There is a well-established relationship between cannabis use and psychosis, although the exact nature of this relationship is not fully understood. Recent studies have observed significant genetic overlap between a diagnosis of schizophrenia and lifetime cannabis use. Expanding on this work, the current study aimed to examine whether genetic overlap also occurs for subclinical psychosis (schizotypy) and cannabis use, as well as examining the phenotypic association between the traits. Phenotypic correlations were calculated for a variety of schizotypy and cannabis phenotypes in the UK Biobank (UKB), and single nucleotide polymorphism (SNP)-based heritability estimates and genetic correlations were calculated for these UKB phenotypes as well as for several other variables taken from recent genomewide association studies. Positive phenotypic correlations were observed between 11 out of 12 pairs of the cannabis use and schizotypy phenotypes (correlation range .05–.18), indicating a robust association between increased symptoms of schizotypy and cannabis use. SNP-based heritability estimates for two schizotypy phenotypes remained significant after multiple testing correction: social anhedonia (h2SNP = .08, SE = .02, N = 4025) and ever seen an unreal vision (h2SNP = .35, SE = .10, N = 150,717). Finally, one significant genetic correlation was observed between schizotypy and cannabis use, a negative correlation between social anhedonia and number of times used cannabis (rg = −.30, p = .012). The current study suggests the relationship between cannabis use and psychosis is also seen in subclinical symptoms of psychosis, but further research with larger samples is needed to determine the biological mechanisms underlying this association.

Background. Frequency and quantity of alcohol consumption are metrics commonly used to measure alcohol consumption behaviors. Epidemiological studies indicate that these alcohol consumption measures are differentially associated with (mental) health outcomes and socioeconomic status (SES). The current study aims to elucidate to what extent genetic risk factors are shared between frequency and quantity of alcohol consumption, and how these alcohol consumption measures are genetically associated with four broad phenotypic categories: (i) SES; (ii) substance use disorders; (iii) other psychiatric disorders; and (iv) psychological/personality traits.

Methods. Genome-Wide Association analyses were conducted to test genetic associations with alcohol consumption frequency (N = 438 308) and alcohol consumption quantity (N = 307 098 regular alcohol drinkers) within UK Biobank. For the other phenotypes, we used genome-wide association studies summary statistics. Genetic correlations (rg) between the alcohol measures and other phenotypes were estimated using LD score regression.

Results. We found a substantial genetic correlation between the frequency and quantity of alcohol consumption (rg = 0.52). Nevertheless, both measures consistently showed opposite genetic correlations with SES traits, and many substance use, psychiatric, and psychological/personality traits. High alcohol consumption frequency was genetically associated with high SES and low risk of substance use disorders and other psychiatric disorders, whereas the opposite applies for high alcohol consumption quantity.

Conclusions. Although the frequency and quantity of alcohol consumption show substantial genetic overlap, they consistently show opposite patterns of genetic associations with SES-related phenotypes. Future studies should carefully consider the potential influence of SES on the shared genetic etiology between alcohol and adverse (mental) health outcomes.

More boys than girls with attention deficit hyperactivity disorder (ADHD) receive treatment. One explanation for this bias may be that boys score higher on disruptive behavior scales than girls. Although this was supported by findings in clinical samples, recent studies in nonreferred samples showed that boys and girls with ADHD are similar with respect to their levels of disruptive behavior as reported by their mother. In this report, we investigate whether the difference in treatment rate is associated with higher teacher problem scores in boys with ADHD than in girls with ADHD. Data were obtained from mothers and teachers in a nonreferred sample of 283 boys and 291 girls with and without ADHD. Children were selected when they scored either low (controls) or high (probands) on attention problems. Mothers completed DSM-IV interviews, Child Behavior Checklists (CBCL) and the Conners Rating Scale (CRS). Teachers filled in the Teacher Report Form (TRF), and the CRS. Boys and girls with ADHD had similar levels of psychiatric illness and school impairment (such as being held back, special class placement and learning problems) by mother report. Mothers reported similar levels of aggression and attention problems in boys and girls with ADHD. In contrast, teachers consistently rated boys with ADHD as having higher scores on reports of attention problems and aggression than girls with ADHD. Gender differences vary across settings: boys and girls with ADHD are rated as behaving differently at school, but not at home. The higher level of teacher reported problem behavior at school may explain the high male–female ratio for ADHD in clinical settings. These findings have implications for the results of genetic studies that rely on referred samples, as these studies may give a distorted view of sex differences in the population.

Previous studies have looked at the structure of attention-deficit/hyperactivity disorder (ADHD) using latent class analysis (LCA) of Child Behavior Checklist (CBCL) or Diagnostic and Statistical Manual of Mental Disorders (DSM) symptom structure. These studies have identified distinct classes of children with inattentive, hyperactive, or combined subtypes and have used these classes to refine genetic analyses. The objective of the current report is to determine if the latent class structure of ADHD subtypes is consistent across informant using the Conners' Rating Scales (CRS). LCA was applied to CRS forms from mother, father, and teacher reports of 1837, 1329 and 1048 latency aged Dutch twins, respectively. The optimal solution for boys was a 5-class solution for mothers, a 3-class solution for fathers, and a 4-class solution for teachers. For girls, a 4-class solution for mothers and a 3-class for fathers and teachers was optimal. Children placed into a class by one informant had markedly increased odds ratio of being placed into the same or similar class by the other informants. Results from LCA using Dutch twins with the CRS show stability across informants suggesting that more stable phenotypes may be accessible for genotyping using a multi-informant approach.

We study the situation in which a cheap measure (X) is observed in a large, representative twin sample, and a more expensive measure (Y) is observed in a selected subsample. The aim of this study is to investigate the optimal selection design in terms of the statistical power to detect genetic and environmental influences on the variance of Y and on the covariance of X and Y. Data were simulated for 4000 dizygotic and 2000 monozygotic twins. Missingness (87% vs. 97%) was then introduced in accordance with 7 selection designs: (i) concordant low + individual high design; (ii) extreme concordant design; (iii) extreme concordant and discordant design (EDAC); (iv) extreme discordant design; (v) individual score selection design; (vi) selection of an optimal number of MZ and DZ twins; and (vii) missing completely at random. The statistical power to detect the influence of additive and dominant genetic and shared environmental effects on the variance of Y and on the covariance between X and Y was investigated. The best selection design is the individual score selection design. The power to detect additive genetic effects is high irrespective of the percentage of missingness or selection design. The power to detect shared environmental effects is acceptable when the percentage of missingness is 87%, but is low when the percentage of missingness is 97%, except for the individual score selection design, in which the power remains acceptable. The power to detect D is low, irrespective of selection design or percentage of missingness. The individual score selection design is therefore the best design for detecting genetic and environmental influences on the variance of Y and on the covariance of X and Y. However, the EDAC design may be preferred when an additional purpose of a study is to detect quantitative trait loci effects.

The Netherlands Twin Register (NTR) was established around 1987 at the Vrije Universiteit in Amsterdam, the Netherlands. The current article summarizes the longitudinal genetic analyses of maternal and paternal ratings of twins' behavior as a function of the sex of the children for the traits of aggression (AGG), attention problems (AP), anxious/depression (ANX), internalizing behavior (INT) and externalizing behavior (EXT). We found that genetic influences are the most important factor in explaining individual differences in these traits. For most phenotypes, influences of genetic factors fluctuate throughout development, with the exception of AP, for which genetic influences remain of similar magnitude. Changes in genetic influences parallel those in shared environmental influences, while nonshared environmental influences remain relatively constant. Around 10% to 20% of the variance is accounted for by parent-specific shared environment, which includes rater bias. For all phenotypes, stability throughout childhood is accounted for by genetic and shared environmental factors, while nonshared environmental influences are mainly age/measurement specific. About 15% of the phenotypic stability is accounted for by rater-specific shared environmental influences, which include rater bias. In conclusion, between ages 3 and 12 genetic factors are the most important cause of individual differences in emotional and behavioral problems.

In 1986 we began The Netherlands Twin Register (NTR) by recruiting young twins and multiples a few weeks or months after birth. Currently we register around 50% of all newborn multiples in The Netherlands. Their parents receive a questionnaire at registration and afterwards when the children are 2, 3, 5, 7, 10 and 12 years of age. Teachers are asked to rate the behavior of the children at ages 7, 10 and 12 years. Adolescent and young-adult twins were recruited through City Councils in the early 1990s. These twins, their parents and siblings participate in longitudinal survey studies that include items about health, fertility, lifestyle, addiction, personality and psychopathology, religion, socioeconomic status, and educational attainment. The total number of twins and multiples registered with the NTR is currently over 60,000. Subgroups of twins and siblings take part in studies of cognitive development, brain function and neuropsychological indices of attention processes, and molecular genetic studies of classical and behavioral cardiovascular risk factors. DNA samples are currently collected in selected twin families for two large linkage studies, which aim to find QTLs for anxious depression and for nicotine addiction. Sisters who are mothers of DZ twins contribute DNA samples for a linkage study of DZ twinning. Large cohorts of phenotyped family members from the general population are very valuable for genetic epidemiological studies and permit selection of informative families for gene finding studies.

In the classic twin design, estimation of genetic and environmental effects is based on the assumption that environmental influences are shared to the same extent by monozygotic and dizygotic twins (equal environment assumption, EEA). We explore the conditions in which the EEA can be tested based on multivariate phenotypic data. We focus on the test whether the correlation between shared environmental factors in dizygotic twins (rC) is less than 1. First, model identification was investigated analytically in Maple and Mx. Second, statistical power was examined in Mx. Third, the amount of bias caused by violation of the EEA was evaluated. Finally, applications to empirical data concern spatial ability in adolescents and aggression in children. Bivariate and trivariate models include several instances in which the EEA can be tested. The number of twin pairs that is needed to detect violation of the EEA with a statistical power of .80 (α = .05) varied between 508 and 3576 pairs for the situations considered. The bias in parameter estimates, given misspecification, ranged from 5% to 34% for additive genetic effects, and from 4% to 34% for shared environmental effects. Estimates of the nonshared environmental effects were not biased. The EEA was not violated for spatial ability or aggression. Multivariate data provide sufficient information to test the validity of the EEA. The number of twin pairs that is needed is no greater than the number typically available in most twin registries. The analysis of spatial ability and aggression indicated no detectable violation of the EEA.

Genetic and environmental influences on variance in phenotypic traits may be estimated with normal theory Maximum Likelihood (ML). However, when the assumption of multivariate normality is not met, this method may result in biased parameter estimates and incorrect likelihood ratio tests. We simulated multivariate normal distributed twin data under the assumption of three different genetic models. Genetic model fitting was performed in six data sets: multivariate normal data, discrete uncensored data, censored data, square root transformed censored data, normal scores of censored data, and categorical data. Estimates were obtained with normal theory ML (data sets 1–5) and with categorical data analysis (data set 6). Statistical power was examined by fitting reduced models to the data. When fitting an ACE model to censored data, an unbiased estimate of the additive genetic effect was obtained. However, the common environmental effect was underestimated and the unique environmental effect was overestimated. Transformations did not remove this bias. When fitting an ADE model, the additive genetic effect was underestimated while the dominant and unique environmental effects were overestimated. In all models, the correct parameter estimates were recovered with categorical data analysis. However, with categorical data analysis, the statistical power decreased. The analysis of L-shaped distributed data with normal theory ML results in biased parameter estimates. Unbiased parameter estimates are obtained with categorical data analysis, but the power decreases.

Family history interviews are widely used in psychiatric research, as well as in genetic and twin studies, and provide a way to collect family history information quickly and economically. To obtain a valid assessment of family history, it is important to investigate which family member will be able to provide accurate information. Previous research shows that the validity of family history reporting can be influenced by characteristics of the informant, such as age, gender and personal history of psychiatric disorder. The aim of this study was to investigate the role of a subject's position in a pedigree on the validity of data collection. Family history data on diabetes and psychiatric disorders were collected in three generations of 33 families by interviewing both an index subject (3rd generation) and his or her mother (2nd generation). Mothers were shown to report higher rates of diabetes and psychiatric disorder in the family compared to the index subjects. There was no significant difference in the disease rate reported by male and female index subject. Mothers who experienced a depressive episode indicated significantly more family members as having a psychiatric disorder than mothers who never experienced such an episode. This could be explained by the presence of informant bias, but may also result from the fact that depression is a heritable disorder and is therefore actually more prevalent in these families. Our findings suggest that family interview data should be collected by interviewing subjects who have a central position in the pedigree and can therefore provide information on his/her own generation, the previous and the next. In addition, psychiatric status of the informant should be carefully addressed.