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Item does not contain fulltext, Background: Individuals with serious mental illness have a markedly shorter life expectancy. A major contributor to premature death is cardiovascular disease (CVD). We investigated associations of (genetic liability for) depressive disorder, bipolar disorder and schizophrenia with a range of CVD traits and examined to what degree these were driven by important confounders. Methods: We included participants of the Dutch Lifelines cohort (N = 147 337) with information on self-reported lifetime diagnosis of depressive disorder, bipolar disorder, or schizophrenia and CVD traits. Employing linear mixed-effects models, we examined associations between mental illness diagnoses and CVD, correcting for psychotropic medication, demographic and lifestyle factors. In a subsample (N = 73 965), we repeated these analyses using polygenic scores (PGSs) for the three mental illnesses. Results: There was strong evidence that depressive disorder diagnosis is associated with increased arrhythmia and atherosclerosis risk and lower heart rate variability, even after confounder adjustment. Positive associations were also found for the depression PGSs with arrhythmia and atherosclerosis. Bipolar disorder was associated with a higher risk of nearly all CVD traits, though most diminished after adjustment. The bipolar disorder PGSs did not show any associations. While the schizophrenia PGSs was associated with increased arrhythmia risk and lower heart rate variability, schizophrenia diagnosis was not. All mental illness diagnoses were associated with lower blood pressure and a lower risk of hypertension. Conclusions: Our study shows widespread associations of (genetic liability to) mental illness (primarily depressive disorder) with CVD, even after confounder adjustment. Future research should focus on clarifying potential causal pathways between mental illness and CVD., 14 september 2023, 9 p.

Item does not contain fulltext, 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 x 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.

Item does not contain fulltext, The cell adhesion molecule 2 (CADM2) gene has appeared among the top associations in a wide range of genome-wide association studies (GWASs). This study aims to: (1) examine how widespread the role of CADM2 is in behavioural traits, and (2) investigate trait-specific effects on CADM2 expression levels across tissues. We conducted a phenome-wide association study in UK Biobank (N = 12,211–453,349) on 242 psycho-behavioral traits, both at the SNP and the gene-level. For comparison, we repeated the analyses for other large (and high LD) genes. We found significant associations between CADM2 and 50 traits (including cognitive, risk taking, and dietary traits), many more than for the comparison genes. We show that many trait associations are reduced when taking geographical stratification into account. S-Predixcan revealed that CADM2 expression in brain tissues was significantly associated with many traits; highly significant effects were also observed for lung, mammary, and adipose tissues. In conclusion, this study shows that the role of CADM2 extends to a wide range of psycho-behavioral traits, suggesting these traits may share a common biological denominator.

Contains fulltext : 285187.pdf (Publisher’s version ) (Open Access), Cannabis is among the most widely consumed psychoactive substances worldwide. Individual differences in cannabis use phenotypes can partly be explained by genetic differences. Technical and methodological advances have increased our understanding of the genetic aetiology of cannabis use. This narrative review discusses the genetic literature on cannabis use, covering twin, linkage, and candidate-gene studies, and the more recent genome-wide association studies (GWASs), as well as the interplay between genetic and environmental factors. Not only do we focus on the insights that these methods have provided on the genetic aetiology of cannabis use, but also on how they have helped to clarify the relationship between cannabis use and co-occurring traits, such as the use of other substances and mental health disorders. Twin studies have shown that cannabis use is moderately heritable, with higher heritability estimates for more severe phases of use. Linkage and candidate-gene studies have been largely unsuccessful, while GWASs so far only explain a small portion of the heritability. Dozens of genetic variants predictive of cannabis use have been identified, located in genes such as CADM2, FOXP2, and CHRNA2. Studies that applied multivariate methods (twin models, genetic correlation analysis, polygenic score analysis, genomic structural equation modelling, Mendelian randomisation) indicate that there is considerable genetic overlap between cannabis use and other traits (especially other substances and externalising disorders) and some evidence for causal relationships (most convincingly for schizophrenia). We end our review by discussing implications of these findings and suggestions for future work.

Contains fulltext : 234454.pdf (Publisher’s version ) (Open Access), 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.

28 september 2021, Item does not contain fulltext, 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.

24 juni 2021, Item does not contain fulltext, 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.

Contains fulltext : 230584.pdf (Publisher’s version ) (Open Access), 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.

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Contains fulltext : 226852.pdf (publisher's version ) (Open Access), Family studies have identified a heritable component to self-harm that is partially independent from comorbid psychiatric disorders. However, the genetic aetiology of broad sense (non-suicidal and suicidal) self-harm has not been characterised on the molecular level. In addition, controversy exists about the degree to which suicidal and non-suicidal self-harm share a common genetic aetiology. In the present study, we conduct genome-wide association studies (GWAS) on lifetime self-harm ideation and self-harm behaviour (i.e. any lifetime self-harm act regardless of suicidal intent) using data from the UK Biobank (n > 156,000). We also perform genome wide gene-based tests and characterize the SNP heritability and genetic correlations between these traits. Finally, we test whether polygenic risk scores (PRS) for self-harm ideation and self-harm behaviour predict suicide attempt, suicide thoughts and non-suicidal self-harm (NSSH) in an independent target sample of 8,703 Australian adults. Our GWAS results identified one genome-wide significant locus associated with each of the two phenotypes. SNP heritability (hsnp2) estimates were ~10%, and both traits were highly genetically correlated (LDSC rg > 0.8). Gene-based tests identified seven genes associated with self-harm ideation and four with self-harm behaviour. Furthermore, in the target sample, PRS for self-harm ideation were significantly associated with suicide thoughts and NSSH, and PRS for self-harm behaviour predicted suicide thoughts and suicide attempt. Follow up regressions identified a shared genetic aetiology between NSSH and suicide thoughts, and between suicide thoughts and suicide attempt. Evidence for shared genetic aetiology between NSSH and suicide attempt was not statistically significant.

Contains fulltext : 226491.pdf (publisher's version ) (Open Access)

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.

Contains fulltext : 220283.pdf (publisher's version ) (Open Access), 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.

Contains fulltext : 217711.pdf (Publisher’s version ) (Closed access), Background: Caffeine, alcohol, nicotine and cannabis are commonly used psychoactive substances. While the use of these substances has been previously shown to be genetically correlated, causality between these substance use traits remains unclear. We aimed to revisit the genetic relationships among different measures of SU using genome-wide association study (GWAS) summary statistics from the UK Biobank, International Cannabis Consortium, and GWAS & Sequencing Consortium of Alcohol and Nicotine use. Methods: We obtained GWAS summary statistics from the aforementioned consortia for ten substance use traits including various measures of alcohol consumption, caffeine consumption, cannabis initiation and smoking behaviours. We then conducted SNP-heritability (h2) estimation for individual SU traits, followed by genetic correlation analyses and two-sample Mendelian randomisation (MR) studies between substance use trait pairs. Results: SNP h2 of the ten traits ranged from 0.03 to 0.11. After multiple testing correction, 29 of the 45 trait pairs showed evidence of being genetically correlated. MR analyses revealed that most SU traits were not causally associated with each other. However, we found evidence for an MR association between regular smoking initiation and caffeine consumption 40.17 mg; 95% CI: [ 24.01, 56.33] increase in caffeine intake per doubling of odds in smoking initiation). Our findings were robust against horizontal pleiotropy, SNP-outliers, and the direction of causality was consistent in all MR analyses. Conclusions: Most of the substance traits were genetically correlated but there is little evidence to establish causality apart from the relationship between smoking initiation and caffeine consumption.

Contains fulltext : 216912.pdf (publisher's version ) (Open Access), 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.

Contains fulltext : 216593.pdf (publisher's version ) (Open Access), Not much is known regarding underlying biological pathways to adolescents' loneliness. Insight in underlying molecular mechanisms could inform intervention efforts aimed at reducing loneliness. Using latent growth curve modeling, baseline levels and development of loneliness were studied in two longitudinal adolescent samples. Genes (OXTR, OXT, AVPR1A, AVPR1B) were examined using SNP-based, gene-based, and polygenic risk score (PRS) approaches. In both samples, SNP- and gene-based tests showed involvement of the OXTR gene in development of loneliness, though, significance levels did not survive correction for multiple testing. The PRS approach provided no evidence for relations with loneliness. We recommend alternative phenotyping methods, including environmental factors, to consider epigenetic studies, and to examine possible endophenotypes in relation to adolescents' loneliness.

Contains fulltext : 219581.pdf (publisher's version ) (Open Access), Background: The use of illicit substances is correlated, meaning that individuals who use one illicit substance are more likely to also use another illicit substance. This association could (partly) be explained by overlapping genetic factors. Genetic overlap may indicate a common underlying genetic predisposition, or can be the result of a causal association. Methods: Polygenic scores for lifetime cannabis use were generated in a sample of Dutch participants (N = 8348). We tested the association of a PGS for cannabis use with ecstasy, stimulants and a broad category of illicit drug use. To explore the nature of the relationship: (1) these analyses were repeated separately in cannabis users and non-users and (2) monozogytic twin pairs discordant for cannabis use were compared on their drug use. Results: The lifetime prevalence was 24.8% for cannabis, 6.2% for ecstasy, 6.5% for stimulants and 7.1% for any illicit drug use. Significant, positive associations were found between PGS for cannabis use with ecstasy use, stimulants and any illicit drug use. These associations seemed to be stronger in cannabis users compared to non-users for both ecstasy and stimulant use, but only in people born after 1968 and not significant after correction for multiple testing. The discordant twin pair analyses suggested that cannabis use could play a causal role in drug use. Conclusions: The genetic liability underlying cannabis use significantly explained variability in ecstasy, stimulant and any illicit drug use. Further research should further explore the underlying mechanism to understand the nature of the association.

Contains fulltext : 216629.pdf (publisher's version ) (Open Access), Background: Little is known about the functional mechanisms through which genetic loci associated with substance use traits ascertain their effect. This study aims to identify and functionally annotate loci associated with substance use traits based on their role in genetic regulation of gene expression. Methods: We evaluated expression Quantitative Trait Loci (eQTLs) from 13 brain regions and whole blood of the Genotype-Tissue Expression (GTEx) database, and from whole blood of the Depression Genes and Networks (DGN) database. The role of single eQTLs was examined for six substance use traits: alcohol consumption (N = 537,349), cigarettes per day (CPD; N = 263,954), former vs. current smoker (N = 312,821), age of smoking initiation (N = 262,990), ever smoker (N = 632,802), and cocaine dependence (N = 4,769). Subsequently, we conducted a gene level analysis of gene expression on these substance use traits using S-PrediXcan. Results: Using an FDR-adjusted p-value < 0.05 we found 2,976 novel candidate genetic loci for substance use traits, and identified genes and tissues through which these loci potentially exert their effects. Using S-PrediXcan, we identified significantly associated genes for all substance traits. Discussion: Annotating genes based on transcriptomic regulation improves the identification and functional characterization of candidate loci and genes for substance use traits.

Item does not contain fulltext, Several occurrences of the word 'schizophrenia' have been re-worded as 'liability to schizophrenia' or 'schizophrenia risk', including in the title, which should have been "GWAS of lifetime cannabis use reveals new risk loci, genetic overlap with psychiatric traits, and a causal effect of schizophrenia liability", as well as in Supplementary Figures 1-10 and Supplementary Tables 7-10, to more accurately reflect the findings of the work.

Contains fulltext : 204120.pdf (publisher's version ) (Open Access), 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 (GxE) 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 GxE 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 GxE in the etiology of substance use.

Item does not contain fulltext, Introduction: Cigarette smoking and cannabis use are heritable traits and share, at least in part, a common genetic substrate. In recent years the prevalence of alternative methods of nicotine intakes, such as e-cigarette and water pipe use, has risen substantially. We tested whether the genetic vulnerability underlying cigarettes smoking and cannabis use explained variability in e-cigarette and water pipe use phenotypes, as these vaping methods are alternatives for smoking tobacco cigarettes and joints. Methods: Based on the summary statistics of the International Cannabis Consortium and the Tobacco and Genetics Consortium we generated polygenic risk scores (PRSs) for smoking and cannabis use traits, and used these to predict e-cigarette and water pipe use phenotypes in a sample of 5,025 individuals from the Netherlands Twin Register. Results: PRSs for cigarettes per day (CPD) were positively associated with lifetime e-cigarette use and early initiation of water pipe use, but only in ex-smokers (OR=1.43, R2=1.56%, p=.011) and never cigarette smokers (OR = 1.35, R2 = 1.60%, p = .013) respectively. Conclusions: Most associations of PRSs for cigarette smoking and cannabis use with e-cigarette and water pipe use were not significant, potentially due to a lack of power. The significant associations between genetic liability to smoking heaviness with e-cigarette and water pipe phenotypes are in line with studies indicating a common genetic background for substance use phenotypes. These associations emerged only in non-smokers, and future studies should investigate the nature of this observation.

Item does not contain fulltext, A commentary on Di Forti et al., 2019: 'The contribution of cannabis use to variation in the incidence of psychotic disorder across Europe (EU-GEI): a multicentre case-control study.'

Humans are social animals that experience intense suffering when they perceive a lack of social connection. Modern societies are experiencing an epidemic of loneliness. Although the experience of loneliness is universally human, some people report experiencing greater loneliness than others. Loneliness is more strongly associated with mortality than obesity, emphasizing the need to understand the nature of the relationship between loneliness and health. Although it is intuitive that circumstantial factors such as marital status and age influence loneliness, there is also compelling evidence of a genetic predisposition toward loneliness. To better understand the genetic architecture of loneliness and its relationship with associated outcomes, we extended the genome-wide association study meta-analysis of loneliness to 511 280 subjects, and detect 19 significant genetic variants from 16 loci, including four novel loci, as well as 58 significantly associated genes. We investigated the genetic overlap with a wide range of physical and mental health traits by computing genetic correlations and by building loneliness polygenic scores in an independent sample of 18 498 individuals with EHR data to conduct a PheWAS with. A genetic predisposition toward loneliness was associated with cardiovascular, psychiatric, and metabolic disorders and triglycerides and high-density lipoproteins. Mendelian randomization analyses showed evidence of a causal, increasing, the effect of both BMI and body fat on loneliness. Our results provide a framework for future studies of the genetic basis of loneliness and its relationship to mental and physical health.

Contains fulltext : 195854.pdf (publisher's version ) (Closed access), Background and aims: Cannabis is one of the most commonly used substances among adolescents and young adults. Earlier age at cannabis initiation is linked to adverse life outcomes including multi-substance use and dependence. This study estimated the heritability of age at first cannabis use and identify associations with genetic variants. Methods: A twin-based heritability analysis using 8,055 twins from three cohorts was performed. We then carried-out a genome wide survival meta-analysis of age at first cannabis use in a discovery sample of 24,953 individuals from nine European, North American, and Australian cohorts, and a replication sample of 3,735 individuals. Results: The twin-based heritability for age at first cannabis use was 38% (95% confidence interval [CI] 19-60%). Shared and unique environmental factors explained 39% (95% CI 20-56%) and 22% (95% CI 16-29%). The genome wide survival meta-analysis identified five SNPs on chromosome 16 within the Calcium-transporting ATPase gene (ATP2C2) at P < 5E-08. All five SNPs are in high LD (r2>0.8) with the strongest association at the intronic variant rs1574587 (P=4.09E-09). Gene-based tests of association identified the ATP2C2 gene on 16q24.1 (P=1.33e-06). Although the five SNPs and ATP2C2 did not replicate, ATP2C2 has been associated with cocaine dependence in a previous study. ATP2B2, which is a member of the same calcium signalling pathway, has been previously associated with opioid dependence. SNP-based heritability for age at first cannabis use was non-significant. Conclusion: Age at cannabis initiation appears to be moderately heritable in Western countries, and individual differences in onset can be explained by separate but correlated genetic liabilities. The significant association between age of initiation and ATP2C2 is consistent with the role of calcium signalling mechanisms in substance use disorders.

Contains fulltext : 195179.pdf (publisher's version ) (Closed access), 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.

Contains fulltext : 190837.pdf (publisher's version ) (Open Access), Background: There is high comorbidity between antisocial behaviour (ASB) and substance use, and twin studies have shown that part of the covariation is due to overlapping genetic influences. Here we used measured genetic effects to estimate the genetic correlations of ASB with nicotine, alcohol, and cannabis use. Methods: We meta-analysed data from two genome-wide association studies for ASB and used existing summary statistics from the largest genome-wide association studies into substance use (ever smoking, cigarettes smoked per day, weekly alcohol consumption, and lifetime cannabis use). We performed cross-trait LD-score regression to estimate genetic correlations between ASB and substance use phenotypes explained by all single nucleotide polymorphisms (SNPs). When significant, we tested whether the signs of the regression coefficients of SNPs from the ASB and substance use phenotypes were in the same direction across multiple p-value thresholds and examined enrichment in overlap of the strongest associated SNPs. Results: We found nominally significant genetic correlations of ASB with lifetime cannabis use (rg=.69, p=.016) and cigarettes per day (rg=.59, p=.036) but not with weekly alcohol consumption or ever smoking. Sign-tests revealed consistent directions of effect of SNPs for ASB and cannabis use for all p-value thresholds except the most stringent one, whereas for ASB with cigarettes per day no consistent evidence was found. We found no evidence of enrichment in overlap of the most associated SNPs across these traits. Conclusion: Using measured genetic variants, we found preliminary support for a genetic correlation of ASB with lifetime cannabis use and cigarettes per day.

Item does not contain fulltext, Background: Body mass index (BMI) is correlated negatively with subjective well-being and positively with depressive symptoms. Whether these associations reflect causal effects is unclear. Methods: We examined bidirectional, causal effects between BMI and mental health with Mendelian randomisation using summary-level data from published genome-wide association studies (BMI: n=339 224; subjective well-being: n=204 966; depressive symptoms: n=161 460). Genetic variants robustly related to the exposure variable acted as instrumental variable to estimate causal effects. We combined estimates of individual genetic variants with inverse-variance weighted meta-analysis, weighted median regression and MR-Egger regression. Results: There was evidence for a causal, increasing effect of BMI on depressive symptoms and suggestive evidence for a decreasing effect of BMI on subjective well-being. We found no evidence for causality in the other direction. Conclusion: This study provides support for a higher BMI causing poorer mental health. Further research should corroborate these findings and explore mechanisms underlying this potential causality.

Contains fulltext : 179407.pdf (publisher's version ) (Closed access), Background: Genetic and environmental factors contribute about equally to alcohol-related phenotypes in adulthood. In the present study, we examined whether more stress at home or low satisfaction with life might be associated with heavier drinking or more alcohol-related problems in individuals with a high genetic susceptibility to alcohol use. Methods: Information on polygenic scores and drinking behavior was available in 6705 adults (65% female; 18-83 years) registered with the Netherlands Twin Register. Polygenic risk scores (PRSs) were constructed for all subjects based on the summary statistics of a large genome-wide association meta-analysis on alcohol consumption (grams per day). Outcome measures were quantity of alcohol consumption and alcohol-related problems assessed with the Alcohol Use Disorders Identification Test (AUDIT). Stress at home and life satisfaction were moderating variables whose significance was tested by Generalized Estimating Equation analyses taking familial relatedness, age and sex into account. Results: PRSs for alcohol were significantly associated with quantity of alcohol consumption and alcohol-related problems in the past year (R2 = 0.11% and 0.10% respectively). Participants who reported to have experienced more stress in the past year and lower life satisfaction, scored higher on alcohol-related problems (R2 = 0.27% and 0.29 respectively), but not on alcohol consumption. Stress and life satisfaction did not moderate the association between PRSs and the alcohol outcome measures. Conclusions: There were significant main effects of polygenic scores and of stress and life satisfaction on drinking behavior, but there was no support for PRS-by-stress or PRS-by-life satisfaction interactions on alcohol consumption and alcohol-related problems.

Item does not contain fulltext, Introduction: Classical twin studies show that smoking is heritable. To determine if shared family environment plays a role in addition to genetic factors, and if they interact (GxE), we use a children-of-twins design. In a second sample, we measure genetic influence with polygenic risk scores (PRS) and environmental influence with a question on exposure to smoking during childhood. Methods: Data on smoking initiation were available for 723 children of 712 twins from the Netherlands Twin Register (NTR;64.9% female, median birth year 1985). Children were grouped in ascending order of risk, based on smoking status and zygosity of their twin-parent and his/her co-twin: never smoking twin-parent with a never smoking co-twin; never smoking twin-parent with a smoking dizygotic co-twin; never smoking twin-parent with a smoking monozygotic co-twin; smoking twin-parent with a smoking or never smoking co-twin. For 4,072 NTR participants (67.3% female, median birth year 1973), PRS for smoking were computed and smoking initiation, smoking heaviness and exposure to smoking during childhood were available. Results: Patterns of smoking initiation in the four group children-of-twins design suggested shared familial influences in addition to genetic factors. PRS for ever smoking were associated with smoking initiation in all individuals. PRS for smoking heaviness were associated with smoking heaviness in individuals exposed to smoking during childhood, but not in non-exposed individuals. Conclusions: Shared family environment influences smoking, over and above genetic factors. Genetic risk of smoking heaviness was only important for individuals exposed to smoking during childhood, versus those not exposed (GxE). Implications: This study adds to the very few existing children-of-twins (CoT) studies on smoking and combines a CoT design with a second research design that utilizes polygenic risk scores and data on exposure to smoking during childhood. The results show that shared family

Item does not contain fulltext, Background: Cannabis is the most frequently used and abused illicit drug worldwide and cannabis (ab)use is associated with social, physical, and psychological problems. Twin and family studies have shown that cannabis use and abuse are heritable traits. The International Cannabis Consortium was initiated with the aim of identifying genetic risk variants for cannabis use phenotypes by meta-analysing data from many contributing cohorts. The (partly preliminary) results of the International Cannabis Consortium will be presented: genome-wide association (GWA) meta-analyses on lifetime cannabis use and age at initiation of use. Additionally, findings from several follow-up studies will be presented, including the genetic association of cannabis use with use of other substances, schizophrenia, and conduct disorder. Methods: GWA analyses of lifetime cannabis use were performed by each contributing group independently (13 groups, total N=32,330) and were subsequently meta-analysed. We tested for replication, and the SNP results were used to perform a gene-based test of association. We also estimated the total SNP-based heritability and the genetic correlation between lifetime cannabis use and cigarette use based on LD-score regression analysis. Secondly, we meta-analysed GWA results of age at initiation of cannabis use from 8 groups (N=24,222) using a survival analysis. Again SNP results are followed up by a gene-based test of association and an estimate of SNP-based heritability. In follow-up projects, LD-score regression analyses were used to determine the genetic correlation of cannabis use with nicotine, alcohol, and caffeine use, as well as schizophrenia and conduct disorder. We also created polygenic risk scores for cannabis use in an independent target sample and determined to what extent these polygenic scores predicted conduct symptoms. Results: Although none of the SNPs were significantly associated with lifetime cannabis use, the gene-based analysis identified 4

Item does not contain fulltext, Background and aim: Previous studies have shown a relationship between schizophrenia and cannabis use. As both traits are substantially heritable, a shared genetic liability could explain the association. We use two recently developed genomics methods to investigate the genetic overlap between schizophrenia and cannabis use. Methods: Firstly, polygenic risk scores for schizophrenia were created based on summary statistics from the largest schizophrenia genome-wide association (GWA) meta-analysis to date. We analysed the association between these schizophrenia polygenic scores and multiple cannabis use phenotypes (lifetime use, regular use, age at initiation, and quantity and frequency of use) in a sample of 6,931 individuals. Secondly, we applied LD-score regression to the GWA summary statistics of schizophrenia and lifetime cannabis use to calculate the genome-wide genetic correlation. Results: Polygenic risk scores for schizophrenia were significantly (alpha < 0.05) associated with five of the eight cannabis use phenotypes, including lifetime use, regular use, and quantity of use, with risk scores explaining up to 0.5% of the variance. Associations were not significant for age at initiation of use and two measures of frequency of use analyzed in lifetime users only, potentially because of reduced power due to a smaller sample size. The LD-score regression revealed a significant genetic correlation of rg = 0.22 (SE = 0.07, p = 0.003) between schizophrenia and lifetime cannabis use. Conclusions: Common genetic variants underlying schizophrenia and lifetime cannabis use are partly overlapping. Individuals with a stronger genetic predisposition to schizophrenia are more likely to initiate cannabis use, use cannabis more regularly, and consume more cannabis over their lifetime.

Item does not contain fulltext, Background: Ecstasy is a widely used psychoactive drug that users often take because they experience positive effects such as increased euphoria, sociability, elevated mood, and heightened sensations. Ecstasy use is not harmless and several immediate and long term side effects have been identified. Lifetime ecstasy use is likely to be partly influenced by genetic factors, but no twin study has determined the heritability. Here, we apply a classical twin design to a large sample of twins and siblings to estimate the heritability of lifetime ecstasy use. Methods: The sample comprised 8,500 twins and siblings aged between 18 and 45 years from 5,402 families registered at the Netherlands Twin Registry. In 2013-2014 participants filled out a questionnaire including a question whether they had ever used ecstasy. We used the classical twin design to partition the individual differences in liability to ecstasy use into that due to genetic, shared environmental, and residual components. Results: Overall, 10.4% of the sample had used ecstasy during their lifetime, with a somewhat higher prevalence in males than females. Twin modelling indicated that individual differences in liability to lifetime ecstasy use are for 74% due to genetic differences between individuals, whereas shared environmental and residual factors explain a small proportion of its liability (5% and 21%, respectively). Although heritability estimates appeared to be higher for females than males, this difference was not significant. Conclusions: Lifetime ecstasy use is a highly heritable trait, which indicates that some people are genetically more vulnerable to start using ecstasy than others.

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Contains fulltext : 162902.pdf (publisher's version ) (Open Access), Non-suicidal and suicidal self-injury are very destructive, yet surprisingly common behaviours. Depressed mood is a major risk factor for non-suicidal self-injury (NSSI), suicidal ideation and suicide attempts. We conducted a genetic risk prediction study to examine the polygenic overlap of depressive symptoms with lifetime NSSI, suicidal ideation, and suicide attempts in a sample of 6237 Australian adult twins and their family members (3740 females, mean age = 42.4 years). Polygenic risk scores for depressive symptoms significantly predicted suicidal ideation, and some predictive ability was found for suicide attempts; the polygenic risk scores explained a significant amount of variance in suicidal ideation (lowest p = 0.008, explained variance ranging from 0.10 to 0.16 %) and, less consistently, in suicide attempts (lowest p = 0.04, explained variance ranging from 0.12 to 0.23 %). Polygenic risk scores did not significantly predict NSSI. Results highlight that individuals genetically predisposed to depression are also more likely to experience suicidal ideation/behaviour, whereas we found no evidence that this is also the case for NSSI.

Contains fulltext : 180452.pdf (publisher's version ) (Open Access), Higher paternal age at offspring conception increases de novo genetic mutations (Kong et al., 2012). Based on evolutionary genetic theory we predicted that the offspring of older fathers would be less likely to survive and reproduce, i.e. have lower fitness. In a sibling control study, we find clear support for negative paternal age effects on offspring survival, mating and reproductive success across four large populations with an aggregate N > 1.3 million in main analyses. Compared to a sibling born when the father was 10 years younger, individuals had 4-13% fewer surviving children in the four populations. Three populations were pre-industrial (1670-1850) Western populations and showed a pattern of paternal age effects across the offspring's lifespan. In 20th-century Sweden, we found no negative paternal age effects on child survival or marriage odds. Effects survived tests for competing explanations, including maternal age and parental loss. To the extent that we succeeded in isolating a mutation-driven effect of paternal age, our results can be understood to show that de novo mutations reduce offspring fitness across populations and time. We can use this understanding to predict the effect of increasingly delayed reproduction on offspring genetic load, mortality and fertility.

Item does not contain fulltext, Choice of romantic partner is an enormously important component of human life, impacting almost every facet of day-to-day existence, however; the processes underlying this choice are remarkably complex and have so far been largely resistant to scientific explanation. One consistent finding is that, on average, members of romantic dyads tend to be more alike than would be expected by chance. Selecting for self-similarity is at least partially driven by phenotypic matching wherein couples share similar phenotypes, and preferences for a number of these traits are partly genetically influenced (e.g., education, height, social attitudes and religiosity). This suggests that genetically influenced preferences for self-similarity might contribute to phenotypic matching (and thus assortative mating), but it has never been studied in actual couples. In the present study, we use a large sample of twins to model sources of variation in self-similarity between partners. Biometrical modelling revealed that very little of the variation in the tendency to assortatively mate across 14 traits was due to genetic effects (7 %) or the shared environment of twins (0 %).

Item does not contain fulltext, Using a sample of 757 British individuals, Pearce et al. (1) tested 24 single-nucleotide polymorphisms (SNPs) in six candidate genes for association with eight social behavior traits. For each SNP for each trait, five genotypic model tests were reported (except the androgen receptor gene, for which two model tests were reported), resulting in 936 reported tests. Of these, 44 (4.7%) were significant at P < 0.05, a proportion of significant associations that would be expected by chance if there was no true association between the SNPs and the traits measured in this dataset.

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Item does not contain fulltext, We examined whether assortative mating for educational attainment ("like marries like") can be detected in the genomes of ~ 1600 UK spouse pairs of European descent. Assortative mating on heritable traits like educational attainment increases the genetic variance and heritability of the trait in the population, which may increase social inequalities. We test for genetic assortative mating in the UK on educational attainment, a phenotype that is indicative of socio-economic status and has shown substantial levels of assortative mating. We use genome-wide allelic effect sizes from a large genome-wide association study on educational attainment (N ~ 300 k) to create polygenic scores that are predictive of educational attainment in our independent sample (r = 0.23, p < 2 x 10- 16). The polygenic scores significantly predict partners' educational outcome (r = 0.14, p = 4 x 10- 8 and r = 0.19, p = 2 x 10- 14, for prediction from males to females and vice versa, respectively), and are themselves significantly correlated between spouses (r = 0.11, p = 7 x 10- 6). Our findings provide molecular genetic evidence for genetic assortative mating on education in the UK.

Contains fulltext : 156357.pdf (publisher's version ) (Open Access), Cannabis is the most widely produced and consumed illicit psychoactive substance worldwide. Occasional cannabis use can progress to frequent use, abuse and dependence with all known adverse physical, psychological and social consequences. Individual differences in cannabis initiation are heritable (40-48%). The International Cannabis Consortium was established with the aim to identify genetic risk variants of cannabis use. We conducted a meta-analysis of genome-wide association data of 13 cohorts (N=32330) and four replication samples (N=5627). In addition, we performed a gene-based test of association, estimated single-nucleotide polymorphism (SNP)-based heritability and explored the genetic correlation between lifetime cannabis use and cigarette use using LD score regression. No individual SNPs reached genome-wide significance. Nonetheless, gene-based tests identified four genes significantly associated with lifetime cannabis use: NCAM1, CADM2, SCOC and KCNT2. Previous studies reported associations of NCAM1 with cigarette smoking and other substance use, and those of CADM2 with body mass index, processing speed and autism disorders, which are phenotypes previously reported to be associated with cannabis use. Furthermore, we showed that, combined across the genome, all common SNPs explained 13-20% (P<0.001) of the liability of lifetime cannabis use. Finally, there was a strong genetic correlation (rg=0.83; P=1.85 × 10-8) between lifetime cannabis use and lifetime cigarette smoking implying that the SNP effect sizes of the two traits are highly correlated. This is the largest meta-analysis of cannabis GWA studies to date, revealing important new insights into the genetic pathways of lifetime cannabis use. Future functional studies should explore the impact of the identified genes on the biological mechanisms of cannabis use.

Item does not contain fulltext, Males and females score differently on some personality traits, but the underlying etiology of these differences is not well understood. This study examined genetic, environmental, and prenatal hormonal influences on individual differences in personality masculinity-femininity (M-F). We used Big-Five personality inventory data of 9,520 Swedish twins (aged 27 to 54) to create a bipolar M-F personality scale. Using biometrical twin modeling, we estimated the influence of genetic and environmental factors on individual differences in a M-F personality score. Furthermore, we tested whether prenatal hormone transfer may influence individuals' M-F scores by comparing the scores of twins with a same-sex versus those with an opposite-sex co-twin. On average, males scored 1.09 standard deviations higher than females on the created M-F scale. Around a third of the variation in M-F personality score was attributable to genetic factors, while family environmental factors had no influence. Males and females from opposite-sex pairs scored significantly more masculine (both approximately 0.1 SD) than those from same-sex pairs. In conclusion, genetic influences explain part of the individual differences in personality M-F, and hormone transfer from the male to the female twin during pregnancy may increase the level of masculinization in females. Additional well-powered studies are needed to clarify this association and determine the underlying mechanisms in both sexes.

Contains fulltext : 161621.pdf (publisher's version ) (Open Access), Objectives. The present study examined whether the relation of parental solicitation, parental control, and child disclosure with adolescent alcohol and cannabis use is similar for native and non-Western immigrant Dutch adolescents. Design. Questionnaire data from two study-samples were used with a combined sample of 705 adolescents (mean age 16.2 years; 47.2% female; 25.2% non-Western immigrant background). Results. Native Dutch adolescents reported more weekly alcohol use than immigrant adolescents, while rates of cannabis use by native and immigrant adolescents were similar. Immigrant females reported lower levels of parental solicitation and child disclosure, but higher levels of parental control than native females. There were no differences in the sources of parental knowledge between native and immigrant males. Regression analyses showed no significant interaction effects of parental solicitation, parental control, or child disclosure with ethnic background for both alcohol and cannabis use (all p values > .05). Conclusion. Despite mean level differences in various factors, we did not find evidence of an interaction effect of the sources of parental knowledge with ethnic background on alcohol and cannabis use. This suggests that theories and prevention strategies focusing on these sources of parental knowledge in relation to substance use can be applicable to both native and immigrant Dutch adolescents.