Genotype-Environment Interaction in ADHD: Genetic Predisposition Determines the Extent to Which Environmental Influences Explain Variability in the Symptom Dimensions Hyperactivity and Inattention.

Although earlier research has shown that individual differences on the spectrum of attention deficit hyperactivity disorder (ADHD) are highly heritable, emerging evidence suggests that symptoms are associated with complex interactions between genes and environmental influences. This study investigated whether a genetic predisposition [Note that the term 'genetic predisposition' was used in this manuscript to refer to an estimate based on twin modeling (an individual's score on the latent trait that resembles additive genetic influences) in the particular population being examined.] for the symptom dimensions hyperactivity and inattention determines the extent to which unique-environmental influences explain variability in these symptoms. To this purpose, we analysed a sample drawn from the Twins Early Development Study (TEDS) that consisted of item-level scores of 2168 16-year-old twin pairs who completed both the Strengths and Difficulties Questionnaire (SDQ; Goodman, in J Child Psychol Psychiatry 38:581-586, 1997) and the Strength and Weaknesses of ADHD Symptoms and Normal Behavior (SWAN; Swanson, in Paper presented at the meeting of the American Psychological Association, Los Angeles, 1981) questionnaire. To maximize the psychometric information to measure ADHD symptoms, psychometric analyses were performed to investigate whether the items from the two questionnaires could be combined to form two longer subscales. In the estimation of genotype-environment interaction, we corrected for error variance heterogeneity in the measurement of ADHD symptoms through the application of item response theory (IRT) measurement models. A positive interaction was found for both hyperactivity (e.g., [Formula: see text] = 2.20 with 95% highest posterior density interval equal to [1.79;2.65] and effect size equal to 3.00) and inattention (e.g., [Formula: see text] = 2.16 with 95% highest posterior density interval equal to [1.56;2.79] and effect size equal to 3.07). These results indicate that unique-environmental influences were more important in creating individual differences in both hyperactivity and inattention for twins with a genetic predisposition for these symptoms than for twins without such a predisposition.

Overview of CAPICE-Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe-an EU Marie Sklodowska-Curie International Training Network.

The Roadmap for Mental Health and Wellbeing Research in Europe (ROAMER) identified child and adolescent mental illness as a priority area for research. CAPICE (Childhood and Adolescence Psychopathology: unravelling the complex etiology by a large Interdisciplinary Collaboration in Europe) is a European Union (EU) funded training network aimed at investigating the causes of individual differences in common childhood and adolescent psychopathology, especially depression, anxiety, and attention deficit hyperactivity disorder. CAPICE brings together eight birth and childhood cohorts as well as other cohorts from the EArly Genetics and Life course Epidemiology (EAGLE) consortium, including twin cohorts, with unique longitudinal data on environmental exposures and mental health problems, and genetic data on participants. Here we describe the objectives, summarize the methodological approaches and initial results, and present the dissemination strategy of the CAPICE network. Besides identifying genetic and epigenetic variants associated with these phenotypes, analyses have been performed to shed light on the role of genetic factors and the interplay with the environment in influencing the persistence of symptoms across the lifespan. Data harmonization and building an advanced data catalogue are also part of the work plan. Findings will be disseminated to non-academic parties, in close collaboration with the Global Alliance of Mental Illness Advocacy Networks-Europe (GAMIAN-Europe).

An Extended Twin-Pedigree Study of Neuroticism in the Netherlands Twin Register.

For the participants in the Netherlands Twin Register (NTR) we constructed the extended pedigrees which specify all relations among nuclear and larger twin families in the register. A total of 253,015 subjects from 58,645 families were linked to each other, to the degree that we had information on the relations among participants. We describe the algorithm that was applied to construct the pedigrees. For > 30,000 adolescent and adult NTR participants data were available on harmonized neuroticism scores. We analyzed these data in the Mendel software package (Lange et al., Bioinformatics 29(12):1568-1570, 2013) to estimate the contributions of additive and non-additive genetic factors. In contrast to much of the earlier work based on twin data rather than on extended pedigrees, we could also estimate the contribution of shared household effects in the presence of non-additive genetic factors. The estimated broad-sense heritability of neuroticism was 47%, with almost equal contributions of additive and non-additive (dominance) genetic factors. A shared household effect explained 13% and unique environmental factors explained the remaining 40% of the variance in neuroticism.

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.

Genes, Culture and Conservatism-A Psychometric-Genetic Approach.

The Wilson-Patterson conservatism scale was psychometrically evaluated using homogeneity analysis and item response theory models. Results showed that this scale actually measures two different aspects in people: on the one hand people vary in their agreement with either conservative or liberal catch-phrases and on the other hand people vary in their use of the "?" response category of the scale. A 9-item subscale was constructed, consisting of items that seemed to measure liberalism, and this subscale was subsequently used in a biometric analysis including genotype-environment interaction, correcting for non-homogeneous measurement error. Biometric results showed significant genetic and shared environmental influences, and significant genotype-environment interaction effects, suggesting that individuals with a genetic predisposition for conservatism show more non-shared variance but less shared variance than individuals with a genetic predisposition for liberalism.

Meta-analysis of Genome-Wide Association Studies for Extraversion: Findings from the Genetics of Personality Consortium.

Extraversion is a relatively stable and heritable personality trait associated with numerous psychosocial, lifestyle and health outcomes. Despite its substantial heritability, no genetic variants have been detected in previous genome-wide association (GWA) studies, which may be due to relatively small sample sizes of those studies. Here, we report on a large meta-analysis of GWA studies for extraversion in 63,030 subjects in 29 cohorts. Extraversion item data from multiple personality inventories were harmonized across inventories and cohorts. No genome-wide significant associations were found at the single nucleotide polymorphism (SNP) level but there was one significant hit at the gene level for a long non-coding RNA site (LOC101928162). Genome-wide complex trait analysis in two large cohorts showed that the additive variance explained by common SNPs was not significantly different from zero, but polygenic risk scores, weighted using linkage information, significantly predicted extraversion scores in an independent cohort. These results show that extraversion is a highly polygenic personality trait, with an architecture possibly different from other complex human traits, including other personality traits. Future studies are required to further determine which genetic variants, by what modes of gene action, constitute the heritable nature of extraversion.

Assessing Technology in the Absence of Proof: Trust Based on the Interplay of Others' Opinions and the Interaction Process.

OBJECTIVE: The present research addresses the question of how trust in systems is formed when unequivocal information about system accuracy and reliability is absent, and focuses on the interaction of indirect information (others' evaluations) and direct (experiential) information stemming from the interaction process. BACKGROUND: Trust in decision-supporting technology, such as route planners, is important for satisfactory user interactions. Little is known, however, about trust formation in the absence of outcome feedback, that is, when users have not yet had opportunity to verify actual outcomes. METHOD: Three experiments manipulated others' evaluations ("endorsement cues") and various forms of experience-based information ("process feedback") in interactions with a route planner and measured resulting trust using rating scales and credits staked on the outcome. Subsequently, an overall analysis was conducted. RESULTS: Study 1 showed that effectiveness of endorsement cues on trust is moderated by mere process feedback. In Study 2, consistent (i.e., nonrandom) process feedback overruled the effect of endorsement cues on trust, whereas inconsistent process feedback did not. Study 3 showed that although the effects of consistent and inconsistent process feedback largely remained regardless of face validity, high face validity in process feedback caused higher trust than those with low face validity. An overall analysis confirmed these findings. CONCLUSION: Experiential information impacts trust even if outcome feedback is not available, and, moreover, overrules indirect trust cues-depending on the nature of the former. APPLICATION: Designing systems so that they allow novice users to make inferences about their inner workings may foster initial trust.

Assessing genotype by environment interaction in case of heterogeneous measurement error.

Considerable effort has been devoted to establish genotype by environment interaction (G x E) in case of unmeasured genetic and environmental influences. Although it has been outlined by various authors that the appearance of G x E can be dependent on properties of the given measurement scale, a non-biased method to assess G x E is still lacking. We show that the incorporation of an explicit measurement model can remedy potential bias due to ceiling and floor effects. By means of a simulation study it is shown that the use of sum scores can lead to biased estimates whereas the proposed method is unbiased. The power of the suggested method is illustrated by means of a second simulation study with different sample sizes and G x E effect sizes.

Harmonization of Neuroticism and Extraversion phenotypes across inventories and cohorts in the Genetics of Personality Consortium: an application of Item Response Theory.

Mega- or meta-analytic studies (e.g. genome-wide association studies) are increasingly used in behavior genetics. An issue in such studies is that phenotypes are often measured by different instruments across study cohorts, requiring harmonization of measures so that more powerful fixed effect meta-analyses can be employed. Within the Genetics of Personality Consortium, we demonstrate for two clinically relevant personality traits, Neuroticism and Extraversion, how Item-Response Theory (IRT) can be applied to map item data from different inventories to the same underlying constructs. Personality item data were analyzed in >160,000 individuals from 23 cohorts across Europe, USA and Australia in which Neuroticism and Extraversion were assessed by nine different personality inventories. Results showed that harmonization was very successful for most personality inventories and moderately successful for some. Neuroticism and Extraversion inventories were largely measurement invariant across cohorts, in particular when comparing cohorts from countries where the same language is spoken. The IRT-based scores for Neuroticism and Extraversion were heritable (48 and 49 %, respectively, based on a meta-analysis of six twin cohorts, total N = 29,496 and 29,501 twin pairs, respectively) with a significant part of the heritability due to non-additive genetic factors. For Extraversion, these genetic factors qualitatively differ across sexes. We showed that our IRT method can lead to a large increase in sample size and therefore statistical power. The IRT approach may be applied to any mega- or meta-analytic study in which item-based behavioral measures need to be harmonized.

Genetic influences on dietary variety - results from a twin study.

The heritability of variety seeking in the food domain was estimated from a large sample (N = 5,543) of middle age to elderly monozygotic and dizygotic twins from the "Virginia 30,000" twin study. Different dietary variety scores were calculated based on a semi-quantitative food choice questionnaire that assessed consumption frequencies and quantities for a list of 99 common foods. Results indicate that up to 30% of the observed variance in dietary variety was explained through heritable influences. Most of the differences between twins were due to environmental influences that are not shared between twins. Additional non-genetic analyses further revealed a weak relationship between dietary variety and particular demographic variables, including socioeconomic status, age, sex, religious faith, and the number of people living in the same household.

Power of IRT in GWAS: successful QTL mapping of sum score phenotypes depends on interplay between risk allele frequency, variance explained by the risk allele, and test characteristics.

As data from sequencing studies in humans accumulate, rare genetic variants influencing liability to disease and disorders are expected to be identified. Three simulation studies show that characteristics and properties of diagnostic instruments interact with risk allele frequency to affect the power to detect a quantitative trait locus (QTL) based on a test score derived from symptom counts or questionnaire items. Clinical tests, that is, tests that show a positively skewed phenotypic sum score distribution in the general population, are optimal to find rare risk alleles of large effect. Tests that show a negatively skewed sum score distribution are optimal to find rare protective alleles of large effect. For alleles of small effect, tests with normally distributed item parameters give best power for a wide range of allele frequencies. The item-response theory framework can help understand why an existing measurement instrument has more power to detect risk alleles with either low or high frequency, or both kinds.

Genetic analysis of rare disorders: bayesian estimation of twin concordance rates.

Twin concordance rates provide insight into the possibility of a genetic background for a disease. These concordance rates are usually estimated within a frequentistic framework. Here we take a Bayesian approach. For rare diseases, estimation methods based on asymptotic theory cannot be applied due to very low cell probabilities. Moreover, a Bayesian approach allows a straightforward incorporation of prior information on disease prevalence coming from non-twin studies that is often available. An MCMC estimation procedure is tested using simulation and contrasted with frequentistic analyses. The Bayesian method is able to include prior information on both concordance rates and prevalence rates at the same time and is illustrated using twin data on cleft lip and rheumatoid arthritis.

Stable genetic effects on symptoms of alcohol abuse and dependence from adolescence into early adulthood.

Relatively little is known about how genetic influences on alcohol abuse and dependence (AAD) change with age. We examined the change in influence of genetic and environmental factors which explain symptoms of AAD from adolescence into early adulthood. Symptoms of AAD were assessed using the four AAD screening questions of the CAGE inventory. Data were obtained up to six times by self-report questionnaires for 8,398 twins from the Netherlands Twin Register aged between 15 and 32 years. Longitudinal genetic simplex modeling was performed with Mx. Results showed that shared environmental influences were present for age 15-17 (57%) and age 18-20 (18%). Unique environmental influences gained importance over time, contributing 15% of the variance at age 15-17 and 48% at age 30-32. At younger ages, unique environmental influences were largely age-specific, while at later ages, age-specific influences became less important. Genetic influences on AAD symptoms over age could be accounted for by one factor, with the relative influence of this factor differing across ages. Genetic influences increased from 28% at age 15-17 to 58% at age 21-23 and remained high in magnitude thereafter. These results are in line with a developmentally stable hypothesis that predicts that a single set of genetic risk factors acts on symptoms of AAD from adolescence into young adulthood.

Heritability of regional and global brain structure at the onset of puberty: a magnetic resonance imaging study in 9-year-old twin pairs.

Puberty represents the phase of sexual maturity, signaling the change from childhood into adulthood. During childhood and adolescence, prominent changes take place in the brain. Recently, variation in frontal, temporal, and parietal areas was found to be under varying genetic control between 5 and 19 years of age. However, at the onset of puberty, the extent to which variation in brain structures is influenced by genetic factors (heritability) is not known. Moreover, whether a direct link between human pubertal development and brain structure exists has not been studied. Here, we studied the heritability of brain structures at 9 years of age in 107 monozygotic and dizygotic twin pairs (N = 210 individuals) using volumetric MRI and voxel-based morphometry. Children showing the first signs of secondary sexual characteristics (N = 47 individuals) were compared with children without these signs, based on Tanner-stages. High heritabilities of intracranial, total brain, cerebellum, and gray and white matter volumes (up to 91%) were found. Regionally, the posterior fronto-occipital, corpus callosum, and superior longitudinal fascicles (up to 93%), and the amygdala, superior frontal and middle temporal cortices (up to 83%) were significantly heritable. The onset of secondary sexual characteristics of puberty was associated with decreased frontal and parietal gray matter densities. Thus, in 9-year-old children, global brain volumes, white matter density in fronto-occipital and superior longitudinal fascicles, and gray matter density of (pre-)frontal and temporal areas are highly heritable. Pubertal development may be directly involved in the decreases in gray matter areas that accompany the transition of our brains from childhood into adulthood.

Sex steroids and brain structure in pubertal boys and girls.

Sex steroids exert important organizational effects on brain structure. Early in life, they are involved in brain sexual differentiation. During puberty, sex steroid levels increase considerably. However, to which extent sex steroid production is involved in structural brain development during human puberty remains unknown. The relationship between pubertal rises in testosterone and estradiol levels and brain structure was assessed in 37 boys and 41 girls (10-15 years). Global brain volumes were measured using volumetric-MRI. Regional gray and white matter were quantified with voxel-based morphometry (VBM), a technique which measures relative concentrations ('density') of gray and white matter after individual global differences in size and shape of brains have been removed. Results showed that, corrected for age, global gray matter volume was negatively associated with estradiol levels in girls, and positively with testosterone levels in boys. Regionally, a higher estradiol level in girls was associated with decreases within prefrontal, parietal and middle temporal areas (corrected for age), and with increases in middle frontal-, inferior temporal- and middle occipital gyri. In boys, estradiol and testosterone levels were not related to regional brain structures, nor were testosterone levels in girls. Pubertal sex steroid levels could not explain regional sex differences in regional gray matter density. Boys were significantly younger than girls, which may explain part of the results. In conclusion, in girls, with the progression of puberty, gray matter development is at least in part directly associated with increased levels of estradiol, whereas in boys, who are in a less advanced pubertal stage, such steroid-related development could not (yet) be found. We suggest that in pubertal girls, estradiol may be implicated in neuronal changes in the cerebral cortex during this important period of brain development.

Imposing nonlinear constraints when estimating genetic and cultural transmission under assortative mating: a simulation study using Mx and BUGS.

Modeling both genetic and cultural transmission in parent-offspring data in the presence of phenotypic assortment requires the imposition of nonlinear constraints. This article reports a simulation study that determined how well the structural equation modeling software package Mx and the Bayesian-oriented BUGS software package can handle such nonlinear constraints under various conditions. Results generally showed good and comparable results for Mx and BUGS, although BUGS was much slower than Mx. However, since BUGS uses Markov-chain Monte Carlo estimation it could be used for parent-offspring models with non-normal data and/or item-response theory models.

Genetic covariance structure of reading, intelligence and memory in children.

This study investigates the genetic relationship among reading performance, IQ, verbal and visuospatial working memory (WM) and short-term memory (STM) in a sample of 112, 9-year-old twin pairs and their older siblings. The relationship between reading performance and the other traits was explained by a common genetic factor for reading performance, IQ, WM and STM and a genetic factor that only influenced reading performance and verbal memory. Genetic variation explained 83% of the variation in reading performance; most of this genetic variance was explained by variation in IQ and memory performance. We hypothesize, based on these results, that children with reading problems possibly can be divided into three groups: (1) children low in IQ and with reading problems; (2) children with average IQ but a STM deficit and with reading problems; (3) children with low IQ and STM deficits; this group may experience more reading problems than the other two.

Combining Text Mining of Long Constructed Responses and Item-Based Measures: A Hybrid Test Design to Screen for Posttraumatic Stress Disorder (PTSD).

This article introduces a new hybrid intake procedure developed for posttraumatic stress disorder (PTSD) screening, which combines an automated textual assessment of respondents' self-narratives and item-based measures that are administered consequently. Text mining technique and item response modeling were used to analyze long constructed response (i.e., self-narratives) and responses to standardized questionnaires (i.e., multiple choices), respectively. The whole procedure is combined in a Bayesian framework where the textual assessment functions as prior information for the estimation of the PTSD latent trait. The purpose of this study is twofold: first, to investigate whether the combination model of textual analysis and item-based scaling could enhance the classification accuracy of PTSD, and second, to examine whether the standard error of estimates could be reduced through the use of the narrative as a sort of routing test. With the sample at hand, the combination model resulted in a reduction in the misclassification rate, as well as a decrease of standard error of latent trait estimation. These findings highlight the benefits of combining textual assessment and item-based measures in a psychiatric screening process. We conclude that the hybrid test design is a promising approach to increase test efficiency and is expected to be applicable in a broader scope of educational and psychological measurement in the future.

A genome-wide linkage scan for age at menarche in three populations of European descent.

CONTEXT: Age at menarche (AAM) is an important trait both biologically and socially, a clearly defined event in female pubertal development, and has been associated with many clinically significant phenotypes. OBJECTIVE: The objective of the study was to identify genetic loci influencing variation in AAM in large population-based samples from three countries. DESIGN/PARTICIPANTS: Recalled AAM data were collected from 13,697 individuals and 4,899 pseudoindependent sister-pairs from three different populations (Australia, The Netherlands, and the United Kingdom) by mailed questionnaire or interview. Genome-wide variance components linkage analysis was implemented on each sample individually and in combination. RESULTS: The mean, sd, and heritability of AAM across the three samples was 13.1 yr, 1.5 yr, and 0.69, respectively. No loci were detected that reached genome-wide significance in the combined analysis, but a suggestive locus was detected on chromosome 12 (logarithm of the odds = 2.0). Three loci of suggestive significance were seen in the U.K. sample on chromosomes 1, 4, and 18 (logarithm of the odds = 2.4, 2.2 and 3.2, respectively). CONCLUSIONS: There was no evidence for common highly penetrant variants influencing AAM. Linkage and association suggest that one trait locus for AAM is located on chromosome 12, but further studies are required to replicate these results.

Cerebral white matter in early puberty is associated with luteinizing hormone concentrations.

Puberty is a period in which cerebral white matter grows considerably, whereas gray matter decreases. The first endocrinological marker of puberty in both boys and girls is an increased secretion of luteinizing hormone (LH). Here we investigated the phenotypic association between LH, global and focal gray and white matter in 104 healthy nine-year-old monozygotic and dizygotic twins. Volumetric MRI and voxel-based morphometry were applied to measure global gray and white matter and to estimate relative concentrations of regional cerebral gray and white matter, respectively. A possible common genetic origin of this association (genetic correlation) was examined. Results showed that higher LH levels are associated with a larger global white matter proportion and with higher regional white matter density. Areas of increased white matter density included the cingulum, middle temporal gyrus and splenium of the corpus callosum. No association between LH and global gray matter proportion or regional gray matter density was found. Our data indicate that a common genetic factor underlies the association between LH level and regional white matter density. We suggest that the increase of white matter growth during puberty reported earlier might be directly or indirectly mediated by LH production. In addition, genes involved in LH production may be promising candidate genes in neuropsychiatric illnesses with an onset in early adolescence.