Harmonizing behavioral outcomes across studies, raters, and countries: application to the genetic analysis of aggression in the ACTION Consortium.

BACKGROUND: Aggression in children has genetic and environmental causes. Studies of aggression can pool existing datasets to include more complex models of social effects. Such analyses require large datasets with harmonized outcome measures. Here, we made use of a reference panel for phenotype data to harmonize multiple aggression measures in school-aged children to jointly analyze data from five large twin cohorts. METHODS: Individual level aggression data on 86,559 children (42,468 twin pairs) were available in five European twin cohorts measured by different instruments. A phenotypic reference panel was collected which enabled a model-based phenotype harmonization approach. A bi-factor integration model in the integrative data analysis framework was developed to model aggression across studies while adjusting for rater, age, and sex. Finally, harmonized aggression scores were analyzed to estimate contributions of genes, environment, and social interaction to aggression. The large sample size allowed adequate power to test for sibling interaction effects, with unique dynamics permitted for opposite-sex twins. RESULTS: The best-fitting model found a high level of overall heritability of aggression (~60%). Different heritability rates of aggression across sex were marginally significant, with heritability estimates in boys of ~64% and ~58% in girls. Sibling interaction effects were only significant in the opposite-sex twin pairs: the interaction effect of males on their female co-twin differed from the effect of females on their male co-twin. An aggressive female had a positive effect on male co-twin aggression, whereas more aggression in males had a negative influence on a female co-twin. CONCLUSIONS: Opposite-sex twins displayed unique social dynamics of aggressive behaviors in a joint analysis of a large, multinational dataset. The integrative data analysis framework, applied in combination with a reference panel, has the potential to elucidate broad, generalizable results in the investigation of common psychological traits in children.

The development of a brief screener for autism using item response theory.

BACKGROUND: Brief screening instruments focusing on autism spectrum disorder (ASD) that can be administered in primary care are scarce; there is a need for shorter and more precise instruments. The Autism-Tics, AD/HD and other Comorbidities inventory (A-TAC) has previously been validated for ASD reporting excellent validity. This study aims to determine the psychometric properties of each item in the ASD domain (17 items) in the A-TAC using item response theory (IRT), and thereby construct and validate a short form that could be used as a screening instrument in the general population. METHODS: Since 2004, parents of all 9-year-old Swedish twins have been invited to participate in a telephone interview in the Child and Adolescent Twin Study in Sweden (CATSS). The CATSS is linked to the National Patient Register (NPR), which includes data from in- and outpatient care. Data on ASD (A-TAC) collected in CATSS were compared with diagnoses from the NPR. Diagnoses that had been made both before (previous validity) and after (predictive validity) the interviews were included. The sample was divided into a developmental sample and a validation sample. An IRT model was fitted to the developmental sample and item parameters were used to select a subset of items for the short form. The performance of the proposed short form was examined in the validation sample by the use of receiver operation characteristic curves. RESULTS: Four items which were able to discriminate among individuals with more autism traits were deemed sufficient for use in the short form. The values of the area under the receiver operating characteristic curve for a clinical diagnosis of ASD was .95 (previous validity) and .72 (predictive validity). CONCLUSIONS: The proposed short form with 4 out of the original 17 items from A-TAC, showed excellent previous validity while the predictive validity was fair. The validity of the short form was in agreement with previous validations of the full ASD domain. The short form can be a valuable screening instrument in primary care settings in order to identify individuals in need for further assessment and for use in epidemiological studies.

The relation between the age at diagnosis of problem behaviors related to aggression and distal outcomes in Swedish children.

Severe childhood aggressive behaviors are known to predict negative outcomes later in life; however, little is known about the effect of when in childhood aggression problems are diagnosed. While an earlier first diagnosis of problematic aggressive behavior might be associated with increased severity and, thus, worse outcomes, it is also possible that an earlier diagnosis affords an earlier start of treatment programs or indicates that greater attention is being paid to behavioral problems, thus resulting in attenuation of the severity of childhood aggression's impact on distal outcomes. The current study analyzed data from the population-based Swedish Data Registries, which include data on all children formally diagnosed by the Swedish medical system with a wide range of aggression problems between ages 8 and 18 (N = 5816) during the years 1987-2013, along with a matched control. Time-to-event analyses investigated whether the age at time of diagnosis affects later life outcomes while controlling for relevant confounders. Results show that for both boys and girls, those with a later diagnosis had lower average incomes (regression coefficient b = - 0.055, p < 0.005) and a higher probability of having a criminal record (odds ratio 1.126, p < 0.005) than children with earlier diagnoses. The effect on suicide attempts was not significant after correcting for multiple testing (odds ratio 1.264, p = 0.016). Grade score was not significantly affected. The results warrant further research concerning the potential advantage of earlier diagnoses, especially concerning generalizability beyond the Swedish population.

Childhood aggression and the co-occurrence of behavioural and emotional problems: results across ages 3-16 years from multiple raters in six cohorts in the EU-ACTION project.

Childhood aggression and its resulting consequences inflict a huge burden on affected children, their relatives, teachers, peers and society as a whole. Aggression during childhood rarely occurs in isolation and is correlated with other symptoms of childhood psychopathology. In this paper, we aim to describe and improve the understanding of the co-occurrence of aggression with other forms of childhood psychopathology. We focus on the co-occurrence of aggression and other childhood behavioural and emotional problems, including other externalising problems, attention problems and anxiety-depression. The data were brought together within the EU-ACTION (Aggression in Children: unravelling gene-environment interplay to inform Treatment and InterventiON strategies) project. We analysed the co-occurrence of aggression and other childhood behavioural and emotional problems as a function of the child's age (ages 3 through 16 years), gender, the person rating the behaviour (father, mother or self) and assessment instrument. The data came from six large population-based European cohort studies from the Netherlands (2x), the UK, Finland and Sweden (2x). Multiple assessment instruments, including the Child Behaviour Checklist (CBCL), the Strengths and Difficulties Questionnaire (SDQ) and Multidimensional Peer Nomination Inventory (MPNI), were used. There was a good representation of boys and girls in each age category, with data for 30,523 3- to 4-year-olds (49.5% boys), 20,958 5- to 6-year-olds (49.6% boys), 18,291 7- to 8-year-olds (49.0% boys), 27,218 9- to 10-year-olds (49.4% boys), 18,543 12- to 13-year-olds (48.9% boys) and 10,088 15- to 16-year-olds (46.6% boys). We replicated the well-established gender differences in average aggression scores at most ages for parental ratings. The gender differences decreased with age and were not present for self-reports. Aggression co-occurred with the majority of other behavioural and social problems, from both externalising and internalising domains. At each age, the co-occurrence was particularly prevalent for aggression and oppositional and ADHD-related problems, with correlations of around 0.5 in general. Aggression also showed substantial associations with anxiety-depression and other internalizing symptoms (correlations around 0.4). Co-occurrence for self-reported problems was somewhat higher than for parental reports, but we found neither rater differences, nor differences across assessment instruments in co-occurrence patterns. There were large similarities in co-occurrence patterns across the different European countries. Finally, co-occurrence was generally stable across age and sex, and if any change was observed, it indicated stronger correlations when children grew older. We present an online tool to visualise these associations as a function of rater, gender, instrument and cohort. In addition, we present a description of the full EU-ACTION projects, its first results and the future perspectives.

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.

The use of vector bootstrapping to improve variable selection precision in Lasso models.

The Lasso is a shrinkage regression method that is widely used for variable selection in statistical genetics. Commonly, K-fold cross-validation is used to fit a Lasso model. This is sometimes followed by using bootstrap confidence intervals to improve precision in the resulting variable selections. Nesting cross-validation within bootstrapping could provide further improvements in precision, but this has not been investigated systematically. We performed simulation studies of Lasso variable selection precision (VSP) with and without nesting cross-validation within bootstrapping. Data were simulated to represent genomic data under a polygenic model as well as under a model with effect sizes representative of typical GWAS results. We compared these approaches to each other as well as to software defaults for the Lasso. Nested cross-validation had the most precise variable selection at small effect sizes. At larger effect sizes, there was no advantage to nesting. We illustrated the nested approach with empirical data comprising SNPs and SNP-SNP interactions from the most significant SNPs in a GWAS of borderline personality symptoms. In the empirical example, we found that the default Lasso selected low-reliability SNPs and interactions which were excluded by bootstrapping.

Joint developmental trajectories of internalizing and externalizing disorders between childhood and adolescence.

This study sought to identify trajectories of DSM-IV based internalizing (INT) and externalizing (EXT) problem scores across childhood and adolescence and to provide insight into the comorbidity by modeling the co-occurrence of INT and EXT trajectories. INT and EXT were measured repeatedly between age 7 and age 15 years in over 7,000 children and analyzed using growth mixture models. Five trajectories were identified for both INT and EXT, including very low, low, decreasing, and increasing trajectories. In addition, an adolescent onset trajectory was identified for INT and a stable high trajectory was identified for EXT. Multinomial regression showed that similar EXT and INT trajectories were associated. However, the adolescent onset INT trajectory was independent of high EXT trajectories, and persisting EXT was mainly associated with decreasing INT. Sex and early life environmental risk factors predicted EXT and, to a lesser extent, INT trajectories. The association between trajectories indicates the need to consider comorbidity when a child presents with INT or EXT disorders, particularly when symptoms start early. This is less necessary when INT symptoms start at adolescence. Future studies should investigate the etiology of co-occurring INT and EXT and the specific treatment needs of these severely affected children.

Genetic analyses benefit from using less heterogeneous phenotypes: an illustration with the hospital anxiety and depression scale (HADS).

Phenotypic heterogeneity of depression has been cited as one of the causes of the limited success to detect genetic variants in genome-wide studies. The 7-item Hospital Anxiety and Depression Scale (HADS-D) was developed to detect depression in individuals with physical health problems. An initial psychometric analysis showed that a short version ("HADS-4") is less heterogeneous and hence more reliable than the full scale, and correlates equally strong with a DSM-oriented depression scale. We compared the HADS-D and the HADS-4 to assess the benefits of using less heterogeneous phenotype measures in genetic analyses. We compared HADS-D and HADS-4 in three separate analyses: (1) twin- and family-based heritability estimation, (2) SNP-based heritability estimation using the software GCTA, and (3) a genome-wide association study (GWAS). The twin study resulted in heritability estimates between 18% and 25%, with additive genetic variance being the largest component. There was also evidence for assortative mating and a dominance component of genetic variance, with HADS-4 having slightly lower estimates of assortment. Importantly, when estimating heritability from SNPs, the HADS-D did not show a significant genetic variance component, while for the HADS-4, a statistically significant amount of heritability was estimated. Moreover, the HADS-4 had substantially more SNPs with small P-values in the GWAS analysis than did the HADS-D. Our results underline the benefits of using more homogeneous phenotypes in psychiatric genetic analyses. Homogeneity can be increased by focusing on core symptoms of disorders, thus reducing the noise in aggregate phenotypes caused by substantially different symptom profiles.

A powerful phenotype for gene-finding studies derived from trajectory analyses of symptoms of anxiety and depression between age seven and 18.

To investigate the utility of longitudinal data in genetic analyses of symptoms of anxiety and depression, we assessed individual differences between age 7 and 18 using growth mixture models, and investigated the genetic and non-genetic factors contributing to the trajectories. Mothers of 7,706 girl and 7,418 boy twins from the Netherlands Twin Register rated the anxious depression scale (SxAnxDep) of the Child Behavior Check List (CBCL) at age 7, 10, and 12 years. Two thousand seven hundred and six girl and 1,856 boy twins completed the Youth Self Report (YSR) at age 14, 16, and 18. While individual trajectories varied considerably, these differences were largely idiosyncratic and could not be grouped into separate latent classes with class-specific average growth curves. The intercept, which reflects the individuals' baseline level of SxAnxDep across time, explained 55-58% of the total phenotypic variance. The slope factor, which captures a common average trend over time, did not explain variance in the phenotype. This finding also underlines the high level of idiosyncrasy of trajectories that lack a common longitudinal structure. The analyses of twin data showed that the random intercept factor of SxAnxDep during childhood and during adolescence is considerably more heritable than the observations at any single age, namely between 60% and 84%. One explanation is that different factors contribute to the level of symptoms of anxiety and depression at any given time point, including temporary events and emotions. When considering baseline stability, these temporary influences average out, with the result of a more reliable and more heritable phenotype. © 2015 Wiley Periodicals, Inc.

Childhood ODD and ADHD Behavior: The Effect of Classroom Sharing, Gender, Teacher Gender and Their Interactions.

One criterion for a diagnostic and statistical manual of mental disorders (DSM-IV) diagnosis of attention deficit hyperactivity disorder (ADHD) and oppositional defiant disorder (ODD) is that symptoms are present in at least two settings, and often teacher ratings are taken into account. The short Conners' Teacher Rating Scales-Revised (CTRS-R) is a widely used standardized instrument measuring ODD and ADHD behavior in a school setting. In the current study CTRS-R data were available for 7, 9 and 12-year-old twins from the Netherlands Twin Register. Measurement invariance (MI) across student gender and teacher gender was established for three of the four scales (Oppositional Behavior, Hyperactivity and ADHD Index) of the CTRS-R. The fourth scale (ATT) showed an unacceptable model fit even without constraints on the data and revision of this scale is recommended. Gene-environment (GxE) interaction models revealed that heritability was larger for children sharing a classroom. There were some gender differences in the heritability of ODD and ADHD behavior and there was a moderating effect of teacher's gender at some of the ages. Taken together, this indicates that there was evidence for GxE interaction for classroom sharing, gender of the student and gender of the teacher.

Multivariate genetic analyses in heterogeneous populations.

Martin and Eaves (Heredity 38(1):79-95, 1977) proposed a multivariate model for twin and family data in order to investigate potential differences in the genetic and environmental architecture of multivariate phenotypes. The general form of the model is the independent pathway model, which differentiates between genetic and environmental influences at the item level, and therefore permits the decomposition to differ across items. A restricted version is the common pathway model, where the decomposition takes place at the factor level. The paper has spurred numerous studies, and evidence for differences in genetic and environmental architecture has been established for personality and several other psychiatric phenotypes by showing a better fit of the independent pathway model compared to the common pathway model. We show that genome-wide association studies (GWAS) that use an aggregate score computed from multiple questionnaire items as a univariate phenotype implicitly assume a similar structure as the common pathway model. It has been shown that in case of a differential genetic and environmental architecture, multivariate GWAS methods can outperform the univariate GWAS approach. However, current multivariate methods rely on the assumptions of phenotypic and genetic homogeneity, that is, item responses are assumed to have the same means and covariances, and genetic effects are assumed to be the same for all subjects. We describe a distance-based regression technique that is designed to account for subgroups in the population, and that therefore can account for differential genetic effects. A first evaluation with simulated data shows a substantial increase of power compared to univariate GWAS.

The predictive value of smoking expectancy and the heritability of its accuracy.

INTRODUCTION: Among smokers, former smokers, and never-smokers, this study aimed to (a) determine the predictive value of smoking expectancy on future smoking status, and (b) test the relative contribution of genes and environment to a person's ability to accurately predict future smoking status. For smokers, smoking expectancy reflects the intention to continue smoking; for former smokers, it reflects the intention to take up smoking again; and for never-smokers, it reflects the intention to initiate smoking. METHODS: A longitudinal design was employed in which participants of the Netherlands Twin Register completed 2 consecutive surveys 2 years apart between 1993 and 2011 (3,591 adolescents aged 14-18 years), or between 1993 and 2004 (11,568 adults, aged 18+ years). Smoking expectancy was measured by asking, "Do you think you'll smoke in a year's time?", with answer categories ranging from "certainly not" to "absolutely yes" on a 5-point scale. To determine the predictive value of smoking expectancy, analyses were performed in smokers, former smokers, and never-smokers separately. Data of 2,987 adolescents and 4,911 adult twins were analyzed to estimate heritability. A dichotomous variable reflected the ability to predict future smoking status (correct/incorrect). RESULTS: Smoking expectancy significantly predicted future smoking status among former smokers and never-smokers. The ability to accurately predict future smoking status was explained by additive genetic factors for 59% of adolescents and 27% of adults, with the remainder being explained by unique environmental factors. CONCLUSIONS: A single question on smoking expectancy helps predict future smoking status. Variation in how well subjects predict their future smoking behavior is influenced by genetic factors, especially during adolescence.

Epi2Loc: an R package to investigate two-locus epistatic models.

Epistasis is a growing area of research in genome-wide studies, but the differences between alternative definitions of epistasis remain a source of confusion for many researchers. One problem is that models for epistasis are presented in a number of formats, some of which have difficult-to-interpret parameters. In addition, the relation between the different models is rarely explained. Existing software for testing epistatic interactions between single-nucleotide polymorphisms (SNPs) does not provide the flexibility to compare the available model parameterizations. For that reason we have developed an R package for investigating epistatic and penetrance models, Epi2Loc, to aid users who wish to easily compare, interpret, and utilize models for two-locus epistatic interactions. Epi2Loc facilitates research on SNP-SNP interactions by allowing the R user to easily convert between common parametric forms for two-locus interactions, generate data for simulation studies, and perform power analyses for the selected model with a continuous or dichotomous phenotype. The usefulness of the package for model interpretation and power analysis is illustrated using data on rheumatoid arthritis.

An integrated approach to reduce the impact of minor allele frequency and linkage disequilibrium on variable importance measures for genome-wide data.

MOTIVATION: There is growing momentum to develop statistical learning (SL) methods as an alternative to conventional genome-wide association studies (GWAS). Methods such as random forests (RF) and gradient boosting machine (GBM) result in variable importance measures that indicate how well each single-nucleotide polymorphism (SNP) predicts the phenotype. For RF, it has been shown that variable importance measures are systematically affected by minor allele frequency (MAF) and linkage disequilibrium (LD). To establish RF and GBM as viable alternatives for analyzing genome-wide data, it is necessary to address this potential bias and show that SL methods do not significantly under-perform conventional GWAS methods. RESULTS: Both LD and MAF have a significant impact on the variable importance measures commonly used in RF and GBM. Dividing SNPs into overlapping subsets with approximate linkage equilibrium and applying SL methods to each subset successfully reduces the impact of LD. A welcome side effect of this approach is a dramatic reduction in parallel computing time, increasing the feasibility of applying SL methods to large datasets. The created subsets also facilitate a potential correction for the effect of MAF using pseudocovariates. Simulations using simulated SNPs embedded in empirical data-assessing varying effect sizes, minor allele frequencies and LD patterns-suggest that the sensitivity to detect effects is often improved by subsetting and does not significantly under-perform the Armitage trend test, even under ideal conditions for the trend test. AVAILABILITY: Code for the LD subsetting algorithm and pseudocovariate correction is available at http://www.nd.edu/~glubke/code.html.

The genetic architecture of liver enzyme levels: GGT, ALT and AST.

High levels of liver enzymes GGT, ALT and AST are predictive of disease and all-cause mortality and can reflect liver injury, fatty liver and/or oxidative stress. Variation in GGT, ALT and AST levels is heritable. Moderation of the heritability of these liver enzymes by age and sex has not often been explored, and it is not clear to what extent non-additive genetic and shared environmental factors may play a role. To examine the genetic architecture of GGT, ALT and AST, plasma levels were assessed in a large sample of twins, their siblings, parents and spouses (N = 8,371; age range 18-90). For GGT and ALT, but not for AST, genetic structural equation modeling showed evidence for quantitative sex differences in the genetic architecture. There was no evidence for qualitative sex differences, i.e. the same genes were expressed in males and females. Both additive and non-additive genetic factors were important for GGT in females (total heritability h(2) 60 %) and AST in both sexes (total h(2) 43 %). The heritability of GGT in males and ALT for both sexes was due to additive effects only (GGT males 30 %; ALT males 40 %, females 22 %). Evidence emerged for shared environmental factors influencing GGT in the male offspring generation (variance explained 28 %). Thus, the same genes influence liver enzyme levels across sex and age, but their relative contribution to the variation in GGT and ALT differs in males and females and for GGT across age. Given adequate sample sizes these results suggest that genome-wide association studies may result in the detection of new susceptibility loci for liver enzyme levels when pooling results over sex and age.

The CHRNA5/A3/B4 gene cluster and tobacco, alcohol, cannabis, inhalants and other substance use initiation: replication and new findings using mixture analyses.

Multiple studies have provided evidence for genetic associations between single nucleotide polymorphisms (SNPs) located on the CHRNA5/A3/B4 gene cluster and various phenotypes related to Nicotine Dependence (Greenbaum et al. 2009). Only a few studies have investigated other substances of abuse. The current study has two aims, (1) to extend previous findings by focusing on associations between the CHRNA5/A3/B4 gene cluster and age of initiation of several different substances, and (2) to investigate heterogeneity in age of initiation across the different substances. All analyses were conducted with a subset of the Add Health study with available genetic data. The first aim was met by modeling onset of tobacco, alcohol, cannabis, inhalants, and other substance use using survival mixture analysis (SMA). Ten SNPs in CHRNA5/A3/B4 were used to predict phenotypic differences in the risk of onset, and differences between users and non-users. The survival models aim at investigating differences in the risk of initiation across the 5-18 age range for each phenotype separately. Significant or marginally significant genetic effects were found for all phenotypes. The genetic effects were mainly related to the risk of initiation and to a lesser extent to discriminating between users and non-users. To address the second goal, the survival analyses were complemented by a latent class analysis that modeled all phenotypes jointly. One of the ten SNPs was found to predict differences between the early and late onset classes. Taken together, our study provides evidence for a general role of the CHRNA5/A3/B4 gene cluster in substance use initiation that is not limited to nicotine and alcohol.

Measuring autism in males and females with a differential item functioning approach: Results from a nation-wide population-based study.

Existing screening instruments for Autism Spectrum Disorder (ASD) might be prone to detect a male manifestation of ASD. Here, we examined the 17 items from the ASD domain in the Autism-Tics, ADHD and other Comorbidities inventory (A-TAC) for Differential Item Functioning (DIF). Data were obtained from the Child and Adolescent Twin Study in Sweden (CATSS) in which parents have responded to the A-TAC. Information regarding a registered diagnosis of ASD were retrieved from the National Patient Register. The cohort was divided into a developmental sample for evaluation of DIF, and a validation sample for examination of the diagnostic accuracy of the total ASD domain, and a novel male and female short form. Our main finding included the identification of DIF for six items, three favouring males and three favouring females. The full, 17 item, ASD domain and the male and female short form showed excellent ability to capture ASD diagnoses in both males and females up to the age of nine years. The full ASD domain in A-TAC is psychometrically largely equivalent across sex and the limited differences between males and females diminish the need for a sex-specific scoring when utilizing the 17 item total score.

Trajectories of CBCL attention problems in childhood.

The first aim of this study was to identify developmental trajectories of Attention Problems in twins followed from age 6 to 12 years. Second, we investigated whether singletons follow similar trajectories. Maternal longitudinal ratings on the Attention Problems (AP) subscale of the Child Behavior Checklist were obtained for a sample of 12,486 twins from the Netherlands Twin Register and for a general population sample of 1,346 singletons. Trajectories were analyzed by growth mixture modeling in twins, and compared with singletons. Teacher ratings on the AP subscale of the Teachers' Report Form were available for 7,179 twins and 1,211 singletons, and were used for cross-sectional mean comparisons at each age. All analyses were conducted for boys and girls separately. We identified three linear trajectories in both boys and girls, i.e., stable low (62-71%), low-increasing (15-18%), and high-decreasing (14-21%). Singletons followed three identical trajectories, with similar class proportions. Teacher ratings yielded no differences in mean levels of Attention Problems between twins and singletons. The development of Attention Problems from age 6 to 12 years can be characterized by stable low, low-increasing, and high-decreasing developmental trajectories. Twins and singletons are comparable with respect to the development of Attention Problems in childhood.