A Transdiagnostic, Hierarchical Taxonomy of Psychopathology Following Traumatic Brain Injury (HiTOP-TBI).

Psychopathology, including depression, anxiety, and post-traumatic stress, is a significant yet inadequately addressed feature of moderate-severe traumatic brain injury (TBI). Progress in understanding and treating post-TBI psychopathology may be hindered by limitations associated with conventional diagnostic approaches, specifically the Diagnostic and Statistical Manual of Mental Disorders (DSM) and International Classification of Diseases (ICD). The Hierarchical Taxonomy of Psychopathology (HiTOP) offers a promising, transdiagnostic alternative to psychiatric classification that may more effectively capture the experiences of individuals with TBI. However, HiTOP lacks validation in the TBI population. To address this gap, we administered a comprehensive questionnaire battery, including 56 scales assessing homogeneous symptom components and maladaptive traits within HiTOP, to 410 individuals with moderate-severe TBI. We evaluated the reliability and unidimensionality of each scale and revised those with psychometric problems. Using a top-down, exploratory latent variable approach (bass-ackwards modeling), we subsequently constructed a hierarchical model of psychopathological dimensions tailored to TBI. The results showed that, relative to norms, participants with moderate-severe TBI experienced greater problems in the established HiTOP internalizing and detachment spectra, but fewer problems with thought disorder and antagonism. Fourteen of the 56 scales demonstrated psychometric problems, which often appeared reflective of the TBI experience and associated disability. The Hierarchical Taxonomy of Psychopathology Following Traumatic Brain Injury (HiTOP-TBI) model encompassed broad internalizing and externalizing spectra, splitting into seven narrower dimensions: Detachment, Dysregulated Negative Emotionality, Somatic Symptoms, Compensatory and Phobic Reactions, Self-Harm and Psychoticism, Rigid Constraint, and Harmful Substance Use. This study presents the most comprehensive empirical classification of psychopathology after TBI to date. It introduces a novel, TBI-specific transdiagnostic questionnaire battery and model, which addresses the limitations of conventional DSM and ICD diagnoses. The empirical structure of psychopathology after TBI largely aligned with the established HiTOP model (e.g., a detachment spectrum). However, these constructs need to be interpreted in relation to the unique experiences associated with TBI (e.g., considering the injury's impact on the person's social functioning). By overcoming limitations of conventional diagnostic approaches, the HiTOP-TBI model has the potential to accelerate our understanding of the causes, correlates, consequences, and treatment of psychopathology after TBI.

Validation of an abbreviated Big Five personality inventory at large population scale: Psychometric structure and associations with common psychiatric and neurological disorders.

BACKGROUND: The five-factor model of personality, as quantified using instruments such as the Big Five Inventory, consists of broad personality domains including Extraversion, Agreeableness, Conscientiousness, Neuroticism (emotional instability), and Openness. Such instruments typically include >40 items. However, instruments with many items can be unwieldly and a cause of measurement error in clinical and cohort studies where multiple scales are sequenced. Conversely, established 5- and 10-item versions of the Big Five Inventory have poor reliability. Here, we developed and validated an abbreviated 18-item Big Five Inventory that balances efficiency, reliability and sensitivity. METHOD: We analysed three datasets (N = 59,797, N = 21,177, and N = 87,983) from individuals who participated in the online Great British Intelligence Test (GBIT) study, a collaborative citizen science project with BBC2 Horizon. We applied factor analyses (FA), predictive normative modelling, and one-sample t-tests to validate the 18-item version of the Big Five and to investigate its associations with psychiatric and neurological conditions. RESULTS: The 18-item version of the Big Five Inventory had higher validity and retest reliability compared to the other previously shortened versions in the literature, with comparable demographic associations to the full Big Five Inventory. It exhibited strong (i.e. large effect size) associations with psychiatric conditions, and moderate (small-medium) associations with neurological conditions. Neuroticism (emotional instability) was substantially higher in all psychiatric conditions, whereas Conscientiousness, Openness and Extraversion showed differential associations across conditions. CONCLUSION: The newly validated 18-item version of the Big Five provides a convenient means of measuring personality traits that is suitable for deployment in a range of studies. It retains psychometric structure, retest reliability and clinical-group sensitivity, as compared to the full original scale.

The distribution of parent-reported attention-deficit/hyperactivity disorder and subclinical autistic traits in children with and without an ADHD diagnosis.

Background: Autistic traits are often reported to be elevated in children diagnosed with attention-deficit/hyperactivity disorder (ADHD). However, the distribution of subclinical autistic traits in children with ADHD has not yet been established; knowing this may have important implications for diagnostic and intervention processes. The present study proposes a preliminary model of the distribution of parent-reported ADHD and subclinical autistic traits in two independent samples of Australian children with and without an ADHD diagnosis. Methods: Factor mixture modelling was applied to Autism Quotient and Conners' Parent Rating Scale - Revised responses from parents of Australian children aged 6-15 years who participated in one of two independent studies. Results: A 2-factor, 2-class factor mixture model with class varying factor variances and intercepts demonstrated the best fit to the data in both discovery and replication samples. The factors corresponded to the latent constructs of 'autism' and 'ADHD', respectively. Class 1 was characterised by low levels of both ADHD and autistic traits. Class 2 was characterised by high levels of ADHD traits and low-to-moderate levels of autistic traits. The classes were largely separated along diagnostic boundaries. The largest effect size for differences between classes on the Autism Quotient was on the Social Communication subscale. Conclusions: Our findings support the conceptualisation of ADHD as a continuum, whilst confirming the utility of current categorical diagnostic criteria. Results suggest that subclinical autistic traits, particularly in the social communication domain, are unevenly distributed across children with clinically significant levels of ADHD traits. These traits might be profitably screened for in assessments of children with high ADHD symptoms and may also represent useful targets for intervention.

Problematic pornography use and novel patterns of escalating use: A cross-sectional network analysis with two independent samples.

Modern internet pornography allows users to harness sexual novelty in numerous ways, which can be used to overcome desensitisation through increasing volume of use (quantitative tolerance), progressing to more stimulating genres (qualitative escalation), skipping between stimuli (tab-jumping), delaying orgasm ('edging'), and engaging in pornographic binges. However, existing research has not yet evaluated how these potentially reciprocal consumption patterns relate to problematic pornography use (PPU). To this end, we recruited two independent samples of male pornography users (N1 = 1,356, Mage = 36.86, SD = 11.26; N2 = 944, Mage = 38.69, SD = 12.26) and examined the relationships between these behavioural dimensions and self-reported difficulties in controlling one's pornography use. Data were analysed through the network analysis approach (using Gaussian graphical models). As hypothesised, i) quantitative tolerance was centrally placed within the overall network, and ii) acted as a statistical bridge node between other patterns of pornography use (e.g., pornographic binges), and all measured facets of PPU. Our results are consistent with other emerging literature suggesting that tolerance, pornographic binges, tab-jumping, and edging behaviours as relevant features ofPPU, and that upscaling overall usage may connect broader patterns of use with problematic engagement. Clinical and theoretical implications, as well as future research directions, are discussed.

Common genetic factors for uncontrolled eating mechanisms.

OBJECTIVE: Reward-based eating drives are putative mechanisms of uncontrolled eating implicated in obesity and disordered eating (e.g., binge eating). Uncovering the genetic and environmental contributions to reward-related eating, and their genetic correlation with BMI, could shed light on key mechanisms underlying eating and weight-related disorders. METHOD: We conducted a classical twin study to examine how much variance in uncontrolled eating phenotypes and body mass index (BMI) was explained by genetic factors, and the extent that these phenotypes shared common genetic factors. 353 monozygotic twins and 128 dizygotic twins completed the Reward-based Eating Drive 13 scale, which measures three distinct uncontrolled eating phenotypes (loss of control over eating, preoccupation with thoughts about food, and lack of satiety), and a demographic questionnaire which included height and weight for BMI calculation. We estimated additive genetic (A), common environmental (C), and unique environmental (E) factors for each phenotype, as well as their genetic correlations, with a multivariate ACE model. A common pathway model also estimated whether genetic variance in the uncontrolled eating phenotypes was better explained by a common latent uncontrolled eating factor. RESULTS: There were moderate genetic correlations between uncontrolled eating phenotypes and BMI (.26-.41). Variance from the uncontrolled eating phenotypes was also best explained by a common latent uncontrolled eating factor that was explained by additive genetic factors (52%). DISCUSSION: These results suggest that uncontrolled eating phenotypes are heritable traits that also share genetic variance with BMI. This has implications for understanding the cognitive mechanisms that underpin obesity and disordered eating. PUBLIC SIGNIFICANCE: Our study clarifies the degree to which uncontrolled eating phenotypes and BMI are influenced by shared genetics and shows that vulnerability to uncontrolled eating traits is impacted by common genetic factors.

A multiscale characterization of cortical shape asymmetries in early psychosis.

Psychosis has often been linked to abnormal cortical asymmetry, but prior results have been inconsistent. Here, we applied a novel spectral shape analysis to characterize cortical shape asymmetries in patients with early psychosis across different spatial scales. We used the Human Connectome Project for Early Psychosis dataset (aged 16-35), comprising 56 healthy controls (37 males, 19 females) and 112 patients with early psychosis (68 males, 44 females). We quantified shape variations of each hemisphere over different spatial frequencies and applied a general linear model to compare differences between healthy controls and patients with early psychosis. We further used canonical correlation analysis to examine associations between shape asymmetries and clinical symptoms. Cortical shape asymmetries, spanning wavelengths from about 22 to 75 mm, were significantly different between healthy controls and patients with early psychosis (Cohen's d = 0.28-0.51), with patients showing greater asymmetry in cortical shape than controls. A single canonical mode linked the asymmetry measures to symptoms (canonical correlation analysis r = 0.45), such that higher cortical asymmetry was correlated with more severe excitement symptoms and less severe emotional distress. Significant group differences in the asymmetries of traditional morphological measures of cortical thickness, surface area, and gyrification, at either global or regional levels, were not identified. Cortical shape asymmetries are more sensitive than other morphological asymmetries in capturing abnormalities in patients with early psychosis. These abnormalities are expressed at coarse spatial scales and are correlated with specific symptom domains.

Leveraging Online Treatment to Re-examine the Association Between Alcohol Use and Disinhibition.

BACKGROUND: Cognitive disinhibition underpins alcohol and drug use problems. Although higher-risk substance use is consistently associated with poorer disinhibition, current findings may be limited by narrow recruitment methods, which over-represent individuals engaged in traditional treatment services with more severe presentations. We embedded a novel gamified disinhibition task (the Cognitive Impulsivity Suite; CIS) in a national online addiction support service ( https://www.counsellingonline.org.au/ ). METHOD: Participants aged 18 to 64 ( N = 137; 109 women) completed the Alcohol-Use Disorders Identification Test (AUDIT) and Drug Use Disorders Identification Test (DUDIT) along with the CIS, which measures three aspects of disinhibition (Attentional Control, Information-Sampling, and Feedback Monitoring/Shifting). The majority of the sample comprised people with alcohol use, and AUDIT scores were differentiated into 'higher-risk' or 'lower-risk' groups using latent-class analysis. These classes were then regressed against CIS performance measures. RESULTS: Compared to lower-risk, higher-risk alcohol use was associated with poorer attentional control and feedback monitoring/shifting. While higher-risk alcohol use was associated with slower information accumulation, this was only observed for older adults, who appeared to compensate with a more conservative response criterion. CONCLUSIONS: Our results reveal novel relationships between higher-risk alcohol use and specific aspects of disinhibition in participants who sought online addiction help services.

Age at diagnosis and diagnostic delay across attention-deficit hyperactivity and autism spectrums.

BACKGROUND: Despite the known benefits of accurate and timely diagnosis for children with attention-deficit hyperactivity disorder and autism spectrum disorders (autism), for some children this goal is not always achieved. Existing research has explored diagnostic delay for autism and attention-deficit hyperactivity disorder only, and when attention-deficit hyperactivity disorder and autism co-occur, autism has been the focus. No study has directly compared age at diagnosis and diagnostic delay for males and females across attention-deficit hyperactivity disorder, autism and specifically, attention-deficit hyperactivity disorder + autism. METHODS: Australian caregivers (N = 677) of children with attention-deficit hyperactivity disorder, autism or attention-deficit hyperactivity disorder + autism were recruited via social media (n = 594) and the Monash Autism and ADHD Genetics and Neurodevelopment Project (n = 83). Caregivers reported on their child's diagnostic process. Diagnostic delay was the mean difference between general initial developmental concerns and the child's attention-deficit hyperactivity disorder and autism diagnosis. RESULTS: Children with autism were significantly younger at autism diagnosis than the attention-deficit hyperactivity disorder + autism group (ηp2 = 0.06), whereas children with attention-deficit hyperactivity disorder were significantly older at attention-deficit hyperactivity disorder diagnosis than the attention-deficit hyperactivity disorder + autism group (ηp2 = 0.01). Delay to attention-deficit hyperactivity disorder and autism diagnosis was significantly longer in the attention-deficit hyperactivity disorder + autism group compared to attention-deficit hyperactivity disorder (ηp2 = 0.02) and autism (η2 = 0.04) only. Delay to autism diagnosis for females with autism (η2 = 0.06) and attention-deficit hyperactivity disorder + autism (η2 = 0.04) was longer compared to males. CONCLUSIONS: Having attention-deficit hyperactivity disorder + autism and being female were associated with longer delays to diagnosis. The reasons for these delays and possible adverse effects on outcomes require further study.

Leveraging Online Treatment to Re-examine the Association Between Alcohol Use and Disinhibition / Tratamiento Online Como Plataforma Para Re-examinar la Relación Entre el Uso de Alcohol y la Desinhibición Cognitiva

Background: Cognitive disinhibition underpins alcohol and drug use problems. Although higher-risk substance use is consistently associated with poorer disinhibition, current findings may be limited by narrow recruitment methods, which over-represent individuals engaged in traditional treatment services with more severe presentations. We embedded a novel gamified disinhibition task (the Cognitive Impulsivity Suite; CIS) in a national online addiction support service (https://www.counsellingonline.org.au). Method: Participants aged 18 to 64 (N = 137; 109 women) completed the Alcohol-Use Disorders Identification Test (AUDIT) and Drug Use Disorders Identification Test (DUDIT) along with the CIS, which measures three aspects of disinhibition (Attentional Control, Information-Sampling, and Feedback Monitoring/Shifting). The majority of the sample comprised people with alcohol use, and AUDIT scores were differentiated into ‘higher-risk’ or ‘lower-risk’ groups using latent-class analysis. These classes were then regressed against CIS performance measures. Results: Compared to lower-risk, higher-risk alcohol use was associated with poorer attentional control and feedback monitoring/shifting. While higher-risk alcohol use was associated with slower information accumulation, this was only observed for older adults, who appeared to compensate with a more conservative response criterion. Conclusions: Our results reveal novel relationships between higher-risk alcohol use and specific aspects of disinhibition in participants who sought online addiction help services.(AU)

Antecedentes: El uso de alcohol se asocia a mayor desinhibición, pero estos hallazgos podrían no ser representativos de toda la población ya que predominan estudios en contextos especializados y casos severos. Aquí, incorporamos una nueva batería de evaluación de la desinhibición (Cognitive Impulsivity Suite o CIS) en una web de tratamiento online con acceso a una población más amplia (https://www.counsellingonline.org.au). Método: Participantes de 18 a 64 años (N = 137; 109 mujeres) completaron vía web el “Alcohol-Use Disorders Identification Test” y la CIS, que evalúa tres componentes de la desinhibición (Control Atencional, Acumulación de Información y Monitorización / Cambio). Clasificamos en grupos de alto-riesgo versus bajo-riesgo aplicando un análisis de clases latentes sobre las puntuaciones del AUDIT. Usamos análisis de regresión para asociar las dos clases resultantes con las medidas de la CIS. Resultados: Alto-riesgo en el consumo de alcohol se asoció con peor rendimiento en Control Atencional y Monitorización / Cambio. La pertenencia al grupo de alto-riesgo se asoció con menor eficiencia en la acumulación de información en participantes de mayor edad. Conclusiones: Revelamos nuevas asociaciones entre el consumo de alcohol de riesgo y el rendimiento cognitivo en distintos componentes de la desinhibición en participantes que buscaban asistencia en una web de tratamiento online.(AU)

Can hubs of the human connectome be identified consistently with diffusion MRI?

Recent years have seen a surge in the use of diffusion MRI to map connectomes in humans, paralleled by a similar increase in processing and analysis choices. Yet these different steps and their effects are rarely compared systematically. Here, in a healthy young adult population (n = 294), we characterized the impact of a range of analysis pipelines on one widely studied property of the human connectome: its degree distribution. We evaluated the effects of 40 pipelines (comparing common choices of parcellation, streamline seeding, tractography algorithm, and streamline propagation constraint) and 44 group-representative connectome reconstruction schemes on highly connected hub regions. We found that hub location is highly variable between pipelines. The choice of parcellation has a major influence on hub architecture, and hub connectivity is highly correlated with regional surface area in most of the assessed pipelines (ρ > 0.70 in 69% of the pipelines), particularly when using weighted networks. Overall, our results demonstrate the need for prudent decision-making when processing diffusion MRI data, and for carefully considering how different processing choices can influence connectome organization.

Clarifying and extending our understanding of problematic pornography use through descriptions of the lived experience.

Problematic pornography use (PPU) is a complex and growing area of research. However, knowledge of the PPU lived experience is limited. To address this gap, we conducted an online qualitative study with 67 individuals who self-identified as having problematic pornography use (76% male; Mage = 24.70 years, SD = 8.54). Results indicated several dimensions that have not been fully explored in the literature. These included various mental and physical complaints following periods of heavy pornography use, sexual functioning deficits with real partners, and a subjectively altered state of sexual arousal while using pornography. Moreover, we expanded on current knowledge regarding the inner conflict associated with PPU and clarified the ways that users can progress to increasingly intensified patterns of pornography use, such as tolerance/escalation and pornographic binges. Our study highlights the complex and nuanced nature of PPU and provides suggestions for future research and clinical practice.

Conceptualising compulsivity through network analysis: A two-sample study.

Compulsivity is a transdiagnostic construct crucial to understanding multiple psychiatric conditions and problematic repetitive behaviours. Despite being identified as a clinical- and research-relevant construct, there are limited insights into the internal conceptual structure of compulsivity. To provide a more nuanced understanding of compulsivity, the current study estimated the structure of compulsivity (indexed using the previously validated Cambridge-Chicago Compulsivity Trait Scale, CHI-T) among two large-scale and geographically distinct samples using the network estimation method. The samples consisted of a United Kingdom cohort (n = 122,346, 51.4% female, Mean age = 43.7, SD = 16.5, range = 9-86 years) and a South Africa cohort (n = 2674, 65.6% female, Mean age = 24.6, SD = 8.6, range = 18-65 years). Network community analysis demonstrated that compulsivity was constituted of three interrelated dimensions, namely: perfectionism, cognitive rigidity and reward drive. Further, 'Completion leads to soothing' and 'Difficulty moving from task to task' were identified as core (central nodes) to compulsivity. The dimensional structure and central nodes of compulsivity networks were consistent across the two samples. These findings facilitate the conceptualisation and measurement of compulsivity and may contribute to the early detection and treatment of compulsivity-related disorders.

Network-Based Spreading of Gray Matter Changes Across Different Stages of Psychosis.

Importance: Psychotic illness is associated with anatomically distributed gray matter reductions that can worsen with illness progression, but the mechanisms underlying the specific spatial patterning of these changes is unknown. Objective: To test the hypothesis that brain network architecture constrains cross-sectional and longitudinal gray matter alterations across different stages of psychotic illness and to identify whether certain brain regions act as putative epicenters from which volume loss spreads. Design, Settings, and Participants: This case-control study included 534 individuals from 4 cohorts, spanning early and late stages of psychotic illness. Early-stage cohorts included patients with antipsychotic-naive first-episode psychosis (n = 59) and a group of patients receiving medications within 3 years of psychosis onset (n = 121). Late-stage cohorts comprised 2 independent samples of people with established schizophrenia (n = 136). Each patient group had a corresponding matched control group (n = 218). A sample of healthy adults (n = 356) was used to derive representative structural and functional brain networks for modeling of network-based spreading processes. Longitudinal illness-related and antipsychotic-related gray matter changes over 3 and 12 months were examined using a triple-blind randomized placebo-control magnetic resonance imaging study of the antipsychotic-naive patients. All data were collected between April 29, 2008, and January 15, 2020, and analyses were performed between March 1, 2021, and January 14, 2023. Main Outcomes and Measures: Coordinated deformation models were used to estimate the extent of gray matter volume (GMV) change in each of 332 parcellated areas by the volume changes observed in areas to which they were structurally or functionally coupled. To identify putative epicenters of volume loss, a network diffusion model was used to simulate the spread of pathology from different seed regions. Correlations between estimated and empirical spatial patterns of GMV alterations were used to quantify model performance. Results: Of 534 included individuals, 354 (66.3%) were men, and the mean (SD) age was 28.4 (7.4) years. In both early and late stages of illness, spatial patterns of cross-sectional volume differences between patients and controls were more accurately estimated by coordinated deformation models constrained by structural, rather than functional, network architecture (r range, >0.46 to <0.57; P < .01). The same model also robustly estimated longitudinal volume changes related to illness (r ≥ 0.52; P < .001) and antipsychotic exposure (r ≥ 0.50; P < .004). Network diffusion modeling consistently identified, across all 4 data sets, the anterior hippocampus as a putative epicenter of pathological spread in psychosis. Epicenters of longitudinal GMV loss were apparent in posterior cortex early in the illness and shifted to the prefrontal cortex with illness progression. Conclusion and Relevance: These findings highlight a central role for white matter fibers as conduits for the spread of pathology across different stages of psychotic illness, mirroring findings reported in neurodegenerative conditions. The structural connectome thus represents a fundamental constraint on brain changes in psychosis, regardless of whether these changes are caused by illness or medication. Moreover, the anterior hippocampus represents a putative epicenter of early brain pathology from which dysfunction may spread to affect connected areas.

Regional, circuit and network heterogeneity of brain abnormalities in psychiatric disorders.

The substantial individual heterogeneity that characterizes people with mental illness is often ignored by classical case-control research, which relies on group mean comparisons. Here we present a comprehensive, multiscale characterization of the heterogeneity of gray matter volume (GMV) differences in 1,294 cases diagnosed with one of six conditions (attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, depression, obsessive-compulsive disorder and schizophrenia) and 1,465 matched controls. Normative models indicated that person-specific deviations from population expectations for regional GMV were highly heterogeneous, affecting the same area in <7% of people with the same diagnosis. However, these deviations were embedded within common functional circuits and networks in up to 56% of cases. The salience-ventral attention system was implicated transdiagnostically, with other systems selectively involved in depression, bipolar disorder, schizophrenia and attention-deficit/hyperactivity disorder. Phenotypic differences between cases assigned the same diagnosis may thus arise from the heterogeneous localization of specific regional deviations, whereas phenotypic similarities may be attributable to the dysfunction of common functional circuits and networks.

Mechanisms of cognitive disinhibition explain individual differences in adult attention deficit hyperactivity disorder traits.

BACKGROUND: Attention deficit hyperactivity disorder (ADHD) in adults is strongly associated with psychiatric comorbidity and functional impairment. Here, we aimed to use a newly developed online cognitive battery with strong psychometric properties for measuring individual differences in three cognitive mechanisms proposed to underlie ADHD traits in adults: 1) attentional control - the ability to mobilize cognitive resources to stop a prepotent motor response; 2) information sampling/gathering - adequate sampling of information in a stimulus detection task prior to making a decision; and 3) shifting - the ability to adapt behavior in response to positive and negative contingencies. METHODS: This cross-sectional and correlational study recruited 650 adults (330 males) aged 18-69 years (M = 33.06; MD = 31.00; SD = 10.50), with previously diagnosed ADHD (n = 329) and those from the general community without a history of ADHD (n = 321). Self-report measures of ADHD traits (i.e., inattention/disorganization, impulsivity, hyperactivity) and the cognitive battery were completed online. RESULTS: Latent class analysis, exploratory structural equation modeling and factor mixture modeling revealed self-reported ADHD traits formed a unidimensional and approximately normally distributed phenotype. Bayesian structural equation modeling demonstrated that all three mechanisms measured by the cognitive battery, explained unique, incremental variance in ADHD traits, with a total of 15.9% explained in the ADHD trait factor. CONCLUSIONS: Attentional control and shifting, as well as the less researched cognitive process of information gathering, explain individual difference variance in self-reported ADHD traits with potential to yield genetic and neurobiological insights into adult ADHD.

Trans-ancestry meta-analysis of genome wide association studies of inhibitory control.

Deficits in effective executive function, including inhibitory control are associated with risk for a number of psychiatric disorders and significantly impact everyday functioning. These complex traits have been proposed to serve as endophenotypes, however, their genetic architecture is not yet well understood. To identify the common genetic variation associated with inhibitory control in the general population we performed the first trans-ancestry genome wide association study (GWAS) combining data across 8 sites and four ancestries (N = 14,877) using cognitive traits derived from the stop-signal task, namely - go reaction time (GoRT), go reaction time variability (GoRT SD) and stop signal reaction time (SSRT). Although we did not identify genome wide significant associations for any of the three traits, GoRT SD and SSRT demonstrated significant and similar SNP heritability of 8.2%, indicative of an influence of genetic factors. Power analyses demonstrated that the number of common causal variants contributing to the heritability of these phenotypes is relatively high and larger sample sizes are necessary to robustly identify associations. In Europeans, the polygenic risk for ADHD was significantly associated with GoRT SD and the polygenic risk for schizophrenia was associated with GoRT, while in East Asians polygenic risk for schizophrenia was associated with SSRT. These results support the potential of executive function measures as endophenotypes of neuropsychiatric disorders. Together these findings provide the first evidence indicating the influence of common genetic variation in the genetic architecture of inhibitory control quantified using objective behavioural traits derived from the stop-signal task.

Modeling relations between event-related potential factors and broader versus narrower dimensions of externalizing psychopathology.

The organization of the Hierarchical Taxonomy of Psychopathology (HiTOP) model provides unique opportunities to evaluate whether neural risk measures operate as indicators of broader latent liabilities (e.g., externalizing proneness) or narrower expressions (e.g., antisociality and alcohol abuse). Following this approach, the current study recruited a sample of 182 participants (54% female) who completed measures of externalizing psychopathology (also internalizing) and associated traits. Participants also completed three tasks (Flanker-No Threat, Flanker-Threat, and Go/No-Go tasks) with event-related potential (ERP) measurement. Three variants of two research domain criteria (RDoC)-based neurophysiological indicators-P3 and error-related negativity (ERN)-were extracted from these tasks and used to model two latent ERP factors. Scores on these two ERP factors independently predicted externalizing factor scores when accounting for their covariance with sex-suggesting distinct neural processes contributing to the broad externalizing factor. No predictive relation with the broad internalizing factor was found for either ERP factor. Analyses at the finer-grained level revealed no unique predictive relations of either ERP factor with any specific externalizing symptom variable when accounting for the broad externalizing factor, indicating that ERN and P3 index general liability for problems in this spectrum. Overall, this study provides new insights about neural processes in externalizing psychopathology at broader and narrower levels of the HiTOP hierarchy. (PsycInfo Database Record (c) 2023 APA, all rights reserved).

Value-based decision-making network functional connectivity correlates with substance use and delay discounting behaviour among young adults.

Substance use disorders are characterized by reduced control over the quantity and frequency of psychoactive substance use and impairments in social and occupational functioning. They are associated with poor treatment compliance and high rates of relapse. Identification of neural susceptibility biomarkers that index risk for developing a substance use disorder can facilitate earlier identification and treatment. Here, we aimed to identify the neurobiological correlates of substance use frequency and severity amongst a sample of 1,200 (652 females) participants aged 22-37 years from the Human Connectome Project. Substance use behaviour across eight classes (alcohol, tobacco, marijuana, sedatives, hallucinogens, cocaine, stimulants, opiates) was measured using the Semi-Structured Assessment for the Genetics of Alcoholism. We explored the latent organization of substance use behaviour using a combination of exploratory structural equation modelling, latent class analysis, and factor mixture modelling to reveal a unidimensional continuum of substance use behaviour. Participants could be rank ordered along a unitary severity spectrum encompassing frequency of use of all eight substance classes, with factor score estimates generated to represent each participant's substance use severity. Factor score estimates and delay discounting scores were compared with functional connectivity in 650 participants with imaging data using the Network-based Statistic. This neuroimaging cohort excludes participants aged 31 and over. We identified brain regions and connections correlated with impulsive decision-making and poly-substance use, with the medial orbitofrontal, lateral prefrontal and posterior parietal cortices emerging as key hubs. Functional connectivity of these networks could serve as susceptibility biomarkers for substance use disorders, informing earlier identification and treatment.

Precision behavioral phenotyping as a strategy for uncovering the biological correlates of psychopathology.

Our capacity to measure diverse aspects of human biology has developed rapidly in the past decades, but the rate at which these techniques have generated insights into the biological correlates of psychopathology has lagged far behind. The slow progress is partly due to the poor sensitivity, specificity and replicability of many findings in the literature, which have in turn been attributed to small effect sizes, small sample sizes and inadequate statistical power. A commonly proposed solution is to focus on large, consortia-sized samples. Yet it is abundantly clear that increasing sample sizes will have a limited impact unless a more fundamental issue is addressed: the precision with which target behavioral phenotypes are measured. Here, we discuss challenges, outline several ways forward and provide worked examples to demonstrate key problems and potential solutions. A precision phenotyping approach can enhance the discovery and replicability of associations between biology and psychopathology.

Gradients of striatal function in antipsychotic-free first-episode psychosis and schizotypy.

Both psychotic illness and subclinical psychosis-like experiences (PLEs) have been associated with cortico-striatal dysfunction. This work has largely relied on a discrete parcellation of the striatum into distinct functional areas, but recent evidence suggests that the striatum comprises multiple overlapping and smoothly varying gradients (i.e., modes) of functional organization. Here, we investigated two of these functional connectivity modes, previously associated with variations in the topographic patterning of cortico-striatal connectivity (first-order gradient), and dopaminergic innervation of the striatum (second-order gradient), and assessed continuities in striatal function from subclinical to clinical domains. We applied connectopic mapping to resting-state fMRI data to obtain the first-order and second-order striatal connectivity modes in two distinct samples: (1) 56 antipsychotic-free patients (26 females) with first-episode psychosis (FEP) and 27 healthy controls (17 females); and (2) a community-based cohort of 377 healthy individuals (213 females) comprehensively assessed for subclinical PLEs and schizotypy. The first-order "cortico-striatal" and second-order "dopaminergic" connectivity gradients were significantly different in FEP patients compared to controls bilaterally. In the independent sample of healthy individuals, variations in the left first-order "cortico-striatal" connectivity gradient were associated with inter-individual differences in a factor capturing general schizotypy and PLE severity. The presumed cortico-striatal connectivity gradient was implicated in both subclinical and clinical cohorts, suggesting that variations in its organization may represent a neurobiological trait marker across the psychosis continuum. Disruption of the presumed dopaminergic gradient was only noticeable in patients, suggesting that neurotransmitter dysfunction may be more apparent to clinical illness.