Maximizing the value of twin studies in health and behaviour.

In the classical twin design, researchers compare trait resemblance in cohorts of identical and non-identical twins to understand how genetic and environmental factors correlate with resemblance in behaviour and other phenotypes. The twin design is also a valuable tool for studying causality, intergenerational transmission, and gene-environment correlation and interaction. Here we review recent developments in twin studies, recent results from twin studies of new phenotypes and recent insights into twinning. We ask whether the results of existing twin studies are representative of the general population and of global diversity, and we conclude that stronger efforts to increase representativeness are needed. We provide an updated overview of twin concordance and discordance for major diseases and mental disorders, which conveys a crucial message: genetic influences are not as deterministic as many believe. This has important implications for public understanding of genetic risk prediction tools, as the accuracy of genetic predictions can never exceed identical twin concordance rates.

Smoking remains associated with education after controlling for social background and genetic factors in a study of 18 twin cohorts.

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

Delayed tracking and inequality of opportunity: Gene-environment interactions in educational attainment.

There are concerns that ability tracking at a young age increases unequal opportunities for children of different socioeconomic background to develop their potential. To disentangle family influence and potential ability, we applied moderation models to twin data on secondary educational track level from the Netherlands Twin Register (N = 8847). Delaying tracking to a later age is associated with a lower shared environmental influence and a larger genetic influence on track level in adolescence. This is in line with the idea that delaying tracking improves equality of opportunity. Our results further suggest that this is mostly because delaying tracking reduces the indirect influence of family background on track level via the test performance of students. Importantly, delaying tracking improves the realization of genetic potential especially among students with low test scores, while it lowers shared environmental influence on track level for students of all test performance levels.

Safe Linkage of Cohort and Population-Based Register Data in a Genomewide Association Study on Health Care Expenditure.

There are research questions whose answers require record linkage of multiple databases that may be characterized by limited options for full data sharing. For this purpose, the Open Data Infrastructure for Social Science and Economic Innovations (ODISSEI) consortium has supported the development of the ODISSEI Secure Supercomputer (OSSC) platform that allows researchers to link cohort data to data from Statistics Netherlands and run large-scale analyses in a high-performance computing (HPC) environment. Here, we report a successful record linkage genomewide association (GWA) study on expenditure for total health, mental health, primary and hospital care, and medication. Record linkage for genotype data from 16,726 participants from the Netherlands Twin Register (NTR) with data from Statistics Netherlands was accomplished in the secure OSSC platform, followed by gene-based tests and estimation of total and single nucleotide polymorphism (SNP)-based heritability. The total heritability of expenditure ranged between 29.4% (SE 0.8) and 37.5% (SE 0.8), but GWA analyses did not identify SNPs or genes that were genomewide significantly associated with health care expenditure. SNP-based heritability was between 0.0% (SE 3.5) and 5.4% (SE 4.0) and was different from zero for mental health care and primary care expenditure. We conclude that successfully linking genotype data to administrative health care expenditure data from Statistics Netherlands is feasible and demonstrates a series of analyses on health care expenditure. The OSSC platform offers secure possibilities for analyzing linked data in large scale and realizing sample sizes required for GWA studies, providing invaluable opportunities to answer many new research questions.

Measurement and genetic architecture of lifetime depression in the Netherlands as assessed by LIDAS (Lifetime Depression Assessment Self-report).

BACKGROUND: Major depressive disorder (MDD) is a common mood disorder, with a heritability of around 34%. Molecular genetic studies made significant progress and identified genetic markers associated with the risk of MDD; however, progress is slowed down by substantial heterogeneity as MDD is assessed differently across international cohorts. Here, we used a standardized online approach to measure MDD in multiple cohorts in the Netherlands and evaluated whether this approach can be used in epidemiological and genetic association studies of depression. METHODS: Within the Biobank Netherlands Internet Collaboration (BIONIC) project, we collected MDD data in eight cohorts involving 31 936 participants, using the online Lifetime Depression Assessment Self-report (LIDAS), and estimated the prevalence of current and lifetime MDD in 22 623 unrelated individuals. In a large Netherlands Twin Register (NTR) twin-family dataset (n ≈ 18 000), we estimated the heritability of MDD, and the prediction of MDD in a subset (n = 4782) through Polygenic Risk Score (PRS). RESULTS: Estimates of current and lifetime MDD prevalence were 6.7% and 18.1%, respectively, in line with population estimates based on validated psychiatric interviews. In the NTR heritability estimates were 0.34/0.30 (s.e. = 0.02/0.02) for current/lifetime MDD, respectively, showing that the LIDAS gives similar heritability rates for MDD as reported in the literature. The PRS predicted risk of MDD (OR 1.23, 95% CI 1.15-1.32, R2 = 1.47%). CONCLUSIONS: By assessing MDD status in the Netherlands using the LIDAS instrument, we were able to confirm previously reported MDD prevalence and heritability estimates, which suggests that this instrument can be used in epidemiological and genetic association studies of depression.

Parental Age and Offspring Childhood Mental Health: A Multi-Cohort, Population-Based Investigation.

To examine the contributions of maternal and paternal age on offspring externalizing and internalizing problems, this study analyzed problem behaviors at age 10-12 years from four Dutch population-based cohorts (N = 32,892) by a multiple informant design. Bayesian evidence synthesis was used to combine results across cohorts with 50% of the data analyzed for discovery and 50% for confirmation. There was evidence of a robust negative linear relation between parental age and externalizing problems as reported by parents. In teacher-reports, this relation was largely explained by parental socio-economic status. Parental age had limited to no association with internalizing problems. Thus, in this large population-based study, either a beneficial or no effect of advanced parenthood on child problem behavior was observed.

Genetic Similarity Assessment of Twin-Family Populations by Custom-Designed Genotyping Array.

Twin registries often take part in large collaborative projects and are major contributors to genome-wide association (GWA) meta-analysis studies. In this article, we describe genotyping of twin-family populations from Australia, the Midwestern USA (Avera Twin Register), the Netherlands (Netherlands Twin Register), as well as a sample of mothers of twins from Nigeria to assess the extent, if any, of genetic differences between them. Genotyping in all cohorts was done using a custom-designed Illumina Global Screening Array (GSA), optimized to improve imputation quality for population-specific GWA studies. We investigated the degree of genetic similarity between the populations using several measures of population variation with genotype data generated from the GSA. Visualization of principal component analysis (PCA) revealed that the Australian, Dutch and Midwestern American populations exhibit negligible interpopulation stratification when compared to each other, to a reference European population and to globally distant populations. Estimations of fixation indices (FST values) between the Australian, Midwestern American and Netherlands populations suggest minimal genetic differentiation compared to the estimates between each population and a genetically distinct cohort (i.e., samples from Nigeria genotyped on GSA). Thus, results from this study demonstrate that genotype data from the Australian, Dutch and Midwestern American twin-family populations can be reasonably combined for joint-genetic analysis.

Neighbourhood characteristics and prevalence and severity of depression: pooled analysis of eight Dutch cohort studies.

BACKGROUND: Studies on neighbourhood characteristics and depression show equivocal results.AimsThis large-scale pooled analysis examines whether urbanisation, socioeconomic, physical and social neighbourhood characteristics are associated with the prevalence and severity of depression. METHOD: Cross-sectional design including data are from eight Dutch cohort studies (n = 32 487). Prevalence of depression, either DSM-IV diagnosis of depressive disorder or scoring for moderately severe depression on symptom scales, and continuous depression severity scores were analysed. Neighbourhood characteristics were linked using postal codes and included (a) urbanisation grade, (b) socioeconomic characteristics: socioeconomic status, home value, social security beneficiaries and non-Dutch ancestry, (c) physical characteristics: air pollution, traffic noise and availability of green space and water, and (d) social characteristics: social cohesion and safety. Multilevel regression analyses were adjusted for the individual's age, gender, educational level and income. Cohort-specific estimates were pooled using random-effects analysis. RESULTS: The pooled analysis showed that higher urbanisation grade (odds ratio (OR) = 1.05, 95% CI 1.01-1.10), lower socioeconomic status (OR = 0.90, 95% CI 0.87-0.95), higher number of social security beneficiaries (OR = 1.12, 95% CI 1.06-1.19), higher percentage of non-Dutch residents (OR = 1.08, 95% CI 1.02-1.14), higher levels of air pollution (OR = 1.07, 95% CI 1.01-1.12), less green space (OR = 0.94, 95% CI 0.88-0.99) and less social safety (OR = 0.92, 95% CI 0.88-0.97) were associated with higher prevalence of depression. All four socioeconomic neighbourhood characteristics and social safety were also consistently associated with continuous depression severity scores. CONCLUSIONS: This large-scale pooled analysis across eight Dutch cohort studies shows that urbanisation and various socioeconomic, physical and social neighbourhood characteristics are associated with depression, indicating that a wide range of environmental aspects may relate to poor mental health.Declaration of interestNone.

Extending Causality Tests with Genetic Instruments: An Integration of Mendelian Randomization with the Classical Twin Design.

Although experimental studies are regarded as the method of choice for determining causal influences, these are not always practical or ethical to answer vital questions in health and social research (e.g., one cannot assign individuals to a "childhood trauma condition" in studying the causal effects of childhood trauma on depression). Key to solving such questions are observational studies. Mendelian Randomization (MR) is an influential method to establish causality in observational studies. MR uses genetic variants to test causal relationships between exposures/risk factors and outcomes such as physical or mental health. Yet, individual genetic variants have small effects, and so, when used as instrumental variables, render MR liable to weak instrument bias. Polygenic scores have the advantage of larger effects, but may be characterized by horizontal pleiotropy, which violates a central assumption of MR. We developed the MR-DoC twin model by integrating MR with the Direction of Causation twin model. This model allows us to test pleiotropy directly. We considered the issue of parameter identification, and given identification, we conducted extensive power calculations. MR-DoC allows one to test causal hypotheses and to obtain unbiased estimates of the causal effect given pleiotropic instruments, while controlling for genetic and environmental influences common to the outcome and exposure. Furthermore, the approach allows one to employ strong instrumental variables in the form of polygenic scores, guarding against weak instrument bias, and increasing the power to detect causal effects of exposures on potential outcomes. Beside allowing to test pleiotropy directly, incorporating in MR data collected from relatives provide additional within-family data that resolve additional assumptions like random mating, the absence of the gene-environment interaction/covariance, no dyadic effects. Our approach will enhance and extend MR's range of applications, and increase the value of the large cohorts collected at twin/family registries as they correctly detect causation and estimate effect sizes even in the presence of pleiotropy.

Mathematical Ability and Socio-Economic Background: IRT Modeling to Estimate Genotype by Environment Interaction.

Genotype by environment interaction in behavioral traits may be assessed by estimating the proportion of variance that is explained by genetic and environmental influences conditional on a measured moderating variable, such as a known environmental exposure. Behavioral traits of interest are often measured by questionnaires and analyzed as sum scores on the items. However, statistical results on genotype by environment interaction based on sum scores can be biased due to the properties of a scale. This article presents a method that makes it possible to analyze the actually observed (phenotypic) item data rather than a sum score by simultaneously estimating the genetic model and an item response theory (IRT) model. In the proposed model, the estimation of genotype by environment interaction is based on an alternative parametrization that is uniquely identified and therefore to be preferred over standard parametrizations. A simulation study shows good performance of our method compared to analyzing sum scores in terms of bias. Next, we analyzed data of 2,110 12-year-old Dutch twin pairs on mathematical ability. Genetic models were evaluated and genetic and environmental variance components estimated as a function of a family's socio-economic status (SES). Results suggested that common environmental influences are less important in creating individual differences in mathematical ability in families with a high SES than in creating individual differences in mathematical ability in twin pairs with a low or average SES.

Sum Scores in Twin Growth Curve Models: Practicality Versus Bias.

To study behavioral or psychiatric phenotypes, multiple indices of the behavior or disorder are often collected that are thought to best reflect the phenotype. Combining these items into a single score (e.g. a sum score) is a simple and practical approach for modeling such data, but this simplicity can come at a cost in longitudinal studies, where the relevance of individual items often changes as a function of age. Such changes violate the assumptions of longitudinal measurement invariance (MI), and this violation has the potential to obfuscate the interpretation of the results of latent growth models fit to sum scores. The objectives of this study are (1) to investigate the extent to which violations of longitudinal MI lead to bias in parameter estimates of the average growth curve trajectory, and (2) whether absence of MI affects estimates of the heritability of these growth curve parameters. To this end, we analytically derive the bias in the estimated means and variances of the latent growth factors fit to sum scores when the assumption of longitudinal MI is violated. This bias is further quantified via Monte Carlo simulation, and is illustrated in an empirical analysis of aggression in children aged 3-12 years. These analyses show that measurement non-invariance across age can indeed bias growth curve mean and variance estimates, and our quantification of this bias permits researchers to weigh the costs of using a simple sum score in longitudinal studies. Simulation results indicate that the genetic variance decomposition of growth factors is, however, not biased due to measurement non-invariance across age, provided the phenotype is measurement invariant across birth-order and zygosity in twins.

Child care, socio-economic status and problem behavior: a study of gene-environment interaction in young Dutch twins.

The influences of formal child care before age 4 on behavioral problems at 3, 5, and 7 years of age were assessed in 18,932 Dutch twins (3,878 attended formal child care). The effect of formal child care was studied on the average level of problem behavior and as moderator of genetic and non-genetic influences, while taking into account effects of sex and parental socio-economic status (SES). There was a small association between attending formal child care and higher externalizing problems, especially when SES was low. Heritability was lower for formal child care and in lower SES conditions. These effects were largest at age 7 and for externalizing problems. In 7 year-old boys and girls, the difference in heritability between the formal child care group of low SES and the home care group of high SES was 30% for externalizing and ~20% for internalizing problems. The decrease in heritability was explained by a larger influence of the environment, rather than by a decrease in genetic variance. These results support a bioecological model in which heritability is lower in circumstances associated with more problem behavior.

GE covariance through phenotype to environment transmission: an assessment in longitudinal twin data and application to childhood anxiety.

We considered identification of phenotype (at occasion t) to environment (at occasion t + 1) transmission in longitudinal model comprising genetic, common and unique environmental simplex models (autoregressions). This type of transmission, which gives rise to genotype-environment covariance, is considered to be important in developmental psychology. Having established identifying constraints, we addressed the issue of statistical power to detect such transmission given a limited set of parameter values. The power is very poor in the ACE simplex, but is good in the AE model. We investigated misspecification, and found that fitting the standard ACE simplex to covariance matrices generated by an AE simplex with phenotype to E transmission produces the particular result of a rank 1 C (common environment) covariance matrix with positive transmission, and a rank 1 D (dominance) matrix given negative transmission. We applied the models to mother ratings of anxiety in female twins (aged 3, 7, 10, and 12 years), and obtained support for the positive effect of one twin's phenotype on the other twin's environment.

Can genetics help psychometrics? Improving dimensionality assessment through genetic factor modeling.

In the present article, we discuss the role that quantitative genetic methodology may play in assessing and understanding the dimensionality of psychological (psychometric) instruments. Specifically, we study the relationship between the observed covariance structures, on the one hand, and the underlying genetic and environmental influences giving rise to such structures, on the other. We note that this relationship may be such that it hampers obtaining a clear estimate of dimensionality using standard tools for dimensionality assessment alone. One situation in which dimensionality assessment may be impeded is that in which genetic and environmental influences, of which the observed covariance structure is a function, differ from each other in structure and dimensionality. We demonstrate that in such situations settling dimensionality issues may be problematic, and propose using quantitative genetic modeling to uncover the (possibly different) dimensionalities of the underlying genetic and environmental structures. We illustrate using simulations and an empirical example on childhood internalizing problems.

Twins, tissue, and time: an assessment of SNPs and CNVs.

With the desire to assess genetic variation across the lifespan in large-scale collaborative projects, one question is whether inference of copy number (CN) is sensitive to the source of material for deoxyribonucleic acid (DNA) analysis (e.g., blood and buccal) and another question is whether CN is stable as individual sage. Here, we address these questions by applying Affymetrix 6.0 single nucleotide polymorphism (SNP)micro-arrays to 1,472 DNA samples from 710 individuals from the Netherlands Twin Register, including twin and non-twin individuals (372 with buccal and blood derived DNA and 388 with longitudinal data).Similar concordance for CN and genotype inference between samples from the same individual [or from the monozygotic (MZ) co-twins] was found for blood and buccal tissues. There was a small but statistically significant decrease in across-tissue concordance compared with concordance of samples from the same tissue type. No temporal effect was seen on CN variation from the 388 individuals sampled at two time points ranging from 1 to 12 years apart. The majority of our individuals were sampled at age younger than 20 years. Genotype concordance was very high (~ > 99%) between co-twins from 43 MZ pairs. For75 dizygotic (DZ) pairs, ~was ~65%. CN estimates were highly consistent between co-twins from MZ pairs for both deletions (f?2 ~ 90%) and duplications (~ ~ 86%). For DZ, these were similar for within-individual comparisons, but naturally lower between co-twins (~ ~ 50-60%). These results suggest that DNA from buccal samples perform as well as DNA from blood samples on the current generation of micro-array technologies.

Adolescent personality profiles, neighborhood income, and young adult alcohol use: a longitudinal study.

Personality traits and socioeconomic factors such as neighborhood income have been identified as risk factors for future alcohol abuse, but findings have been inconsistent possibly due to interactions between risk and protective factors. The present study examined the prediction of drinking behavior using empirically derived multi-trait patterns and tested for moderation by average neighborhood income. Using latent profile analysis (LPA) in a sample of 863 Dutch adolescents, four empirical personality profiles based on 6 traits were observed: Extraverted, Dysregulated, Neurotic, and Regulated. Dysregulated and Extraverted youth drank higher quantities of alcohol more frequently in young adulthood relative to the Regulated group, above and beyond the effects of baseline adolescent drinking, age, and sex. Profile levels of neuroticism did not appear to affect drinking behavior. Average neighborhood income did not moderate adolescent personality and young adult drinking. These findings suggest that future alcohol research should consider individual trait patterns to inform prevention and intervention efforts, and theories implicating both positive and negative emotionality traits as risk factors for drinking are preferable to those emphasizing the importance of the latter.

Long term costs and effects of reducing the number of twin pregnancies in IVF by single embryo transfer: the TwinSing study.

BACKGROUND: Pregnancies induced by in vitro fertilisation (IVF) often result in twin gestations, which are associated with both maternal and perinatal complications. An effective way to reduce the number of IVF twin pregnancies is to decrease the number of embryos transferred from two to one. The interpretation of current studies is limited because they used live birth as outcome measure and because they applied limited time horizons. So far, research on long-term outcomes of IVF twins and singletons is scarce and inconclusive. The objective of this study is to investigate the short (1-year) and long-term (5 and 18-year) costs and health outcomes of IVF singleton and twin children and to consider these in estimating the cost-effectiveness of single embryo transfer compared with double embryo transfer, from a societal and a healthcare perspective. METHODS/DESIGN: A multi-centre cohort study will be performed, in which IVF singletons and IVF twin children born between 2003 and 2005 of whom parents received IVF treatment in one of the five participating Dutch IVF centres, will be compared. Data collection will focus on children at risk of health problems and children in whom health problems actually occurred. First year of life data will be collected in approximately 1,278 children (619 singletons and 659 twin children). Data up to the fifth year of life will be collected in approximately 488 children (200 singletons and 288 twin children). Outcome measures are health status, health-related quality of life and costs. Data will be obtained from hospital information systems, a parent questionnaire and existing registries. Furthermore, a prognostic model will be developed that reflects the short and long-term costs and health outcomes of IVF singleton and twin children. This model will be linked to a Markov model of the short-term cost-effectiveness of single embryo transfer strategies versus double embryo transfer strategies to enable the calculation of the long-term cost-effectiveness. DISCUSSION: This is, to our knowledge, the first study that investigates the long-term costs and health outcomes of IVF singleton and twin children and the long-term cost-effectiveness of single embryo transfer strategies versus double embryo transfer strategies.

Assessment of borderline personality features in population samples: is the Personality Assessment Inventory-Borderline Features scale measurement invariant across sex and age?

Borderline personality disorder (BPD) is more often diagnosed in women than in men, and symptoms tend to decline with age. Using a large community sample, the authors investigated whether sex and age differences in four main features of BPD, measured with the Personality Assessment Inventory-Borderline Features scale (PAI-BOR; Morey, 1991), are a result of measurement bias or if they represent true differences. The PAI-BOR was completed by four Sex x Age groups (N = 6,838). Multigroup confirmatory factor analysis showed that the PAI-BOR is measurement invariant across sex and age. Compared with men, women reported more borderline characteristics for affective instability, identity problems, and negative relationships but not for self-harm. Younger men had higher scores for identity problems and self-harm than did older men. Younger women had higher scores for identity problems and affective instability than did older women. Results suggest that the PAI-BOR can be used to study the etiology of BPD features in population-based samples and to screen for BPD features in clinical settings in both men and women of varying ages. (PsycINFO Database Record (c) 2009 APA, all rights reserved).

Predictors of problem drinking in adolescence and young adulthood. A longitudinal twin-family study.

We examined drinking behavior of parents, siblings, and friends of twins as predictors of adolescent and young adult problem drinking over a period of 2 and a period of 7 years. Data of 12 to 30-year-old twins and their family members from the Netherlands Twin Register were analyzed. Problem drinking in twins was assessed in 1995 and 2000 and was defined based on the CAGE and amount of drinking. Data on alcohol use of parents, siblings and friends were collected in 1993. Multinomial logistic regression analyses were used to examine the short-term (1993-1995; n = 2,994) and the long-term longitudinal predictors (1993-2000; n = 1,796) of problem drinking. Age, sex and own alcohol use in 1993 explained 25% of the variance in adolescent and young adult problem drinking. Moreover, adolescents and young adults with fathers who drank frequently and with a large numbers of drinking friends, were at the highest risk for problem drinking 2 years later. Over a period of 7 years the number of drinking friends was no longer a risk factor, but few times a week or daily alcohol use of fathers remained a risk factor for later problem drinking. Drinking behavior of mother and siblings did not substantially predict problem drinking. Sex and age did not moderate these effects.

A twin study of cognitive costs of low birth weight and catch-up growth.

OBJECTIVE: To investigate whether there is an association between catch-up growth and cognitive performance in humans. STUDY DESIGN: Catch-up growth was defined as the change in weight standard deviation scores during the first 2 years of life. Cognitive performance was assessed with psychometric IQ tests, administered at ages 12 and 18 years. Data were collected in twin pairs, and analyses were carried out within pairs. RESULTS: There was a significant negative association between catch-up growth and IQ at both ages 12 and 18 years. CONCLUSIONS: A larger gain in weight during the first 2 years of life is associated with a lower IQ. However, catch-up growth is correlated with birth weight and this correlation may explain part of the association.