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• Inflammation in schizophrenia may be related to heterogeneous mechanistic pathways. • IL-6 and IL-8 have the most widespread neuroanatomical impact. • IFN-γ plays a potentially protective role in schizophrenia. • Advanced semi-supervised machine-learning techniques can aid detection of inflammation subgroups based on peripheral, accessible blood-based biomarkers. Immune system dysfunction is hypothesised to contribute to structural brain changes through aberrant synaptic pruning in schizophrenia. However, evidence is mixed and there is a lack of evidence of inflammation and its effect on grey matter volume (GMV) in patients. We hypothesised that inflammatory subgroups can be identified and that the subgroups will show distinct neuroanatomical and neurocognitive profiles. The total sample consisted of 1067 participants (chronic patients with schizophrenia n = 467 and healthy controls (HCs) n = 600) from the Australia Schizophrenia Research Bank (ASRB) dataset, together with 218 recent-onset patients with schizophrenia from the external Benefit of Minocycline on Negative Symptoms of Psychosis: Extent and Mechanism (BeneMin) dataset. HYDRA (HeterogeneitY through DiscRiminant Analysis) was used to separate schizophrenia from HC and define disease-related subgroups based on inflammatory markers. Voxel-based morphometry and inferential statistics were used to explore GMV alterations and neurocognitive deficits in these subgroups. An optimal clustering solution revealed five main schizophrenia groups separable from HC: Low Inflammation, Elevated CRP, Elevated IL-6/IL-8, Elevated IFN-γ, and Elevated IL-10 with an adjusted Rand index of 0.573. When compared with the healthy controls, the IL-6/IL-8 cluster showed the most widespread, including the anterior cingulate, GMV reduction. The IFN-γ inflammation cluster showed the least GMV reduction and impairment of cognitive performance. The CRP and the Low Inflammation clusters dominated in the younger external dataset. Inflammation in schizophrenia may not be merely a case of low vs high, but rather there are pluripotent, heterogeneous mechanisms at play which could be reliably identified based on accessible, peripheral measures. This could inform the successful development of targeted interventions. [ABSTRACT FROM AUTHOR]

Objective: To investigate the clinical characteristics of tertiary students and non-students attending a specialist clinic for severe mood disorders. Method: Medical record audit of clients discharged from the Youth Mood Clinic (YMC). Data extracted included depressive symptomatology, suicidal ideation, self-harm, suicide attempt, tertiary education engagement, drop-out and deferral. Results: Data from 131 clients (M age = 19.58 years, SD = 2.66) were analysed, including 46 tertiary students. Relative to non-students, at intake, tertiary students reported more severe depressive symptomatology (d = 0.43). They were more likely to experience suicidal ideation at intake (V = 0.23), and during treatment (V = 0.18). Tertiary students were also more likely to be living separately to their family of origin (V = 0.20) but were less likely to have experienced parental separation (V = 0.19). 21.73% of tertiary students dropped out or deferred study during care. Conclusion: In this cohort, those engaged in tertiary education experience more severe depression and more commonly experienced suicidal ideation. These young people require targeted support for their mental health while they undertake tertiary education. [ABSTRACT FROM AUTHOR]

Suicide is the second most common cause of death among young people. Structural brain alterations, rumination, and recent stressful experiences contribute to suicidal thoughts and behaviors (STBs). Here, we employed structural equation modeling (SEM) to examine the unique and combined relationships of these risk factors with STBs in a sample of young people with major depressive disorder (MDD) from the Magnetic Resonance-Improving Mood with Psychoanalytic and Cognitive Therapies (MR-IMPACT) study (N = 67, mean age = 15.90; standard deviation ± 1.32). Whereas increased rumination and lower surface area of brain regions, that have been previously reported to be involved in both STBs and rumination, were associated with each other (Beta = −0.268, standard error (SE) = 0.114, Z = −2.346, p = 0.019), only increased rumination was related to greater severity of suicidal ideation (Beta = 0.281, SE = 0.132, Z = 2.134, p = 0.033). In addition, we observed that recent stress was associated with lower surface area in the suicidal ideation model without covariate only (Beta = −0.312, SE = 0.149, Z = −2.089, p = 0.037). For the attempt models, no associations were found between any of the risk factors and suicide attempts. We emphasize that these findings from this secondary analysis are hypothesis-forming and preliminary in nature given the small sample size for SEM analyses. Our findings suggest that neither lower surface area nor recent stress are directly associated with youth suicidal ideation or attempt. However, lower surface area is related to recent stress and increased rumination, which predicted greater severity of suicidal ideation in young people with MDD. • Cognitive rumination was associated with suicidal ideation. • Rumination was related to brain regions involved in both suicide and rumination. • Findings are hypothesis-forming and preliminary based on secondary analyses. [ABSTRACT FROM AUTHOR]

Identifying neurobiologically based transdiagnostic categories of depression and psychosis may elucidate heterogeneity and provide better candidates for predictive modeling. We aimed to identify clusters across patients with recent-onset depression (ROD) and recent-onset psychosis (ROP) based on structural neuroimaging data. We hypothesized that these transdiagnostic clusters would identify patients with poor outcome and allow more accurate prediction of symptomatic remission than traditional diagnostic structures. HYDRA (Heterogeneity through Discriminant Analysis) was trained on whole-brain volumetric measures from 577 participants from the discovery sample of the multisite PRONIA study to identify neurobiologically driven clusters, which were then externally validated in the PRONIA replication sample (n = 404) and three datasets of chronic samples (Centre for Biomedical Research Excellence, n = 146; Mind Clinical Imaging Consortium, n = 202; Munich, n = 470). The optimal clustering solution was two transdiagnostic clusters (cluster 1: n = 153, 67 ROP, 86 ROD; cluster 2: n = 149, 88 ROP, 61 ROD; adjusted Rand index = 0.618). The two clusters contained both patients with ROP and patients with ROD. One cluster had widespread gray matter volume deficits and more positive, negative, and functional deficits (impaired cluster), and one cluster revealed a more preserved neuroanatomical signature and more core depressive symptomatology (preserved cluster). The clustering solution was internally and externally validated and assessed for clinical utility in predicting 9-month symptomatic remission, outperforming traditional diagnostic structures. We identified two transdiagnostic neuroanatomically informed clusters that are clinically and biologically distinct, challenging current diagnostic boundaries in recent-onset mental health disorders. These results may aid understanding of the etiology of poor outcome patients transdiagnostically and improve development of stratified treatments. [ABSTRACT FROM AUTHOR]

Background: Structural brain alterations are observed in major depressive disorder (MDD). However, MDD is a highly heterogeneous disorder and specific clinical or biological characteristics of depression might relate to specific structural brain alterations. Clinical symptom subtypes of depression, as well as immuno-metabolic dysregulation associated with subtypes of depression, have been associated with brain alterations. Therefore, we examined if specific clinical and biological characteristics of depression show different brain alterations compared to overall depression.Method: Individuals with and without depressive and/or anxiety disorders from the Netherlands Study of Depression and Anxiety (NESDA) (328 participants from three timepoints leading to 541 observations) and the Mood Treatment with Antidepressants or Running (MOTAR) study (123 baseline participants) were included. Symptom profiles (atypical energy-related profile, melancholic profile and depression severity) and biological indices (inflammatory, metabolic syndrome, and immuno-metabolic indices) were created. The associations of the clinical and biological profiles with depression-related structural brain measures (anterior cingulate cortex [ACC], orbitofrontal cortex, insula, and nucleus accumbens) were examined dimensionally in both studies and meta-analysed.Results: Depression severity was negatively associated with rostral ACC thickness (B = -0.55, pFDR = 0.03), and melancholic symptoms were negatively associated with caudal ACC thickness (B = -0.42, pFDR = 0.03). The atypical energy-related symptom profile and immuno-metabolic indices did not show a consistent association with structural brain measures across studies.Conclusion: Overall depression- and melancholic symptom severity showed a dose-response relationship with reduced ACC thickness. No associations between immuno-metabolic dysregulation and structural brain alterations were found, suggesting that although both are associated with depression, distinct mechanisms may be involved. [ABSTRACT FROM AUTHOR]

Objective: Brain imaging studies of structural abnormalities in OCD have yielded inconsistent results, partly because of limited statistical power, clinical heterogeneity, and methodological differences. The authors conducted meta- and mega-analyses comprising the largest study of cortical morphometry in OCD ever undertaken. Method: T1-weighted MRI scans of 1,905 OCD patients and 1,760 healthy controls from 27 sites worldwide were processed locally using Free Surfer to assess cortical thickness and surface area. Effect sizes for differences between patients and controls, and associations with clinical characteristics, were calculated using linear regression models controlling for age, sex, site, and intracranial volume. Results: In adult OCD patients versus controls, we found a significantly lower surface area for the transverse temporal cortex and a thinner inferior parietal cortex. Medicated adult OCD patients also showed thinner cortices throughout the brain. In pediatric OCD patients compared with controls, we found significantly thinner inferior and superior parietal cortices, but none of the regions analyzed showed significant differences in surface area. However, medicated pediatric OCD patients had lower surface area in frontal regions. Cohen's d effect sizes varied from -0.10 to -0.33. Conclusions: The parietal cortex was consistently implicated in both adults and children with OCD. More widespread cortical thickness abnormalities were found in medicated adult OCD patients, and more pronounced surface area deficits (mainly in frontal regions) were founding medicated pediatric OCD patients. These cortical measures represent distinct morphological features and may be differentially affected during different stages of development and illness, and possibly moderated by disease profile and medication. [ABSTRACT FROM AUTHOR]

Background Immunometabolic dysregulation (low-grade inflammation and metabolic dysregulation) has been associated with the onset and more severe course of multiple psychiatric disorders, partly due to neuroanatomical changes and impaired neuroplasticity. We examined the effect of multiple markers of immunometabolic dysregulation on hippocampal and amygdala volume and anterior cingulate cortex thickness in a large sample of patients with depression and/or anxiety and healthy subjects (N = 283). Methods Interleukin-6 (IL-6), tumor necrosis factor-alpha (TNF-a), c-reactive protein (CRP), triglyceride levels and HDL-cholesterol and genomic profile risk scores (GPRS) for immunometabolic dysregulation were determined in peripheral blood and T1 MRI scans were acquired at 3T. Regional brain volume and cortical thickness was assessed using FreeSurfer. Covariate-adjusted linear regression analyses were performed to examine the relationship between immunometabolic dysregulation and brain volume/thickness across all subjects. Results Multiple immunometabolic dysregulation markers (i.e. triglyceride levels and inflammation) were associated with lower rostral ACC thickness across all subjects. IL-6 was inversely associated with hippocampal and amygdala volume in healthy subjects only. GPRS for immunometabolic dysregulation were not associated with brain volume or cortical thickness. Conclusions Multiple serum, but not genetic immunometabolic dysregulation markers were found to relate to rostral ACC structure, suggesting that inflammation and metabolic dysregulation may impact the ACC through similar mechanisms. [ABSTRACT FROM AUTHOR]

The article presents a mega- and meta-analyses of data from obsessive-compulsive disorder (OCD). The meta-analysis showed that adult patients had larger pallidum volumes and smaller hippocampal volumes compared with adult controls. It revealed that the hippocampus and pallidum seem to be of significance in adult OCD, while the thalamus appears to be key in pediatric OCD.

Childhood maltreatment (CM) has been associated with altered brain morphology, which may partly be due to a direct impact on neural growth, e.g. through the brain-derived neurotrophic factor (BDNF) pathway. Findings on CM, BDNF and brain volume are inconsistent and have never accounted for the entire BDNF pathway. We examined the effects of CM, BDNF (genotype, gene expression and protein level) and their interactions on hippocampus, amygdala and anterior cingulate cortex (ACC) morphology. Data were collected from patients with depression and/or an anxiety disorder and healthy subjects within the Netherlands Study of Depression and Anxiety (NESDA) (N = 289). CM was assessed using the Childhood Trauma Interview. BDNF Val66Met genotype, gene expression and serum protein levels were determined in blood and T1 MRI scans were acquired at 3T. Regional brain morphology was assessed using FreeSurfer. Covariate-adjusted linear regression analyses were performed. Amygdala volume was lower in maltreated individuals. This was more pronounced in maltreated met-allele carriers. The expected positive relationship between BDNF gene expression and volume of the amygdala is attenuated in maltreated subjects. Finally, decreased cortical thickness of the ACC was identified in maltreated subjects with the val/val genotype. CM was associated with altered brain morphology, partly in interaction with multiple levels of the BNDF pathway. Our results suggest that CM has different effects on brain morphology in met-carriers and val-homozygotes and that CM may disrupt the neuroprotective effect of BDNF. [ABSTRACT FROM AUTHOR]

Background A chronic course of major depressive disorder (MDD) is associated with profound alterations in brain volumes and emotional and cognitive processing. However, no neurobiological markers have been identified that prospectively predict MDD course trajectories. This study evaluated the prognostic value of different neuroimaging modalities, clinical characteristics, and their combination to classify MDD course trajectories. Methods One hundred eighteen MDD patients underwent structural and functional magnetic resonance imaging (MRI) (emotional facial expressions and executive functioning) and were clinically followed-up at 2 years. Three MDD trajectories (chronic n = 23, gradual improving n = 36, and fast remission n = 59) were identified based on Life Chart Interview measuring the presence of symptoms each month. Gaussian process classifiers were employed to evaluate prognostic value of neuroimaging data and clinical characteristics (including baseline severity, duration, and comorbidity). Results Chronic patients could be discriminated from patients with more favorable trajectories from neural responses to various emotional faces (up to 73% accuracy) but not from structural MRI and functional MRI related to executive functioning. Chronic patients could also be discriminated from remitted patients based on clinical characteristics (accuracy 69%) but not when age differences between the groups were taken into account. Combining different task contrasts or data sources increased prediction accuracies in some but not all cases. Conclusions Our findings provide evidence that the prediction of naturalistic course of depression over 2 years is improved by considering neuroimaging data especially derived from neural responses to emotional facial expressions. Neural responses to emotional salient faces more accurately predicted outcome than clinical data. [ABSTRACT FROM AUTHOR]

Objective Structural MRI studies investigating the neural correlates of OCD have been numerous. Nevertheless, results of these studies have not always been consistent. Variability in study results may partially be explained by small sample sizes resulting in limited statistical power, clinical heterogeneity between patient samples, and methodological differences between studies. In this context, we initiated the ENIGMA-OCD working group. Our aim is to identify robust imaging markers of OCD using coordinated standardized image processing and statistical analysis protocols. Here, we perform the largest study to date of subcortical brain volumes in OCD patients and healthy controls using an individual participant data (IPD) based meta-analysis approach. Methods Structural T1-weightred MRI scans from 3722 subjects (361 paediatric OCD patients, 1574 adult OCD patients, 314 paediatric controls and 1473 adult controls) from 25 research sites worldwide were analysed using FreeSurfer 5.3. Segmentations of subcortical regions, lateral ventricles and total intracranial volumes (ICV) were visually inspected for accuracy and compared between patients and controls using regression models controlling for age, sex, and ICV. Each site followed standardized protocols designed to facilitate harmonized image analysis across multiple sites. Separate stratified analyses assessing effects of age of onset, disease duration, symptom dimensions, and symptom severity were performed. Results were combined in random-effects meta-analysis models. Meta-regression analyses were used to test whether mean age of each sample and field strength of MR images explained a significant proportion of the variance in effect seizes across sites in the meta-analysis. Results were considered significant if they exceeded a Bonferroni corrected P-value threshold (p=0.05/9 regions = 5.6x10 -3 ). Results Adult patients, compared to adult controls, had significantly smaller hippocampal volumes (Cohen’s d= -0.15, p= 7.4x10 -4 ) and bigger pallidum volumes (d= 0.16, p=1.8x10 -3 ). This effect was notably stronger in medicated patients versus controls (d= -0.29, p=2.8x10 -6 and d= 0.24, p=2.5x10 -4 , respectively). The hippocampus effect seemed to be driven by patients with comorbid depression d= 0.29, p=4.8x10 -5 ). Also, symptom severity was associated with a smaller hippocampus (R= -0.08, p=4.9x10 -3 ). Sample characteristics such as mean age and field strength did not moderate brain volume alterations. None of the subcortical structures, neither ICV nor lateral ventricles were significantly different between paediatric OCD cases and controls after Bonferroni correction. However, unmedicated paediatric patients show bigger thalamus volumes (d= 0.40, p=9.0x10 -4 ) relative to control children. Additionally, longer disease duration and ad trend-significant level, younger age of onset was associated with bigger thalamus volume in paediatric OCD (d= 0.18, p=5.1x10 -3 and d= -0.17, p=5.7x10 -3 , respectively). Conclusion Results of this subcortical meta-analysis indicate a key role of the pallidum in the pathophysiology of OCD. Different ENIGMA disease working groups, such as MDD, schizophrenia, and bipolar disorder also observed hippocampal abnormalities, which suggests that our findings regarding hippocampal abnormalities are aspecific for OCD. In addition, we showed that unmedicated paediatric OCD patients have significantly enlarged thalamus volumes. Moreover, our findings suggest a different pattern of subcortical abnormalities in paediatric OCD patients and adult OCD patients in line with the developmental nature of the disease. [ABSTRACT FROM AUTHOR]

Background: Chronic alcohol abuse is associated with deficits in cognitive control functions. Cognitive control is likely to be mediated through the interaction between intrinsic large-scale brain networks involved in externally oriented executive functioning and internally focused thought processing. Improving the interaction between these functional brain networks could be an important target for treatment. Therefore, the current study aimed to investigate the effects of the cognitive enhancer modafinil on within-network and between-network resting-state functional connectivity and cognitive control functions in alcohol-dependent patients. Methods: In a double-blind, placebo-controlled cross-over design, resting-state functional magnetic resonance imaging and a Stroop task were employed in alcohol-dependent patients (n = 15) and healthy control subjects (n = 16). Within-network and between-network functional connectivity was calculated using a combination of independent component analysis and functional network connectivity analysis. Results: Modafinil significantly increased the negative coupling between executive networks and the default mode network, which was associated with modafinil-induced improvement in cognitive control in alcohol-dependent patients. Conclusions: These findings demonstrate that modafinil at least partly exerts its effects by targeting intrinsic functional relationships between large-scale brain systems underlying cognitive control. The current study therefore provides a neurobiological rationale for implementing modafinil as an adjunct in the treatment of alcohol dependence, although clinical studies are needed to substantiate this promise. [ABSTRACT FROM AUTHOR]

Background Differences in clinical characteristics between early and late onset alcohol dependent patients have been examined intensively, but little is known about the differences in neuropsychological functioning between these patient groups. Clinical characteristics and neuropsychological functions of inpatients with early onset and late onset alcohol dependence are therefore investigated in this study. Methods Ninety-three abstinent alcohol dependent inpatients meeting a current diagnosis of DSM- IV alcohol dependence were divided into early onset alcohol dependent patients ( EOA; ≤25 years; n = 36) and late onset alcohol dependent patients (LOA; >25 years; n = 57). Patients using psychoactive medication and patients dependent on other substances than alcohol (and nicotine) were excluded. A comprehensive neuropsychological test battery was administered. Results EOA reported higher trait impulsivity, antisocial traits, and attention deficit hyperactivity disorder-related traits and exhibited an impulsive reflection style, especially in a high-risk context, compared with LOA. Against expectations, EOA performed significantly better on measures of planning, cognitive control, visual memory, and delayed recognition memory than LOA, whereas no significant group differences occurred on measures of delay discounting, digit span, and attention. Better Stroop interference, better visual memory, and a more impulsive reflection style was predictive of an early age of onset, and explained a significant and additional amount of variance (18.8%) on top of the clinical characteristics, together explaining 53.4% of the variance. Conclusions Both clinical characteristics and neuropsychological variables contributed independently to the age of onset of problematic alcohol use. Results indicate that especially an impulsive reflection style, besides higher trait impulsivity, may be the core feature of early onset alcohol dependence. However, the contribution of the neuropsychological variables is complex and more research is needed to clarify the role of psychiatric comorbidity and poly-substance abuse in an unselected sample of alcohol dependent patients. [ABSTRACT FROM AUTHOR]

Background: Impaired response inhibition is a key feature of patients with alcohol dependence. Improving impulse control is a promising target for the treatment of alcohol dependence. The pharmacologic agent modafinil enhances cognitive control functions in both healthy subjects and in patients with various psychiatric disorders. However, very little is known about the underlying neural correlates of improvements in response inhibition following modafinil. Methods: We conducted a randomized, double-blind, placebo-controlled, crossover study using functional magnetic resonance imaging with a stop signal task to examine effects of a single dose of modafinil (200 mg) on response inhibition and underlying neural correlates in abstinent alcohol-dependent patients (AD) (n = 16) and healthy control subjects (n = 16). Results: Within the AD group modafinil administration improved response inhibition (reflected by the stop signal reaction time [SSRT]) in subjects with initial poor response inhibition, whereas response inhibition was diminished in better performing subjects. In AD patients with initial poor response inhibition, modafinil-induced SSRT improvement was accompanied by greater activation in the thalamus and supplementary motor area (SMA) and reduced connectivity between the thalamus and the primary motor cortex. In addition, the relationship between baseline response inhibition and modafinil-induced SSRT improvement was mediated by these changes in thalamus and SMA activation. Conclusions: These findings indicate that modafinil can improve response inhibition in alcohol-dependent patients through its effect on thalamus and SMA function but only in subjects with poor baseline response inhibition. Therefore, baseline levels of response inhibition should be taken into account when considering treatment with modafinil in AD. [ABSTRACT FROM AUTHOR]

Treatment with N-acetylcysteine (NAC) normalizes glutamate (Glu) homeostasis and prevents relapse in drug-dependent animals. However, the effect of NAC on brain Glu levels in substance-dependent humans has not yet been investigated. Proton magnetic resonance spectroscopy (1H MRS) was used to investigate Glu changes in the dorsal anterior cingulate cortex (dACC) after a single dose of NAC in cocaine-dependent patients and normal controls. In an open-label, randomized, crossover study, 8 cocaine-dependent patients and 14 healthy controls underwent two scan sessions: one group receiving no compound and the other following a single administration of 2400 mg NAC. The Barratt Impulsiveness Scale was administered to examine the relation between dACC Glu levels and impulsivity. In the medication-free condition, Glu levels in the dACC were significantly higher in cocaine-dependent patients compared with healthy controls. After administration of NAC, Glu levels were reduced in the cocaine-dependent group, whereas NAC had no effect in healthy controls. Higher baseline Glu levels were associated with higher impulsivity, and both were predictive of greater NAC-induced Glu reduction. The current findings indicate that NAC can normalize elevated Glu levels in cocaine-dependent patients. These findings may have important implications for treatment, because abnormal Glu levels are related to relapse, and treatment with NAC prevented relapse in animal studies. Furthermore, clinical studies have indicated beneficial effects of NAC in cocaine-dependent patients, and the current study suggests that these beneficial effects might in part be mediated by the ability of NAC to normalize glutamatergic abnormalities. [ABSTRACT FROM AUTHOR]

Maladaptive impulsivity is a core symptom in various psychiatric disorders. However, there is only limited evidence available on whether different measures of impulsivity represent largely unrelated aspects or a unitary construct. In a cross-species translational study, thirty rats were trained in impulsive choice (delayed reward task) and impulsive action (five-choice serial reaction time task) paradigms. The correlation between those measures was assessed during baseline performance and after pharmacological manipulations with the psychostimulant amphetamine and the norepinephrine reuptake inhibitor atomoxetine. In parallel, to validate the animal data, 101 human subjects performed analogous measures of impulsive choice (delay discounting task, DDT) and impulsive action (immediate and delayed memory task, IMT/DMT). Moreover, all subjects completed the Stop Signal Task (SST, as an additional measure of impulsive action) and filled out the Barratt impulsiveness scale (BIS-11). Correlations between DDT and IMT/DMT were determined and a principal component analysis was performed on all human measures of impulsivity. In both rats and humans measures of impulsive choice and impulsive action did not correlate. In rats the within-subject pharmacological effects of amphetamine and atomoxetine did not correlate between tasks, suggesting distinct underlying neural correlates. Furthermore, in humans, principal component analysis identified three independent factors: (1) self-reported impulsivity (BIS-11); (2) impulsive action (IMT/DMT and SST); (3) impulsive choice (DDT). This is the first study directly comparing aspects of impulsivity using a cross-species translational approach. The present data reveal the non-unitary nature of impulsivity on a behavioral and pharmacological level. Collectively, this warrants a stronger focus on the relative contribution of distinct forms of impulsivity in psychopathology. [ABSTRACT FROM AUTHOR]

Relapse is the rule rather than the exception in smokers aiming to quit smoking. Recently, evidence has emerged that glutamate transmission plays an important role in relapse. N-acetylcysteine (NAC), a cysteine prodrug, restores glutamate homeostasis and appears to be a potential new treatment for substance dependence. In the current pilot study, the effects of NAC on short-term abstinence of smoking were investigated. Subjects were heavy smokers randomized to receive placebo (n = 12) or NAC 3,600 mg/day (n = 10) in a double-blind fashion during 3.5 days. Subjects were asked to stop smoking and report on nicotine craving, nicotine withdrawal symptoms, and cigarette smoking during treatment. At the end of the treatment, subjects were invited to smoke a cigarette and to rate the rewarding effect of this cigarette. There was no significant effect of NAC on craving (p = 0.23, d = 0.52) and only a statistical trend towards fewer withdrawal symptoms in the NAC condition (p = 0.07, d = 0.80). Interestingly, subjects receiving NAC rated the first cigarette after the abstinence period of 3.5 days as significantly less rewarding than subjects on placebo (p = 0.04, d = 0.85). It is concluded that the results of this pilot study are encouraging and suggest that NAC might be a promising new treatment option for relapse prevention in nicotine dependence. Copyright © 2011 S. Karger AG, Basel [ABSTRACT FROM AUTHOR]

The article reports that heterogeneity remains a challenge within the current nosology of most mental disorders, but more so for mood disorders. Topics include examines this is partly be due to the expanded conceptualization of major mood episodes and disorders over the successive iterations of international classificatory systems.

This Special Issue of Human Brain Mapping is dedicated to a 10‐year anniversary of the Enhancing NeuroImaging Genetics through Meta‐Analysis (ENIGMA) Consortium. It reports updates from a broad range of international neuroimaging projects that pool data from around the world to answer fundamental questions in neuroscience. Since ENIGMA was formed in December 2009, the initiative grew into a worldwide effort with over 2,000 participating scientists from 45 countries, and over 50 working groups leading large‐scale studies of human brain disorders. Over the last decade, many lessons were learned on how best to pool brain data from diverse sources. Working groups were created to develop methods to analyze worldwide data from anatomical and diffusion magnetic resonance imaging (MRI), resting state and task‐based functional MRI, electroencephalography (EEG), magnetoencephalography (MEG), and magnetic resonance spectroscopy (MRS). The quest to understand genetic effects on human brain development and disease also led to analyses of brain scans on an unprecedented scale. Genetic roadmaps of the human cortex were created by researchers worldwide who collaborated to perform statistically well‐powered analyses of common and rare genetic variants on brain measures and rates of brain development and aging. Here, we summarize the 31 papers in this Special Issue, covering: (a) technical approaches to harmonize analysis of different types of brain imaging data, (b) reviews of the last decade of work by several of ENIGMA's clinical and technical working groups, and (c) new empirical papers reporting large‐scale international brain mapping analyses in patients with substance use disorders, schizophrenia, bipolar disorders, major depression, posttraumatic stress disorder, obsessive compulsive disorder, epilepsy, and stroke. [ABSTRACT FROM AUTHOR]

Dysfunctional mental imagery is integral to the maintenance of many psychological disorders and is typically associated with stronger affective and behavioural responses than verbal cognitions. This finding extends itself to the high prevalence of suicidal mental imagery in disorders such as depression and bipolar disorder. Imagery Rescripting is a therapy approach which has been found to effectively reduce dysfunctional mental images across various mental health conditions. Thus, Imagery Rescripting of suicidal mental imagery may be effective at reducing such cognitions and ultimately associated risk. However, this remains an unexplored area within the treatment literature. This paper puts out an urgent call for clinical research to evaluate the effectiveness of such a treatment intervention, and to assist, we propose and describe a clinical approach to this to stimulate further thought and research. There are also many research questions of clinical relevance that must be explored in this field of work, which we put forward and consider in this commentary piece. What is already known about this topic: Mental imagery is a form of cognition that generates stronger emotional responses compared to verbal-linguistic thinking and is integral to the maintenance of most psychological disorders. Cognitive Behavioural Therapy (CBT) approaches are typically more effective when mental imagery techniques – such as Imagery Rescripting (ImRs) – are incorporated to target intrusive, distressing mental imagery. Mental images of suicide (comprised of both flash-back and/or flash-forward mental images) are more distressing, realistic and promote suicidal behaviours more than verbal thoughts, and are common in disorders such as depression and bipolar disorder. What this topic adds: Urgent clinical research is needed to evaluate the effectiveness of ImRs at reducing intrusive suicidal mental images, and thus related risk, and this paper proposes and describes an approach for researchers to use as a framework. There are several clinical research considerations to be made when examining ImRs of suicidal mental images, including around the delivery and safety of the intervention. More research is needed to clarify the above clinical considerations, and to further understand change mechanisms, to learn the most safe and effective ImRs approach. If ImRs is found to be effective at reducing suicidal images in upcoming clinical trials, it is strongly recommended clinicians receive adequate training and ongoing clinical supervision from an experienced practitioner given the complexities around this approach. [ABSTRACT FROM AUTHOR]

Background: Depressive and anxiety disorders have shown to be associated to premature or advanced biological aging and consequently to adversely impact somatic health. Treatments with antidepressant medication or running therapy are both found to be effective for many but not all patients with mood and anxiety disorders. These interventions may, however, work through different pathophysiological mechanisms and could differ in their impact on biological aging and somatic health. This study protocol describes the design of an unique intervention study that examines whether both treatments are similarly effective in reducing or reversing biological aging (primary outcome), psychiatric status, metabolic stress and neurobiological indicators (secondary outcomes). Methods: The MOod Treatment with Antidepressants or Running (MOTAR) study will recruit a total of 160 patients with a current major depressive and/or anxiety disorder in a mental health care setting. Patients will receive a 16-week treatment with either antidepressant medication or running therapy (3 times/week). Patients will undergo the treatment of their preference and a subsample will be randomized (1:1) to overcome preference bias. An additional no-disease-no-treatment group of 60 healthy controls without lifetime psychopathology, will be included as comparison group for primary and secondary outcomes at baseline. Assessments are done at week 0 for patients and controls, and at week 16 and week 52 for patients only, including written questionnaires, a psychiatric and medical examination, blood, urine and saliva collection and a cycle ergometer test, to gather information about biological aging (telomere length and telomerase activity), mental health (depression and anxiety disorder characteristics), general fitness, metabolic stress-related biomarkers (inflammation, metabolic syndrome, cortisol) and genetic determinants. In addition, neurobiological alterations in brain processes will be assessed using structural and functional Magnetic Resonance Imaging (MRI) in a subsample of at least 25 patients per treatment arm and in all controls. Discussion: This intervention study aims to provide a better understanding of the impact of antidepressant medication and running therapy on biological aging, metabolic stress and neurobiological indicators in patients with depressive and anxiety disorders in order to guide a more personalized medicine treatment. Trial registration: Trialregister.nl Number of identification: NTR3460, May 2012. [ABSTRACT FROM AUTHOR]

Background: Existing treatments for young people with severe depression have limited effectiveness. The aim of the Study of Ketamine for Youth Depression (SKY-D) trial is to determine whether a 4-week course of low-dose subcutaneous ketamine is an effective adjunct to treatment-as-usual in young people with major depressive disorder (MDD). Methods: SKY-D is a double-masked, randomised controlled trial funded by the Australian Government's National Health and Medical Research Council (NHMRC). Participants aged between 16 and 25 years (inclusive) with moderate-to-severe MDD will be randomised to receive either low-dose ketamine (intervention) or midazolam (active control) via subcutaneous injection once per week for 4 weeks. The primary outcome is change in depressive symptoms on the Montgomery-Åsberg Depression Rating Scale (MADRS) after 4 weeks of treatment. Further follow-up assessment will occur at 8 and 26 weeks from treatment commencement to determine whether treatment effects are sustained and to investigate safety outcomes. Discussion: Results from this trial will be important in determining whether low-dose subcutaneous ketamine is an effective treatment for young people with moderate-to-severe MDD. This will be the largest randomised trial to investigate the effects of ketamine to treat depression in young people. Trial registration: Australian and New Zealand Clinical Trials Registry ID: ACTRN12619000683134. Registered on May 7, 2019. https://www.anzctr.org.au/Trial/Registration/TrialReview.aspx?id=377513. [ABSTRACT FROM AUTHOR]

Objective: Most evidence for structural brain abnormalities associated with adolescent depression is based on cross-sectional study designs that do not take into account the dynamic course of depressive symptoms and brain maturation across adolescence. In this study, a longitudinal design was used to investigate the association between different trajectories of depressive symptoms and longitudinal changes in brain structure throughout adolescence.Method: One hundred forty-nine adolescents were assessed on depressive symptoms and underwent structural magnetic resonance imaging at 12 years of age and were followed up multiple times until 19 years. Three depressive symptom trajectories (low-stable [n = 97], early-decreasing [n = 33], late-increasing [n = 19]) were identified, and effects of group and group by time on hippocampus and amygdala volume and prefrontal cortical thickness and surface area were evaluated.Results: The early-decreasing symptoms group exhibited differences in cortical surface area compared to the low-stable and late-increasing symptoms groups, moderated by sex. Specifically, females in the early-decreasing symptoms group showed lower anterior cingulate and orbitofrontal cortex surface areas across adolescence compared to females in the other groups. Males in the early-decreasing symptoms group showed lower right orbitofrontal cortex surface area expansion over time compared to males in the low-stable and late-increasing symptoms groups. No effects were found for cortical thickness or for hippocampus and amygdala volume.Conclusion: Alterations in cortical surface area were specifically observed in young people experiencing depressive symptoms in early adolescence. These findings suggest that early adolescence is a particularly sensitive period for cortical surface area abnormalities associated with depressive symptoms and could provide a critical window for treatment of (subthreshold) depressive symptoms. [ABSTRACT FROM AUTHOR]

Emerging evidence suggests distinct neurobiological correlates of alcohol use disorder (AUD) between sexes, which however remain largely unexplored. This work from ENIGMA Addiction Working Group aimed to characterize the sex differences in gray matter (GM) and white matter (WM) correlates of AUD using a whole‐brain, voxel‐based, multi‐tissue mega‐analytic approach, thereby extending our recent surface‐based region of interest findings on a nearly matching sample using a complementary methodological approach. T1‐weighted magnetic resonance imaging (MRI) data from 653 people with AUD and 326 controls was analyzed using voxel‐based morphometry. The effects of group, sex, group‐by‐sex, and substance use severity in AUD on brain volumes were assessed using General Linear Models. Individuals with AUD relative to controls had lower GM volume in striatal, thalamic, cerebellar, and widespread cortical clusters. Group‐by‐sex effects were found in cerebellar GM and WM volumes, which were more affected by AUD in females than males. Smaller group‐by‐sex effects were also found in frontotemporal WM tracts, which were more affected in AUD females, and in temporo‐occipital and midcingulate GM volumes, which were more affected in AUD males. AUD females but not males showed a negative association between monthly drinks and precentral GM volume. Our results suggest that AUD is associated with both shared and distinct widespread effects on GM and WM volumes in females and males. This evidence advances our previous region of interest knowledge, supporting the usefulness of adopting an exploratory perspective and the need to include sex as a relevant moderator variable in AUD. [ABSTRACT FROM AUTHOR]

Objective: To develop targeted treatment for young people experiencing mental illness, a better understanding of the biological, psychological, and social changes is required, particularly during the early stages of illness. To do this, large datasets need to be collected using standardized methods. A harmonized data collection protocol was tested in a youth mental health research setting to determine its acceptability and feasibility. Method: Eighteen participants completed the harmonization protocol, including a clinical interview, self‐report measures, neurocognitive measures, and mock assessments of magnetic resonance imaging (MRI) and blood. The feasibility of the protocol was assessed by recording recruitment rates, study withdrawals, missing data, and protocol deviations. Subjective responses from participant surveys and focus groups were used to examine the acceptability of the protocol. Results: Twenty‐eight young people were approached, 18 consented, and four did not complete the study. Most participants reported positive subjective impressions of the protocol as a whole and showed interest in participating in the study again, if given the opportunity. Participants generally perceived the MRI and neurocognitive tasks as interesting and suggested that the assessment of clinical presentation could be shortened. Conclusion: Overall, the harmonized data collection protocol appeared to be feasible and generally well‐accepted by participants. With a majority of participants finding the assessment of clinical presentation too long and repetitive, the authors have made suggestions to shorten the self‐reports. The broader implementation of this protocol could allow researchers to create large datasets and better understand how psychopathological and neurobiological changes occur in young people with mental ill‐health. [ABSTRACT FROM AUTHOR]

Metabolic illnesses (MET) are detrimental to brain integrity and are common comorbidities in patients with mental illnesses, including major depressive disorder (MDD). We quantified effects of MET on standard regional brain morphometric measures from 3D brain MRI as well as diffusion MRI in a large sample of UK BioBank participants. The pattern of regional effect sizes of MET in non‐psychiatric UKBB subjects was significantly correlated with the spatial profile of regional effects reported by the largest meta‐analyses in MDD but not in bipolar disorder, schizophrenia or Alzheimer's disease. We used a regional vulnerability index (RVI) for MET (RVI‐MET) to measure individual's brain similarity to the expected patterns in MET in the UK Biobank sample. Subjects with MET showed a higher effect size for RVI‐MET than for any of the individual brain measures. We replicated elevation of RVI‐MET in a sample of MDD participants with MET versus non‐MET. RVI‐MET scores were significantly correlated with the volume of white matter hyperintensities, a neurological consequence of MET and age, in both groups. Higher RVI‐MET in both samples was associated with obesity, tobacco smoking and frequent alcohol use but was unrelated to antidepressant use. In summary, MET effects on the brain were regionally specific and individual similarity to the pattern was more strongly associated with MET than any regional brain structural metric. Effects of MET overlapped with the reported brain differences in MDD, likely due to higher incidence of MET, smoking and alcohol use in subjects with MDD. [ABSTRACT FROM AUTHOR]

Childhood adversity plays an important role for development of major depressive disorder (MDD). There are differences in subcortical brain structures between patients with MDD and healthy controls, but the specific impact of childhood adversity on such structures in MDD remains unclear. Thus, aim of the present study was to investigate whether childhood adversity is associated with subcortical volumes and how it interacts with a diagnosis of MDD and sex. Within the ENIGMA-MDD network, nine university partner sites, which assessed childhood adversity and magnetic resonance imaging in patients with MDD and controls, took part in the current joint mega-analysis. In this largest effort world-wide to identify subcortical brain structure differences related to childhood adversity, 3036 participants were analyzed for subcortical brain volumes using FreeSurfer. A significant interaction was evident between childhood adversity, MDD diagnosis, sex, and region. Increased exposure to childhood adversity was associated with smaller caudate volumes in females independent of MDD. All subcategories of childhood adversity were negatively associated with caudate volumes in females - in particular emotional neglect and physical neglect (independently from age, ICV, imaging site and MDD diagnosis). There was no interaction effect between childhood adversity and MDD diagnosis on subcortical brain volumes. Childhood adversity is one of the contributors to brain structural abnormalities. It is associated with subcortical brain abnormalities that are relevant to psychiatric disorders such as depression. [ABSTRACT FROM AUTHOR]

Objectives Recent studies have indicated that pattern recognition techniques of functional magnetic resonance imaging ( fMRI) data for individual classification may be valuable for distinguishing between major depressive disorder ( MDD) and bipolar disorder ( BD). Importantly, medication may have affected previous classification results as subjects with MDD and BD use different classes of medication. Furthermore, almost all studies have investigated only depressed subjects. Therefore, we focused on medication-free subjects. We additionally investigated whether classification would be mood state independent by including depressed and remitted subjects alike. Methods We applied Gaussian process classifiers to investigate the discriminatory power of structural MRI (gray matter volumes of emotion regulation areas) and resting-state fMRI (resting-state networks implicated in mood disorders: default mode network [ DMN], salience network [ SN], and lateralized frontoparietal networks [ FPNs]) in depressed (n=42) and remitted (n=49) medication-free subjects with MDD and BD. Results Depressed subjects with MDD and BD could be classified based on the gray matter volumes of emotion regulation areas as well as DMN functional connectivity with 69.1% prediction accuracy. Prediction accuracy using the FPNs and SN did not exceed chance level. It was not possible to discriminate between remitted subjects with MDD and BD. Conclusions For the first time, we showed that medication-free subjects with MDD and BD can be differentiated based on structural MRI as well as resting-state functional connectivity. Importantly, the results indicated that research concerning diagnostic neuroimaging tools distinguishing between MDD and BD should consider mood state as only depressed subjects with MDD and BD could be correctly classified. Future studies, in larger samples are needed to investigate whether the results can be generalized to medication-naïve or first-episode subjects. [ABSTRACT FROM AUTHOR]

Objective: Each year, around one million people die by suicide. Despite its recognition as a public health concern, large-scale research on causal determinants of suicide attempt risk is scarce. Here, we leverage results from a recent genome-wide association study (GWAS) of suicide attempt to perform a data-driven screening of traits causally associated with suicide attempt. Methods: We performed a hypothesis-generating phenome-wide screening of causal relationships between suicide attempt risk and 1520 traits, which have been systematically aggregated on the Complex-Traits Genomics Virtual Lab platform. We employed the latent causal variable (LCV) method, which uses results from GWAS to assess whether a causal relationship can explain a genetic correlation between two traits. If a trait causally influences another one, the genetic variants that increase risk for the causal trait will also increase the risk for the outcome inducing a genetic correlation. Nonetheless, a genetic correlation can also be observed when traits share common pathways. The LCV method can assess whether the pattern of genetic effects for two genetically correlated traits support a causal association rather than a shared aetiology. Results: Our approach identified 62 traits that increased risk for suicide attempt. Risk factors identified can be broadly classified into (1) physical health disorders, including oesophagitis, fibromyalgia, hernia and cancer; (2) mental health-related traits, such as depression, substance use disorders and anxiety; and (3) lifestyle traits including being involved in combat or exposure to a war zone, and specific job categories such as being a truck driver or machine operator. Conclusions: Suicide attempt risk is likely explained by a combination of behavioural phenotypes and risk for both physical and psychiatric disorders. Our results also suggest that substance use behaviours and pain-related conditions are associated with an increased suicide attempt risk, elucidating important causal mechanisms that underpin this significant public health problem. [ABSTRACT FROM AUTHOR]

It is increasingly recognized that multiple psychiatric conditions are underpinned by shared neural pathways, affecting similar brain systems. Here, we carried out a multiscale neural contextualization of shared alterations of cortical morphology across six major psychiatric conditions (autism spectrum disorder, attention deficit/hyperactivity disorder, major depression disorder, obsessive-compulsive disorder, bipolar disorder, and schizophrenia). Our framework cross-referenced shared morphological anomalies with respect to cortical myeloarchitecture and cytoarchitecture, as well as connectome and neurotransmitter organization. Pooling disease-related effects on MRI-based cortical thickness measures across six ENIGMA working groups, including a total of 28,546 participants (12,876 patients and 15,670 controls), we identified a cortex-wide dimension of morphological changes that described a sensory-fugal pattern, with paralimbic regions showing the most consistent alterations across conditions. The shared disease dimension was closely related to cortical gradients of microstructure as well as neurotransmitter axes, specifically cortex-wide variations in serotonin and dopamine. Multiple sensitivity analyses confirmed robustness with respect to slight variations in analytical choices. Our findings embed shared effects of common psychiatric conditions on brain structure in multiple scales of brain organization, and may provide insights into neural mechanisms of transdiagnostic vulnerability. Individuals across six major psychiatric conditions from the ENIGMA consortium reveals a shared morphological effect, following a sensory-fugal axis, which is related to microstructural gradient and neurotransmitter axes. [ABSTRACT FROM AUTHOR]

Traditionally, neurobiological research on psychopathy has focused on categorical differences in adults. However, there is evidence that psychopathy is best described by a set of relatively independent personality dimensions, that is, callous-unemotional, grandiose-manipulative, and impulsive-irresponsible traits, which can be reliably detected in juveniles, allowing investigation of the neural mechanisms leading to psychopathy. Furthermore, complex psychiatric disorders like psychopathy are increasingly being conceptualized as disorders of brain networks. The intrinsic organization of the brain in such networks is reflected by coherent fluctuations in resting state networks (RSNs), but these have not been studied in sufficient detail in relation to juvenile psychopathic traits yet. The current study investigated the distinct associations of juvenile psychopathic traits dimensions with RSN connectivity. Resting-state functional MRI and independent component analysis were used to assess RSN connectivity in a large sample of adolescents (n=130, mean age 17.8 years) from a childhood arrestee cohort. Associations between scores on each of the three psychopathic traits dimensions and connectivity within and between relevant RSNs were investigated. Callous-unemotional traits were related to aberrant connectivity patterns of the default mode network, which has been implicated in self-referential and moral processes. Impulsive-irresponsible traits were associated with altered connectivity patterns in the frontoparietal cognitive control networks. Grandiose-manipulative traits were not associated with altered connectivity patterns. These findings confirm the association between psychopathic traits and brain network connectivity, and considerably add to emerging evidence supporting neurobiological heterogeneity in the processes leading to psychopathy. [ABSTRACT FROM AUTHOR]

The reproducibility crisis in neuroimaging has led to an increased demand for standardized data processing workflows. Within the ENIGMA consortium, we developed HALFpipe (Harmonized Analysis of Functional MRI pipeline), an open‐source, containerized, user‐friendly tool that facilitates reproducible analysis of task‐based and resting‐state fMRI data through uniform application of preprocessing, quality assessment, single‐subject feature extraction, and group‐level statistics. It provides state‐of‐the‐art preprocessing using fMRIPrep without the requirement for input data in Brain Imaging Data Structure (BIDS) format. HALFpipe extends the functionality of fMRIPrep with additional preprocessing steps, which include spatial smoothing, grand mean scaling, temporal filtering, and confound regression. HALFpipe generates an interactive quality assessment (QA) webpage to rate the quality of key preprocessing outputs and raw data in general. HALFpipe features myriad post‐processing functions at the individual subject level, including calculation of task‐based activation, seed‐based connectivity, network‐template (or dual) regression, atlas‐based functional connectivity matrices, regional homogeneity (ReHo), and fractional amplitude of low‐frequency fluctuations (fALFF), offering support to evaluate a combinatorial number of features or preprocessing settings in one run. Finally, flexible factorial models can be defined for mixed‐effects regression analysis at the group level, including multiple comparison correction. Here, we introduce the theoretical framework in which HALFpipe was developed, and present an overview of the main functions of the pipeline. HALFpipe offers the scientific community a major advance toward addressing the reproducibility crisis in neuroimaging, providing a workflow that encompasses preprocessing, post‐processing, and QA of fMRI data, while broadening core principles of data analysis for producing reproducible results. Instructions and code can be found at https://github.com/HALFpipe/HALFpipe. [ABSTRACT FROM AUTHOR]

This review compares the main brain abnormalities in schizophrenia (SZ), bipolar disorder (BD), major depressive disorder (MDD), and 22q11.2 Deletion Syndrome (22q11DS) determined by ENIGMA (Enhancing Neuro Imaging Genetics through Meta Analysis) consortium investigations. We obtained ranked effect sizes for subcortical volumes, regional cortical thickness, cortical surface area, and diffusion tensor imaging abnormalities, comparing each of these disorders relative to healthy controls. In addition, the studies report on significant associations between brain imaging metrics and disorder‐related factors such as symptom severity and treatments. Visual comparison of effect size profiles shows that effect sizes are generally in the same direction and scale in severity with the disorders (in the order SZ > BD > MDD). The effect sizes for 22q11DS, a rare genetic syndrome that increases the risk for psychiatric disorders, appear to be much larger than for either of the complex psychiatric disorders. This is consistent with the idea of generally larger effects on the brain of rare compared to common genetic variants. Cortical thickness and surface area effect sizes for 22q11DS with psychosis compared to 22q11DS without psychosis are more similar to those of SZ and BD than those of MDD; a pattern not observed for subcortical brain structures and fractional anisotropy effect sizes. The observed similarities in effect size profiles for cortical measures across the psychiatric disorders mimic those observed for shared genetic variance between these disorders reported based on family and genetic studies and are consistent with shared genetic risk for SZ and BD and structural brain phenotypes. [ABSTRACT FROM AUTHOR]

Cognitive deficits are highly prevalent in alcohol-dependent (AD) patients and may have a detrimental impact on treatment response and treatment outcome. Enhancing cognitive functions may improve treatment success. Modafinil is a promising compound in this respect. Therefore, a randomized double-blind placebo-controlled trial was conducted with modafinil (300 mg/d) or placebo in 83 AD patients for 10 weeks. Various cognitive functions (digit span task, Tower of London task, Stroop task) were measured at baseline, during and after treatment. Compared to placebo, modafinil improved verbal short-term memory (number of forward digit spans) (p=0.030), but modafinil exerted a negative effect on the working memory score of the digit span task (p=0.003). However, subgroup analyses revealed that modafinil did improve both working memory and verbal short-term memory in AD patients with a poor working memory ability at baseline (25% worst performers), whereas no significant treatment effect of modafinil was found on these two dependent variables in patients with good working memory skills at baseline (25% best performers). No effect of modafinil was found on measures of planning (Tower of London task) and selective attention (Stroop task). Further research is needed to better understand the relationship between cognitive remediation and treatment outcome in order to design targeted treatments. [ABSTRACT FROM PUBLISHER]

Aim: The concept of severe and complex youth depression has evolved from clinical experience. Here we conducted a file audit study to evaluate supporting data for the construct. Methods: A retrospective file audit was undertaken with 84 consecutively discharged patients over 6‐months from Orygen's Youth Mood Clinic (YMC; 50% female). Results: Over a third (36.9%) were disengaged from vocation and education, with exposure to traumatic events common (84.5%). Almost all patients (91.7%) reported past 2‐week suicidal ideation at clinic entry. Hospital emergency departments were the most frequent referral source (31.0%). Most (72.6%) had received previous mental health treatment. Multimorbidity was frequently observed. The presence of a substance use disorder, or ≥ 3 comorbidities were both associated with a greater likelihood of prior suicide attempt. Conclusions: These data highlight the clinical needs associated with severe and complex depression. Findings have implications for youth experiencing mood disorders attending tertiary and community mental health settings. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

Structural hippocampal abnormalities are common in many neurological and psychiatric disorders, and variation in hippocampal measures is related to cognitive performance and other complex phenotypes such as stress sensitivity. Hippocampal subregions are increasingly studied, as automated algorithms have become available for mapping and volume quantification. In the context of the Enhancing Neuro Imaging Genetics through Meta Analysis Consortium, several Disease Working Groups are using the FreeSurfer software to analyze hippocampal subregion (subfield) volumes in patients with neurological and psychiatric conditions along with data from matched controls. In this overview, we explain the algorithm's principles, summarize measurement reliability studies, and demonstrate two additional aspects (subfield autocorrelation and volume/reliability correlation) with illustrative data. We then explain the rationale for a standardized hippocampal subfield segmentation quality control (QC) procedure for improved pipeline harmonization. To guide researchers to make optimal use of the algorithm, we discuss how global size and age effects can be modeled, how QC steps can be incorporated and how subfields may be aggregated into composite volumes. This discussion is based on a synopsis of 162 published neuroimaging studies (01/2013–12/2019) that applied the FreeSurfer hippocampal subfield segmentation in a broad range of domains including cognition and healthy aging, brain development and neurodegeneration, affective disorders, psychosis, stress regulation, neurotoxicity, epilepsy, inflammatory disease, childhood adversity and posttraumatic stress disorder, and candidate and whole genome (epi‐)genetics. Finally, we highlight points where FreeSurfer‐based hippocampal subfield studies may be optimized. [ABSTRACT FROM AUTHOR]

Gray matter volume (GMV) in frontal cortical and limbic regions is susceptible to cocaine‐associated reductions in cocaine‐dependent individuals (CD) and is negatively associated with duration of cocaine use. Gender differences in CD individuals have been reported clinically and in the context of neural responses to cue‐induced craving and stress reactivity. The variability of GMV in select brain areas between men and women (e.g., limbic regions) underscores the importance of exploring interaction effects between gender and cocaine dependence on brain structure. Therefore, voxel‐based morphometry data derived from the ENIGMA Addiction Consortium were used to investigate potential gender differences in GMV in CD individuals compared to matched controls (CTL). T1‐weighted MRI scans and clinical data were pooled from seven sites yielding 420 gender‐ and age‐matched participants: CD men (CDM, n = 140); CD women (CDW, n = 70); control men (CTLM, n = 140); and control women (CTLW, n = 70). Differences in GMV were assessed using a 2 × 2 ANCOVA, and voxelwise whole‐brain linear regressions were conducted to explore relationships between GMV and duration of cocaine use. All analyses were corrected for age, total intracranial volume, and site. Diagnostic differences were predominantly found in frontal regions (CD < CTL). Interestingly, gender × diagnosis interactions in the left anterior insula and left lingual gyrus were also documented, driven by differences in women (CDW < CTLW). Further, lower right hippocampal GMV was associated with greater cocaine duration in CDM. Given the importance of the anterior insula to interoception and the hippocampus to learning contextual associations, results may point to gender‐specific mechanisms in cocaine addiction. [ABSTRACT FROM AUTHOR]