An exploration into the causal relationships between educational attainment, intelligence, and wellbeing: an observational and two-sample Mendelian randomisation study

Educational attainment is associated with a range of positive outcomes, yet its impact on wellbeing is unclear, and complicated by high correlations with intelligence. We use genetic and observational data to investigate for the first time, whether educational attainment and intelligence are causally and independently related to wellbeing. Results from our multivariable Mendelian randomisation demonstrated a positive causal impact of a genetic predisposition to higher educational attainment on wellbeing that remained after accounting for intelligence, and a negative impact of intelligence that was independent of educational attainment. Observational analyses suggested that these associations may be subject to sex differences, with benefits to wellbeing greater for females who attend higher education compared to males. For intelligence, males scoring more highly on measures related to happiness were those with lower intelligence. Our findings demonstrate a unique benefit for wellbeing of staying in school, over and above improving cognitive abilities, with benefits likely to be greater for females compared to males.

Assessing causal links between age at menarche and adolescent mental health: a Mendelian randomisation study

BACKGROUND

The timing of puberty may have an important impact on adolescent mental health. In particular, earlier age at menarche has been associated with elevated rates of depression in adolescents. Previous research suggests that this relationship may be causal, but replication and an investigation of whether this effect extends to other mental health domains is warranted.

METHODS

In this Registered Report, we triangulated evidence from different causal inference methods using a new wave of data (N = 13,398) from the Norwegian Mother, Father, and Child Cohort Study. We combined multiple regression, one- and two-sample Mendelian randomisation (MR), and negative control analyses (using pre-pubertal symptoms as outcomes) to assess the causal links between age at menarche and different domains of adolescent mental health.

RESULTS

Our results supported the hypothesis that earlier age at menarche is associated with elevated depressive symptoms in early adolescence based on multiple regression (β =  - 0.11, 95% CI [- 0.12, - 0.09], pone-tailed < 0.01). One-sample MR analyses suggested that this relationship may be causal (β =  - 0.07, 95% CI [- 0.13, 0.00], pone-tailed = 0.03), but the effect was small, corresponding to just a 0.06 standard deviation increase in depressive symptoms with each earlier year of menarche. There was also some evidence of a causal relationship with depression diagnoses during adolescence based on one-sample MR (OR = 0.74, 95% CI [0.54, 1.01], pone-tailed = 0.03), corresponding to a 29% increase in the odds of receiving a depression diagnosis with each earlier year of menarche. Negative control and two-sample MR sensitivity analyses were broadly consistent with this pattern of results. Multivariable MR analyses accounting for the genetic overlap between age at menarche and childhood body size provided some evidence of confounding. Meanwhile, we found little consistent evidence of effects on other domains of mental health after accounting for co-occurring depression and other confounding.

CONCLUSIONS

We found evidence that age at menarche affected diagnoses of adolescent depression, but not other domains of mental health. Our findings suggest that earlier age at menarche is linked to problems in specific domains rather than adolescent mental health in general.

Estimating the health impact of nicotine exposure by dissecting the effects of nicotine versus non-nicotine constituents of tobacco smoke: A multivariable Mendelian randomisation study

The detrimental health effects of smoking are well-known, but the impact of regular nicotine use without exposure to the other constituents of tobacco is less clear. Given the increasing daily use of alternative nicotine delivery systems, such as e-cigarettes, it is increasingly important to understand and separate the effects of nicotine use from the impact of tobacco smoke exposure. Using a multivariable Mendelian randomisation framework, we explored the direct effects of nicotine compared with the non-nicotine constituents of tobacco smoke on health outcomes (lung cancer, chronic obstructive pulmonary disease [COPD], forced expiratory volume in one second [FEV-1], forced vital capacity [FVC], coronary heart disease [CHD], and heart rate [HR]). We used Genome-Wide Association Study (GWAS) summary statistics from Buchwald and colleagues, the GWAS and Sequencing Consortium of Alcohol and Nicotine, the International Lung Cancer Consortium, and UK Biobank. Increased nicotine metabolism increased the risk of COPD, lung cancer, and lung function in the univariable analysis. However, when accounting for smoking heaviness in the multivariable analysis, we found that increased nicotine metabolite ratio (indicative of decreased nicotine exposure per cigarette smoked) decreases heart rate (b = -0.30, 95% CI -0.50 to -0.10) and lung function (b = -33.33, 95% CI -41.76 to -24.90). There was no clear evidence of an effect on the remaining outcomes. The results suggest that these smoking-related outcomes are not due to nicotine exposure but are caused by the other components of tobacco smoke; however, there are multiple potential sources of bias, and the results should be triangulated using evidence from a range of methodologies.

Loneliness and depression: bidirectional mendelian randomization analyses using data from three large genome-wide association studies

Major depression (MD) is a serious psychiatric illness afflicting nearly 5% of the world's population. A large correlational literature suggests that loneliness is a prospective risk factor for MD; correlational assocations of this nature may be confounded for a variety of reasons. This report uses Mendelian Randomization (MR) to examine potentially causal associations between loneliness and MD. We report on analyses using summary statistics from three large genome wide association studies (GWAS). MR analyses were conducted using three independent sources of GWAS summary statistics. In the first set of analyses, we used available summary statistics from an extant GWAS of loneliness to predict MD risk. We used two sources of outcome data: the Psychiatric Genomics Consortium (PGC) meta-analysis of MD (PGC-MD; N = 142,646) and the Million Veteran Program (MVP-MD; N = 250,215). Finally, we reversed analyses using data from the MVP and PGC samples to identify risk variants for MD and used loneliness outcome data from UK Biobank. We find robust evidence for a bidirectional causal relationship between loneliness and MD, including between loneliness, depression cases status, and a continuous measure of depressive symptoms. The estimates remained significant across several sensitivity analyses, including models that account for horizontal pleiotropy. This paper provides the first genetically-informed evidence that reducing loneliness may play a causal role in decreasing risk for depressive illness, and these findings support efforts to reduce loneliness in order to prevent or ameliorate MD. Discussion focuses on the public health significance of these findings, especially in light of the SARS-CoV-2 pandemic.

Proxy gene-by-environment Mendelian randomization study of the association between cigarette smoking during pregnancy and offspring mental health

BACKGROUND

Smoking prevalence is higher among individuals with schizophrenia or depression, and previous work has suggested this relationship is causal. However, this may be due to dynastic effects, for example reflecting maternal smoking during pregnancy rather than a direct effect of smoking. We used a proxy gene-by-environment Mendelian randomization approach to investigate whether there is a causal effect of maternal heaviness of smoking during pregnancy on offspring mental health.

METHODS

Analyses were performed in the UK Biobank cohort. Individuals with data on smoking status, maternal smoking during pregnancy, a diagnosis of schizophrenia or depression, and genetic data were included. We used participants' genotype (rs16969968 in the CHRNA5 gene) as a proxy for their mothers' genotype. Analyses were stratified on participants' own smoking status in order to estimate the effect of maternal smoking heaviness during pregnancy independently of offspring smoking.

RESULTS

The effect of maternal smoking on offspring schizophrenia was in opposing directions when stratifying on offspring smoking status. Among offspring of never smokers, each additional risk allele for maternal smoking heaviness appeared to have a protective effect [odds ratio (OR) = 0.77, 95% confidence interval (CI) 0.62 to 0.95, P = 0.015], whereas among ever smokers the effect of maternal smoking was in the reverse direction (OR = 1.23, 95% CI 1.05 to 1.45, P = 0.011, Pinteraction <0.001). There was no clear evidence of an association between maternal smoking heaviness and offspring depression.

CONCLUSIONS

These findings do not provide clear evidence of an effect of maternal smoking during pregnancy on offspring schizophrenia or depression, which implies that any causal effect of smoking on schizophrenia or depression is direct.

Exploring the bidirectional causal pathways between smoking behaviours and headache: A Mendelian randomisation study

INTRODUCTION

Although observational data suggests a relationship between headache and smoking, there remain questions about causality. Smoking may increase headache risk, individuals may smoke to alleviate headaches, or smoking and headache may share common risk factors. Mendelian randomisation (MR) is a method that uses genetic variants as instruments for making causal inferences about an exposure and an outcome.

METHODS

First, we conducted logistic regression of observational data in UK Biobank assessing the association between smoking behaviours (smoking status, cigarettes per day amongst daily smokers and lifetime smoking score) on risk of self-reported headache (in the last month and for more than 3 months). Second, we used genetic instruments for smoking behaviours and headache (identified in independent genome-wide association studies) to perform bidirectional MR analysis.

RESULTS

Observationally, there is a weak association between smoking behaviour and experiencing headache, with increased cigarettes per day associated with increased headache risk. In the MR analysis, genetic liability to smoking initiation and lifetime smoking increased odds of headache in the last month but not odds of headaches lasting more than three months. In the opposite direction there was weak evidence for higher genetic liability to headaches decreasing the chance of quitting.

CONCLUSION

There was weak evidence for a partially bidirectional causal relationship between smoking behaviours and headache in the last month. Given this relationship is distinct from smoking heaviness, it suggests headache and smoking may share common risk factors such as personality traits.

IMPLICATIONS

Using Mendelian Randomisation, this study addresses the uncertainty regarding the observed relationship between headache and smoking. There was evidence for weak causal effects of smoking initiation and lifetime smoking (but not smoking heaviness) on likelihood of experiencing headache in the last month, but not over a prolonged period of more than three months. Those at higher genetic liability for headaches were also less likely to successfully stop smoking. This partially bidirectional causal relationship distinct from smoking heaviness, suggests that observed associations are unlikely due to biological effects of tobacco smoke exposure and may be explained by shared personality traits.

Extensions of the causal framework to Mendelian randomisation and gene-environment interaction

In our commentary we ask whether we should ultimately endeavour to find the deep causes of behaviours? Then we discuss two extensions of the proposed framework: (1) Mendelian randomisation and (2) hypothesis-free gene-environment interaction (leveraging heterogeneity in genetic associations). These complementary methods help move us towards second-generation causal knowledge, ultimately understanding mechanistic pathways and identifying more effective intervention targets.

Educational inequality in multimorbidity: causality and causal pathways. A mendelian randomisation study in UK Biobank

BACKGROUND

Multimorbidity, typically defined as having two or more long-term health conditions, is associated with reduced wellbeing and life expectancy. Understanding the determinants of multimorbidity, including whether they are causal, may help with the design and prioritisation of prevention interventions. This study seeks to assess the causality of education, BMI, smoking and alcohol as determinants of multimorbidity, and the degree to which BMI, smoking and alcohol mediate differences in multimorbidity by level of education.

METHODS

Participants were 181,214 females and 155,677 males, mean ages 56.7 and 57.1 years respectively, from UK Biobank. We used a Mendelian randomization design; an approach that uses genetic variants as instrumental variables to interrogate causality.

RESULTS

The prevalence of multimorbidity was 55.1%. Mendelian randomization suggests that lower education, higher BMI and higher levels of smoking causally increase the risk of multimorbidity. For example, one standard deviation (equivalent to 5.1 years) increase in genetically-predicted years of education decreases the risk of multimorbidity by 9.0% (95% CI: 6.5 to 11.4%). A 5 kg/m2 increase in genetically-predicted BMI increases the risk of multimorbidity by 9.2% (95% CI: 8.1 to 10.3%) and a one SD higher lifetime smoking index increases the risk of multimorbidity by 6.8% (95% CI: 3.3 to 10.4%). Evidence for a causal effect of genetically-predicted alcohol consumption on multimorbidity was less strong; an increase of 5 units of alcohol per week increases the risk of multimorbidity by 1.3% (95% CI: 0.2 to 2.5%). The proportions of the association between education and multimorbidity explained by BMI and smoking are 20.4% and 17.6% respectively. Collectively, BMI and smoking account for 31.8% of the educational inequality in multimorbidity.

CONCLUSIONS

Education, BMI, smoking and alcohol consumption are intervenable causal risk factors for multimorbidity. Furthermore, BMI and lifetime smoking make a considerable contribution to the generation of educational inequalities in multimorbidity. Public health interventions that improve population-wide levels of these risk factors are likely to reduce multimorbidity and inequalities in its occurrence.

Cognitive functioning in anxiety and depression: results from the ALSPAC cohort

Anxiety and depression are associated with a range of impairments in cognitive functioning. Understanding the nature of these deficits may identify targets for intervention and prevent functional decline. We used observational and genetic methods to investigate the relationship of anxiety and depression with three cognitive domains: emotion recognition, response inhibition, and working memory, in the Avon Longitudinal Study of Parents and Children (ALSPAC). We examined: (i) cross-sectional associations between anxiety, depression, and cognition at age 24 (n = 2187), (ii) prospective associations between anxiety and depression at age 18 and cognition at age 24 (n = 1855), and (iii) the casual effect of anxiety and depression on cognition using Mendelian randomization (MR). Both disorders were associated with altered emotion recognition; anxiety with decreased happiness recognition (b = -0.27 [-0.54,0.01], p = 0.045), and depression with increased sadness recognition (b = 0.35 [0.07,0.64], p = 0.016). Anxiety was also associated with poorer working memory (b = -0.14 [-0.24,0.04], p = 0.005). There was no evidence for an association with response inhibition. MR provided no clear evidence of causal relationships between mental health and cognition, but these analyses were underpowered. Overall, there was little evidence for impairments in executive functioning, but moderate alterations in emotion recognition. This may inform the development of psychosocial interventions.

The absence of association between anorexia nervosa and smoking: converging evidence across two studies

Previous studies have found increased smoking prevalence amongst adults with anorexia nervosa (AN) compared to the general population. The current investigation explored bidirectional associations between AN and smoking behaviour (initiation and heaviness), to address questions surrounding causation. In Study One, logistic regression models with variance robust standard errors assessed longitudinal associations between AN and smoking, using data from adolescent participants of the Avon Longitudinal Study of Parents and Children (N = 5100). In Study Two, two-sample Mendelian randomisation (MR) tested possible causal effects using summary statistics from publicly available genome-wide association studies (GWAS). Study One provided no clear evidence for a predictive effect of AN on subsequent smoking behaviour, or for smoking heaviness/initiation predicting later AN. MR findings did not support causal effects between AN and smoking behaviour, in either direction. Findings do not support predictive or causal effects between AN and smoking behaviour. Previously reported associations may have been vulnerable to confounding, highlighting the possibility of smoking and AN sharing causal risk factors.

Associations between health behaviours, fertility and reproductive outcomes: triangulation of evidence in the Norwegian Mother, Father and Child Cohort Study (MoBa)

BACKGROUND

Guidance to improve fertility includes reducing alcohol and caffeine consumption, achieving healthy weight-range and stopping smoking. Advice is informed by observational evidence, which is often biased by confounding.

METHODS

This study primarily used data from a pregnancy cohort, the Norwegian Mother, Father and Child Cohort Study. First, we conducted multivariable regression of health behaviours (alcohol and caffeine consumption, body-mass index (BMI), and smoking) on fertility outcomes (e.g. time to conception) and reproductive outcomes (e.g. age at first birth) (n = 84,075 females, 68,002 males), adjusting for birth year, education and attention-deficit and hyperactive-impulsive (ADHD) traits. Second, we used individual-level Mendelian randomisation (MR) to explore possible causal effects of health behaviours on fertility/reproductive outcomes (n = 63,376 females, 45,460 males). Finally, we performed summary-level MR for available outcomes in UK Biobank (n = 91,462-1,232,091) and controlled for education and ADHD liability using multivariable MR.

RESULTS

In multivariable regression analyses, higher BMI associated with fertility (longer time to conception, increased odds of infertility treatment and miscarriage), and smoking was associated with longer time to conception. In individual-level MR analyses, there was strong evidence for effects of smoking initiation and higher BMI on younger age at first birth, of higher BMI on increased time to conception, and weak evidence for effects of smoking initiation on increased time to conception. Age at first birth associations were replicated in summary-level MR analysis; however, effects attenuated using multivariable MR.

CONCLUSIONS

Smoking behaviour and BMI showed the most consistent associations for increased time to conception and a younger age at first birth. Given that age at first birth and time to conception are positively correlated, this suggests that the mechanisms for reproductive outcomes are distinct to the mechanisms acting on fertility outcomes. Multivariable MR suggested that effects on age at first birth might be explained by underlying liability to ADHD and education.

Mendelian randomization study of maternal coffee consumption and its influence on birthweight, stillbirth, miscarriage, gestational age and pre-term birth

BACKGROUND

Coffee consumption has been associated with several adverse pregnancy outcomes, although data from randomized-controlled trials are lacking. We investigate whether there is a causal relationship between coffee consumption and miscarriage, stillbirth, birthweight, gestational age and pre-term birth using Mendelian randomization (MR).

METHODS

A two-sample MR study was performed using summary results data from a genome-wide association meta-analysis of coffee consumption (N = 91 462) from the Coffee and Caffeine Genetics Consortium. Outcomes included self-reported miscarriage (N = 49 996 cases and 174 109 controls from a large meta-analysis); the number of stillbirths [N = 60 453 from UK Biobank (UKBB)]; gestational age and pre-term birth (N = 43 568 from the 23andMe, Inc cohort) and birthweight (N = 297 356 reporting own birthweight and N = 210 248 reporting offspring's birthweight from UKBB and the Early Growth Genetics Consortium). Additionally, a one-sample genetic risk score (GRS) analysis of coffee consumption in UKBB women (N up to 194 196) and the Avon Longitudinal Study of Parents and Children (N up to 6845 mothers and 4510 children) and its relationship with offspring outcomes was performed.

RESULTS

Both the two-sample MR and one-sample GRS analyses showed no change in risk of sporadic miscarriages, stillbirths, pre-term birth or effect on gestational age connected to coffee consumption. Although both analyses showed an association between increased coffee consumption and higher birthweight, the magnitude of the effect was inconsistent.

CONCLUSION

Our results suggest that coffee consumption during pregnancy might not itself contribute to adverse outcomes such as stillbirth, sporadic miscarriages and pre-term birth or lower gestational age or birthweight of the offspring.

The effect of maternal BMI, smoking and alcohol on congenital heart diseases: a Mendelian randomisation study

BACKGROUND

Congenital heart diseases (CHDs) remain a significant cause of infant morbidity and mortality. Epidemiological studies have explored maternal risk factors for offspring CHDs, but few have used genetic epidemiology methods to improve causal inference.

METHODS

Three birth cohorts, including 65,510 mother/offspring pairs (N = 562 CHD cases) were included. We used Mendelian randomisation (MR) analyses to explore the effects of genetically predicted maternal body mass index (BMI), smoking and alcohol on offspring CHDs. We generated genetic risk scores (GRS) using summary data from large-scale genome-wide association studies (GWAS) and validated the strength and relevance of the genetic instrument for exposure levels during pregnancy. Logistic regression was used to estimate the odds ratio (OR) of CHD per 1 standard deviation (SD) higher GRS. Results for the three cohorts were combined using random-effects meta-analyses. We performed several sensitivity analyses including multivariable MR to check the robustness of our findings.

RESULTS

The GRSs associated with the exposures during pregnancy in all three cohorts. The associations of the GRS for maternal BMI with offspring CHD (pooled OR (95% confidence interval) per 1SD higher GRS: 0.95 (0.88, 1.03)), lifetime smoking (pooled OR: 1.01 (0.93, 1.09)) and alcoholic drinks per week (pooled OR: 1.06 (0.98, 1.15)) were close to the null. Sensitivity analyses yielded similar results.

CONCLUSIONS

Our results do not provide robust evidence of an effect of maternal BMI, smoking or alcohol on offspring CHDs. However, results were imprecise. Our findings need to be replicated, and highlight the need for more and larger studies with maternal and offspring genotype and offspring CHD data.

Prenatal Mercury Exposure and Infant Weight Trajectories in a UK Observational Birth Cohort

Mercury is highly toxic metal found in trace quantities in common foods. There is concern that exposure during pregnancy could impair infant development. Epidemiological evidence is mixed, but few studies have examined postnatal growth. Differences in nutrition, exposures, and the living environment after birth may make it easier to detect a negative impact from mercury toxicity on infant growth. This study includes 544 mother-child pairs from the Avon Longitudinal Study of Parents and Children. Blood mercury was measured in early pregnancy and infant weight at 10 intervals between 4 and 61 months. Mixed-effect models were used to estimate the change in infant weight associated with prenatal mercury exposure. The estimated difference in monthly weight gain was -0.02 kg per 1 standard deviation increase in Hg (95% confidence intervals: -0.10 to 0.06 kg). When restricted to the 10th decile of Hg, the association with weight at each age level was consistently negative but with wide confidence intervals. The lack of evidence for an association may indicate that at Hg levels in this cohort (median 1.9 µg/L) there is minimal biological impact, and the effect is too small to be either clinically relevant or detectable.

Maternal vitamin D during pregnancy and offspring autism and autism-associated traits: a prospective cohort study

BACKGROUND

There has been a growing interest in the association between maternal levels of vitamin D during pregnancy and offspring autism. However, whether any associations reflect causal effects is still inconclusive.

METHODS

We used data from a UK-based pregnancy cohort study (Avon Longitudinal Study of Parents and Children) comprising 7689 births between 1991 and 1992 with maternal blood vitamin D levels recorded during pregnancy and at least one recorded outcome measure, including autism diagnosis and autism-associated traits. The association between each outcome with seasonal and gestational age-adjusted maternal serum 25-hydroxyvitamin D during pregnancy was estimated using confounder-adjusted regression models. Multiple imputation was used to account for missing data, and restricted cubic splines were used to investigate nonlinear associations. Mendelian randomization was used to strengthen causal inference.

RESULTS

No strong evidence of an association between maternal serum 25-hydroxyvitamin D during pregnancy and any offspring autism-associated outcome was found using multivariable regression analysis (autism diagnosis: adjusted OR = 0.98, 95% CI = 0.90-1.06), including with multiple imputation (autism diagnosis: adjusted OR = 0.99, 95% CI = 0.93-1.06), and no evidence of a causal effect was suggested by Mendelian randomization (autism diagnosis: causal OR = 1.08, 95% CI = 0.46-2.55). Some evidence of increased odds of autism-associated traits at lower levels of maternal serum 25-hydroxyvitamin D was found using spline analysis.

LIMITATIONS

Our study was potentially limited by low power, particularly for diagnosed autism cases as an outcome. The cohort may not have captured the extreme lows of the distribution of serum 25-hydroxyvitamin D, and our analyses may have been biased by residual confounding and missing data.

CONCLUSIONS

The present study found no strong evidence of a causal link between maternal vitamin D levels in pregnancy and offspring diagnosis or traits of autism.

"Late-onset" ADHD symptoms in young adulthood: Is this ADHD?

Objective: We investigated whether "late-onset" ADHD that emerges in adolescence/adulthood is similar in risk factor profile to: (1) child-onset ADHD, but emerges later because of scaffolding/compensation from childhood resources; and (2) depression, because it typically onsets in adolescence/adulthood and shows symptom and genetic overlaps with ADHD. Methods: We examined associations between late-onset ADHD and ADHD risk factors, cognitive tasks, childhood resources and depression risk factors in a population-based cohort followed-up to age 25 years (N=4224-9764). Results: Parent-rated late-onset ADHD was like child-onset persistent ADHD in associations with ADHD polygenic risk scores and cognitive task performance, although self-rated late-onset ADHD was not. Late-onset ADHD was associated with higher levels of childhood resources than child-onset ADHD and did not show strong evidence of association with depression risk factors. Conclusions: Late-onset ADHD shares characteristics with child-onset ADHD when parent-rated, but differences for self-reports require investigation. Childhood resources may delay the onset of ADHD.

Associations Between Pregnancy-Related Predisposing Factors for Offspring Neurodevelopmental Conditions and Parental Genetic Liability to Attention-Deficit/Hyperactivity Disorder, Autism, and Schizophrenia: The Norwegian Mother, Father and Child Cohort Study (MoBa)

Importance

Several maternal exposures during pregnancy are considered predisposing factors for offspring neurodevelopmental conditions. However, many of these exposures may be noncausal and biased by maternal genetic liability.

Objective

To assess whether pregnancy-related predisposing factors for offspring neurodevelopmental conditions are associated with maternal genetic liability for attention-deficit/hyperactivity disorder (ADHD), autism, and schizophrenia and to compare associations for maternal genetic liability with those for paternal genetic liability, which could indicate that paternal exposures are not suitable negative controls for maternal exposures.

Design, Setting, and Participants

The Norwegian Mother, Father and Child Cohort Study (MoBa) is a population-based pregnancy cohort that recruited parents from June 1999 to December 2008. Polygenic scores (PGS) for ADHD, autism, and schizophrenia were derived in mothers and fathers. The associations between maternal PGS and 37 pregnancy-related measures were estimated, and these results were compared with those from paternal PGS predicting paternal measures during the mother's pregnancy. Analysis took place between March 2021 and March 2022.

Exposures

PGS for ADHD, autism, and schizophrenia, calculated (using discovery effect size estimates and threshold of P < .05) from the largest available genome-wide association studies.

Main Outcomes and Measures

Self-reported pregnancy-related measures capturing lifestyle behaviors, metabolism, infectious and autoimmune diseases, other physical health conditions, and medication use.

Results

Data were available for up to 14 539 mothers (mean [SD] age, 30.00 [4.45] years) and 14 897 fathers (mean [SD] age, 32.46 [5.13] years) of European ancestry. Modest but robust associations were observed between specific pregnancy-related measures and maternal PGS, including ADHD PGS with asthma (odds ratio [OR], 1.15 [95% CI, 1.06-1.25]), smoking (OR, 1.26 [95% CI, 1.19-1.33]), prepregnancy body mass index (β, 0.25 [95% CI, 0.18-0.31]), pregnancy weight gain (β, 0.20 [95% CI, 0.10-0.30]), taking folate (OR, 0.92 [95% CI, 0.88-0.96]), and not taking supplements (OR, 1.09 [95% CI, 1.04-1.14]). Schizophrenia PGS was associated with coffee consumption (OR, 1.09 [95% CI, 1.05-1.12]), smoking (OR, 1.12 [95% CI, 1.06-1.19]), prepregnancy body mass index (β, -0.18 [95% CI, -0.25 to -0.11]), and pregnancy weight gain (β, 0.17 [95% CI, 0.07-0.27]). All 3 PGSs associated with symptoms of depression/anxiety (ADHD: OR, 1.15 [95% CI, 1.09-1.22]; autism: OR, 1.13 [95% CI, 1.06-1.19]; schizophrenia: OR, 1.13 [95% CI, 1.07-1.20]). Associations were largely consistent for maternal and paternal PGS, except ADHD PGS and smoking (fathers: OR, 1.13 [95% CI, 1.09-1.17]).

Conclusions and Relevance

In this study, genetic liability to neurodevelopmental conditions that is passed from mothers to children was associated with several pregnancy-related factors and may therefore confound associations between these pregnancy-related factors and offspring neurodevelopment that have previously been thought to be causal. It is crucial that future study designs account for genetic confounding to obtain valid causal inferences so that accurate advice can be given to pregnant individuals.

Smoking and infertility: multivariable regression and Mendelian randomization analyses in the Norwegian Mother, Father and Child Cohort Study

OBJECTIVE

To investigate the association between smoking and infertility.

DESIGN

Prospective study.

SETTING

Nationwide cohort.

PATIENTS

28,606 women and 27,096 men with questionnaire and genotype information from the Norwegian Mother, Father, and Child Cohort Study.

INTERVENTION

Self-reported information on smoking (having ever smoked [both sexes], age at initiation [women only], cessation [women only], and cigarettes/week in current smokers [both sexes]) was gathered. Genetically predetermined levels or likelihood of presenting these traits were estimated for Mendelian randomization.

MAIN OUTCOME MEASURE

Infertility (time-to-pregnancy ≥12 months).

RESULTS

Having ever smoked was unrelated to infertility in women or men. Higher smoking intensity in women was associated with greater infertility odds (+1 standard deviation [SD, 48 cigarettes/week]: odds ratio [OR]crude, 1.19; 95% confidence interval [CI] 1.11-1.28; ORadjusted 1.12; 95% CI, 1.03-1.21), also after adjusting for the partner's tobacco use. Later smoking initiation (+1 SD [3.2 years]: ORcrude, 0.94; 95% CI, 0.88-0.99; ORadjusted 0.89; 95% CI, 0.84-0.95) and smoking cessation (vs. not quitting: ORcrude, 0.83; 95% CI, 0.75-0.91; ORadjusted, 0.83; 95% CI, 0.75-0.93) were linked to decreased infertility in women. Nevertheless, Mendelian randomization results were not directionally consistent for smoking intensity and cessation and were estimated imprecisely in the 2-sample approach. In men, greater smoking intensity was not robustly associated with infertility in multivariable regression and Mendelian randomization.

CONCLUSIONS

We did not find robust evidence of an effect of smoking on infertility. This may be due to a true lack of effect, weak genetic instruments, or other kinds of confounding.

Decline in attention-deficit hyperactivity disorder traits over the life course in the general population: trajectories across five population birth cohorts spanning ages 3 to 45 years

BACKGROUND

Trajectories of attention-deficit hyperactivity disorder (ADHD) traits spanning early childhood to mid-life have not been described in general populations across different geographical contexts. Population trajectories are crucial to better understanding typical developmental patterns.

METHODS

We combined repeated assessments of ADHD traits from five population-based cohorts, spanning ages 3 to 45 years. We used two measures: (i) the Strengths and Difficulties Questionnaire (SDQ) hyperactive-inattentive subscale (175 831 observations, 29 519 individuals); and (ii) scores from DSM-referenced scales (118 144 observations, 28 685 individuals). Multilevel linear spline models allowed for non-linear change over time and differences between cohorts and raters (parent/teacher/self).

RESULTS

Patterns of age-related change differed by measure, cohort and country: overall, SDQ scores decreased with age, most rapidly declining before age 8 years (-0.157, 95% CI: -0.170, -0.144 per year). The pattern was generally consistent using DSM scores, although with greater between-cohort variation. DSM scores decreased most rapidly between ages 14 and 17 years (-1.32%, 95% CI: -1.471, -1.170 per year). Average scores were consistently lower for females than males (SDQ: -0.818, 95% CI: -0.856, -0.780; DSM: -4.934%, 95% CI: -5.378, -4.489). This sex difference decreased over age for both measures, due to an overall steeper decrease for males.

CONCLUSIONS

ADHD trait scores declined from childhood to mid-life, with marked variation between cohorts. Our results highlight the importance of taking a developmental perspective when considering typical population traits. When interpreting changes in clinical cohorts, it is important to consider the pattern of expected change within the general population, which is influenced by cultural context and measurement.

Does smoking cause lower educational attainment and general cognitive ability? Triangulation of causal evidence using multiple study designs

BACKGROUND

Observational studies have found associations between smoking and both poorer cognitive ability and lower educational attainment; however, evaluating causality is challenging. We used two complementary methods to explore this.

METHODS

We conducted observational analyses of up to 12 004 participants in a cohort study (Study One) and Mendelian randomisation (MR) analyses using summary and cohort data (Study Two). Outcome measures were cognitive ability at age 15 and educational attainment at age 16 (Study One), and educational attainment and fluid intelligence (Study Two).

RESULTS

Study One: heaviness of smoking at age 15 was associated with lower cognitive ability at age 15 and lower educational attainment at age 16. Adjustment for potential confounders partially attenuated findings (e.g. fully adjusted cognitive ability β -0.736, 95% CI -1.238 to -0.233, p = 0.004; fully adjusted educational attainment β -1.254, 95% CI -1.597 to -0.911, p < 0.001). Study Two: MR indicated that both smoking initiation and lifetime smoking predict lower educational attainment (e.g. smoking initiation to educational attainment inverse-variance weighted MR β -0.197, 95% CI -0.223 to -0.171, p = 1.78 × 10^-49). Educational attainment results were robust to sensitivity analyses, while analyses of general cognitive ability were less so.

CONCLUSION

We find some evidence of a causal effect of smoking on lower educational attainment, but not cognitive ability. Triangulation of evidence across observational and MR methods is a strength, but the genetic variants associated with smoking initiation may be pleiotropic, suggesting caution in interpreting these results. The nature of this pleiotropy warrants further study.

Using Mendelian randomization to explore the gateway hypothesis: possible causal effects of smoking initiation and alcohol consumption on substance use outcomes

BACKGROUND AND AIMS

Initial use of drugs such as tobacco and alcohol may lead to subsequent more problematic drug use-the 'gateway' hypothesis. However, observed associations may be due to a shared underlying risk factor, such as trait impulsivity. We used bidirectional Mendelian randomization (MR) to test the gateway hypothesis.

DESIGN

Our main method was inverse-variance weighted (IVW) MR, with other methods included as sensitivity analyses (where consistent results across methods would raise confidence in our primary results). MR is a genetic instrumental variable approach used to support stronger causal inference in observational studies.

SETTING AND PARTICIPANTS

Genome-wide association summary data among European ancestry individuals for smoking initiation, alcoholic drinks per week, cannabis use and dependence, cocaine and opioid dependence (n = 1749-1 232 091).

MEASUREMENTS

Genetic variants for exposure.

FINDINGS

We found evidence of causal effects from smoking initiation to increased drinks per week [(IVW): β = 0.06; 95% confidence interval (CI) = 0.03-0.09; P = 9.44 × 10-06 ], cannabis use [IVW: odds ratio (OR) = 1.34; 95% CI = 1.24-1.44; P = 1.95 × 10-14 ] and cannabis dependence (IVW: OR = 1.68; 95% CI = 1.12-2.51; P = 0.01). We also found evidence of an effect of cannabis use on the increased likelihood of smoking initiation (IVW: OR = 1.39; 95% CI = 1.08-1.80; P = 0.01). We did not find evidence of an effect of drinks per week on other substance use outcomes, except weak evidence of an effect on cannabis use (IVW: OR = 0.55; 95% CI = 0.16-1.93; P-value = 0.35). We found weak evidence of an effect of opioid dependence on increased drinks per week (IVW: β = 0.002; 95% CI = 0.0005-0.003; P = 8.61 × 10-03 ).

CONCLUSIONS

Bidirectional Mendelian randomization testing of the gateway hypothesis reveals that smoking initiation may lead to increased alcohol consumption, cannabis use and cannabis dependence. Cannabis use may also lead to smoking initiation and opioid dependence to alcohol consumption. However, given that tobacco and alcohol use typically begin before other drug use, these results may reflect a shared risk factor or a bidirectional effect for cannabis use and opioid dependence.

Trans-ethnic Mendelian-randomization study reveals causal relationships between cardiometabolic factors and chronic kidney disease

BACKGROUND

This study was to systematically test whether previously reported risk factors for chronic kidney disease (CKD) are causally related to CKD in European and East Asian ancestries using Mendelian randomization.

METHODS

A total of 45 risk factors with genetic data in European ancestry and 17 risk factors in East Asian participants were identified as exposures from PubMed. We defined the CKD by clinical diagnosis or by estimated glomerular filtration rate of <60 ml/min/1.73 m2. Ultimately, 51 672 CKD cases and 958 102 controls of European ancestry from CKDGen, UK Biobank and HUNT, and 13 093 CKD cases and 238 118 controls of East Asian ancestry from Biobank Japan, China Kadoorie Biobank and Japan-Kidney-Biobank/ToMMo were included.

RESULTS

Eight risk factors showed reliable evidence of causal effects on CKD in Europeans, including genetically predicted body mass index (BMI), hypertension, systolic blood pressure, high-density lipoprotein cholesterol, apolipoprotein A-I, lipoprotein(a), type 2 diabetes (T2D) and nephrolithiasis. In East Asians, BMI, T2D and nephrolithiasis showed evidence of causality on CKD. In two independent replication analyses, we observed that increased hypertension risk showed reliable evidence of a causal effect on increasing CKD risk in Europeans but in contrast showed a null effect in East Asians. Although liability to T2D showed consistent effects on CKD, the effects of glycaemic phenotypes on CKD were weak. Non-linear Mendelian randomization indicated a threshold relationship between genetically predicted BMI and CKD, with increased risk at BMI of >25 kg/m2.

CONCLUSIONS

Eight cardiometabolic risk factors showed causal effects on CKD in Europeans and three of them showed causality in East Asians, providing insights into the design of future interventions to reduce the burden of CKD.

Associations between alcohol use and accelerated biological ageing

Harmful alcohol use is a leading cause of premature death and is associated with age-related disease. Biological ageing is highly variable between individuals and may deviate from chronological ageing, suggesting that biomarkers of biological ageing (derived from DNA methylation or brain structural measures) may be clinically relevant. Here, we investigated the relationships between alcohol phenotypes and both brain and DNA methylation age estimates. First, using data from UK Biobank and Generation Scotland, we tested the association between alcohol consumption (units/week) or hazardous use (Alcohol Use Disorders Identification Test [AUDIT] scores) and accelerated brain and epigenetic ageing in 20,258 and 8051 individuals, respectively. Second, we used Mendelian randomisation (MR) to test for a causal effect of alcohol consumption levels and alcohol use disorder (AUD) on biological ageing. Alcohol use showed a consistent positive association with higher predicted brain age (AUDIT-C: β = 0.053, p = 3.16 × 10-13 ; AUDIT-P: β = 0.052, p = 1.6 × 10-13 ; total AUDIT score: β = 0.062, p = 5.52 × 10-16 ; units/week: β = 0.078, p = 2.20 × 10-16 ), and two DNA methylation-based estimates of ageing, GrimAge (units/week: β = 0.053, p = 1.48 × 10-7 ) and PhenoAge (units/week: β = 0.077, p = 2.18x10-10 ). MR analyses revealed limited evidence for a causal effect of AUD on accelerated brain ageing (β = 0.118, p = 0.044). However, this result should be interpreted cautiously as the significant effect was driven by a single genetic variant. We found no evidence for a causal effect of alcohol consumption levels on accelerated biological ageing. Future studies investigating the mechanisms associating alcohol use with accelerated biological ageing are warranted.

Mendelian randomisation for psychiatry: how does it work, and what can it tell us?

The successful prevention of mental illness relies upon the identification of causal, modifiable risk factors. However, observational evidence exploring such risk factors often produces contradictory results and randomised control trials are often expensive, time-consuming or unethical to conduct. Mendelian randomisation (MR) is a complementary approach that uses naturally occurring genetic variation to identify possible causal effects between a risk factor and an outcome in a time-efficient and low-cost manner. MR utilises genetic variants as instrumental variables for the risk factor of interest. MR studies are becoming more frequent in the field of psychiatry, warranting a reflection upon both the possibilities and the pitfalls. In this Perspective, we consider several limitations of the MR method that are of particular relevance to psychiatry. We also present new MR methods that have exciting applications to questions of mental illness. While we believe that MR can make an important contribution to the field of psychiatry, we also wish to emphasise the importance of clear causal questions, thorough sensitivity analyses, and triangulation with other forms of evidence.

Exploring the Relationship Between Schizophrenia and Cardiovascular Disease: A Genetic Correlation and Multivariable Mendelian Randomization Study

Individuals with schizophrenia have a reduced life-expectancy compared to the general population, largely due to an increased risk of cardiovascular disease (CVD). Clinical and epidemiological studies have been unable to unravel the nature of this relationship. We obtained summary-data of genome-wide-association studies of schizophrenia (N = 130 644), heart failure (N = 977 323), coronary artery disease (N = 332 477), systolic and diastolic blood pressure (N = 757 601), heart rate variability (N = 46 952), QT interval (N = 103 331), early repolarization and dilated cardiomyopathy ECG patterns (N = 63 700). We computed genetic correlations and conducted bi-directional Mendelian randomization (MR) to assess causality. With multivariable MR, we investigated whether causal effects were mediated by smoking, body mass index, physical activity, lipid levels, or type 2 diabetes. Genetic correlations between schizophrenia and CVD were close to zero (-0.02-0.04). There was evidence that liability to schizophrenia causally increases heart failure risk. This effect remained consistent with multivariable MR. There was also evidence that liability to schizophrenia increases early repolarization pattern, largely mediated by BMI and lipids. Finally, there was evidence that liability to schizophrenia increases heart rate variability, a direction of effect contrasting clinical studies. There was weak evidence that higher systolic blood pressure increases schizophrenia risk. Our finding that liability to schizophrenia increases heart failure is consistent with the notion that schizophrenia involves a systemic dysregulation of the body with detrimental effects on the heart. To decrease cardiovascular mortality among individuals with schizophrenia, priority should lie with optimal treatment in early stages of psychosis.

Maternal and child genetic liability for smoking and caffeine consumption and child mental health: an intergenerational genetic risk score analysis in the ALSPAC cohort

BACKGROUND AND AIMS

Previous studies suggest an association between maternal tobacco and caffeine consumption during and outside of pregnancy and offspring mental health. We aimed to separate effects of the maternal environment (intrauterine or postnatal) from pleiotropic genetic effects.

DESIGN

Secondary analysis of a longitudinal study. We (i) validated smoking and caffeine genetic risk scores (GRS) derived from published genome-wide association study (GWAS) for use during pregnancy, (ii) compared estimated effects of maternal and offspring GRS on childhood mental health outcomes and (iii) tested associations between maternal and offspring GRS on their respective outcomes.

SETTING

We used data from a longitudinal birth cohort study from England, the Avon Longitudinal Study of Parents and Children (ALSPAC).

PARTICIPANTS

Our sample included 7921 mothers and 7964 offspring.

MEASUREMENTS

Mental health and non-mental health phenotypes were derived from questionnaires and clinical assessments: 79 maternal phenotypes assessed during and outside of pregnancy and 71 offspring phenotypes assessed in childhood (<10 years) and adolescence (11-18 years).

FINDINGS

The maternal smoking and caffeine GRS were associated with maternal smoking and caffeine consumption during pregnancy (2nd trimester: Psmoking  = 3.0 × 10-7 , Pcaffeine  = 3.28 × 10-5 ). Both the maternal and offspring smoking GRS showed evidence of association with reduced childhood anxiety symptoms (βmaternal  = -0.033; βoffspring  = -0.031) and increased conduct disorder symptoms (βmaternal  = 0.024; βoffspring  = 0.030), after correcting for multiple testing. Finally, the maternal and offspring smoking GRS were associated with phenotypes related to sensation seeking behaviours in mothers and adolescence (e.g. increased symptoms of externalising disorders, extraversion and monotony avoidance). The caffeine GRS showed weaker evidence for associations with mental health outcomes.

CONCLUSIONS

We did not find strong evidence that maternal smoking and caffeine genetic risk scores have a causal effect on offspring mental health outcomes. Our results confirm that the smoking genetic risk scores also captures liability for sensation seeking personality traits.

Validation of the short Mood and Feelings Questionnaire in young adulthood

Depression often onsets in adolescence and is associated with recurrence in adulthood. There is a need to identify and monitor depression symptoms across adolescence and into young adulthood. The short Mood and Feelings Questionnaire (sMFQ) is commonly used to measure depression symptoms in adolescence but has not been validated in young adulthood. This study aimed to (1) examine whether the sMFQ is valid in young adulthood, and (2) identify cut-points best capturing DSM-5 depression diagnosis at age 25 METHODS: The sample included participants in the Avon Longitudinal Study of Parents and Children (ALSPAC) at age 25 (n = 4098). Receiver Operating Characteristic analyses examined how well the self-rated sMFQ discriminates between cases and non-cases of DSM-5 Major Depressive Disorder (MDD) classified using the self-rated Development and Well Being Assessment. Sensitivity and specificity values were used to identify cut-points on the sMFQ RESULTS: The sMFQ had high accuracy for discriminating MDD cases from non-cases at age 25. The commonly used cut-point in adolescence (≥12) performed well at this age, best balancing sensitivity and specificity. However, a lower cut-point (≥10) may be appropriate when favouring sensitivity over specificity e.g., in context of screening. Sensitivity analyses suggested similar results for males and females LIMITATIONS: ALSPAC is a longitudinal population cohort that suffers from non-random attrition CONCLUSIONS: The sMFQ is a valid measure of depression in young adults in the general population. It can be used to screen for and monitor depression across adolescence and early adulthood.

Mental Health as a Mediator of the Association Between Educational Inequality and Cardiovascular Disease: A Mendelian Randomization Study

Background

Education is inversely associated with cardiovascular disease (CVD). Several mediators of this have been established; however, a proportion of the protective effect remains unaccounted for. Mental health is a proposed mediator, but current evidence is mixed and subject to bias from confounding factors and reverse causation. Mendelian randomization is an instrumental variable technique that uses genetic proxies for exposures and mediators to reduce such bias.

Methods and Results

We performed logistic regression and 2‐step Mendelian randomization analyses using UK Biobank data and genetic summary statistics to investigate whether educational attainment affects risk of mental health disorders. We then performed mediation analyses to explore whether mental health disorders mediate the association between educational attainment and cardiovascular risk. Higher levels of educational attainment were associated with reduced depression, anxiety, and CVD in observational analyses (odds ratio [OR], 0.79 [95% CI, 0.77–0.81], 0.76 [95% CI, 0.73–0.79], and 0.75 [95% CI, 0.74–0.76], respectively), and Mendelian randomization analyses provided evidence of causality (OR, 0.72 [95% CI, 0.67–0.77], 0.50 [95% CI, 0.42–0.59], and 0.62 [95% CI, 0.58–0.66], respectively). Both anxiety and depression were associated with CVD in observational analyses (OR, 1.63 [95% CI, 1.49–1.79] and 1.70 [95% CI, 1.59–1.82], respectively) but only depression showed evidence of causality in the Mendelian randomization analyses (OR, 1.09; 95% CI, 1.03–1.15). An estimated 2% of the total protective effect of education on CVD was mediated by depression.

Conclusions

Higher levels of educational attainment protect against mental health disorders, and reduced depression accounts for a small proportion of the total protective effect of education on CVD.

Variable Emergence of Autism Spectrum Disorder Symptoms From Childhood to Early Adulthood

OBJECTIVE

Autism spectrum disorder (ASD) is currently considered an early-onset neurodevelopmental condition. Follow-up studies of clinic-ascertained autism suggest that autistic symptoms typically decline with age, although symptom improvement is limited for some. To date there have been no population-based prospective studies investigating the natural history of autistic symptoms from childhood to adulthood. The aim of this study was to characterize the development and heterogeneity of autistic symptoms in a population-based cohort from childhood to age 25.

METHODS

Data were analyzed in a prospective U.K. population-based cohort (ALSPAC). Trajectories were derived using five assessments of the parent-rated Social and Communication Disorders Checklist (SCDC) spanning ages 7-25. Additional measures were used to validate symptom trajectories.

RESULTS

Three distinct SCDC symptom trajectory classes were identified: low (88.5%), declining (5.0%), and late-emerging (6.5%). Both the declining and late-emerging trajectory classes were associated with child and adult ASD measures, low IQ, communication problems, peer problems, and worse adult functioning compared with the low trajectory class. Male sex was associated with a higher likelihood of being in the declining trajectory class (odds ratio=2.84, 95% CI=2.19, 3.69). This sex difference was not observed in the late-emerging class (odds ratio=1.00, 95% CI=0.80, 1.24) compared with the low trajectory class.

CONCLUSIONS

ASD symptom levels that emerged early tended to decline across development, although impairment was still present in adulthood for some. For others, autistic symptoms emerged across adolescence and adulthood. This challenges our current understanding that ASD symptoms inevitably first manifest early in development.

Investigating the validity of the Strengths and Difficulties Questionnaire to assess ADHD in young adulthood

Attention Deficit Hyperactivity Disorder (ADHD) symptoms typically onset early and persist into adulthood for many. Robust investigation of symptom continuity and discontinuity requires repeated assessments using the same measure, but research is lacking into whether measures used to assess ADHD symptoms in childhood are also valid in adulthood. The Strengths and Difficulties Questionnaire (SDQ) is widely used to assess ADHD symptoms in children, but little is known about its utility in adulthood. The aim of this study was to assess the validity of the SDQ hyperactivity/ADHD subscale to distinguish between cases and non-cases of DSM-5 ADHD at age 25 years in a UK population cohort (N = 4121). ADHD diagnosis was derived using the Barkley Adult ADHD Rating Scale-IV. Analyses suggested that the self-rated SDQ ADHD subscale had high validity in distinguishing ADHD cases/non-cases in young adulthood (area under the curve=0.90, 95% CI=0.87-0.93) and indicated a lower cut-point for identifying those who may have an ADHD diagnosis in this age group compared to that currently recommended for younger ages. Findings were similar for parent-reports. Our findings suggest that the SDQ is suitable for ADHD research across different developmental periods, which will aid the robust investigation of ADHD from childhood to young adulthood.

Risk factors mediating the effect of body mass index and waist-to-hip ratio on cardiovascular outcomes: Mendelian randomization analysis

BACKGROUND

Higher body mass index (BMI) and waist-to-hip ratio (WHR) increase the risk of cardiovascular disease, but the extent to which this is mediated by blood pressure, diabetes, lipid traits, and smoking is not fully understood.

METHODS

Using consortia and UK Biobank genetic association summary data from 140,595 to 898,130 participants predominantly of European ancestry, Mendelian randomization mediation analysis was performed to investigate the degree to which systolic blood pressure (SBP), diabetes, lipid traits, and smoking mediated an effect of BMI and WHR on the risk of coronary artery disease (CAD), peripheral artery disease (PAD) and stroke.

RESULTS

The odds ratio of CAD per 1-standard deviation increase in genetically predicted BMI was 1.49 (95% CI 1.39 to 1.60). This attenuated to 1.34 (95% CI 1.24 to 1.45) after adjusting for genetically predicted SBP (proportion mediated 27%, 95% CI 3% to 50%), to 1.27 (95% CI 1.17 to 1.37) after adjusting for genetically predicted diabetes (41% mediated, 95% CI 18% to 63%), to 1.47 (95% CI 1.36 to 1.59) after adjusting for genetically predicted lipids (3% mediated, 95% -23% to 29%), and to 1.46 (95% CI 1.34 to 1.58) after adjusting for genetically predicted smoking (6% mediated, 95% CI -20% to 32%). Adjusting for all the mediators together, the estimate attenuated to 1.14 (95% CI 1.04 to 1.26; 66% mediated, 95% CI 42% to 91%). A similar pattern was observed when considering genetically predicted WHR as the exposure, and PAD or stroke as the outcome.

CONCLUSIONS

Measures to reduce obesity will lower the risk of cardiovascular disease primarily by impacting downstream metabolic risk factors, particularly diabetes and hypertension. Reduction of obesity prevalence alongside control and management of its mediators is likely to be most effective for minimizing the burden of obesity.

The Effect of Attention Deficit/Hyperactivity Disorder on Physical Health Outcomes: A 2-Sample Mendelian Randomization Study

Attention-deficit/hyperactivity disorder (ADHD) is associated with a broad range of physical health problems. Using different research designs to test whether ADHD has a causal role in these associations is important because comorbid health problems increase the serious social and economic impacts of ADHD. We used 2-sample Mendelian randomization (MR) to infer causal relationships between ADHD and previously implicated physical health conditions. Different MR methods were used to test the robustness and plausibility of our findings. Consistent findings underwent bidirectional and multivariable MR. We found evidence of ADHD having a causal effect on childhood obesity (odds ratio = 1.29, 95% confidence interval: 1.02, 1.63) and coronary artery disease (odds ratio = 1.11, 95% confidence interval: 1.03, 1.19) with consistent results across MR approaches. There was additional MR evidence for a bidirectional relationship between ADHD and childhood obesity. The relationship with coronary artery disease attenuated when controlling for childhood obesity. There was little evidence for inferring a causal effect on other cardiometabolic, autoimmune, allergic, and neurological diseases. Our findings strengthen the argument for effective treatment of children with ADHD, and suggest that clinicians who manage ADHD need to be aware of the risk of childhood obesity to reduce future risks of coronary artery disease.

Characterization of alcohol polygenic risk scores in the context of mental health outcomes: Within-individual and intergenerational analyses in the Avon Longitudinal Study of Parents and Children

BACKGROUND

Heavy alcohol consumption often co-occurs with mental health problems; this could be due to confounding, shared biological mechanisms, or causal effects. Polygenic risk scores (PRS) for alcohol use can be used to explore this association at critical life stages.

DESIGN

We characterized a PRS reliably associated with patterns of adult alcohol consumption by 1) validating whether it predicts own alcohol use at different life-stages (pregnancy, adolescence) of interest for mental health impact. Additionally, we explored associations of alcohol PRS on mental health phenotypes 2) within-individuals (using own alcohol PRS on own phenotypes) and 3) intergenerationally (using maternal alcohol PRS on offspring phenotypes). We used data from the Avon Longitudinal Study of Parents and Children (ALSPAC) (n = 960-7841). Additional substance abuse behaviors and mental health/behavioral outcomes were investigated (alcohol phenotypes n = 22; health phenotypes n = 91).

FINDINGS

Maternal alcohol PRS was associated with consumption during pregnancy (strongest signal: alcohol frequency at 18 weeks' gestation: β = 0.041, 95%CI = 0.0.02-0.06), p = 1.01 × 10-5, adjusted R2 = 1.6 %), offspring alcohol PRS did not predict offspring alcohol consumption. We found evidence for an association of maternal alcohol PRS with own perinatal depression (OR  = 1.10, 95% CI = 1.02 to 1.18, p = 0.022) and decreased offspring intellectual ability (β=-0.209, 95% CI -0.38 to -0.04, p= 0.016).

CONCLUSIONS

These alcohol PRS are a valid proxy for maternal alcohol use in pregnancy. Offspring alcohol PRS was not associated with drinking in adolescence. Consistently with results from different study designs, we found evidence that maternal alcohol PRS are associated with both prenatal depression and decreased offspring intellectual ability.

Association of genetic liability to smoking initiation with e-cigarette use in young adults: A cohort study

BACKGROUND

Tobacco smoking and e-cigarette use are strongly associated, but it is currently unclear whether this association is causal, or due to shared factors that influence both behaviours such as a shared genetic liability. The aim of this study was to investigate whether polygenic risk scores (PRS) for smoking initiation are associated with ever use of e-cigarettes.

METHODS AND FINDINGS

Smoking initiation PRS were calculated for young adults (N = 7,859, mean age = 24 years, 51% male) of European ancestry in the Avon Longitudinal Study of Parents and Children, a prospective birth cohort study initiated in 1991. PRS were calculated using the GWAS & Sequencing Consortium of Alcohol and Nicotine use (GSCAN) summary statistics. Five thresholds ranging from 5 × 10-8 to 0.5 were used to calculate 5 PRS for each individual. Using logistic regression, we investigated the association between smoking initiation PRS and the main outcome, self-reported e-cigarette use (n = 2,894, measured between 2016 and 2017), as well as self-reported smoking initiation and 8 negative control outcomes (socioeconomic position at birth, externalising disorders in childhood, and risk-taking in young adulthood). A total of 878 young adults (30%) had ever used e-cigarettes at 24 years, and 150 (5%) were regular e-cigarette users at 24 years. We observed positive associations of similar magnitude between smoking initiation PRS (created using the p < 5 × 10-8 threshold) and both smoking initiation (odds ratio (OR) = 1.29, 95% CI 1.19 to 1.39, p < 0.001) and ever e-cigarette use (OR = 1.24, 95% CI 1.14 to 1.34, p < 0.001) by the age of 24 years, indicating that a genetic predisposition to smoking initiation is associated with an increased risk of using e-cigarettes. At lower p-value thresholds, we observed an association between smoking initiation PRS and ever e-cigarette use among never smokers. We also found evidence of associations between smoking initiation PRS and some negative control outcomes, particularly when less stringent p-value thresholds were used to create the PRS, but also at the strictest threshold (e.g., gambling, number of sexual partners, conduct disorder at 7 years, and parental socioeconomic position at birth). However, this study is limited by the relatively small sample size and potential for collider bias.

CONCLUSIONS

Our results indicate that there may be a shared genetic aetiology between smoking and e-cigarette use, and also with socioeconomic position, externalising disorders in childhood, and risky behaviour more generally. This indicates that there may be a common genetic vulnerability to both smoking and e-cigarette use, which may reflect a broad risk-taking phenotype.

Bidirectional effects between loneliness, smoking and alcohol use: evidence from a Mendelian randomization study

BACKGROUND AND AIMS

Loneliness is associated with cigarette smoking and problematic alcohol use. Observational evidence suggests these associations arise because loneliness increases substance use; however, there is potential for reverse causation (problematic drinking damages social networks, leading to loneliness). With conventional epidemiological methods, controlling for (residual) confounding and reverse causality is difficult. This study applied Mendelian randomization (MR) to assess bidirectional causal effects among loneliness, smoking behaviour and alcohol (mis)use. MR uses genetic variants as instrumental variables to estimate the causal effect of an exposure on an outcome, if the assumptions are satisfied.

DESIGN

Our primary method was inverse-variance weighted (IVW) regression and the robustness of these findings was assessed with five different sensitivity methods.

SETTING

European ancestry.

PARTICIPANTS

Summary-level data were drawn from the largest available independent genome-wide association studies (GWAS) of loneliness (n = 511 280), smoking (initiation (n = 249 171), cigarettes per day (n = 249 171) and cessation (n = 143 852), alcoholic drinks per week (n = 226 223) and alcohol dependence (n = 46 568).

MEASUREMENTS

Genetic variants predictive of the exposure variable were selected as instruments from the respective GWAS.

FINDINGS

There was weak evidence of increased loneliness leading to higher likelihood of initiating smoking, smoking more cigarettes, and a lower likelihood of quitting smoking. Additionally, there was evidence that initiating smoking increases loneliness [IVW, β = 0.30, 95% confidence interval (CI) = 0.22-0.38, P = 2.8 × 10^-13 ]. We found no clear evidence for a causal effect of loneliness on drinks per week (IVW, β = 0.01, 95% CI = -0.11, 0.13, P = 0.865) or alcohol dependence (IVW, β = 0.09, 95% CI = -0.19, 0.36, P = 0.533) nor of alcohol use on loneliness (drinks per week IVW, β = 0.09, 95% CI = -0.02, 0.22, P = 0.076; alcohol dependence IVW, β = 0.06, 95% CI = -0.02, 0.13, P  =  0.162).

CONCLUSIONS

There appears to be tentative evidence for causal, bidirectional, increasing effects between loneliness and cigarette smoking, especially for smoking initiation increasing loneliness.

Smoking and the risk for bipolar disorder: evidence from a bidirectional Mendelian randomisation study

BACKGROUND

There is increasing evidence that smoking is a risk factor for severe mental illness, including bipolar disorder. Conversely, patients with bipolar disorder might smoke more (often) as a result of the psychiatric disorder.

AIMS

We conducted a bidirectional Mendelian randomisation (MR) study to investigate the direction and evidence for a causal nature of the relationship between smoking and bipolar disorder.

METHOD

We used publicly available summary statistics from genome-wide association studies on bipolar disorder, smoking initiation, smoking heaviness, smoking cessation and lifetime smoking (i.e. a compound measure of heaviness, duration and cessation). We applied analytical methods with different, orthogonal assumptions to triangulate results, including inverse-variance weighted (IVW), MR-Egger, MR-Egger SIMEX, weighted-median, weighted-mode and Steiger-filtered analyses.

RESULTS

Across different methods of MR, consistent evidence was found for a positive effect of smoking on the odds of bipolar disorder (smoking initiation ORIVW = 1.46, 95% CI 1.28-1.66, P = 1.44 × 10-8, lifetime smoking ORIVW = 1.72, 95% CI 1.29-2.28, P = 1.8 × 10-4). The MR analyses of the effect of liability to bipolar disorder on smoking provided no clear evidence of a strong causal effect (smoking heaviness betaIVW = 0.028, 95% CI 0.003-0.053, P = 2.9 × 10-2).

CONCLUSIONS

These findings suggest that smoking initiation and lifetime smoking are likely to be a causal risk factor for developing bipolar disorder. We found some evidence that liability to bipolar disorder increased smoking heaviness. Given that smoking is a modifiable risk factor, these findings further support investment into smoking prevention and treatment in order to reduce mental health problems in future generations.

Relationship between smoking and ALS: Mendelian randomisation interrogation of causality

OBJECTIVE

Smoking has been widely studied as a susceptibility factor for amyotrophic lateral sclerosis (ALS), but results are conflicting and at risk of confounding bias. We used the results of recently published large genome-wide association studies and Mendelian randomisation methods to reduce confounding to assess the relationship between smoking and ALS.

METHODS

Two genome-wide association studies investigating lifetime smoking (n=463 003) and ever smoking (n=1 232 091) were identified and used to define instrumental variables for smoking. A genome-wide association study of ALS (20 806 cases; 59 804 controls) was used as the outcome for inverse variance weighted Mendelian randomisation, and four other Mendelian randomisation methods, to test whether smoking is causal for ALS. Analyses were bidirectional to assess reverse causality.

RESULTS

There was no strong evidence for a causal or reverse causal relationship between smoking and ALS. The results of Mendelian randomisation using the inverse variance weighted method were: lifetime smoking OR 0.94 (95% CI 0.74 to 1.19), p value 0.59; ever smoking OR 1.10 (95% CI 1 to 1.23), p value 0.05.

CONCLUSIONS

Using multiple methods, large sample sizes and sensitivity analyses, we find no evidence with Mendelian randomisation techniques that smoking causes ALS. Other smoking phenotypes, such as current smoking, may be suitable for future Mendelian randomisation studies.

Examining the effect of smoking on suicidal ideation and attempts: triangulation of epidemiological approaches

BACKGROUND

Previous literature has demonstrated a strong association between cigarette smoking, suicidal ideation and suicide attempts. This association has not previously been examined in a causal inference framework and could have important implications for suicide prevention strategies.

AIMS

We aimed to examine the evidence for an association between smoking behaviours (initiation, smoking status, heaviness, lifetime smoking) and suicidal thoughts or attempts by triangulating across observational and Mendelian randomisation analyses.

METHOD

First, in the UK Biobank, we calculated observed associations between smoking behaviours and suicidal thoughts or attempts. Second, we used Mendelian randomisation to explore the relationship between smoking and suicide attempts and ideation, using genetic variants as instruments to reduce bias from residual confounding and reverse causation.

RESULTS

Our observational analysis showed a relationship between smoking behaviour, suicidal ideation and attempts, particularly between smoking initiation and suicide attempts (odds ratio, 2.07; 95% CI 1.91-2.26; P < 0.001). The Mendelian randomisation analysis and single-nucleotide polymorphism analysis, however, did not support this (odds ratio for lifetime smoking on suicidal ideation, 0.050; 95% CI -0.027 to 0.127; odds ratio on suicide attempts, 0.053; 95% CI, -0.003 to 0.110). Despite past literature showing a positive dose-response relationship, our results showed no clear evidence for a causal effect of smoking on suicidal ideation or attempts.

CONCLUSIONS

This was the first Mendelian randomisation study to explore the effect of smoking on suicidal ideation and attempts. Our results suggest that, despite observed associations, there is no clear evidence for a causal effect.

Little evidence for an effect of smoking on multiple sclerosis risk: A Mendelian Randomization study

The causes of multiple sclerosis (MS) remain unknown. Smoking has been associated with MS in observational studies and is often thought of as an environmental risk factor. We used two-sample Mendelian randomization (MR) to examine whether this association is causal using genetic variants identified in genome-wide association studies (GWASs) as associated with smoking. We assessed both smoking initiation and lifetime smoking behaviour (which captures smoking duration, heaviness, and cessation). There was very limited evidence for a meaningful effect of smoking on MS susceptibility as measured using summary statistics from the International Multiple Sclerosis Genetics Consortium (IMSGC) meta-analysis, including 14,802 cases and 26,703 controls. There was no clear evidence for an effect of smoking on the risk of developing MS (smoking initiation: odds ratio [OR] 1.03, 95% confidence interval [CI] 0.92-1.61; lifetime smoking: OR 1.10, 95% CI 0.87-1.40). These findings suggest that smoking does not have a detrimental consequence on MS susceptibility. Further work is needed to determine the causal effect of smoking on MS progression.

A meta-review of "lifestyle psychiatry": the role of exercise, smoking, diet and sleep in the prevention and treatment of mental disorders

There is increasing academic and clinical interest in how "lifestyle factors" traditionally associated with physical health may also relate to mental health and psychological well-being. In response, international and national health bodies are producing guidelines to address health behaviors in the prevention and treatment of mental illness. However, the current evidence for the causal role of lifestyle factors in the onset and prognosis of mental disorders is unclear. We performed a systematic meta-review of the top-tier evidence examining how physical activity, sleep, dietary patterns and tobacco smoking impact on the risk and treatment outcomes across a range of mental disorders. Results from 29 meta-analyses of prospective/cohort studies, 12 Mendelian randomization studies, two meta-reviews, and two meta-analyses of randomized controlled trials were synthesized to generate overviews of the evidence for targeting each of the specific lifestyle factors in the prevention and treatment of depression, anxiety and stress-related disorders, schizophrenia, bipolar disorder, and attention-deficit/hyperactivity disorder. Standout findings include: a) convergent evidence indicating the use of physical activity in primary prevention and clinical treatment across a spectrum of mental disorders; b) emerging evidence implicating tobacco smoking as a causal factor in onset of both common and severe mental illness; c) the need to clearly establish causal relations between dietary patterns and risk of mental illness, and how diet should be best addressed within mental health care; and d) poor sleep as a risk factor for mental illness, although with further research required to understand the complex, bidirectional relations and the benefits of non-pharmacological sleep-focused interventions. The potentially shared neurobiological pathways between multiple lifestyle factors and mental health are discussed, along with directions for future research, and recommendations for the implementation of these findings at public health and clinical service levels.

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

BACKGROUND

Smoking prevalence is higher amongst individuals with schizophrenia and depression compared with the general population. Mendelian randomisation (MR) can examine whether this association is causal using genetic variants identified in genome-wide association studies (GWAS).

METHODS

We conducted two-sample MR to explore the bi-directional effects of smoking on schizophrenia and depression. For smoking behaviour, we used (1) smoking initiation GWAS from the GSCAN consortium and (2) we conducted our own GWAS of lifetime smoking behaviour (which captures smoking duration, heaviness and cessation) in a sample of 462690 individuals from the UK Biobank. We validated this instrument using positive control outcomes (e.g. lung cancer). For schizophrenia and depression we used GWAS from the PGC consortium.

RESULTS

There was strong evidence to suggest smoking is a risk factor for both schizophrenia (odds ratio (OR) 2.27, 95% confidence interval (CI) 1.67-3.08, p < 0.001) and depression (OR 1.99, 95% CI 1.71-2.32, p < 0.001). Results were consistent across both lifetime smoking and smoking initiation. We found some evidence that genetic liability to depression increases smoking (β = 0.091, 95% CI 0.027-0.155, p = 0.005) but evidence was mixed for schizophrenia (β = 0.022, 95% CI 0.005-0.038, p = 0.009) with very weak evidence for an effect on smoking initiation.

CONCLUSIONS

These 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 on mental health.

Food and mood: how do diet and nutrition affect mental wellbeing?

Poor nutrition may be a causal factor in the experience of low mood, and improving diet may help to protect not only the physical health but also the mental health of the population, say Joseph Firth and colleagues

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 an individual's environment and it is important to examine how traits within life history strategies affect each other. 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 (markers or results of exposure to early life adversity) on outcomes related to reproduction, education and risky behaviour in UK Biobank (N = 114 883-181 255). 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 < 0.001). 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 we therefore cannot infer causality from this analysis. 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.

Testing for causality between systematically identified risk factors and glioma: a Mendelian randomization study

BACKGROUND

Whilst epidemiological studies have provided evidence of associations between certain risk factors and glioma onset, inferring causality has proven challenging. Using Mendelian randomization (MR), we assessed whether associations of 36 reported glioma risk factors showed evidence of a causal relationship.

METHODS

We performed a systematic search of MEDLINE from inception to October 2018 to identify candidate risk factors and conducted a meta-analysis of two glioma genome-wide association studies (5739 cases and 5501 controls) to form our exposure and outcome datasets. MR analyses were performed using genetic variants to proxy for candidate risk factors. We investigated whether risk factors differed by subtype diagnosis (either glioblastoma (n = 3112) or non-glioblastoma (n = 2411)). MR estimates for each risk factor were determined using multiplicative random effects inverse-variance weighting (IVW). Sensitivity analyses investigated potential pleiotropy using MR-Egger regression, the weighted median estimator, and the mode-based estimator. To increase power, trait-specific polygenic risk scores were used to test the association of a genetically predicated increase in each risk factor with glioma onset.

RESULTS

Our systematic search identified 36 risk factors that could be proxied using genetic variants. Using MR, we found evidence that four genetically predicted traits increased risk of glioma, glioblastoma or non-glioblastoma: longer leukocyte telomere length, liability to allergic disease, increased alcohol consumption and liability to childhood extreme obesity (> 3 standard deviations from the mean). Two traits decreased risk of non-glioblastoma cancers: increased low-density lipoprotein cholesterol (LDLc) and triglyceride levels. Our findings were similar across sensitivity analyses that made allowance for pleiotropy (genetic confounding).

CONCLUSIONS

Our comprehensive investigation provides evidence of a causal link between both genetically predicted leukocyte telomere length, allergic disease, alcohol consumption, childhood extreme obesity, and LDLc and triglyceride levels, and glioma. The findings from our study warrant further research to uncover mechanisms that implicate these traits in glioma onset.

The effect of smoking intensity on all-cause and cause-specific mortality-a Mendelian randomization analysis

BACKGROUND

Smoking is an important cause of mortality and recent studies have suggested that even low-intensity smoking might be associated with increased mortality. Still, smoking is associated with lower socio-economic status as well as other potential risk factors, and disease onset might motivate smoking cessation, thus residual confounding and reverse causality might bias results. We aimed to assess the evidence of a causal relationship between smoking intensity and cause-specific as well as all-cause-mortality using Mendelian randomization analyses.

METHODS

We included 56 019 participants from the Norwegian HUNT2 Study and 337 103 participants from UK Biobank, linked to national registry data on causes of death. We estimated associations of self-reported smoking as well as the genetic variant rs1051730 as an instrument for smoking intensity with all-cause and cause-specific mortality. We subsequently meta-analysed the results from the two cohorts.

RESULTS

Each effect allele of the rs1051730 was associated with a 9% increased hazard of all-cause mortality [95% confidence interval (CI) 6-11] among ever smokers. Effect alleles were also associated with death by neoplasms [hazard ratio (HR) 1.11, 95% CI 1.06-1.15], circulatory diseases (HR 1.06, 95% CI 1.01-1.11) and respiratory diseases (HR 1.15, 95% CI 1.05-1.26) among ever smokers. The association was stronger among ever than never smokers for all-cause mortality (p < 0.001), neoplasms (p = 0.001) and respiratory diseases (p = 0.038).

CONCLUSIONS

Our results indicate a causal effect of smoking intensity on all-cause mortality and death by neoplasms and respiratory diseases. There was weaker evidence of a causal effect of smoking intensity on death by circulatory diseases.