, which (in study two) persisted for 6 weeks after the end of the CBM phase. In study one, CBM resulted in increases neural activation to happy faces compared to sad faces, with this effect driven by an increase in neural activity for happy faces. We saw this increase in activation for this contrast at both the whole brain level and among our a priori ROIs, specifically the mPFC and bilateral amygdala. In study two, CBM did not lead to a reduction in depressive symptoms on the BDI-ii, or on related measures of mood, motivation and persistence, or depressive interpretation bias.\n\nCONCLUSIONS AND RELEVANCECBM of emotion recognition appears to have effects on neural activity that are similar in some respects to those induced by SSRI administration (study one), but we find no evidence that this has any effect on self-reported mood in an analogue sample of healthy volunteers with low mood (study two).

neuroscience↗

bioRxiv2018

Association of intrauterine alcohol exposure and offspring depression:A negative control analysis of maternal and partner consumption.

BackgroundPrevious research has suggested that intrauterine alcohol exposure is associated with a variety of adverse outcomes in offspring. However, few studies have investigated its association with offspring internalising disorders in late adolescence.\n\nMethodsUsing data from the Avon Longitudinal Study of Parents and Children (ALSPAC), we investigated the associations of maternal drinking in pregnancy with offspring depression at age 18. We also examined partner drinking as a negative control for intrauterine exposure for comparison.\n\nResultsOffspring of mothers that consumed any alcohol at 18 weeks gestation were at increased risk of having a diagnosis of depression (OR 1.15, 95% CI 1.00 to 1.32), but there was no clear evidence of association between partners alcohol consumption during pregnancy and increased risk of offspring depression (OR 0.90, 95% CI 0.78 to 1.04).\n\nConclusionsMaternal drinking in pregnancy was associated with increased risk of offspring depression at age 18. Residual confounding may explain this association, but the negative control comparison of paternal drinking provides some evidence that it may be causal, and this warrants further investigation.

epidemiology↗

bioRxiv2018

Testing the causal effects between subjective wellbeing and physical health using Mendelian randomisation

ObjectivesTo investigate whether the association between subjective wellbeing (subjective happiness and life satisfaction) and physical health is causal.\n\nDesignWe conducted two-sample bidirectional Mendelian randomisation between subjective wellbeing and six measures of physical health: coronary artery disease, myocardial infarction, total cholesterol, HDL cholesterol, LDL cholesterol and body mass index (BMI).\n\nParticipantsWe used summary data from four large genome-wide association study consortia: CARDIoGRAMplusC4D for coronary artery disease and myocardial infarction; the Global Lipids Genetics Consortium for cholesterol measures; the Genetic Investigation of Anthropometric Traits consortium for BMI; and the Social Science Genetics Association Consortium for subjective wellbeing. A replication analysis was conducted using 337,112 individuals from the UK Biobank (54% female, mean age =56.87, SD=8.00 years at recruitment).\n\nMain outcome measuresCoronary artery disease, myocardial infarction, total cholesterol, HDL cholesterol, LDL cholesterol, BMI and subjective wellbeing.\n\nResultsThere was evidence of a causal effect of BMI on subjective wellbeing such that each 1 kg/m2 increase in BMI caused a 0.045 (95%CI 0.006 to 0.084, p=0.023) SD reduction in subjective wellbeing. Replication analyses provided strong evidence of an effect of BMI on satisfaction with health ({beta}=0.034 (95% CI: -0.042 to -0.026) unit decrease in health satisfaction per SD increase in BMI, p<2-16). There was no clear evidence of a causal effect between subjective wellbeing and the other physical health measures in either direction.\n\nConclusionsOur results suggest that a higher BMI lowers subjective wellbeing. Our replication analysis confirmed this finding, suggesting the effect in middle-age is driven by satisfaction with health. BMI is a modifiable determinant and therefore, our study provides further motivation to tackle the obesity epidemic because of the knock-on effects of higher BMI on subjective wellbeing.

epidemiology↗