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.

Limitations of conventional approaches to identify photochemically produced reactive intermediates involved in contaminant indirect photodegradation.

Dissolved organic matter (DOM) mediated indirect photodegradation can play an important role in the degradation of aquatic contaminants. Predicting the rate of this process requires knowledge of the photochemically produced reactive intermediates (PPRI) that react with the compound of interest, as well as the ability of individual DOM samples to produce PPRI. Key PPRI are typically identified using quencher studies, yet this approach often leads to results that are difficult to interpret. In this work, we analyze the indirect photodegradation of atorvastatin, carbamazepine, sulfadiazine, and benzotriazole using a diverse set of 48 waters from natural and engineered aquatic systems. We use this large data set to evaluate relationships between PPRI formation and indirect photodegradation rate constants, which are directly compared to results using standard quenching experiments. These data demonstrate that triplet state DOM (3DOM) and singlet oxygen (1O2) are critical PPRI for atorvastatin, carbamazepine, and sulfadiazine, while hydroxyl radical (˙OH) contributes to the indirect photodegradation of benzotriazole. We caution against relying on quenching studies because quenching of 3DOM limits the formation of 1O2 and all studied quenchers react with ˙OH. Furthermore, we show that DOM composition directly influences indirect photodegradation and that low molecular weight, microbial-like DOM is positively correlated with the indirect photodegradation rates of carbamazepine, sulfadiazine, and benzotriazole.

Dissolved Organic Matter Photoreactivity Is Determined by Its Optical Properties, Redox Activity, and Molecular Composition.

Predicting the formation of photochemically produced reactive intermediates (PPRI) during the irradiation of dissolved organic matter (DOM) has remained challenging given the complex nature of this material and differences in PPRI formation mechanisms. We investigate the role of DOM composition in photoreactivity using 48 samples that span the range of DOM in freshwater systems and wastewater. We relate quantum yields for excited triplet-state organic matter (fTMP), singlet oxygen (Φ1O2), and hydroxylating species (Φ•OH) to DOM composition determined using spectroscopy, Fourier-transform ion cyclotron resonance mass spectrometry, and electron-donating capacity (EDC). fTMP and Φ1O2 follow similar trends and are correlated with bulk properties derived from UV-vis spectra and EDC. In contrast, no individual bulk property can be used to predict Φ•OH. At the molecular level, the subset of DOM that is positively correlated to both Φ•OH and EDC is distinct from DOM formulas related to Φ1O2, demonstrating that •OH and 1O2 are formed from different DOM fractions. Multiple linear regressions are used to relate quantum yields of each PPRI to DOM composition parameters derived from multiple techniques, demonstrating that complementary methods are ideal for characterizing DOM because each technique only samples a subset of DOM.

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).

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.

The Role of Dissolved Organic Matter Composition in Determining Photochemical Reactivity at the Molecular Level.

Dissolved organic matter (DOM) composition influences its ability to form photochemically produced reactive intermediates (PPRI). While relationships have been established between bulk DOM properties and triplet DOM (3DOM) and singlet oxygen (1O2) quantum yields, contradictory evidence exists for hydroxyl radical (•OH) and hydroxylating species. Furthermore, little is known about these relationships at the molecular level. We evaluated DOM composition and photochemical reactivity of water samples from a wastewater treatment plant and the St. Louis River in Minnesota and Wisconsin, U.S.A. Bulk characterization using ultraviolet-visible spectroscopy demonstrates that color and apparent size of DOM decrease downstream, while molecular composition analysis using Fourier-transform ion cyclotron resonance mass spectrometry reveals that saturation and chemodiversity is highest near Lake Superior. 3DOM quantum yield coefficients and 1O2 quantum yields increase downstream and correlate strongly with saturated formulas. Similar results are observed for carbon-normalized photodegradation rate constants of atorvastatin, carbamazepine, and venlafaxine, which react primarily with 3DOM and 1O2. In contrast, •OH quantum yields are lowest downstream and correlate with less saturated, more oxygenated DOM, suggesting that 3DOM is not its major precursor. Mixed relationships are observed for DEET, which reacts with multiple PPRI. Molecular-level compositional data reveal insights into the differing formation pathways of individual PPRI, but information about specific contaminants is needed to predict their photochemical fate.

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.

Can We Validate the Results of Twin Studies? A Census-Based Study on the Heritability of Educational Achievement.

As for most phenotypes, the amount of variance in educational achievement explained by SNPs is lower than the amount of additive genetic variance estimated in twin studies. Twin-based estimates may however be biased because of self-selection and differences in cognitive ability between twins and the rest of the population. Here we compare twin registry based estimates with a census-based heritability estimate, sampling from the same Dutch birth cohort population and using the same standardized measure for educational achievement. Including important covariates (i.e., sex, migration status, school denomination, SES, and group size), we analyzed 893,127 scores from primary school children from the years 2008-2014. For genetic inference, we used pedigree information to construct an additive genetic relationship matrix. Corrected for the covariates, this resulted in an estimate of 85%, which is even higher than based on twin studies using the same cohort and same measure. We therefore conclude that the genetic variance not tagged by SNPs is not an artifact of the twin method itself.

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.

Environmental photochemistry of dienogest: phototransformation to estrogenic products and increased environmental persistence via reversible photohydration.

Potent trienone and dienone steroid hormones undergo a coupled photohydration (in light)-thermal dehydration (in dark) cycle that ultimately increases their environmental persistence. Here, we studied the photolysis of dienogest, a dienone progestin prescribed as a next-generation oral contraceptive, and used high resolution mass spectrometry and both 1D and 2D nuclear magnetic resonance spectroscopy to identify its phototransformation products. Dienogest undergoes rapid direct photolysis (t1/2 ∼ 1-10 min), forming complex photoproduct mixtures across the pH range examined (pH 2 to 7). Identified products include three photohydrates that account for ∼80% of the converted mass at pH 7 and revert back to parent dienogest in the absence of light. Notably, we also identified two estrogenic compounds produced via the A-ring aromatization of dienogest, evidence for a photochemically-induced increase in estrogenic activity in product mixtures. These results imply that dienogest will undergo complete and facile photolytic transformation in sunlit surface water, yet exhibit greater environmental persistence than might be anticipated by inspection of kinetic rates. Photoproduct mixtures also include transformation products with different nuclear receptor binding capabilities than the parent compound dienogest. These outcomes reveal a dynamic fate and biological risk profile for dienogest that must also take into account the composition and endocrine activity of its transformation products. Collectively, this study further illustrates the need for more holistic regulatory, risk assessment, and monitoring approaches for high potency synthetic pharmaceuticals and their bioactive transformation products.

Assessing Model Selection Uncertainty Using a Bootstrap Approach: An update.

Model comparisons in the behavioral sciences often aim at selecting the model that best describes the structure in the population. Model selection is usually based on fit indices such as AIC or BIC, and inference is done based on the selected best-fitting model. This practice does not account for the possibility that due to sampling variability, a different model might be selected as the preferred model in a new sample from the same population. A previous study illustrated a bootstrap approach to gauge this model selection uncertainty using two empirical examples. The current study consists of a series of simulations to assess the utility of the proposed bootstrap approach in multi-group and mixture model comparisons. These simulations show that bootstrap selection rates can provide additional information over and above simply relying on the size of AIC and BIC differences in a given sample.

Environmental Photochemistry of Altrenogest: Photoisomerization to a Bioactive Product with Increased Environmental Persistence via Reversible Photohydration.

Despite its wide use as a veterinary pharmaceutical, environmental fate data is lacking for altrenogest, a potent synthetic progestin. Here, it is reported that direct photolysis of altrenogest under environmentally relevant conditions was extremely efficient and rapid (half-life ∼25 s). Photolysis rates (observed rate constant kobs = 2.7 ± 0.2 × 10(-2) s(-1)) were unaffected by changes in pH or temperature but were sensitive to oxygen concentrations (N2-saturated kobs = 9.10 ± 0.32 × 10(-2) s(-1); O2-saturated kobs = 1.38 ± 0.11 × 10(-2) s(-1)). The primary photoproduct was identified as an isomer formed via an internal 2 + 2 cycloaddition reaction; the triplet lifetime (8.4 ± 0.2 µs) and rate constant (8 × 10(4) s(-1)) of this reaction were measured using transient absorption spectroscopy. Subsequent characterization determined that this primary cycloaddition photoproduct undergoes photohydration. The resultant photostable secondary photoproducts are subject to thermal dehydration in dark conditions, leading to reversion to the primary cycloaddition photoproduct on a time scale of hours to days, with the photohydration and dehydration repeatable over several light/dark cycles. This dehydration reaction occurs more rapidly at higher temperatures and is also accelerated at both high and low pH values. In vitro androgen receptor (AR)-dependent gene transcriptional activation cell assays and in silico nuclear hormone receptor screening revealed that certain photoproducts retain significant androgenic activity, which has implications for exposure risks associated with the presence and cycling of altrenogest and its photoproducts in the environment.

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.

A New Approach to Handle Missing Covariate Data in Twin Research : With an Application to Educational Achievement Data.

The often-used ACE model which decomposes phenotypic variance into additive genetic (A), common-environmental (C) and unique-environmental (E) parts can be extended to include covariates. Collection of these variables however often leads to a large amount of missing data, for example when self-reports (e.g. questionnaires) are not fully completed. The usual approach to handle missing covariate data in twin research results in reduced power to detect statistical effects, as only phenotypic and covariate data of individual twins with complete data can be used. Here we present a full information approach to handle missing covariate data that makes it possible to use all available data. A simulation study shows that, independent of missingness scenario, number of covariates or amount of missingness, the full information approach is more powerful than the usual approach. To illustrate the new method, we applied it to test scores on a Dutch national school achievement test (Eindtoets Basisonderwijs) in the final grade of primary school of 990 twin pairs. The effects of school-aggregated measures (e.g. school denomination, pedagogical philosophy, school size) and the effect of the sex of a twin on these test scores were tested. None of the covariates had a significant effect on individual differences in test scores.

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.

Meta-analysis of Genome-wide Association Studies for Neuroticism, and the Polygenic Association With Major Depressive Disorder.

IMPORTANCE: Neuroticism is a pervasive risk factor for psychiatric conditions. It genetically overlaps with major depressive disorder (MDD) and is therefore an important phenotype for psychiatric genetics. The Genetics of Personality Consortium has created a resource for genome-wide association analyses of personality traits in more than 63,000 participants (including MDD cases). OBJECTIVES: To identify genetic variants associated with neuroticism by performing a meta-analysis of genome-wide association results based on 1000 Genomes imputation; to evaluate whether common genetic variants as assessed by single-nucleotide polymorphisms (SNPs) explain variation in neuroticism by estimating SNP-based heritability; and to examine whether SNPs that predict neuroticism also predict MDD. DESIGN, SETTING, AND PARTICIPANTS: Genome-wide association meta-analysis of 30 cohorts with genome-wide genotype, personality, and MDD data from the Genetics of Personality Consortium. The study included 63,661 participants from 29 discovery cohorts and 9786 participants from a replication cohort. Participants came from Europe, the United States, or Australia. Analyses were conducted between 2012 and 2014. MAIN OUTCOMES AND MEASURES: Neuroticism scores harmonized across all 29 discovery cohorts by item response theory analysis, and clinical MDD case-control status in 2 of the cohorts. RESULTS: A genome-wide significant SNP was found on 3p14 in MAGI1 (rs35855737; P = 9.26 × 10-9 in the discovery meta-analysis). This association was not replicated (P = .32), but the SNP was still genome-wide significant in the meta-analysis of all 30 cohorts (P = 2.38 × 10-8). Common genetic variants explain 15% of the variance in neuroticism. Polygenic scores based on the meta-analysis of neuroticism in 27 cohorts significantly predicted neuroticism (1.09 × 10-12 < P < .05) and MDD (4.02 × 10-9 < P < .05) in the 2 other cohorts. CONCLUSIONS AND RELEVANCE: This study identifies a novel locus for neuroticism. The variant is located in a known gene that has been associated with bipolar disorder and schizophrenia in previous studies. In addition, the study shows that neuroticism is influenced by many genetic variants of small effect that are either common or tagged by common variants. These genetic variants also influence MDD. Future studies should confirm the role of the MAGI1 locus for neuroticism and further investigate the association of MAGI1 and the polygenic association to a range of other psychiatric disorders that are phenotypically correlated with neuroticism.

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.

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.