The Concept of Resistance to Substance Use and a Research Approach: The Resist! Project.

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.

Effects of family history of alcohol problems on alcohol consumption: Stronger for medically underserved men.

Family history (FH), informed by genetics and family environment, can be used by practitioners for risk prediction. This study compares the associations of FH with alcohol outcomes for medically underserved (MUS) men and women with the associations for non-underserved individuals to assess the utility of FH as a screening tool for this high-priority group. Data were from 29,993 adult lifetime drinkers in the Wave 1 (2001-2002) and Wave 2 (2004-2005) National Epidemiologic Survey on Alcohol and Related Conditions. All variables except FH were measured at Wave 2. Dependent variables were 12-month alcohol consumption and alcohol use disorder (AUD). FH scores (FH-SCORE) measured the proportion of first- and second-degree biological relatives with alcohol problems. MUS status was defined by household income at or below 100% of the federal poverty line and participants reporting no usual source of health care. Multivariate linear and logistic regression models tested main and interaction effects. Models showed a significant interaction of FH-SCORE with MUS status (p < .01), with a stronger effect of FH on alcohol consumption for the MUS group. This moderating effect was weaker for women than for men (FH-SCORE x MUS x Sex three-way interaction: p < .01). AUD models showed a significant positive association with FH-SCORE (p < .001) but no association with MUS status and no significant interaction effects. In this sample of lifetime drinkers, FH was associated with higher alcohol consumption, especially for MUS men. These results encourage additional validation of FH scores to prioritize MUS adults at high risk for alcohol problems to receive preventive interventions.

The Association Between Health Literacy and Tobacco Use: Results from a Nationally Representative Survey.

Dual use of conventional cigarettes and electronic cigarettes presents an emerging public health issue. Previous research has demonstrated a negative relationship between health literacy and conventional cigarette (CIG) use. However, the relationship between health literacy and e-cigarette (ECIG) use remains unclear. This studies examines the possible association of health literacy and CIG, ECIG, or dual use. A multinomial regression was used to model the association between health literacy and current CIG use, current ECIG use, or dual tobacco use status using state-optional data from the 2016 Behavioral Risk Factor Surveillance System (BRFSS; N = 40,404). One-third of the sample (N = 13,478; 33.3%) had initiated tobacco use. Approximately 36.6% of participants exclusively used cigarettes. A smaller proportion of participants were dual users of ECIG and CIGs (7.0%) and e-cigarette exclusive users (4.5%). After adjusting for covariates, higher levels of oral health literacy was associated with lower odds of current dual use. However, there was no significant association between written HL and either conventional cigarette use or electronic cigarette use or after adjusting for covariates. Oral messaging around the dangers of CIG use may be effective at lowering odds of CIG or dual use, especially for those with higher levels of HL. Further research is needed to examine how to best disseminate information regarding the health risks of ECIGs.

Using Genetic Marginal Effects to Study Gene-Environment Interactions with GWAS Data.

Gene-environment interactions (GxE) play a central role in the theoretical relationship between genetic factors and complex traits. While genome wide GxE studies of human behaviors remain underutilized, in part due to methodological limitations, existing GxE research in model organisms emphasizes the importance of interpreting genetic associations within environmental contexts. In this paper, we present a framework for conducting an analysis of GxE using raw data from genome wide association studies (GWAS) and applying the techniques to analyze gene-by-age interactions for alcohol use frequency. To illustrate the effectiveness of this procedure, we calculate genetic marginal effects from a GxE GWAS analysis for an ordinal measure of alcohol use frequency from the UK Biobank dataset, treating the respondent's age as the continuous moderating environment. The genetic marginal effects clarify the interpretation of the GxE associations and provide a direct and clear understanding of how the genetic associations vary across age (the environment). To highlight the advantages of our proposed methods for presenting GxE GWAS results, we compare the interpretation of marginal genetic effects with an interpretation that focuses narrowly on the significance of the interaction coefficients. The results imply that the genetic associations with alcohol use frequency vary considerably across ages, a conclusion that may not be obvious from the raw regression or interaction coefficients. GxE GWAS is less powerful than the standard "main effect" GWAS approach, and therefore require larger samples to detect significant moderated associations. Fortunately, the necessary sample sizes for a successful application of GxE GWAS can rely on the existing and on-going development of consortia and large-scale population-based studies.

GW-SEM 2.0: Efficient, Flexible, and Accessible Multivariate GWAS.

Most genome-wide association study (GWAS) analyses test the association between single-nucleotide polymorphisms (SNPs) and a single trait or outcome. While valuable second-step analyses of these associations (e.g., calculating genetic correlations between traits) are common, single-step multivariate analyses of GWAS data are rarely performed. This is unfortunate because multivariate analyses can reveal information which is irrevocably obscured in multi-step analysis. One simple example is the distinction between variance common to a set of measures, and variance specific to each. Neither GWAS of sum- or factor-scores, nor GWAS of the individual measures will deliver a clean picture of loci associated with each measure's specific variance. While multivariate GWAS opens up a broad new landscape of feasible and informative analyses, its adoption has been slow, likely due to the heavy computational demands and difficulties specifying models it requires. Here we describe GW-SEM 2.0, which is designed to simplify model specification and overcome the inherent computational challenges associated with multivariate GWAS. In addition, GW-SEM 2.0 allows users to accurately model ordinal items, which are common in behavioral and psychological research, within a GWAS context. This new release enhances computational efficiency, allows users to select the fit function that is appropriate for their analyses, expands compatibility with standard genomic data formats, and outputs results for seamless reading into other standard post-GWAS processing software. To demonstrate GW-SEM's utility, we conducted (1) a series of GWAS using three substance use frequency items from data in the UK Biobank, (2) a timing study for several predefined GWAS functions, and (3) a Type I Error rate study. Our multivariate GWAS analyses emphasize the utility of GW-SEM for identifying novel patterns of associations that vary considerably between genomic loci for specific substances, highlighting the importance of differentiating between substance-specific use behaviors and polysubstance use. The timing studies demonstrate that the analyses take a reasonable amount of time and show the cost of including additional items. The Type I Error rate study demonstrates that hypothesis tests for genetic associations with latent variable models follow the hypothesized uniform distribution. Taken together, we suggest that GW-SEM may provide substantially deeper insights into the underlying genomic architecture for multivariate behavioral and psychological systems than is currently possible with standard GWAS methods. The current release of GW-SEM 2.0 is available on CRAN (stable release) and GitHub (beta release), and tutorials are available on our github wiki ( https://jpritikin.github.io/gwsem/ ).

The Genetic and Environmental Influences Contributing to the Association between Electronic and Conventional Cigarette Initiation.

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.

Assessing Stakeholder Perceptions of the Utility of Genetic Information for the Clinical Care of Mental Health Disorders: We Have a Will but Need to See the Way.

Academic stakeholders' (primarily mental health researchers and clinicians) practices and attitudes related to the translation of genetic information into mental health care were assessed. A three-part survey was administered at two large, urban universities. Response frequencies were calculated. Participants (N = 64) reported moderate levels of translational practice, adequate levels of genetic knowledge, and variable levels of genetic competence. They held positive attitudes toward translating genetic information about mental health broadly but negative attitudes about the impact that such information would have on specific aspects of care. The current study lays the groundwork for further inquiry into translating genetic information to mental health care.

Association between caregiver depression and child after-school program participation.

Depressive symptoms in parents and caregivers to children are associated with adverse biopsychosocial outcomes for caregivers themselves and the children in their custody. Higher overall and parenting-related stress, including stress over children's unsupervised after-school time, is associated with increased caregiver depression risk. Child after-school program participation is a form of social support that may mitigate parenting-related stress and reduce caregiver depression risk. This study tested for the association between child after-school program participation and caregiver depression in a sample of 486 caregivers in Richmond, Virginia. Child after-school program participation was associated with a significant reduction in the likelihood of a past caregiver depression diagnosis (OR = 0.58, 95% CI = 0.39 - 0.86, p = 0.007). This relationship remained significant after adjusting for the influence of caregiver anxiety, stress, financial hardship, and sociodemographic characteristics (OR = 0.49, 95% CI = 0.27 - 0.86, p = 0.015). Child after-school program participation may function as a protective factor that reduces caregiver depression risk. More research is needed to determine whether the observed association is causal in nature and dosage dependent. Findings from this and future studies may be used to inform evaluation of the impact of after-school programs at the family-level.

Assessment of Co-Occurring Substance Use During Opiate Treatment Programs in the United States.

The effectiveness of opiate treatment programs (OTPs) can be significantly influenced by co-occurring substance use, yet there are no standardized guidelines for assessing the influence of co-occurring substance use on treatment outcomes. In this review, we aim to provide an overview on the status of the assessment of co-occurring substance use during participation in OTPs in the United States. We searched 4 databases-MEDLINE/PubMed, EMBASE, PsychINFO, and the Cumulative Index to Nursing and Allied Health Literature (CINAHL)-from database inception to November 2018 to select relevant publications on OTPs that assessed participants' co-occurring substance use. We used a standardized protocol to extract study, intervention, and co-occurring substance use characteristics. Methodological quality was assessed using the Quality in Prognosis Studies tool. Of the 3,219 titles screened, 614 abstracts and 191 full-text original publications were assessed, leaving 85 eligible articles. Co-occurring substance use was most often assessed during opioid treatments using combined (pharmacological and behavioral) (n = 57 studies) and pharmacological (n = 25 studies) interventions. Cocaine, alcohol, marijuana, and benzodiazepines were frequently measured, while amphetamines and tobacco were rarely assessed. Great variation existed between studies in the timing and measurement of co-occurring substance use, as well as definitions for substances and polysubstance/polydrug use. Inconsistencies in the investigation of co-occurring substance use make comparison of results across studies challenging. Standardized measures and consensus on research on co-occurring substance use is needed to produce the evidence required to develop personalized treatment programs for persons using multiple substances and to inform best-practice guidelines for addressing polydrug use during participation in OTPs.

The Influence of Co-Occurring Substance Use on the Effectiveness of Opiate Treatment Programs According to Intervention Type.

This systematic review describes the influence of co-occurring substance use on the effectiveness of opiate treatment programs. MEDLINE/PubMed, Embase, PsychINFO, and the Cumulative Index to Nursing and Allied Health Literature were searched from database inception to November 28, 2018, to identify eligible opioid treatment studies in the United States that assessed the relationship between co-occurring substance use and treatment outcome (i.e., opioid abstinence and treatment retention). A total of 34 eligible studies were included. Overall, co-occurring substance use was associated with negative treatment outcomes regardless of intervention type. However, patterns varied by substance and intervention type. In particular, co-occurring use of cocaine or marijuana with opioids was associated with reduced treatment retention and opioid abstinence regardless of intervention type. Co-occurring use of amphetamines, compared with no use or reduced use of amphetamines, decreased treatment retention. Co-occurring use of alcohol was both positively and negatively associated with treatment outcomes. One study reported a significant positive association between sedative use and opioid abstinence. Generally, findings suggest that combined interventions reported better health outcomes compared with pharmacological or behavioral intervention studies alone. The findings of this review emphasize the need to comprehensively study and address co-occurring substance use to improve opiate treatment programs.

Type I Error Rates and Parameter Bias in Multivariate Behavioral Genetic Models.

For many multivariate twin models, the numerical Type I error rates are lower than theoretically expected rates using a likelihood ratio test (LRT), which implies that the significance threshold for statistical hypothesis tests is more conservative than most twin researchers realize. This makes the numerical Type II error rates higher than theoretically expected. Furthermore, the discrepancy between the observed and expected error rates increases as more variables are included in the analysis and can have profound implications for hypothesis testing and statistical inference. In two simulation studies, we examine the Type I error rates for the Cholesky decomposition and Correlated Factors models. Both show markedly lower than nominal Type I error rates under the null hypothesis, a discrepancy that increases with the number of variables in the model. In addition, we observe slightly biased parameter estimates for the Cholesky decomposition and Correlated Factors models. By contrast, if the variance-covariance matrices for variance components are estimated directly (without constraints), the numerical Type I error rates are consistent with theoretical expectations and there is no bias in the parameter estimates regardless of the number of variables analyzed. We call this the direct symmetric approach. It appears that each model-implied boundary, whether explicit or implicit, increases the discrepancy between the numerical and theoretical Type I error rates by truncating the sampling distributions of the variance components and inducing bias in the parameters. The direct symmetric approach has several advantages over other multivariate twin models as it corrects the Type I error rate and parameter bias issues, is easy to implement in current software, and has fewer optimization problems. Implications for past and future research, and potential limitations associated with direct estimation of genetic and environmental covariance matrices are discussed.

Associations Between Initial Subjective Experiences with Tobacco and Self-Reported Recent Use in Young Adulthood.

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.

A Genetic Epidemiological Mega Analysis of Smoking Initiation in Adolescents.

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.

Assessing the Association Between E-Cigarette Use and Exposure to Social Media in College Students: A Cross-Sectional Study.

BACKGROUND: Social media platforms provide an indirect medium for encouraging e-cigarette use between individuals and also serve as a direct marketing tool from e-cigarette brands to potential users. E-cigarette users share information via social media that often contains product details or health-related claims. OBJECTIVE: Determine whether e-cigarette use is associated with exposure to e-cigarettes on social media in college students. METHODS: Data from a sample of 258 college students was obtained via a clicker-response questionnaire (90% response rate). Demographic, lifetime and current e-cigarette/cigarette use, and e-cigarette exposure via social media (peer posts or advertisements) were examined. Logistic regression was used to assess the relationship between lifetime and current e-cigarette use and viewing peer posts or advertisements on social media while adjusting for cigarette use and self-posting about e-cigarettes. RESULTS: Overall, 46% of participants reported lifetime e-cigarette use, 16% current e-cigarette use, and 7% were current dual users of e-cigarettes and cigarettes. There were positive and significant associations between lifetime e-cigarette use and viewing peer posts (aOR = 3.11; 95% CI = 1.25-7.76) as well as advertisements (aOR = 3.01; 95% CI = 1.19-7.65) on e-cigarettes via social media after adjusting for cigarette use. Current e-cigarette use was only significantly associated with viewing peer posts via social media (aOR = 7.58; 95% CI = 1.66-34.6) after adjusting for cigarette use. Conclusions/Importance: Almost half of college students view peer posts and advertisements on e-cigarettes via social media. This exposure is associated with individual e-cigarette use. Continued efforts to examine online e-cigarette content are needed to help future interventions decrease e-cigarette use.

Association between major depression and type 2 diabetes in midlife: findings from the Screening Across the Lifespan Twin Study.

OBJECTIVE: Cohort studies suggest that the relationship between major depression (MD) and Type 2 diabetes (T2DM) is bidirectional. However, this association may be confounded by shared genetic or environmental factors. The objective of this study was to use a twin design to investigate the association between MD and T2DM. METHODS: Data come from the Screening Across the Lifespan Twin Study, a sample of monozygotic and dizygotic twins 40 years or older sampled from the Swedish Twin Registry (n = 37,043). MD was assessed by using the Composite International Diagnostic Inventory. Structural equation twin modeling and Cox proportional hazards modeling were used to assess the relationship between MD and T2DM. RESULTS: Approximately 19% of respondents had a history of MD and 5% had a history of T2DM. MD was associated with 32% increased likelihood of T2DM (95% confidence interval = 1.00-1.80) among twins aged 40 to 55 years, even after accounting for genetic risk, but was not associated with T2DM among twins older than 55 years. T2DM was associated with 33% increased likelihood of MD (95% confidence interval = 1.02-1.72) among younger, but not older twins. Cholesky decomposition twin modeling indicated that common unique environmental factors contribute to the association between MD and T2DM. CONCLUSIONS: Environmental factors that are unique to individuals (i.e., not shared within families) but common to both MD and T2DM contribute to their co-occurrence in midlife. However, we cannot exclude the possibility of bidirectional causation as an alternate explanation. It is likely that multiple processes are operating to effect the relation between psychiatric and medical conditions in midlife.

Comparison of Twin and Extended Pedigree Designs for Obtaining Heritability Estimates.

This study explores power assumptions relating to extended pedigree designs (EPD) and classical twin designs (CTD). We conducted statistical analyses to compare the power of the two designs for examining neuroimaging phenotypes, varying heritability and varying whether shared environmental variance is fixed or free. Results indicated that CTDs have more power to estimate heritability, with the exception of one condition: in EPDs, the power increases relative to CTDs when shared environmental variance contributes to sibling similarity only. We additionally show that assuming a priori that shared environmental effects play no role in a phenotype-as is commonly done in pedigree designs-can lead to substantially biased heritability estimates. General results indicate that both CTDs and EPDs obtain quite precise heritability estimates. Finally, we discuss methodological considerations relating to assumptions about age effects and shared environment.

Genetic and environmental contributions to the relationships between brain structure and average lifetime cigarette use.

Chronic cigarette use has been consistently associated with differences in the neuroanatomy of smokers relative to nonsmokers in case-control studies. However, the etiology underlying the relationships between brain structure and cigarette use is unclear. A community-based sample of male twin pairs ages 51-59 (110 monozygotic pairs, 92 dizygotic pairs) was used to determine the extent to which there are common genetic and environmental influences between brain structure and average lifetime cigarette use. Brain structure was measured by high-resolution structural magnetic resonance imaging, from which subcortical volume and cortical volume, thickness and surface area were derived. Bivariate genetic models were fitted between these measures and average lifetime cigarette use measured as cigarette pack-years. Widespread, negative phenotypic correlations were detected between cigarette pack-years and several cortical as well as subcortical structures. Shared genetic and unique environmental factors contributed to the phenotypic correlations shared between cigarette pack-years and subcortical volume as well as cortical volume and surface area. Brain structures involved in many of the correlations were previously reported to play a role in specific aspects of networks of smoking-related behaviors. These results provide evidence for conducting future research on the etiology of smoking-related behaviors using measures of brain morphology.

Genetic and Environmental Influences on Smoking Behavior across Adolescence and Young Adulthood in the Virginia Twin Study of Adolescent Behavioral Development and the Transitions to Substance Abuse Follow-Up.

Little is known regarding the underlying relationship between smoking initiation and current quantity smoked during adolescence into young adulthood. It is possible that the influences of genetic and environmental factors on this relationship vary across sex and age. To investigate this further, the current study applied a common causal contingency model to data from a Virginia-based twin study to determine: (1) if the same genetic and environmental factors are contributing to smoking initiation and current quantity smoked; (2) whether the magnitude of genetic and environmental factor contributions are the same across adolescence and young adulthood; and (3) if qualitative and quantitative differences in the sources of variance between males and females exist. Study results found no qualitative or quantitative sex differences in the relationship between smoking initiation and current quantity smoked, though relative contributions of genetic and environmental factors changed across adolescence and young adulthood. More specifically, smoking initiation and current quantity smoked remain separate constructs until young adulthood, when liabilities are correlated. Smoking initiation is explained by genetic, shared, and unique environmental factors in early adolescence and by genetic and unique environmental factors in young adulthood; while current quantity smoked is explained by shared environmental and unique environmental factors until young adulthood, when genetic and unique environmental factors play a larger role.