Search

Youth living with perinatally acquired HIV (YLPHIV) have been found to have a range of mental disorders. Some adult HIV studies have linked mental health to adverse metabolic outcomes due to dysregulation of the sympathetic nervous system and hypothalamic-pituitary-adrenal axis, but this association has not previously been explored in YLPHIV.We investigated the association of mental health measures with metabolic outcomes in YLPHIV and HIV-uninfected youth (HIV-U) and linear regression was used to assess the adjusted associations.Overall, 203 YLPHIV (median age = 10.7years; 52% female; mean duration on ART 8 years, 12% CD4 count 50 copies/mL) and 44 HIV-U (median age = 10.3 years; 55% female) were enrolled. YLPHIV had higher median total cholesterol (4.2 vs 3.9 mmol/L, p = 0.049) and triglyceride (0.9 vs 0.7 mmol/L, p < 0.001) compared to HIV-U. We found higher percentage of poor functional competence (40% vs 25%, p = 0.02) and self-concept (23% vs 9%, p = 0.03) and higher depression (6% vs 2%, p < 0.01), anger (6% vs 2%, p = 0.04) and disruptive behaviour (4% vs 0%, p < 0.01) in YLPHIV as compared to HIV-U. Among YLPHIV, higher scores of anger were associated with higher total cholesterol and higher low-density lipoprotein (s = 0.010, p = 0.041 and s = 0.012, p = 0.048 respectively) and disruptive behaviour with higher low-density lipoprotein (s = 0.010, p = 0.043) after adjusting for age, sex and BMIZ.This is the one of first study to investigate the association of mental health with metabolic outcomes among YLPHIV. The association of increased anger and disruptive behaviour with increased lipid concentration is a novel finding. Further longitudinal studies are needed to evaluate the causal relationships between mental health and metabolic outcomes.

SummaryAfrican populations are the most diverse in the world yet are sorely underrepresented in medical genetics research. Here, we examine the structure of African populations using genetic and comprehensive multigenerational ethnolinguistic data from the Neuropsychiatric Genetics of African Populations-Psychosis study (NeuroGAP-Psychosis) consisting of 900 individuals from Ethiopia, Kenya, South Africa, and Uganda. We find that self-reported language classifications meaningfully tag underlying genetic variation that would be missed with consideration of geography alone, highlighting the importance of culture in shaping genetic diversity. Leveraging our uniquely rich multi-generational ethnolinguistic metadata, we track language transmission through the pedigree, observing the disappearance of several languages in our cohort as well as notable shifts in frequency over three generations. We find suggestive evidence for the rate of language transmission in matrilineal groups having been higher than that for patrilineal ones. We highlight both the diversity of variation within the African continent, as well as how within-Africa variation can be informative for broader variant interpretation; many variants appearing rare elsewhere are common in parts of Africa. The work presented here improves the understanding of the spectrum of genetic variation in African populations and highlights the enormous and complex genetic and ethnolinguistic diversity within Africa.

Purpose: To investigate the associations of childhood adversities (CAs) with lifetime onset and transitions across suicidal thoughts and behaviors (STB) among incoming college students. Methods: Web-based self-report surveys administered to 20,842 incoming college students from nine countries (response rate 45.6%) assessed lifetime suicidal ideation, plans and attempts along with seven CAs: parental psychopathology, three types of abuse (emotional, physical, sexual), neglect, bully victimization, and dating violence. Logistic regression estimated individual- and population-level associations using CA operationalizations for type, number, severity, and frequency. Results: Associations of CAs with lifetime ideation and the transition from ideation to plan were best explained by the exact number of CA types (OR range 1.32–52.30 for exactly two to seven CAs). Associations of CAs with a transition to attempts were best explained by the frequency of specific CA types (scaled 0–4). Attempts among ideators with a plan were significantly associated with all seven CAs (OR range 1.16–1.59) and associations remained significant in adjusted analyses with the frequency of sexual abuse (OR = 1.42), dating violence (OR = 1.29), physical abuse (OR = 1.17) and bully victimization (OR = 1.17). Attempts among ideators without plan were significantly associated with frequency of emotional abuse (OR = 1.29) and bully victimization (OR = 1.36), in both unadjusted and adjusted analyses. Population attributable risk simulations found 63% of ideation and 30–47% of STB transitions associated with CAs. Conclusion: Early-life adversities represent a potentially important driver in explaining lifetime STB among incoming college students. Comprehensive intervention strategies that prevent or reduce the negative effects of CAs may reduce subsequent onset of STB.

Large nest building behaviour (LNB), as expressed by a subpopulation of laboratory housed deer mice (Peromyscus maniculatus bairdii), is persistent and repetitive. However, the response of LNB to an anxiogenic environment has not yet been investigated. Here, we employed LNB and normal nesting (NNB) expressing mice, subdivided into three drug-exposed groups per cohort, i.e. water (28 days), escitalopram (50 mg/kg/day, 28 days) and lorazepam (2 mg/kg/day; 4 days) to investigate this theme. During the last 4 days of drug exposure, mice were placed inside anxiogenic open field arenas which contained a separate enclosed and dark area for 4 consecutive nights during which open field and/or nest building assessments were performed. We show that LNB behaviour in deer mice is stable, irrespective of the anxiety-related context in which it is assessed, and that LNB mice find an open field arena to be less aversive compared to NNB mice. Escitalopram and lorazepam differentially affected the nesting and open field behaviour of LNB expressing mice, confirming deer mouse LNB as a repetitive behavioural phenotype that is related to a compulsive-like process which is regulated by the serotonergic system.

BackgroundThe most common treatment for major depressive disorder (MDD) is antidepressant medication (ADM). Results are reported on frequency of ADM use, reasons for use, and perceived effectiveness of use in general population surveys across 20 countries.MethodsFace-to-face interviews with community samples totaling n = 49 919 respondents in the World Health Organization (WHO) World Mental Health (WMH) Surveys asked about ADM use anytime in the prior 12 months in conjunction with validated fully structured diagnostic interviews. Treatment questions were administered independently of diagnoses and asked of all respondents.Results3.1% of respondents reported ADM use within the past 12 months. In high-income countries (HICs), depression (49.2%) and anxiety (36.4%) were the most common reasons for use. In low- and middle-income countries (LMICs), depression (38.4%) and sleep problems (31.9%) were the most common reasons for use. Prevalence of use was 2–4 times as high in HICs as LMICs across all examined diagnoses. Newer ADMs were proportionally used more often in HICs than LMICs. Across all conditions, ADMs were reported as very effective by 58.8% of users and somewhat effective by an additional 28.3% of users, with both proportions higher in LMICs than HICs. Neither ADM class nor reason for use was a significant predictor of perceived effectiveness.ConclusionADMs are in widespread use and for a variety of conditions including but going beyond depression and anxiety. In a general population sample from multiple LMICs and HICs, ADMs were widely perceived to be either very or somewhat effective by the people who use them.

Background: Substance use disorders (SUDs) occur frequently in patients with psychotic disorders and have been associated with various demographic and clinical correlates. There is an absence of research on the prevalence and clinical correlates of SUDs in psychotic disorders in low-and-middle-income countries (LMICs). Aim: We aimed to determine the prevalence and correlates of SUDs in psychotic disorders. Setting: Patients attending a large secondary-level psychiatric hospital in Cape Town South Africa. Methods: We used the Structured Clinical Interview for DSM-IV (SCID-I) to determine psychiatric and substance use diagnoses, depressive, anxiety, obsessive-compulsive and post-traumatic symptoms. We used logistic regression models to determine significant predictors of SUDs. Results: In total sample ( N = 248), 55.6% of participants had any SUD, 34.3% had cannabis use disorders, 30.6% alcohol use disorders, 27.4% methamphetamine use disorders, 10.4% methaqualone use disorders and 4.8% had other SUDs. There were significant associations with male sex for most SUDs, with younger age and Coloured ethnicity for methamphetamine use disorders, and with lower educational attainment for cannabis use disorders. Anxiety symptoms and suicide attempts were significantly associated with alcohol use disorders; a diagnosis of a substance induced psychosis with cannabis and methamphetamine use disorders. Across most SUDs legal problems and criminal involvement were significantly increased. Conclusion: This study found a high prevalence and wide distribution of SUDs in patients with psychotic disorders, consistent with previous work from high income countries. Given clinical correlates, in individuals with psychotic disorders and SUDs it is important to assess anxiety symptoms, suicidality and criminal involvement.

Prenatal exposure to maternal depression increases the risk for onset of emotional and behavioral disorders in children. Here, we investigated the effects of exposure to prenatal depression on white matter microstructural integrity at birth and at 2–3 years, and associated neurodevelopment. Diffusion-weighted images were acquired for children of the Drakenstein Child Health Study at 2–4 weeks postpartum (n = 70, 47% boys) and at 2–3 years of age (n = 60, 58% boys). Tract-Based Spatial Statistics was used to compare diffusion tensor metrics across groups defined by presence (> 19 on Beck’s Depression Inventory and/or > 12 on the Edinburgh Postnatal Depression Scale) or absence (below depression thresholds) of depression, and associations with neurodevelopmental measures at age 2–3 years were determined. We did not detect group differences in white matter integrity at neonatal age in this cohort, but at 2–3 years, children in the exposed group demonstrated higher fractional anisotropy, and lower mean and radial diffusivity in association tracts compared to control children. This was notable in the sagittal stratum (radial diffusivity: p

Contains fulltext : 248376.pdf (Publisher’s version ) (Open Access) For many traits, males show greater variability than females, with possible implications for understanding sex differences in health and disease. Here, the ENIGMA (Enhancing Neuro Imaging Genetics through Meta-Analysis) Consortium presents the largest-ever mega-analysis of sex differences in variability of brain structure, based on international data spanning nine decades of life. Subcortical volumes, cortical surface area and cortical thickness were assessed in MRI data of 16,683 healthy individuals 1-90 years old (47% females). We observed significant patterns of greater male than female between-subject variance for all subcortical volumetric measures, all cortical surface area measures, and 60% of cortical thickness measures. This pattern was stable across the lifespan for 50% of the subcortical structures, 70% of the regional area measures, and nearly all regions for thickness. Our findings that these sex differences are present in childhood implicate early life genetic or gene-environment interaction mechanisms. The findings highlight the importance of individual differences within the sexes, that may underpin sex-specific vulnerability to disorders.

Special Issue: The ENIGMA Consortium: the first 10 years., Delineating the association of age and cortical thickness in healthy individuals is critical given the association of cortical thickness with cognition and behavior. Previous research has shown that robust estimates of the association between age and brain morphometry require large-scale studies. In response, we used cross-sectional data from 17,075 individuals aged 3–90 years from the Enhancing Neuroimaging Genetics through Meta-Analysis (ENIGMA) Consortium to infer age-related changes in cortical thickness. We used fractional polynomial (FP) regression to quantify the association between age and cortical thickness, and we computed normalized growth centiles using the parametric Lambda, Mu, and Sigma method. Interindividual variability was estimated using meta-analysis and one-way analysis of variance. For most regions, their highest cortical thickness value was observed in childhood. Age and cortical thickness showed a negative association; the slope was steeper up to the third decade of life and more gradual thereafter; notable exceptions to this general pattern were entorhinal, temporopolar, and anterior cingulate cortices. Interindividual variability was largest in temporal and frontal regions across the lifespan. Age and its FP combinations explained up to 59% variance in cortical thickness. These results may form the basis of further investigation on normative deviation in cortical thickness and its significance for behavioral and cognitive outcomes., European Community's Seventh Framework Programme, Grant/Award Numbers: 278948, 602450, 603016, 602805; US National Institute of Child Health and Human Development, Grant/Award Numbers: RO1HD050735, 1009064, 496682; QIMR Berghofer Medical Research Institute and the Centre for Advanced Imaging, University of Queensland; ICTSI NIH/NCRR, Grant/Award Number: RR025761; European Community's Horizon 2020 Programme, Grant/Award Numbers: 667302, 643051; Vici Innovation Program, Grant/Award Numbers: #91619115, 016-130-669; NWO Brain & Cognition Excellence Program, Grant/Award Number: 433-09-229; Biobanking and Biomolecular Resources Research Infrastructure (Netherlands) (BBMRI-NL); Spinozapremie, Grant/Award Number: NWO-56-464-14192; Biobanking and Biomolecular Resources Research Infrastructure, Grant/Award Numbers: 184.033.111, 184.021.007; Netherlands Organization for Health Research and Development (ZonMW), Grant/Award Numbers: 480-15-001/674, 024.001.003, 911-09-032, 056-32-010, 481-08-011, 016-115-035, 31160008, 400-07-080, 400-05-717, 451-04-034, 463-06-001, 480-04-004, 904-61-193, 912-10-020, 985-10-002, 904-61-090; NIMH, Grant/Award Number: R01 MH090553; Geestkracht programme of the Dutch Health Research Council, Grant/Award Number: 10-000-1001; FP7 Ideas: European Research Council; Nederlandse Organisatie voor Wetenschappelijk Onderzoek, Grant/Award Numbers: NWO/SPI 56-464-14192, NWO-MagW 480-04-004, 433-09-220, NWO 51.02.062, NWO 51.02.061; National Center for Advancing Translational Sciences, National Institutes of Health, Grant/Award Number: UL1 TR000153; National Center for Research Resources; National Center for Research Resources at the National Institutes of Health, Grant/Award Numbers: NIH 1U24 RR025736-01, NIH 1U24 RR021992; NIH Institutes contributing to the Big Data to Knowledge; U.S. National Institutes of Health, Grant/Award Numbers: R01 CA101318, P30 AG10133, R01 AG19771; Medical Research Council, Grant/Award Numbers: U54EB020403, G0500092; National Institute of Mental Health, Grant/Award Numbers: R01MH117014, R01MH042191; Fundación Instituto de Investigación Marqués de Valdecilla, Grant/Award Numbers: API07/011, NCT02534363, NCT0235832; Instituto de Salud Carlos III, Grant/Award Numbers: PI14/00918, PI14/00639, PI060507, PI050427, PI020499; Swedish Research Council, Grant/Award Numbers: 523-2014-3467, 2017-00949, 521-2014-3487; South-Eastern Norway Health Authority; the Research Council of Norway, Grant/Award Number: 223273; South Eastern Norway Regional Health Authority, Grant/Award Numbers: 2017-112, 2019107; Icahn School of Medicine at Mount Sinai; Seventh Framework Programme (FP7/2007-2013), Grant/Award Number: 602450; National Institutes of Health, Grant/Award Numbers: R01 MH116147, R01 MH113619, R01 MH104284; South London and Maudsley NHS Foundation Trust; the National Institute for Health Research (NIHR)

To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, it may be useful to develop classification models that are explicitly generalizable to unseen sites and populations. This problem was explored in a mega‐analysis of previously published datasets from 2,034 AD and comparison participants spanning 27 sites curated by the ENIGMA Addiction Working Group. Data were grouped into a training set used for internal validation including 1,652 participants (692 AD, 24 sites), and a test set used for external validation with 382 participants (146 AD, 3 sites). An exploratory data analysis was first conducted, followed by an evolutionary search based feature selection to site generalizable and high performing subsets of brain measurements. Exploratory data analysis revealed that inclusion of case‐ and control‐only sites led to the inadvertent learning of site‐effects. Cross validation methods that do not properly account for site can drastically overestimate results. Evolutionary‐based feature selection leveraging leave‐one‐site‐out cross‐validation, to combat unintentional learning, identified cortical thickness in the left superior frontal gyrus and right lateral orbitofrontal cortex, cortical surface area in the right transverse temporal gyrus, and left putamen volume as final features. Ridge regression restricted to these features yielded a test‐set area under the receiver operating characteristic curve of 0.768. These findings evaluate strategies for handling multi‐site data with varied underlying class distributions and identify potential biomarkers for individuals with current AD., To identify neuroimaging biomarkers of alcohol dependence (AD) from structural magnetic resonance imaging, we developed classifiers on data collected from multiple sites. Exploratory data analysis revealed that inclusion of case‐ and control‐only sites led to the inadvertent learning of site‐effects. Evolutionary‐based feature selection leveraging leave‐one‐site‐out cross‐validation, to combat unintentional learning, yielded a test‐set area under the receiver operating characteristic curve of 0.768.

MRI‐derived brain measures offer a link between genes, the environment and behavior and have been widely studied in bipolar disorder (BD). However, many neuroimaging studies of BD have been underpowered, leading to varied results and uncertainty regarding effects. The Enhancing Neuro Imaging Genetics through Meta‐Analysis (ENIGMA) Bipolar Disorder Working Group was formed in 2012 to empower discoveries, generate consensus findings and inform future hypothesis‐driven studies of BD. Through this effort, over 150 researchers from 20 countries and 55 institutions pool data and resources to produce the largest neuroimaging studies of BD ever conducted. The ENIGMA Bipolar Disorder Working Group applies standardized processing and analysis techniques to empower large‐scale meta‐ and mega‐analyses of multimodal brain MRI and improve the replicability of studies relating brain variation to clinical and genetic data. Initial BD Working Group studies reveal widespread patterns of lower cortical thickness, subcortical volume and disrupted white matter integrity associated with BD. Findings also include mapping brain alterations of common medications like lithium, symptom patterns and clinical risk profiles and have provided further insights into the pathophysiological mechanisms of BD. Here we discuss key findings from the BD working group, its ongoing projects and future directions for large‐scale, collaborative studies of mental illness., This review discusses the major challenges facing neuroimaging research of bipolar disorder and highlights the major accomplishments, ongoing challenges and future goals of the ENIGMA Bipolar Disorder Working Group.

INTRODUCTION: The COVID-19 (coronavirus disease 2019)-related pandemic represents a global source of societal and health burden. Yet, the impact of the pandemic on people with severe mental illness, including bipolar disorder (BD), remains unclear, warranting scoping review on the matter. METHODS: The MEDLINE and EMBASE databases were systematically searched from inception up to April 24, 2021, adopting broad inclusion criteria to assess a variety of clinical and public health themes related to people with a primary diagnosis of BD during the COVID-19 pandemics. The present work complying with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for scoping reviews (PRISMA-ScR) registered in the Open Science Framework (OSF) repository (https://osf.io/7evpx/). RESULTS: Fourteen papers informed the present scoping review. Four major themes were identified: (i) impact of COVID-19-related stressors on BD; (ii) impact of COVID-19 on mental health service utilization among people with BD; (iii) impact of BD on the risk of acquiring SARS-CoV-2 infection; (iv) engagement in preventative behaviors among people with BD. Additional themes warranting further research were nonetheless detected. LIMITATIONS: Further original studies are needed. CONCLUSION: The present study confirmed the high-vulnerability hypothesis concerning people with BD versus the general population, reinforcing the need for further research related to the COVID-19 pandemic. Additional information is warranted to compare the impact of the pandemic period among BD people against pre-pandemic records, the general population, and other severe mental illnesses, namely people with schizophrenia or major depressive disorder, to inform the public health and the delivery of patient-tailored interventions.

BackgroundTrichotillomania (TTM) and skin picking disorder (SPD) are common and often debilitating mental health conditions, grouped under the umbrella term of body-focused repetitive behaviors (BFRBs). Recent clinical subtyping found that there were three distinct subtypes of TTM and two of SPD. Whether these clinical subtypes map on to any unique neurobiological underpinnings, however, remains unknown.MethodsTwo hundred and fifty one adults [193 with a BFRB (85.5% [n = 165] female) and 58 healthy controls (77.6% [n = 45] female)] were recruited from the community for a multicenter between-group comparison using structural neuroimaging. Differences in whole brain structure were compared across the subtypes of BFRBs, controlling for age, sex, scanning site, and intracranial volume.ResultsWhen the subtypes of TTM were compared, low awareness hair pullers demonstrated increased cortical volume in the lateral occipital lobe relative to controls and sensory sensitive pullers. In addition, impulsive/perfectionist hair pullers showed relative decreased volume near the lingual gyrus of the inferior occipital–parietal lobe compared with controls.ConclusionsThese data indicate that the anatomical substrates of particular forms of BFRBs are dissociable, which may have implications for understanding clinical presentations and treatment response.

BackgroundAlthough non-suicidal self-injury (NSSI) is an issue of major concern to colleges worldwide, we lack detailed information about the epidemiology of NSSI among college students. The objectives of this study were to present the first cross-national data on the prevalence of NSSI and NSSI disorder among first-year college students and its association with mental disorders.MethodsData come from a survey of the entering class in 24 colleges across nine countries participating in the World Mental Health International College Student (WMH-ICS) initiative assessed in web-based self-report surveys (20 842 first-year students). Using retrospective age-of-onset reports, we investigated time-ordered associations between NSSI and Diagnostic and Statistical Manual of Mental Disorders, Fifth Edition (DSM-IV) mood (major depressive and bipolar disorder), anxiety (generalized anxiety and panic disorder), and substance use disorders (alcohol and drug use disorder).ResultsNSSI lifetime and 12-month prevalence were 17.7% and 8.4%. A positive screen of 12-month DSM-5 NSSI disorder was 2.3%. Of those with lifetime NSSI, 59.6% met the criteria for at least one mental disorder. Temporally primary lifetime mental disorders predicted subsequent onset of NSSI [median odds ratio (OR) 2.4], but these primary lifetime disorders did not consistently predict 12-month NSSI among respondents with lifetime NSSI. Conversely, even after controlling for pre-existing mental disorders, NSSI consistently predicted later onset of mental disorders (median OR 1.8) as well as 12-month persistence of mental disorders among students with a generalized anxiety disorder (OR 1.6) and bipolar disorder (OR 4.6).ConclusionsNSSI is common among first-year college students and is a behavioral marker of various common mental disorders.

Emerging evidence suggests that obesity impacts brain physiology at multiple levels. Here we aimed to clarify the relationship between obesity and brain structure using structural MRI (n = 6420) and genetic data (n = 3907) from the ENIGMA Major Depressive Disorder (MDD) working group. Obesity (BMI > 30) was significantly associated with cortical and subcortical abnormalities in both mass-univariate and multivariate pattern recognition analyses independent of MDD diagnosis. The most pronounced effects were found for associations between obesity and lower temporo-frontal cortical thickness (maximum Cohen´s d (left fusiform gyrus) = −0.33). The observed regional distribution and effect size of cortical thickness reductions in obesity revealed considerable similarities with corresponding patterns of lower cortical thickness in previously published studies of neuropsychiatric disorders. A higher polygenic risk score for obesity significantly correlated with lower occipital surface area. In addition, a significant age-by-obesity interaction on cortical thickness emerged driven by lower thickness in older participants. Our findings suggest a neurobiological interaction between obesity and brain structure under physiological and pathological brain conditions.

BackgroundA number of recent investigations have focused on the neurobiology of obsessive–compulsive personality disorder (OCPD). However, there have been few reviews of this literature with no detailed model proposed. We therefore undertook a systematic review of these investigations, aiming to map the available evidence and investigate whether it is possible to formulate a detailed model of the neurobiology of OCPD.MethodsOCPD can be considered from both categorical and dimensional perspectives. An electronic search was therefore conducted using terms that would address not only OCPD as a category, but also related constructs, such as perfectionism, that would capture research on neuropsychology, neuroimaging, neurochemistry, and neurogenetics.ResultsA total of 1059 articles were retrieved, with 87 ultimately selected for abstract screening, resulting in a final selection of 49 articles focusing on neurobiological investigations relevant to OCPD. Impaired executive function and cognitive inflexibility are common neuropsychological traits in this condition, and suggest that obsessive–compulsive disorder (OCD) and OCPD may lie on a continuum. However, neuroimaging studies in OCPD indicate the involvement of specific neurocircuitry, including the precuneus and amygdala, and so suggest that OCD and OCPD may have important differences. Although OCPD has a heritable component, we found no well-powered genetic studies of OCPD.ConclusionAlthough knowledge in this area has advanced, there are insufficient data on which to base a comprehensive model of the neurobiology of OCPD. Given the clinical importance of OCPD, further work to understand the mechanisms that underpin this condition is warranted.

Introduction: Obsessive-compulsive disorder (OCD), characterized by repetitive anxiety-inducing intrusive thoughts and compulsive behaviors, is associated with higher suicide ideation and suicide attempts than the general population. This study investigates the prevalence and the correlates of current suicide risk in adult outpatients in an international multisite cross-sectional sample of OCD outpatients. Methods: Data were derived from the International College of Obsessive-Compulsive Spectrum Disorders (ICOCS) network's cross-sectional data set (N = 409). Current suicide risk (assessed by Item C of the MINI) and diagnoses of psychiatric disorders were based on DSM-IV. Chi-squared test for categorical variables and t-test for continuous variables were used to make statistical inferences about main features associated with current suicide risk. P < .05 was considered as statistically significant. Results: The prevalence of current suicidal risk was 15.9%, with equal likelihood in sociodemographic variables, including age and gender. Increased rates of major depression and generalized anxiety disorder were associated to higher current suicide risk. Current suicide risk was also associated with higher severity of OCD, depressive comorbidity, and higher levels of disability. There were no significant differences in treatment correlates—including type of treatment and psychiatric hospitalizations—between the groups of individuals with and without current suicide risk. Conclusion: Our findings suggest that current suicide risk is common in patients with OCD and associated with various forms of pathology. Our work also provides further empirical data to support what is already known clinically: a worse clinical picture characterized by a high severity of OCD, high distress related to obsessions and compulsions, and the presence of comorbidities such as major depression and generalized anxiety disorder should be considered as relevant risk factors for suicide risk.

Background Screening, brief intervention and referral to treatment (SBIRT) programmes have resulted in generally positive outcomes in healthcare settings, particularly for problem alcohol use, yet implementation is hampered by barriers such as concerns regarding the burden on healthcare professionals. In low-resourced settings, task-sharing approaches can reduce this burden by using non-professional healthcare workers, yet data are scarce regarding the outcomes and acceptability to patients within a SBIRT service. This study aims to evaluate patient-reported outcomes, patient acceptability, perceived benefits and recommendations for improving a task-shared SBIRT service in South African emergency centres (ECs). Methods This mixed methods study incorporates quantitative substance use screening and patient satisfaction data collected routinely within the service at three hospitals, and qualitative semi-structured interviews with 18 EC patient beneficiaries of the programme exploring acceptability and perceived benefits of the programme, as well as recommendations to improve the service. Approximately three months after the acute EC visit, a sub-sample of patients were followed up telephonically to assess patient-reported satisfaction and substance use outcomes. Results Of the 4847 patients eligible for the brief intervention, 3707 patients (76%) used alcohol as their primary substance and 794 (16%) used cannabis. At follow-up (n = 273), significant reductions in substance use frequency and severity were noted and over 95% of patients were satisfied with the service. In the semi-structured interviews, participants identified the non-judgemental caring approach of the counsellors, and the screening and psychoeducation components of the intervention as being the most valuable, motivating them to decrease substance use and make other positive lifestyle changes. Study participants made recommendations to include group sessions, market the programme in communities and extend the programme’s reach to include a broader age group and a variety of settings. Conclusions This task-shared SBIRT service was found to be acceptable to patients, who reported several benefits of a single SBIRT contact session delivered during an acute EC visit. These findings add to the SBIRT literature by highlighting the role of non-professional healthcare workers in delivering a low-intensity SBIRT service feasible to implement in low-resourced settings.

Individuals with bipolar disorders (BD) frequently suffer from obesity, which is often associated with neurostructural alterations. Yet, the effects of obesity on brain structure in BD are under-researched. We obtained MRI-derived brain subcortical volumes and body mass index (BMI) from 1134 BD and 1601 control individuals from 17 independent research sites within the ENIGMA-BD Working Group. We jointly modeled the effects of BD and BMI on subcortical volumes using mixed-effects modeling and tested for mediation of group differences by obesity using nonparametric bootstrapping. All models controlled for age, sex, hemisphere, total intracranial volume, and data collection site. Relative to controls, individuals with BD had significantly higher BMI, larger lateral ventricular volume, and smaller volumes of amygdala, hippocampus, pallidum, caudate, and thalamus. BMI was positively associated with ventricular and amygdala and negatively with pallidal volumes. When analyzed jointly, both BD and BMI remained associated with volumes of lateral ventricles and amygdala. Adjusting for BMI decreased the BD vs control differences in ventricular volume. Specifically, 18.41% of the association between BD and ventricular volume was mediated by BMI (Z = 2.73, p = 0.006). BMI was associated with similar regional brain volumes as BD, including lateral ventricles, amygdala, and pallidum. Higher BMI may in part account for larger ventricles, one of the most replicated findings in BD. Comorbidity with obesity could explain why neurostructural alterations are more pronounced in some individuals with BD. Future prospective brain imaging studies should investigate whether obesity could be a modifiable risk factor for neuroprogression.

This study aimed to identify alcohol use patterns associated with viral non-suppression among women living with HIV (WLWH) and the extent to which adherence mediated these relationships. Baseline data on covariates, alcohol consumption, ART adherence, and viral load were collected from 608 WLWH on ART living in the Western Cape, South Africa. We defined three consumption patterns: no/light drinking (drinking ≤ 1/week and ≤ 4 drinks/occasion), occasional heavy episodic drinking (HED) (drinking > 1 and ≤ 2/week and ≥ 5 drinks/occasion) and frequent HED (drinking ≥ 3 times/week and ≥ 5 drinks/occasion). In multivariable analyses, occasional HED (OR 3.07, 95% CI 1.78–5.30) and frequent HED (OR 7.11, 95% CI 4.24–11.92) were associated with suboptimal adherence. Frequent HED was associated with viral non-suppression (OR 2.08, 95% CI 1.30–3.28). Suboptimal adherence partially mediated the relationship between frequent HED and viral non-suppression. Findings suggest a direct relationship between frequency of HED and viral suppression. Given the mediating effects of adherence on this relationship, alcohol interventions should be tailored to frequency of HED while also addressing adherence.

PURPOSE: Suicidal ideation and behaviour (SIB) in the perinatal period is prevalent in low- and middle-income countries (LMICs). Past work has been limited by reliance on self-rated scales, and there are few data on SIB severity in such settings. We collected cross-sectional data on SIB using a clinician-administered scale and explored risk factors associated with the presence of SIB and SIB severity. METHODS: Data were collected from the Drakenstein Child Health Study cohort antenatally and at 6 months postpartum. SIB was measured using the Mini International Neuropsychiatric Interview and potential sociodemographic, psychosocial, and psychiatric risk factors were assessed. Multivariable analysis determined cross-sectional risk factors. Multinomial regressions determined predictors of SIB risk categories. RESULTS: Among 748 women the antenatal SIB prevalence was 19.9% and postpartum 22.6%. SIB was associated with younger age (antepartum), PTSD (postpartum), and depression (ante- and postpartum). Depression and PTSD predicted belonging to the high risk SIB group. The medium risk group was more likely to have depression, alcohol use during pregnancy and substance abuse. Depression, PTSD, food insecurity, recent intimate partner violence (IPV), and childhood trauma were associated with the low risk group versus the no risk group. CONCLUSION: Screening is needed for perinatal SIB. Associations of perinatal SIB with younger age and major depression are consistent with previous work. The association with PTSD is novel, and underscores the importance of assessment of trauma exposure and outcomes in this population. Different risk categories of SIB may have different causal pathways and require different interventions.

While hundreds of genes have been associated with pain, much of the molecular mechanisms of pain remain unknown. As a result, current analgesics are limited to few clinically validated targets. Here, we trained a machine learning (ML) ensemble model to predict new targets for 17 categories of pain. The model utilizes features from transcriptomics, proteomics, and gene ontology to prioritize targets for modulating pain. We focused on identifying novel G-protein-coupled receptors (GPCRs), ion channels, and protein kinases because these proteins represent the most successful drug target families. The performance of the model to predict novel pain targets is 0.839 on average based on AUROC, while the predictions for arthritis had the highest accuracy (AUROC = 0.929). The model predicts hundreds of novel targets for pain; for example, GPR132 and GPR109B are highly ranked GPCRs for rheumatoid arthritis. Overall, gene-pain association predictions cluster into three groups that are enriched for cytokine, calcium, and GABA-related cell signaling pathways. These predictions can serve as a foundation for future experimental exploration to advance the development of safer and more effective analgesics.

Introduction The purpose of this study is to investigate the effects of agomelatine on anxious symptoms and functional impairment in a pooled dataset from randomized placebo-controlled trials for generalized anxiety disorder (GAD). Methods Data from three randomized, placebo-controlled trials that evaluated the efficacy of agomelatine 25–50 mg were pooled. The short-term (12 weeks) efficacy of agomelatine was assessed in regards to (1) anxious symptoms using the Hamilton Anxiety Scale (HAM-A), and (2) functional impairment using the Sheehan Disability Scale (SDS). Meta-analysis using a random effect model was used to assess differences between groups. Remission and response rates for the HAM-A and SDS were calculated, and analyses were repeated in participants with more severe anxiety symptoms. Results In total, 669 patients (340 on agomelatine; 329 on placebo) were included in the analyses. Compared to placebo, the agomelatine group had a significant reduction in HAM-A total score at week 12 (between group difference: 6.30 ± 2.51, p = 0.012). Significant effects were also found for symptom response on the HAM-A (67.1% of patients on agomelatine vs. 32.5% on placebo) and symptom remission (38.8% of patients on agomelatine vs. 17.3% on placebo). Compared to placebo, there was a significant difference in favour of the agomelatine group at week 12 on the SDS total score (5.11 ± 1.81, p = 0.005). Significant effects were also found for functional response on the SDS (79.1% of patients on agomelatine vs. 43.2% of placebo) and functional remission (55.2% of patients on agomelatine vs. 25.4% on placebo). All findings for anxious symptoms and functional impairment were confirmed in the subset of more severely anxious patients. Agomelatine was well tolerated by patients. Conclusion This meta-analysis confirms that agomelatine reduces anxiety symptoms and improves the global functioning of GAD patients. Supplementary Information The online version of this article (10.1007/s12325-020-01583-9) contains supplementary material, which is available to authorized users.

Purpose Childhood maltreatment elevates risk for common mental disorders (CMDs) during late adolescence and adulthood. Although CMDs are highly prevalent among university students, few studies have examined the relationship between childhood maltreatment and 12 month CMDs in a low- to middle-income countries. This paper describes the prevalence of maltreatment and the relationship between type, number and patterns of maltreatment exposure and 12 month CMDs among first-year university students in South Africa. Methods Maltreatment and CMD data were collected via well-validated self-report scales (corresponding with DSM-IV diagnoses) in a web-based survey of first-year students from two large urban universities (n = 1290) in South Africa. Various multivariate modelling approaches (additive, restrictive interactive and latent class) were used to examine the relationship between maltreatment and CMDs. Results Overall, 48.4% of participants reported childhood maltreatment, the most common type being emotional abuse (26.7%). Regardless of the modelling approach used, emotional abuse was the only type of maltreatment independently associated with 12-month diagnoses of major depressive disorder (MDD), generalised anxiety disorder (GAD) or drug use disorder (DUD) even after adjusting for types and number of types of maltreatment. Similarly, students in the latent class reflecting histories of emotional abuse (either alone or combined with physical abuse) were more likely to meet criteria for 12-month MDD, GAD or DUD. Conclusion Findings confirm the high prevalence of childhood maltreatment among South African students. As this exposure elevates risk for MDD, GAD and DUD, interventions aimed at preventing and treating CMDs among first-year students should address experiences of childhood maltreatment. Electronic supplementary material The online version of this article (10.1007/s00127-020-01992-9) contains supplementary material, which is available to authorized users.

BackgroundMajor depressive disorder (MDD) is associated with an increased risk of brain atrophy, aging-related diseases, and mortality. We examined potential advanced brain aging in MDD patients, and whether this process is associated with clinical characteristics in a large multi-center international dataset.MethodsWe performed a mega-analysis by pooling brain measures derived from T1-weighted MRI scans from 29 samples worldwide. Normative brain aging was estimated by predicting chronological age (10-75 years) from 7 subcortical volumes, 34 cortical thickness and 34 surface area, lateral ventricles and total intracranial volume measures separately in 1,147 male and 1,386 female controls from the ENIGMA MDD working group. The learned model parameters were applied to 1,089 male controls and 1,167 depressed males, and 1,326 female controls and 2,044 depressed females to obtain independent unbiased brain-based age predictions. The difference between predicted “brain age” and chronological age was calculated to indicate brain predicted age difference (brain-PAD).FindingsOn average, MDD patients showed a higher brain-PAD of +0.90 (SE 0.21) years (Cohen’s d=0.12, 95% CI 0.06-0.17) compared to controls. Relative to controls, first-episode and currently depressed patients showed higher brain-PAD (+1.2 [0.3] years), and the largest effect was observed in those with late-onset depression (+1.7 [0.7] years). In addition, higher brain-PAD was associated with higher self-reported depressive symptomatology (b=0.05, p=0.004).InterpretationThis highly powered collaborative effort showed subtle patterns of abnormal structural brain aging in MDD. Substantial within-group variance and overlap between groups were observed. Longitudinal studies of MDD and somatic health outcomes are needed to further assess the predictive value of these brain-PAD estimates.FundingThis work was supported, in part, by NIH grants U54 EB020403 and R01 MH116147.