Evidence for Genetic Correlations and Bidirectional, Causal Effects Between Smoking and Sleep Behaviors

INTRODUCTION: Cigarette smokers are at increased risk of poor sleep behaviors. However, it is largely unknown whether these associations are due to shared (genetic) risk factors and/or causal effects (which may be bidirectional). METHODS: We obtained summary-level data of genome-wide association studies of smoking (smoking initiation [n = 74 035], cigarettes per day [n = 38 181], and smoking cessation [n = 41 278]) and sleep behaviors (sleep duration and chronotype, or "morningness" [n = 128 266] and insomnia [n = 113 006]). Using linkage disequilibrium (LD) score regression, we calculated genetic correlations between smoking and sleep behaviors. To investigate causal effects, we employed Mendelian randomization (MR), both with summary-level data and individual-level data (n = 333 581 UK Biobank participants). For MR with summary-level data, individual genetic variants were combined with inverse variance-weighted meta-analysis, weighted median regression, MR-Robust Adjusted Profile Score, and MR Egger methods. RESULTS: We found negative genetic correlations between smoking initiation and sleep duration (rg = -.14, 95% CI = -0.26 to -0.01) and smoking cessation and chronotype (rg = -.18, 95% CI = -0.31 to -0.06), and positive genetic correlations between smoking initiation and insomnia (rg = .27, 95% CI = 0.06 to 0.49) and cigarettes per day and insomnia (rg = .15, 95% CI = 0.01 to 0.28). MR provided strong evidence that smoking more cigarettes causally decreases the odds of being a morning person, (RAPS) and weak evidence that insomnia causally increases smoking heaviness and decreases smoking cessation odds. CONCLUSIONS: Smoking and sleep behaviors show moderate genetic correlation. Heavier smoking seems to causally affect circadian rhythm and there is some indication that insomnia increases smoking heaviness and hampers cessation. Our findings point to sleep as a potentially interesting smoking treatment target. IMPLICATIONS: Using LD score regression, we found evidence that smoking and different sleep behaviors (sleep duration, chronotype (morningness), and insomnia) are moderately genetically correlated-genetic variants associated with less or poorer sleep also increased the odds of smoking (more heavily). MR analyses suggested that heavier smoking causally affects circadian rhythm (decreasing the odds of being a morning person) and there was some indication that insomnia increases smoking heaviness and hampers smoking cessation. Our findings indicate a complex, bidirectional relationship between smoking and sleep behaviors and point to sleep as a potentially interesting smoking treatment target

Comparing ecstasy users and non-users in a population-based and co-twin control design across multiple traits

Contains fulltext : 219151.pdf (Publisher’s version ) (Closed access)Objective: Ecstasy is one of the most commonly used illicit substances in Western countries. The aim of this study is to identify characteristics of ecstasy users in a large population-based sample of adults aged 18-45 years. Method: With generalized estimating equation models we explored the association between self-reported lifetime ecstasy use and urbanicity, educational attainment, health, wellbeing, stress, other substance use, personality traits and psychopathology in a Dutch twin sample (N=9,578, 66.8% female, 18-45 years). We also explored the nature of the association (underlying genetic factors, shared environmental factors or a causal relationship) with the co-twin control method. Results: Lifetime ecstasy users (N=945, 9.9%) were more often male, younger, living more often in urban areas, higher educated, less satisfied with life and more stressed than non-users. Ecstasy users scored differently on most personality and psychopathology scales compared to non-users and were more likely to have used every other substance we investigated. Whereas smoking tobacco and alcohol use often preceded first use of ecstasy, first ecstasy use often preceded first use of other illicit substances. A combination of scenarios (both causal and environmental/genetic) explained the strong associations between ecstasy and substance use. For the other variables no causal association was likely but genetic factors (i.e. psychopathology), shared environmental factors (i.e. demographics) or no clear pattern (i.e. personality) were likely scenarios. Conclusions: Ecstasy users differ on many characteristics from non-users, and especially on illicit substance use. In addition, our results indicate that causal effects may play a role in explaining the relationship between ecstasy use and other illicit substance use.8 p

Investigating genetic correlations and causal effects between caffeine consumption and sleep behaviours

Observationally, higher caffeine consumption is associated with poorer sleep and insomnia. We investigated whether these associations are a result of shared genetic risk factors and/or (possibly bidirectional) causal effects. Summary-level data were available from genome-wide association studies on caffeine intake (n = 91 462), plasma caffeine and caffeine metabolic rate (n = 9876), sleep duration and chronotype (being a “morning” versus an “evening” person) (n = 128 266), and insomnia complaints (n = 113 006). First, genetic correlations were calculated, reflecting the extent to which genetic variants influencing caffeine consumption and those influencing sleep overlap. Next, causal effects were estimated with bidirectional, two-sample Mendelian randomization. This approach utilizes the genetic variants most robustly associated with an exposure variable as an “instrument” to test causal effects. Estimates from individual variants were combined using inverse-variance weighted meta-analysis, weighted median regression and MR-Egger regression. We found no clear evidence for a genetic correlation between caffeine intake and sleep duration (rg = 0.000, p =.998), chronotype (rg = 0.086, p =.192) or insomnia complaints (rg = −0.034, p =.700). For plasma caffeine and caffeine metabolic rate, genetic correlations could not be calculated because of the small sample size. Mendelian randomization did not support causal effects of caffeine intake on sleep, or vice versa. There was weak evidence that higher plasma caffeine levels causally decrease the odds of being a morning person. Although caffeine may acutely affect sleep when taken shortly before bedtime, our findings suggest that a sustained pattern of high caffeine consumption is more likely to be associated with poorer sleep through shared environmental factors. Future research should identify such environments, which could aid the development of interventions to improve sleep

E-cigarette and waterpipe use in two adolescent cohorts: cross-sectional and longitudinal associations with conventional cigarette smoking.

Alternative tobacco products are increasing in popularity. An important question is whether their use is associated with or even leads to conventional smoking, but large-scale (European) studies are scarce. In two cohorts of Dutch adolescents (Cohort I n = 6819, mean age = 13.8 SD = 1.1, 48.2% female; Cohort II n = 2758, mean age = 17.3 SD = 1.8, 61.3% female), we investigated use of electronic (e)-cigarettes with nicotine, e-cigarettes without nicotine and waterpipe. Generalized estimating equation modelling was conducted with ever conventional smoking as the dependent variable (0 = no, 1 = yes) and ever alternative tobacco use as the independent variable, correcting for clustering within schools, age, sex and education in both cohorts. In a subsample (n = 2100), the association between alternative tobacco use at baseline and conventional smoking 6 months later was tested, taking into account smoking propensity (based on personality, susceptibility to peer pressure and smoking intentions). Ever use prevalence was 13.7% for e-cigarettes with nicotine, 29.4% for e-cigarettes without nicotine and 22.1% for waterpipe in Cohort I and 12.3, 27.6 and 45.3% respectively in Cohort II. Ever smokers had tried alternative tobacco products more often than never smokers. Among never-smoking adolescents at baseline, alternative tobacco use predicted ever smoking 6 months later (e-cigarettes with nicotine OR 11.90 95% CI 3.36-42.11; e-cigarettes without nicotine OR 5.36 95% CI 2.73-10.52; waterpipe OR 5.36 95% CI 2.78-10.31). This association was strongest for adolescents with a low baseline risk of smoking. Experimenting with alternative tobacco products is common among Dutch youth. Alternative tobacco use predicts (future) smoking, especially among adolescents with a low smoking propensity

Associations between smoking and caffeine consumption in two European cohorts

AIMS: To estimate associations between smoking initiation, smoking persistence and smoking heaviness and caffeine consumption in two population‐based samples from the Netherlands and the United Kingdom. DESIGN: Observational study employing data on self‐reported smoking behaviour and caffeine consumption. SETTING: Adults from the general population in the Netherlands and the United Kingdom. PARTICIPANTS: Participants from the Netherlands Twin Register [NTR: n = 21 939, mean age 40.8, standard deviation (SD) = 16.9, 62.6% female] and the Avon Longitudinal Study of Parents and Children (ALSPAC: n = 9086, mean age 33.2, SD = 4.7, 100% female). MEASUREMENTS: Smoking initiation (ever versus never smoking), smoking persistence (current versus former smoking), smoking heaviness (number of cigarettes smoked) and caffeine consumption in mg per day through coffee, tea, cola and energy drinks. FINDINGS: After correction for age, gender (NTR), education and social class (ALSPAC), smoking initiation was associated with consuming on average 52.8 [95% confidence interval (CI) = 45.6–60.0; NTR] and 59.5 (95% CI = 51.8–67.2; ALSPAC) mg more caffeine per day. Smoking persistence was also associated with consuming more caffeine [+57.9 (95% CI = 45.2–70.5) and +83.2 (95% CI = 70.2–96.3) mg, respectively]. Each additional cigarette smoked per day was associated with 3.7 (95% CI = 1.9–5.5; NTR) and 8.4 (95% CI = 6.9–10.0; ALSPAC) mg higher daily caffeine consumption in current smokers. Smoking was associated positively with coffee consumption and less strongly with cola and energy drinks. For tea, associations were positive in ALSPAC and negative in NTR. CONCLUSIONS: There appears to be a positive association between smoking and caffeine consumption in the Netherlands and the United Kingdom

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