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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.

Contains fulltext : 241621.pdf (Publisher’s version ) (Open Access), 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.

Contains fulltext : 252629.pdf (Publisher’s version ) (Open Access), 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 : 252629.pdf (Publisher’s version ) (Open Access), 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.

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.

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.

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.

Item does not contain fulltext

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.

Contains fulltext : 226537.pdf (Publisher’s version ) (Closed access)

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 : 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 : 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.

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 : 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 : 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.

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 : 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 : 226537.pdf (Publisher’s version ) (Closed access)

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.'

Item does not contain fulltext