Validation of the structured interview section of the penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT GOASSESS)

Large-scale studies and burdened clinical settings require precise, efficient measures that assess multiple domains of psychopathology. Computerized adaptive tests (CATs) can reduce administration time without compromising data quality. We examined feasibility and validity of an adaptive psychopathology measure, GOASSESS, in a clinical community-based sample (N = 315; ages 18-35) comprising three groups: healthy controls, psychosis, mood/anxiety disorders. Assessment duration was compared between the Full and CAT GOASSESS. External validity was tested by comparing how the CAT and Full versions related to demographic variables, study group, and socioeconomic status. The relationships between scale scores and criteria were statistically compared within a mixed-model framework to account for dependency between relationships. Convergent validity was assessed by comparing scores of the CAT and the Full GOASSESS using Pearson correlations. The CAT GOASSESS reduced interview duration by more than 90 % across study groups and preserved relationships to external criteria and demographic variables as the Full GOASSESS. All CAT GOASSESS scales could replace those of the Full instrument. Overall, the CAT GOASSESS showed acceptable psychometric properties and demonstrated feasibility by markedly reducing assessment time compared to the Full GOASSESS. The adaptive version could be used in large-scale studies or clinical settings for intake screening.

Functional connectivity development along the sensorimotor-association axis enhances the cortical hierarchy

Human cortical maturation has been posited to be organized along the sensorimotor-association axis, a hierarchical axis of brain organization that spans from unimodal sensorimotor cortices to transmodal association cortices. Here, we investigate the hypothesis that the development of functional connectivity during childhood through adolescence conforms to the cortical hierarchy defined by the sensorimotor-association axis. We tested this pre-registered hypothesis in four large-scale, independent datasets (total n = 3355; ages 5-23 years): the Philadelphia Neurodevelopmental Cohort (n = 1207), Nathan Kline Institute-Rockland Sample (n = 397), Human Connectome Project: Development (n = 625), and Healthy Brain Network (n = 1126). Across datasets, the development of functional connectivity systematically varied along the sensorimotor-association axis. Connectivity in sensorimotor regions increased, whereas connectivity in association cortices declined, refining and reinforcing the cortical hierarchy. These consistent and generalizable results establish that the sensorimotor-association axis of cortical organization encodes the dominant pattern of functional connectivity development.

Remote assessment of the Penn computerised neurocognitive battery in individuals with 22q11.2 deletion syndrome

BACKGROUND

Neurocognitive functioning is an integral phenotype of 22q11.2 deletion syndrome relating to severity of psychopathology and outcomes. A neurocognitive battery that could be administered remotely to assess multiple cognitive domains would be especially beneficial to research on rare genetic variants, where in-person assessment can be unavailable or burdensome. The current study compares in-person and remote assessments of the Penn computerised neurocognitive battery (CNB).

METHODS

Participants (mean age = 17.82, SD = 6.94 years; 48% female) completed the CNB either in-person at a laboratory (n = 222) or remotely (n = 162).

RESULTS

Results show that accuracy of CNB performance was equivalent across the two testing locations, while slight differences in speed were detected in 3 of the 11 tasks.

CONCLUSIONS

These findings suggest that the CNB can be used in remote settings to assess multiple neurocognitive domains.

In-vivo whole-cortex marker of excitation-inhibition ratio indexes cortical maturation and cognitive ability in youth

A balanced excitation-inhibition ratio (E/I ratio) is critical for healthy brain function. Normative development of cortex-wide E/I ratio remains unknown. Here we non-invasively estimate a putative marker of whole-cortex E/I ratio by fitting a large-scale biophysically-plausible circuit model to resting-state functional MRI (fMRI) data. We first confirm that our model generates realistic brain dynamics in the Human Connectome Project. Next, we show that the estimated E/I ratio marker is sensitive to the GABA-agonist benzodiazepine alprazolam during fMRI. Alprazolam-induced E/I changes are spatially consistent with positron emission tomography measurement of benzodiazepine receptor density. We then investigate the relationship between the E/I ratio marker and neurodevelopment. We find that the E/I ratio marker declines heterogeneously across the cerebral cortex during youth, with the greatest reduction occurring in sensorimotor systems relative to association systems. Importantly, among children with the same chronological age, a lower E/I ratio marker (especially in association cortex) is linked to better cognitive performance. This result is replicated across North American (8.2 to 23.0 years old) and Asian (7.2 to 7.9 years old) cohorts, suggesting that a more mature E/I ratio indexes improved cognition during normative development. Overall, our findings open the door to studying how disrupted E/I trajectories may lead to cognitive dysfunction in psychopathology that emerges during youth.

Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ): Rationale and Study Design of the Largest Global Prospective Cohort Study of Clinical High Risk for Psychosis

This article describes the rationale, aims, and methodology of the Accelerating Medicines Partnership® Schizophrenia (AMP® SCZ). This is the largest international collaboration to date that will develop algorithms to predict trajectories and outcomes of individuals at clinical high risk (CHR) for psychosis and to advance the development and use of novel pharmacological interventions for CHR individuals. We present a description of the participating research networks and the data processing analysis and coordination center, their processes for data harmonization across 43 sites from 13 participating countries (recruitment across North America, Australia, Europe, Asia, and South America), data flow and quality assessment processes, data analyses, and the transfer of data to the National Institute of Mental Health (NIMH) Data Archive (NDA) for use by the research community. In an expected sample of approximately 2000 CHR individuals and 640 matched healthy controls, AMP SCZ will collect clinical, environmental, and cognitive data along with multimodal biomarkers, including neuroimaging, electrophysiology, fluid biospecimens, speech and facial expression samples, novel measures derived from digital health technologies including smartphone-based daily surveys, and passive sensing as well as actigraphy. The study will investigate a range of clinical outcomes over a 2-year period, including transition to psychosis, remission or persistence of CHR status, attenuated positive symptoms, persistent negative symptoms, mood and anxiety symptoms, and psychosocial functioning. The global reach of AMP SCZ and its harmonized innovative methods promise to catalyze the development of new treatments to address critical unmet clinical and public health needs in CHR individuals.

Immune and oxidative stress biomarkers in pediatric psychosis and psychosis-risk: Meta-analyses and systematic review

OBJECTIVE

While genetic and cohort studies suggest immune and reduction/oxidation (redox) alterations occur in psychosis, less is known about potential alterations in children and adolescents.

METHODS

We conducted a systematic review to identify immune and redox biomarker studies in children and adolescents (mean age ≤ 18 years old) across the psychosis spectrum: from psychotic like experiences, which are common in children, to threshold psychotic disorders like schizophrenia. We conducted meta-analyses when at least three studies measured the same biomarker.

RESULTS

The systematic review includes 38 pediatric psychosis studies. The meta-analyses found that youth with threshold psychotic disorders had higher neutrophil/lymphocyte ratio (Hedge's g = 0.40, 95 % CI 0.17 - 0.64), tumor necrosis factor (Hedge's g = 0.38, 95 % CI 0.06 - 0.69), C-reactive protein (Hedge's g = 0.38, 95 % CI 0.05 - 0.70), interleukin-6 (Hedge's g = 0.35; 95 % CI 0.11 - 0.64), and total white blood cell count (Hedge's g = 0.29, 95 % CI 0.12 - 0.46) compared to youth without psychosis. Other immune and oxidative stress meta-analytic findings were very heterogeneous.

CONCLUSION

Results from several studies are consistent with the hypothesis that signals often classified as "proinflammatory" are elevated in threshold pediatric psychotic disorders. Data are less clear for immune markers in subthreshold psychosis and redox markers across the subthreshold and threshold psychosis spectrum. Immune and redox biomarker intervention studies are lacking, and research investigating interventions targeting the immune system in threshold pediatric psychosis is especially warranted.

Regression and Alignment for Functional Data and Network Topology

In the brain, functional connections form a network whose topological organization can be described by graph-theoretic network diagnostics. These include characterizations of the community structure, such as modularity and participation coefficient, which have been shown to change over the course of childhood and adolescence. To investigate if such changes in the functional network are associated with changes in cognitive performance during development, network studies often rely on an arbitrary choice of pre-processing parameters, in particular the proportional threshold of network edges. Because the choice of parameter can impact the value of the network diagnostic, and therefore downstream conclusions, we propose to circumvent that choice by conceptualizing the network diagnostic as a function of the parameter. As opposed to a single value, a network diagnostic curve describes the connectome topology at multiple scales-from the sparsest group of the strongest edges to the entire edge set. To relate these curves to executive function and other covariates, we use scalar-on-function regression, which is more flexible than previous functional data-based models used in network neuroscience. We then consider how systematic differences between networks can manifest in misalignment of diagnostic curves, and consequently propose a supervised curve alignment method that incorporates auxiliary information from other variables. Our algorithm performs both functional regression and alignment via an iterative, penalized, and nonlinear likelihood optimization. The illustrated method has the potential to improve the interpretability and generalizability of neuroscience studies where the goal is to study heterogeneity among a mixture of function- and scalar-valued measures.

Omega-3 Supplementation Reduces Schizotypal Personality in Children: A Randomized Controlled Trial

BACKGROUND AND HYPOTHESIS

Based on a childhood intervention from ages 3 to 5 years that included additional fish consumption and which resulted in reduced schizotypal personality at age 23, we had previously hypothesized that omega-3 could reduce schizotypy. The current study tests the hypothesis that omega-3 supplementation reduces schizotypy in children.

STUDY DESIGN

In this intention-to-treat, randomized, single-blind, stratified, factorial trial, a community sample of 290 children aged 11-12 years were randomized into Omega-3 Only, Cognitive Behavioral Therapy (CBT) Only, Omega-3 + CBT, and Control groups. Schizotypy was assessed using the SPQ-C (Schizotypal Personality Questionnaire for Children) at 0 months (baseline), 3 months (end of treatment), 6 months (3 months post-treatment), and 12 months (9 months post-treatment).

STUDY RESULTS

A significant group × time interaction (P = .013) indicated that, compared with Controls, total schizotypy scores were reduced in both Omega-3 Only and Omega-3 + CBT groups immediately post-treatment (d = 0.56 and 0.47, respectively), and also 3 months after supplementation terminated (d = 0.49, d = 0.70). Stronger findings were observed for the interpersonal schizotypy factor, with both omega-3 groups showing reductions 9 months post-treatment compared with the CBT Only group. Schizotypy reductions were significantly stronger for those with higher dietary intake of omega-3 at intake. Sensitivity analyses confirmed findings.

CONCLUSIONS

Results are unique in the field and suggest that omega-3 can help reduce schizotypal personality in community-residing children. From an epidemiological standpoint, if replicated and extended, these findings could have implications for early prevention of more significant schizotypal features developing later in adolescence.

CLINICAL TRIAL REGISTRATION

"Healthy Brains & Behavior: Understanding and Treating Youth Aggression (HBB)." ClinicalTrials.gov Identifier: NCT00842439, https://clinicaltrials.gov/ct2/show/NCT00842439.

The schizophrenia syndrome, circa 2024: What we know and how that informs its nature

With new data about different aspects of schizophrenia being continually generated, it becomes necessary to periodically revisit exactly what we know. Along with a need to review what we currently know about schizophrenia, there is an equal imperative to evaluate the construct itself. With these objectives, we undertook an iterative, multi-phase process involving fifty international experts in the field, with each step building on learnings from the prior one. This review assembles currently established findings about schizophrenia (construct, etiology, pathophysiology, clinical expression, treatment) and posits what they reveal about its nature. Schizophrenia is a heritable, complex, multi-dimensional syndrome with varying degrees of psychotic, negative, cognitive, mood, and motor manifestations. The illness exhibits a remitting and relapsing course, with varying degrees of recovery among affected individuals with most experiencing significant social and functional impairment. Genetic risk factors likely include thousands of common genetic variants that each have a small impact on an individual's risk and a plethora of rare gene variants that have a larger individual impact on risk. Their biological effects are concentrated in the brain and many of the same variants also increase the risk of other psychiatric disorders such as bipolar disorder, autism, and other neurodevelopmental conditions. Environmental risk factors include but are not limited to urban residence in childhood, migration, older paternal age at birth, cannabis use, childhood trauma, antenatal maternal infection, and perinatal hypoxia. Structural, functional, and neurochemical brain alterations implicate multiple regions and functional circuits. Dopamine D-2 receptor antagonists and partial agonists improve psychotic symptoms and reduce risk of relapse. Certain psychological and psychosocial interventions are beneficial. Early intervention can reduce treatment delay and improve outcomes. Schizophrenia is increasingly considered to be a heterogeneous syndrome and not a singular disease entity. There is no necessary or sufficient etiology, pathology, set of clinical features, or treatment that fully circumscribes this syndrome. A single, common pathophysiological pathway appears unlikely. The boundaries of schizophrenia remain fuzzy, suggesting the absence of a categorical fit and need to reconceptualize it as a broader, multi-dimensional and/or spectrum construct.

Validation of the cognitive section of the Penn computerized adaptive test for neurocognitive and clinical psychopathology assessment (CAT-CCNB)

BACKGROUND

The Penn Computerized Neurocognitive Battery is an efficient tool for assessing brain-behavior domains, and its efficiency was augmented via computerized adaptive testing (CAT). This battery requires validation in a separate sample to establish psychometric properties.

METHODS

In a mixed community/clinical sample of N = 307 18-to-35-year-olds, we tested the relationships of the CAT tests with the full-form tests. We compared discriminability among recruitment groups (psychosis, mood, control) and examined how their scores relate to demographics. CAT-Full relationships were evaluated based on a minimum inter-test correlation of 0.70 or an inter-test correlation within at least 0.10 of the full-form correlation with a previous administration of the full battery. Differences in criterion relationships were tested via mixed models.

RESULTS

Most tests (15/17) met the minimum criteria for replacing the full-form with the updated CAT version (mean r = 0.67; range = 0.53-0.80) when compared to relationships of the full-forms with previous administrations of the full-forms (mean r = 0.68; range = 0.50-0.85). Most (16/17) CAT-based relationships with diagnostics and other validity criteria were indistinguishable (interaction p > 0.05) from their full-form counterparts.

CONCLUSIONS

The updated CNB shows psychometric properties acceptable for research. The full-forms of some tests should be retained due to insufficient time savings to justify the loss in precision.

Psychosis superspectrum I: Nosology, etiology, and lifespan development

This review describes the Hierarchical Taxonomy of Psychopathology (HiTOP) model of psychosis-related psychopathology, the psychosis superspectrum. The HiTOP psychosis superspectrum was developed to address shortcomings of traditional diagnoses for psychotic disorders and related conditions including low reliability, arbitrary boundaries between psychopathology and normality, high symptom co-occurrence, and heterogeneity within diagnostic categories. The psychosis superspectrum is a transdiagnostic dimensional model comprising two spectra-psychoticism and detachment-which are in turn broken down into fourteen narrow components, and two auxiliary domains-cognition and functional impairment. The structure of the spectra and their components are shown to parallel the genetic structure of psychosis and related traits. Psychoticism and detachment have distinct patterns of association with urbanicity, migrant and ethnic minority status, childhood adversity, and cannabis use. The superspectrum also provides a useful model for describing the emergence and course of psychosis, as components of the superspectrum are relatively stable over time. Changes in psychoticism predict the onset of psychosis-related psychopathology, whereas changes in detachment and cognition define later course. Implications of the superspectrum for genetic, socio-environmental, and longitudinal research are discussed. A companion review focuses on neurobiology, treatment response, and clinical utility of the superspectrum, and future research directions.

Observations of Positive Parenting from Online Parent-Child Interactions at Age 1

Objective

Brief, reliable, and cost-effective methods to assess parenting are critical for advancing parenting research.

Design

We adapted the Three Bags task and Parent Child Interaction Rating System (PCIRS) for rating online visits with 219 parent-child dyads (White, n = 104 [47.5%], Black, n = 115 [52.5%]) and combined the video data with survey data collected during pregnancy and when children were aged 1.

Results

The PCIRS codes of positive regard, stimulation of child cognitive development, and sensitivity showed high reliability across the three parent-child interaction tasks. A latent positive parenting factor combining ratings across codes and tasks showed good model fit, which was similar regardless of parent self-identified race or ethnicity, age, socioeconomic disadvantage, marital/partnered status, and parity, as well as methodological factors relevant to the online video assessment method (e.g., phone vs. laptop/tablet). In support of construct validity, observed positive parenting was related to parent-reported positive parenting and child socioemotional development. Finally, parent reports of supportive relationships in pregnancy, but not neighborhood safety or pandemic worries, were prospectively related to higher positive parenting observed at age 1. With the exception of older parental age and married/partnered status, no other parent, child, sociodemographic, or methodological variables were related to higher overall video exclusions across tasks.

Conclusions

PCIRS may provide a reliable approach to rate positive parenting at age 1, providing future avenues for developing more ecologically valid assessments and implementing interventions through online encounters that may be more acceptable, accessible, or preferred among parents of young children.

Source-based morphometry reveals structural brain pattern abnormalities in 22q11.2 deletion syndrome

22q11.2 deletion syndrome (22q11DS) is the most frequently occurring microdeletion in humans. It is associated with a significant impact on brain structure, including prominent reductions in gray matter volume (GMV), and neuropsychiatric manifestations, including cognitive impairment and psychosis. It is unclear whether GMV alterations in 22q11DS occur according to distinct structural patterns. Then, 783 participants (470 with 22q11DS: 51% females, mean age [SD] 18.2 [9.2]; and 313 typically developing [TD] controls: 46% females, mean age 18.0 [8.6]) from 13 datasets were included in the present study. We segmented structural T1-weighted brain MRI scans and extracted GMV images, which were then utilized in a novel source-based morphometry (SBM) pipeline (SS-Detect) to generate structural brain patterns (SBPs) that capture co-varying GMV. We investigated the impact of the 22q11.2 deletion, deletion size, intelligence quotient, and psychosis on the SBPs. Seventeen GMV-SBPs were derived, which provided spatial patterns of GMV covariance associated with a quantitative metric (i.e., loading score) for analysis. Patterns of topographically widespread differences in GMV covariance, including the cerebellum, discriminated individuals with 22q11DS from healthy controls. The spatial extents of the SBPs that revealed disparities between individuals with 22q11DS and controls were consistent with the findings of the univariate voxel-based morphometry analysis. Larger deletion size was associated with significantly lower GMV in frontal and occipital SBPs; however, history of psychosis did not show a strong relationship with these covariance patterns. 22q11DS is associated with distinct structural abnormalities captured by topographical GMV covariance patterns that include the cerebellum. Findings indicate that structural anomalies in 22q11DS manifest in a nonrandom manner and in distinct covarying anatomical patterns, rather than a diffuse global process. These SBP abnormalities converge with previously reported cortical surface area abnormalities, suggesting disturbances of early neurodevelopment as the most likely underlying mechanism.

Development of white matter fiber covariance networks supports executive function in youth

During adolescence, the brain undergoes extensive changes in white matter structure that support cognition. Data-driven approaches applied to cortical surface properties have led the field to understand brain development as a spatially and temporally coordinated mechanism that follows hierarchically organized gradients of change. Although white matter development also appears asynchronous, previous studies have relied largely on anatomical tract-based atlases, precluding a direct assessment of how white matter structure is spatially and temporally coordinated. Harnessing advances in diffusion modeling and machine learning, we identified 14 data-driven patterns of covarying white matter structure in a large sample of youth. Fiber covariance networks aligned with known major tracts, while also capturing distinct patterns of spatial covariance across distributed white matter locations. Most networks showed age-related increases in fiber network properties, which were also related to developmental changes in executive function. This study delineates data-driven patterns of white matter development that support cognition.

Genomic loci influence patterns of structural covariance in the human brain

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain.

Similarity-based multimodal regression

To better understand complex human phenotypes, large-scale studies have increasingly collected multiple data modalities across domains such as imaging, mobile health, and physical activity. The properties of each data type often differ substantially and require either separate analyses or extensive processing to obtain comparable features for a combined analysis. Multimodal data fusion enables certain analyses on matrix-valued and vector-valued data, but it generally cannot integrate modalities of different dimensions and data structures. For a single data modality, multivariate distance matrix regression provides a distance-based framework for regression accommodating a wide range of data types. However, no distance-based method exists to handle multiple complementary types of data. We propose a novel distance-based regression model, which we refer to as Similarity-based Multimodal Regression (SiMMR), that enables simultaneous regression of multiple modalities through their distance profiles. We demonstrate through simulation, imaging studies, and longitudinal mobile health analyses that our proposed method can detect associations between clinical variables and multimodal data of differing properties and dimensionalities, even with modest sample sizes. We perform experiments to evaluate several different test statistics and provide recommendations for applying our method across a broad range of scenarios.

Normative Modeling of Brain Morphometry Across the Lifespan Using CentileBrain: Algorithm Benchmarking and Model Optimization

We present an empirically benchmarked framework for sex-specific normative modeling of brain morphometry that can inform about the biological and behavioral significance of deviations from typical age-related neuroanatomical changes and support future study designs. This framework was developed using regional morphometric data from 37,407 healthy individuals (53% female; aged 3-90 years) following a comparative evaluation of eight algorithms and multiple covariate combinations pertaining to image acquisition and quality, parcellation software versions, global neuroimaging measures, and longitudinal stability. The Multivariate Factorial Polynomial Regression (MFPR) emerged as the preferred algorithm optimized using nonlinear polynomials for age and linear effects of global measures as covariates. The MFPR models showed excellent accuracy across the lifespan and within distinct age-bins, and longitudinal stability over a 2-year period. The performance of all MFPR models plateaued at sample sizes exceeding 3,000 study participants. The model and scripts described here are freely available through CentileBrain (https://centilebrain.org/).

Distinct neurocognitive profiles and clinical phenotypes associated with copy number variation at the 22q11.2 locus

Rare genetic variants that confer large effects on neurodevelopment and behavioral phenotypes can reveal novel gene-brain-behavior relationships relevant to autism. Copy number variation at the 22q11.2 locus offer one compelling example, as both the 22q11.2 deletion (22qDel) and duplication (22qDup) confer increased likelihood of autism spectrum disorders (ASD) and cognitive deficits, but only 22qDel confers increased psychosis risk. Here, we used the Penn Computerized Neurocognitive Battery (Penn-CNB) to characterized neurocognitive profiles of 126 individuals: 55 22qDel carriers (MAge  = 19.2 years, 49.1% male), 30 22qDup carriers (MAge  = 17.3 years, 53.3% male), and 41 typically developing (TD) subjects (MAge  = 17.3 years, 39.0% male). We performed linear mixed models to assess group differences in overall neurocognitive profiles, domain scores, and individual test scores. We found all three groups exhibited distinct overall neurocognitive profiles. 22qDel and 22qDup carriers showed significant accuracy deficits across all domains relative to controls (episodic memory, executive function, complex cognition, social cognition, and sensorimotor speed), with 22qDel carriers exhibiting more severe accuracy deficits, particularly in episodic memory. However, 22qDup carriers generally showed greater slowing than 22qDel carriers. Notably, slower social cognition speed was uniquely associated with increased global psychopathology and poorer psychosocial functioning in 22qDup. Compared to TD, 22q11.2 copy number variants (CNV) carriers failed to show age-associated improvements in multiple cognitive domains. Exploratory analyses revealed 22q11.2 CNV carriers with ASD exhibited differential neurocognitive profiles, based on 22q11.2 copy number. These results suggest that there are distinct neurocognitive profiles associated with either a loss or gain of genomic material at the 22q11.2 locus.

Securing direct stakeholder feedback to inform clinical research in serious mental illness: Results of a patient and family perspectives survey

Mental illness research routinely includes unfamiliar or potentially frightening procedures like lumbar puncture (LP), contributing to low enrollment and retention. Previous studies related to LP acceptance have focused on older individuals, and little information on participant preferences for educational materials is available. We developed an online survey assessing existing knowledge, comfort and concerns, and preferences for educational materials in the context of our clinical study on schizophrenia spectrum conditions (SSCs). We found that participants were generally knowledgeable and interested in engaging with clinical SSC research. Frequency of engagement with research publications differed significantly by participant groups and age. Comfort levels were consistently highest for study procedures other than LP, though surprisingly the average number of informational needs per procedure was not significantly different for LP compared to other procedures. Preferences for format and source of educational materials varied across participant groups and age. Our results suggest that younger individuals with an SSC diagnosis are likely to have limited exposure to information, and proactively providing accessible and accurate educational materials may improve positive perceptions of LP. Providing content in a range of formats and sources will ensure that participants and their support networks have access to their preferred resources.

The Ethics of Risk Prediction for Psychosis and Suicide Attempt in Youth Mental Health

OBJECTIVE

To identify potential clinical utility of polygenic risk scores (PRS) and exposomic risk scores (ERS) for psychosis and suicide attempt in youth and assess the ethical implications of these tools.

STUDY DESIGN

We conducted a narrative literature review of emerging findings on PRS and ERS for suicide and psychosis as well as a literature review on the ethics of PRS. We discuss the ethical implications of the emerging findings for the clinical potential of PRS and ERS.

RESULTS

Emerging evidence suggests that PRS and ERS may offer clinical utility in the relatively near future but that this utility will be limited to specific, narrow clinical questions, in contrast to the suggestion that population-level screening will have sweeping impact. Combining PRS and ERS might optimize prediction. This clinical utility would change the risk-benefit balance of PRS, and further empirical assessment of proposed risks would be necessary. Some concerns for PRS, such as those about counseling, privacy, and inequities, apply to ERS. ERS raise distinct ethical challenges as well, including some that involve informed consent and direct-to-consumer advertising. Both raise questions about the ethics of machine-learning/artificial intelligence approaches.

CONCLUSIONS

Predictive analytics using PRS and ERS may soon play a role in youth mental health settings. Our findings help educate clinicians about potential capabilities, limitations, and ethical implications of these tools. We suggest that a broader discussion with the public is needed to avoid overenthusiasm and determine regulations and guidelines for use of predictive scores.

The molecular genetic landscape of human brain size variation

Human brain size changes dynamically through early development, peaks in adolescence, and varies up to 2-fold among adults. However, the molecular genetic underpinnings of interindividual variation in brain size remain unknown. Here, we leveraged postmortem brain RNA sequencing and measurements of brain weight (BW) in 2,531 individuals across three independent datasets to identify 928 genome-wide significant associations with BW. Genes associated with higher or lower BW showed distinct neurodevelopmental trajectories and spatial patterns that mapped onto functional and cellular axes of brain organization. Expression of BW genes was predictive of interspecies differences in brain size, and bioinformatic annotation revealed enrichment for neurogenesis and cell-cell communication. Genome-wide, transcriptome-wide, and phenome-wide association analyses linked BW gene sets to neuroimaging measurements of brain size and brain-related clinical traits. Cumulatively, these results represent a major step toward delineating the molecular pathways underlying human brain size variation in health and disease.

Network Enrichment Significance Testing in Brain-Phenotype Association Studies

Functional networks often guide our interpretation of spatial maps of brain-phenotype associations. However, methods for assessing enrichment of associations within networks of interest have varied in terms of both scientific rigor and underlying assumptions. While some approaches have relied on subjective interpretations, others have made unrealistic assumptions about the spatial structure of imaging data, leading to inflated false positive rates. We seek to address this gap in existing methodology by borrowing insight from a method widely used in genomics research for testing enrichment of associations between a set of genes and a phenotype of interest. We propose Network Enrichment Significance Testing (NEST), a flexible framework for testing the specificity of brain-phenotype associations to functional networks or other sub-regions of the brain. We apply NEST to study phenotype associations with structural and functional brain imaging data from a large-scale neurodevelopmental cohort study.

Evaluation of a new intrinsic and extrinsic motivation scale in youth with psychosis spectrum symptoms

BACKGROUND

Impairment in intrinsic motivation (IM), the drive to satisfy internal desires like mastery, may play a key role in disability in psychosis. However, we have limited knowledge regarding relative impairments in IM compared to extrinsic motivation (EM) or general motivation (GM), in part due to limitations in existing measures.

METHODS

Here we address this gap using a novel Trait Intrinsic and Extrinsic Motivation self-report scale in a sample of n = 243 participants including those with schizophrenia, psychosis-risk, and healthy controls. Each of the 7 IM and 6 EM items used a 7-point Likert scale assessing endorsement of dispositional statements. Bifactor analyses of these items yielded distinct IM, EM, and GM factor scores. Convergent and discriminant validity were examined in relation to General Causality Orientation Scale (GCOS-CP) and Quality of Life 3-item IM measure (QLS-IM). Utility was assessed in relation to psychosis-spectrum (PS) status and CAINS clinical amotivation.

RESULTS

IM and EM showed acceptable inter-item consistency (IM: α = 0.88; EM: α = 0.66); the bifactor model exhibited fit that varied from good to borderline to inadequate depending on the specific fit metric (SRMR = 0.038, CFI = 0.94, RMSEA = 0.106 ± 0.014). IM scores correlated with established IM measures: GCOS-CP Autonomy (rho = 0.38, p < 0.01) and QLS-IM (rho = 0.29, p < 0.01). Supporting discriminant validity, IM did not correlate with GCOS-CP Control (rho = -0.14, p > 0.05). Two-year stability in an available longitudinal subset (n = 35) was strong (IM: rho = 0.64, p < 0.01; EM: rho = 0.55, p < 0.01). Trait IM was lower in PS youth (t = 4.24, p < 0.01), and correlated with clinical amotivation (rho = -0.36, p < 0.01); EM did not show significant clinical associations.

CONCLUSIONS

These results demonstrate the clinical relevance of IM in psychosis risk. They also provide preliminary support for the reliability, validity and utility of this new Trait IM-EM scale, which addresses a measurement gap and can facilitate identification of neurobehavioral and clinical correlates of IM deficits.

The Influence of Pandemic-Related Worries During Pregnancy on Child Development at 12 Months

The COVID-19 pandemic has been linked to increased risk for perinatal anxiety and depression among parents, as well as negative consequences for child development. Less is known about how worries arising from the pandemic during pregnancy are related to later child development, nor if resilience factors buffer negative consequences. The current study addresses this question in a prospective longitudinal design. Data was collected from a sub-study (n = 184) of a longitudinal study of pregnant individuals (total n = 1173). During pregnancy (April 17-July 8, 2020) and the early postpartum period (August 11, 2020-March 2, 2021), participants completed online surveys. At 12 months postpartum (June 17, 2021-March 23, 2022), participants completed online surveys and a virtual laboratory visit, which included parent-child interaction tasks. We found more pregnancy-specific pandemic worries were prospectively related to lower levels of child socioemotional development based on parent report (B = - 1.13, SE = .43, p = .007) and observer ratings (B = - 0.13, SE = .07, p = .045), but not to parent-reported general developmental milestones. Parental emotion regulation in the early postpartum period moderated the association between pregnancy-specific pandemic worries and child socioemotional development such that pregnancy-specific pandemic worries did not relate to worse child socioemotional development among parents with high (B = - .02, SE = .10, t = - .14, p = .89) levels of emotion regulation. Findings suggest the negative consequences of parental worry and distress during pregnancy on the early socioemotional development of children in the context of the COVID-19 pandemic. Results highlight that parental emotion regulation may represent a target for intervention to promote parental resilience and support optimized child development.

The overlapping genetic architecture of psychiatric disorders and cortical brain structure

Both psychiatric vulnerability and cortical structure are shaped by the cumulative effect of common genetic variants across the genome. However, the shared genetic underpinnings between psychiatric disorders and brain structural phenotypes, such as thickness and surface area of the cerebral cortex, remains elusive. In this study, we employed pleiotropy-informed conjunctional false discovery rate analysis to investigate shared loci across genome-wide association scans of regional cortical thickness, surface area, and seven psychiatric disorders in approximately 700,000 individuals of European ancestry. Aggregating regional measures, we identified 50 genetic loci shared between psychiatric disorders and surface area, as well as 26 genetic loci shared with cortical thickness. Risk alleles exhibited bidirectional effects on both cortical thickness and surface area, such that some risk alleles for each disorder increased regional brain size while other risk alleles decreased regional brain size. Due to bidirectional effects, in many cases we observed extensive pleiotropy between an imaging phenotype and a psychiatric disorder even in the absence of a significant genetic correlation between them. The impact of genetic risk for psychiatric disorders on regional brain structure did exhibit a consistent pattern across highly comorbid psychiatric disorders, with 80% of the genetic loci shared across multiple disorders displaying consistent directions of effect. Cortical patterning of genetic overlap revealed a hierarchical genetic architecture, with the association cortex and sensorimotor cortex representing two extremes of shared genetic influence on psychiatric disorders and brain structural variation. Integrating multi-scale functional annotations and transcriptomic profiles, we observed that shared genetic loci were enriched in active genomic regions, converged on neurobiological and metabolic pathways, and showed differential expression in postmortem brain tissue from individuals with psychiatric disorders. Cumulatively, these findings provide a significant advance in our understanding of the overlapping polygenic architecture between psychopathology and cortical brain structure.

The contribution of medical burden to 22q11.2 deletion syndrome quality of life and functioning

PURPOSE

To date, there is no systematic method to quantify the medical burden of individuals with 22q11.2 deletion syndrome (22q11.2DS). This study aimed to design a Medical Burden Scale for 22q11.2DS to evaluate the effect of medical symptoms severity on quality of life (QoL) and functioning in individuals with this syndrome.

METHODS

Individuals with 22q11.2DS (n = 76) were included in the study. A multidisciplinary group of physicians determined the severity of symptoms (on a scale of 0 to 4) of 8 major medical systems affected in 22q11.2DS, as well as the level of cognitive deficits and psychiatric morbidity. Regression models were used to evaluate the impact of medical, cognitive, and psychiatric symptoms' severity on global assessment of functioning (GAF) and QoL.

RESULTS

The total Medical Burden Scale score was significantly associated with both QoL and GAF scores, beyond the effect of the psychiatric and cognitive deficits. We also found that QoL and GAF scores were associated with the severity scores of specific medical systems, particularly neurological symptoms, but also cardiovascular, ear-nose-throat, endocrinology, and orthopedics.

CONCLUSION

Quantifying the medical burden of 22q11.2DS individuals is feasible and indicates the overall and specific contribution of medical symptoms to QoL and functioning of 22q11.2DS individuals.

Development and application of novel performance validity metrics for computerized neurocognitive batteries

OBJECTIVES

Data from neurocognitive assessments may not be accurate in the context of factors impacting validity, such as disengagement, unmotivated responding, or intentional underperformance. Performance validity tests (PVTs) were developed to address these phenomena and assess underperformance on neurocognitive tests. However, PVTs can be burdensome, rely on cutoff scores that reduce information, do not examine potential variations in task engagement across a battery, and are typically not well-suited to acquisition of large cognitive datasets. Here we describe the development of novel performance validity measures that could address some of these limitations by leveraging psychometric concepts using data embedded within the Penn Computerized Neurocognitive Battery (PennCNB).

METHODS

We first developed these validity measures using simulations of invalid response patterns with parameters drawn from real data. Next, we examined their application in two large, independent samples: 1) children and adolescents from the Philadelphia Neurodevelopmental Cohort (n = 9498); and 2) adult servicemembers from the Marine Resiliency Study-II (n = 1444).

RESULTS

Our performance validity metrics detected patterns of invalid responding in simulated data, even at subtle levels. Furthermore, a combination of these metrics significantly predicted previously established validity rules for these tests in both developmental and adult datasets. Moreover, most clinical diagnostic groups did not show reduced validity estimates.

CONCLUSIONS

These results provide proof-of-concept evidence for multivariate, data-driven performance validity metrics. These metrics offer a novel method for determining the performance validity for individual neurocognitive tests that is scalable, applicable across different tests, less burdensome, and dimensional. However, more research is needed into their application.

Contribution of risk and resilience factors to anxiety trajectories during the early stages of the COVID-19 pandemic: A longitudinal study

The COVID-19 pandemic, and the response of governments to mitigate the pandemic's spread, resulted in exceptional circumstances that comprised a major global stressor, with broad implications for mental health. We aimed to delineate anxiety trajectories over three time-points in the first 6 months of the pandemic and identify baseline risk and resilience factors that predicted anxiety trajectories. Within weeks of the pandemic onset, we established a website (covid19resilience.org), and enrolled 1362 participants (n = 1064 from US; n = 222 from Israel) who provided longitudinal data between April-September 2020. We used latent growth mixture modelling to identify anxiety trajectories and ran multivariate regression models to compare characteristics between trajectory classes. A four-class model best fit the data, including a resilient trajectory (stable low anxiety) the most common (n = 961, 75.08%), and chronic anxiety (n = 149, 11.64%), recovery (n = 96, 7.50%) and delayed anxiety (n = 74, 5.78%) trajectories. Resilient participants were older, not living alone, with higher income, more education, and reported fewer COVID-19 worries and better sleep quality. Higher resilience factors' scores, specifically greater emotion regulation and lower conflict relationships, also uniquely distinguished the resilient trajectory. Results are consistent with the pre-pandemic resilience literature suggesting that most individuals show stable mental health in the face of stressful events. Findings can inform preventative interventions for improved mental health.

Brain Growth Charts for Quantitative Analysis of Pediatric Clinical Brain MRI Scans with Limited Imaging Pathology

Background Clinically acquired brain MRI scans represent a valuable but underused resource for investigating neurodevelopment due to their technical heterogeneity and lack of appropriate controls. These barriers have curtailed retrospective studies of clinical brain MRI scans compared with more costly prospectively acquired research-quality brain MRI scans. Purpose To provide a benchmark for neuroanatomic variability in clinically acquired brain MRI scans with limited imaging pathology (SLIPs) and to evaluate if growth charts from curated clinical MRI scans differed from research-quality MRI scans or were influenced by clinical indication for the scan. Materials and Methods In this secondary analysis of preexisting data, clinical brain MRI SLIPs from an urban pediatric health care system (individuals aged ≤22 years) were scanned across nine 3.0-T MRI scanners. The curation process included manual review of signed radiology reports and automated and manual quality review of images without gross pathology. Global and regional volumetric imaging phenotypes were measured using two image segmentation pipelines, and clinical brain growth charts were quantitatively compared with charts derived from a large set of research controls in the same age range by means of Pearson correlation and age at peak volume. Results The curated clinical data set included 532 patients (277 male; median age, 10 years [IQR, 5-14 years]; age range, 28 days after birth to 22 years) scanned between 2005 and 2020. Clinical brain growth charts were highly correlated with growth charts derived from research data sets (22 studies, 8346 individuals [4947 male]; age range, 152 days after birth to 22 years) in terms of normative developmental trajectories predicted by the models (median r = 0.979). Conclusion The clinical indication of the scans did not significantly bias the output of clinical brain charts. Brain growth charts derived from clinical controls with limited imaging pathology were highly correlated with brain charts from research controls, suggesting the potential of curated clinical MRI scans to supplement research data sets. © RSNA, 2023 Supplemental material is available for this article. See also the editorial by Ertl-Wagner and Pai in this issue.

Hoarding behavior and its association with mental health and functioning in a large youth sample

Hoarding behavior is prevalent in children and adolescents, yet clinicians do not routinely inquire about it and youth may not spontaneously report it due to stigma. It is unknown whether hoarding behavior, over and above obsessive-compulsive symptoms (OCS), is associated with major clinical factors in a general youth population. This observational study included N = 7054 youth who were not seeking help for mental health problems (ages 11-21, 54% female) and completed a structured interview that included evaluation of hoarding behavior and OCS, as a part of the Philadelphia Neurodevelopmental Cohort between November 2009 and December 2011. We employed regression models with hoarding behavior and OCS (any/none) as independent variables, and continuous (linear regression) or binary (logistic regression) mental health measures as dependent variables. All models covaried for age, sex, race, and socioeconomic status. A total of 374 participants endorsed HB (5.3%), most of which reported additional OCS (n = 317). When accounting for OCS presence, hoarding behavior was associated with greater dimensional psychopathology burden (i.e., higher P-factor) (β = 0.19, p < .001), and with poorer functioning (i.e., lower score on the child global assessment scale) (β = - 0.07, p < .001). The results were consistent when modeling psychopathology using binary variables. The results remained significant in sensitivity analyses accounting for count of endorsed OCS and excluding participants who met criteria for obsessive-compulsive disorder (n = 210). These results suggest that hoarding behavior among youth is associated with poorer mental health and functioning, independent of OCS. Brief hoarding-behavior assessments in clinical settings may prove useful given hoarding behavior's stigma and detrimental health associations.

Using network control theory to study the dynamics of the structural connectome

Network control theory (NCT) is a simple and powerful tool for studying how network topology informs and constrains dynamics. Compared to other structure-function coupling approaches, the strength of NCT lies in its capacity to predict the patterns of external control signals that may alter dynamics in a desired way. We have extensively developed and validated the application of NCT to the human structural connectome. Through these efforts, we have studied (i) how different aspects of connectome topology affect neural dynamics, (ii) whether NCT outputs cohere with empirical data on brain function and stimulation, and (iii) how NCT outputs vary across development and correlate with behavior and mental health symptoms. In this protocol, we introduce a framework for applying NCT to structural connectomes following two main pathways. Our primary pathway focuses on computing the control energy associated with transitioning between specific neural activity states. Our second pathway focuses on computing average controllability, which indexes nodes' general capacity to control dynamics. We also provide recommendations for comparing NCT outputs against null network models. Finally, we support this protocol with a Python-based software package called network control theory for python (nctpy).

Individual differences in delay discounting are associated with dorsal prefrontal cortex connectivity in children, adolescents, and adults

Delay discounting is a measure of impulsive choice relevant in adolescence as it predicts many real-life outcomes, including obesity and academic achievement. However, resting-state functional networks underlying individual differences in delay discounting during youth remain incompletely described. Here we investigate the association between multivariate patterns of functional connectivity and individual differences in impulsive choice in a large sample of children, adolescents, and adults. A total of 293 participants (9-23 years) completed a delay discounting task and underwent 3T resting-state fMRI. A connectome-wide analysis using multivariate distance-based matrix regression was used to examine whole-brain relationships between delay discounting and functional connectivity. These analyses revealed that individual differences in delay discounting were associated with patterns of connectivity emanating from the left dorsal prefrontal cortex, a default mode network hub. Greater delay discounting was associated with greater functional connectivity between the dorsal prefrontal cortex and other default mode network regions, but reduced connectivity with regions in the dorsal and ventral attention networks. These results suggest delay discounting in children, adolescents, and adults is associated with individual differences in relationships both within the default mode network and between the default mode and networks involved in attentional and cognitive control.

Alprazolam modulates persistence energy during emotion processing in first-degree relatives of individuals with schizophrenia: a network control study

Schizophrenia is marked by deficits in facial affect processing associated with abnormalities in GABAergic circuitry, deficits also found in first-degree relatives. Facial affect processing involves a distributed network of brain regions including limbic regions like amygdala and visual processing areas like fusiform cortex. Pharmacological modulation of GABAergic circuitry using benzodiazepines like alprazolam can be useful for studying this facial affect processing network and associated GABAergic abnormalities in schizophrenia. Here, we use pharmacological modulation and computational modeling to study the contribution of GABAergic abnormalities toward emotion processing deficits in schizophrenia. Specifically, we apply principles from network control theory to model persistence energy - the control energy required to maintain brain activation states - during emotion identification and recall tasks, with and without administration of alprazolam, in a sample of first-degree relatives and healthy controls. Here, persistence energy quantifies the magnitude of theoretical external inputs during the task. We find that alprazolam increases persistence energy in relatives but not in controls during threatening face processing, suggesting a compensatory mechanism given the relative absence of behavioral abnormalities in this sample of unaffected relatives. Further, we demonstrate that regions in the fusiform and occipital cortices are important for facilitating state transitions during facial affect processing. Finally, we uncover spatial relationships (i) between regional variation in differential control energy (alprazolam versus placebo) and (ii) both serotonin and dopamine neurotransmitter systems, indicating that alprazolam may exert its effects by altering neuromodulatory systems. Together, these findings provide a new perspective on the distributed emotion processing network and the effect of GABAergic modulation on this network, in addition to identifying an association between schizophrenia risk and abnormal GABAergic effects on persistence energy during threat processing.

The impact of postpartum social support on postpartum mental health outcomes during the COVID-19 pandemic

Social support is an influential component of postpartum recovery, adjustment, and bonding, which was disrupted by social distancing recommendations related to the COVID-19 pandemic. This study reports on changes in the availability of social support for postpartum women during the pandemic, investigates how those changes may have contributed to postpartum mental health, and probes how specific types of social support buffered against poor postpartum mental health and maternal-infant bonding impairment. Participants were 833 pregnant patients receiving prenatal care in an urban USA setting and using an electronic patient portal to access self-report surveys at two time points, during pregnancy (April-July 2020) and at ~12 weeks postpartum (August 2020-March 2021). Measures included an assessment of COVID-19 pandemic-related change in social support, sources of social support, ratings of emotional and practical support, and postpartum outcomes including depression, anxiety, and maternal-infant bonding. Overall self-reported social support decreased during the pandemic. Decreased social support was associated with an increased risk of postpartum depression, postpartum anxiety, and impaired parent-infant bonding. Among women reporting low practical support, emotional support appeared to protect against clinically significant depressive symptoms and impaired bonding with the infant. Decreases in social support are associated with a risk for poor postpartum mental health outcomes and impaired maternal-infant bonding. Evaluation and promotion of social support are recommended for healthy adjustment and functioning of postpartum women and families.

Chromatin regulators in the TBX1 network confer risk for conotruncal heart defects in 22q11.2DS

Congenital heart disease (CHD) affecting the conotruncal region of the heart, occurs in 40-50% of patients with 22q11.2 deletion syndrome (22q11.2DS). This syndrome is a rare disorder with relative genetic homogeneity that can facilitate identification of genetic modifiers. Haploinsufficiency of TBX1, encoding a T-box transcription factor, is one of the main genes responsible for the etiology of the syndrome. We suggest that genetic modifiers of conotruncal defects in patients with 22q11.2DS may be in the TBX1 gene network. To identify genetic modifiers, we analyzed rare, predicted damaging variants in whole genome sequence of 456 cases with conotruncal defects and 537 controls, with 22q11.2DS. We then performed gene set approaches and identified chromatin regulatory genes as modifiers. Chromatin genes with recurrent damaging variants include EP400, KAT6A, KMT2C, KMT2D, NSD1, CHD7 and PHF21A. In total, we identified 37 chromatin regulatory genes, that may increase risk for conotruncal heart defects in 8.5% of 22q11.2DS cases. Many of these genes were identified as risk factors for sporadic CHD in the general population. These genes are co-expressed in cardiac progenitor cells with TBX1, suggesting that they may be in the same genetic network. The genes KAT6A, KMT2C, CHD7 and EZH2, have been previously shown to genetically interact with TBX1 in mouse models. Our findings indicate that disturbance of chromatin regulatory genes impact the TBX1 gene network serving as genetic modifiers of 22q11.2DS and sporadic CHD, suggesting that there are some shared mechanisms involving the TBX1 gene network in the etiology of CHD.

Executive function as a generalized determinant of psychopathology and functional outcome in school-aged autism spectrum disorder: a case-control study

BACKGROUND

Individuals with autism spectrum disorder (ASD) are challenged not only by the defining features of social-communication deficits and restricted repetitive behaviors, but also by a myriad of psychopathology varying in severity. Different cognitive deficits underpin these psychopathologies, which could be subjected to intervention to alter the course of the disorder. Understanding domain-specific mediating effects of cognition is essential for developing targeted intervention strategies. However, the high degree of inter-correlation among different cognitive functions hinders elucidation of individual effects.

METHODS

In the Philadelphia Neurodevelopmental Cohort, 218 individuals with ASD were matched with 872 non-ASD controls on sex, age, race, and socioeconomic status. Participants of this cohort were deeply and broadly phenotyped on neurocognitive abilities and dimensional psychopathology. Using structural equation modeling, inter-correlation among cognitive domains were adjusted before mediation analysis on outcomes of multi-domain psychopathology and functional level.

RESULTS

While social cognition, complex cognition, and memory each had a unique pattern of mediating effect on psychopathology domains in ASD, none had significant effects on the functional level. In contrast, executive function was the only cognitive domain that exerted a generalized negative impact on every psychopathology domain (p factor, anxious-misery, psychosis, fear, and externalizing), as well as functional level.

CONCLUSIONS

Executive function has a unique association with the severity of comorbid psychopathology in ASD, and could be a target of interventions. As executive dysfunction occurs variably in ASD, our result also supports the clinical utility of assessing executive function for prognostic purposes.

Illness Phase as a Key Assessment and Intervention Window for Psychosis

The phenotype of schizophrenia, regardless of etiology, represents the most studied psychotic disorder with respect to neurobiology and distinct phases of illness. The early phase of illness represents a unique opportunity to provide effective and individualized interventions that can alter illness trajectories. Developmental age and illness stage, including temporal variation in neurobiology, can be targeted to develop phase-specific clinical assessment, biomarkers, and interventions. We review an earlier model whereby an initial glutamate signaling deficit progresses through different phases of allostatic adaptation, moving from potentially reversible functional abnormalities associated with early psychosis and working memory dysfunction, and ending with difficult-to-reverse structural changes after chronic illness. We integrate this model with evidence of dopaminergic abnormalities, including cortical D1 dysfunction, which develop during adolescence. We discuss how this model and a focus on a potential critical window of intervention in the early stages of schizophrenia impact the approach to research design and clinical care. This impact includes stage-specific considerations for symptom assessment as well as genetic, cognitive, and neurophysiological biomarkers. We examine how phase-specific biomarkers of illness phase and brain development can be incorporated into current strategies for large-scale research and clinical programs implementing coordinated specialty care. We highlight working memory and D1 dysfunction as early treatment targets that can substantially affect functional outcome.

Development of Iron Status Measures during Youth: Associations with Sex, Neighborhood Socioeconomic Status, Cognitive Performance, and Brain Structure

BACKGROUND

Iron is essential to brain function, and iron deficiency during youth may adversely impact neurodevelopment. Understanding the developmental time course of iron status and its association with neurocognitive functioning is important for identifying windows for intervention.

OBJECTIVES

This study aimed to characterize developmental change in iron status and understand its association with cognitive performance and brain structure during adolescence using data from a large pediatric health network.

METHODS

This study included a cross-sectional sample of 4899 participants (2178 males; aged 8-22 y at the time of participation, M [SD] = 14.24 [3.7]) who were recruited from the Children's Hospital of Philadelphia network. Prospectively collected research data were enriched with electronic medical record data that included hematological measures related to iron status, including serum hemoglobin, ferritin, and transferrin (33,015 total samples). At the time of participation, cognitive performance was assessed using the Penn Computerized Neurocognitive Battery, and brain white matter integrity was assessed using diffusion-weighted MRI in a subset of individuals.

RESULTS

Developmental trajectories were characterized for all metrics and revealed that sex differences emerged after menarche such that females had reduced iron status relative to males [all R2partial > 0.008; all false discovery rates (FDRs) < 0.05]. Higher socioeconomic status was associated with higher hemoglobin concentrations throughout development (R2partial = 0.005; FDR < 0.001), and the association was greatest during adolescence. Higher hemoglobin concentrations were associated with better cognitive performance during adolescence (R2partial = 0.02; FDR < 0.001) and mediated the association between sex and cognition (mediation effect = -0.107; 95% CI: -0.191, -0.02). Higher hemoglobin concentration was also associated with greater brain white matter integrity in the neuroimaging subsample (R2partial = 0.06, FDR = 0.028).

CONCLUSIONS

Iron status evolves during youth and is lowest in females and individuals of low socioeconomic status during adolescence. Diminished iron status during adolescence has consequences for neurocognition, suggesting that this critical period of neurodevelopment may be an important window for intervention that has the potential to reduce health disparities in at-risk populations.

Rare coding variants as risk modifiers of the 22q11.2 deletion implicate postnatal cortical development in syndromic schizophrenia

22q11.2 deletion is one of the strongest known genetic risk factors for schizophrenia. Recent whole-genome sequencing of schizophrenia cases and controls with this deletion provided an unprecedented opportunity to identify risk modifying genetic variants and investigate their contribution to the pathogenesis of schizophrenia in 22q11.2 deletion syndrome. Here, we apply a novel analytic framework that integrates gene network and phenotype data to investigate the aggregate effects of rare coding variants and identified modifier genes in this etiologically homogenous cohort (223 schizophrenia cases and 233 controls of European descent). Our analyses revealed significant additive genetic components of rare nonsynonymous variants in 110 modifier genes (adjusted P = 9.4E-04) that overall accounted for 4.6% of the variance in schizophrenia status in this cohort, of which 4.0% was independent of the common polygenic risk for schizophrenia. The modifier genes affected by rare coding variants were enriched with genes involved in synaptic function and developmental disorders. Spatiotemporal transcriptomic analyses identified an enrichment of coexpression between modifier and 22q11.2 genes in cortical brain regions from late infancy to young adulthood. Corresponding gene coexpression modules are enriched with brain-specific protein-protein interactions of SLC25A1, COMT, and PI4KA in the 22q11.2 deletion region. Overall, our study highlights the contribution of rare coding variants to the SCZ risk. They not only complement common variants in disease genetics but also pinpoint brain regions and developmental stages critical to the etiology of syndromic schizophrenia.

Activation of Internal Correctness Monitoring Circuitry in Youths With Psychosis Spectrum Symptoms

BACKGROUND

Self-directed performance monitoring is a critical contributor to cognitive performance and general functioning and is impacted by psychiatric symptoms and personality traits, but has been understudied in psychosis-risk states. We have shown that ventral striatum (VS) responds to correctness during cognitive tasks where no explicit feedback is required, and this intrinsic reinforcement response is reduced in schizophrenia.

METHODS

Here, we examined this phenomenon in youths (n = 796, age range 11-22 years) from the Philadelphia Neurodevelopmental Cohort (PNC) performing a working memory functional magnetic resonance imaging task. We hypothesized that VS would respond to internal correctness monitoring, while classic salience network regions, such as dorsal anterior cingulate cortex and anterior insular cortex, would reflect internal error monitoring and that these responses would increase with age. We expected that neurobehavioral measures of performance monitoring would be reduced in youths with subclinical psychosis spectrum features and would correlate with amotivation severity.

RESULTS

Supporting these hypotheses, we found correct>incorrect activation in VS and incorrect>correct activation in anterior cingulate cortex and anterior insular cortex. Furthermore, VS activation was positively correlated with age, reduced in youths with psychosis spectrum features, and inversely correlated with amotivation. However, these patterns were not significant in anterior cingulate cortex and anterior insular cortex.

CONCLUSIONS

These findings advance our understanding of the neural underpinnings of performance monitoring and its impairment in adolescents with psychosis spectrum features. Such understanding can facilitate investigation of the developmental trajectory of normative and aberrant performance monitoring; contribute to early identification of youths at elevated risk for poor academic, occupational, or psychiatric outcomes; and provide potential targets for therapeutic development.

ModelArray: An R package for statistical analysis of fixel-wise data

Diffusion MRI is the dominant non-invasive imaging method used to characterize white matter organization in health and disease. Increasingly, fiber-specific properties within a voxel are analyzed using fixels. While tools for conducting statistical analyses of fixel-wise data exist, currently available tools support only a limited number of statistical models. Here we introduce ModelArray, an R package for mass-univariate statistical analysis of fixel-wise data. At present, ModelArray supports linear models as well as generalized additive models (GAMs), which are particularly useful for studying nonlinear effects in lifespan data. In addition, ModelArray also aims for scalable analysis. With only several lines of code, even large fixel-wise datasets can be analyzed using a standard personal computer. Detailed memory profiling revealed that ModelArray required only limited memory even for large datasets. As an example, we applied ModelArray to fixel-wise data derived from diffusion images acquired as part of the Philadelphia Neurodevelopmental Cohort (n = 938). ModelArray revealed anticipated nonlinear developmental effects in white matter. Moving forward, ModelArray is supported by an open-source software development model that can incorporate additional statistical models and other imaging data types. Taken together, ModelArray provides a flexible and efficient platform for statistical analysis of fixel-wise data.

Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium

Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups-a 'lower brain volume' subgroup (SG1) and an 'higher striatal volume' subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium. Our prior MRI subgrouping models (671 participants; USA, Germany, and China) were applied to both FEP and HC. Participants were assigned into 1 of 4 categories: subgroup 1 (SG1), subgroup 2 (SG2), no subgroup membership ('None'), and mixed SG1 + SG2 subgroups ('Mixed'). Voxel-wise analyses characterized SG1 and SG2 subgroups. Supervised machine learning analyses characterized baseline and remission signatures related to SG1 and SG2 membership. The two dominant patterns of 'lower brain volume' in SG1 and 'higher striatal volume' (with otherwise normal neuromorphology) in SG2 were identified already at the first episode of psychosis. SG1 had a significantly higher proportion of FEP (32%) vs. HC (19%) than SG2 (FEP, 21%; HC, 23%). Clinical multivariate signatures separated the SG1 and SG2 subgroups (balanced accuracy = 64%; p < 0.0001), with SG2 showing higher education but also greater positive psychosis symptoms at first presentation, and an association with symptom remission at 1-year, 5-year, and when timepoints were combined. Neuromorphological subtypes of schizophrenia are already evident at illness onset, separated by distinct clinical presentations, and differentially associated with subsequent remission. These results suggest that the subgroups may be underlying risk phenotypes that could be targeted in future treatment trials and are critical to consider when interpreting neuroimaging literature.

Assessment of Neuroanatomical Endophenotypes of Autism Spectrum Disorder and Association With Characteristics of Individuals With Schizophrenia and the General Population

Importance

Autism spectrum disorder (ASD) is associated with significant clinical, neuroanatomical, and genetic heterogeneity that limits precision diagnostics and treatment.

Objective

To assess distinct neuroanatomical dimensions of ASD using novel semisupervised machine learning methods and to test whether the dimensions can serve as endophenotypes also in non-ASD populations.

Design, Setting, and Participants

This cross-sectional study used imaging data from the publicly available Autism Brain Imaging Data Exchange (ABIDE) repositories as the discovery cohort. The ABIDE sample included individuals diagnosed with ASD aged between 16 and 64 years and age- and sex-match typically developing individuals. Validation cohorts included individuals with schizophrenia from the Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging (PHENOM) consortium and individuals from the UK Biobank to represent the general population. The multisite discovery cohort included 16 internationally distributed imaging sites. Analyses were performed between March 2021 and March 2022.

Main Outcomes and Measures

The trained semisupervised heterogeneity through discriminative analysis models were tested for reproducibility using extensive cross-validations. It was then applied to individuals from the PHENOM and the UK Biobank. It was hypothesized that neuroanatomical dimensions of ASD would display distinct clinical and genetic profiles and would be prominent also in non-ASD populations.

Results

Heterogeneity through discriminative analysis models trained on T1-weighted brain magnetic resonance images of 307 individuals with ASD (mean [SD] age, 25.4 [9.8] years; 273 [88.9%] male) and 362 typically developing control individuals (mean [SD] age, 25.8 [8.9] years; 309 [85.4%] male) revealed that a 3-dimensional scheme was optimal to capture the ASD neuroanatomy. The first dimension (A1: aginglike) was associated with smaller brain volume, lower cognitive function, and aging-related genetic variants (FOXO3; Z = 4.65; P = 1.62 × 10-6). The second dimension (A2: schizophrenialike) was characterized by enlarged subcortical volumes, antipsychotic medication use (Cohen d = 0.65; false discovery rate-adjusted P = .048), partially overlapping genetic, neuroanatomical characteristics to schizophrenia (n = 307), and significant genetic heritability estimates in the general population (n = 14 786; mean [SD] h2, 0.71 [0.04]; P < 1 × 10-4). The third dimension (A3: typical ASD) was distinguished by enlarged cortical volumes, high nonverbal cognitive performance, and biological pathways implicating brain development and abnormal apoptosis (mean [SD] β, 0.83 [0.02]; P = 4.22 × 10-6).

Conclusions and Relevance

This cross-sectional study discovered 3-dimensional endophenotypic representation that may elucidate the heterogeneous neurobiological underpinnings of ASD to support precision diagnostics. The significant correspondence between A2 and schizophrenia indicates a possibility of identifying common biological mechanisms across the 2 mental health diagnoses.

Computing personalized brain functional networks from fMRI using self-supervised deep learning

A novel self-supervised deep learning (DL) method is developed to compute personalized brain functional networks (FNs) for characterizing brain functional neuroanatomy based on functional MRI (fMRI). Specifically, a DL model of convolutional neural networks with an encoder-decoder architecture is developed to compute personalized FNs directly from fMRI data. The DL model is trained to optimize functional homogeneity of personalized FNs without utilizing any external supervision in an end-to-end fashion. We demonstrate that a DL model trained on fMRI scans from the Human Connectome Project can identify personalized FNs and generalizes well across four different datasets. We further demonstrate that the identified personalized FNs are informative for predicting individual differences in behavior, brain development, and schizophrenia status. Taken together, the self-supervised DL allows for rapid, generalizable computation of personalized FNs.

Intrinsic activity development unfolds along a sensorimotor-association cortical axis in youth

Animal studies of neurodevelopment have shown that recordings of intrinsic cortical activity evolve from synchronized and high amplitude to sparse and low amplitude as plasticity declines and the cortex matures. Leveraging resting-state functional MRI (fMRI) data from 1,033 youths (ages 8-23 years), we find that this stereotyped refinement of intrinsic activity occurs during human development and provides evidence for a cortical gradient of neurodevelopmental change. Declines in the amplitude of intrinsic fMRI activity were initiated heterochronously across regions and were coupled to the maturation of intracortical myelin, a developmental plasticity regulator. Spatiotemporal variability in regional developmental trajectories was organized along a hierarchical, sensorimotor-association cortical axis from ages 8 to 18. The sensorimotor-association axis furthermore captured variation in associations between youths' neighborhood environments and intrinsic fMRI activity; associations suggest that the effects of environmental disadvantage on the maturing brain diverge most across this axis during midadolescence. These results uncover a hierarchical neurodevelopmental axis and offer insight into the progression of cortical plasticity in humans.

Psychosis spectrum features, neurocognition and functioning in a longitudinal study of youth with 22q11.2 deletion syndrome

BACKGROUND

Neuropsychiatric disorders are common in 22q11.2 Deletion Syndrome (22q11DS) with about 25% of affected individuals developing schizophrenia spectrum disorders by young adulthood. Longitudinal evaluation of psychosis spectrum features and neurocognition can establish developmental trajectories and impact on functional outcome.

METHODS

157 youth with 22q11DS were assessed longitudinally for psychopathology focusing on psychosis spectrum symptoms, neurocognitive performance and global functioning. We contrasted the pattern of positive and negative psychosis spectrum symptoms and neurocognitive performance differentiating those with more prominent Psychosis Spectrum symptoms (PS+) to those without prominent psychosis symptoms (PS-).

RESULTS

We identified differences in the trajectories of psychosis symptoms and neurocognitive performance between the groups. The PS+ group showed age associated increase in symptom severity, especially negative symptoms and general nonspecific symptoms. Correspondingly, their level of functioning was worse and deteriorated more steeply than the PS- group. Neurocognitive performance was generally comparable in PS+ and PS- groups and demonstrated a similar age-related trajectory. However, worsening executive functioning distinguished the PS+ group from PS- counterparts. Notably, of the three executive function measures examined, only working memory showed a significant difference between the groups in rate of change. Finally, structural equation modeling showed that neurocognitive decline drove the clinical change.

CONCLUSIONS

Youth with 22q11DS and more prominent psychosis features show worsening of symptoms and functional decline driven by neurocognitive decline, most related to executive functions and specifically working memory. The results underscore the importance of working memory in the developmental progression of psychosis.

The Influence of Pandemic-Related Worries During Pregnancy on Child Development at 12 Months

The COVID-19 pandemic has been linked to increased risk for perinatal anxiety and depression among parents, as well as negative consequences for child development. Less is known about how worries arising from the pandemic during pregnancy are related to later child development, nor if resilience factors buffer negative consequences. The current study addresses this question in a prospective longitudinal design. Data was collected from a sub-study ( n  = 184) of a longitudinal study of pregnant individuals (total n  = 1,173). During pregnancy (April 17-July 8, 2020) and the early postpartum period (August 11, 2020-March 2, 2021), participants completed online surveys. At 12 months postpartum (June 17, 2021-March 23, 2022), participants completed online surveys and a virtual laboratory visit, which included parent-child interaction tasks. We found more pregnancy-specific pandemic worries were prospectively related to lower levels of child socioemotional development based on parent report (B=-1.13, SE = .43, p  = .007) and observer ratings (B=-0.13, SE = .07, p  = .045), but not to parent-reported general developmental milestones. Parental emotion regulation in the early postpartum period moderated the association between pregnancy-specific pandemic worries and child socioemotional development such that pregnancy-specific pandemic worries did not related to worse child socioemotional development among parents with high (B=-.02, SE = .10, t=-.14, p = .89) levels of emotion regulation. Findings suggest the negative consequences of parental worry and distress during pregnancy on the early socioemotional development of children in the context of the COVID-19 pandemic. Results highlight that parental emotion regulation may represent a target for intervention to promote parental resilience and support optimized child development.

COVID-19 Worries and Insomnia: A Follow-Up Study

The COVID-19 pandemic was associated with significant increases in sleep disorder symptoms and chronic worry. We previously demonstrated that worry about the pandemic was more strongly associated with subsequent insomnia than the converse during the acute (first 6 months) phase of the pandemic. In this report, we evaluated whether that association held over one year of the pandemic. Participants (n = 3560) completed self-reported surveys of worries about the pandemic, exposure to virus risk factors, and the Insomnia Severity Index on five occasions throughout the course of one year. In cross-sectional analyses, insomnia was more consistently associated with worries about the pandemic than exposure to COVID-19 risk factors. In mixed-effects models, changes in worries predicted changes in insomnia and vice versa. This bidirectional relationship was further confirmed in cross-lagged panel models. Clinically, these findings suggest that during a global disaster, patients who report elevations in either worry or insomnia should be considered for evidence-based treatments for these symptoms to prevent secondary symptoms in the future. Future research should evaluate the extent to which dissemination of evidence-based practices for chronic worry (a core feature of generalized anxiety disorder or illness anxiety disorder) or insomnia reduces the development of co-occurring symptoms during a global disaster.