Search

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

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. Author summary: We used a new method called genomic structural equation modeling to analyse data from 165,717 men and 193,073 women from the UKBiobank. Our results revealed that genetic influences on BMI were very stable between ages 40 and 73. In other words, there did not appear to be any age-dependent genetic influences on BMI during this period. The same results were seen in men and women. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Graph The Reverend Dr. Lindon John Eaves was an eminent professor in behavior genetics, with an international reputation as an exceptional scientist. Dr. Eaves was also highly influential in his supervision of graduate and post-doctoral students at the University of Birmingham, the University of Oxford, and subsequently VCU, of whom many have very distinguished careers of their own. Professor Eaves was a distinguished professor, scholar, mentor and friend, but foremost a genuine human being. [Extracted from the article]

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. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]