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Deepak Cyril D'Souza, Staff Psychiatrist, VA Connecticut Healthcare System; Professor of Psychiatry, Yale University School of Medicine,David Castle, University of Tasmania, Australia,Sir Robin Murray, Honorary Consultant Psychiatrist, Psychosis Service at the South London and Maudsley NHS Trust; Professor of Psychiatric Research at the Institute of Psychiatry
Cannabis use and cannabis use disorder (CUD) are heritable (~50%) complex traits closely linked to multiple neuropsychiatric syndromes. The largest genome-wide association studies have begun to identify variants that contribute to this heritability. These discoveries have started yielding answers to longstanding questions in the fields of mental health and substance use related to comorbidity and causal influence of cannabis use and CUD on other neuropsychiatric syndromes. The genetics of cannabis use appears to relate positively to psychosocial outcomes while CUD genetics map more closely to lower educational and socio-economic characteristics. The genetics of cannabis use and CUD considerably overlap with that of other substance use disorders and are being elucidated through very large genome-wide association studies. Similarly, the relationships between cannabis use, psychosis, depression, anxiety, externalizing syndromes and neurodevelopment are also being uncovered using novel genetic methods. In this chapter, we review these exciting advances in the light of pre-existing evidence from twin and family studies.
Alcohol use disorder (AUD) and schizophrenia (SCZ) frequently co-occur, and large-scale genome-wide association studies (GWAS) have identified significant genetic correlations between these disorders.
We used the largest published GWAS for AUD (total cases = 77 822) and SCZ (total cases = 46 827) to identify genetic variants that influence both disorders (with either the same or opposite direction of effect) and those that are disorder specific.
We identified 55 independent genome-wide significant single nucleotide polymorphisms with the same direction of effect on AUD and SCZ, 8 with robust effects in opposite directions, and 98 with disorder-specific effects. We also found evidence for 12 genes whose pleiotropic associations with AUD and SCZ are consistent with mediation via gene expression in the prefrontal cortex. The genetic covariance between AUD and SCZ was concentrated in genomic regions functional in brain tissues (p = 0.001).
Our findings provide further evidence that SCZ shares meaningful genetic overlap with AUD.
Drug classes are grouped based on their chemical and pharmacological properties, but prescription and illicit drugs differ in other important ways. Potential differences in genetic and environmental influences on the (mis)use of prescription and illicit drugs that are subsumed under the same class should be examined. Opioid and stimulant classes contain prescription and illicit forms differentially associated with salient risk factors (common route of administration, legality), making them useful comparators for addressing this etiological issue.
A total of 2410 individual Australian twins [Mage = 31.77 (s.d. = 2.48); 67% women] were interviewed about prescription misuse and illicit use of opioids and stimulants. Univariate and bivariate biometric models partitioned variances and covariances into additive genetic, shared environmental, and unique environmental influences across drug types.
Variation in the propensity to misuse prescription opioids was attributable to genes (41%) and unique environment (59%). Illicit opioid use was attributable to shared (71%) and unique (29%) environment. Prescription stimulant misuse was attributable to genes (79%) and unique environment (21%). Illicit stimulant use was attributable to genes (48%), shared environment (29%), and unique environment (23%). There was evidence for genetic influence common to both stimulant types, but limited evidence for genetic influence common to both opioid types. Bivariate correlations suggested that prescription opioid use may be more genetically similar to prescription stimulant use than to illicit opioid use.
Prescription opioid misuse may share little genetic influence with illicit opioid use. Future research may consider avoiding unitary drug classifications, particularly when examining genetic influences.
Impairment in reciprocal social behavior (RSB), an essential component of early social competence, clinically defines autism spectrum disorder (ASD). However, the behavioral and genetic architecture of RSB in toddlerhood, when ASD first emerges, has not been fully characterized. We analyzed data from a quantitative video-referenced rating of RSB (vrRSB) in two toddler samples: a community-based volunteer research registry (n = 1,563) and an ethnically diverse, longitudinal twin sample ascertained from two state birth registries (n = 714). Variation in RSB was continuously distributed, temporally stable, significantly associated with ASD risk at age 18 months, and only modestly explained by sociodemographic and medical factors (r2 = 9.4%). Five latent RSB factors were identified and corresponded to aspects of social communication or restricted repetitive behaviors, the two core ASD symptom domains. Quantitative genetic analyses indicated substantial heritability for all factors at age 24 months (h2 ≥ .61). Genetic influences strongly overlapped across all factors, with a social motivation factor showing evidence of newly-emerging genetic influences between the ages of 18 and 24 months. RSB constitutes a heritable, trait-like competency whose factorial and genetic structure is generalized across diverse populations, demonstrating its role as an early, enduring dimension of inherited variation in human social behavior. Substantially overlapping RSB domains, measurable when core ASD features arise and consolidate, may serve as markers of specific pathways to autism and anchors to inform determinants of autism's heterogeneity.
Studies suggest that alcohol consumption and alcohol use disorders have distinct genetic backgrounds.
We examined whether polygenic risk scores (PRS) for consumption and problem subscales of the Alcohol Use Disorders Identification Test (AUDIT-C, AUDIT-P) in the UK Biobank (UKB; N = 121 630) correlate with alcohol outcomes in four independent samples: an ascertained cohort, the Collaborative Study on the Genetics of Alcoholism (COGA; N = 6850), and population-based cohorts: Avon Longitudinal Study of Parents and Children (ALSPAC; N = 5911), Generation Scotland (GS; N = 17 461), and an independent subset of UKB (N = 245 947). Regression models and survival analyses tested whether the PRS were associated with the alcohol-related outcomes.
In COGA, AUDIT-P PRS was associated with alcohol dependence, AUD symptom count, maximum drinks (R2 = 0.47–0.68%, p = 2.0 × 10−8–1.0 × 10−10), and increased likelihood of onset of alcohol dependence (hazard ratio = 1.15, p = 4.7 × 10−8); AUDIT-C PRS was not an independent predictor of any phenotype. In ALSPAC, the AUDIT-C PRS was associated with alcohol dependence (R2 = 0.96%, p = 4.8 × 10−6). In GS, AUDIT-C PRS was a better predictor of weekly alcohol use (R2 = 0.27%, p = 5.5 × 10−11), while AUDIT-P PRS was more associated with problem drinking (R2 = 0.40%, p = 9.0 × 10−7). Lastly, AUDIT-P PRS was associated with ICD-based alcohol-related disorders in the UKB subset (R2 = 0.18%, p < 2.0 × 10−16).
AUDIT-P PRS was associated with a range of alcohol-related phenotypes across population-based and ascertained cohorts, while AUDIT-C PRS showed less utility in the ascertained cohort. We show that AUDIT-P is genetically correlated with both use and misuse and demonstrate the influence of ascertainment schemes on PRS analyses.
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.
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).
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.
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.
Gambling disorder (GD), recognized in Diagnostic and Statistical Manual of Mental Disorders, Version 5 (DSM-5) as a behavioral addiction, is associated with a range of adverse outcomes. However, there has been little research on the genetic and environmental influences on the development of this disorder. This study reports results from the largest twin study of GD conducted to date.
Replication and combined analyses were based on samples of 3292 (mean age 31.8, born 1972–79) and 4764 (mean age 37.7, born 1964–71) male, female, and unlike-sex twin pairs from the Australian Twin Registry. Univariate biometric twin models estimated the proportion of variation in the latent GD liability that could be attributed to genetic, shared environmental, and unique environmental factors, and whether these differed quantitatively or qualitatively for men and women.
In the replication study, when using a lower GD threshold, there was evidence for significant genetic (60%; 95% confidence interval (CI) 45–76%) and unique environmental (40%; 95% CI 24–56%), but not shared environmental contributions (0%; 95% CI 0–0%) to GD liability; this did not significantly differ from the original study. In the combined analysis, higher GD thresholds (such as one consistent with DSM-5 GD) and a multiple threshold definitions of GD yielded similar results. There was no evidence for quantitative or qualitative sex differences in the liability for GD.
Twin studies of GD are few in number but they tell a remarkably similar story: substantial genetic and unique environmental influences, with no evidence for shared environmental contributions or sex differences in GD liability.
Prior research has documented shared heritable contributions to non-suicidal self-injury (NSSI) and suicidal ideation (SI) as well as NSSI and suicide attempt (SA). In addition, trauma exposure has been implicated in risk for NSSI and suicide. Genetically informative studies are needed to determine common sources of liability to all three self-injurious thoughts and behaviors, and to clarify the nature of their associations with traumatic experiences.
Multivariate biometric modeling was conducted using data from 9526 twins [59% female, mean age = 31.7 years (range 24–42)] from two cohorts of the Australian Twin Registry, some of whom also participated in the Childhood Trauma Study and the Nicotine Addiction Genetics Project.
The prevalences of high-risk trauma exposure (HRT), NSSI, SI, and SA were 24.4, 5.6, 27.1, and 4.6%, respectively. All phenotypes were moderately to highly correlated. Genetic influences on self-injurious thoughts and behaviors and HRT were significant and highly correlated among men [rG = 0.59, 95% confidence interval (CI) (0.37–0.81)] and women [rG = 0.56 (0.49–0.63)]. Unique environmental influences were modestly correlated in women [rE = 0.23 (0.01–0.45)], suggesting that high-risk trauma may confer some direct risk for self-injurious thoughts and behaviors among females.
Individuals engaging in NSSI are at increased risk for suicide, and common heritable factors contribute to these associations. Preventing trauma exposure may help to mitigate risk for self-harm and suicide, either directly or indirectly via reductions in liability to psychopathology more broadly. In addition, targeting pre-existing vulnerability factors could significantly reduce risk for life-threatening behaviors among those who have experienced trauma.
The genetic component of Cannabis Use Disorder may overlap with influences acting more generally on early stages of cannabis use. This paper aims to determine the extent to which genetic influences on the development of cannabis abuse/dependence are correlated with those acting on the opportunity to use cannabis and frequency of use.
A cross-sectional study of 3303 Australian twins, measuring age of onset of cannabis use opportunity, lifetime frequency of cannabis use, and lifetime DSM-IV cannabis abuse/dependence. A trivariate Cholesky decomposition estimated additive genetic (A), shared environment (C) and unique environment (E) contributions to the opportunity to use cannabis, the frequency of cannabis use, cannabis abuse/dependence, and the extent of overlap between genetic and environmental factors associated with each phenotype.
Variance components estimates were A = 0.64 [95% confidence interval (CI) 0.58–0.70] and E = 0.36 (95% CI 0.29–0.42) for age of opportunity to use cannabis, A = 0.74 (95% CI 0.66–0.80) and E = 0.26 (95% CI 0.20–0.34) for cannabis use frequency, and A = 0.78 (95% CI 0.65–0.88) and E = 0.22 (95% CI 0.12–0.35) for cannabis abuse/dependence. Opportunity shares 45% of genetic influences with the frequency of use, and only 17% of additive genetic influences are unique to abuse/dependence from those acting on opportunity and frequency.
There are significant genetic contributions to lifetime cannabis abuse/dependence, but a large proportion of this overlaps with influences acting on opportunity and frequency of use. Individuals without drug use opportunity are uninformative, and studies of drug use disorders must incorporate individual exposure to accurately identify aetiology.
Downward trends in a number of adolescent risk behaviors including violence, crime, and drug use have been observed in the USA in recent years. It is unknown whether these are separate trends or whether they might relate to a general reduction in propensity to engage in such behaviors. Our objectives were to quantify trends in substance use disorders (SUDs) and delinquent behaviors over the 2003–2014 period and to determine whether they might reflect a single trend in an Externalizing-like trait.
We analyzed data from 12 to 17 year old participants from the National Survey on Drug Use and Health, a representative survey of the household dwelling population of the USA, across the 2003–2014 period (N = 210 599). Outcomes included past-year prevalence of six categories of substance use disorder and six categories of delinquent behavior.
Trend analysis suggested a net decline of 49% in mean number of SUDs and a 34% decline in delinquent behaviors over the 12-year period. Item Response Theory models were consistent with the interpretation that declines in each set of outcomes could be attributed to changes in mean levels of a latent, Externalizing-like trait.
Our findings suggest that declines in SUDs and some delinquent behaviors reflect a single trend related to an Externalizing-like trait. Identifying the factors contributing to this trend may facilitate continued improvement across a spectrum of adolescent risk behaviors.
Neuroticism, a ‘Big Five’ personality trait, has been associated with sub-clinical traits of both autism spectrum disorder (ASD) and attention deficit hyperactivity disorder (ADHD). The objective of the current study was to examine whether causal overlap between ASD and ADHD traits can be accounted for by genetic and environmental risk factors that are shared with neuroticism. We performed twin-based structural equation modeling using self-report data from 12 items of the Neo Five-Factor Inventory Neuroticism domain, 11 Social Responsiveness Scale items, and 12 Adult ADHD Self-Report Scale items obtained from 3,170 young adult Australian individual twins (1,081 complete pairs). Univariate analysis for neuroticism, ASD, and ADHD traits suggested that the most parsimonious models were those with additive genetic and unique environmental components, without sex limitation effects. Heritability of neuroticism, ASD, and ADHD traits, as measured by these methods, was moderate (between 40% and 45% for each respective trait). In a trivariate model, we observed moderate phenotypic (between 0.45 and 0.62), genetic (between 0.56 and 0.71), and unique environmental correlations (between 0.37and 0.55) among neuroticism, ASD, and ADHD traits, with the highest value for the shared genetic influence between neuroticism and self-reported ASD traits (rg = 0.71). Together, our results suggest that in young adults, genetic, and unique environmental risk factors indexed by neuroticism overlap with those that are shared by ASD and ADHD.
It is unknown whether there are racial differences in the heritability of major depressive disorder (MDD) because most psychiatric genetic studies have been conducted in samples comprised largely of white non-Hispanics. To examine potential differences between African-American (AA) and European-American (EA) young adult women in (1) Diagnostic and Statistical Manual of Mental Disorders, 4th Edition (DSM-IV) MDD prevalence, symptomatology, and risk factors, and (2) genetic and/or environmental liability to MDD, we analyzed data from a large population-representative sample of twins ascertained from birth records (n = 550 AA and n = 3226 EA female twins) aged 18–28 years at the time of MDD assessment by semi-structured psychiatric interview. AA women were more likely to have MDD risk factors; however, there were no significant differences in lifetime MDD prevalence between AA and EA women after adjusting for covariates (odds ratio = 0.88, 95% confidence interval [CI]: 0.67–1.15). Most MDD risk factors identified among AA women were also associated with MDD at similar magnitudes among EA women. Although the MDD heritability point estimate was higher among AA women than EA women in a model with paths estimated separately by race (56%, 95% CI: 29–78% vs. 41%, 95% CI: 29–52%), the best fitting model was one in which additive genetic and non-shared environmental paths for AA and EA women were constrained to be equal (A = 43%, 33–53% and E = 57%, 47–67%). In spite of a marked elevation in the prevalence of environmental risk exposures related to MDD among AA women, there were no significant differences in lifetime prevalence or heritability of MDD between AA and EA young women.
Aspects of disordered eating and personality traits, such as neuroticism, are correlated and individually heritable. We examined the phenotypic correlation between binge eating episodes and indices of personality (neuroticism, extraversion, openness to experience, agreeableness, conscientiousness, and control/impulsivity). For correlations ≥|0.20|, we estimated the extent to which genetic and environmental factors contributed to this correlation. Participants included 3,446 European American same-sex female twins from the Missouri Adolescent Female Twin Study (median age = 22 years). Binge eating episode was assessed via interview questions. Personality traits were assessed by self-report questionnaires. There was a significant moderate phenotypic correlation between binge eating episode and neuroticism (r = 0.33) as well as conscientiousness (r = -0.21), while other correlations were significant but smaller (r ranging from -0.14 to 0.14). Individual differences in binge eating episodes, neuroticism, and conscientiousness were attributed to additive genetic influences (38% [95% CI: 21–53%], 45% [95% CI: 38–52%], and 44% [95% CI: 0.33–0.55%] respectively), with the remaining variance attributed to individual-specific environmental influences. Covariance was attributable to genetic (neuroticism rg = 0.37; conscientiousness rg = -0.22) and individual-specific environmental (neuroticism re = 0.28; conscientiousness re = -0.19) influences. Personality traits may be an early indicator of genetic vulnerability to a variety of pathological behaviors, including binge eating episode. Furthermore, prior research documenting phenotypic correlations between eating disorder diagnoses and personality may have stemmed from etiological overlap between these personality traits and aspects of disordered eating, such as binge eating episode.
Context: The detection and replication of genes involved in psychiatric outcome has been notoriously difficult. Phenotypic measurement has been offered as one explanation, although most of this discussion has focused on problems with binary diagnoses. Objective: This article focuses on two additional components of phenotypic measurement that deserve further consideration in evaluating genetic associations: (1) the measure used to reflect the outcome of interest, and (2) the developmental stage of the study population. We focus our discussion of these issues around the construct of impulsivity and externalizing disorders, and the association of these measures with a specific gene, GABRA2. Design, Setting, and Participants: Data were analyzed from the Collaborative Study on the Genetics of Alcoholism Phase IV assessment of adolescents and young adults (ages 12–26; N = 2,128). Main Outcome Measures: Alcohol dependence, illicit drug dependence, childhood conduct disorder, and adult antisocial personality disorder symptoms were measured by psychiatric interview; Achenbach youth/adult self-report externalizing scale; Zuckerman Sensation-Seeking scale; Barratt Impulsivity scale; NEO extraversion and consciousness. Results: GABRA2 was associated with subclinical levels of externalizing behavior as measured by the Achenbach in both the adolescent and young adult samples. Contrary to previous associations in adult samples, it was not associated with clinical-level DSM symptom counts of any externalizing disorders in these younger samples. There was also association with sensation-seeking and extraversion, but only in the adolescent sample. There was no association with the Barratt impulsivity scale or conscientiousness. Conclusions: Our results suggest that the pathway by which GABRA2 initially confers risk for eventual alcohol problems begins with a predisposition to sensation-seeking early in adolescence. The findings support the heterogeneous nature of impulsivity and demonstrate that both the measure used to assess a construct of interest and the age of the participants can have profound implications for the detection of genetic associations.
This study examined the interplay between the influence of peers who promote alcohol use and μ-opioid receptor M1 (OPRM1) genetic variation in the intergenerational transmission of alcohol use disorder (AUD) symptoms while separating the “traitlike” components of AUD symptoms from their age-specific manifestations at three ages from emerging adulthood (17–23 years) to adulthood (29–40 years). The results for males were consistent with genetically influenced peer selection mechanisms as mediators of parent alcoholism effects. Male children of alcoholics were less likely to be carriers of the G allele in single nucleotide polymorphism A118G (rs1799971), and those who were homozygous for the A allele were more likely to affiliate with alcohol use promoting peers who increased the risk for AUD symptoms at all ages. There was evidence for women of an interaction between OPRM1 variation and peer affiliations but only at the earliest age band. Peer influences had stronger effects among women who were G-carriers. These results illustrate the complex ways in which the interplay between influences at multiple levels of analysis can underlie the intergenerational transmission of alcohol disorders as well as the importance of considering age and gender differences in these pathways.
Cannabis is the most widely used illicit drug throughout the developed world and there is consistent evidence of heritable influences on multiple stages of cannabis involvement including initiation of use and abuse/dependence. In this paper, we describe the methodology and preliminary results of a large-scale interview study of 3,824 young adult twins (born 1972–1979) and their siblings. Cannabis use was common with 75.2% of males and 64.7% of females reporting some lifetime use of cannabis while 24.5% of males and 11.8% of females reported meeting criteria for DSM-IV cannabis abuse or dependence. Rates of other drug use disorders and common psychiatric conditions were highly correlated with extent of cannabis involvement and there was consistent evidence of heritable influences across a range of cannabis phenotypes including early (≤15 years) opportunity to use (h2 = 72%), early (≤16 years) onset use (h2 = 80%), using cannabis 11+ times lifetime (h2 = 76%), and DSM abuse/dependence (h2 = 72%). Early age of onset of cannabis use was strongly associated with increased rates of subsequent use of other illicit drugs and with illicit drug abuse/dependence; further analyses indicating that some component of this association may have been mediated by increasing exposure to and opportunity to use other illicit drugs.
Although personality measures such as neuroticism (N), extraversion (E) and novelty-seeking (NS) are associated with the use and abuse/dependence of illicit drugs, little is known about the degree to which these associations are due to genetic or environmental factors. The goal of this analysis was to estimate the extent of genetic and environmental overlap between three dimensions of personality (N, E and NS) and illicit psychoactive substance use and abuse/dependence. Using data from adult male and female twins from the Mid-Atlantic Twin Registry, we used the structural equation modeling package Mx to perform bivariate Cholesky decompositions for personality measures of N, E and NS, individually with cannabis, cocaine, sedatives, stimulants and hallucinogens. This was done separately for use and for a polychotomous diagnosis of abuse and/or dependence. Sex differences were tested. The phenotypic relationship between personality and use and abuse/dependence of illicit drugs were moderate and most of the covariance was explained by genetic factors. Sexes could be equated for N and E but not for NS. For NS, use and abuse/dependence of illicit drugs showed greater phenotypic and genetic overlap in males than females. Of the personality measures, NS and illicit drug use and abuse/dependence were most closely related. NS was most closely related to cannabis use while N showed significant genetic overlap with sedative use. NS in males appears to be a good indicator of risk for cannabis use. This result may be useful for candidate gene studies.
Alcohol dependence symptoms and consumption measures were examined for stability and heritability. Data were collected from 12,045 individuals (5376 twin pairs, 1293 single twins) aged 19 to 90 years in telephone interviews conducted in three collection phases. Phases 1 and 2 were independent samples, but Phase 3 targeted families of smokers and drinkers from the Phase 1 and 2 samples. The stability of dependence symptoms and consumption was examined for 1158 individuals interviewed in both Phases 1 and 3 (mean interval = 11.0 years). For 1818 individuals interviewed in Phases 2 and 3 (mean interval = 5.5 years) the stability of consumption was examined. Heritability was examined for each collection phase and retest samples from the selected Phase 3 collection. The measures examined were a dependence score, based on DSM-IIIR and DSM-IV criteria for substance dependence, and a quantity × frequency measure. Measures were moderately stable, with test–retest correlations ranging from .58 to .61 for dependence and from .55 to .64 for consumption. However, the pattern of changes over time for dependence suggested that the measure may more strongly reflect recent than lifetime experience. Similar to previous findings, heritabilities ranged from .42 to .51 for dependence and from .31 to .51 for consumption. Consumption was significantly less heritable in the younger Phase 2 cohort (23–39 years) compared to the older Phase 1 cohort (28–90 years).
Depressive symptoms reflect depressed mood over a relatively short period of time and are measured using symptom checklists such as the SCL-90. There is some evidence that depressive symptoms are associated with major depression (MD), which is a clinically diagnosed psychiatric illness. Genetic studies of depressive symptomatology suggest a role for genetic factors as well as unique environmental influences. While epidemio-logical research suggests that depressive symptoms may be influenced by sex-specific factors, few genetically informative findings support this result entirely. We used data from male and female same-sex and opposite-sex twin pairs to assess the extent to which genetic, shared and unique environmental factors influence depressive symptoms. Furthermore, we tested for the presence of qualitative and quantitative sex differences in depressive symptoms. Our results suggest that similar to other studies, depressive symptomatology is moderately heritable (31%) with no evidence for shared environmental factors. Our best fitting model suggests that there are no qualitative or quantitative sex differences in depressive symptoms. Our analyses suggest that while there may be mean differences in the levels of depressive symptoms across sexes, the genetic and environmental factors that predispose males and females to depressive symptoms are not different.
This article applies methods of latent class analysis (LCA) to data on lifetime illicit drug use in order to determine whether qualitatively distinct classes of illicit drug users can be identified. Self-report data on lifetime illicit drug use (cannabis, stimulants, hallucinogens, sedatives, inhalants, cocaine, opioids and solvents) collected from a sample of 6265 Australian twins (average age 30 years) were analyzed using LCA. Rates of childhood sexual and physical abuse, lifetime alcohol and tobacco dependence, symptoms of illicit drug abuse/dependence and psychiatric comorbidity were compared across classes using multinomial logistic regression. LCA identified a 5-class model: Class 1 (68.5%) had low risks of the use of all drugs except cannabis; Class 2 (17.8%) had moderate risks of the use of all drugs; Class 3 (6.6%) had high rates of cocaine, other stimulant and hallucinogen use but lower risks for the use of sedatives or opioids. Conversely, Class 4 (3.0%) had relatively low risks of cocaine, other stimulant or hallucinogen use but high rates of sedative and opioid use. Finally, Class 5 (4.2%) had uniformly high probabilities for the use of all drugs. Rates of psychiatric comorbidity were highest in the polydrug class although the sedative/opioid class had elevated rates of depression/suicidal behaviors and exposure to childhood abuse. Aggregation of population-level data may obscure important subgroup differences in patterns of illicit drug use and psychiatric comorbidity. Further exploration of a ‘self-medicating’ subgroup is needed.