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 (ß = - 0.11, 95% CI [- 0.12, - 0.09], pone-tailed < 0.01). One-sample MR analyses suggested that this relationship may be causal (ß = - 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.

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.

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.

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.

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.

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.

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.

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.

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.

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.

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 (ß, 0.25 [95% CI, 0.18-0.31]), pregnancy weight gain (ß, 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 (ß, -0.18 [95% CI, -0.25 to -0.11]), and pregnancy weight gain (ß, 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.

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.

"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.

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 ß -0.736, 95% CI -1.238 to -0.233, p = 0.004; fully adjusted educational attainment ß -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 ß -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.