A statistical method for image-mediated association studies discovers genes and pathways associated with four brain disorders.

Brain imaging and genomics are critical tools enabling characterization of the genetic basis of brain disorders. However, imaging large cohorts is expensive and may be unavailable for legacy datasets used for genome-wide association studies (GWASs). Using an integrated feature selection/aggregation model, we developed an image-mediated association study (IMAS), which utilizes borrowed imaging/genomics data to conduct association mapping in legacy GWAS cohorts. By leveraging the UK Biobank image-derived phenotypes (IDPs), the IMAS discovered genetic bases underlying four neuropsychiatric disorders and verified them by analyzing annotations, pathways, and expression quantitative trait loci (eQTLs). A cerebellar-mediated mechanism was identified to be common to the four disorders. Simulations show that, if the goal is identifying genetic risk, our IMAS is more powerful than a hypothetical protocol in which the imaging results were available in the GWAS dataset. This implies the feasibility of reanalyzing legacy GWAS datasets without conducting additional imaging, yielding cost savings for integrated analysis of genetics and imaging.

Genome-Wide Association Study of Obsessive-Compulsive Symptoms including 33,943 individuals from the general population.

While 1-2% of individuals meet the criteria for a clinical diagnosis of obsessive-compulsive disorder (OCD), many more (~13-38%) experience subclinical obsessive-compulsive symptoms (OCS) during their life. To characterize the genetic underpinnings of OCS and its genetic relationship to OCD, we conducted the largest genome-wide association study (GWAS) meta-analysis of parent- or self-reported OCS to date (N = 33,943 with complete phenotypic and genome-wide data), combining the results from seven large-scale population-based cohorts from Sweden, the Netherlands, England, and Canada (including six twin cohorts and one cohort of unrelated individuals). We found no genome-wide significant associations at the single-nucleotide polymorphism (SNP) or gene-level, but a polygenic risk score (PRS) based on the OCD GWAS previously published by the Psychiatric Genetics Consortium (PGC-OCD) was significantly associated with OCS (Pfixed = 3.06 × 10-5). Also, one curated gene set (Mootha Gluconeogenesis) reached Bonferroni-corrected significance (Ngenes = 28, Beta = 0.79, SE = 0.16, Pbon = 0.008). Expression of genes in this set is high at sites of insulin mediated glucose disposal. Dysregulated insulin signaling in the etiology of OCS has been suggested by a previous study describing a genetic overlap of OCS with insulin signaling-related traits in children and adolescents. We report a SNP heritability of 4.1% (P = 0.0044) in the meta-analyzed GWAS, and heritability estimates based on the twin cohorts of 33-43%. Genetic correlation analysis showed that OCS were most strongly associated with OCD (rG = 0.72, p = 0.0007) among all tested psychiatric disorders (N = 11). Of all 97 tested phenotypes, 24 showed a significant genetic correlation with OCS, and 66 traits showed concordant directions of effect with OCS and OCD. OCS have a significant polygenic contribution and share genetic risk with diagnosed OCD, supporting the hypothesis that OCD represents the extreme end of widely distributed OCS in the population.

White matter diffusion estimates in obsessive-compulsive disorder across 1653 individuals: machine learning findings from the ENIGMA OCD Working Group.

White matter pathways, typically studied with diffusion tensor imaging (DTI), have been implicated in the neurobiology of obsessive-compulsive disorder (OCD). However, due to limited sample sizes and the predominance of single-site studies, the generalizability of OCD classification based on diffusion white matter estimates remains unclear. Here, we tested classification accuracy using the largest OCD DTI dataset to date, involving 1336 adult participants (690 OCD patients and 646 healthy controls) and 317 pediatric participants (175 OCD patients and 142 healthy controls) from 18 international sites within the ENIGMA OCD Working Group. We used an automatic machine learning pipeline (with feature engineering and selection, and model optimization) and examined the cross-site generalizability of the OCD classification models using leave-one-site-out cross-validation. Our models showed low-to-moderate accuracy in classifying (1) "OCD vs. healthy controls" (Adults, receiver operator characteristic-area under the curve = 57.19 ± 3.47 in the replication set; Children, 59.8 ± 7.39), (2) "unmedicated OCD vs. healthy controls" (Adults, 62.67 ± 3.84; Children, 48.51 ± 10.14), and (3) "medicated OCD vs. unmedicated OCD" (Adults, 76.72 ± 3.97; Children, 72.45 ± 8.87). There was significant site variability in model performance (cross-validated ROC AUC ranges 51.6-79.1 in adults; 35.9-63.2 in children). Machine learning interpretation showed that diffusivity measures of the corpus callosum, internal capsule, and posterior thalamic radiation contributed to the classification of OCD from HC. The classification performance appeared greater than the model trained on grey matter morphometry in the prior ENIGMA OCD study (our study includes subsamples from the morphometry study). Taken together, this study points to the meaningful multivariate patterns of white matter features relevant to the neurobiology of OCD, but with low-to-moderate classification accuracy. The OCD classification performance may be constrained by site variability and medication effects on the white matter integrity, indicating room for improvement for future research.

Effect of CYP2D6 genetic variation on patient-reported symptom improvement and side effects among children and adolescents treated with amphetamines.

OBJECTIVES: Amphetamine-based medications are recommended as a first-line pharmacotherapy for the treatment of attention-deficit/hyperactivity disorder in children and adolescents. However, the efficacy and tolerability of these medications vary across individuals, which could be related to interindividual differences in amphetamine metabolism. This study examined if genotype-predicted phenotypes of the cytochrome P450 isozyme CYP2D6 were associated with self-reported side effects and symptom improvement in youth treated with amphetamines. METHODS: Two hundred fourteen participants aged 6-24 who had a history of past or current amphetamine treatment were enrolled from Western Canada. Amphetamine dose and duration information was collected from the participants along with questions regarding adherence, concomitant medications, symptom improvement and side effects. DNA was extracted from saliva samples and genotyped for CYP2D6 . Binomial logistic regression models were used to determine the effect of CYP2D6 metabolizer phenotype with and without correction for phenoconversion on self-reported symptom improvement and side effects. RESULTS: Genotype-predicted CYP2D6 poor metabolizers had significantly higher odds of reporting symptom improvement when compared to intermediate metabolizers (OR = 3.67, 95% CI = 1.15-11.7, P  = 0.029) after correction for phenoconversion and adjusting for sex, age, dose, duration, and adherence. There was no association between CYP2D6 metabolizer phenotype and self-reported side effects. CONCLUSION: Our findings indicate that phenoconverted and genotype-predicted CYP2D6 poor metabolizer phenotype is significantly associated with higher odds of symptom improvement in children and adolescents treated with amphetamine. If replicated, these results could inform the development of future dosing guidelines for amphetamine treatment in children and adolescents.

Dataset factors associated with age-related changes in brain structure and function in neurodevelopmental conditions.

With brain structure and function undergoing complex changes throughout childhood and adolescence, age is a critical consideration in neuroimaging studies, particularly for those of individuals with neurodevelopmental conditions. However, despite the increasing use of large, consortium-based datasets to examine brain structure and function in neurotypical and neurodivergent populations, it is unclear whether age-related changes are consistent between datasets and whether inconsistencies related to differences in sample characteristics, such as demographics and phenotypic features, exist. To address this, we built models of age-related changes of brain structure (regional cortical thickness and regional surface area; N = 1218) and function (resting-state functional connectivity strength; N = 1254) in two neurodiverse datasets: the Province of Ontario Neurodevelopmental Network and the Healthy Brain Network. We examined whether deviations from these models differed between the datasets, and explored whether these deviations were associated with demographic and clinical variables. We found significant differences between the two datasets for measures of cortical surface area and functional connectivity strength throughout the brain. For regional measures of cortical surface area, the patterns of differences were associated with race/ethnicity, while for functional connectivity strength, positive associations were observed with head motion. Our findings highlight that patterns of age-related changes in the brain may be influenced by demographic and phenotypic characteristics, and thus future studies should consider these when examining or controlling for age effects in analyses.

The genetic architecture of youth anxiety: a study protocol.

BACKGROUND: Anxiety disorders are the most common psychiatric problems among Canadian youth and typically have an onset in childhood or adolescence. They are characterized by high rates of relapse and chronicity, often resulting in substantial impairment across the lifespan. Genetic factors play an important role in the vulnerability toward anxiety disorders. However, genetic contribution to anxiety in youth is not well understood and can change across developmental stages. Large-scale genetic studies of youth are needed with detailed assessments of symptoms of anxiety disorders and their major comorbidities to inform early intervention or preventative strategies and suggest novel targets for therapeutics and personalization of care. METHODS: The Genetic Architecture of Youth Anxiety (GAYA) study is a Pan-Canadian effort of clinical and genetic experts with specific recruitment sites in Calgary, Halifax, Hamilton, Toronto, and Vancouver. Youth aged 10-19 (n = 13,000) will be recruited from both clinical and community settings and will provide saliva samples, complete online questionnaires on demographics, symptoms of mental health concerns, and behavioural inhibition, and complete neurocognitive tasks. A subset of youth will be offered access to a self-managed Internet-based cognitive behavioral therapy resource. Analyses will focus on the identification of novel genetic risk loci for anxiety disorders in youth and assess how much of the genetic risk for anxiety disorders is unique or shared across the life span. DISCUSSION: Results will substantially inform early intervention or preventative strategies and suggest novel targets for therapeutics and personalization of care. Given that the GAYA study will be the biggest genomic study of anxiety disorders in youth in Canada, this project will further foster collaborations nationally and across the world.

Racial/Ethnic Disparities in Psychiatric Traits and Diagnoses within a Community-based Sample of Children and Youth: Disparités raciales/ethniques dans les traits et diagnostics psychiatriques au sein d'un échantillon communautaire d'enfants et de jeunes.

OBJECTIVE: Racial/ethnic disparities in the prevalence of psychiatric disorders have been reported, but have not accounted for the prevalence of the traits that underlie these disorders. Examining rates of diagnoses in relation to traits may yield a clearer understanding of the degree to which racial/ethnic minority youth in Canada differ in their access to care. We sought to examine differences in self/parent-reported rates of diagnoses for obsessive-compulsive disorder (OCD), attention-deficit/hyperactivity disorder (ADHD) and anxiety disorders after adjusting for differences in trait levels between youth from three racial/ethnic groups: White, South Asian and East Asian. METHOD: We collected parent or self-reported ratings of OCD, ADHD and anxiety traits and diagnoses for 6- to 17-year-olds from a Canadian general population sample (Spit for Science). We examined racial/ethnic differences in trait levels and the odds of reporting a diagnosis using mixed-effects linear models and logistic regression models. RESULTS: East Asian (N = 1301) and South Asian (N = 730) youth reported significantly higher levels of OCD and anxiety traits than White youth (N = 6896). East Asian and South Asian youth had significantly lower odds of reporting a diagnosis for OCD (odds ratio [OR]East Asian = 0.08 [0.02, 0.41]; ORSouth Asian = 0.05 [0.00, 0.81]), ADHD (OREast Asian = 0.27 [0.16, 0.45]; ORSouth Asian = 0.09 [0.03, 0.30]) and anxiety (OREast Asian = 0.21 [0.11, 0.39]; ORSouth Asian = 0.12 [0.05, 0.32]) than White youth after accounting for psychiatric trait levels. CONCLUSIONS: These results suggest a discrepancy between trait levels of OCD, ADHD and anxiety and rates of diagnoses for East Asian and South Asian youth. This discrepancy may be due to increased barriers for ethnically diverse youth to access mental health care. Efforts to understand and mitigate these barriers in Canada are needed.

We know that there is there are differences in the prevalence of childhood mental illnesses by race/ethnic group, which may be related to disproportionate access to mental health care. What is unknown is whether there this difference in prevalence is related to differences in the presence of symptoms for mental illness or whether children and youth from marginalized racial/ethnic groups have symptoms but are not getting diagnosed. This information is needed to understand the degree to which children and youth from marginalized race/ethnicity groups are accessing mental health care in Canada. We tested the differences in reported symptoms and diagnosis of three common and impairing childhood-onset disorders (obsessive-compulsive disorder­OCD), attention-deficit/hyperactivity disorder­ADHD and anxiety disorders) in children and youth (6­17 years of age) living in Canada that were from three racial/ethnic groups: White, South Asian and East Asian. East Asian and South Asian youth reported significantly higher levels of OCD and anxiety traits than White youth. However, East Asian and South Asian youth were significantly less likely than White youth to have a reported diagnosis of OCD, ADHD or anxiety even after accounting for symptom levels for each disorder. Our findings suggest that East and South Asian children are less likely than White children to get a diagnosis for common mental illness even if they have symptoms of that mental illness. This gap in receiving a diagnosis might be because of more barriers to mental health care for children and youth from marginalized racial/ethnic groups but we need more research to pinpoint the cause.

A protocol for the formative evaluation of the implementation of patient-reported outcome measures in child and adolescent mental health services as part of a learning health system.

BACKGROUND: Mental health conditions affect one in seven young people and research suggests that current mental health services are not meeting the needs of most children and youth. Learning health systems are an approach to enhancing services through rapid, routinized cycles of continuous learning and improvement. Patient-reported outcome measures provide a key data source for learning health systems. They have also been shown to improve outcomes for patients when integrated into routine clinical care. However, implementing these measures into health systems is a challenging process. This paper describes a protocol for a formative evaluation of the implementation of patient-reported measures in a newly operational child and adolescent mental health centre in Calgary, Canada. The purpose is to optimize the collection and use of patient-reported outcome measures. Our specific objectives are to assess the implementation progress, identify barriers and facilitators to implementation, and explore patient, caregivers and clinician experiences of using these measures in routine clinical care. METHODS: This study is a mixed-methods, formative evaluation using the Consolidated Framework for Implementation Research. Participants include patients and caregivers who have used the centre's services, as well as leadership, clinical and support staff at the centre. Focus groups and semi-structured interviews will be conducted to assess barriers and facilitators to the implementation and sustainability of the use of patient-reported outcome measures, as well as individuals' experiences with using these measures within clinical care. The data generated by the patient-reported measures over the first five months of the centre's operation will be analyzed to understand implementation progress, as well as validity of the chosen measures for the centres' population. DISCUSSION: The findings of this evaluation will help to identify and address the factors that are affecting the successful implementation of patient-reported measures at the centre. They will inform the co-design of strategies to improve implementation with key stakeholders, which include patients, clinical staff, and leadership at the centre. To our knowledge, this is the first study of the implementation of patient-reported outcome measures in child and adolescent mental health services and our findings can be used to enhance future implementation efforts in similar settings.

Is irritability multidimensional: Psychometrics of The Irritability and Dysregulation of Emotion Scale (TIDES-13).

Irritability is a common, impairing, and potentially multifaceted manifestation of psychopathology. We designed The Irritability and Dysregulation of Emotion Scale (TIDES-13) to determine whether various expressions of irritability in children and youth form multiple subdimensions with distinct correlates. We administered parent-report (n = 3875, mean age = 8.9) and youth self-report (n = 579, mean age = 15.1) versions of TIDES-13 in a population and community-based sample. We conducted exploratory/confirmatory factor analyses and regression analyses to examine the dimensionality of TIDES-13 and the associations of the scale with age, gender, anxiety, depression, ODD, ADHD traits, and the Affective Reactivity Index (ARI). A higher-order model with a global irritability dimension and four subdimensions, including proneness to anger (PA), internalized negative emotional reactivity (iNER), externalized negative emotional reactivity (eNER), and reactive aggression (RA), showed good to excellent fit in both parent-report and self-report. The global irritability dimension showed excellent internal reliability (⍵Total; parent-report = 0.97, ⍵Total; self-report = 0.95), explained a majority of the item variance (⍵Hierarchical; parent-report = 0.94, ⍵Hierarchical; self-report = 0.90), and was moderately correlated with the ARI (rparent = 0.68, rself = 0.77). Subdimensions PA, eNER, and RA were negatively associated with age in males, whereas iNER was positively associated with age in females. Traits of ODD and ADHD were associated primarily with the global irritability dimension, whereas iNER was strongly associated with anxiety and depression traits over and above the global irritability dimension. Our results support a unidimensional interpretation of irritability in a population sample. However, limited evidence of specific behavioral, age, and sex correlates with particular irritability subdimensions may warrant further investigation.

Altered Error Monitoring and Decreased Flanker Task Accuracy in Pediatric Obsessive-Compulsive Disorder.

The error-related negativity (ERN) and error positivity (Pe) are components of the event-related potential following an error that are potential mechanistic biomarkers of obsessive-compulsive disorder (OCD). The study examined the ERN, Pe, flanker task accuracy, and clinical measures in 105 OCD cases and 105 matched healthy controls (HC) ages 8-18 years. Higher flanker task accuracy in all participants was associated with an increased ERN amplitude and increased difference between Pe and correct positivity amplitudes (ΔPe). Compared to HC, OCD cases had an increased ERN but decreased ΔPe and flanker task accuracy. Those differences were also significant in tic-related and non-tic-related OCD cases compared to HC. A lower ΔPe was associated in cases with an earlier age at OCD symptom onset. The results support the hypothesis that OCD involves defects in an error monitoring system and suggest a reduced ΔPe may compromise error signaling and cause uncertainty about the correctness of a response.

Systematic comparisons of different quality control approaches applied to three large pediatric neuroimaging datasets.

INTRODUCTION: Poor quality T1-weighted brain scans systematically affect the calculation of brain measures. Removing the influence of such scans requires identifying and excluding scans with noise and artefacts through a quality control (QC) procedure. While QC is critical for brain imaging analyses, it is not yet clear whether different QC approaches lead to the exclusion of the same participants. Further, the removal of poor-quality scans may unintentionally introduce a sampling bias by excluding the subset of participants who are younger and/or feature greater clinical impairment. This study had two aims: (1) examine whether different QC approaches applied to T1-weighted scans would exclude the same participants, and (2) examine how exclusion of poor-quality scans impacts specific demographic, clinical and brain measure characteristics between excluded and included participants in three large pediatric neuroimaging samples. METHODS: We used T1-weighted, resting-state fMRI, demographic and clinical data from the Province of Ontario Neurodevelopmental Disorders network (Aim 1: n = 553, Aim 2: n = 465), the Healthy Brain Network (Aim 1: n = 1051, Aim 2: n = 558), and the Philadelphia Neurodevelopmental Cohort (Aim 1: n = 1087; Aim 2: n = 619). Four different QC approaches were applied to T1-weighted MRI (visual QC, metric QC, automated QC, fMRI-derived QC). We used tetrachoric correlation and inter-rater reliability analyses to examine whether different QC approaches excluded the same participants. We examined differences in age, mental health symptoms, everyday/adaptive functioning, IQ and structural MRI-derived brain indices between participants that were included versus excluded following each QC approach. RESULTS: Dataset-specific findings revealed mixed results with respect to overlap of QC exclusion. However, in POND and HBN, we found a moderate level of overlap between visual and automated QC approaches (rtet=0.52-0.59). Implementation of QC excluded younger participants, and tended to exclude those with lower IQ, and lower everyday/adaptive functioning scores across several approaches in a dataset-specific manner. Across nearly all datasets and QC approaches examined, excluded participants had lower estimates of cortical thickness and subcortical volume, but this effect did not differ by QC approach. CONCLUSION: The results of this study provide insight into the influence of QC decisions on structural pediatric imaging analyses. While different QC approaches exclude different subsets of participants, the variation of influence of different QC approaches on clinical and brain metrics is minimal in large datasets. Overall, implementation of QC tends to exclude participants who are younger, and those who have more cognitive and functional impairment. Given that automated QC is standardized and can reduce between-study differences, the results of this study support the potential to use automated QC for large pediatric neuroimaging datasets.

Latin American Trans-ancestry INitiative for OCD genomics (LATINO): Study protocol.

Obsessive-compulsive disorder (OCD) is a debilitating psychiatric disorder. Worldwide, its prevalence is ~2% and its etiology is mostly unknown. Identifying biological factors contributing to OCD will elucidate underlying mechanisms and might contribute to improved treatment outcomes. Genomic studies of OCD are beginning to reveal long-sought risk loci, but >95% of the cases currently in analysis are of homogenous European ancestry. If not addressed, this Eurocentric bias will result in OCD genomic findings being more accurate for individuals of European ancestry than other ancestries, thereby contributing to health disparities in potential future applications of genomics. In this study protocol paper, we describe the Latin American Trans-ancestry INitiative for OCD genomics (LATINO, https://www.latinostudy.org). LATINO is a new network of investigators from across Latin America, the United States, and Canada who have begun to collect DNA and clinical data from 5000 richly phenotyped OCD cases of Latin American ancestry in a culturally sensitive and ethical manner. In this project, we will utilize trans-ancestry genomic analyses to accelerate the identification of OCD risk loci, fine-map putative causal variants, and improve the performance of polygenic risk scores in diverse populations. We will also capitalize on rich clinical data to examine the genetics of treatment response, biologically plausible OCD subtypes, and symptom dimensions. Additionally, LATINO will help elucidate the diversity of the clinical presentations of OCD across cultures through various trainings developed and offered in collaboration with Latin American investigators. We believe this study will advance the important goal of global mental health discovery and equity.

Amygdala subnuclei volumes and anxiety behaviors in children and adolescents with autism spectrum disorder, attention deficit hyperactivity disorder, and obsessive-compulsive disorder.

Alterations in the structural maturation of the amygdala subnuclei volumes are associated with anxiety behaviors in adults and children with neurodevelopmental and associated disorders. This study investigated the relationship between amygdala subnuclei volumes and anxiety in 233 children and adolescents (mean age = 11.02 years; standard deviation = 3.17) with autism spectrum disorder (ASD), attention deficit hyperactivity disorder (ADHD), and children with obsessive compulsive disorder (OCD), as well as typically developing (TD) children. Parents completed the Child Behavior Checklist (CBCL), and the children underwent structural MRI at 3 T. FreeSurfer software was used to automatically segment the amygdala subnuclei. A general linear model revealed that children and adolescents with ASD, ADHD, and OCD had higher anxiety scores compared to TD children (p < .001). A subsequent interaction analysis revealed that children with ASD (B = 0.09, p < .0001) and children with OCD (B = 0.1, p < .0001) who had high anxiety had larger right central nuclei volumes compared with TD children. Similar results were obtained for the right anterior amygdaloid area. Amygdala subnuclei volumes may be key to identifying children with neurodevelopmental disorders or those with OCD who are at high risk for anxiety. Findings may inform the development of targeted behavioral interventions to address anxiety behaviors and to assess the downstream effects of such interventions.

Obsessive-compulsive disorder in children and youth: neurocognitive function in clinic and community samples.

BACKGROUND: Neurocognitive impairments are common in OCD, although not well studied in children and youth with the disorder. METHOD: Using the stop-signal task (SST), we measured response inhibition (stop-signal reaction time-SSRT), sustained attention (reaction time variability-RTV), reaction time (RT), and performance monitoring (post-error slowing-PES) in OCD cases and controls from two samples of children and youth. A Clinic OCD group (n = 171, aged 7-17 years) was recruited from a specialty clinic after rigorous assessment. A typically developing (Clinic TD, n = 157) group was enlisted through advertisement. A community OCD sample (Community OCD, n = 147) and controls (Community TD n = 13,832, aged 6-17 years) were recruited at a science museum. We also identified a community group with high OCD traits without an OCD diagnosis (Community High Trait; n = 125). RESULTS: Clinic OCD participants had longer SSRT and greater RTV than Clinic TD. These effects were greater in younger OCD participants and, for SSRT, in those on medication for OCD. The Community OCD group did not differ from Controls but was similar to the Clinic OCD group in ADHD and ASD comorbidity and medication usage. The Community High Trait group had longer SSRT and atypical PES suggesting that symptom severity predicts neurocognitive function. No group differences were found in RT. CONCLUSIONS: In the largest study of neurocognitive performance in children with OCD to date, we found impaired response inhibition and sustained attention in OCD participants in comparison to typically developing peers. Performance was worse in younger OCD participants. In the community sample, participants with high OCD trait scores but no OCD diagnosis had impaired response inhibition and error processing, suggesting that OCD might be under-recognized.

Mostly worse, occasionally better: impact of COVID-19 pandemic on the mental health of Canadian children and adolescents.

This large cross-sectional study examined the impact of COVID-19 emergency measures on child/adolescent mental health for children/adolescents with and without pre-existing psychiatric diagnoses. Using adapted measures from the CRISIS questionnaire, parents of children aged 6-18 (N = 1013; 56% male; 62% pre-existing psychiatric diagnosis) and self-reporting children/adolescents aged 10-18 (N = 385) indicated changes in mental health across six domains: depression, anxiety, irritability, attention, hyperactivity, and obsessions/compulsions. Changes in anxiety, irritability, and hyperactivity were calculated for children aged 2-5 years using the Strengths and Difficulties Questionnaire. COVID-19 exposure, compliance with emergency measures, COVID-19 economic concerns, and stress from social isolation were measured with the CRISIS questionnaire. Prevalence of change in mental health status was estimated for each domain; multinomial logistic regression was used to determine variables associated with mental health status change in each domain. Depending on the age group, 67-70% of children/adolescents experienced deterioration in at least one mental health domain; however, 19-31% of children/adolescents experienced improvement in at least one domain. Children/adolescents without and with psychiatric diagnoses tended to experience deterioration during the first wave of COVID-19. Rates of deterioration were higher in those with a pre-exiting diagnosis. The rate of deterioration was variable across different age groups and pre-existing psychiatric diagnostic groups: depression 37-56%, anxiety 31-50%, irritability 40-66%, attention 40-56%, hyperactivity 23-56%, obsessions/compulsions 13-30%. Greater stress from social isolation was associated with deterioration in all mental health domains (all ORs 11.12-55.24). The impact of pre-existing psychiatric diagnosis was heterogenous, associated with deterioration in depression, irritability, hyperactivity, obsession/compulsions for some children (ORs 1.96-2.23) but also with improvement in depression, anxiety, and irritability for other children (ORs 2.13-3.12). Economic concerns were associated with improvement in anxiety, attention, and obsessions/compulsions (ORs 3.97-5.57). Children/adolescents with and without pre-existing psychiatric diagnoses reported deterioration. Deterioration was associated with increased stress from social isolation. Enhancing social interactions for children/adolescents will be an important mitigation strategy for current and future COVID-19 waves.

Confidence, Training and Challenges for Canadian Child Advocacy Center Staff When Working with Cases of Online and In-person Child Sexual Exploitation.

Child Advocacy Centers are interdisciplinary hubs that play a vital role in responding to child maltreatment, especially sexual abuse. Sexual abuse cases increasingly involve an online component, but no studies have examined the experience of Child Advocacy Center staff in dealing with online sexual exploiftation. This study surveyed 37 staff at five Child Advocacy Centers in Alberta, Canada to understand their ability to recognize and respond to concerns about online and in-person sexual exploitation of their clients. The majority of respondents (54%) dealt with cases that involved grooming, luring, sexual abuse and child sexual abuse imagery (also known as child pornography) in the last year. Staff were equally confident in their ability to recognize and respond to grooming, luring, sexual abuse and child sexual abuse imagery. However, staff were more likely to have formal training in identifying sexual abuse and less likely to encounter difficulties in responding to sexual abuse relative to grooming, luring or child sexual abuse imagery. Clinicians used similar therapies when working with youth impacted by sexual abuse versus child sexual abuse imagery. Given that most Child Advocacy Center staff in our sample dealt with online child sexual exploitation, additional training in this area may be warranted.

Examination of the shared genetic basis of anorexia nervosa and obsessive-compulsive disorder.

Anorexia nervosa (AN) and obsessive-compulsive disorder (OCD) are often comorbid and likely to share genetic risk factors. Hence, we examine their shared genetic background using a cross-disorder GWAS meta-analysis of 3495 AN cases, 2688 OCD cases, and 18,013 controls. We confirmed a high genetic correlation between AN and OCD (rg = 0.49 ± 0.13, p = 9.07 × 10-7) and a sizable SNP heritability (SNP h2 = 0.21 ± 0.02) for the cross-disorder phenotype. Although no individual loci reached genome-wide significance, the cross-disorder phenotype showed strong positive genetic correlations with other psychiatric phenotypes (e.g., rg = 0.36 with bipolar disorder and 0.34 with neuroticism) and negative genetic correlations with metabolic phenotypes (e.g., rg = -0.25 with body mass index and -0.20 with triglycerides). Follow-up analyses revealed that although AN and OCD overlap heavily in their shared risk with other psychiatric phenotypes, the relationship with metabolic and anthropometric traits is markedly stronger for AN than for OCD. We further tested whether shared genetic risk for AN/OCD was associated with particular tissue or cell-type gene expression patterns and found that the basal ganglia and medium spiny neurons were most enriched for AN-OCD risk, consistent with neurobiological findings for both disorders. Our results confirm and extend genetic epidemiological findings of shared risk between AN and OCD and suggest that larger GWASs are warranted.

Brain structural covariance networks in obsessive-compulsive disorder: a graph analysis from the ENIGMA Consortium.

Brain structural covariance networks reflect covariation in morphology of different brain areas and are thought to reflect common trajectories in brain development and maturation. Large-scale investigation of structural covariance networks in obsessive-compulsive disorder (OCD) may provide clues to the pathophysiology of this neurodevelopmental disorder. Using T1-weighted MRI scans acquired from 1616 individuals with OCD and 1463 healthy controls across 37 datasets participating in the ENIGMA-OCD Working Group, we calculated intra-individual brain structural covariance networks (using the bilaterally-averaged values of 33 cortical surface areas, 33 cortical thickness values, and six subcortical volumes), in which edge weights were proportional to the similarity between two brain morphological features in terms of deviation from healthy controls (i.e. z-score transformed). Global networks were characterized using measures of network segregation (clustering and modularity), network integration (global efficiency), and their balance (small-worldness), and their community membership was assessed. Hub profiling of regional networks was undertaken using measures of betweenness, closeness, and eigenvector centrality. Individually calculated network measures were integrated across the 37 datasets using a meta-analytical approach. These network measures were summated across the network density range of K = 0.10-0.25 per participant, and were integrated across the 37 datasets using a meta-analytical approach. Compared with healthy controls, at a global level, the structural covariance networks of OCD showed lower clustering (P < 0.0001), lower modularity (P < 0.0001), and lower small-worldness (P = 0.017). Detection of community membership emphasized lower network segregation in OCD compared to healthy controls. At the regional level, there were lower (rank-transformed) centrality values in OCD for volume of caudate nucleus and thalamus, and surface area of paracentral cortex, indicative of altered distribution of brain hubs. Centrality of cingulate and orbito-frontal as well as other brain areas was associated with OCD illness duration, suggesting greater involvement of these brain areas with illness chronicity. In summary, the findings of this study, the largest brain structural covariance study of OCD to date, point to a less segregated organization of structural covariance networks in OCD, and reorganization of brain hubs. The segregation findings suggest a possible signature of altered brain morphometry in OCD, while the hub findings point to OCD-related alterations in trajectories of brain development and maturation, particularly in cingulate and orbitofrontal regions.

Serotonin system genes and hoarding with and without other obsessive-compulsive traits in a population-based, pediatric sample: A genetic association study.

BACKGROUND: Hoarding, originally only considered a symptom of obsessive-compulsive disorder (OCD), is now categorized as a separate disorder in the fifth edition of the Diagnostic and Statistical Manual of Mental Disorders (DSM-5). We studied candidate serotonergic genes and the distinctness of hoarding in children and adolescents and hypothesized that unique gene variants would be associated with hoarding alone. METHODS: We examined obsessive-compulsive (OC) traits, including hoarding, in a total of 5,213 pediatric participants in the community. We genotyped candidate serotonin genes (5-HTTLPR polymorphism in SLC6A4 for 2,018 individuals and single nucleotide polymorphisms [SNPs] across genes SLC6A4, HTR2A, and HTR1B for 4,711 individuals). In a previous study conducted by our group in the same sample, we identified a significant association between 5-HTTLPR and hoarding in males. In this study, we examined hoarding more closely by testing the association between serotonin gene variants and hoarding traits with and without other accompanying OC traits. RESULTS: The [LG +S] variant in 5-HTTLPR was significantly associated with hoarding alone in males (p-value of 0.009). There were no significant findings for 5-HTTLPR in females. There were no significant findings after correction for multiple comparisons using SNP array data, but top SNP findings suggested that variation downstream of HTR1B may be implicated in hoarding alone in females. CONCLUSIONS: Our results suggest specific serotonin gene variants are associated with hoarding traits alone, differing between sexes. Top findings are in line with our former study, suggesting that individuals with hoarding alone were driving previous results. Our paper supports hoarding disorder's new designation.