Assessing structural models of neighborhood and family sociodemographic characteristics and their relations with externalizing psychopathology

Externalizing psychopathology has been found to have small to moderate associations with neighborhood and family sociodemographic characteristics. However, prior studies may have used suboptimal operationalizations of neighborhood sociodemographic characteristics and externalizing psychopathology, potentially misestimating relations between these constructs. To address these limitations, in the current study we test different measurement models of these constructs and assess the structural relations between them. Using a population-representative sample of 2,195 twins and siblings from the Georgia Twin Study and data from the National Neighborhood Data Archive and 2000 U.S. Census, we assessed the fit of competing measurement models for family sociodemographic, neighborhood sociodemographic, and neighborhood environment characteristics. In structural models, we regressed a general externalizing dimension on different operationalizations of these variables separately and then simultaneously in a final model. Latent variable operationalizations of family sociodemographic, neighborhood sociodemographic, and neighborhood environment characteristics explained no more variance in broad externalizing psychopathology than other operationalizations. In an omnibus model, family sociodemographic characteristics showed a small association with externalizing psychopathology, while neighborhood sociodemographic and environmental characteristics did not. Family sociodemographic characteristics showed small associations with neighborhood sociodemographic and environmental characteristics, and neighborhood sociodemographic characteristics were moderately associated with neighborhood environment. These findings suggest that family sociodemographic characteristics are more associated with the development of broad externalizing psychopathology in youth than neighborhood sociodemographic characteristics and neighborhood environment. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Fine-mapping genomic loci refines bipolar disorder risk genes

Bipolar disorder (BD) is a heritable mental illness with complex etiology. While the largest published genome-wide association study identified 64 BD risk loci, the causal SNPs and genes within these loci remain unknown. We applied a suite of statistical and functional fine-mapping methods to these loci, and prioritized 22 likely causal SNPs for BD. We mapped these SNPs to genes, and investigated their likely functional consequences by integrating variant annotations, brain cell-type epigenomic annotations, brain quantitative trait loci, and results from rare variant exome sequencing in BD. Convergent lines of evidence supported the roles of SCN2A, TRANK1, DCLK3, INSYN2B, SYNE1, THSD7A, CACNA1B, TUBBP5, PLCB3, PRDX5, KCNK4, AP001453.3, TRPT1, FKBP2, DNAJC4, RASGRP1, FURIN, FES, YWHAE, DPH1, GSDMB, MED24, THRA, EEF1A2, and KCNQ2 in BD. These represent promising candidates for functional experiments to understand biological mechanisms and therapeutic potential. Additionally, we demonstrated that fine-mapping effect sizes can improve performance and transferability of BD polygenic risk scores across ancestrally diverse populations, and present a high-throughput fine-mapping pipeline (https://github.com/mkoromina/SAFFARI).

Principles and procedures for revising the hierarchical taxonomy of psychopathology

Quantitative, empirical approaches to establishing the structure of psychopathology hold promise to improve on traditional psychiatric classification systems. The Hierarchical Taxonomy of Psychopathology (HiTOP) is a framework that summarizes the substantial and growing body of quantitative evidence on the structure of psychopathology. To achieve its aims, HiTOP must incorporate emerging research in a systematic, ongoing fashion. In this article, we describe the historical context and grounding of the principles and procedures for revising the HiTOP framework. Informed by strengths and shortcomings of previous classification systems, the proposed revisions protocol is a formalized system focused around three pillars: (a) prioritizing systematic evaluation of quantitative evidence by a set of transparent criteria and processes, (b) balancing stability with flexibility, and (c) promoting inclusion over gatekeeping in all aspects of the process. We detail how the revisions protocol will be applied in practice, including the scientific and administrative aspects of the process. Additionally, we describe areas of the HiTOP structure that will be a focus of early revisions and outline challenges for the revisions protocol moving forward. The proposed revisions protocol is designed to ensure that the HiTOP framework reflects the current state of scientific knowledge on the structure of psychopathology and fulfils its potential to advance clinical research and practice. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Dimensional and transdiagnostic phenotypes in psychiatric genome-wide association studies

Genome-wide association studies (GWAS) provide biological insights into disease onset and progression and have potential to produce clinically useful biomarkers. A growing body of GWAS focuses on quantitative and transdiagnostic phenotypic targets, such as symptom severity or biological markers, to enhance gene discovery and the translational utility of genetic findings. The current review discusses such phenotypic approaches in GWAS across major psychiatric disorders. We identify themes and recommendations that emerge from the literature to date, including issues of sample size, reliability, convergent validity, sources of phenotypic information, phenotypes based on biological and behavioral markers such as neuroimaging and chronotype, and longitudinal phenotypes. We also discuss insights from multi-trait methods such as genomic structural equation modelling. These provide insight into how hierarchical 'splitting' and 'lumping' approaches can be applied to both diagnostic and dimensional phenotypes to model clinical heterogeneity and comorbidity. Overall, dimensional and transdiagnostic phenotypes have enhanced gene discovery in many psychiatric conditions and promises to yield fruitful GWAS targets in the years to come.

Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics

Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an externalizing factor, we assessed the impact of down-sampling on (1) the strength of the genetic signal in univariate GWASs, (2) the factor loadings and model fit in multivariate Genomic SEM, (3) the strength of the genetic signal at the factor level, (4) insights from gene-property analyses, (5) the pattern of genetic correlations with other traits, and (6) polygenic score analyses in independent samples. For the externalizing GWAS, although down-sampling resulted in a loss of genetic signal and fewer genome-wide significant loci; the factor loadings and model fit, gene-property analyses, genetic correlations, and polygenic score analyses were found robust. Given the importance of data sharing for the advancement of open science, we recommend that investigators who generate and share down-sampled summary statistics report these analyses as accompanying documentation to support other researchers' use of the summary statistics.

Evaluating alternative models of youth externalizing using quantitative genetic analyses

Interest has increased in the recent literature on characterizing psychopathology dimensionally in hierarchical models. One dimension of psychopathology that has received considerable attention is externalizing. Although extensively studied and well-characterized in late adolescents and adults, delineation of the externalizing spectrum in youth has lagged behind. As a complement to structural analyses of externalizing, in this study, we use quantitative genetic analyses of twin data to adjudicate among alternative models of youth externalizing that differ in granularity. Specifically, we compared model fit, estimates of genetic and environmental influences on the externalizing dimension, and the average, variability, and precision of genetic and environmental influences on individual symptoms due to the externalizing dimension, specific symptom dimensions, and unique etiological influences. Given that none of these criteria are definitive on their own, we looked to the confluence of these criteria to exclude particular models while highlighting others as leading contenders. We analyzed parent-report data on 38 externalizing symptoms from a population-representative, ethnically diverse sample of 883 youth twin pairs (51% female), who were on average 8.5 years old. Although models including an externalizing composite and attention deficit hyperactivity disorder, oppositional defiant disorder, and conduct disorder diagnoses and symptom dimensions showed similar heritability to latent variable models of externalizing, models that included latent dimensions of externalizing and more fine-grained symptom dimensions fit better and were more balanced in the magnitude of genetic and environmental influences on individual symptoms due to the externalizing dimension and specific symptom dimensions. Pending replication, these more granular and elaborated model(s) can be useful for advancing research on causes and outcomes of youth externalizing and its fine-grained specific components. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

A multivariate approach to understanding the genetic overlap between externalizing phenotypes and substance use disorders

Substance use disorders (SUDs) are phenotypically and genetically correlated with each other and with other psychological traits characterized by behavioural under-control, termed externalizing phenotypes. In this study, we used genomic structural equation modelling to explore the shared genetic architecture among six externalizing phenotypes and four SUDs used in two previous multivariate genome-wide association studies of an externalizing and an addiction risk factor, respectively. We first evaluated five confirmatory factor analytic models, including a common factor model, alternative parameterizations of two-factor structures and a bifactor model. We next explored the genetic correlations between factors identified in these models and other relevant psychological traits. Finally, we quantified the degree of polygenic overlap between externalizing and addiction risk using MiXeR. We found that the common and two-factor structures provided the best fit to the data, evidenced by high factor loadings, good factor reliability and no evidence of concerning model characteristics. The two-factor models yielded high genetic correlations between factors (rg s ≥ 0.87), and between the effect sizes of genetic correlations with external traits (rg  ≥ 0.95). Nevertheless, 21 of the 84 correlations with external criteria showed small, significant differences between externalizing and addiction risk factors. MiXer results showed that approximately 81% of influential externalizing variants were shared with addiction risk, whereas addiction risk shared 56% of its influential variants with externalizing. These results suggest that externalizing and addiction genetic risk are largely shared, though both constructs also retain meaningful unshared genetic variance. These results can inform future efforts to identify specific genetic influences on externalizing and SUDs.

Guidelines for Evaluating the Comparability of Down-Sampled GWAS Summary Statistics

Proprietary genetic datasets are valuable for boosting the statistical power of genome-wide association studies (GWASs), but their use can restrict investigators from publicly sharing the resulting summary statistics. Although researchers can resort to sharing down-sampled versions that exclude restricted data, down-sampling reduces power and might change the genetic etiology of the phenotype being studied. These problems are further complicated when using multivariate GWAS methods, such as genomic structural equation modeling (Genomic SEM), that model genetic correlations across multiple traits. Here, we propose a systematic approach to assess the comparability of GWAS summary statistics that include versus exclude restricted data. Illustrating this approach with a multivariate GWAS of an externalizing factor, we assessed the impact of down-sampling on (1) the strength of the genetic signal in univariate GWASs, (2) the factor loadings and model fit in multivariate Genomic SEM, (3) the strength of the genetic signal at the factor level, (4) insights from gene-property analyses, (5) the pattern of genetic correlations with other traits, and (6) polygenic score analyses in independent samples. For the externalizing GWAS, down-sampling resulted in a loss of genetic signal and fewer genome-wide significant loci, while the factor loadings and model fit, gene-property analyses, genetic correlations, and polygenic score analyses are robust. Given the importance of data sharing for the advancement of open science, we recommend that investigators who share down-sampled summary statistics report these analyses as accompanying documentation to support other researchers' use of the summary statistics.

A broad internalizing dimension accounts for the genetic associations between personality and individual internalizing disorders

Much research has demonstrated that psychopathology can be described in terms of broad dimensions, representing liability for multiple psychiatric disorders. Broad spectra of psychopathology (e.g., internalizing and externalizing) are increasingly used as targets for research investigating the development, etiology, and course of psychopathology because they account for patterns of relatedness among disorders that were once presumed distinct. Thus, these spectra represent alluring targets due to their comprehensive and parsimonious nature. Nevertheless, little research has established the role of individual disorders over and above broad dimensions in the study of psychopathology. In the current study, we investigate whether there are unique etiological associations between individual internalizing disorders and personality traits after accounting for their etiological associations with a broad internalizing dimension. We used a community sample of twins (Npairs = 448) ages 4 to 19 to examine the etiological associations between internalizing psychopathology and Big Five personality dimensions. In terms of genetic covariation, a broad internalizing dimension was positively associated with neuroticism and negatively associated with extraversion, agreeableness, and conscientiousness. Moreover, internalizing accounted for most of the genetic variance shared between individual internalizing disorders and personality traits. Nevertheless, there were unique genetic associations between the following pairs of personality traits and disorders: neuroticism and social anxiety, extraversion and social anxiety, agreeableness and depression, and conscientiousness and compulsions. There was little evidence of environmental influences shared between internalizing and personality. In sum, a broad internalizing dimension adequately accounted for almost all of the etiologic covariation between internalizing disorders and personality, with several interesting exceptions. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

The Hierarchical Taxonomy of Psychopathology (HiTOP) in psychiatric practice and research

The Hierarchical Taxonomy of Psychopathology (HiTOP) has emerged out of the quantitative approach to psychiatric nosology. This approach identifies psychopathology constructs based on patterns of co-variation among signs and symptoms. The initial HiTOP model, which was published in 2017, is based on a large literature that spans decades of research. HiTOP is a living model that undergoes revision as new data become available. Here we discuss advantages and practical considerations of using this system in psychiatric practice and research. We especially highlight limitations of HiTOP and ongoing efforts to address them. We describe differences and similarities between HiTOP and existing diagnostic systems. Next, we review the types of evidence that informed development of HiTOP, including populations in which it has been studied and data on its validity. The paper also describes how HiTOP can facilitate research on genetic and environmental causes of psychopathology as well as the search for neurobiologic mechanisms and novel treatments. Furthermore, we consider implications for public health programs and prevention of mental disorders. We also review data on clinical utility and illustrate clinical application of HiTOP. Importantly, the model is based on measures and practices that are already used widely in clinical settings. HiTOP offers a way to organize and formalize these techniques. This model already can contribute to progress in psychiatry and complement traditional nosologies. Moreover, HiTOP seeks to facilitate research on linkages between phenotypes and biological processes, which may enable construction of a system that encompasses both biomarkers and precise clinical description.

Answering questions about the Hierarchical Taxonomy of Psychopathology (HiTOP): Analogies to whales and sharks miss the boat

This commentary discusses questions and misconceptions about HiTOP raised by Haeffel et al. (2021). We explain what the system classifies and why it is descriptive and atheoretical, highlighting benefits and limitations of this approach. We clarify why the system is organized according to patterns of covariation or comorbidity among signs and symptoms of psychopathology, and we discuss how it is designed to be falsifiable and revised in a manner that is responsive to data. We refer to the body of evidence for HiTOP's external validity and for its scientific and clinical utility. We further describe how the system is currently used in clinics. In sum, many of Haeffel et al.'s concerns about HiTOP are unwarranted, and for those concerns that reflect real current limitations of HiTOP, our consortium is working to address them, with the aim of creating a nosology that is comprehensive and useful to both scientists and clinicians.

Multivariate analysis of 1.5 million people identifies genetic associations with traits related to self-regulation and addiction

Behaviors and disorders related to self-regulation, such as substance use, antisocial behavior and attention-deficit/hyperactivity disorder, are collectively referred to as externalizing and have shared genetic liability. We applied a multivariate approach that leverages genetic correlations among externalizing traits for genome-wide association analyses. By pooling data from ~1.5 million people, our approach is statistically more powerful than single-trait analyses and identifies more than 500 genetic loci. The loci were enriched for genes expressed in the brain and related to nervous system development. A polygenic score constructed from our results predicts a range of behavioral and medical outcomes that were not part of genome-wide analyses, including traits that until now lacked well-performing polygenic scores, such as opioid use disorder, suicide, HIV infections, criminal convictions and unemployment. Our findings are consistent with the idea that persistent difficulties in self-regulation can be conceptualized as a neurodevelopmental trait with complex and far-reaching social and health correlates.

Clarifying the structure and nature of left-wing authoritarianism

Authoritarianism has been the subject of scientific inquiry for nearly a century, yet the vast majority of authoritarianism research has focused on right-wing authoritarianism. In the present studies, we investigate the nature, structure, and nomological network of left-wing authoritarianism (LWA), a construct famously known as "the Loch Ness Monster" of political psychology. We iteratively construct a measure and data-driven conceptualization of LWA across six samples (N = 7,258) and conduct quantitative tests of LWA's relations with more than 60 authoritarianism-related variables. We find that LWA, right-wing authoritarianism, and social dominance orientation reflect a shared constellation of personality traits, cognitive features, beliefs, and motivational values that might be considered the "heart" of authoritarianism. Relative to right-wing authoritarians, left-wing authoritarians were lower in dogmatism and cognitive rigidity, higher in negative emotionality, and expressed stronger support for a political system with substantial centralized state control. Our results also indicate that LWA powerfully predicts behavioral aggression and is strongly correlated with participation in political violence. We conclude that a movement away from exclusively right-wing conceptualizations of authoritarianism may be required to illuminate authoritarianism's central features, conceptual breadth, and psychological appeal. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

Neurobiology and the Hierarchical Taxonomy of Psychopathology: progress toward ontogenetically informed and clinically useful nosology

The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirical structural model of psychological symptoms formulated to improve the reliability and validity of clinical assessment. Neurobiology can inform assessments of early risk and intervention strategies, and the HiTOP model has greater potential to interface with neurobiological measures than traditional categorical diagnoses given its enhanced reliability. However, one complication is that observed biological correlates of clinical symptoms can reflect various factors, ranging from dispositional risk to consequences of psychopathology. In this paper, we argue that the HiTOP model provides an optimized framework for conducting research on the biological correlates of psychopathology from an ontogenetic perspective that distinguishes among indicators of liability, current symptoms, and consequences of illness. Through this approach, neurobiological research can contribute more effectively to identifying individuals at high dispositional risk, indexing treatment-related gains, and monitoring the consequences of mental illness, consistent with the aims of the HiTOP framework.


Genome-wide association study of more than 40,000 bipolar disorder cases provides new insights into the underlying biology

Bipolar disorder is a heritable mental illness with complex etiology. We performed a genome-wide association study of 41,917 bipolar disorder cases and 371,549 controls of European ancestry, which identified 64 associated genomic loci. Bipolar disorder risk alleles were enriched in genes in synaptic signaling pathways and brain-expressed genes, particularly those with high specificity of expression in neurons of the prefrontal cortex and hippocampus. Significant signal enrichment was found in genes encoding targets of antipsychotics, calcium channel blockers, antiepileptics and anesthetics. Integrating expression quantitative trait locus data implicated 15 genes robustly linked to bipolar disorder via gene expression, encoding druggable targets such as HTR6, MCHR1, DCLK3 and FURIN. Analyses of bipolar disorder subtypes indicated high but imperfect genetic correlation between bipolar disorder type I and II and identified additional associated loci. Together, these results advance our understanding of the biological etiology of bipolar disorder, identify novel therapeutic leads and prioritize genes for functional follow-up studies.

Rethinking the Diagnosis of Mental Disorders: Data-Driven Psychological Dimensions, Not Categories, as a Framework for Mental-Health Research, Treatment, and Training

Generations of psychologists have been taught that mental disorder can be carved into discrete categories, each qualitatively different from the others and from normality. This model is now outdated. A preponderance of evidence indicates that (a) individual differences in mental health (health vs. illness) are a matter of degree, not kind, and (b) broad mental-health conditions (e.g., internalizing) account for the tendency of narrower ones (e.g., depression, social anxiety, panic) to co-occur. With these observations in mind, we discuss an alternative diagnostic system, called the Hierarchical Taxonomy of Psychopathology (HiTOP), that describes the broad and specific components of mental disorder. It deconstructs traditional diagnostic categories, such as those listed in the Diagnostic and Statistical Manual of Mental Disorders, and recasts them in terms of profiles of dimensions. Recent findings support the utility of this approach for mental-health research and intervention efforts. HiTOP has the potential to put mental-health research, training, and treatment on a much sounder scientific footing.

Three recommendations based on a comparison of the reliability and validity of the predominant models used in research on the empirical structure of psychopathology

The present study compared the primary models used in research on the structure of psychopathology (i.e., correlated factor, higher-order, and bifactor models) in terms of structural validity (model fit and factor reliability), longitudinal measurement invariance, concurrent and prospective predictive validity in relation to important outcomes, and longitudinal consistency in individuals' factor score profiles. Two simpler operationalizations of a general factor of psychopathology were also examined-a single-factor model and a count of diagnoses. Models were estimated based on structured clinical interview diagnoses in two longitudinal waves of nationally representative data from the United States (n = 43,093 and n = 34,653). Models that included narrower factors (fear, distress, and externalizing) were needed to capture the observed multidimensionality of the data. In the correlated factor and higher-order models these narrower factors were reliable, largely invariant over time, had consistent associations with indicators of adaptive functioning, and had moderate stability within individuals over time. By contrast, the fear- and distress-specific factors in the bifactor model did not show good reliability or validity throughout the analyses. Notably, the general factor of psychopathology (p factor) performed similarly well across tests of reliability and validity regardless of whether the higher-order or bifactor model was used; the simplest (single factor) model was also comparable across most tests, with the exception of model fit. Given the limitations of categorical diagnoses, it will be important to repeat these analyses using dimensional measures. We conclude that when aiming to understand the structure and correlates of psychopathology it is important to (a) look beyond model fit indices to choose between different models, (b) examine the reliability of latent variables directly, and (c) be cautious when isolating and interpreting the unique effects of specific psychopathology factors, regardless of which model is used. (PsycInfo Database Record (c) 2021 APA, all rights reserved).

The Hierarchical Taxonomy of Psychopathology (HiTOP): A Quantitative Nosology Based on Consensus of Evidence

Traditional diagnostic systems went beyond empirical evidence on the structure of mental health. Consequently, these diagnoses do not depict psychopathology accurately, and their validity in research and utility in clinicalpractice are therefore limited. The Hierarchical Taxonomy of Psychopathology (HiTOP) consortium proposed a model based on structural evidence. It addresses problems of diagnostic heterogeneity, comorbidity, and unreliability. We review the HiTOP model, supporting evidence, and conceptualization of psychopathology in this hierarchical dimensional framework. The system is not yet comprehensive, and we describe the processes for improving and expanding it. We summarize data on the ability of HiTOP to predict and explain etiology (genetic, environmental, and neurobiological), risk factors, outcomes, and treatment response. We describe progress in the development of HiTOP-based measures and in clinical implementation of the system. Finally, we review outstanding challenges and the research agenda. HiTOP is of practical utility already, and its ongoing development will produce a transformative map of psychopathology.

Risk variants and polygenic architecture of disruptive behavior disorders in the context of attention-deficit/hyperactivity disorder

Attention-Deficit/Hyperactivity Disorder (ADHD) is a childhood psychiatric disorder often comorbid with disruptive behavior disorders (DBDs). Here, we report a GWAS meta-analysis of ADHD comorbid with DBDs (ADHD + DBDs) including 3802 cases and 31,305 controls. We identify three genome-wide significant loci on chromosomes 1, 7, and 11. A meta-analysis including a Chinese cohort supports that the locus on chromosome 11 is a strong risk locus for ADHD + DBDs across European and Chinese ancestries (rs7118422, P = 3.15×10⁻¹⁰, OR = 1.17). We find a higher SNP heritability for ADHD + DBDs (h²_SNP = 0.34) when compared to ADHD without DBDs (h²_SNP = 0.20), high genetic correlations between ADHD + DBDs and aggressive (r_g = 0.81) and anti-social behaviors (r_g = 0.82), and an increased burden (polygenic score) of variants associated with ADHD and aggression in ADHD + DBDs compared to ADHD without DBDs. Our results suggest an increased load of common risk variants in ADHD + DBDs compared to ADHD without DBDs, which in part can be explained by variants associated with aggressive behavior.

ADHD is often found to be comorbid with disruptive behavior disorders, but the genetic loci underlying this comorbidity are unknown. Here, the authors have performed a GWAS meta-analysis of ADHD with disruptive behavior disorders, finding three genome-wide significant loci in Europeans, and replicating one in a Chinese cohort.

Les progrès dans la réalisation de la classification quantitative de la psychopathologie☆

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level" dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity" by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.

Testing structural models of psychopathology at the genomic level

Genome-wide association studies (GWAS) have revealed hundreds of genetic loci associated with the vulnerability to major psychiatric disorders, and post-GWAS analyses have shown substantial genetic correlations among these disorders. This evidence supports the existence of a higher-order structure of psychopathology at both the genetic and phenotypic levels. Despite recent efforts by collaborative consortia such as the Hierarchical Taxonomy of Psychopathology (HiTOP), this structure remains unclear. In this study, we tested multiple alternative structural models of psychopathology at the genomic level, using the genetic correlations among fourteen psychiatric disorders and related psychological traits estimated from GWAS summary statistics. The best-fitting model included four correlated higher-order factors - externalizing, internalizing, thought problems, and neurodevelopmental disorders - which showed distinct patterns of genetic correlations with external validity variables and accounted for substantial genetic variance in their constituent disorders. A bifactor model including a general factor of psychopathology as well as the four specific factors fit worse than the above model. Several model modifications were tested to explore the placement of some disorders - such as bipolar disorder, obsessive-compulsive disorder, and eating disorders - within the broader psychopathology structure. The best-fitting model indicated that eating disorders and obsessive-compulsive disorder, on the one hand, and bipolar disorder and schizophrenia, on the other, load together on the same thought problems factor. These findings provide support for several of the HiTOP higher-order dimensions and suggest a similar structure of psychopathology at the genomic and phenotypic levels.

Construct validity of youth psychopathic traits as assessed by the Antisocial Process Screening Device

The study of psychopathic traits in youth is in its nascent stages and the nature and the structure of these traits is still poorly understood. In one of the most comprehensive analyses to date of the construct validity of the widely used Antisocial Processing Screening Device (APSD), we used two independent samples of youth, one community (N = 2203) and one clinic-referred (N = 534), ages 4 to 19 (51% female), to investigate the external correlates of the Callous-unemotionality (CU), Narcissism, and Impulsivity dimensions of youth psychopathy. We used parent reports of externalizing and internalizing psychopathology, personality, and aggressive behavior to examine the pattern of associations between psychopathic trait dimensions and relevant external correlates. Across both samples, CU was positively related to all forms of externalizing psychopathology and aggression, mostly unrelated to internalizing psychopathology, and negatively related to agreeableness and conscientiousness. Narcissism and Impulsivity were positively related to externalizing psychopathology, and aggression, negatively related to agreeableness and conscientiousness, and weakly positively related to internalizing psychopathology. In most cases, each dimension of the APSD manifested statistically significantly different relations with these external correlates. Many of our findings replicate and extend work conducted with both youth and adults, although others suggest that these dimensions do not distinguish among psychopathological domains in conceptually expected ways. Broadly speaking, these findings provide evidence that psychopathic traits in youth are best characterized by a multidimensional model and bear implications for models integrating normative with pathological personality. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

Correction to: The Association of Oxytocin Receptor Gene (OXTR) Polymorphisms with Antisocial Behavior: A Meta-analysis

The original version of this article inadvertently omitted the word "with" between "Polymorphisms" and "Antisocial" from the title. The title "The Association of Oxytocin Receptor Gene (OXTR) Polymorphisms Antisocial Behavior: A Meta-Analysis" should be "The Association of Oxytocin Receptor Gene (OXTR) Polymorphisms with Antisocial Behavior: A Meta-Analysis." as presented above.

Redefining phenotypes to advance psychiatric genetics: Implications from hierarchical taxonomy of psychopathology

Genetic discovery in psychiatry and clinical psychology is hindered by suboptimal phenotypic definitions. We argue that the hierarchical, dimensional, and data-driven classification system proposed by the Hierarchical Taxonomy of Psychopathology (HiTOP) consortium provides a more effective approach to identifying genes that underlie mental disorders, and to studying psychiatric etiology, than current diagnostic categories. Specifically, genes are expected to operate at different levels of the HiTOP hierarchy, with some highly pleiotropic genes influencing higher order psychopathology (e.g., the general factor), whereas other genes conferring more specific risk for individual spectra (e.g., internalizing), subfactors (e.g., fear disorders), or narrow symptoms (e.g., mood instability). We propose that the HiTOP model aligns well with the current understanding of the higher order genetic structure of psychopathology that has emerged from a large body of family and twin studies. We also discuss the convergence between the HiTOP model and findings from recent molecular studies of psychopathology indicating broad genetic pleiotropy, such as cross-disorder SNP-based shared genetic covariance and polygenic risk scores, and we highlight molecular genetic studies that have successfully redefined phenotypes to enhance precision and statistical power. Finally, we suggest how to integrate a HiTOP approach into future molecular genetic research, including quantitative and hierarchical assessment tools for future data-collection and recommendations concerning phenotypic analyses. (PsycINFO Database Record (c) 2020 APA, all rights reserved).

Are fit indices used to test psychopathology structure biased? A simulation study

Structural models of psychopathology provide dimensional alternatives to traditional categorical classification systems. Competing models, such as the bifactor and correlated factors models, are typically compared via statistical indices to assess how well each model fits the same data. However, simulation studies have found evidence for probifactor fit index bias in several psychological research domains. The present study sought to extend this research to models of psychopathology, wherein the bifactor model has received much attention, but its susceptibility to bias is not well characterized. We used Monte Carlo simulations to examine how various model misspecifications produced fit index bias for 2 commonly used estimators, WLSMV and MLR. We simulated binary indicators to represent psychiatric diagnoses and positively skewed continuous indicators to represent symptom counts. Across combinations of estimators, indicator distributions, and misspecifications, complex patterns of bias emerged, with fit indices more often than not failing to correctly identify the correlated factors model as the data-generating model. No fit index emerged as reliably unbiased across all misspecification scenarios. Although, tests of model equivalence indicated that in one instance fit indices were not biased-they favored the bifactor model, albeit not unfairly. Overall, results suggest that comparisons of bifactor models to alternatives using fit indices may be misleading and call into question the evidentiary meaning of previous studies that identified the bifactor model as superior based on fit. We highlight the importance of comparing models based on substantive interpretability and their utility for addressing study aims, the methodological significance of model equivalence, as well as the need for implementation of statistical metrics that evaluate model quality. (PsycINFO Database Record (c) 2019 APA, all rights reserved).

A Hierarchical Taxonomy of Psychopathology Can Transform Mental Health Research

For more than a century, research on psychopathology has focused on categorical diagnoses. Although this work has produced major discoveries, growing evidence points to the superiority of a dimensional approach to the science of mental illness. Here we outline one such dimensional system-the Hierarchical Taxonomy of Psychopathology (HiTOP)-that is based on empirical patterns of co-occurrence among psychological symptoms. We highlight key ways in which this framework can advance mental-health research, and we provide some heuristics for using HiTOP to test theories of psychopathology. We then review emerging evidence that supports the value of a hierarchical, dimensional model of mental illness across diverse research areas in psychological science. These new data suggest that the HiTOP system has the potential to accelerate and improve research on mental-health problems as well as efforts to more effectively assess, prevent, and treat mental illness.

Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder

Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.

Discovery of the first genome-wide significant risk loci for attention deficit/hyperactivity disorder

Attention deficit/hyperactivity disorder (ADHD) is a highly heritable childhood behavioral disorder affecting 5% of children and 2.5% of adults. Common genetic variants contribute substantially to ADHD susceptibility, but no variants have been robustly associated with ADHD. We report a genome-wide association meta-analysis of 20,183 individuals diagnosed with ADHD and 35,191 controls that identifies variants surpassing genome-wide significance in 12 independent loci, finding important new information about the underlying biology of ADHD. Associations are enriched in evolutionarily constrained genomic regions and loss-of-function intolerant genes and around brain-expressed regulatory marks. Analyses of three replication studies: a cohort of individuals diagnosed with ADHD, a self-reported ADHD sample and a meta-analysis of quantitative measures of ADHD symptoms in the population, support these findings while highlighting study-specific differences on genetic overlap with educational attainment. Strong concordance with GWAS of quantitative population measures of ADHD symptoms supports that clinical diagnosis of ADHD is an extreme expression of continuous heritable traits.

Progress in achieving quantitative classification of psychopathology

Shortcomings of approaches to classifying psychopathology based on expert consensus have given rise to contemporary efforts to classify psychopathology quantitatively. In this paper, we review progress in achieving a quantitative and empirical classification of psychopathology. A substantial empirical literature indicates that psychopathology is generally more dimensional than categorical. When the discreteness versus continuity of psychopathology is treated as a research question, as opposed to being decided as a matter of tradition, the evidence clearly supports the hypothesis of continuity. In addition, a related body of literature shows how psychopathology dimensions can be arranged in a hierarchy, ranging from very broad "spectrum level" dimensions, to specific and narrow clusters of symptoms. In this way, a quantitative approach solves the "problem of comorbidity" by explicitly modeling patterns of co-occurrence among signs and symptoms within a detailed and variegated hierarchy of dimensional concepts with direct clinical utility. Indeed, extensive evidence pertaining to the dimensional and hierarchical structure of psychopathology has led to the formation of the Hierarchical Taxonomy of Psychopathology (HiTOP) Consortium. This is a group of 70 investigators working together to study empirical classification of psychopathology. In this paper, we describe the aims and current foci of the HiTOP Consortium. These aims pertain to continued research on the empirical organization of psychopathology; the connection between personality and psychopathology; the utility of empirically based psychopathology constructs in both research and the clinic; and the development of novel and comprehensive models and corresponding assessment instruments for psychopathology constructs derived from an empirical approach.

Enhancing Psychosis-Spectrum Nosology Through an International Data Sharing Initiative

The latent structure of schizotypy and psychosis-spectrum symptoms remains poorly understood. Furthermore, molecular genetic substrates are poorly defined, largely due to the substantial resources required to collect rich phenotypic data across diverse populations. Sample sizes of phenotypic studies are often insufficient for advanced structural equation modeling approaches. In the last 50 years, efforts in both psychiatry and psychological science have moved toward (1) a dimensional model of psychopathology (eg, the current Hierarchical Taxonomy of Psychopathology [HiTOP] initiative), (2) an integration of methods and measures across traits and units of analysis (eg, the RDoC initiative), and (3) powerful, impactful study designs maximizing sample size to detect subtle genomic variation relating to complex traits (the Psychiatric Genomics Consortium [PGC]). These movements are important to the future study of the psychosis spectrum, and to resolving heterogeneity with respect to instrument and population. The International Consortium of Schizotypy Research is composed of over 40 laboratories in 12 countries, and to date, members have compiled a body of schizotypy- and psychosis-related phenotype data from more than 30000 individuals. It has become apparent that compiling data into a protected, relational database and crowdsourcing analytic and data science expertise will result in significant enhancement of current research on the structure and biological substrates of the psychosis spectrum. The authors present a data-sharing infrastructure similar to that of the PGC, and a resource-sharing infrastructure similar to that of HiTOP. This report details the rationale and benefits of the phenotypic data collective and presents an open invitation for participation.

Prospective test of the developmental propensity model of antisocial behavior: from childhood and adolescence into early adulthood

BACKGROUND

The developmental propensity model of antisocial behavior posits that several dispositional characteristics of children transact with the environment to influence the likelihood of learning antisocial behavior across development. Specifically, greater dispositional negative emotionality, greater daring, and lower prosociality-operationally, the inverse of callousness- and lower cognitive abilities are each predicted to increase risk for developing antisocial behavior.

METHODS

Prospective tests of key predictions derived from the model were conducted in a high-risk sample of 499 twins who were assessed on dispositions at 10-17 years of age and assessed for antisocial personality disorder (APD) symptoms at 22-31 years of age. Predictions were tested separately for parent and youth informants on the dispositions using multiple regressions that adjusted for oversampling, nonresponse, and clustering within twin pairs, controlling demographic factors and time since the first assessment.

RESULTS

Consistent with predictions, greater numbers of APD symptoms in adulthood were independently predicted over a 10-15 year span by higher youth ratings on negative emotionality and daring and lower youth ratings on prosociality, and by parent ratings of greater negative emotionality and lower prosociality. A measure of working memory did not predict APD symptoms.

CONCLUSIONS

These findings support future research on the role of these dispositions in the development of antisocial behavior.

Measuring the hierarchical general factor model of psychopathology in young adults

There is evidence that models of psychopathology specifying a general factor and specific second-order factors fit better than competing structural models. Nonetheless, additional tests are needed to examine the generality and boundaries of the general factor model. In a selected second wave of a cohort study, first-order dimensions of psychopathology symptoms in 499 23- to 31-year-old twins were analyzed. Using confirmatory factor analysis, a bifactor model specifying a general factor and specific internalizing and externalizing factors fit better than competing models. Factor loadings in this model were sex invariant despite greater variances in the specific internalizing factor among females and greater variances in the general and specific externalizing factors among males. The bifactor structure was robust to the exclusion of any single first-order dimension of psychopathology. Furthermore, the results were essentially unchanged when all overlapping symptoms that define multiple disorders were excluded from symptom dimensions. Furthermore, the best-fitting bifactor model also emerged in exploratory structural equation modeling with freely estimated cross-loadings. The general factor of psychopathology was robust across variations in measurement and analysis.

The nature and correlates of the dark triad: The answers depend on the questions

The past several decades have witnessed a proliferation of research on the dark triad (DT), a set of traits comprising Machiavellianism, narcissism, and psychopathy. The bulk of DT research has been marked by several core assumptions, most notably that each DT construct is a monolithic entity that is clearly separable from its counterpart DT constructs. To examine the tenability of these assumptions, we pooled data from 2 samples of North American community members (ns = 312 and 351) to explore (a) the external validity and profile similarities of DT indicators and (b) the factor structure of the DT. Using general personality dimensions as external criteria, we demonstrated that each DT measure is multidimensional and that subdimensions within DT measures often display sharply different and at times even opposing relations with personality domains; these opposing relations were largely obscured at the total score level adopted in most of the DT literature. In both samples, confirmatory factor analyses and exploratory structural equation models provided no clear support for the traditional tripartite DT structure delineated in the literature. Instead, various aspects of the DT constructs fractionated across a number of factors that represented more basic personality elements (e.g., emotional stability, grandiosity). Taken together, our findings raise serious questions regarding the standard model of DT research and suggest that the questions posed regarding the correlates of DT constructs hinge crucially on the specific DT measure and subdimension examined. (PsycINFO Database Record

External validity of a hierarchical dimensional model of child and adolescent psychopathology: Tests using confirmatory factor analyses and multivariate behavior genetic analyses

Several recent studies of the hierarchical phenotypic structure of psychopathology have identified a General psychopathology factor in addition to the more expected specific Externalizing and Internalizing dimensions in both youth and adult samples and some have found relevant unique external correlates of this General factor. We used data from 1,568 twin pairs (599 MZ & 969 DZ) age 9 to 17 to test hypotheses for the underlying structure of youth psychopathology and the external validity of the higher-order factors. Psychopathology symptoms were assessed via structured interviews of caretakers and youth. We conducted phenotypic analyses of competing structural models using Confirmatory Factor Analysis and used Structural Equation Modeling and multivariate behavior genetic analyses to understand the etiology of the higher-order factors and their external validity. We found that both a General factor and specific Externalizing and Internalizing dimensions are necessary for characterizing youth psychopathology at both the phenotypic and etiologic levels, and that the 3 higher-order factors differed substantially in the magnitudes of their underlying genetic and environmental influences. Phenotypically, the specific Externalizing and Internalizing dimensions were slightly negatively correlated when a General factor was included, which reflected a significant inverse correlation between the nonshared environmental (but not genetic) influences on Internalizing and Externalizing. We estimated heritability of the general factor of psychopathology for the first time. Its moderate heritability suggests that it is not merely an artifact of measurement error but a valid construct. The General, Externalizing, and Internalizing factors differed in their relations with 3 external validity criteria: mother's smoking during pregnancy, parent's harsh discipline, and the youth's association with delinquent peers. Multivariate behavior genetic analyses supported the external validity of the 3 higher-order factors by suggesting that the General, Externalizing, and Internalizing factors were correlated with peer delinquency and parent's harsh discipline for different etiologic reasons. (PsycINFO Database Record

A hierarchical causal taxonomy of psychopathology across the life span

We propose a taxonomy of psychopathology based on patterns of shared causal influences identified in a review of multivariate behavior genetic studies that distinguish genetic and environmental influences that are either common to multiple dimensions of psychopathology or unique to each dimension. At the phenotypic level, first-order dimensions are defined by correlations among symptoms; correlations among first-order dimensions similarly define higher-order domains (e.g., internalizing or externalizing psychopathology). We hypothesize that the robust phenotypic correlations among first-order dimensions reflect a hierarchy of increasingly specific etiologic influences. Some nonspecific etiologic factors increase risk for all first-order dimensions of psychopathology to varying degrees through a general factor of psychopathology. Other nonspecific etiologic factors increase risk only for all first-order dimensions within a more specific higher-order domain. Furthermore, each first-order dimension has its own unique causal influences. Genetic and environmental influences common to family members tend to be nonspecific, whereas environmental influences unique to each individual are more dimension-specific. We posit that these causal influences on psychopathology are moderated by sex and developmental processes. This causal taxonomy also provides a novel framework for understanding the heterogeneity of each first-order dimension: Different persons exhibiting similar symptoms may be influenced by different combinations of etiologic influences from each of the 3 levels of the etiologic hierarchy. Furthermore, we relate the proposed causal taxonomy to transdimensional psychobiological processes, which also impact the heterogeneity of each psychopathology dimension. This causal taxonomy implies the need for changes in strategies for studying the etiology, psychobiology, prevention, and treatment of psychopathology. (PsycINFO Database Record

Genetic and Environmental Contributions to Associations between Infant Fussy Temperament and Antisocial Behavior in Childhood and Adolescence

Previous research suggests that fussy temperament in infancy predicts risk for later antisocial behavior (ASB) in childhood and adolescence. It remains unclear, however, to what extent infant fussiness is related to later ASB through causal processes or if they both reflect the same family risk factors for ASB. The current study used two approaches, the comparison of siblings and bivariate biometric modeling, to reduce familial confounding and examine genetic and environmental influences on associations between fussiness in the first 2 years of life and ASB in childhood and late adolescence. Analyses were conducted on data from a prospective cohort (9237 at 4-9 years and 7034 at 14-17 years) who are the offspring of a nationally representative sample of US women. In the full sample, fussiness predicted both child and adolescent ASB to small but significant extents, controlling for a wide range of measured child and family-level covariates. When siblings who differed in their fussiness were compared, fussiness predicted ASB in childhood, but not ASB during adolescence. Furthermore, results from a bivariate Cholesky model suggested that even the association of fussiness with childhood ASB found when comparing siblings is attributable to familial factors. That is, although families with infants who are higher in fussiness also tend to have children and adolescents who engage in greater ASB, the hypothesis that infant fussiness has an environmentally mediated impact on the development of future ASB was not strongly supported.

An examination of the developmental propensity model of conduct problems

The present study tested specific hypotheses advanced by the developmental propensity model of the etiology of conduct problems in the Colorado Longitudinal Twin Study, a prospective, longitudinal, genetically informative sample. High negative emotionality, low behavioral inhibition, low concern and high disregard for others, and low cognitive ability assessed during toddlerhood (age 14 to 36 months) were examined as predictors of conduct problems in later childhood and adolescence (age 4 to 17 years). Each hypothesized antisocial propensity dimension predicted conduct problems, but some predictions may be context specific or due to method covariance. The most robust predictors were observed disregard for others (i.e., responding to others' distress with active, negative responses such as anger and hostility), general cognitive ability, and language ability, which were associated with conduct problems reported by parents, teachers, and adolescents, and change in observed negative emotionality (i.e., frustration tolerance), which was associated with conduct problems reported by teachers and adolescents. Furthermore, associations between the most robust early predictors and later conduct problems were influenced by the shared environment rather than genes. We conclude that shared environmental influences that promote disregard for others and detract from cognitive and language development during toddlerhood also predispose individuals to conduct problems in later childhood and adolescence. The identification of those shared environmental influences common to early antisocial propensity and later conduct problems is an important future direction, and additional developmental behavior genetic studies examining the interaction between children's characteristics and socializing influences on conduct problems are needed. (PsycINFO Database Record

Extending the 'cross-disorder' relevance of executive functions to dimensional neuropsychiatric traits in youth

BACKGROUND

Evidence that different neuropsychiatric conditions share genetic liability has increased interest in phenotypes with 'cross-disorder' relevance, as they may contribute to revised models of psychopathology. Cognition is a promising construct for study; yet, evidence that the same cognitive functions are impaired across different forms of psychopathology comes primarily from separate studies of individual categorical diagnoses versus controls. Given growing support for dimensional models that cut across traditional diagnostic boundaries, we aimed to determine, within a single cohort, whether performance on measures of executive functions (EFs) predicted dimensions of different psychopathological conditions known to share genetic liability.

METHODS

Data are from 393 participants, ages 8-17, consecutively enrolled in the Longitudinal Study of Genetic Influences on Cognition (LOGIC). This project is conducting deep phenotyping and genomic analyses in youth referred for neuropsychiatric evaluation. Using structural equation modeling, we examined whether EFs predicted variation in core dimensions of the autism spectrum disorder, bipolar illness, and schizophrenia (including social responsiveness, mania/emotion regulation, and positive symptoms of psychosis, respectively).

RESULTS

We modeled three cognitive factors (working memory, shifting, and executive processing speed) that loaded on a second-order EF factor. The EF factor predicted variation in our three target traits, but not in a negative control (somatization). Moreover, this EF factor was primarily associated with the overlapping (rather than unique) variance across the three outcome measures, suggesting that it related to a general increase in psychopathology symptoms across those dimensions.

CONCLUSIONS

Findings extend support for the relevance of cognition to neuropsychiatric conditions that share underlying genetic risk. They suggest that higher-order cognition, including EFs, relates to the dimensional spectrum of each of these disorders and not just the clinical diagnoses. Moreover, results have implications for bottom-up models linking genes, cognition, and a general psychopathology liability.

Thinking About Data, Research Methods, and Statistical Analyses: Commentary on Sijtsma's (2014) "Playing with Data"

We comment on Sijtsma's (2014) thought-provoking essay on how to minimize questionable research practices (QRPs) in psychology. We agree with Sijtsma that proactive measures to decrease the risk of QRPs will ultimately be more productive than efforts to target individual researchers and their work. In particular, we concur that encouraging researchers to make their data and research materials public is the best institutional antidote against QRPs, although we are concerned that Sijtsma's proposal to delegate more responsibility to statistical and methodological consultants could inadvertently reinforce the dichotomy between the substantive and statistical aspects of research. We also discuss sources of false-positive findings and replication failures in psychological research, and outline potential remedies for these problems. We conclude that replicability is the best metric of the minimization of QRPs and their adverse effects on psychological research.

A common oxytocin receptor gene (OXTR) polymorphism modulates intranasal oxytocin effects on the neural response to social cooperation in humans

Intranasal oxytocin (OT) can modulate social-emotional functioning and related brain activity in humans. Consequently, OT has been discussed as a potential treatment for psychiatric disorders involving social behavioral deficits. However, OT effects are often heterogeneous across individuals. Here we explore individual differences in OT effects on the neural response to social cooperation as a function of the rs53576 polymorphism of the oxytocin receptor gene (OXTR). Previously, we conducted a double-blind, placebo-controlled study in which healthy men and women were randomized to treatment with intranasal OT or placebo. Afterwards, they were imaged with functional magnetic resonance imaging while playing an iterated Prisoner's Dilemma Game with same-sex partners. Within the left ventral caudate nucleus, intranasal OT treatment increased activation to reciprocated cooperation in men, but tended to decrease activation in women. Here, we show that these sex differences in OT effects are specific to individuals with the rs53576 GG genotype, and are not found for other genotypes (rs53576 AA/AG). Thus, OT may increase the reward or salience of positive social interactions for male GG homozygotes, while decreasing those processes for female GG homozygotes. These results suggest that rs53576 genotype is an important variable to consider in future investigations of the clinical efficacy of intranasal OT treatment.

Fifty psychological and psychiatric terms to avoid: a list of inaccurate, misleading, misused, ambiguous, and logically confused words and phrases

The goal of this article is to promote clear thinking and clear writing among students and teachers of psychological science by curbing terminological misinformation and confusion. To this end, we present a provisional list of 50 commonly used terms in psychology, psychiatry, and allied fields that should be avoided, or at most used sparingly and with explicit caveats. We provide corrective information for students, instructors, and researchers regarding these terms, which we organize for expository purposes into five categories: inaccurate or misleading terms, frequently misused terms, ambiguous terms, oxymorons, and pleonasms. For each term, we (a) explain why it is problematic, (b) delineate one or more examples of its misuse, and (c) when pertinent, offer recommendations for preferable terms. By being more judicious in their use of terminology, psychologists and psychiatrists can foster clearer thinking in their students and the field at large regarding mental phenomena.

Child abuse, disruptive behavior disorders, depression, and salivary cortisol levels among institutionalized and community-residing boys in Mongolia

INTRODUCTION

Hypothalamic-pituitary-adrenal (HPA) axis activity is related to childhood disruptive behavior disorders and to exposure to abuse and neglect. This study explores the relationship of diurnal salivary cortisol levels with oppositional defiant disorder (ODD) and caregiver attitudes toward physical punishment among boys in Mongolia.

METHODS

Salivary cortisol was collected in the home or institution 4 times daily for 4 days from 46 boys, aged 4-10 years, in Ulaanbaatar, Mongolia. Caregivers rated child disruptive behavior symptoms, attitudes toward physical punishment, and community violence exposures. Mixed effects models were used to estimate the association of psychopathology and caregiver attitudes with salivary cortisol levels.

RESULTS

Boys meeting criteria for ODD displayed consistently lower diurnal salivary cortisol levels compared to boys without ODD diagnoses. Controlling for ODD diagnosis, boys with depression showed higher cortisol levels throughout the day. No other diagnosis was associated with cortisol levels. Psychiatric diagnosis accounted for 17% of between individual variations in cortisol levels unexplained by the covariates. In a separate model, caregivers' beliefs regarding physical punishment accounted for 11% of between individual differences: boys with caregivers who stated physical punishment was necessary for discipline displayed hypocortisolism. Institutionalization did not associate with cortisol levels.

DISCUSSION

Salivary cortisol data from a non-Western naturalistic setting support an association of reduced basal HPA activity with disruptive behavior disorders and caregiver attitudes toward discipline. These findings suggest HPA functioning may be a reflection of or mediate disruptive behavior disorders in children across ethnic and cultural settings.

Comorbidity Among Dimensions of Childhood Psychopathology: Converging Evidence from Behavior Genetics

In this article, we review evidence from recent behavior genetic studies that examined the covariance among common childhood psychopathological conditions and tested specific hypotheses regarding common and broadband-specific underlying features of childhood psychopathology. Specifically, we review the distinction between internalizing and externalizing disorders, the support for the generalist genes and specialist environments model, negative emotionality as a heritable underlying feature common to both internalizing and externalizing disorders, and daring as a heritable broadband-specific underlying feature that distinguishes externalizing disorders from internalizing disorders. We also discuss the implications of research in the search for specific genes that influence childhood psychopathology and suggest avenues for new research.

Identifying the irritability dimension of ODD: Application of a modified bifactor model across five large community samples of children

The importance of irritability, as measured among the symptoms of oppositional defiant disorder (ODD), has dramatically come to the fore in recent years. New diagnostic categories rely on the distinct clinical utility of irritability, and models of psychopathology suggest it plays a key role in explaining developmental pathways within and between disorders into adulthood. However, only a few studies have tested multidimensional models of ODD, and the results have been conflicting. Further, consensus has not been reached regarding which symptoms best identify irritability. The present analyses use 5 large community data sets with 5 different measures of parent-reported ODD, comprising 16,280 youth in total, to help resolve these questions. Across the samples, ages ranged from 5 to 18, and included both boys and girls. Confirmatory factor analyses demonstrated that a modified bifactor model showed the best fit in each data set. The structure of the model included 2 correlated specific factors (irritability and oppositional behavior) in addition to a general ODD factor. In 4 models, the best fit was obtained using the items "being touchy," "angry," and "often losing temper" as indicators of irritability. Given the structure of the models and the generally high correlation between the specific dimensions, the results suggest that irritability may not be sufficiently distinct from oppositional behavior to support an entirely independent diagnosis. Rather, irritability may be better understood as a dimension of psychopathology that can be distinguished within ODD, and which may be related to particular forms of psychopathology apart from ODD.