Disentangling the interplay between genes, cognitive skills, and educational level in adolescent and young adult smoking - The TRAILS study.

Recent studies suggest that smoking and lower educational attainment may have genetic influences in common. However, little is known about the mechanisms through which genetics contributes to educational inequalities in adolescent and young adult smoking. Common genetic liabilities may underlie cognitive skills associated with both smoking and education, such as IQ and effortful control, in line with indirect health-related selection explanations. Additionally, by affecting cognitive skills, genes may predict educational trajectories and hereby adolescents' social context, which may be associated with smoking, consistent with social causation explanations. Using data from the Dutch TRAILS Study (N = 1581), we estimated the extent to which polygenic scores (PGSs) for ever smoking regularly (PGSSMOK) and years of education (PGSEDU) predict IQ and effortful control, measured around age 11, and whether these cognitive skills then act as shared predictors of smoking and educational level around age 16, 19, 22, and 26. Second, we assessed if educational level mediated associations between PGSs and smoking. Both PGSs were associated with lower effortful control, and PGSEDU also with lower IQ. Lower IQ and effortful control, in turn, predicted having a lower educational level. However, neither of these cognitive skills were directly associated with smoking behaviour after controlling for covariates and PGSs. This suggests that IQ and effortful control are not shared predictors of smoking and education (i.e., no indirect health-related selection related to cognitive skills). Instead, PGSSMOK and PGSEDU, partly through their associations with lower cognitive skills, predicted selection into a lower educational track, which in turn was associated with more smoking, in line with social causation explanations. Our findings suggest that educational differences in the social context contribute to associations between genetic liabilities and educational inequalities in smoking.

Interplay between genetic risk and the parent environment in adolescence and substance use in young adulthood: A TRAILS study.

Many adolescents start using tobacco, alcohol, and cannabis. Genetic vulnerability, parent characteristics in young adolescence, and interaction (GxE) and correlation (rGE) between these factors could contribute to the development of substance use. Using prospective data from the TRacking Adolescent Individuals' Lives Survey (TRAILS; N = 1,645), we model latent parent characteristics in young adolescence to predict young adult substance use. Polygenic scores (PGS) are created based on genome-wide association studies (GWAS) for smoking, alcohol use, and cannabis use. Using structural equation modeling we model the direct, GxE, and rGE effects of parent factors and PGS on young adult smoking, alcohol use, and cannabis initiation. The PGS, parental involvement, parental substance use, and parent-child relationship quality predicted smoking. There was GxE such that the PGS amplified the effect of parental substance use on smoking. There was rGE between all parent factors and the smoking PGS. Alcohol use was not predicted by genetic or parent factors, nor by interplay. Cannabis initiation was predicted by the PGS and parental substance use, but there was no GxE or rGE. Genetic risk and parent factors are important predictors of substance use and show GxE and rGE in smoking. These findings can act as a starting point for identifying people at risk.

Investigating the causal nature of the relationship of subcortical brain volume with smoking and alcohol use.

BACKGROUND: Structural variation in subcortical brain regions has been linked to substance use, including the most commonly used substances nicotine and alcohol. Pre-existing differences in subcortical brain volume may affect smoking and alcohol use, but there is also evidence that smoking and alcohol use can lead to structural changes. AIMS: We assess the causal nature of the complex relationship of subcortical brain volume with smoking and alcohol use, using bi-directional Mendelian randomisation. METHOD: Mendelian randomisation uses genetic variants predictive of a certain 'exposure' as instrumental variables to test causal effects on an 'outcome'. Because of random assortment at meiosis, genetic variants should not be associated with confounders, allowing less biased causal inference. We used summary-level data of genome-wide association studies of subcortical brain volumes (nucleus accumbens, amygdala, caudate, hippocampus, pallidum, putamen and thalamus; n = 50 290) and smoking and alcohol use (smoking initiation, n = 848 460; cigarettes per day, n = 216 590; smoking cessation, n = 378 249; alcoholic drinks per week, n = 630 154; alcohol dependence, n = 46 568). The main analysis, inverse-variance weighted regression, was verified by a wide range of sensitivity methods. RESULTS: There was strong evidence that liability to alcohol dependence decreased amygdala and hippocampal volume, and smoking more cigarettes per day decreased hippocampal volume. From subcortical brain volumes to substance use, there was no or weak evidence for causal effects. CONCLUSIONS: Our findings suggest that heavy alcohol use and smoking can causally reduce subcortical brain volume. This adds to accumulating evidence that alcohol and smoking affect the brain, and likely mental health, warranting more recognition in public health efforts.

Interactions between Genetic, Prenatal, Cortisol, and Parenting Influences on Adolescent Substance Use and Frequency: A TRAILS Study.

INTRODUCTION: Dynamic relations between genetic, hormone, and pre- and postnatal environments are theorized as critically important for adolescent substance use but are rarely tested in multifactorial models. This study assessed the impact of interactions of genetic risk and cortisol reactivity with prenatal and parenting influences on both any and frequency of adolescent substance use. METHODS: Data are from the TRacking Adolescents' Individual Lives Survey (TRAILS), a prospective longitudinal, multi-rater study of 2,230 Dutch adolescents. Genetic risk was assessed via 3 substance-specific polygenic scores. Mothers retrospectively reported prenatal risk when adolescents were 11 years old. Adolescents rated their parents' warmth and hostility at age 11. Salivary cortisol reactivity was measured in response to a social stress task at age 16. Adolescents' self-reported cigarette, alcohol, and cannabis use frequency at age 16. RESULTS: A multivariate hurdle regression model showed that polygenic risk for smoking, alcohol, and cannabis predicted any use of each substance, respectively, but predicted more frequent use only for smoking. Blunted cortisol reactivity predicted any use and more frequent use for all 3 outcomes. There were 2 interactions: blunted cortisol reactivity exacerbated the association of polygenic risk with any smoking and the association of prenatal risk with any alcohol use. CONCLUSION: Polygenic risk seems of importance for early use but less so for frequency of use, whereas blunted cortisol reactivity was correlated with both. Blunted cortisol reactivity may also catalyze early risks for substance use, though to a limited degree. Gene-environment interactions play no role in the context of this multifactorial model.

Genetic Risk for Smoking: Disentangling Interplay Between Genes and Socioeconomic Status.

This study aims to disentangle the contribution of genetic liability, educational attainment (EA), and their overlap and interaction in lifetime smoking. We conducted genome-wide association studies (GWASs) in UK Biobank (N = 394,718) to (i) capture variants for lifetime smoking, (ii) variants for EA, and (iii) variants that contribute to lifetime smoking independently from EA ('smoking-without-EA'). Based on the GWASs, three polygenic scores (PGSs) were created for individuals from the Netherlands Twin Register (NTR, N = 17,805) and the Netherlands Mental Health Survey and Incidence Study-2 (NEMESIS-2, N = 3090). We tested gene-environment (G × E) interactions between each PGS, neighborhood socioeconomic status (SES) and EA on lifetime smoking. To assess if the PGS effects were specific to smoking or had broader implications, we repeated the analyses with measures of mental health. After subtracting EA effects from the smoking GWAS, the SNP-based heritability decreased from 9.2 to 7.2%. The genetic correlation between smoking and SES characteristics was reduced, whereas overlap with smoking traits was less affected by subtracting EA. The PGSs for smoking, EA, and smoking-without-EA all predicted smoking. For mental health, only the PGS for EA was a reliable predictor. There were suggestions for G × E for some relationships, but there were no clear patterns per PGS type. This study showed that the genetic architecture of smoking has an EA component in addition to other, possibly more direct components. PGSs based on EA and smoking-without-EA had distinct predictive profiles. This study shows how disentangling different models of genetic liability and interplay can contribute to our understanding of the etiology of smoking.

Associations between the CADM2 gene, substance use, risky sexual behavior, and self-control: A phenome-wide association study.

Risky behaviors, such as substance use and unprotected sex, are associated with various physical and mental health problems. Recent genome-wide association studies indicated that variation in the cell adhesion molecule 2 (CADM2) gene plays a role in risky behaviors and self-control. In this phenome-wide scan for risky behavior, it was tested if underlying common vulnerability could be (partly) explained by pleiotropic effects of this gene and how large the effects were. Single nucleotide polymorphism (SNP)-level and gene-level association tests within four samples (25 and Up, Spit for Science, Netherlands Twin Register, and UK Biobank and meta-analyses over all samples (combined sample of 362,018 participants) were conducted to test associations between CADM2, substance- and sex-related risk behaviors, and various measures related to self-control. We found significant associations between the CADM2 gene, various risky behaviors, and different measures of self-control. The largest effect sizes were found for cannabis use, sensation seeking, and disinhibition. Effect sizes ranged from 0.01% to 0.26% for single top SNPs and from 0.07% to 3.02% for independent top SNPs together, with sufficient power observed only in the larger samples and meta-analyses. In the largest cohort, we found indications that risk-taking proneness mediated the association between CADM2 and latent factors for lifetime smoking and regular alcohol use. This study extends earlier findings that CADM2 plays a role in risky behaviors and self-control. It also provides insight into gene-level effect sizes and demonstrates the feasibility of testing mediation. These findings present a good starting point for investigating biological etiological pathways underlying risky behaviors.

Investigating genetic correlation and causality between nicotine dependence and ADHD in a broader psychiatric context.

People with attention-deficit/hyperactivity disorder (ADHD) or other psychiatric disorders show high rates of nicotine dependence (ND). This comorbidity might be (partly) explained by shared genetic factors. Genetic correlations between ND and ADHD (or other psychiatric disorders) have not yet been estimated. A significant genetic correlation might indicate genetic overlap, but could also reflect a causal relationship. In the present study we investigated the genetic correlation (with LD score regression analyses) between ND and ADHD, as well as between ND and other major psychiatric conditions (major depressive disorder, schizophrenia, anxiety, bipolar disorder, autism spectrum, anorexia nervosa, and antisocial behavior) based on the summary statistics of large Genome Wide Association studies. We explored the causal nature of the relationship between ND and ADHD using two-sample Mendelian randomization. We found a high genetic correlation between ND and ADHD (rg  = .53, p = 1.85 × 10-13 ), and to a lesser extent also between ND-major depressive disorder (rg  = .42, p = 3.6 × 10-11 ) and ND-schizophrenia (rg  = .18, p = 1.1 × 10-3 ). We did not find evidence for a causal relationship from liability for ADHD to ND (which could be due to a lack of power). The strong genetic correlations might reflect different phenotypic manifestations of (partly) shared underlying genetic vulnerabilities. Combined with the lack of evidence for a causal relationship from liability for ADHD to ND, these findings stress the importance to further investigate the underlying genetic vulnerability explaining co-morbidity in psychiatric disorders.

Causal relationships between substance use and insomnia.

BACKGROUND: Poor sleep quality and insomnia have been associated with the use of tobacco, alcohol, and cannabis, but it is unclear if there is a causal link. In this Mendelian Randomization (MR) study we examine if insomnia causes substance use and/or if substance use causes insomnia. METHODS: MR uses summary effect estimates from a genome-wide association study (GWAS) to create a genetic instrumental variable for a proposed 'exposure' variable and then identifies that same genetic instrument in an 'outcome' GWAS. Using GWASs of insomnia, smoking (initiation, heaviness, cessation), alcohol use (drinks per week, dependence), and cannabis initiation, bi-directional causal effects were tested. Multiple sensitivity analyses were applied to assess the robustness of the findings. RESULTS: There was strong evidence for positive causal effects of liability to insomnia on all substance use phenotypes (smoking traits, alcohol dependence, cannabis initiation), except alcohol per week. In the other direction, there was strong evidence that smoking initiation increased insomnia risk (smoking heaviness and cessation could not be tested as exposures). We found no evidence that alcohol use per week, alcohol dependence, or cannabis initiation causally affect insomnia risk. CONCLUSIONS: There were unidirectional effects of liability to insomnia on alcohol dependence and cannabis initiation, and bidirectional effects between liability to insomnia and smoking measures. Bidirectional effects between smoking and insomnia might give rise to a vicious circle. Future research should investigate if interventions aimed at insomnia are beneficial for substance use treatment.

Substance use: Interplay between polygenic risk and neighborhood environment.

BACKGROUND: Tobacco, alcohol, and cannabis use are prevalent behaviors that pose considerable health risks. Genetic vulnerability and characteristics of the neighborhood of residence form important risk factors for substance use. Possibly, these factors do not act in isolation. This study tested the interaction between neighborhood characteristics and genetic risk (gene-environment interaction, GxE) and the association between these classes of risk factors (gene-environment correlation, rGE) in substance use. METHODS: Two polygenic scores (PGS) each (based on different discovery datasets) were created for smoking initiation, cigarettes per day, and glasses of alcohol per week based on summary statistics of different genome-wide association studies (GWAS). For cannabis initiation one PGS was created. These PGS were used to predict their respective phenotype in a large population-based sample from the Netherlands Twin Register (N = 6,567). Neighborhood characteristics as retrieved from governmental registration systems were factor analyzed and resulting measures of socioeconomic status (SES) and metropolitanism were used as predictors. RESULTS: There were (small) main effects of neighborhood characteristics and PGS on substance use. One of the 14 tested GxE effects was significant, such that the PGS was more strongly associated with alcohol use in individuals with high SES. This was effect was only significant for one out of two PGS. There were weak indications of rGE, mainly with age and cohort covariates. CONCLUSION: We conclude that both genetic and neighborhood-level factors are predictors for substance use. More research is needed to establish the robustness of the findings on the interplay between these factors.

Systematic Review of Polygenic Gene-Environment Interaction in Tobacco, Alcohol, and Cannabis Use.

Studies testing the effect of single genetic variants on substance use have had modest success. This paper reviewed 39 studies using polygenic measures to test interaction with any type of environmental exposure (G×E) in alcohol, tobacco, and cannabis use. Studies using haplotype combinations, sum scores of candidate-gene risk alleles, and polygenic scores (PS) were included. Overall study quality was moderate, with lower ratings for the polygenic methods in the haplotype and candidate-gene score studies. Heterogeneity in investigated environmental exposures, genetic factors, and outcomes was substantial. Most studies (N = 30) reported at least one significant G×E interaction, but overall evidence was weak. The majority (N = 26) found results in line with differential susceptibility and diathesis-stress frameworks. Future studies should pay more attention to methodological and statistical rigor, and focus on replication efforts. Additional work is needed before firm conclusions can be drawn about the importance of G×E in the etiology of substance use.

GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal influence of schizophrenia.

Cannabis use is a heritable trait that has been associated with adverse mental health outcomes. In the largest genome-wide association study (GWAS) for lifetime cannabis use to date (N = 184,765), we identified eight genome-wide significant independent single nucleotide polymorphisms in six regions. All measured genetic variants combined explained 11% of the variance. Gene-based tests revealed 35 significant genes in 16 regions, and S-PrediXcan analyses showed that 21 genes had different expression levels for cannabis users versus nonusers. The strongest finding across the different analyses was CADM2, which has been associated with substance use and risk-taking. Significant genetic correlations were found with 14 of 25 tested substance use and mental health-related traits, including smoking, alcohol use, schizophrenia and risk-taking. Mendelian randomization analysis showed evidence for a causal positive influence of schizophrenia risk on cannabis use. Overall, our study provides new insights into the etiology of cannabis use and its relation with mental health.

The prevalence of food addiction in a large sample of adolescents and its association with addictive substances.

The prevalence of overweight and obesity is increasing, due to, among other factors, increased availability of highly palatable food (food high in fat, salt and/or sugar). It has been proposed that certain foods and/or eating behaviours may be addictive, to a degree comparable to substances of abuse. The Yale Food Addiction Scale (YFAS) measures 'food addiction' by translating the diagnostic criteria for substance use disorder to eating behaviour. So far, only a few studies have examined the prevalence of food addiction in children with the YFAS for children (YFAS-C). Large-scale studies, especially among adolescents, are lacking. Adolescence is of particular interest because it is a period wherein unhealthy eating behaviours or addictive tendencies are likely to develop. The current study examines the prevalence of food addiction using the YFAS-C in a large group of Dutch adolescents (N = 2653) aged 14-21 years. With Generalized Estimation Equation (GEE) analysis we tested the relationship between food addiction symptoms and smoking, cannabis use, alcohol use, and sugar intake through drinks, while controlling for gender, age, educational level and weight class. In the total sample 2.6% met the criteria for a food addiction 'diagnosis', and the average symptom count was 1.0 (SD = 1.3, range 0-7). Symptoms of food addiction were positively associated with smoking, alcohol use, cannabis use and sugar intake. We propose that future studies focus on possible genetic/(neuro)biological mechanisms involved in both food addiction and substance use and that longitudinal designs are needed to examine possible causal pathways.