Perinatal and neonatal factors and mental disorders in children and adolescents: looking for the contributions of the early environment to common and dissociable aspects of psychopathology

High rates of co-occurrence of mental disorders have been hypothesized to represent a result of common susceptibility to overall psychopathology. The purpose of this study is to test the hypothesis that commonalities among psychiatric disorders might be partially driven by sharable perinatal and neonatal environmental factors for mental disorders. Participants were 6-14 years of age children and their parents. Primary caregivers provided data on perinatal and neonatal information assessed retrospectively (n = 2231). Psychiatric disorders diagnoses were assessed using the Development and Well Being Behavior Assessment (DAWBA). We used bifactor models to disentangle common from dissociable aspects of psychopathology. These models allow modeling psychiatric disorders as the result of a common domain of psychopathology (p-factor) and three dissociable domains (fear, distress, and externalizing symptoms). Associations were tested using linear and tobit regression models. The p-factor was associated with male sex, low socioeconomic status, gestational smoking, gestational drinking, low levels of maternal education and presence of mental disorder in the mother. Associations with specific factors also emerged suggesting some risk factors might also have some role for fear, distress and externalizing factors. Our study supports the hypothesis that overall susceptibility to psychopathology might be partially driven by sharable perinatal and neonatal factors.

Unpacking the p-factor. Associations Between Maladaptive Personality Traits and General Psychopathology in Female and Male Adolescents

Adolescence is a period of rapid physical, psychological, and neural maturation that makes youth vulnerable to emerging psychopathology, highlighting the need for improved identification of psychopathology risk indicators. Recently, a higher-order latent psychopathology factor (p-factor) was identified that explains latent liability for psychopathology beyond internalizing and externalizing difficulties. However, recent proposals suggest reconceptualizing the p-factor model in terms of impairments in personality encompassing difficulties in both self-regulation (borderline features) and self-esteem (narcissistic features), but this remains untested. To address this, this study examined the p-factor structure and the contribution of borderline and narcissistic features using two cross-sectional data collections. In Study 1, 974 cisgender adolescents (63% assigned females at birth; age range: 13-19; Mage = 16.68, SD = 1.40) reported on internalizing and externalizing problems (YSR) to test via structural equation models (SEM) different theoretical models for adolescent psychopathology. In Study 2, 725 cisgender adolescents (64.5% assigned females at birth; age range: 13-19; Mage = 16.22, SD = 1.32) reported internalizing and externalizing problems (YSR), borderline personality features (BPFSC-11), and narcissistic personality traits (PNI), to explore, via SEM, the contribution of borderline and narcissistic traits to the p-factor and accounting for gender differences. Results confirmed the utility of a bi-factor model in adolescence. Furthermore, findings highlighted the contribution of borderline features and narcissistic vulnerability to general psychopathology. The study provides the first evidence supporting a p-factor model reconceptualized in terms of personality impairments encompassing difficulties in self-regulation and self-esteem in adolescents.

An Evaluation of Item Harmonization Strategies Between Assessment Tools of Psychopathology in Children and Adolescents

Data aggregation in mental health is complicated by using different questionnaires, and little is known about the impact of item harmonization strategies on measurement precision. Therefore, we aimed to assess the impact of various item harmonization strategies for a target and proxy questionnaire using correlated and bifactor models. Data were obtained from the Brazilian High-Risk Study for Mental Conditions (BHRCS) and the Healthy Brain Network (HBN; N = 6,140, ages 5-22 years, 39.6% females). We tested six item-wise harmonization strategies and compared them based on several indices. The one-by-one (1:1) expert-based semantic item harmonization presented the best strategy as it was the only that resulted in scalar-invariant models for both samples and factor models. The between-questionnaires factor correlation, reliability, and factor score difference in using a proxy instead of a target measure improved little when all other harmonization strategies were compared with a completely at-random strategy. However, for bifactor models, between-questionnaire specific factor correlation increased from 0.05-0.19 (random item harmonization) to 0.43-0.60 (expert-based 1:1 semantic harmonization) in BHRCS and HBN samples, respectively. Therefore, item harmonization strategies are relevant for specific factors from bifactor models and had little impact on p-factors and first-order correlated factors when the child behavior checklist (CBCL) and strengths and difficulties questionnaire (SDQ) were harmonized.

The general psychopathology factor (p) from adolescence to adulthood: Exploring the developmental trajectories of p using a multi-method approach

Considerable attention has been directed towards studying co-occurring psychopathology through the lens of a general factor (p-factor). However, the developmental trajectory and stability of the p-factor have yet to be fully understood. The present study examined the explanatory power of dynamic mutualism theory - an alternative framework that suggests the p-factor is a product of lower-level symptom interactions that strengthen throughout development. Data were drawn from a population-based sample of girls (N = 2450) who reported on the severity of internalizing and externalizing problems each year from age 14 to age 21. Predictions of dynamic mutualism were tested using three distinct complementary statistical approaches including: longitudinal bifactor models, random-intercept cross-lagged panel models (RI-CLPMs), and network models. Across methods, study results document preliminary support for mutualistic processes in the development of co-occurring psychopathology (that is captured in p). Findings emphasize the importance of exploring alternative frameworks and methods for better understanding the p-factor and its development.

Harmonizing bifactor models of psychopathology between distinct assessment instruments: Reliability, measurement invariance, and authenticity

OBJECTIVES

Model configuration is important for mental health data harmonization. We provide a method to investigate the performance of different bifactor model configurations to harmonize different instruments.

METHODS

We used data from six samples from the Reproducible Brain Charts initiative (N = 8,606, ages 5-22 years, 41.0% females). We harmonized items from two psychopathology instruments, Child Behavior Checklist (CBCL) and GOASSESS, based on semantic content. We estimated bifactor models using confirmatory factor analysis, and calculated their model fit, factor reliability, between-instrument invariance, and authenticity (i.e., the correlation and factor score difference between the harmonized and original models).

RESULTS

Five out of 12 model configurations presented acceptable fit and were instrument-invariant. Correlations between the harmonized factor scores and the original full-item models were high for the p-factor (>0.89) and small to moderate (0.12-0.81) for the specific factors. 6.3%-50.9% of participants presented factor score differences between harmonized and original models higher than 0.5 z-score.

CONCLUSIONS

The CBCL-GOASSESS harmonization indicates that few models provide reliable specific factors and are instrument-invariant. Moreover, authenticity was high for the p-factor and moderate for specific factors. Future studies can use this framework to examine the impact of harmonizing instruments in psychiatric research.

The developmental interplay between the p-factor of psychopathology and the g-factor of intelligence from age 7 through 16 years

Intelligence and mental health are the core pillars of individual adaptation, growth, and opportunity. Here, we charted across childhood and adolescence the developmental interplay between the p-factor of psychopathology, which captures the experience of symptoms across the spectrum of psychiatric disorders, and the g-factor of general intelligence that describes the ability to think, reason, and learn.Our preregistered analyses included 7,433 twin pairs from the Twins Early Development Study (TEDS), who were born 1994 to 1996 in England and Wales. At the ages 7, 9, 12, and 16 years, the twins completed two to four intelligence tests, and multi-informant measures (i.e., self-, parent- and teacher-rated) of psychopathology were collected.Independent of their cross-sectional correlations, p- and g-factors were linked by consistent, bidirectional, and negative cross-lagged paths across childhood and adolescence (from -.07 to -.13 with 95% CIs from -.03 to -.15). The cross-lagged paths from intelligence to psychopathology were largely due to genetic influences, but the paths from psychopathology to intelligence were driven by environmental factors, and increasingly so with age.Our findings suggest that intelligence and psychopathology are developmentally intertwined due to fluctuating etiological processes. Understanding the interplay of g- and p-factors is key for improving children's developmental outcomes.

Defining the p-factor: an empirical test of five leading theories

BACKGROUND

Despite statistical evidence of a general factor of psychopathology (i.e., p-factor), there is little agreement about what the p-factor represents. Researchers have proposed five theories: dispositional negative emotionality (neuroticism), impulsive responsivity to emotions (impulsivity), thought dysfunction, low cognitive functioning, and impairment. These theories have primarily been inferred from patterns of loadings of diagnoses on p-factors with different sets of diagnoses included in different studies. Researchers who have directly examined these theories of p have examined a subset of the theories in any single sample, limiting the ability to compare the size of their associations with a p-factor.

METHODS

In a sample of adults (N = 1833, Mage = 34.20, 54.4% female, 53.3% white) who completed diagnostic assessments, self-report measures, and cognitive tests, we evaluated statistical p-factor structures across modeling approaches and compared the strength of associations among the p-factor and indicators of each of these five theories.

RESULTS

We found consistent evidence of the p-factor's unidimensionality across one-factor and bifactor models. The p-factor was most strongly and similarly associated with neuroticism (r = .88), impairment (r = .88), and impulsivity (r = .87), χ2(1)s < .15, ps > .70, and less strongly associated with thought dysfunction (r = .78), χ2(1)s > 3.92, ps < .05, and cognitive functioning (r = -.25), χ2(1)s > 189.56, ps < .01.

CONCLUSIONS

We discuss a tripartite definition of p that involves the transaction of impulsive responses to frequent negative emotions leading to impairment that extends and synthesizes previous theories of psychopathology.

Parent- and teacher-reported associations from adolescent bifactor models of psychopathology: an outcome-wide association study of 26 outcomes in mid-life

BACKGROUND

Adolescent mental health problems have lasting impacts on health and social functioning later in life. Evidence to date mostly comes from studies of specific diagnostic categories/dimensions, but hierarchical models can elucidate associations with general as well as specific dimensions of psychopathology. We provide evidence on long-term outcomes of general and specific dimensions of adolescent psychopathology using both parent and teacher reports.

METHODS

Parents and teachers from the Isle of Wight study completed Rutter behaviour scales when participants were 14-15 years old (n = 2,275), assessing conduct, emotional and hyperactivity problems. Metric-invariant bifactor models for parents and teachers were used to test domain-specific and domain-general associations with 26 self-reported psychosocial outcomes at mid-life (age 44-45 years, n = 1,423). Analyses examined the individual and joint contributions of parent and teacher reports of adolescent psychopathology. All analyses were adjusted for covariates (gender, IQ and family social class) and weighted to adjust for the probability of nonresponse.

RESULTS

Parent- and teacher-reported general factors of psychopathology (GFP) were associated with 15 and 12 outcomes, respectively, across the socioeconomic, relationship, health and personality domains, along with an index of social exclusion. Nine outcomes were associated with both parent- and teacher-reported GFP, with no differences in the strength of the associations across reporters. Teacher-reported specific factors (conduct, emotional and hyperactivity) were associated with 21 outcomes, and parent-reported specific factors were associated with seven. Five outcomes were associated with the same specific factors from both reporters; only one showed reporter differences in the strength of the associations.

CONCLUSIONS

These findings confirm the relevance of the GFP and the utility of teacher as well as parent reports of adolescent mental health in predicting psychosocial outcomes later in the life course.

General psychopathology factor (p-factor) prediction using resting-state functional connectivity and a scanner-generalization neural network

The general psychopathology factor (p-factor) represents shared variance across mental disorders based on psychopathologic symptoms. The Adolescent Brain Cognitive Development (ABCD) Study offers an unprecedented opportunity to investigate functional networks (FNs) from functional magnetic resonance imaging (fMRI) associated with the psychopathology of an adolescent cohort (n > 10,000). However, the heterogeneities associated with the use of multiple sites and multiple scanners in the ABCD Study need to be overcome to improve the prediction of the p-factor using fMRI. We proposed a scanner-generalization neural network (SGNN) to predict the individual p-factor by systematically reducing the scanner effect for resting-state functional connectivity (RSFC). We included 6905 adolescents from 18 sites whose fMRI data were collected using either Siemens or GE scanners. The p-factor was estimated based on the Child Behavior Checklist (CBCL) scores available in the ABCD study using exploratory factor analysis. We evaluated the Pearson's correlation coefficients (CCs) for p-factor prediction via leave-one/two-site-out cross-validation (LOSOCV/LTSOCV) and identified important FNs from the weight features (WFs) of the SGNN. The CCs were higher for the SGNN than for alternative models when using both LOSOCV (0.1631 ± 0.0673 for the SGNN vs. 0.1497 ± 0.0710 for kernel ridge regression [KRR]; p < 0.05 from a two-tailed paired t-test) and LTSOCV (0.1469 ± 0.0381 for the SGNN vs. 0.1394 ± 0.0359 for KRR; p = 0.01). It was found that (a) the default-mode and dorsal attention FNs were important for p-factor prediction, and (b) the intra-visual FN was important for scanner generalization. We demonstrated the efficacy of our novel SGNN model for p-factor prediction while simultaneously eliminating scanner-related confounding effects for RSFC.

Neurocognitive Artificial Neural Network Models Are Superior to Linear Models at Accounting for Dimensional Psychopathology

In recent years, there has been debate about the optimal conceptualisation of psychopathology. Structural models of psychopathology have been developed to counter issues, including comorbidity and poor diagnostic stability prevalent within the traditional nosological approach. Regardless of the conceptualisation of psychological dysfunction, deficits in neurocognitive abilities have been claimed to be an aetiological feature of psychopathology. Explorations of the association between neurocognition and psychopathology have typically taken a linear approach, overlooking the potential interactive dynamics of neurocognitive abilities. Previously, we proposed a multidimensional hypothesis, where within-person interactions between neurocognitive domains are fundamental to understanding the role of neurocognition within psychopathology. In this study, we used previously collected psychopathology data for 400 participants on psychopathological symptoms, substance use, and performance on eight neurocognitive tasks and compared the predictive accuracy of linear models to artificial neural network models. The artificial neural network models were significantly more accurate than the traditional linear models at predicting actual (a) lower-level and (b) high-level dimensional psychopathology. These results provide support for the multidimensional hypothesis: that the study of non-linear interactions and compensatory neurocognitive profiles are integral to understanding the functional associations between neurocognition and of psychopathology.

Identifying Youth at Risk for Suicidal Thoughts and Behaviors Using the "p" factor in Primary Care: An Exploratory Study

Suicide is a major, preventable public health problem. The general factor of psychopathology ("p" factor) might help improve detection and prediction of individuals at risk for suicide. This cross-sectional proof-of-concept study tests whether the p-factor score is associated with suicidal thoughts and behaviors (STB) better than a depression scale alone. Youth (N = 841; mean age 18.02, SD = 3.36) in primary care were universally screened using the Behavioral Health Screen (BHS). Factor analysis and ROC results showed the BHS assesses the p-factor, and the p-factor score demonstrates higher classification accuracy of several types of STB than a depression scale. The p-factor could help clinicians in the identification of youths with STB.

How Robust Is the p Factor? Using Multitrait-Multimethod Modeling to Inform the Meaning of General Factors of Youth Psychopathology

We used multitrait-multimethod (MTMM) modeling to examine general factors of psychopathology in three samples of youth (Ns = 2119, 303, 592) for whom three informants reported on the youth's psychopathology (e.g., child, parent, teacher). Empirical support for the p-factor diminished in multi-informant models compared with mono-informant models: the correlation between externalizing and internalizing factors decreased and the general factor in bifactor models essentially reflected externalizing. Widely used MTMM-informed approaches for modeling multi-informant data cannot distinguish between competing interpretations of the patterns of effects we observed, including that the p-factor reflects, in part, evaluative consistency bias or that psychopathology manifests differently across contexts (e.g., home vs. school). Ultimately, support for the p-factor may be stronger in mono-informant designs, although it is does not entirely vanish in multi-informant models. Instead, the general factor of psychopathology in any given mono-informant model likely reflects a complex mix of variances, some substantive and some methodological.

Diagnosis on the way out - personality on the way in? Priorities in treatment in child and adolescent psychiatry

The scientific basis for practice in child psychiatry has developed apace. And has thrown up several quandries for an accepted paradigm for good practice anchored to the diagnostic schema developed in adult psychiatry. This paper hopes to stimulate discussion about where alternative paradigms might lead us on a path to precision medicine as applied to child psychiatry.

Maternal Depressive Symptoms Predict General Liability in Child Psychopathology

Objective: The current study examines how maternal depressive symptoms relate to child psychopathology when structured via the latent bifactor model of psychopathology, a new organizational structure of psychopathological symptoms consisting of a general common psychopathology factor (p-factor) and internalizing- and externalizing-specific risk.Method: Maternal report of depressive symptoms (Beck Depression Inventory - II) and child psychopathological symptoms (Child Behavior Checklist and Children's Behavior Questionnaire) were provided by 554 mother-child pairs. Children in the sample were 7.7 years old on average (SD = 1.35, range = 5-11 years), and were 49.8% female, 46% Latinx, and 67% White, 6% Black, 5% Asian/Pacific Islander, and 21% multiracial.Results: Maternal depressive symptoms were positively associated with the child p-factor but not with the internalizing- or externalizing-specific factors. We did not find evidence of sex/gender or race/ethnicity moderation when using latent factors of psychopathology. Consistent with past research, maternal depressive symptoms were positively associated with internalizing and externalizing composite scores on the Child Behavior Checklist.Conclusions: Findings suggest that maternal depressive symptoms are associated with transdiagnostic risk for broad child psychopathology (p-factor). Whereas the traditional Achenbach-style approach of psychopathological assessment suggests that maternal depressive symptoms are associated with both child internalizing and externalizing problems, the latent bifactor model suggests that these associations may be accounted for by risk pathways related to the p-factor rather than internalizing or externalizing specific risk. We discuss clinical and research implications of using a latent bifactor structure of psychopathology to understand how maternal depression may impact children's mental health.

Investigating the molecular genetic, genomic, brain structural, and brain functional correlates of latent transdiagnostic dimensions of psychopathology across the lifespan: Protocol for a systematic review and meta-analysis of cross-sectional and longitudinal studies in the general population

BACKGROUND

Research using latent variable modelling has identified a superordinate general dimension of psychopathology, as well as several specific/lower-order transdiagnostic dimensions (e.g., internalising and externalising) within the meta-structure of psychiatric symptoms. These models can facilitate discovery in genetic and neuroscientific research by providing empirically derived psychiatric phenotypes, offering greater validity and reliability than traditional diagnostic categories. The prospective review outlined in this protocol aims to integrate and assess evidence from research investigating the biological correlates of general psychopathology and specific/lower-order transdiagnostic symptom dimensions. Cross-sectional and longitudinal studies investigating general population samples of any age group or developmental period will be included to capture evidence from across the lifespan.

METHODS AND ANALYSIS

MEDLINE, Embase, and PsycINFO databases will be systematically searched for relevant literature. The review will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Eligibility criteria were designed to capture psychiatric genetic (i.e., molecular genetic and genomic) and neuroimaging (i.e., brain structural and brain functional) studies investigating latent transdiagnostic dimension(s) or structural model(s) of psychopathology across any age group. Studies which include or exclude participants based on clinical symptoms, disorders, or relevant risk factors (e.g., history of abuse, neglect, and trauma) will be excluded. Biometric genetic research (e.g., twin and family studies), candidate gene studies, neurophysiology studies, and other non-imaging based neuroscientific studies (e.g., post-mortem studies) will be excluded. Study quality and risk of bias will be assessed using the Joanna Briggs Checklist for Analytical Cross-Sectional Studies, the Joanna Briggs Checklist for Cohort Studies, and the Grades of Recommendation, Assessment, Development, and Evaluation (GRADE) system. Meta-analysis will be conducted if sufficient data is available.

DISCUSSION

This protocol outlines the first systematic review to examine evidence from studies investigating the latent structure and underlying biology of psychopathology and to characterise these relationships developmentally across the lifespan. The prospective review will cover a broad range of statistical techniques and models used to investigate latent transdiagnostic dimensions of psychopathology, as well as a numerous genetic and neuroscientific methods.

SYSTEMATIC REVIEW REGISTRATION

[https://www.crd.york.ac.uk/prospero/], identifier[CRD42021262717].

The structure of dimensions of psychopathology in normative and clinical samples: Applying causal discovery to MMPI-2-RF scales to investigate clustering of psychopathology spectra and p-factors

We applied a Bayesian Constraint-based Causal Discovery method (BCCD) to examine the hierarchical structure of the Minnesota Multiphasic Personality Inventory-2-Restructured Form (MMPI-2-RF) Restructured Clinical (RC) scales. Two different general psychopathology super spectra (p-factor) scales were extracted from (1) all RC scales and (2) all RC scales except the RCd (Demoralization) scale. These p-factor scales were included in separate models to investigate the structure of dimensions of psychopathology in a normative (n = 3,242) and clinical (n = 2,466) sample, as well as the combined normative/clinical sample (N = 5,708), by applying the BCCD algorithm to obtain a data-driven reconstruction of the internal hierarchical structure of the MMPI-2-RF. Research on the underlying structure of the MMPI-2-RF has clinical relevance as well as conceptual relevance in the context of the HiTOP model. Results demonstrated that the syndromes measured with the RC-scales-in presence of a p-factor-cluster into six spectra: internalizing, disinhibited-externalizing, antagonistic-externalizing, thought disorder, detachment, and somatoform. These results may support a super spectrum construct, as it was necessary for obtaining a bottom-up reconstruction of this six-spectrum structure. We found support for superiority of a broad super spectrum with additional variance over and above demoralization, as it resulted in the clearest structure (i.e., clustering of the RC scales). Furthermore, our results indicate independent support for the bifactor structure model of psychopathology.

Going "Up" to Move Forward: S-1 Bifactor Models and the Study of Neurocognitive Abilities in Psychopathology

Recently, structural models of psychopathology, that address the diagnostic stability and comorbidity issues of the traditional nosological approach, have dominated much of the psychopathology literature. Structural approaches have given rise to the p-factor, which is claimed to reflect an individual's propensity toward all common psychopathological symptoms. Neurocognitive abilities are argued to be important to the development and maintenance of a wide range of disorders, and have been suggested as an important driver of the p-factor. However, recent evidence argues against p being an interpretable substantive construct, limiting conclusions that can be drawn from associations between p, the specific factors of a psychopathology model, and neurocognitive abilities. Here, we argue for the use of the S-1 bifactor approach, where the general factor is defined by neurocognitive abilities, to explore the association between neurocognitive performance and a wide range of psychopathological symptoms. We use simulation techniques to give examples of how S-1 bifactor models can be used to examine this relationship, and how the results can be interpreted.

One p-Factor for All? Exploring the Applicability of Structural Models of Psychopathology within Subgroups of a Population

Structural models of psychopathology have emerged as an alternative to traditional categorical approaches. The bifactor model, which incorporates a general p-factor, has become the preferred structure. The p-factor is claimed to represent a substantive construct or property of the system; however, recent evidence suggests that it may be without substantive meaning. If a universal substantive p, and associated specific factors, is to be developed they not only must be applicable and consistent between populations but also must be applicable and consistent within subgroups of a population. This consistency needs to include not only factor loadings but also factor correlates. We used a simulated data approach to explore the applicability and consistency of four popular models of psychopathology to a range of heterogeneous subgroups and examined the consistency of their neurocognitive correlates. We found that only eight out of sixty-three subgroups fitted any of the models with all significant loadings, no negative loadings, no non-positive-definite identification issues, and no negative variance. All eight of these subgroups fit the correlated factors model, none fit the original bifactor model, four subgroups fit the revised bifactor model, and one subgroup fit the single-factor model. Correlates of the factors also varied substantially between the subgroups fitted to the same model. We discuss the implications of the findings, including the implications for the development of universal substantive factors of psychopathology.

The Habenula in the Link Between ADHD and Mood Disorder

Attention-deficit/hyperactivity disorder (ADHD) is a childhood-onset, neurodevelopmental disorder, whereas major depressive disorder (MDD) is a mood disorder that typically emerges in adulthood. Accumulating evidence suggests that these seemingly unrelated psychiatric disorders, whose symptoms even appear antithetical [e.g., psychomotor retardation in depression vs. hyperactivity (psychomotor acceleration) in ADHD], are in fact associated with each other. Thus, individuals with ADHD exhibit high comorbidity with MDD later in life. Moreover, genetic studies have shown substantial overlaps of susceptibility genes between ADHD and MDD. Here, we propose a novel and testable hypothesis that the habenula, the epithalamic brain region important for the regulation of monoamine transmission, may be involved in both ADHD and MDD. The hypothesis suggests that an initially hypoactive habenula during childhood in individuals with ADHD may undergo compensatory changes during development, priming the habenula to be hyperactive in response to stress exposure and thereby increasing vulnerability to MDD in adulthood. Moreover, we propose a new perspective on habenular deficits in psychiatric disorders that consider the habenula a neural substrate that could explain multiple psychiatric disorders.

Evaluating the Viability of Neurocognition as a Transdiagnostic Construct Using Both Latent Variable Models and Network Analysis

The relational structure of psychological symptoms and disorders is of crucial importance to mechanistic and causal research. Methodologically, factor analytic approaches (latent variable modeling) and network analyses are two dominant approaches. Amidst some debate about their relative merits, use of both methods simultaneously in the same data set has rarely been reported in child or adolescent psychopathology. A second issue is that the nosological structure can be enriched by inclusion of transdiagnostic constructs, such as neurocognition (e.g., executive functions and other processes). These cut across traditional diagnostic boundaries and are rarely included even though they can help map the mechanistic architecture of psychopathology. Using a sample enriched for ADHD (n = 498 youth ages 6 to 17 years; M = 10.8 years, SD = 2.3 years, 55% male), both approaches were used in two ways: (a) to model symptom structure and (b) to model seven neurocognitive domains hypothesized as important transdiagnostic features in ADHD and associated disorders. The structure of psychopathology domains was similar across statistical approaches with internalizing, externalizing, and neurocognitive performance clusters. Neurocognition remained a distinct domain according to both methods, showing small to moderate associations with internalizing and externalizing domains in latent variable models and high connectivity in network analyses. Overall, the latent variable and network approaches yielded more convergent than discriminant findings, suggesting that both may be complementary tools for evaluating the utility of transdiagnostic constructs for psychopathology research.

Associations Between Resting-State Functional Connectivity and a Hierarchical Dimensional Structure of Psychopathology in Middle Childhood

BACKGROUND

Previous research from the Adolescent Brain Cognitive Development (ABCD) Study delineated and validated a hierarchical 5-factor structure with a general psychopathology (p) factor at the apex and 5 specific factors (internalizing, somatoform, detachment, neurodevelopmental, externalizing) using parent-reported child symptoms. The present study is the first to examine associations between dimensions from a hierarchical structure and resting-state functional connectivity (RSFC) networks.

METHODS

Using 9- to 11-year-old children from the ABCD Study baseline sample, we examined the variance explained by each hierarchical structure level (p-factor, 2-factor, 3-factor, 4-factor, and 5-factor models) in associations with RSFC. Analyses were first conducted in a discovery dataset (n = 3790), and significant associations were examined in a replication dataset (n = 3791).

RESULTS

There were robust associations between the p-factor and lower connectivity within the default mode network, although stronger effects emerged for the neurodevelopmental factor. Neurodevelopmental impairments were also related to variation in RSFC networks associated with attention to internal states and external stimuli. Analyses revealed robust associations between the neurodevelopmental dimension and several RSFC metrics, including within the default mode network, between the default mode network with cingulo-opercular and "Other" (unassigned) networks, and between the dorsal attention network with the Other network.

CONCLUSIONS

The hierarchical structure of psychopathology showed replicable links to RSFC associations in middle childhood. The specific neurodevelopmental dimension showed robust associations with multiple RSFC metrics. These results show the utility of examining associations between intrinsic brain architecture and specific dimensions of psychopathology, revealing associations especially with neurodevelopmental impairments.

GWAS SNPs Impact Shared Regulatory Pathways Amongst Multimorbid Psychiatric Disorders and Cognitive Functioning

Background: Epidemiological research has reported that attention-deficit hyperactivity disorder (ADHD), anxiety, bipolar disorder (BD), schizophrenia (SCZ), and unipolar depression (UD) are multimorbid conditions that are typically accompanied by cognitive advantages or deficits, suggesting that common biological mechanisms may underlie these phenotypes. Genome-wide association studies (GWAS) have identified single-nucleotide polymorphisms (SNPs) associated with psychiatric disorders and cognitive functioning. However, the mechanisms by which these SNPs contribute to multimorbidities amongst psychiatric and cognitive phenotypes remains largely unknown. Objective: To identify shared regulatory mechanisms amongst multimorbid psychiatric disorders and cognitive functioning. Methods: We integrated data on 3D genome organization, expression quantitative trait loci (eQTLs), and pathway analyses to identify shared and specific regulatory impacts of 2,893 GWAS SNPs (p < 1 × 10^-6) associated with ADHD, anxiety, BD, SCZ, UD, and cognitive functioning on genes and biological pathways. Drug-gene interaction analysis was performed to identify potential pharmacological impacts on these genes and pathways. Results: The analysis revealed 33 genes and 62 pathways that were commonly affected by tissue-specific gene regulatory interactions associated with all six phenotypes despite there being no common SNPs in our original dataset. The analysis of brain-specific regulatory connections revealed similar patterns at eQTL and eGene levels, but no pathways shared by all six phenotypes. Instead, pairwise overlaps and individualized pathways were identified for psychiatric and cognitive phenotypes in brain tissues. Conclusions: This study offers insight into the shared genes and biological pathways that are affected by tissue-specific regulatory impacts resulting from psychiatric- and cognition-associated genetic variants. These results provide limited support for the "p-factor" hypothesis for psychiatric disorders and potential mechanisms that explain drug side-effects. Our results highlight key biological pathways for development of therapies that target single or multiple psychiatric and cognitive phenotypes.

Using Genetics to Examine a General Liability to Childhood Psychopathology

Psychiatric disorders show phenotypic as well as genetic overlaps. There are however also marked developmental changes throughout childhood. We investigated the extent to which, for a full range of early childhood psychopathology, a general “p” factor was explained by genetic liability, as indexed by multiple different psychiatric polygenic risk scores (PRS) and whether these relationships altered with age. The sample was a UK, prospective, population-based cohort with psychopathology data at age 7 (N = 8161) and age 13 (N = 7017). PRS were generated from large published genome-wide association studies. At both ages, we found evidence for a childhood “p” factor as well as for specific factors. Schizophrenia and attention-deficit/hyperactivity disorder (ADHD) PRS were associated with this general “p” factor at both ages but depression and autism spectrum disorder (ASD) PRS were not. We also found some evidence of associations between schizophrenia, ADHD and depression PRS with specific factors, but these were less robust and there was evidence for developmental changes.

Heterotypic trajectories of dimensional psychopathology across the lifespan: the case of youth-onset attention deficit/hyperactivity disorder

BACKGROUND

Recent studies have demonstrated the existence of a distinct late-onset attention deficit/hyperactivity disorder (ADHD) trajectory. Our objective is to test if there are distinct ADHD trajectories regarding age of onset from childhood to adolescence and to compare clinical manifestations, cognitive functions and genetic risk for ADHD among distinct longitudinal groups.

METHOD

Nine hundred and twenty four children and adolescents from the community participated in the study. We compared clinical, cognitive features and genetic risk among four groups of participants: (a) childhood-limited, (b) youth-onset, (c) childhood-onset with youth persistence, and (d) community comparisons without ADHD. Symptomatic and diagnostic assessments were performed using the Development and Well-Being Behavior Assessment, the Strengths and Difficulties Questionnaire, and the Child Behavior Checklist. Cognitive functions were measured using a battery of standardized tests. Genetic risk for ADHD was calculating using summary statistics from the Psychiatric Genomics Consortium.

RESULTS

Half of the adolescents (52%) with ADHD had their symptom onset in adolescence. The impairment level of this group in adolescence is similar to the persistent group. Despite not having ADHD, the youth-onset group already presented in childhood more symptoms from other domains of psychopathology, higher shared variance in psychiatric symptomatology (p-factor), school impairment, and executive dysfunctions than community comparisons. Furthermore, the youth-onset group presented lower levels of genetic risk for ADHD compared to other cases.

CONCLUSIONS

A significant proportion of adolescents with ADHD were youth-onset cases and presented similar impairment levels as those cases with early-onset ADHD. The presence of cognitive impairments and higher levels of clinical symptoms in the youth-onset group already at childhood speaks in favor of a heterotypic trajectory of psychopathology suggesting that youth-onset ADHD might be an artificial consequence of categorizing dimensional psychopathology into discrete diagnostic groups.

"P" and "DP:" Examining Symptom-Level Bifactor Models of Psychopathology and Dysregulation in Clinically Referred Children and Adolescents

OBJECTIVE

This study examined cross-informant evidence for a general factor of psychopathology ("P") and a narrower, clinically oriented dysregulation general factor based on the Dysregulation Profile ("DP") in a large clinical sample of children and adolescents. We also compared the magnitude of P and DP general factor associations with self-harm and suicidal ideation as an indicator of criterion validity.

METHOD

Itemwise data from the Child Behavior Checklist (N = 2,934; 4-18 years of age) were analyzed using confirmatory bifactor modeling and replicated in a supplementary analysis using Youth Self Report data (N = 2,395).

RESULTS

General P and DP bifactor models fit the data better than single-factor and correlated factor models. Cross-informant criterion analyses on a subset of youth (n = 1,552) suggested that whether modeled as latent P or DP, associations with a brief composite index of self-harm and suicidal ideation are essentially of the same magnitude.

CONCLUSION

Our findings provide novel, large-sample support for the existence of general factors of psychopathology and dysregulation in clinically referred children and adolescents using a standardized rating system of psychopathology symptoms. Moreover, our results provide preliminary evidence that general psychopathology and dysregulation factors are clinically meaningful constructs. In addition, our findings raise the possibility that the DP general factor may serve as an efficient proxy for the general psychopathology factor in future clinical applications. Further efforts are necessary to understand the core empirical meaning of the P factor and to determine how it can be applied to clinical assessment and intervention.

Criterion Validity and Utility of the General Factor of Psychopathology in Childhood: Predictive Associations With Independently Measured Severe Adverse Mental Health Outcomes in Adolescence

OBJECTIVE

We examined whether a parent-rated general factor of psychopathology in childhood would predict independently measured, severe adverse mental health outcomes in adolescence.

METHOD

We used the Child and Adolescent Twin Study in Sweden, which targets all twin children in Sweden. Parents rated their children (N = 16,806) on 43 symptoms of inattention, hyperactivity/impulsivity, conduct problems, and anxiety/emotionality when the twins turned 9 or 12 years of age. Adverse mental health outcomes in adolescence were retrieved from national registers, and included psychiatric diagnoses, prescription of anxiolytic or antidepressant medication, court convictions of crimes, and failure to achieve eligibility for high school.

RESULTS

Parent-rated inattention, hyperactivity/impulsivity, conduct problems, and anxiety/emotionality in childhood predicted all adverse mental health outcomes in adolescence (mean odds ratio = 1.76; range = 1.41-2.18; all p < .05). However, several of these associations were nonsignificant in a multiple regression framework, suggesting the influence of common variance. A general factor of psychopathology uniquely predicted all outcomes (mean odds ratio = 1.58; range = 1.34-1.84; all p < .05), whereas the specific factors predicted only a subset of the outcomes.

CONCLUSION

Mental health problems in childhood are associated with a host of adverse outcomes in adolescence, and, to a considerable extent, these associations are driven by a general factor of psychopathology. The general factor may therefore be important to clinical prognosis, which informs clinical decision making for children.

The Development of the General Factor of Psychopathology 'p Factor' Through Childhood and Adolescence

Recent studies have suggested that the structure of psychopathology may be usefully represented in terms of a general factor of psychopathology (p-factor) capturing variance common to a broad range of symptoms transcending diagnostic domains in addition to specific factors capturing variance common to smaller subsets of more closely related symptoms. Little is known about how the general co-morbidity captured by this p-factor develops and whether general co-morbidity increases or decreases over childhood and adolescence. We evaluated two competing hypotheses: 1) dynamic mutualism which predicts growth in general co-morbidity and associated p-factor strength over time and 2) p-differentiation which predicts that manifestations of liabilities towards psychopathology become increasingly specific over time. Data came from the Zurich Project on the Social Development of Children and Youths (z-proso), a longitudinal study of a normative sample (approx. 50 % male) measured at 8 time points from ages 7 to 15. We operationalised general co-morbidity as p-factor strength in a bi-factor model and used omega hierarchical to track how this changed over development. In contrast to the predictions of both dynamic mutualism and p-differentiation, p-factor strength remained relatively constant over the studied period suggesting that such processes do not govern the interplay between psychopathological symptoms during this phase of development. Future research should focus on earlier phases of development and on factors that maintain the consistency of symptom-general covariation across this period.

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