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.

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.

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.

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.

Measuring Compulsivity as a Self-Reported Multidimensional Transdiagnostic Construct: Large-Scale (N = 182,000) Validation of the Cambridge-Chicago Compulsivity Trait Scale

Compulsivity has potential transdiagnostic relevance to a range of psychiatric disorders, but it has not been well-characterized and there are few existing measures available for measuring the construct across clinical and nonclinical samples that have been validated at large population scale. We aimed to characterize the multidimensional latent structure of self-reported compulsivity in a population-based sample of British children and adults (N = 182,145) using the Cambridge-Chicago Compulsivity Trait Scale (CHI-T). Exploratory structural equation modeling provided evidence for a correlated two-factor model consisting of (a) Perfectionism and (b) Reward Drive dimensions. Evidence was obtained for discriminant validity in relation to the big five personality dimensions and acceptable test-retest reliability. The CHI-T, here validated at extremely large scale, is suitable for use in studies seeking to understand the correlates and basis of compulsivity in clinical and nonclinical participants. We provide extensive normative data to facilitate interpretation in future studies.

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.

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.

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.

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).

Against the use of the Strengths and Difficulties Questionnaire for Aboriginal and Torres Strait Islander children aged 2-15 years

OBJECTIVE

The Strengths and Difficulties Questionnaire is a widely used screening tool for emotional and behavioural problems in children. Recent quantitative analyses have raised concerns regarding its structural validity in Aboriginal and Torres Strait Islander communities. This paper aims to extend upon existing findings by analysing the factor structure of both the parent- and teacher-reported Strengths and Difficulties Questionnaire in this population across a broader age range than in previous studies.

METHODS

Participants were the caregivers and teachers of 1624 Aboriginal and Torres Strait Islander children (820 male, 804 female) aged 2-15 years from Waves 2-11 of the Longitudinal Study of Indigenous Children. The majority of children were Aboriginal living in major cities and inner regional areas. Internal consistency was estimated with McDonald's Omega. Exploratory structural equation modelling was conducted to investigate the factor structure of the parent-reported and teacher-reported versions of the Strengths and Difficulties Questionnaire.

RESULTS

Responses from teachers demonstrated higher internal consistency than responses from parents, which was unacceptably low across most age groups. The purported five-factor structure of the Strengths and Difficulties Questionnaire failed to be replicated across both parent- and teacher-reported questionnaires. The results of bifactor and hierarchical exploratory structural equation models also failed to approximate the higher-order summary scales. These results indicate that the Strengths and Difficulties Questionnaire subscales and summary scores do not provide a valid index of emotional and behavioural problems in Aboriginal and Torres Strait Islander children.

CONCLUSION

The Strengths and Difficulties Questionnaire should not be used with Aboriginal and Torres Strait Islander children.

Dissecting Schizotypy and Its Association With Cognition and Polygenic Risk for Schizophrenia in a Nonclinical Sample

Schizotypy is a multidimensional construct that captures a continuum of risk for developing schizophrenia-spectrum psychopathology. Existing 3-factor models of schizotypy, consisting of positive, negative, and disorganized dimensions have yielded mixed evidence of genetic continuity with schizophrenia using polygenic risk scores. Here, we propose an approach that involves splitting positive and negative schizotypy into more specific subdimensions that are phenotypically continuous with distinct positive symptoms and negative symptoms recognized in clinical schizophrenia. We used item response theory to derive high-precision estimates of psychometric schizotypy using 251 self-report items obtained from a non-clinical sample of 727 (424 females) adults. These subdimensions were organized hierarchically using structural equation modeling into 3 empirically independent higher-order dimensions enabling associations with polygenic risk for schizophrenia to be examined at different levels of phenotypic generality and specificity. Results revealed that polygenic risk for schizophrenia was associated with variance specific to delusional experiences (γ = 0.093, P = .001) and reduced social interest and engagement (γ = 0.076, P = .020), and these effects were not mediated via the higher-order general, positive, or negative schizotypy factors. We further fractionated general intellectual functioning into fluid and crystallized intelligence in 446 (246 females) participants that underwent onsite cognitive assessment. Polygenic risk scores explained 3.6% of the variance in crystallized intelligence. Our precision phenotyping approach could be used to enhance the etiologic signal in future genetic association studies and improve the detection and prevention of schizophrenia-spectrum psychopathology.

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.

Country-level gender inequality is associated with structural differences in the brains of women and men

Gender inequality across the world has been associated with a higher risk to mental health problems and lower academic achievement in women compared to men. We also know that the brain is shaped by nurturing and adverse socio-environmental experiences. Therefore, unequal exposure to harsher conditions for women compared to men in gender-unequal countries might be reflected in differences in their brain structure, and this could be the neural mechanism partly explaining women's worse outcomes in gender-unequal countries. We examined this through a random-effects meta-analysis on cortical thickness and surface area differences between adult healthy men and women, including a meta-regression in which country-level gender inequality acted as an explanatory variable for the observed differences. A total of 139 samples from 29 different countries, totaling 7,876 MRI scans, were included. Thickness of the right hemisphere, and particularly the right caudal anterior cingulate, right medial orbitofrontal, and left lateral occipital cortex, presented no differences or even thicker regional cortices in women compared to men in gender-equal countries, reversing to thinner cortices in countries with greater gender inequality. These results point to the potentially hazardous effect of gender inequality on women's brains and provide initial evidence for neuroscience-informed policies for gender equality.

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.

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.

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.

A cross-national validation of the Internet Severity and Activities Addiction Questionnaire (ISAAQ)

Problematic usage of the internet (PUI) is of increasing concern in a digitalized world. While several screening tools have been developed to assess PUI, few have had their psychometric properties evaluated, and existing scales are also not typically designed to quantify both the severity of PUI and the nature of diverse problematic online activities. The Internet Severity and Activities Addiction Questionnaire (ISAAQ), consisting of a severity scale (ISAAQ Part A) and an online activities scale (ISAAQ part B) was previously developed to address these limitations. This study undertook psychometric validation of ISAAQ Part A using data from three countries. The optimal one-factor structure of ISAAQ Part A was determined in a large dataset from South Africa, then validated against datasets from the United Kingdom and United States. The scale had high Cronbach's alpha (≥0.9 in each country). A working operational cut-off point was determined to distinguish between those with some degree of problematic use and those without (ISAAQ Part A), and insight was given into the types of potentially problematic activities that may encompass PUI (ISAAQ Part B).

Circuit-Based Approaches to Understanding Corticostriatothalamic Dysfunction Across the Psychosis Continuum

Dopamine is known to play a role in the pathogenesis of psychotic symptoms, but the mechanisms driving dopaminergic dysfunction in psychosis remain unclear. Considerable attention has focused on the role of corticostriatothalamic (CST) circuits, given that they regulate and are modulated by the activity of dopaminergic cells in the midbrain. Preclinical studies have proposed multiple models of CST dysfunction in psychosis, each prioritizing different brain regions and pathophysiological mechanisms. A particular challenge is that CST circuits have undergone considerable evolutionary modification across mammals, complicating comparisons across species. Here, we consider preclinical models of CST dysfunction in psychosis and evaluate the degree to which they are supported by evidence from human resting-state functional magnetic resonance imaging studies conducted across the psychosis continuum, ranging from subclinical schizotypy to established schizophrenia. In partial support of some preclinical models, human studies indicate that dorsal CST and hippocampal-striatal functional dysconnectivity are apparent across the psychosis spectrum and may represent a vulnerability marker for psychosis. In contrast, midbrain dysfunction may emerge when symptoms warrant clinical assistance and may thus be a trigger for illness onset. The major difference between clinical and preclinical findings is the strong involvement of the dorsal CST in the former, consistent with an increasing prominence of this circuitry in the primate brain. We close by underscoring the need for high-resolution characterization of phenotypic heterogeneity in psychosis to develop a refined understanding of how the dysfunction of specific circuit elements gives rise to distinct symptom profiles.

Examining the neural correlates of error awareness in a large fMRI study

Goal-directed behavior is dependent upon the ability to detect errors and implement appropriate posterror adjustments. Accordingly, several studies have explored the neural activity underlying error-monitoring processes, identifying the insula cortex as crucial for error awareness and reporting mixed findings with respect to the anterior cingulate cortex (ACC). Variable patterns of activation have previously been attributed to insufficient statistical power. We therefore sought to clarify the neural correlates of error awareness in a large event-related functional magnetic resonance imaging (fMRI) study. Four hundred and two healthy participants undertook the error awareness task, a motor Go/No-Go response inhibition paradigm in which participants were required to indicate their awareness of commission errors. Compared to unaware errors, aware errors were accompanied by significantly greater activity in a network of regions, including the insula cortex, supramarginal gyrus (SMG), and midline structures, such as the ACC and supplementary motor area (SMA). Error awareness activity was related to indices of task performance and dimensional measures of psychopathology in selected regions, including the insula, SMG, and SMA. Taken together, we identified a robust and reliable neural network associated with error awareness.

Transdiagnostic phenotypes of compulsive behavior and associations with psychological, cognitive, and neurobiological affective processing

Compulsivity is a poorly understood transdiagnostic construct thought to underlie multiple disorders, including obsessive-compulsive disorder, addictions, and binge eating. Our current understanding of the causes of compulsive behavior remains primarily based on investigations into specific diagnostic categories or findings relying on one or two laboratory measures to explain complex phenotypic variance. This proof-of-concept study drew on a heterogeneous sample of community-based individuals (N = 45; 18-45 years; 25 female) exhibiting compulsive behavioral patterns in alcohol use, eating, cleaning, checking, or symmetry. Data-driven statistical modeling of multidimensional markers was utilized to identify homogeneous subtypes that were independent of traditional clinical phenomenology. Markers were based on well-defined measures of affective processing and included psychological assessment of compulsivity, behavioral avoidance, and stress, neurocognitive assessment of reward vs. punishment learning, and biological assessment of the cortisol awakening response. The neurobiological validity of the subtypes was assessed using functional magnetic resonance imaging. Statistical modeling identified three stable, distinct subtypes of compulsivity and affective processing, which we labeled "Compulsive Non-Avoidant", "Compulsive Reactive" and "Compulsive Stressed". They differed meaningfully on validation measures of mood, intolerance of uncertainty, and urgency. Most importantly, subtypes captured neurobiological variance on amygdala-based resting-state functional connectivity, suggesting they were valid representations of underlying neurobiology and highlighting the relevance of emotion-related brain networks in compulsive behavior. Although independent larger samples are needed to confirm the stability of subtypes, these data offer an integrated understanding of how different systems may interact in compulsive behavior and provide new considerations for guiding tailored intervention decisions.

Cortical and subcortical neuroanatomical signatures of schizotypy in 3004 individuals assessed in a worldwide ENIGMA study

Neuroanatomical abnormalities have been reported along a continuum from at-risk stages, including high schizotypy, to early and chronic psychosis. However, a comprehensive neuroanatomical mapping of schizotypy remains to be established. The authors conducted the first large-scale meta-analyses of cortical and subcortical morphometric patterns of schizotypy in healthy individuals, and compared these patterns with neuroanatomical abnormalities observed in major psychiatric disorders. The sample comprised 3004 unmedicated healthy individuals (12-68 years, 46.5% male) from 29 cohorts of the worldwide ENIGMA Schizotypy working group. Cortical and subcortical effect size maps with schizotypy scores were generated using standardized methods. Pattern similarities were assessed between the schizotypy-related cortical and subcortical maps and effect size maps from comparisons of schizophrenia (SZ), bipolar disorder (BD) and major depression (MDD) patients with controls. Thicker right medial orbitofrontal/ventromedial prefrontal cortex (mOFC/vmPFC) was associated with higher schizotypy scores (r = 0.067, p_FDR = 0.02). The cortical thickness profile in schizotypy was positively correlated with cortical abnormalities in SZ (r = 0.285, p_spin = 0.024), but not BD (r = 0.166, p_spin = 0.205) or MDD (r = -0.274, p_spin = 0.073). The schizotypy-related subcortical volume pattern was negatively correlated with subcortical abnormalities in SZ (rho = -0.690, p_spin = 0.006), BD (rho = -0.672, p_spin = 0.009), and MDD (rho = -0.692, p_spin = 0.004). Comprehensive mapping of schizotypy-related brain morphometry in the general population revealed a significant relationship between higher schizotypy and thicker mOFC/vmPFC, in the absence of confounding effects due to antipsychotic medication or disease chronicity. The cortical pattern similarity between schizotypy and schizophrenia yields new insights into a dimensional neurobiological continuity across the extended psychosis phenotype.

Understanding the Diversity of Pharmacotherapeutic Management of ADHD With Co-occurring Autism: An Australian Cross-Sectional Survey

OBJECTIVES

Attention deficit hyperactivity disorder (ADHD) frequently co-occurs with other neurodevelopmental diagnoses, such as autism spectrum disorder (autism), which can make clinical decision making around symptom management challenging for clinicians. There is a paucity of research examining pharmacotherapeutic management of children who have ADHD with co-occurring diagnoses. We aimed to report on the co-occurring diagnoses and symptom profile of children, and report on medication use, stratified by ADHD, autism and ADHD + autism diagnoses.

METHODS AND MATERIALS

Caregivers of 505 children (2-18 years) with ADHD (n = 239), autism (n = 117), and co-occurring ADHD + autism (n = 149) completed a questionnaire on current medication use and clinical rating scales about their child's symptoms, as part of a broader project investigating diagnosis and management of symptoms in children with ADHD or autism.

RESULTS

The parents of the ADHD group reported a higher proportion of their children had learning disorders (17.15%) and speech and language disorders (4.60%) compared to the parents of the autism and ADHD + autism groups. Parents of the ADHD + autism group reported higher proportions of intellectual disability (5.37%), oppositional defiant disorder (20.13%), anxiety (38.93%), depression (6.71%) and genetic conditions (3.36%) in their children, in comparison to the parents of the ADHD and autism groups. Children with ADHD were reported to be taking a higher proportion of psychotropic medication (90%), followed by ADHD + autism (86%) and autism (39%). The parents of children with ADHD + autism reported a higher proportion of non-stimulant ADHD medication (25.5%), antipsychotic (18.79%), antidepressant (22.15%) and melatonin (31.54%) use by their children, compared to the parents of the ADHD and autism groups.

CONCLUSIONS

A similar proportion of children with ADHD + autism and ADHD were reported to be taking medication. However, the types of medication taken were different, as expected with reported co-occurring diagnoses. The complexity of symptoms and diagnoses in ADHD + autism warrants targeted research to optimize management and therapeutic outcomes.

The Monash Autism-ADHD genetics and neurodevelopment (MAGNET) project design and methodologies: a dimensional approach to understanding neurobiological and genetic aetiology

Background

ASD and ADHD are prevalent neurodevelopmental disorders that frequently co-occur and have strong evidence for a degree of shared genetic aetiology. Behavioural and neurocognitive heterogeneity in ASD and ADHD has hampered attempts to map the underlying genetics and neurobiology, predict intervention response, and improve diagnostic accuracy. Moving away from categorical conceptualisations of psychopathology to a dimensional approach is anticipated to facilitate discovery of data-driven clusters and enhance our understanding of the neurobiological and genetic aetiology of these conditions. The Monash Autism-ADHD genetics and neurodevelopment (MAGNET) project is one of the first large-scale, family-based studies to take a truly transdiagnostic approach to ASD and ADHD. Using a comprehensive phenotyping protocol capturing dimensional traits central to ASD and ADHD, the MAGNET project aims to identify data-driven clusters across ADHD-ASD spectra using deep phenotyping of symptoms and behaviours; investigate the degree of familiality for different dimensional ASD-ADHD phenotypes and clusters; and map the neurocognitive, brain imaging, and genetic correlates of these data-driven symptom-based clusters.

Methods

The MAGNET project will recruit 1,200 families with children who are either typically developing, or who display elevated ASD, ADHD, or ASD-ADHD traits, in addition to affected and unaffected biological siblings of probands, and parents. All children will be comprehensively phenotyped for behavioural symptoms, comorbidities, neurocognitive and neuroimaging traits and genetics.

Conclusion

The MAGNET project will be the first large-scale family study to take a transdiagnostic approach to ASD-ADHD, utilising deep phenotyping across behavioural, neurocognitive, brain imaging and genetic measures.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13229-021-00457-3.

Potential role for immune-related genes in autism spectrum disorders: Evidence from genome-wide association meta-analysis of autistic traits

The clinical heterogeneity of autism spectrum disorders majorly challenges their genetic study. Autism spectrum disorders symptoms occur in milder forms in the general population, as autistic-like traits, and share genetic factors with autism spectrum disorders. Here, we investigate the genetics of individual autistic-like traits to improve our understanding of autism spectrum disorders. We meta-analysed four population-based genome-wide association studies investigating four autistic-like traits – ‘attention-to-detail’, ‘imagination’, ‘rigidity’ and ‘social-skills’ (n = 4600). Using autism spectrum disorder summary statistics from the Psychiatric Genomic Consortium (N = 46,350), we applied polygenic risk score analyses to understand the genetic relationship between autism spectrum disorders and autistic-like traits. Using MAGMA, we performed gene-based and gene co-expression network analyses to delineate involved genes and pathways. We identified two novel genome-wide significant loci – rs6125844 and rs3731197 – associated with ‘attention-to-detail’. We demonstrated shared genetic aetiology between autism spectrum disorders and ‘rigidity’. Analysing top variants and genes, we demonstrated a role of the immune-related genes RNF114, CDKN2A, KAZN, SPATA2 and ZNF816A in autistic-like traits. Brain-based genetic expression analyses further linked autistic-like traits to genes involved in immune functioning, and neuronal and synaptic signalling. Overall, our findings highlight the potential of the autistic-like trait–based approach to address the challenges of genetic research in autism spectrum disorders. We provide novel insights showing a potential role of the immune system in specific autism spectrum disorder dimensions.

Genetic influences on hub connectivity of the human connectome

Brain network hubs are both highly connected and highly inter-connected, forming a critical communication backbone for coherent neural dynamics. The mechanisms driving this organization are poorly understood. Using diffusion-weighted magnetic resonance imaging in twins, we identify a major role for genes, showing that they preferentially influence connectivity strength between network hubs of the human connectome. Using transcriptomic atlas data, we show that connected hubs demonstrate tight coupling of transcriptional activity related to metabolic and cytoarchitectonic similarity. Finally, comparing over thirteen generative models of network growth, we show that purely stochastic processes cannot explain the precise wiring patterns of hubs, and that model performance can be improved by incorporating genetic constraints. Our findings indicate that genes play a strong and preferential role in shaping the functionally valuable, metabolically costly connections between connectome hubs.

Examining the relationship between altered brain functional connectome and disinhibition across 33 impulsive and compulsive behaviours

Impulsive and compulsive problem behaviours are associated with a variety of mental disorders. Latent phenotyping indicates the expression of impulsive and compulsive problem behaviours is predominantly governed by a transdiagnostic 'disinhibition' phenotype. In a cohort of 117 individuals, recruited as part of the Neuroscience in Psychiatry Network (NSPN), we examined how brain functional connectome and network properties relate to disinhibition. Reduced functional connectivity within a subnetwork of frontal (especially right inferior frontal gyrus), occipital and parietal regions was linked to disinhibition. Findings provide insights into neurobiological pathways underlying the emergence of impulsive and compulsive disorders.

Distress-driven impulsivity interacts with cognitive inflexibility to determine addiction-like eating

BACKGROUND

Researchers are only just beginning to understand the neurocognitive drivers of addiction-like eating behaviours, a highly distressing and relatively common condition. Two constructs have been consistently linked to addiction-like eating: distress-driven impulsivity and cognitive inflexibility. Despite a large body of addiction research showing that impulsivity-related traits can interact with other risk markers to result in an especially heightened risk for addictive behaviours, no study to date has examined how distress-driven impulsivity interacts with cognitive inflexibility in relation to addiction-like eating behaviours. The current study examines the interactive contribution of distress-driven impulsivity and cognitive inflexibility to addiction-like eating behaviours.

METHOD

One hundred and thirty-one participants [mean age 21 years (SD = 2.3), 61.8% female] completed the modified Yale Food Addiction Scale, the S-UPPS-P impulsivity scale, and a cognitive flexibility task. A bootstrap method was used to examine the associations between distress-driven impulsivity, cognitive inflexibility, and their interaction with addiction-like eating behaviours.

RESULTS

There was a significant interaction effect between distress-driven impulsivity and cognitive flexibility (P = 0.03). The follow-up test revealed that higher distress-driven impulsivity was associated with more addiction-like eating behaviours among participants classified as cognitively inflexible only.

CONCLUSION

The current findings shed light on the mechanisms underlying addiction-like eating behaviours, including how traits and cognition might interact to drive them. The findings also suggest that interventions that directly address distress-driven impulsivity and cognitive inflexibility might be effective in reducing risk for addiction-like eating and related disorders.

Measurement of the problematic usage of the Internet unidimensional quasitrait continuum with item response theory

Problematic usage of the internet (PUI) describes maladaptive use of online resources and is recognized as a growing worldwide issue. Here, we refined the Internet Addiction Test (IAT) for use as a screening tool to measure generalized internet use problems in normative samples. Analysis of response data with parametric unidimensional item response theory identified 10 items of the IAT that measured most of the PUI latent trait continuum with high precision in a subsample of 816 participants with meaningful variance in internet use problems. Selected items may characterize minor, or early stages of, PUI by measuring a preoccupation with the Internet, motivations to use online activities to escape aversive emotional experiences and regulate mood, as well as secrecy, defensiveness, and interpersonal conflict associated with internet use. Summed scores on these 10 items demonstrated a strong correlation with full-length IAT scores and comparable, or better, convergence with measures of impulsivity and compulsivity. Proposed cut-off scores differentiated between individuals potentially at risk of developing PUI from those with few self-reported internet use problems with good sensitivity and specificity. Differential item function testing revealed measurement equivalence between the sexes, Caucasians and non-Caucasians. However, evidence for differential test functioning between independent samples drawn from South Africa and the United States of America suggests that raw scores cannot be meaningfully compared between different geographic regions. These findings have implications for conceptualization and measurement of PUI in normative samples.

We provide recommendations for measuring symptoms of problematic usage of the internet, which can be identified in a subset of the population using our refined version of the IAT and suggested cut-off scores. Relevant self-reported internet use problems include a preference for online over face-to-face social interactions, use of the internet to regulate emotions, excessive online engagement, interpersonal conflict, and emotional withdrawal following cessation of internet use.

A multivariate analysis of the association between corticostriatal functional connectivity and psychosis-like experiences in the general community

Dysfunction of dorsal corticostriatal (CST) circuitry is thought to play an important role in psychosis. Here, we use multivariate analysis to characterize covariance between CST functional connectivity and psychosis-like experiences (PLEs) in non-clinical individuals. In 353 healthy adults (155 males), we use partial least squares (PLS) to identify latent variables (LV) describing covariance between seven PLE questionnaire measures and functional connectivity estimated between each of six striatal seed regions and the rest of the brain using multiband resting-state fMRI. Hypothesis-driven PLS of the dorsal caudate (DC) seed identified one significant LV, accounting for 23.88% of covariance, with loadings from nearly all PLE subscales. Cortical regions implicated in this LV comprise anterior cingulate and left dorsolateral prefrontal cortex. Lower connectivity between these cortical areas and the DC seed was associated with more severe PLEs. Using multivariate modeling, we identified an association between dorsal CST connectivity and PLEs in the general community that implicates similar brain regions to those identified in patient groups. Our results highlight that the severity of both positive/negative symptom-like PLEs is related with functional coupling between the DC and dorsolateral PFC, suggesting this neural circuit may play a role in mediating risk for general psychosis-related psychopathology.

Trans-diagnostic measurement of impulsivity and compulsivity: A review of self-report tools

INTRODUCTION

Impulsivity and compulsivity are important constructs, relevant to understanding behaviour in the general population, as well as in particular mental disorders (e.g. attention deficit hyperactivity disorder, obsessive-compulsive disorder). The current paper provides a narrative review of self-report impulsivity and compulsivity scales.

METHODS

A literature search was conducted using the following terms: ("impulsivity" OR "compulsivity") AND ("self-report" OR "questionnaire" OR "psychometric" OR "scale").

RESULTS

25 impulsive and 11 compulsive scales were identified, which varied considerably in psychometric properties, convenience, and validity. For impulsivity, the most commonly used scales were the BIS and the UPPS-P, whilst for compulsivity, the Padua Inventory was commonly used. The majority of compulsivity scales measured OCD symptoms (obsessions and compulsions) rather than being trans-diagnostic or specific to compulsivity (as opposed to obsessions). Scales capable of overcoming these limitations were highlighted.

DISCUSSION

This review provides clarity regarding relative advantages and disadvantages of different scales relevant to the measurement of impulsivity and compulsivity in many contexts. Areas for further research and refinement are highlighted.

Reward-Related Attentional Capture Moderates the Association between Fear-Driven Motives and Heavy Drinking

BACKGROUND

To date, there has been little investigation on how motivational and cognitive mechanisms interact to influence problematic drinking behaviours. Towards this aim, the current study examined whether reward-related attentional capture is associated with reward, fear (relief), and habit drinking motives, and further, whether it interacts with these motives in relation to problematic drinking patterns.

METHODS

Ninety participants (mean age = 34.8 years, SD = 9.1, 54% male) who reported having consumed alcohol in the past month completed an online visual search task that measured reward-related attentional capture as well as the Habit Reward Fear Scale, a measure of drinking motives. Participants also completed measures of psychological distress, impulsivity, compulsive drinking, and consumption items of Alcohol Use Disorders Identification Test. Regression analyses examined the associations between motives for alcohol consumption and reward-related attentional capture, as well as the associations between reward-related attentional capture, motives, and their interaction, with alcohol consumption and problems.

RESULTS

Greater reward-related attentional capture was associated with greater reward motives. Further, reward-related attentional capture also interacted with fear motives in relation to alcohol consumption. Follow-up analyses showed that this interaction was driven by greater fear motives being associated with heavier drinking among those with lower reward-related attentional capture (i.e., "goal-trackers").

CONCLUSION

These findings have implications for understanding how cognition may interact with motives in association with problematic drinking. Specifically, the findings highlight different potential pathways to problematic drinking according to an individual's cognitive-motivational profile and may inform tailored interventions to target profile-specific mechanisms. Finally, these findings offer support for contemporary models of addiction that view excessive goal-directed behaviour under negative affect as a critical contributor to addictive behaviours.

The role of Experiential Avoidance in transdiagnostic compulsive behavior: A structural model analysis

Compulsivity is recognized as a transdiagnostic phenotype, underlying a variety of addictive and obsessive-compulsive behaviors. However, current understanding of how it should be operationalized and the processes contributing to its development and maintenance is limited. The present study investigated if there was a relationship between the affective process Experiential Avoidance (EA), an unwillingness to tolerate negative internal experiences, and the frequency and severity of transdiagnostic compulsive behaviors. A large sample of adults (N = 469) completed online questionnaires measuring EA, psychological distress and the severity of seven obsessive-compulsive and addiction-related behaviors. Using structural equation modelling, results indicated a one-factor model of compulsivity was superior to the two-factor model (addictive- vs OCD-related behaviors). The effect of EA on compulsivity was fully mediated by psychological distress, which in turn had a strong direct effect on compulsivity. This suggests distress is a key mechanism in explaining why people with high EA are more prone to compulsive behaviors. The final model explained 41% of the variance in compulsivity, underscoring the importance of these constructs as likely risk and maintenance factors for compulsive behavior. Implications for designing effective psychological interventions for compulsivity are discussed.

Impact of CYP2C19 genotype-predicted enzyme activity on hippocampal volume, anxiety, and depression

Cytochrome P450 C19 (CYP2C19) metabolizes exogenous and endogenous compounds. Although CYP2C19 is highly expressed in the liver, it is also expressed in the brain during early life. Previous human and animal studies have linked CYP2C19 genotype-predicted enzyme activity to hippocampal volumes, depressive symptoms, and anxiety-like behaviors. We examined these promising associations in a general community sample comprising 386 Caucasian adults with no history of psychiatric or neurological illnesses. Contrary to previous findings, CYP2C19 genotype-predicted enzyme activity was not associated with hippocampal volumes, nor depressive and anxiety symptoms. Interstudy differences in CYP2C19 frequencies and/or study methodology may explain this discrepancy.

Common mechanisms of executive attention underlie executive function and effortful control in children

Executive Function (EF) and Effortful Control (EC) have traditionally been viewed as distinct constructs related to cognition and temperament during development. More recently, EF and EC have been implicated in top-down self-regulation - the goal-directed control of cognition, emotion, and behavior. We propose that executive attention, a limited-capacity attentional resource subserving goal-directed cognition and behavior, is the common cognitive mechanism underlying the self-regulatory capacities captured by EF and EC. We addressed three related questions: (a) Do behavioral ratings of EF and EC represent the same self-regulation construct? (b) Is this self-regulation construct explained by a common executive attention factor as measured by performance on cognitive tasks? and (c) Does the executive attention factor explain additional variance in attention deficit hyperactivity disorder (ADHD) problems to behavioral ratings of self-regulation? Measures of performance on complex span, general intelligence, and response inhibition tasks were obtained from 136 preadolescent children (M = 11 years, 10 months, SD = 8 months), along with self- and parent-reported EC, and parent-reported EF, and ADHD problems. Results from structural equation modeling demonstrated that behavioral ratings of EF and EC measured the same self-regulation construct. Cognitive tasks measured a common executive attention factor that significantly explained 30% of the variance in behavioral ratings of self-regulation. Executive attention failed to significantly explain additional variance in ADHD problems beyond that explained by behavioral ratings of self-regulation. These findings raise questions about the utility of task-based cognitive measures in research and clinical assessment of self-regulation and psychopathology in developmental samples.

Problematic use of the Internet is a unidimensional quasi-trait with impulsive and compulsive subtypes

BACKGROUND

Problematic use of the Internet has been highlighted as needing further study by international bodies, including the European Union and American Psychiatric Association. Knowledge regarding the optimal classification of problematic use of the Internet, subtypes, and associations with clinical disorders has been hindered by reliance on measurement instruments characterized by limited psychometric properties and external validation.

METHODS

Non-treatment seeking individuals were recruited from the community of Stellenbosch, South Africa (N = 1661), and Chicago, United States of America (N = 827). Participants completed an online version of the Internet Addiction Test, a widely used measure of problematic use of the Internet consisting of 20-items, measured on a 5-point Likert-scale. The online questions also included demographic measures, time spent engaging in different online activities, and clinical scales. The psychometric properties of the Internet Addiction Test, and potential problematic use of the Internet subtypes, were characterized using factor analysis and latent class analysis.

RESULTS

Internet Addiction Test data were optimally conceptualized as unidimensional. Latent class analysis identified two groups: those essentially free from Internet use problems, and those with problematic use of the Internet situated along a unidimensional spectrum. Internet Addiction Test scores clearly differentiated these groups, but with different optimal cut-offs at each site. In the larger Stellenbosch dataset, there was evidence for two subtypes of problematic use of the Internet that differed in severity: a lower severity "impulsive" subtype (linked with attention-deficit hyperactivity disorder), and a higher severity "compulsive" subtype (linked with obsessive-compulsive personality traits).

CONCLUSIONS

Problematic use of the Internet as measured by the Internet Addiction Test reflects a quasi-trait - a unipolar dimension in which most variance is restricted to a subset of people with problems regulating Internet use. There was no evidence for subtypes based on the type of online activities engaged in, which increased similarly with overall severity of Internet use problems. Measures of comorbid psychiatric symptoms, along with impulsivity, and compulsivity, appear valuable for differentiating clinical subtypes and could be included in the development of new instruments for assessing the presence and severity of Internet use problems.

Fractionation of impulsive and compulsive trans-diagnostic phenotypes and their longitudinal associations

OBJECTIVE

Young adulthood is a crucial neurodevelopmental period during which impulsive and compulsive problem behaviours commonly emerge. While traditionally considered diametrically opposed, impulsive and compulsive symptoms tend to co-occur. The objectives of this study were as follows: (a) to identify the optimal trans-diagnostic structural framework for measuring impulsive and compulsive problem behaviours, and (b) to use this optimal framework to identify common/distinct antecedents of these latent phenotypes.

METHOD

In total, 654 young adults were recruited as part of the Neuroscience in Psychiatry Network, a population-based cohort in the United Kingdom. The optimal trans-diagnostic structural model capturing 33 types of impulsive and compulsive problem behaviours was identified. Baseline predictors of subsequent impulsive and compulsive trans-diagnostic phenotypes were characterised, along with cross-sectional associations, using partial least squares.

RESULTS

Current problem behaviours were optimally explained by a bi-factor model, which yielded dissociable measures of impulsivity and compulsivity, as well as a general disinhibition factor. Impulsive problem behaviours were significantly explained by prior antisocial and impulsive personality traits, male gender, general distress, perceived dysfunctional parenting and teasing/arguments within friendships. Compulsive problem behaviours were significantly explained by prior compulsive traits and female gender.

CONCLUSION

This study demonstrates that trans-diagnostic phenotypes of 33 impulsive and compulsive problem behaviours are identifiable in young adults, utilising a bi-factor model based on responses to a single questionnaire. Furthermore, these phenotypes have different antecedents. The findings yield a new framework for fractionating impulsivity and compulsivity, and suggest different early intervention targets to avert emergence of problem behaviours. This framework may be useful for future biological and clinical dissection of impulsivity and compulsivity.

Transdiagnostic variations in impulsivity and compulsivity in obsessive-compulsive disorder and gambling disorder correlate with effective connectivity in cortical-striatal-thalamic-cortical circuits

Individual differences in impulsivity and compulsivity is thought to underlie vulnerability to a broad range of disorders and are closely tied to cortical-striatal-thalamic-cortical function. However, whether impulsivity and compulsivity in clinical disorders is continuous with the healthy population and explains cortical-striatal-thalamic-cortical dysfunction across different disorders remains unclear. Here, we characterized the relationship between cortical-striatal-thalamic-cortical effective connectivity, estimated using dynamic causal modelling of resting-state functional magnetic resonance imaging data, and dimensional phenotypes of impulsivity and compulsivity in two symptomatically distinct but phenotypically related disorders, obsessive-compulsive disorder and gambling disorder. 487 online participants provided data for modelling of dimensional phenotypes. These data were combined with 34 obsessive-compulsive disorder patients, 22 gambling disorder patients, and 39 healthy controls, who underwent functional magnetic resonance imaging. Three core dimensions were identified: disinhibition, impulsivity, and compulsivity. Patients' scores on these dimensions were continuously distributed with the healthy participants, supporting a continuum model of psychopathology. Across all participants, higher disinhibition correlated with lower bottom-up connectivity in the dorsal circuit and greater bottom-up connectivity in the ventral circuit, and higher compulsivity correlated with lower bottom-up connectivity in the dorsal circuit. In patients, higher clinical severity was also linked to lower bottom-up connectivity in the dorsal circuit, but these findings were independent of phenotypic variation, demonstrating convergence towards behaviourally and clinically relevant changes in brain dynamics. Effective connectivity did not differ as a function of traditional diagnostic labels and only weak associations were observed for functional connectivity measures. Together, our results demonstrate that cortical-striatal-thalamic-cortical dysfunction across obsessive-compulsive disorder and gambling disorder may be better characterized by dimensional phenotypes than diagnostic comparisons, supporting investigation of quantitative liability phenotypes.

A case-control genome-wide association study of ADHD discovers a novel association with the tenascin R (TNR) gene

It is well-established that there is a strong genetic contribution to the aetiology of attention deficit hyperactivity disorder (ADHD). Here, we employed a hypothesis-free genome-wide association study (GWAS) design in a sample of 480 clinical childhood ADHD cases and 1208 controls to search for novel genetic risk loci for ADHD. DNA was genotyped using Illumina's Human Infinium PsychArray-24v1.2., and the data were subsequently imputed to the 1000 Genomes reference panel. Rigorous quality control and pruning of genotypes at both individual subject and single nucleotide polymorphism (SNP) levels was performed. Polygenic risk score (PGRS) analysis revealed that ADHD case-control status was explained by genetic risk for ADHD, but no other major psychiatric disorders. Logistic regression analysis was performed genome-wide to test the association between SNPs and ADHD case-control status. We observed a genome-wide significant association (p = 3.15E-08) between ADHD and rs6686722, mapped to the Tenascin R (TNR) gene. Members of this gene family are extracellular matrix glycoproteins that play a role in neural cell adhesion and neurite outgrowth. Suggestive evidence of associations with ADHD was observed for an additional 111 SNPs (⩽9.91E-05). Although intriguing, the association between DNA variation in the TNR gene and ADHD should be viewed as preliminary given the small sample size of this discovery dataset.

Genome-wide association study reveals novel genetic locus associated with intra-individual variability in response time

Intra-individual response time variability (IIRTV) is proposed as a viable endophenotype for many psychiatric disorders, particularly attention-deficit hyperactivity disorder (ADHD). Here we assessed whether IIRTV was associated with common DNA variation genome-wide and whether IIRTV mediated the relationship between any associated loci and self-reported ADHD symptoms. A final data set from 857 Australian young adults (489 females and 368 males; Mage = 22.14 years, SDage = 4.82 years) who completed five response time tasks and self-reported symptoms of ADHD using the Conners' Adult ADHD Rating Scale was used. Principal components analysis (PCA) on these response time measures (standard deviation of reaction times and the intra-individual coefficient of variation) produced two variability factors (labelled response selection and selective attention). To understand the genetic drivers of IIRTV we performed a genome-wide association analysis (GWAS) on these PCA-derived indices of IIRTV. For the selective attention variability factor, we identified one single-nucleotide polymorphism (SNP) attaining genome-wide significance; rs62182100 in the HDAC4 gene located on chromosome 2q37. A bootstrapping mediation analysis demonstrated that the selective attention variability factor mediated the relationship between rs62182100 and self-reported ADHD symptoms. Our findings provide the first evidence of a genome-wide significant SNP association with IIRTV and support the potential utility of IIRTV as a valid endophenotype for ADHD symptoms. However, limitations of this study suggest that these observations should be interpreted with caution until replication samples become available.

A Hierarchical Model of Inhibitory Control

Inhibitory control describes the suppression of goal-irrelevant stimuli and behavioral responses. Current developmental taxonomies distinguish between Response Inhibition – the ability to suppress a prepotent motor response, and Attentional Inhibition – the ability to resist interference from distracting stimuli. Response Inhibition and Attentional Inhibition have exhibited moderately strong positive correlations in previous studies, suggesting they are closely related cognitive abilities. These results may reflect the use of cognitive tasks combining Stimulus–Stimulus- and Stimulus–Response-conflict as indicators of both constructs, which may have conflated their empirical association. Additionally, previous statistical modeling studies have not controlled for individual differences in Working Memory Capacity, which may account for some of the empirical overlap between Response Inhibition and Attentional Inhibition. The aim of the current study was to test a hierarchical model of inhibitory control that specifies Working Memory Capacity as a higher-order cognitive construct. Response Inhibition and Attentional Inhibition were conceptualized as lower-order cognitive mechanisms that should be empirically independent constructs apart from their shared reliance on Working Memory Capacity for active maintenance of goal-relevant representations. Measures of performance on modified stimulus–response compatibility tasks, complex memory span, and non-selective stopping tasks were obtained from 136 preadolescent children (M = 11 years, 10 months, SD = 8 months). Consistent with hypotheses, results from Structural Equation Modeling demonstrated that the Response Inhibition and Attentional Inhibition factors were empirically independent constructs that exhibited partial statistical dependence on the Working Memory Capacity factor. These findings have important implications for current theories and models of inhibitory control during development.