Co-occurrence of child and adolescent neurodevelopmental and mental health conditions is the rule rather than the exception, yet translating this insight into shared frameworks and clinical practice remains challenging. In this Editorial, we are pleased to introduce the 26 papers included in the 2026 Special Issue of JCPP Advances. This Special Issue aimed to advance our understanding of transdiagnostic mechanisms, dimensions, and practices in child and adolescent mental health, and includes original articles, reviews, commentaries, and an editorial perspective. Collectively, these articles illustrate three main 'transdiagnostic' conceptualisations; (i) mechanistic approaches identifying shared biological, cognitive, or affective processes across diagnostic boundaries; (ii) dimensional approaches mapping symptom covariance onto hierarchical structures such as the general 'p' factor and internalising, externalising, and neurodevelopmental spectra; and (iii) developmental, clinical-staging approaches treating early, non-specific features as precursors to a broad range of later outcomes. Methodologically, the current Special Issue highlights both the opportunities and limitations of large existing datasets, multi-informant assessment, and neuroimaging and genomic approaches, while underscoring the persistent difficulty of modelling transdiagnostic dimensions developmentally. Importantly, while translation into routine clinical care remains limited, the field is now well positioned to test the clinical utility and effectiveness of transdiagnostic dimensional assessments and interventions in routine care.

We investigate gene-environment interplay for the development of externalizing (EXT) behaviors in Add Health. Latent trajectories of substance use (SUB) and antisocial behaviors (ASB) spanning ages 13 to 41 were extracted in a prior study (Sasia et al., 2025). Adolescent psychosocial environments (i.e., supportive parenting, delinquent peer affiliation, school connectedness, and neighborhood connectedness) were modeled to moderate and mediate the effects of EXT polygenic scores (PGS) in predicting SUB and ASB trajectories in European (n = 5,025; main analyses), African (n = 1,728), Asian (n = 382), and Hispanic (n = 773) genetic similarity groups. There was no evidence of moderation effects. However, PGS effects operated indirectly through psychosocial environments, notably via delinquent peer affiliation. Despite the prominence of genetic effects underlying EXT, peer influences may play an especially important role in the ways in which genetic effects influence EXT trajectories. Clinical and theoretical implications are discussed.

Polygenic scores (PGS) are widely used in psychiatric genetic associations studies due to their predictive power for focal outcomes. However, they lack discriminatory power, in part due to the high degree of genetic overlap between psychiatric disorders. The lack of prediction specificity limits the clinical utility of psychiatric PGS, particularly for diagnostic applications. The goal of the study was to enhance the discriminatory power of psychiatric PGS for two highly comorbid and genetically correlated neurodevelopmental disorders in ADHD and autism spectrum disorder (ASD). Genomic structural equation modeling (GenomicSEM) was used to generate novel PGS for ADHD and ASD by accounting for the genetic overlap between these disorders (and eight others) to achieve greater discriminatory power in non-focal outcome predictions. PGS associations were tested in two large independent samples – the Philadelphia Neurodevelopmental Cohort (N = 4,789) and the Simons Foundation Powering Autism Research for Knowledge (SPARK) ASD and sibling controls (N = 5,045) cohort. PGS from GenomicSEM achieved superior discriminatory power in terms of showing significantly attenuated associations with non-focal outcomes relative to traditionally computed PGS for these disorders. Additionally, genetic correlations between GenomicSEM PGS for ASD and ADHD were significantly attenuated in cross-trait associations with other psychiatric disorders and outcomes. Psychiatric PGS associations are likely inflated by the high degree of genetic overlap between the psychiatric disorders. Methods such as GenomicSEM can be used to refine PGS signals to be more disorder-specific, thereby enhancing their discriminatory power for future diagnostic applications.

Introduction: Clinicians often determine an ‘expected body weight’ (EBW) for patients who have lost weight due to an eating disorder (ED). However, there is inconsistent guidance and limited empirical research on whether and when these weights should be shared with patients. This study explores clinician and patient perspectives on discussions of EBWs.Methods: Semi-structured interviews were conducted with 24 multidisciplinary clinicians treating EDs and 16 individuals with recent outpatient ED treatment experience (i.e., in the past 6 months). Clinicians shared their experiences with and rationales for sharing EBWs with patients and patients’ family members. Patients shared their experiences being informed of their EBWs in ED treatment, factors influencing their comfort level discussing EBWs with clinicians, and perceived impact of these discussions on their recovery. Interviews were analyzed using reflexive thematic analysis with a critical realist lens. Results: Clinician and patient perspectives aligned regarding when, how, and why to hold these discussions. Both groups emphasized that these discussions should occur after patients are medically stable and underscored the importance of framing the EBW as one aspect of a holistic recovery. Additionally, clinicians and patients highlighted the potential therapeutic benefits of these discussions, while also acknowledging challenges relating to parental involvement and weight bias. Discussion: Findings suggest that when discussions of EBWs are approached intentionally—accounting for timing, framing, and individual patient needs—clinicians and patients see potential therapeutic benefit. Future research can focus on developing evidence-based guidelines for sharing EBWs, addressing patient willingness to be informed of their EBW, weight bias, and parental involvement.

PURPOSE:To extend and automate a data-consistent, self-navigated motion-correction method for 3D radial T1-weighted imaging. METHODS:This method incorporated rigid-body motion effects into the forward model, solving for parameters that maximize consistency with the data. The method was tested on five datasets with a range of motion types and severities. A separate collection of datasets was used to study the effect that the method has on the test-retest reliability of cortical thickness estimates. RESULTS:Image quality was improved across a wide range of distinct motion types, including some cases that would have been unusable if left uncorrected. The error-based weighting scheme and the increased timing resolution afforded by the proposed method were especially useful in cases of extreme and rapid motions. Moreover, the method improved test-retest reliability of cortical thickness measures in pediatric subjects, decreasing the average coefficient of variation from 2 . 73 % ± 1 . 75 % $$ 2.73\%\pm 1.75\% $$ in uncorrected images (with freesurfer failing on one subject) down to 0 . 88 % ± 0 . 21 % $$ 0.88\%\pm 0.21\% $$ for images corrected at ∼ 2 s $$ \sim 2\kern0.3em \mathrm{s} $$ timing resolution and 0 . 79 % ± 0 . 16 % $$ 0.79\%\pm 0.16\% $$ when corrected at faster temporal rates. CONCLUSION:This method was found to be effective when used on T1-weighted radial data, both qualitatively and quantitatively. The fine-scale timing resolution and error-based weighting afforded by this technique will likely provide only a small benefit, unless one is investigating motion-prone populations or is searching for a very small effect size.

Quality of life (QoL) is important for everyone and has been identified as a priority for autistic people. However, studies typically focus on caregiver-proxy-reported QoL and its related individual characteristics, even though self- and caregiver-proxy-reported QoL may differ in autistic children. In 74 autistic children (5.04-10.99 years old, intelligence quotient [IQ] 47-141), we sought to determine the level of agreement between self- and caregiver-proxy-reported QoL and determine if self- and caregiver-proxy-reported QoL are differently related to personal characteristics such as age, IQ, autism features, attention-deficit/hyperactivity disorder (ADHD) features, sleep difficulties, and sensory features. Findings suggested poor inter-rater agreement (ICC = 0.16) between self- and caregiver-proxy-reported QoL. Across both self- and caregiver-proxy reports, sensory features and sleep difficulties related to QoL, but age and IQ did not. We also found an interaction effect of reporter on the relation between QoL and both autism and ADHD features, with these associations driven by caregiver-proxy-reported QoL. These findings emphasize the importance of measuring both self- and caregiver-proxy-reported QoL to provide complementary perspectives. Moreover, these results underscore the importance of understanding a child's sensory features and sleep difficulties, as these two areas were similarly related to both self- and caregiver-proxy-reported QoL.

The Hierarchical Taxonomy of Psychopathology (HiTOP) has gained significant traction in clinical psychological science. However, HiTOP has not been extensively validated across diverse populations. This study tested measurement invariance-the degree to which latent constructs are measured with equivalence across groups-in HiTOP across racial and ethnic groups using the Child Behavior Checklist (CBCL) in the Adolescent Brain Cognitive Development (ABCD) Study. These models were followed with rigorous tests of construct validation (i.e., convergent, discriminant, and concurrent) on the latent factors using a Multitrait-Multimethod (MTMM) framework. Comparing across non-Hispanic White (n = 7,166), Hispanic (n = 2,411), and non-Hispanic Black (n = 1,862) youths, the five-factor model comprising Externalizing, Neurodevelopmental, Internalizing, Somatoform, and Detachment factors demonstrated configural, metric, scalar, and strict measurement invariance. While each of the five factors demonstrated good evidence of concurrent and convergent validity, evidence for their discriminant validity was not as robust. Establishing measurement invariance and construct validity of the HiTOP model has critical scientific and clinical implications, particularly if dimensions are to be used in addressing mental health disparities in minoritized populations.

Polygenic scores (PGSs) have garnered increasing attention in the clinical sciences due to their robust prediction signals for psychopathology, including externalizing (EXT) behaviors. However, studies leveraging PGSs have rarely accounted for the phenotypic and developmental heterogeneity in EXT outcomes. We used the National Longitudinal Study of Adolescent to Adult Health (analytic N = 4,416), spanning ages 13 to 41, to examine associations between EXT PGSs and trajectories of antisocial behaviors (ASB) and substance use behaviors (SUB) identified via growth mixture modeling. Four trajectories of ASB were identified: High Decline (3.6% of the sample), Moderate (18.9%), Adolescence-Peaked (10.6%), and Low (67%), while three were identified for SUB: High Use (35.2%), Typical Use (41.7%), and Low Use (23%). EXT PGSs were consistently associated with persistent trajectories of ASB and SUB (High Decline and High Use, respectively), relative to comparison groups. EXT PGSs were also associated with the Low Use trajectory of SUB, relative to the comparison group. Results suggest PGSs may be sensitive to developmental typologies of EXT, where PGSs are more strongly predictive of chronicity in addition to (or possibly rather than) absolute severity.

BACKGROUND:Violence exposure during childhood and adolescence is associated with increased prevalence and severity of psychopathology. Neurobiological correlates suggest that abnormal maturation of emotion-related brain circuitry, such as the amygdala-prefrontal cortex (PFC) circuit, may underlie the development of psychiatric symptoms after exposure. However, it remains unclear how amygdala-PFC circuit maturation is related to psychiatric risk in the context of violence. METHODS:In this study, we analyzed individual differences in amygdala-PFC circuit maturity using data collected from the PNC (Philadelphia Neurodevelopmental Cohort) (n = 1133 youths). Neurodevelopment models of amygdala-PFC resting-state functional connectivity were built using deep learning and trained to predict chronological age in typically developing youths (not violence exposed and without a psychiatric diagnosis). Using the brain age gap estimate, an index of relative circuit maturation, patterns of atypical neurodevelopment were investigated. RESULTS:Violence exposure was associated with delayed maturation of basolateral amygdala (BLA)-PFC circuits, driven by increased BLA-medial orbitofrontal cortex functional connectivity. In contrast, increased psychiatric symptoms were associated with advanced maturation of BLA-PFC functional connectivity, driven by decreased BLA-dorsolateral PFC functional connectivity. CONCLUSIONS:Delayed frontoamygdala maturation after exposure to violence suggests atypical, but adaptive, development of threat appraisal processes, potentially reflecting a greater threat generalization characteristic of younger children. Advanced circuit maturation with increasing symptoms suggests divergent neurodevelopmental mechanisms underlying illness after emotion circuits have adapted to adversity, exacerbated by preexisting vulnerabilities to early maturation. Disentangling the effects of adversity and psychopathology on neurodevelopment is crucial for helping youths recover from violence and preventing illness from continuing into adulthood.

IntroductionMaximal grip strength, a measure of how much force a person’s hand can generate when squeezing an object, may be an effective method for understanding potential neurobiological differences during motor tasks. Grip strength in autistic individuals may be of particular interest due to its unique developmental trajectory. While autism-specific differences in grip-brain relationships have been found in adult populations, it is possible that such differences in grip-brain relationships may be present at earlier ages when grip strength is behaviorally similar in autistic and non-autistic groups. Further, such neural differences may lead to the later emergence of diagnostic-group grip differences in adolescence. The present study sought to examine this possibility, while also examining if grip strength could elucidate the neuro-motor sources of phenotypic heterogeneity commonly observed within autism.MethodsUsing high resolution, multi-shell diffusion, and quantitative R1 relaxometry imaging, this study examined how variations in key sensorimotor-related white matter pathways of the proprioception input, lateral grasping, cortico-cerebellar, and corticospinal networks were associated with individual variations in grip strength in 68 autistic children and 70 non-autistic (neurotypical) children (6–11 years-old).ResultsIn both groups, results indicated that stronger grip strength was associated with higher proprioceptive input, lateral grasping, and corticospinal (but not cortico-cerebellar modification) fractional anisotropy and R1, indirect measures concordant with stronger microstructural coherence and increased myelination. Diagnostic group differences in these grip-brain relationships were not observed, but the autistic group exhibited more variability particularly in the cortico-cerebellar modification indices. An examination into the variability within the autistic group revealed that attention-deficit/hyperactivity disorder (ADHD) features moderated the relationships between grip strength and both fractional anisotropy and R1 relaxometry in the premotor-primary motor tract of the lateral grasping network and the cortico-cerebellar network tracts. Specifically, in autistic children with elevated ADHD features (60% of the autistic group) stronger grip strength was related to higher fractional anisotropy and R1 of the cerebellar modification network (stronger microstructural coherence and more myelin), whereas the opposite relationship was observed in autistic children with reduced ADHD features.DiscussionTogether, this work suggests that while the foundational elements of grip strength are similar across school-aged autistic and non-autistic children, neural mechanisms of grip strength within autistic children may additionally depend on the presence of ADHD features. Specifically, stronger, more coherent connections of the cerebellar modification network, which is thought to play a role in refining and optimizing motor commands, may lead to stronger grip in children with more ADHD features, weaker grip in children with fewer ADHD features, and no difference in grip in non-autistic children. While future research is needed to understand if these findings extend to other motor tasks beyond grip strength, these results have implications for understanding the biological basis of neuromotor control in autistic children and emphasize the importance of assessing co-occurring conditions when evaluating brain-behavior relationships in autism.

The generalizability of the Hierarchical Taxonomy of Psychopathology (HiTOP) model remains in question for many groups. Available data offers some understanding of the generalizability of HiTOP based on race, ethnicity, nation of origin, age, sexual orientation, and gender identity. In this brief review, we review the advantages of the HiTOP model for underrepresented populations, including its early focus on generalizability, incorporation of social determinants of health, and potential for alleviating diagnostic bias. We also consider future directions for the HiTOP model, such as further maximizing the representativeness of its associated literature.This review was published in The Clinical Psychologist (Issue 77) in 2024.

Features of autism spectrum disorder, attention-deficit/hyperactivity disorder, learning disorders, intellectual disabilities, and communication and motor disorders usually emerge early in life and are associated with atypical neurodevelopment. These "neurodevelopmental conditions" are grouped together in the DSM-5 and ICD-11 to reflect their shared characteristics. Yet, reliance on categorical diagnoses poses significant challenges in both research and clinical settings (e.g., high co-occurrence, arbitrary diagnostic boundaries, high within-disorder heterogeneity). Taking a transdiagnostic dimensional approach provides a useful alternative for addressing these limitations, accounting for shared underpinnings across neurodevelopmental conditions, and characterizing their common co-occurrence and developmental continuity with other psychiatric conditions. Neurodevelopmental features have not been adequately considered in transdiagnostic psychiatric frameworks, although this would have fundamental implications for research and clinical practices. Growing evidence from studies on the structure of neurodevelopmental and other psychiatric conditions indicates that features of neurodevelopmental conditions cluster together, delineating a "neurodevelopmental spectrum" ranging from normative to impairing profiles. Studies on shared genetic underpinnings, overlapping cognitive and neural profiles, and similar developmental course and efficacy of support/treatment strategies indicate the validity of this neurodevelopmental spectrum. Further, characterizing this spectrum alongside other psychiatric dimensions has clinical utility, as it provides a fuller view of an individual's needs and strengths, and greater prognostic utility than diagnostic categories. Based on this compelling body of evidence, we argue that incorporating a new neurodevelopmental spectrum into transdiagnostic frameworks has considerable potential for transforming our understanding, classification, assessment, and clinical practices around neurodevelopmental and other psychiatric conditions.

Attention-deficit/hyperactivity disorder (ADHD) commonly co-occurs in autistic children. However, additional research is needed to explore the differences in motor skills and sensory features in autistic children with and without ADHD, as well as the impacts of these factors on daily living skills (DLS). This observational study sought to fill this gap with 67 autistic children (6.14–10.84 years-old), 43 of whom had ADHD. Autistic children with ADHD demonstrated higher sensory features and lower motor skills than autistic children without ADHD. In examining autism and ADHD features dimensionally, we found that overall sensory features, seeking, and hyporesponsiveness were driven by both autism and ADHD features, whereas motor skills, enhanced perception, and hyperresponsiveness were driven by only autism features. Additionally, in using these dimensional variables of autism and ADHD features, we found that differences in motor skills, sensory and autism features, but not ADHD features, impact DLS of autistic children, with autism features and motor skills being the strongest individual predictors of DLS. Together, these results demonstrate the uniqueness of motor skills and sensory features in autistic children with and without ADHD, as well as how autism features, sensory features, and motor skills contribute to DLS, emphasizing the importance of a comprehensive understanding of each individual and complexities of human development when supporting autistic children.

The majority of children with maltreatment histories do not go on to develop depression in their adolescent and adult years. These individuals are often identified as being "resilient", but this characterization may conceal difficulties that individuals with maltreatment histories might face in their interpersonal relationships, substance use, physical health, and/or socioeconomic outcomes in their later lives. This study examined how adolescents with maltreatment histories who exhibit low levels of depression function in other domains during their adult years. Longitudinal trajectories of depression (across ages 13-32) in individuals with (n = 3,809) and without (n = 8,249) maltreatment histories were modeled in the National Longitudinal Study of Adolescent to Adult Health. The same "Low," "increasing," and "declining" depression trajectories in both individuals with and without maltreatment histories were identified. Youths with maltreatment histories in the "low" depression trajectory reported lower romantic relationship satisfaction, more exposure to intimate partner and sexual violence, more alcohol abuse/dependency, and poorer general physical health compared to individuals without maltreatment histories in the same "low" depression trajectory in adulthood. Findings add further caution against labeling individuals as "resilient" based on a just single domain of functioning (low depression), as childhood maltreatment has harmful effects on a broad spectrum of functional domains.

The Hierarchical Taxonomy of Psychopathology (HiTOP) has gained significant traction in clinical psychological science. However, whether this emerging model of psychopathology is generalizable to diverse populations has been understudied. This study tested measurement invariance – the degree to which latent constructs are measured with equivalence across groups – in HiTOP across racial and ethnic groups using the Adolescent Brain Cognitive Development (ABCD) Study. Comparing across non-Hispanic white (n=7,166), Hispanic (n=2,411), and non-Hispanic Black (n=1,862) youths, the five-factor model comprising of Externalizing, Neurodevelopmental, Internalizing, Somatoform, and Detachment dimensions demonstrated configural, metric, scalar, and strict measurement invariance. Furthermore, each of the five factors demonstrated evidence of concurrent and convergent validity, reinforcing HiTOP’s utility in research with respect to diverse racial and ethnic groups. Establishing measurement invariance has critical scientific and clinical implications, particularly if latent dimensions of the HiTOP are to be used in addressing mental health disparities in minoritized populations.

The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirically based, hierarchical model of the structure of psychopathology that was created in response to the limitations of traditional, categorical psychiatric classification frameworks. The HiTOP model has become increasingly popular in clinical psychology and psychiatry since its publication in 2017. In this Review, we consider the applicability of the HiTOP model to diverse, underrepresented and epistemically excluded populations. We first review the philosophy underlying psychopathology research in general to understand the impact of scientific norms on the inclusion of diverse populations within the research canon. We then review the HiTOP approach to modelling psychopathology, and how diverse populations have been included within HiTOP-related research to date. We conclude by highlighting ways for future research to increase the applicability of the HiTOP framework to diverse populations. Seriously engaging with the HiTOP model’s suitability for diverse, underrepresented and epistemically excluded populations is imperative in order to achieve the HiTOP consortium’s goal of delineating a fully empirical classification of psychopathology, and to provide a model that can guide the field of psychopathology research and training to increase representation. The Hierarchical Taxonomy of Psychopathology (HiTOP) is an empirically based, hierarchical model of the structure of psychopathology. In this Review, Rodriguez-Seijas et al. consider the applicability of the HiTOP model to diverse, underrepresented and epistemically excluded populations.

Background ADHD polygenic scores (PGSs) have been previously shown to predict ADHD outcomes in several studies. However, ADHD PGSs are typically correlated with ADHD but not necessarily reflective of causal mechanisms. More research is needed to elucidate the neurobiological mechanisms underlying ADHD. We leveraged functional annotation information into an ADHD PGS to (1) improve the prediction performance over a non-annotated ADHD PGS and (2) test whether volumetric variation in brain regions putatively associated with ADHD mediate the association between PGSs and ADHD outcomes. Methods Data were from the Philadelphia Neurodevelopmental Cohort ( N = 555). Multiple mediation models were tested to examine the indirect effects of two ADHD PGSs—one using a traditional computation involving clumping and thresholding and another using a functionally annotated approach (i.e., AnnoPred )—on ADHD inattention (IA) and hyperactivity-impulsivity (HI) symptoms, via gray matter volumes in the cingulate gyrus, angular gyrus, caudate, dorsolateral prefrontal cortex (DLPFC), and inferior temporal lobe. Results A direct effect was detected between the AnnoPred ADHD PGS and IA symptoms in adolescents. No indirect effects via brain volumes were detected for either IA or HI symptoms. However, both ADHD PGSs were negatively associated with the DLPFC. Conclusions The AnnoPred ADHD PGS was a more developmentally specific predictor of adolescent IA symptoms compared to the traditional ADHD PGS. However, brain volumes did not mediate the effects of either a traditional or AnnoPred ADHD PGS on ADHD symptoms, suggesting that we may still be underpowered in clarifying brain-based biomarkers for ADHD using genetic measures.

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.

Objective: Polygenic scores (PGS) are widely used in psychiatric genetic associations studies due to their impressive power to predict focal outcomes. However, they lack in discriminatory power, in part due to the high degree of genetic overlap between psychiatric disorders. The lack of prediction specificity limits the clinical utility of psychiatric PGS, particularly for diagnostic applications. The goal of the study was to enhance the discriminatory power of psychiatric PGS for two highly comorbid and genetically correlated neurodevelopmental disorders in ADHD and autism spectrum disorder (ASD). Methods: Genomic structural equation modeling (GenomicSEM) was used to generate novel PGS for ADHD and ASD by accounting for the genetic overlap between these disorders (and eight others) to achieve greater discriminatory power in non-focal outcome predictions. PGS associations were tested in two large independent samples, the Philadelphia Neurodevelopmental Cohort (N=4,789) and the Simons Foundation Powering Autism Research for Knowledge (SPARK) ASD and sibling controls (N=5,045) cohort. Results: PGS from GenomicSEM achieved superior discriminatory power in terms of showing significantly attenuated associations with non-focal outcomes relative to traditionally computed PGS for these disorders. Additionally, genetic correlations between GenomicSEM PGS for ASD and ADHD were significantly attenuated in cross-trait associations with other psychiatric disorders and outcomes. Conclusions: Psychiatric PGS associations are likely inflated by the high degree of genetic overlap between the psychiatric disorders. Methods such as GenomicSEM can be used to refine PGS signals to be more disorder-specific, thereby enhancing their discriminatory power for future diagnostic applications.