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Regular cigarette smoking and cannabis consumption are strongly positively related to each other, yet few studies explore their underlying variation and covariation. We evaluated the genetic and environmental decomposition of variance and covariance of these two traits in twin data from three countries with different social norms and legislation. Data from the Netherlands Twin Register, FinnTwin12/16, and the Minnesota Center for Twin Family Research (total N = 21,617) were analyzed in bivariate threshold models of lifetime regular smoking initiation (RSI) and lifetime cannabis initiation (CI). We ran unstratified models and models stratified by sex and country. Prevalence of RSI was lowest in the Netherlands and prevalence of CI was highest in Minnesota. In the unstratified model, genetic (A) and common environmental factors (C) contributed substantially to the liabilities of RSI (A = 0.47, C = 0.34) and CI (A = 0.28, C = 0.51). The two liabilities were significantly phenotypically (rP = 0.56), genetically (rA = 0.74), and environmentally correlated in the unstratified model (rC = 0.47and rE = 0.48, representing correlations between common and unique environmental factors). The magnitude of phenotypic correlation between liabilities varied by country but not sex (Minnesota rP ~ 0.70, Netherlands rP ~ 0.59, Finland rP ~ 0.45). Comparisons of decomposed correlations could not be reliably tested in the stratified models. The prevalence and association of RSI and CI vary by sex and country. These two behaviors are correlated because there is genetic and environmental overlap between their underlying latent liabilities. There is heterogeneity in the genetic architecture of these traits across country., (© 2024. The Author(s).)

The major anxiety disorders (ANX; including generalized anxiety disorder, panic disorder, and phobias) are highly prevalent, often onset early, persist throughout life, and cause substantial global disability. Although distinct in their clinical presentations, they likely represent differential expressions of a dysregulated threat-response system. Here we present a genome-wide association meta-analysis comprising 122,341 European ancestry ANX cases and 729,881 controls. We identified 58 independent genome-wide significant ANX risk variants and 66 genes with robust biological support. In an independent sample of 1,175,012 self-report ANX cases and 1,956,379 controls, 51 of the 58 associated variants were replicated. As predicted by twin studies, we found substantial genetic correlation between ANX and depression, neuroticism, and other internalizing phenotypes. Follow-up analyses demonstrated enrichment in all major brain regions and highlighted GABAergic signaling as one potential mechanism underlying ANX genetic risk. These results advance our understanding of the genetic architecture of ANX and prioritize genes for functional follow-up studies., Competing Interests: Per Hoffmann receives Salary from the Life & Brain GmbH, Bonn, Germany. James L. Kennedy is a member of the Scientific Advisory Board for Myriad Neuroscience Inc. Ian B. Hickie was an inaugural Commissioner on Australia’s National Mental Health Commission (2012-18). He is the Co-Director, Health and Policy at the Brain and Mind Centre (BMC) University of Sydney. The BMC operates an early-intervention youth services at Camperdown under contract to headspace. He is the Chief Scientific Advisor to, and a 5% equity shareholder in, InnoWell Pty Ltd. InnoWell was formed by the University of Sydney (45% equity) and PwC (Australia; 45% equity) to deliver the $30 M Australian Government-funded Project Synergy (2017-20; a three-year program for the transformation of mental health services) and to lead transformation of mental health services internationally through the use of innovative technologies. Andrew M. Mcintosh has received research support from Eli Lilly, Janssen, and The Sackler Trust. AMM has also received speaker fees from Illumina and Janssen. Murray B. Stein has in the past 3 years received consulting income from Acadia Pharmaceuticals, Aptinyx, atai Life Sciences, Boehringer Ingelheim, Bionomics, BioXcel Therapeutics, Clexio, Eisai, EmpowerPharm, Engrail Therapeutics, Janssen, Jazz Pharmaceuticals, and Roche/Genentech. Dr. Stein has stock options in Oxeia Biopharmaceuticals and EpiVario. He is paid for his editorial work on Depression and Anxiety (Editor-in-Chief), Biological Psychiatry (Deputy Editor), and UpToDate (Co-Editor-in-Chief for Psychiatry). He has also received research support from NIH, Department of Veterans Affairs, and the Department of Defense. He is on the scientific advisory board for the Brain and Behavior Research Foundation and the Anxiety and Depression Association of America. Joel Gelernter is named as an inventor on PCT patent application #15/878,640 entitled: “Genotype-guided dosing of opioid agonists,” filed January 24, 2018 and issued on January 26, 2021 as U.S. Patent No. 10,900,082; and is paid for editorial work for the journal “Complex Psychiatry.” Iiris Hovatta received speaker’s honoraria from Lundbeck. Ole A. Andreassen received speaker’s honorarium from Lundbeck and Sunovion, consultant for Cortechs.ai and Precision Health AS. Katharina Domschke has been a member of the Steering Committee Neurosciences, Janssen, Inc. until 2022 and is currently a member of the Board of the German National Society of Psychiatry (DGPPN) and the Neurotorium Editorial Board of the Lundbeck Foundation. Jordan W. Smoller is a member of the Scientific Advisory Board of Sensorium Therapeutics (with equity) and has received an honorarium for an internal seminar Tempus Labs. He is PI of a collaborative study of the genetics of depression and bipolar disorder sponsored by 23andMe for which 23andMe provides analysis time as in-kind support but no payments. Eduard Maron has received research support and has also received speaker fees from Lundbeck. Hans J. Grabe has received travel grants and speakers honoraria from Indorsia, Neuraxpharm, Servier and Janssen Cilag. Henrik Larsson has served as a speaker for Evolan Pharma, Medici and Shire/Takeda and has received research grants from Shire/Takeda; all outside the submitted work. Gerome Breen is an advisory board member for Compass Pathways. Jürgen Deckert is a member of the board of the German Society of Biological Psychiatry and is on the scientific advisory boards of non-profit organizations and foundations. Volker Arolt worked as an advisor for Sanofi-Adventis Germany. Zach Fuller and Xin Wang are employees of 23andMe and hold stock or stock options in 23andMe. All other authors have no competing interests to declare.

Epigenome-wide association studies (EWAS) aim to identify differentially methylated loci associated with complex traits and disorders. EWAS of cigarette smoking shows some of the most widespread DNA methylation (DNAm) associations in blood. However, traditional EWAS cannot differentiate between causation and confounding, leading to ambiguity in etiological interpretations. Here, we apply an integrated approach combining Mendelian Randomization and twin-based Direction-of-Causation analyses (MR-DoC) to examine causality underlying smoking-associated blood DNAm changes in the Netherlands Twin Register (N=2577). Evidence across models suggests that current smoking's causal effects on DNAm likely drive many of the previous EWAS findings, implicating functional pathways relevant to several adverse health outcomes of smoking, including hemopoiesis, cell- and neuro-development, and immune regulation. Additionally, we find evidence of potential reverse causal influences at some DNAm sites, with 17 of these sites enriched for gene regulatory functional elements in the brain. The top three sites with evidence of DNAm's effects on smoking annotate to genes involved in G protein-coupled receptor signaling ( GNG7 , RGS3 ) and innate immune response ( SLC15A4 ), elucidating potential biological risk factors for smoking. This study highlights the utility of integrating genotypic and DNAm measures in twin cohorts to clarify the causal relationships between health behaviors and blood DNAm., Competing Interests: Conflicts of Interest Nothing to declare.

Introduction: Population research indicates that smoking behaviors in Finland have varied over time by sex and birth cohort. Smoking behaviors are influenced by genes and the environment; like the behaviors themselves, these underlying influences are not necessarily stable over time and may be modifiable by national drug policy., Methods: We utilized longitudinal mixed effects models and causal-common-contingent twin models to evaluate sex and cohort effects on tobacco consumption and the underlying genetic and environmental variance components in a birth cohort sample of same-sex twins born in Finland between 1880-1957, assessed in 1975, 1981, 1990, and 2011., Results: We identified significant main effects of age, sex, and cohort on quantity of cigarette consumption, as well as significant age×cohort and sex×cohort interactions. We also identified sex and cohort effects on the liability to initiate regular smoking and the magnitude of variation underlying quantity of cigarette consumption. That said, heritability and environmental contributions to both traits were not different between the four sex×cohort groups., Conclusions: Our results indicate sex and cohort effects on the prevalence of smoking and its underlying variation. Our results on changing prevalence mirror existing population-level research in Finnish samples, but we did not identify differences in heritability found in other studies of cohort effects in tobacco use, potentially due to power issues. These results highlight the importance of considering age, cohort, and timing of policy changes when evaluating changes in substance consumption across time., Implications: This study identifies sex and cohort effects influencing tobacco consumption in a sample of Finnish adult twins born between 1880-1957. Our results are in line with other population level research in Finland and research on cohort effects influencing alcohol use in the same sample. Our results highlight the intertwining effects of age, cohort, sex, and substance policies on substance use., (© The Author(s) 2024. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco.)

Cross-lagged panel models (CLPMs) are commonly used to estimate causal influences between two variables with repeated assessments. The lagged effects in a CLPM depend on the time interval between assessments, eventually becoming undetectable at longer intervals. To address this limitation, we incorporate instrumental variables (IVs) into the CLPM with two study waves and two variables. Doing so enables estimation of both the lagged (i.e., "distal") effects and the bidirectional cross-sectional (i.e., "proximal") effects at each wave. The distal effects reflect Granger-causal influences across time, which decay with increasing time intervals. The proximal effects capture causal influences that accrue over time and can help infer causality when the distal effects become undetectable at longer intervals. Significant proximal effects, with a negligible distal effect, would imply that the time interval is too long to estimate a lagged effect at that time interval using the standard CLPM. Through simulations and an empirical application, we demonstrate the impact of time intervals on causal inference in the CLPM and present modeling strategies to detect causal influences regardless of the time interval in a study. Furthermore, to motivate empirical applications of the proposed model, we highlight the utility and limitations of using genetic variables as IVs in large-scale panel studies.

Objective: Using Swedish nationwide registry data, we investigated the contribution of genetic and environmental risk factors to the etiology of alcohol use disorder (AUD) by extended twin pedigree modeling., Method: AUD was defined using public inpatient, outpatient, prescription, and criminal records. Three-generational pedigrees were selected for index individuals born between 1980 and 1990, obtained from the national twin and genealogical registers, whose parents were twins. Relatives of the twins included in the pedigrees were their parents, siblings, spouses, and children. Genetic structural equation modeling was applied to the population-based data on AUD, using OpenMx, with age used as a covariate., Results: Analyses including up to 162,469 individuals in 18,971 pedigrees estimated AUD prevalence at 5%-12% in men and 2%-5% in women. Results indicated substantial heritability (about 50%-60%), of which a portion upwards of 5% was attributable to the consequences of assortative mating. Contributions of shared environmental factors to AUD, which represent a mix of within- and cross-generational effects, appeared to be moderate (about 10%-20%). Unique environment accounted for the remaining variance (about 20%-30%). Sex differences in the magnitude of the variance components suggested higher heritability in men and correspondingly higher shared environmental contributions in women., Conclusions: Using objective registry data, we found that AUD is highly heritable. Furthermore, shared environmental factors contributed significantly to the liability of AUD in both men and women.

Music engagement is a powerful, influential experience that often begins early in life. Music engagement is moderately heritable in adults (~ 41-69%), but fewer studies have examined genetic influences on childhood music engagement, including their association with language and executive functions. Here we explored genetic and environmental influences on music listening and instrument playing (including singing) in the baseline assessment of the Adolescent Brain Cognitive Development study. Parents reported on their 9-10-year-old children's music experiences (N = 11,876 children; N = 1543 from twin pairs). Both music measures were explained primarily by shared environmental influences. Instrument exposure (but not frequency of instrument engagement) was associated with language skills (r = .27) and executive functions (r = .15-0.17), and these associations with instrument engagement were stronger than those for music listening, visual art, or soccer engagement. These findings highlight the role of shared environmental influences between early music experiences, language, and executive function, during a formative time in development., (© 2023. The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature.)

Twin studies yield valuable insights into the sources of variation, covariation and causation in human traits. The ABCD Study® (abcdstudy.org) was designed to take advantage of four universities known for their twin research, neuroimaging, population-based sampling, and expertise in genetic epidemiology so that representative twin studies could be performed. In this paper we use the twin data to: (i) provide initial estimates of heritability for the wide range of phenotypes assessed in the ABCD Study using a consistent direct variance estimation approach, assuring that both data and methodology are sound; and (ii) provide an online resource for researchers that can serve as a reference point for future behavior genetic studies of this publicly available dataset. Data were analyzed from 772 pairs of twins aged 9-10 years at study inception, with zygosity determined using genotypic data, recruited and assessed at four twin hub sites. The online tool provides twin correlations and both standardized and unstandardized estimates of additive genetic, and environmental variation for 14,500 continuously distributed phenotypic features, including: structural and functional neuroimaging, neurocognition, personality, psychopathology, substance use propensity, physical, and environmental trait variables. The estimates were obtained using an unconstrained variance approach, so they can be incorporated directly into meta-analyses without upwardly biasing aggregate estimates. The results indicated broad consistency with prior literature where available and provided novel estimates for phenotypes without prior twin studies or those assessed at different ages. Effects of site, self-identified race/ethnicity, age and sex were statistically controlled. Results from genetic modeling of all 53,172 continuous variables, including 38,672 functional MRI variables, will be accessible via the user-friendly open-access web interface we have established, and will be updated as new data are released from the ABCD Study. This paper provides an overview of the initial results from the twin study embedded within the ABCD Study, an introduction to the primary research domains in the ABCD study and twin methodology, and an evaluation of the initial findings with a focus on data quality and suitability for future behavior genetic studies using the ABCD dataset. The broad introductory material is provided in recognition of the multidisciplinary appeal of the ABCD Study. While this paper focuses on univariate analyses, we emphasize the opportunities for multivariate, developmental and causal analyses, as well as those evaluating heterogeneity by key moderators such as sex, demographic factors and genetic background., (© 2022. The Author(s).)

Illicit substance use is dangerous in both acute and chronic forms, frequently resulting in lethal poisoning, addiction, and other negative consequences. Similar to research in other psychiatric conditions, whose ultimate goal is to enable effective prevention and treatment, studies in substance use are focused on factors elevating the risk for the disorder. The rapid growth of the substance use problem despite the effort invested in fighting it, however, suggests the need in changing the research approach. Instead of attempting to identify risk factors, whose neutralization is often infeasible if not impossible, it may be more promising to systematically reverse the perspective to the factors enhancing the aspect of liability to disorder that shares the same dimension but is opposite to risk, that is, resistance to substance use. Resistance factors, which enable the majority of the population to remain unaffected despite the ubiquity of psychoactive substances, may be more amenable to translation. While the resistance aspect of liability is symmetric to risk, the resistance approach requires substantial changes in sampling (high-resistance rather than high-risk) and using quantitative indices of liability. This article provides an overview and a practical approach to research in resistance to substance use/addiction, currently implemented in a NIH-funded project. The project benefits from unique opportunities afforded by the data originating from two longitudinal twin studies, the Virginia Twin Study of Adolescent and Behavioral Development and the Minnesota Twin Family Study. The methodology described is also applicable to other psychiatric disorders.

Genome-wide association studies (GWAS) have successfully identified common variants associated with BMI. However, the stability of aggregate genetic variation influencing BMI from midlife and beyond is unknown. By analysing 165,717 men and 193,073 women from the UKBiobank, we performed BMI GWAS on six independent five-year age intervals between 40 and 72 years. We then applied genomic structural equation modeling to test competing hypotheses regarding the stability of genetic effects for BMI. LDSR genetic correlations between BMI assessed between ages 40 to 73 were all very high and ranged 0.89 to 1.00. Genomic structural equation modeling revealed that molecular genetic variance in BMI at each age interval could not be explained by the accumulation of any age-specific genetic influences or autoregressive processes. Instead, a common set of stable genetic influences appears to underpin genome-wide variation in BMI from middle to early old age in men and women alike., Competing Interests: The authors have declared that no competing interests exist.

We tested the causality between education and smoking using the natural experiment of discordant twin pairs allowing to optimally control for background genetic and childhood social factors. Data from 18 cohorts including 10,527 monozygotic (MZ) and same-sex dizygotic (DZ) twin pairs discordant for education and smoking were analyzed by linear fixed effects regression models. Within twin pairs, education levels were lower among the currently smoking than among the never smoking co-twins and this education difference was larger within DZ than MZ pairs. Similarly, education levels were higher among former smoking than among currently smoking co-twins, and this difference was larger within DZ pairs. Our results support the hypothesis of a causal effect of education on both current smoking status and smoking cessation. However, the even greater intra-pair differences within DZ pairs, who share only 50% of their segregating genes, provide evidence that shared genetic factors also contribute to these associations., (© 2022. The Author(s).)

Objective: To investigate the genetic architecture of internalizing symptoms in childhood and adolescence., Method: In 22 cohorts, multiple univariate genome-wide association studies (GWASs) were performed using repeated assessments of internalizing symptoms, in a total of 64,561 children and adolescents between 3 and 18 years of age. Results were aggregated in meta-analyses that accounted for sample overlap, first using all available data, and then using subsets of measurements grouped by rater, age, and instrument., Results: The meta-analysis of overall internalizing symptoms (INT overall ) detected no genome-wide significant hits and showed low single nucleotide polymorphism (SNP) heritability (1.66%, 95% CI = 0.84-2.48%, n effective  = 132,260). Stratified analyses indicated rater-based heterogeneity in genetic effects, with self-reported internalizing symptoms showing the highest heritability (5.63%, 95% CI = 3.08%-8.18%). The contribution of additive genetic effects on internalizing symptoms appeared to be stable over age, with overlapping estimates of SNP heritability from early childhood to adolescence. Genetic correlations were observed with adult anxiety, depression, and the well-being spectrum (|r g | > 0.70), as well as with insomnia, loneliness, attention-deficit/hyperactivity disorder, autism, and childhood aggression (range |r g | = 0.42-0.60), whereas there were no robust associations with schizophrenia, bipolar disorder, obsessive-compulsive disorder, or anorexia nervosa., Conclusion: Genetic correlations indicate that childhood and adolescent internalizing symptoms share substantial genetic vulnerabilities with adult internalizing disorders and other childhood psychiatric traits, which could partially explain both the persistence of internalizing symptoms over time and the high comorbidity among childhood psychiatric traits. Reducing phenotypic heterogeneity in childhood samples will be key in paving the way to future GWAS success., (Copyright © 2022 The Authors. Published by Elsevier Inc. All rights reserved.)

Background and Aims: Electronic cigarette use has escalated rapidly in recent years, particularly among youth. Little is known about the genetic influences on e-cigarette use. This study aimed to determine whether genetic risk for regular use of combustible cigarettes or for number of cigarettes smoked per day confers risk for ever e-cigarette use or frequency of e-cigarette use., Design, Setting, Participants, and Measurements: We used data from 9541 young adults from the Spit for Science longitudinal cohort study (2011-2019). Polygenic scores (PGS) of regular combustible cigarette use (PGS-RCU) and cigarettes per day (PGS-CPD) were constructed using summary statistics from the two largest available genome-wide association study (GWAS) meta-analysis of European ancestry and East Asian ancestry of combustible cigarette use and used to test whether the PGS of RCU or CPD predicted lifetime e-cigarette use and frequency of past 30-day e-cigarette use in a diverse sample of young adults of African (AFR), Admixed American (AMR), East Asian (EAS), European (EUR), and South Asian (SAS) ancestry., Findings: The PGS-RCU was associated with lifetime e-cigarette use in the EUR sample (OR = 1.27, 95% CI = 1.19-1.36, P = 7.53 × 10 -12 ), but not in the other subsamples (ps > 0.12). This association remained significant after excluding regular combustible cigarette smokers (OR = 1.21, 95% CI = 1.12-1.31, P = 3.36 × 10 -6 ). There was no statistically significant association between PGS-CPD and lifetime e-cigarette use and neither the PGS-RCU nor the PGS-CPD were associated with frequency of e-cigarette use in the past 30 days in any of the subsamples., Conclusions: Genetic factors associated with regular combustible cigarette use appear to be associated with ever e-cigarette use in young adults. We did not find evidence for shared genetic factors influencing heaviness of use of combustible cigarettes and current e-cigarette use frequency., (© 2021 Society for the Study of Addiction.)

Comparing twins from same- and opposite-sex pairs can provide information on potential sex differences in a variety of outcomes, including socioeconomic-related outcomes such as educational attainment. It has been suggested that this design can be applied to examine the putative role of intrauterine exposure to testosterone for educational attainment, but the evidence is still disputed. Thus, we established an international database of twin data from 11 countries with 88,290 individual dizygotic twins born over 100 years and tested for differences between twins from same- and opposite-sex dizygotic pairs in educational attainment. Effect sizes with 95% confidence intervals (CI) were estimated by linear regression models after adjusting for birth year and twin study cohort. In contrast to the hypothesis, no difference was found in women (β = -0.05 educational years, 95% CI -0.11, 0.02). However, men with a same-sex co-twin were slightly more educated than men having an opposite-sex co-twin (β = 0.14 educational years, 95% CI 0.07, 0.21). No consistent differences in effect sizes were found between individual twin study cohorts representing Europe, the USA, and Australia or over the cohorts born during the 20th century, during which period the sex differences in education reversed favoring women in the latest birth cohorts. Further, no interaction was found with maternal or paternal education. Our results contradict the hypothesis that there would be differences in the intrauterine testosterone levels between same-sex and opposite-sex female twins affecting education. Our findings in men may point to social dynamics within same-sex twin pairs that may benefit men in their educational careers., (Copyright © 2021 The Authors. Published by Elsevier Inc. All rights reserved.)

Childhood aggressive behavior (AGG) has a substantial heritability of around 50%. Here we present a genome-wide association meta-analysis (GWAMA) of childhood AGG, in which all phenotype measures across childhood ages from multiple assessors were included. We analyzed phenotype assessments for a total of 328 935 observations from 87 485 children aged between 1.5 and 18 years, while accounting for sample overlap. We also meta-analyzed within subsets of the data, i.e., within rater, instrument and age. SNP-heritability for the overall meta-analysis (AGG overall ) was 3.31% (SE = 0.0038). We found no genome-wide significant SNPs for AGG overall . The gene-based analysis returned three significant genes: ST3GAL3 (P = 1.6E-06), PCDH7 (P = 2.0E-06), and IPO13 (P = 2.5E-06). All three genes have previously been associated with educational traits. Polygenic scores based on our GWAMA significantly predicted aggression in a holdout sample of children (variance explained = 0.44%) and in retrospectively assessed childhood aggression (variance explained = 0.20%). Genetic correlations (r g ) among rater-specific assessment of AGG ranged from r g  = 0.46 between self- and teacher-assessment to r g  = 0.81 between mother- and teacher-assessment. We obtained moderate-to-strong r g s with selected phenotypes from multiple domains, but hardly with any of the classical biomarkers thought to be associated with AGG. Significant genetic correlations were observed with most psychiatric and psychological traits (range [Formula: see text]: 0.19-1.00), except for obsessive-compulsive disorder. Aggression had a negative genetic correlation (r g  = ~-0.5) with cognitive traits and age at first birth. Aggression was strongly genetically correlated with smoking phenotypes (range [Formula: see text]: 0.46-0.60). The genetic correlations between aggression and psychiatric disorders were weaker for teacher-reported AGG than for mother- and self-reported AGG. The current GWAMA of childhood aggression provides a powerful tool to interrogate the rater-specific genetic etiology of AGG., (© 2021. The Author(s).)

Nicotine dependence and smoking quantity are both robustly associated with the CHRNA5-A3-B4 gene cluster in the 15q25 region, and SNP rs16969968 in particular. The purpose of this paper is to use structural equation modeling techniques (SEM) to disentangle the complex pattern of relationships between rs16969968, nicotine quantity (as measured by the number of cigarettes an individual smokes per day; CPD) and nicotine dependence (as measured by the Fagerström Test for Nicotine Dependence; FTND). CPD is an indicator, but also a potential cause, of FTND, complicating the interpretation of associations between these constructs and requires a more detailed investigation than standard GWAS or general linear regression models can provide. FTND items and genotypes were collected in four samples, with a combined sample size of 5,373 respondents. A mega-analysis was conducted using a multiple group SEM approach to test competing hypotheses regarding the relationships between the SNP rs16969968, FTND and CPD. In the best fitting model, the FTND items loaded onto two correlated factors. The first, labeled "maintenance," assesses the motivation to maintain constant levels of nicotine through out the day. The second was labeled "urgency" as its items concern the urgency to restore nicotine levels after abstinence. We focus our attention on the "maintenance" factor, of which CPD was an indicator. The best fitting model included a negative feedback loop between the Maintenance factor and CPD. Accordingly, the motivation to maintain higher levels of nicotine increased the quantity of nicotine consumed, which subsequently decreases the maintenance motivation. The fact that the Maintenance-CPD feedback model fits the data best implies that there are at least two biological pathways that lead from rs16969968 to smoking behaviors. The model is consistent with a supply and demand system, which allows individuals to achieve a homeostatic equilibrium for their nicotine concentration.

Is engaging with music good for your mental health? This question has long been the topic of empirical clinical and nonclinical investigations, with studies indicating positive associations between music engagement and quality of life, reduced depression or anxiety symptoms, and less frequent substance use. However, many earlier investigations were limited by small populations and methodological limitations, and it has also been suggested that aspects of music engagement may even be associated with worse mental health outcomes. The purpose of this scoping review is first to summarize the existing state of music engagement and mental health studies, identifying their strengths and weaknesses. We focus on broad domains of mental health diagnoses including internalizing psychopathology (e.g., depression and anxiety symptoms and diagnoses), externalizing psychopathology (e.g., substance use), and thought disorders (e.g., schizophrenia). Second, we propose a theoretical model to inform future work that describes the importance of simultaneously considering music-mental health associations at the levels of (1) correlated genetic and/or environmental influences vs. (bi)directional associations, (2) interactions with genetic risk factors, (3) treatment efficacy, and (4) mediation through brain structure and function. Finally, we describe how recent advances in large-scale data collection, including genetic, neuroimaging, and electronic health record studies, allow for a more rigorous examination of these associations that can also elucidate their neurobiological substrates.

Introduction: Substance use and mood disorders account for about 10% of the global burden of disease and, among adolescents, are a significant source of disability. The present study examined whether additive genetic or shared environmental factors influenced the covariance of internalizing symptoms and cigarette use during adolescence when both of these problems begin to increase., Aims and Methods: We used data (n = 1230 pairs of twins) from the Virginia Twin Study of Adolescent Behavioral Development (mean age = 15.3) to decompose the variance of internalizing symptoms, cigarette initiation, and quantity of cigarettes smoked in a variance decomposition model that included a beta coefficient to allow for estimates of cigarette initiation to influence quantity of cigarettes smoked., Results: In biometric models we were able to equate all parameter estimates by sex. After identifying the best fitting model, parameter estimates were calculated and the significance of overlapping paths between internalizing symptoms and cigarette initiation were tested. After accounting for the genetic architecture of cigarette initiation and quantity smoked, the covariance between internalizing symptoms and cigarette use was accounted for by sex-specific shared and unique environmental factors., Conclusions: Among adolescents, the overlap in risk factors between internalizing symptoms and cigarette use is because of non-genetic, environmental factors. Further exploration of the environmental sources of variance involved in the onset of adolescents internalizing symptoms and cigarette use is warranted., Implications: We find that during adolescence common environmental factors influence the association between internalizing symptoms and cigarette use. Correlated vulnerabilities because of environmental sources between internalizing and cigarette use may be open to intervention and likely will influence the progression of internalizing and cigarette use., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: As the use of electronic cigarette (EC) continues to rise in the United States, especially among adolescents and young adults, it is necessary to better understand the factors associated with EC initiation. Specifically, it is unclear how genetic and environmental contributions influence the initiation of EC. Furthermore, the degree to which genetic and environmental influences are shared between EC initiation and conventional cigarette (CC) initiation is unknown., Methods: A sample of young adult twins ages 15-20 (N = 858 individuals; 421 complete twin pairs) was used to estimate the genetic and environmental influences on the liability of initiation unique to EC and CC as well as the degree to which these factors are shared between the two. Approximately 24% of participants initiated the use of EC, 19% initiated the use of CC, and 11% initiated the dual use., Results: Combined contributions of additive genetic and shared environmental influences were significant for CC (ACC = 0.19 [95% confidence interval {CI} = 0-0.79], p = 0.57; CCC = 0.42 [95% CI = 0-0.70], p = 0.13) and EC (AEC = 0.25 [95% CI = 0-0.83, p = 0.44; CEC = 0.42 [95% CI = 0-0.73], p = 0.12), whereas unique environmental influences were significant (ECC = 0.39 [95% CI = 0.18-0.57], p < 0.001; EEC = 0.32 [95% CI = 0.14-0.56], p < 0.001). Results also demonstrated a significant overlap of the unique environmental (rE = 0.87, p < 0.001) and familial influences contributing to correlation between the two phenotypes in the bivariate analysis., Conclusions: These preliminary results suggest that both genes and environmental influences are potential drivers of EC initiation among adolescents and young adults., Implications: This article is the first to use a sample of twin to estimate the contributions of genetic and environmental influences toward EC initiation and estimate the potential for overlapping influences with CC initiation. This study has implications for future debate about the etiology of EC and CC use with respect to potential overlapping genetic and environmental influences., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Since 1987, a group of behavior geneticists have been teaching an annual methodology workshop on how to use state-of-the-art methods to analyze genetically informative data. In the early years, the focus was on analyzing twin and family data, using information of their known genetic relatedness to infer the role of genetic and environmental factors on phenotypic variation. With the rapid evolution of genotyping and sequencing technology and availability of measured genetic data, new methods to detect genetic variants associated with human traits were developed and became the focus of workshop teaching in alternate years. Over the years, many of the methodological advances in the field of statistical genetics have been direct outgrowths of the workshop, as evidence by the software and methodological publications authored by workshop faculty. We provide data and demographics of workshop attendees and evaluate the impact of the methodology workshops on scientific output in the field by evaluating the number of papers applying specific statistical genetic methodologies authored by individuals who have attended workshops.

Aim: To examine individual variability between perceived physical features and hormones of pubertal maturation in 9-10-year-old children as a function of sociodemographic characteristics., Methods: Cross-sectional metrics of puberty were utilized from the baseline assessment of the Adolescent Brain Cognitive Development (ABCD) Study-a multi-site sample of 9-10 year-olds (n = 11,875)-and included perceived physical features via the pubertal development scale (PDS) and child salivary hormone levels (dehydroepiandrosterone and testosterone in all, and estradiol in females). Multi-level models examined the relationships among sociodemographic measures, physical features, and hormone levels. A group factor analysis (GFA) was implemented to extract latent variables of pubertal maturation that integrated both measures of perceived physical features and hormone levels., Results: PDS summary scores indicated more males (70%) than females (31%) were prepubertal. Perceived physical features and hormone levels were significantly associated with child's weight status and income, such that more mature scores were observed among children that were overweight/obese or from households with low-income. Results from the GFA identified two latent factors that described individual differences in pubertal maturation among both females and males, with factor 1 driven by higher hormone levels, and factor 2 driven by perceived physical maturation. The correspondence between latent factor 1 scores (hormones) and latent factor 2 scores (perceived physical maturation) revealed synchronous and asynchronous relationships between hormones and concomitant physical features in this large young adolescent sample., Conclusions: Sociodemographic measures were associated with both objective hormone and self-report physical measures of pubertal maturation in a large, diverse sample of 9-10 year-olds. The latent variables of pubertal maturation described a complex interplay between perceived physical changes and hormone levels that hallmark sexual maturation, which future studies can examine in relation to trajectories of brain maturation, risk/resilience to substance use, and other mental health outcomes., Competing Interests: In the interest of full disclosure, DG is founder and chief scientific and strategy advisor at Salimetrics LLC and Salivabio LLC (Carlsbad, CA) and these relationships are managed by the policies of the committee’s on conflict of interest at Johns Hopkins University School of Medicine and the University of California at Irvine. ND and DF have a financial interest in Nous Imaging Inc. and may financially benefit if the company is successful in marketing FIRMM software products. DF is a patent holder on the Framewise Integrated Real-Time Motion Monitoring (FIRMM) software and is a co-founder of Nous Imaging Inc. KG provides consultation to Pfizer, Inc. MP is an advisor to Spring Care, Inc., a behavioral startup and has received royalties for an article about methamphetamine in Uptodate. Authors AG and FB were employed by the company SRI International. SW has stock ownership in GE and Merck. All other authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2021 Herting, Uban, Gonzalez, Baker, Kan, Thompson, Granger, Albaugh, Anokhin, Bagot, Banich, Barch, Baskin-Sommers, Breslin, Casey, Chaarani, Chang, Clark, Cloak, Constable, Cottler, Dagher, Dapretto, Dick, Dosenbach, Dowling, Dumas, Edwards, Ernst, Fair, Feldstein-Ewing, Freedman, Fuemmeler, Garavan, Gee, Giedd, Glaser, Goldstone, Gray, Hawes, Heath, Heitzeg, Hewitt, Heyser, Hoffman, Huber, Huestis, Hyde, Infante, Ivanova, Jacobus, Jernigan, Karcher, Laird, LeBlanc, Lisdahl, Luciana, Luna, Maes, Marshall, Mason, McGlade, Morris, Nagel, Neigh, Palmer, Paulus, Potter, Puttler, Rajapakse, Rapuano, Reeves, Renshaw, Schirda, Sher, Sheth, Shilling, Squeglia, Sutherland, Tapert, Tomko, Yurgelun-Todd, Wade, Weiss, Zucker and Sowell.)

Eating disorders and substance use disorders frequently co-occur. Twin studies reveal shared genetic variance between liabilities to eating disorders and substance use, with the strongest associations between symptoms of bulimia nervosa and problem alcohol use (genetic correlation [r g ], twin-based = 0.23-0.53). We estimated the genetic correlation between eating disorder and substance use and disorder phenotypes using data from genome-wide association studies (GWAS). Four eating disorder phenotypes (anorexia nervosa [AN], AN with binge eating, AN without binge eating, and a bulimia nervosa factor score), and eight substance-use-related phenotypes (drinks per week, alcohol use disorder [AUD], smoking initiation, current smoking, cigarettes per day, nicotine dependence, cannabis initiation, and cannabis use disorder) from eight studies were included. Significant genetic correlations were adjusted for variants associated with major depressive disorder and schizophrenia. Total study sample sizes per phenotype ranged from ~2400 to ~537 000 individuals. We used linkage disequilibrium score regression to calculate single nucleotide polymorphism-based genetic correlations between eating disorder- and substance-use-related phenotypes. Significant positive genetic associations emerged between AUD and AN (r g = 0.18; false discovery rate q = 0.0006), cannabis initiation and AN (r g = 0.23; q < 0.0001), and cannabis initiation and AN with binge eating (r g = 0.27; q = 0.0016). Conversely, significant negative genetic correlations were observed between three nondiagnostic smoking phenotypes (smoking initiation, current smoking, and cigarettes per day) and AN without binge eating (r gs = -0.19 to -0.23; qs < 0.04). The genetic correlation between AUD and AN was no longer significant after co-varying for major depressive disorder loci. The patterns of association between eating disorder- and substance-use-related phenotypes highlights the potentially complex and substance-specific relationships among these behaviors., (© 2020 Society for the Study of Addiction.)

Objective: To explore and apply multimodel inference to test the relative contributions of latent genetic, environmental and direct causal factors to the covariation between two variables with data from the classical twin design by estimating model-averaged parameters., Methods: Behavior genetics is concerned with understanding the causes of variation in phenotypes and the causes of covariation between two or more phenotypes. Two variables may correlate as a result of genetic, shared environmental or unique environmental factors contributing to variation in both variables. Two variables may also correlate because one or both directly cause variation in the other. Furthermore, covariation may result from any combination of these sources, leading to 25 different identified structural equation models. OpenMx was used to fit all these models to account for covariation between two variables collected in twins. Multimodel inference and model averaging were used to summarize the key sources of covariation, and estimate the magnitude of these causes of covariance. Extensions of these models to test heterogeneity by sex are discussed., Results: We illustrate the application of multimodel inference by fitting a comprehensive set of bivariate models to twin data from the Virginia Twin Study of Psychiatric and Substance Use Disorders. Analyses of body mass index and tobacco consumption data show sufficient power to reject distinct models, and to estimate the contribution of each of the five potential sources of covariation, irrespective of selecting the best fitting model. Discrimination between models on sample size, type of variable (continuous versus binary or ordinal measures) and the effect size of sources of variance and covariance., Conclusions: We introduce multimodel inference and model averaging approaches to the behavior genetics community, in the context of testing models for the causes of covariation between traits in term of genetic, environmental and causal explanations.

Background: Variation in liability to cannabis use disorder has a strong genetic component (estimated twin and family heritability about 50-70%) and is associated with negative outcomes, including increased risk of psychopathology. The aim of the study was to conduct a large genome-wide association study (GWAS) to identify novel genetic variants associated with cannabis use disorder., Methods: To conduct this GWAS meta-analysis of cannabis use disorder and identify associations with genetic loci, we used samples from the Psychiatric Genomics Consortium Substance Use Disorders working group, iPSYCH, and deCODE (20 916 case samples, 363 116 control samples in total), contrasting cannabis use disorder cases with controls. To examine the genetic overlap between cannabis use disorder and 22 traits of interest (chosen because of previously published phenotypic correlations [eg, psychiatric disorders] or hypothesised associations [eg, chronotype] with cannabis use disorder), we used linkage disequilibrium score regression to calculate genetic correlations., Findings: We identified two genome-wide significant loci: a novel chromosome 7 locus (FOXP2, lead single-nucleotide polymorphism [SNP] rs7783012; odds ratio [OR] 1·11, 95% CI 1·07-1·15, p=1·84 × 10 -9 ) and the previously identified chromosome 8 locus (near CHRNA2 and EPHX2, lead SNP rs4732724; OR 0·89, 95% CI 0·86-0·93, p=6·46 × 10 -9 ). Cannabis use disorder and cannabis use were genetically correlated (r g 0·50, p=1·50 × 10 -21 ), but they showed significantly different genetic correlations with 12 of the 22 traits we tested, suggesting at least partially different genetic underpinnings of cannabis use and cannabis use disorder. Cannabis use disorder was positively genetically correlated with other psychopathology, including ADHD, major depression, and schizophrenia., Interpretation: These findings support the theory that cannabis use disorder has shared genetic liability with other psychopathology, and there is a distinction between genetic liability to cannabis use and cannabis use disorder., Funding: National Institute of Mental Health; National Institute on Alcohol Abuse and Alcoholism; National Institute on Drug Abuse; Center for Genomics and Personalized Medicine and the Centre for Integrative Sequencing; The European Commission, Horizon 2020; National Institute of Child Health and Human Development; Health Research Council of New Zealand; National Institute on Aging; Wellcome Trust Case Control Consortium; UK Research and Innovation Medical Research Council (UKRI MRC); The Brain & Behavior Research Foundation; National Institute on Deafness and Other Communication Disorders; Substance Abuse and Mental Health Services Administration (SAMHSA); National Institute of Biomedical Imaging and Bioengineering; National Health and Medical Research Council (NHMRC) Australia; Tobacco-Related Disease Research Program of the University of California; Families for Borderline Personality Disorder Research (Beth and Rob Elliott) 2018 NARSAD Young Investigator Grant; The National Child Health Research Foundation (Cure Kids); The Canterbury Medical Research Foundation; The New Zealand Lottery Grants Board; The University of Otago; The Carney Centre for Pharmacogenomics; The James Hume Bequest Fund; National Institutes of Health: Genes, Environment and Health Initiative; National Institutes of Health; National Cancer Institute; The William T Grant Foundation; Australian Research Council; The Virginia Tobacco Settlement Foundation; The VISN 1 and VISN 4 Mental Illness Research, Education, and Clinical Centers of the US Department of Veterans Affairs; The 5th Framework Programme (FP-5) GenomEUtwin Project; The Lundbeck Foundation; NIH-funded Shared Instrumentation Grant S10RR025141; Clinical Translational Sciences Award grants; National Institute of Neurological Disorders and Stroke; National Heart, Lung, and Blood Institute; National Institute of General Medical Sciences., (Copyright © 2020 The Author(s). Published by Elsevier Ltd. This is an Open Access article under the CC BY-NC-ND 4.0 license. Published by Elsevier Ltd.. All rights reserved.)

Introduction: Using Swedish nationwide registry data, we investigated the contribution of genetic and environmental risk factors to the etiology of smoking status across stages of pregnancy with increasing degrees of social and psychological pressure to reduce or quit smoking, by twin and sibling modeling., Aims and Methods: Smoking status was available before, and during early and late pregnancy from the Medical Birth Register. Twin, full-, and half-sibling pairs, both reared together and apart, born between 1960 and 1990 were obtained from national twin and genealogical registers. Genetic structural equation modeling in OpenMx was applied to the population-based data to estimate shared genetic and/or environmental covariance across stages of pregnancy, accounting for maternal birth cohort and age at pregnancy., Results: Analyses of paired data on 258 749 individuals suggested that risk factors for smoking status changed across stages of pregnancy. Results predicted substantial heritability (60-70%) and moderate contributions of shared environmental factors (10-15%) for smoking status. Whilst the same shared environmental factors were amplified from before pregnancy to late pregnancy, new primarily unique environmental factors explained ~10% of the variance during early pregnancy which was carried forward to late pregnancy., Conclusions: Using registry data on women across pregnancy, we replicated that smoking status is highly heritable. Furthermore, we found support for increased impact of shared environmental factors during pregnancy of factors already present prior to pregnancy, and an independent set of mostly new unique environmental factors that may be triggered by increased social pressure to reduce or quit smoking during pregnancy., Implications: As new factors partially explain smoking status during pregnancy and the effects of familial factors increase across pregnancy, efforts to prevent or reduce smoking during pregnancy should receive continued attention, with a focus on both the individual and the family unit., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

To provide insights into the biology of opioid dependence (OD) and opioid use (i.e., exposure, OE), we completed a genome-wide analysis comparing 4503 OD cases, 4173 opioid-exposed controls, and 32,500 opioid-unexposed controls, including participants of European and African descent (EUR and AFR, respectively). Among the variants identified, rs9291211 was associated with OE (exposed vs. unexposed controls; EUR z = -5.39, p = 7.2 × 10 -8 ). This variant regulates the transcriptomic profiles of SLC30A9 and BEND4 in multiple brain tissues and was previously associated with depression, alcohol consumption, and neuroticism. A phenome-wide scan of rs9291211 in the UK Biobank (N > 360,000) found association of this variant with propensity to use dietary supplements (p = 1.68 × 10 -8 ). With respect to the same OE phenotype in the gene-based analysis, we identified SDCCAG8 (EUR + AFR z = 4.69, p = 10 -6 ), which was previously associated with educational attainment, risk-taking behaviors, and schizophrenia. In addition, rs201123820 showed a genome-wide significant difference between OD cases and unexposed controls (AFR z = 5.55, p = 2.9 × 10 -8 ) and a significant association with musculoskeletal disorders in the UK Biobank (p = 4.88 × 10 -7 ). A polygenic risk score (PRS) based on a GWAS of risk-tolerance (n = 466,571) was positively associated with OD (OD vs. unexposed controls, p = 8.1 × 10 -5 ; OD cases vs. exposed controls, p = 0.054) and OE (exposed vs. unexposed controls, p = 3.6 × 10 -5 ). A PRS based on a GWAS of neuroticism (n = 390,278) was positively associated with OD (OD vs. unexposed controls, p = 3.2 × 10 -5 ; OD vs. exposed controls, p = 0.002) but not with OE (p = 0.67). Our analyses highlight the difference between dependence and exposure and the importance of considering the definition of controls in studies of addiction.

We investigated the heritability of educational attainment and how it differed between birth cohorts and cultural-geographic regions. A classical twin design was applied to pooled data from 28 cohorts representing 16 countries and including 193,518 twins with information on educational attainment at 25 years of age or older. Genetic factors explained the major part of individual differences in educational attainment (heritability: a 2  = 0.43; 0.41-0.44), but also environmental variation shared by co-twins was substantial (c 2  = 0.31; 0.30-0.33). The proportions of educational variation explained by genetic and shared environmental factors did not differ between Europe, North America and Australia, and East Asia. When restricted to twins 30 years or older to confirm finalized education, the heritability was higher in the older cohorts born in 1900-1949 (a 2  = 0.44; 0.41-0.46) than in the later cohorts born in 1950-1989 (a 2  = 0.38; 0.36-0.40), with a corresponding lower influence of common environmental factors (c 2  = 0.31; 0.29-0.33 and c 2  = 0.34; 0.32-0.36, respectively). In conclusion, both genetic and environmental factors shared by co-twins have an important influence on individual differences in educational attainment. The effect of genetic factors on educational attainment has decreased from the cohorts born before to those born after the 1950s.

Background: Great variability exists in response to stressful or traumatic events, leading to an interest in the construct of resilience as a trait and an outcome. The etiologic sources of variability across differing conceptualizations of resilience are poorly understood., Methods: Using behavioral genetic methods in a sample of 2,056 female twins, the present study sought to (a) examine the etiologic sources of a trait-based self-report measure of perceived resilience (PR), (b) determine the genetic and environmental overlap with an outcome-based measure of resilience, as defined by the absence of psychiatric symptoms after stressful life events, previously used by our research team (discrepancy-based psychiatric resilience [DBPR]), and (c) determine the etiologic overlap of these two resilience measures with major depressive disorder (MDD)., Results: PR was modestly (11%) heritable. A moderate degree of genetic overlap (39%) and a nominal amount of environmental overlap (3%) were found between the two alternative measures of resilience. Genetic factors that influence PR accounted for 3% of MDD heritability, whereas 31% of MDD heritability was due to DBPR genetic factors., Conclusions: Findings of a higher genetic correlation between the outcome-based resilience measure and MDD compared to the trait-based measure and MDD suggest gene-finding efforts may benefit from considering the multifaceted nature of resilience and that resilience is best understood as both a phenotypically and genetically heterogeneous construct., (© 2020 Wiley Periodicals, Inc.)

Genetic factors explain a major proportion of human height variation, but differences in mean stature have also been found between socio-economic categories suggesting a possible effect of environment. By utilizing a classical twin design which allows decomposing the variation of height into genetic and environmental components, we tested the hypothesis that environmental variation in height is greater in offspring of lower educated parents. Twin data from 29 cohorts including 65,978 complete twin pairs with information on height at ages 1 to 69 years and on parental education were pooled allowing the analyses at different ages and in three geographic-cultural regions (Europe, North America and Australia, and East Asia). Parental education mostly showed a positive association with offspring height, with significant associations in mid-childhood and from adolescence onwards. In variance decomposition modeling, the genetic and environmental variance components of height did not show a consistent relation to parental education. A random-effects meta-regression analysis of the aggregate-level data showed a trend towards greater shared environmental variation of height in low parental education families. In conclusion, in our very large dataset from twin cohorts around the globe, these results provide only weak evidence for the study hypothesis.

The extended twin model is a unique design in the genetic epidemiology toolbox that allows to simultaneously estimate multiple causes of variation such as genetic and cultural transmission, genotype-environment covariance and assortative mating, among others. Nick Martin has played a key role in the conception of the model, the collection of substantially large data sets to test the model, the application of the model to a range of phenotypes, the publication of the results including cross-cultural comparisons, the evaluation of bias and power of the design and the further elaborations of the model, such as the children-of-twins design.

The Adolescent Brain Cognitive Development (ABCD) Study is an ongoing, nationwide study of the effects of environmental influences on behavioral and brain development in adolescents. The main objective of the study is to recruit and assess over eleven thousand 9-10-year-olds and follow them over the course of 10 years to characterize normative brain and cognitive development, the many factors that influence brain development, and the effects of those factors on mental health and other outcomes. The study employs state-of-the-art multimodal brain imaging, cognitive and clinical assessments, bioassays, and careful assessment of substance use, environment, psychopathological symptoms, and social functioning. The data is a resource of unprecedented scale and depth for studying typical and atypical development. The aim of this manuscript is to describe the baseline neuroimaging processing and subject-level analysis methods used by ABCD. Processing and analyses include modality-specific corrections for distortions and motion, brain segmentation and cortical surface reconstruction derived from structural magnetic resonance imaging (sMRI), analysis of brain microstructure using diffusion MRI (dMRI), task-related analysis of functional MRI (fMRI), and functional connectivity analysis of resting-state fMRI. This manuscript serves as a methodological reference for users of publicly shared neuroimaging data from the ABCD Study., (Copyright © 2019 Elsevier Inc. All rights reserved.)

Objective: The objective of this study was to analyze how parental education modifies the genetic and environmental variances of BMI from infancy to old age in three geographic-cultural regions., Methods: A pooled sample of 29 cohorts including 143,499 twin individuals with information on parental education and BMI from age 1 to 79 years (299,201 BMI measures) was analyzed by genetic twin modeling., Results: Until 4 years of age, parental education was not consistently associated with BMI. Thereafter, higher parental education level was associated with lower BMI in males and females. Total and additive genetic variances of BMI were smaller in the offspring of highly educated parents than in those whose parents had low education levels. Especially in North American and Australian children, environmental factors shared by co-twins also contributed to the higher BMI variation in the low education level category. In Europe and East Asia, the associations of parental education with mean BMI and BMI variance were weaker than in North America and Australia., Conclusions: Lower parental education level is associated with higher mean BMI and larger genetic variance of BMI after early childhood, especially in the obesogenic macro-environment. The interplay among genetic predisposition, childhood social environment, and macro-social context is important for socioeconomic differences in BMI., (© 2019 The Obesity Society.)

Background: Despite established clinical associations among major depression (MD), alcohol dependence (AD), and alcohol consumption (AC), the nature of the causal relationship between them is not completely understood. We leveraged genome-wide data from the Psychiatric Genomics Consortium (PGC) and UK Biobank to test for the presence of shared genetic mechanisms and causal relationships among MD, AD, and AC., Methods: Linkage disequilibrium score regression and Mendelian randomization (MR) were performed using genome-wide data from the PGC (MD: 135 458 cases and 344 901 controls; AD: 10 206 cases and 28 480 controls) and UK Biobank (AC-frequency: 438 308 individuals; AC-quantity: 307 098 individuals)., Results: Positive genetic correlation was observed between MD and AD (rgMD-AD = + 0.47, P = 6.6 × 10-10). AC-quantity showed positive genetic correlation with both AD (rgAD-AC quantity = + 0.75, P = 1.8 × 10-14) and MD (rgMD-AC quantity = + 0.14, P = 2.9 × 10-7), while there was negative correlation of AC-frequency with MD (rgMD-AC frequency = -0.17, P = 1.5 × 10-10) and a non-significant result with AD. MR analyses confirmed the presence of pleiotropy among these four traits. However, the MD-AD results reflect a mediated-pleiotropy mechanism (i.e. causal relationship) with an effect of MD on AD (beta = 0.28, P = 1.29 × 10-6). There was no evidence for reverse causation., Conclusion: This study supports a causal role for genetic liability of MD on AD based on genetic datasets including thousands of individuals. Understanding mechanisms underlying MD-AD comorbidity addresses important public health concerns and has the potential to facilitate prevention and intervention efforts.

Background: Youth tobacco use behaviors are predictive of patterns in adulthood and effect long-term health outcomes. Yet, few studies have examined the effect of initial subjective experiences (ISEs) during first tobacco use, which has been found to be an indicator of individuals. sensitivity to nicotine and vulnerability to dependence., Objective: The present study aimed to determine the prevalence of ISEs across a variety of tobacco products, evaluate the factor structure of ISEs by first tobacco product used, and examine the relationship between ISEs and recent (30-day) use of tobacco products across time, using a university sample., Methods: Exploratory factor analyses were conducted to identify latent factors present with respect to items measuring ISEs with tobacco, separately by tobacco product (e.g. cigarettes, cigars, hookah, e-cigarettes). Factor scores for positive and negative ISEs were calculated. Multiple logistic regression analyses were conducted to examine associations between ISEs and recent use of each tobacco product, adjusted for age at first use, sex, race/ethnicity, and cohort., Results: ISEs differ by the first tobacco product used. Associations between factor scores for positive and negative ISEs and recent use were found across a variety of tobacco products. Overall, positive ISEs were more strongly associated with recent use, relative to negative ISEs., Conclusions: Further research is needed to identify genetic and biological pathways and social contexts influencing initial subjective experiences with tobacco use, in efforts to delay the initiation for tobacco use and reduce risk for continued use among young adults.

Liability to alcohol dependence (AD) is heritable, but little is known about its complex polygenic architecture or its genetic relationship with other disorders. To discover loci associated with AD and characterize the relationship between AD and other psychiatric and behavioral outcomes, we carried out the largest genome-wide association study to date of DSM-IV-diagnosed AD. Genome-wide data on 14,904 individuals with AD and 37,944 controls from 28 case-control and family-based studies were meta-analyzed, stratified by genetic ancestry (European, n = 46,568; African, n = 6,280). Independent, genome-wide significant effects of different ADH1B variants were identified in European (rs1229984; P = 9.8 × 10 -13 ) and African ancestries (rs2066702; P = 2.2 × 10 -9 ). Significant genetic correlations were observed with 17 phenotypes, including schizophrenia, attention deficit-hyperactivity disorder, depression, and use of cigarettes and cannabis. The genetic underpinnings of AD only partially overlap with those for alcohol consumption, underscoring the genetic distinction between pathological and nonpathological drinking behaviors.

Background: Alcohol involvement has familial associations with bulimic symptoms (i.e., binge eating, inappropriate compensatory behaviors), with several studies indicating a genetic overlap between the two. It is unclear whether overlapping familial risk with alcohol involvement extends to other eating disorder symptoms. Understanding the genetic overlap between alcohol involvement and other eating disorder symptoms may aid in more targeted interventions for comorbid alcohol use-eating disorder symptoms. Thus, we investigated associations between alcohol involvement and 2 core eating disorder symptoms: drive for thinness and body dissatisfaction in adolescent female and male twins., Methods: We assessed 3 levels of alcohol involvement: alcohol use in the last month, having ever been intoxicated, and alcohol intoxication frequency via self-report. The Eating Disorder Inventory-II assessed drive for thinness and body dissatisfaction. Sex-specific biometrical twin modeling examined the genetic overlap between alcohol involvement and eating disorder symptoms., Results: Phenotypic associations between alcohol involvement, drive for thinness, and body dissatisfaction were significantly greater in girls compared with boys. A majority of the associations between alcohol involvement, drive for thinness, and body dissatisfaction in girls, but not boys, met our threshold for twin modeling (phenotypic r > 0.20). Moderate genetic correlations were observed between the 3 aspects of alcohol involvement and drive for thinness. Moderate genetic correlations were observed between alcohol use and intoxication frequency and body dissatisfaction., Conclusions: Together with the literature on alcohol involvement and bulimic symptoms, these findings suggest a generalized association between alcohol involvement and eating disorder symptoms in girls, whereas this association may be symptom specific in boys. Genetic correlations indicate that the amount and direction of this genetic overlap differs across specific symptoms. When intervening on comorbid alcohol involvement and eating disorder symptoms, it may be important to target-specific eating disorder symptoms., (© 2018 by the Research Society on Alcoholism.)

Objective: Twin studies have shown that genetic factors in part explain the established relation between alcohol use (i.e., problematic use or abuse/dependence) and eating disorder symptoms in adolescent and adult females. However, studies have yet to elucidate if there are similar shared genetic factors between other aspects of substance involvement, such as illicit drug use and repeated cigarette smoking., Method: For those sex-specific phenotypic correlations above our threshold of .20, we used a behavioral genetic design to examine potential shared genetic overlap between self-reported lifetime illicit drug use and repeated cigarette smoking and the eating disorder symptoms of drive for thinness (DT), bulimia (BU), and body dissatisfaction (BD), as assessed with the Eating Disorder Inventory-II, in 16- to 17-year-old female and male twin pairs., Results: Only phenotypic correlations with illicit drug use met our threshold for twin modeling. Small to moderate genetic correlations were observed between illicit drug use and BU in both girls and boys and between illicit drug use and DT in girls., Conclusions: Similar etiological factors are at play in the overlap between illicit drug use and certain eating disorder symptoms in girls and boys during adolescence, such that genetic factors are important for covariance. Specifically, illicit drug use was associated with bulimia nervosa symptoms in girls and boys, which parallels previous substance use research finding a genetic overlap between alcohol use and bulimia nervosa symptoms. Future research should prospectively examine developmental trajectories to further understand the etiological overlap between substance involvement and eating disorder symptoms.

Background: Smokers tend to weigh less than never smokers, while successful quitting leads to an increase in body weight. Because smokers and non-smokers may differ in genetic and environmental family background, we analysed data from twin pairs in which the co-twins differed by their smoking behaviour to evaluate if the association between smoking and body mass index (BMI) remains after controlling for family background., Methods and Findings: The international CODATwins database includes information on smoking and BMI measured between 1960 and 2012 from 156,593 twin individuals 18-69 years of age. Individual-based data (230,378 measurements) and data of smoking discordant twin pairs (altogether 30,014 pairwise measurements, 36% from monozygotic [MZ] pairs) were analysed with linear fixed-effects regression models by 10-year periods. In MZ pairs, the smoking co-twin had, on average, 0.57 kg/m2 lower BMI in men (95% confidence interval (CI): 0.49, 0.70) and 0.65 kg/m2 lower BMI in women (95% CI: 0.52, 0.79) than the never smoking co-twin. Former smokers had 0.70 kg/m2 higher BMI among men (95% CI: 0.63, 0.78) and 0.62 kg/m2 higher BMI among women (95% CI: 0.51, 0.73) than their currently smoking MZ co-twins. Little difference in BMI was observed when comparing former smoking co-twins with their never smoking MZ co-twins (0.13 kg/m2, 95% CI 0.04, 0.23 among men; -0.04 kg/m2, 95% CI -0.16, 0.09 among women). The associations were similar within dizygotic pairs and when analysing twins as individuals. The observed series of cross-sectional associations were independent of sex, age, and measurement decade., Conclusions: Smoking is associated with lower BMI and smoking cessation with higher BMI. However, the net effect of smoking and subsequent cessation on weight development appears to be minimal, i.e. never more than an average of 0.7 kg/m2., Competing Interests: TK reports personal consultation fees from Pfizer Finland, during the conduct of the study but outside of this study. JK reports grants from the Academy of Finland and the Sigrid Juselius Foundation, during the conduct of the study, and personal fees from Pfizer Inc., outside the submitted study. AB reports working in the HealthTwiSt GmbH but the company did not have any impact on this study. FI reports grants from JSPS KAKENHI JP (23593419,16K15978), during the conduct of the study. MG reports grants from the National Institutes of Health, during the conduct of the study, and other grants from National Institutes of Health, outside the submitted work period. All other authors have nothing to declare. None of the funders played a role in the study design, data collection and analysis, decision to publish, or preparation of the manuscript and only provided financial support in the form of authors' salaries and/or research materials. None of the commercial affiliations affects our adherence to PLOS ONE policies on sharing data and materials. The specific roles of authors with commercial affiliations (AB, JK, TK) are articulated in the 'author contributions' section. The corresponding author had full access to all of the data in the study and had final responsibility for the decision to submit the paper for publication.

Childhood socioeconomic status (SES) is an important aspect of early life environment associated with later life health/health behaviors, including alcohol misuse. However, alcohol misuse is modestly heritable and involves differing etiological pathways. Externalizing disorders show significant genetic overlap with substance use, suggesting an impulsivity pathway to alcohol misuse. Alcohol misuse also overlaps with internalizing disorders, suggesting alcohol is used to cope. These differing pathways could lead to different patterns over time and/or differential susceptibility to environmental conditions, such as childhood SES. We examine whether: 1) genetic risk for externalizing and internalizing disorders influence trajectories of alcohol problems across adolescence to adulthood, 2) childhood SES alters genetic risk these disorders on trajectories of alcohol problems, and 3) these patterns are consistent across sex. We find modest evidence of gene-environment interaction. Higher childhood SES increases the risk of alcohol problems in late adolescence/early adulthood, while lower childhood SES increases the risk of alcohol problems in later adulthood, but only among males at greater genetic risk of externalizing disorders. Females from lower SES families with higher genetic risk of internalizing or externalizing disorders have greater risk of developing alcohol problems., (Copyright © 2018 Elsevier Ltd. All rights reserved.)

Drinking alcohol is a normal behavior in many societies, and prior studies have demonstrated it has both genetic and environmental sources of variation. Using two very large samples of twins and their first-degree relatives (Australia ≈ 20,000 individuals from 8,019 families; Virginia ≈ 23,000 from 6,042 families), we examine whether there are differences: (1) in the genetic and environmental factors that influence four interrelated drinking behaviors (quantity, frequency, age of initiation, and number of drinks in the last week), (2) between the twin-only design and the extended twin design, and (3) the Australian and Virginia samples. We find that while drinking behaviors are interrelated, there are substantial differences in the genetic and environmental architectures across phenotypes. Specifically, drinking quantity, frequency, and number of drinks in the past week have large broad genetic variance components, and smaller but significant environmental variance components, while age of onset is driven exclusively by environmental factors. Further, the twin-only design and the extended twin design come to similar conclusions regarding broad-sense heritability and environmental transmission, but the extended twin models provide a more nuanced perspective. Finally, we find a high level of similarity between the Australian and Virginian samples, especially for the genetic factors. The observed differences, when present, tend to be at the environmental level. Implications for the extended twin model and future directions are discussed.

Background: Considerable evidence from twin and adoption studies indicates that genetic and shared environmental factors play a role in the initiation of smoking behavior. Although twin and adoption designs are powerful to detect genetic and environmental influences, they do not provide information on the processes of assortative mating and parent-offspring transmission and their contribution to the variability explained by genetic and/or environmental factors., Methods: We examined the role of genetic and environmental factors in individual differences for smoking initiation (SI) using an extended kinship design. This design allows the simultaneous testing of additive and non-additive genetic, shared and individual-specific environmental factors, as well as sex differences in the expression of genes and environment in the presence of assortative mating and combined genetic and cultural transmission, while also estimating the regression of the prevalence of SI on age. A dichotomous lifetime 'ever' smoking measure was obtained from twins and relatives in the 'Virginia 30,000' sample and the 'Australian 25,000'., Results: Results demonstrate that both genetic and environmental factors play a significant role in the liability to SI. Major influences on individual differences appeared to be additive genetic and unique environmental effects, with smaller contributions from assortative mating, shared sibling environment, twin environment, cultural transmission, and resulting genotype-environment covariance. Age regression of the prevalence of SI was significant. The finding of negative cultural transmission without dominance led us to investigate more closely two possible mechanisms for the lower parent-offspring correlations compared to the sibling and DZ twin correlations in subsets of the data: (1) age × gene interaction, and (2) social homogamy. Neither of the mechanism provided a significantly better explanation of the data., Conclusions: This study showed significant heritability, partly due to assortment, and significant effects of primarily non-parental shared environment on liability to SI.

Objective: Social relationships, such as committed partnerships, limit risky behaviors like heavy drinking, in part, because of increased social control. The current analyses examine whether involvement in committed relationships or social support extend beyond a main effect to limit genetic liability in heavy drinking (gene-environment interaction) during young adulthood., Method: Using data from the young adult wave of the Finnish Twin Study, FinnTwin12 (n = 3,269), we tested whether involvement in romantic partnerships or social support moderated genetic influences on heavy drinking using biometric twin modeling for gene-environment interaction., Results: Involvement in a romantic partnership was associated with a decline in genetic variance in both males and females, although the overall magnitude of genetic influence was greater in males. Sex differences emerged for social support: increased social support was associated with increased genetic influence for females and reduced genetic influence for males., Conclusions: These findings demonstrate that social relationships are important moderators of genetic influences on young adult alcohol use. Mechanisms of social control that are important in limiting genetic liability during adolescence extend into young adulthood. In addition, although some relationships limit genetic liability equally, others, such as extensive social networks, may operate differently across sex.

Whether monozygotic (MZ) and dizygotic (DZ) twins differ from each other in a variety of phenotypes is important for genetic twin modeling and for inferences made from twin studies in general. We analyzed whether there were differences in individual, maternal and paternal education between MZ and DZ twins in a large pooled dataset. Information was gathered on individual education for 218,362 adult twins from 27 twin cohorts (53% females; 39% MZ twins), and on maternal and paternal education for 147,315 and 143,056 twins respectively, from 28 twin cohorts (52% females; 38% MZ twins). Together, we had information on individual or parental education from 42 twin cohorts representing 19 countries. The original education classifications were transformed to education years and analyzed using linear regression models. Overall, MZ males had 0.26 (95% CI [0.21, 0.31]) years and MZ females 0.17 (95% CI [0.12, 0.21]) years longer education than DZ twins. The zygosity difference became smaller in more recent birth cohorts for both males and females. Parental education was somewhat longer for fathers of DZ twins in cohorts born in 1990-1999 (0.16 years, 95% CI [0.08, 0.25]) and 2000 or later (0.11 years, 95% CI [0.00, 0.22]), compared with fathers of MZ twins. The results show that the years of both individual and parental education are largely similar in MZ and DZ twins. We suggest that the socio-economic differences between MZ and DZ twins are so small that inferences based upon genetic modeling of twin data are not affected.

Background: Genes and the environment contribute to variation in adult body mass index [BMI (in kg/m 2 )], but factors modifying these variance components are poorly understood. Objective: We analyzed genetic and environmental variation in BMI between men and women from young adulthood to old age from the 1940s to the 2000s and between cultural-geographic regions representing high (North America and Australia), moderate (Europe), and low (East Asia) prevalence of obesity. Design: We used genetic structural equation modeling to analyze BMI in twins ≥20 y of age from 40 cohorts representing 20 countries (140,379 complete twin pairs). Results: The heritability of BMI decreased from 0.77 (95% CI: 0.77, 0.78) and 0.75 (95% CI: 0.74, 0.75) in men and women 20-29 y of age to 0.57 (95% CI: 0.54, 0.60) and 0.59 (95% CI: 0.53, 0.65) in men 70-79 y of age and women 80 y of age, respectively. The relative influence of unique environmental factors correspondingly increased. Differences in the sets of genes affecting BMI in men and women increased from 20-29 to 60-69 y of age. Mean BMI and variances in BMI increased from the 1940s to the 2000s and were greatest in North America and Australia, followed by Europe and East Asia. However, heritability estimates were largely similar over measurement years and between regions. There was no evidence of environmental factors shared by co-twins affecting BMI. Conclusions: The heritability of BMI decreased and differences in the sets of genes affecting BMI in men and women increased from young adulthood to old age. The heritability of BMI was largely similar between cultural-geographic regions and measurement years, despite large differences in mean BMI and variances in BMI. Our results show a strong influence of genetic factors on BMI, especially in early adulthood, regardless of the obesity level in the population., (© 2017 American Society for Nutrition.)

We introduce the optimizer CSOLNP, which is a C++ implementation of the R package RSOLNP (Ghalanos & Theussl, 2012, Rsolnp: General non-linear optimization using augmented Lagrange multiplier method. R package version, 1) alongside some improvements. CSOLNP solves non-linearly constrained optimization problems using a Sequential Quadratic Programming (SQP) algorithm. CSOLNP, NPSOL (a very popular implementation of SQP method in FORTRAN (Gill et al., 1986, User's guide for NPSOL (version 4.0): A Fortran package for nonlinear programming (No. SOL-86-2). Stanford, CA: Stanford University Systems Optimization Laboratory), and SLSQP (another SQP implementation available as part of the NLOPT collection (Johnson, 2014, The NLopt nonlinear-optimization package. Retrieved from http://ab-initio.mit.edu/nlopt)) are three optimizers available in OpenMx package. These optimizers are compared in terms of runtimes, final objective values, and memory consumption. A Monte Carlo analysis of the performance of the optimizers was performed on ordinal and continuous models with five variables and one or two factors. While the relative difference between the objective values is less than 0.5%, CSOLNP is in general faster than NPSOL and SLSQP for ordinal analysis. As for continuous data, none of the optimizers performs consistently faster than the others. In terms of memory usage, we used Valgrind's heap profiler tool, called Massif, on one-factor threshold models. CSOLNP and NPSOL consume the same amount of memory, while SLSQP uses 71 MB more memory than the other two optimizers.

Improving the accuracy of phenotyping through the use of advanced psychometric tools will increase the power to find significant associations with genetic variants and expand the range of possible hypotheses that can be tested on a genome-wide scale. Multivariate methods, such as structural equation modeling (SEM), are valuable in the phenotypic analysis of psychiatric and substance use phenotypes, but these methods have not been integrated into standard genome-wide association analyses because fitting a SEM at each single nucleotide polymorphism (SNP) along the genome was hitherto considered to be too computationally demanding. By developing a method that can efficiently fit SEMs, it is possible to expand the set of models that can be tested. This is particularly necessary in psychiatric and behavioral genetics, where the statistical methods are often handicapped by phenotypes with large components of stochastic variance. Due to the enormous amount of data that genome-wide scans produce, the statistical methods used to analyze the data are relatively elementary and do not directly correspond with the rich theoretical development, and lack the potential to test more complex hypotheses about the measurement of, and interaction between, comorbid traits. In this paper, we present a method to test the association of a SNP with multiple phenotypes or a latent construct on a genome-wide basis using a diagonally weighted least squares (DWLS) estimator for four common SEMs: a one-factor model, a one-factor residuals model, a two-factor model, and a latent growth model. We demonstrate that the DWLS parameters and p-values strongly correspond with the more traditional full information maximum likelihood parameters and p-values. We also present the timing of simulations and power analyses and a comparison with and existing multivariate GWAS software package.

Background: The comparison of traits in twins from opposite-sex (OS) and same-sex (SS) dizygotic twin pairs is considered a proxy measure of prenatal hormone exposure. To examine possible prenatal hormonal influences on anthropometric traits, we compared mean height, body mass index (BMI), and the prevalence of being overweight or obese between men and women from OS and SS dizygotic twin pairs., Methods: The data were derived from the COllaborative project of Development of Anthropometrical measures in Twins (CODATwins) database, and included 68,494 SS and 53,808 OS dizygotic twin individuals above the age of 20 years from 31 twin cohorts representing 19 countries. Zygosity was determined by questionnaires or DNA genotyping depending on the study. Multiple regression and logistic regression models adjusted for cohort, age, and birth year with the twin type as a predictor were carried out to compare height and BMI in twins from OS pairs with those from SS pairs and to calculate the adjusted odds ratios and 95% confidence intervals for being overweight or obese., Results: OS females were, on average, 0.31 cm (95% confidence interval (CI) 0.20, 0.41) taller than SS females. OS males were also, on average, taller than SS males, but this difference was only 0.14 cm (95% CI 0.02, 0.27). Mean BMI and the prevalence of overweight or obesity did not differ between males and females from SS and OS twin pairs. The statistically significant differences between OS and SS twins for height were small and appeared to reflect our large sample size rather than meaningful differences of public health relevance., Conclusions: We found no evidence to support the hypothesis that prenatal hormonal exposure or postnatal socialization (i.e., having grown up with a twin of the opposite sex) has a major impact on height and BMI in adulthood.

Introduction: Previous studies in adolescents were not adequately powered to accurately disentangle genetic and environmental influences on smoking initiation (SI) across adolescence., Methods: Mega-analysis of pooled genetically informative data on SI was performed, with structural equation modeling, to test equality of prevalence and correlations across cultural backgrounds, and to estimate the significance and effect size of genetic and environmental effects according to the classical twin study, in adolescent male and female twins from same-sex and opposite-sex twin pairs (N = 19 313 pairs) between ages 10 and 19, with 76 358 longitudinal assessments between 1983 and 2007, from 11 population-based twin samples from the United States, Europe, and Australia., Results: Although prevalences differed between samples, twin correlations did not, suggesting similar etiology of SI across developed countries. The estimate of additive genetic contributions to liability of SI increased from approximately 15% to 45% from ages 13 to 19. Correspondingly, shared environmental factors accounted for a substantial proportion of variance in liability to SI at age 13 (70%) and gradually less by age 19 (40%)., Conclusions: Both additive genetic and shared environmental factors significantly contribute to variance in SI throughout adolescence. The present study, the largest genetic epidemiological study on SI to date, found consistent results across 11 studies for the etiology of SI. Environmental factors, especially those shared by siblings in a family, primarily influence SI variance in early adolescence, while an increasing role of genetic factors is seen at later ages, which has important implications for prevention strategies., Implications: This is the first study to find evidence of genetic factors in liability to SI at ages as young as 12. It also shows the strongest evidence to date for decay of effects of the shared environment from early adolescence to young adulthood. We found remarkable consistency of twin correlations across studies reflecting similar etiology of liability to initiate smoking across different cultures and time periods. Thus familial factors strongly contribute to individual differences in who starts to smoke with a gradual increase in the impact of genetic factors and a corresponding decrease in that of the shared environment., (© The Author 2017. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)

Introduction: There has been rapid growth in research exploring gene-environment interaction (G×E) contributing to smoking behaviors. Yet, no systematic review exists to date., Methods: This article aims to review evidence on the contribution of G×E to the risk of smoking. Through a search of electronic databases (ie, Google Scholar, PubMed, ScienceDirect, and Elsevier) up until May 2014, 16 studies of G×E focused on smoking behaviors were identified. These studies were compared in terms of: research design and sample studied, measure of smoking behavior and environments used, genes explored, and G×E in relation to these factors., Results: Thirteen of 16 studies (81.2%) found at least one significant G×E association. Wide variation in analytic methods was found across studies, especially with respect to the phenotypes of interest, environmental measures used, and tests conducted to estimate G×E. Heterogeneity across studies made it difficult to compare findings and evaluate the strength of evidence for G×E., Conclusions: G×E research on smoking contains studies that are methodologically different, making it difficult to assess the current state of the evidence. To decrease heterogeneity, we offer recommendations related to: (1) choice of measurement for environmental variables, (2) testing and reporting of main and interaction effects, (3) treatment of covariates, (4) reporting gene-environment correlation, and (5) conducting sensitivity analyses and checking for scaling artifacts. Continued study is needed to identify mechanisms by which genes and environmental factors combine to influence smoking behaviors., Implications: No comprehensive review of G×E studies of smoking behavior has previously been published. The present article seeks to fill this gap by providing a comprehensive review of: how G×E has been defined, how twin and molecular genetic methodologies have been used to test for G×E, and which genes and environmental factors are associated with smoking behaviors. Variations in methodological approaches make it difficult to interpret and summarize findings, so recommendations for future research are provided as a means to more easily compare and replicate findings across studies., (© The Author 2016. Published by Oxford University Press on behalf of the Society for Research on Nicotine and Tobacco. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)