Genomic loci influence patterns of structural covariance in the human brain.

Normal and pathologic neurobiological processes influence brain morphology in coordinated ways that give rise to patterns of structural covariance (PSC) across brain regions and individuals during brain aging and diseases. The genetic underpinnings of these patterns remain largely unknown. We apply a stochastic multivariate factorization method to a diverse population of 50,699 individuals (12 studies and 130 sites) and derive data-driven, multi-scale PSCs of regional brain size. PSCs were significantly correlated with 915 genomic loci in the discovery set, 617 of which are newly identified, and 72% were independently replicated. Key pathways influencing PSCs involve reelin signaling, apoptosis, neurogenesis, and appendage development, while pathways of breast cancer indicate potential interplays between brain metastasis and PSCs associated with neurodegeneration and dementia. Using support vector machines, multi-scale PSCs effectively derive imaging signatures of several brain diseases. Our results elucidate genetic and biological underpinnings that influence structural covariance patterns in the human brain.

Algorithmic fairness in precision psychiatry: analysis of prediction models in individuals at clinical high risk for psychosis.

BACKGROUND: Computational models offer promising potential for personalised treatment of psychiatric diseases. For their clinical deployment, fairness must be evaluated alongside accuracy. Fairness requires predictive models to not unfairly disadvantage specific demographic groups. Failure to assess model fairness prior to use risks perpetuating healthcare inequalities. Despite its importance, empirical investigation of fairness in predictive models for psychiatry remains scarce. AIMS: To evaluate fairness in prediction models for development of psychosis and functional outcome. METHOD: Using data from the PRONIA study, we examined fairness in 13 published models for prediction of transition to psychosis (n = 11) and functional outcome (n = 2) in people at clinical high risk for psychosis or with recent-onset depression. Using accuracy equality, predictive parity, false-positive error rate balance and false-negative error rate balance, we evaluated relevant fairness aspects for the demographic attributes 'gender' and 'educational attainment' and compared them with the fairness of clinicians' judgements. RESULTS: Our findings indicate systematic bias towards assigning less favourable outcomes to individuals with lower educational attainment in both prediction models and clinicians' judgements, resulting in higher false-positive rates in 7 of 11 models for transition to psychosis. Interestingly, the bias patterns observed in algorithmic predictions were not significantly more pronounced than those in clinicians' predictions. CONCLUSIONS: Educational bias was present in algorithmic and clinicians' predictions, assuming more favourable outcomes for individuals with higher educational level (years of education). This bias might lead to increased stigma and psychosocial burden in patients with lower educational attainment and suboptimal psychosis prevention in those with higher educational attainment.

Psychosis brain subtypes validated in first-episode cohorts and related to illness remission: results from the PHENOM consortium.

Using machine learning, we recently decomposed the neuroanatomical heterogeneity of established schizophrenia to discover two volumetric subgroups-a 'lower brain volume' subgroup (SG1) and an 'higher striatal volume' subgroup (SG2) with otherwise normal brain structure. In this study, we investigated whether the MRI signatures of these subgroups were also already present at the time of the first-episode of psychosis (FEP) and whether they were related to clinical presentation and clinical remission over 1-, 3-, and 5-years. We included 572 FEP and 424 healthy controls (HC) from 4 sites (Sao Paulo, Santander, London, Melbourne) of the PHENOM consortium. Our prior MRI subgrouping models (671 participants; USA, Germany, and China) were applied to both FEP and HC. Participants were assigned into 1 of 4 categories: subgroup 1 (SG1), subgroup 2 (SG2), no subgroup membership ('None'), and mixed SG1 + SG2 subgroups ('Mixed'). Voxel-wise analyses characterized SG1 and SG2 subgroups. Supervised machine learning analyses characterized baseline and remission signatures related to SG1 and SG2 membership. The two dominant patterns of 'lower brain volume' in SG1 and 'higher striatal volume' (with otherwise normal neuromorphology) in SG2 were identified already at the first episode of psychosis. SG1 had a significantly higher proportion of FEP (32%) vs. HC (19%) than SG2 (FEP, 21%; HC, 23%). Clinical multivariate signatures separated the SG1 and SG2 subgroups (balanced accuracy = 64%; p < 0.0001), with SG2 showing higher education but also greater positive psychosis symptoms at first presentation, and an association with symptom remission at 1-year, 5-year, and when timepoints were combined. Neuromorphological subtypes of schizophrenia are already evident at illness onset, separated by distinct clinical presentations, and differentially associated with subsequent remission. These results suggest that the subgroups may be underlying risk phenotypes that could be targeted in future treatment trials and are critical to consider when interpreting neuroimaging literature.

Theta burst stimulation add on to dialectical behavioral therapy in borderline-personality-disorder: methods and design of a randomized, single-blind, placebo-controlled pilot trial.

Specialized psychotherapeutic treatments like dialectical behavioral therapy (DBT) are recommended as first treatment for borderline personality disorder (BPD). In recent years, studies have emerged that focus on repetitive transcranial magnetic stimulation (rTMS) in BPD. Both have independently demonstrated efficacy in the treatment of BPD. Intermitted theta burst stimulation (iTBS), a modified design of rTMS, is thought to increase the excitability of neurons and could be a supplement to psychotherapy in addition to being a standalone treatment. However, no studies to date have investigated the combination of DBT and rTMS/iTBS. This study protocol describes the methods and design of a randomized, single-blinded, sham-controlled clinical pilot study in which BPD patients will be randomly assigned to either iTBS or sham during four consecutive weeks (20 sessions in total) in addition to standardized DBT treatment. The stimulation will focus on the unilateral stimulation of the left dorsolateral prefrontal cortex (DLPFC), which plays an important role in the control of impulsivity and risk-taking. Primary outcome is the difference in borderline symptomatology, while secondary target criteria are depressive symptoms, general functional level, impulsivity and self-compassion. Statistical analysis of therapy response will be conducted by Mixed Model Repeated Measurement using a 2 × 2-factorial between-subjects design with the between-subject factor stimulation (TMS vs. Sham) and the within-subject factor time (T0 vs. T1). Furthermore, structural magnetic resonance imaging (MRI) will be conducted and analyzed. The study will provide evidence and insight on whether iTBS has an enhancing effect as add-on to DBT in BPD.Trial registration: drks.de (DRKS00020413) registered 13/01/2020.

[Ethical Considerations of Including Minors in Clinical Trials Using the Example of the Indicated Prevention of Psychotic Disorders]. / Minderjährige in klinischen Prüfungen: Ethische Abwägungen ihres Einbezugs am Beispiel der indizierten Prävention psychotischer Erkrankungen.

Ethical Considerations of Including Minors in Clinical Trials Using the Example of the Indicated Prevention of Psychotic Disorders Abstract: As a vulnerable group, minors require special protection in studies. For this reason, researchers are often reluctant to initiate studies, and ethics committees are reluctant to authorize such studies. This often excludes minors from participating in clinical studies. This exclusion can lead to researchers and clinicians receiving only incomplete data or having to rely on adult-based findings in the treatment of minors. Using the example of the study "Computer-Assisted Risk Evaluation in the Early Detection of Psychotic Disorders" (CARE), which was conducted as an 'other clinical investigation' according to the Medical Device Regulation, we present a line of argumentation for the inclusion of minors which weighs the ethical principles of nonmaleficence (especially regarding possible stigmatization), beneficence, autonomy, and fairness. We show the necessity of including minors based on the development-specific differences in diagnostics and early intervention. Further, we present specific protective measures. This argumentation can also be transferred to other disorders with the onset in childhood and adolescence and thus help to avoid excluding minors from appropriate evidence-based care because of insufficient studies.

Neurocognitive skills and vulnerability for psychosis in depression and across the psychotic spectrum: findings from the PRONIA Consortium.

BACKGROUND: Neurocognitive deficits are a core feature of psychosis and depression. Despite commonalities in cognitive alterations, it remains unclear if and how the cognitive deficits in patients at clinical high risk for psychosis (CHR) and those with recent-onset psychosis (ROP) are distinct from those seen in recent-onset depression (ROD). AIMS: This study was carried out within the European project 'Personalized Prognostic Tools for Early Psychosis Management', and aimed to characterise the cognitive profiles of patients with psychosis or depression. METHOD: We examined cognitive profiles for patients with ROP (n = 105), patients with ROD (n = 123), patients at CHR (n = 116) and healthy controls (n = 372) across seven sites in five European countries. Confirmatory factor analysis identified four cognitive factors independent of gender, education and site: speed of processing, attention and working memory, verbal learning and spatial learning. RESULTS: Patients with ROP performed worse than healthy controls in all four domains (P < 0.001), whereas performance of patients with ROD was not affected (P > 0.05). Patients at CHR performed worse than healthy controls in speed of processing (P = 0.001) and spatial learning (P = 0.003), but better than patients with ROP across all cognitive domains (all P ≤ 0.01). CHR and ROD groups did not significantly differ in any cognitive domain. These findings were independent of comorbid depressive symptoms, substance consumption and illness duration. CONCLUSIONS: These results show that neurocognitive abilities are affected in CHR and ROP, whereas ROD seems spared. Although our findings may support the notion that those at CHR have a specific vulnerability to psychosis, future studies investigating broader transdiagnostic risk cohorts in longitudinal designs are needed.

The non-specific nature of mental health and structural brain outcomes following childhood trauma.

BACKGROUND: Childhood trauma (CT) is associated with an increased risk of mental health disorders; however, it is unknown whether this represents a diagnosis-specific risk factor for specific psychopathology mediated by structural brain changes. Our aim was to explore whether (i) a predictive CT pattern for transdiagnostic psychopathology exists, and whether (ii) CT can differentiate between distinct diagnosis-dependent psychopathology. Furthermore, we aimed to identify the association between CT, psychopathology and brain structure. METHODS: We used multivariate pattern analysis in data from 643 participants of the Personalised Prognostic Tools for Early Psychosis Management study (PRONIA), including healthy controls (HC), recent onset psychosis (ROP), recent onset depression (ROD), and patients clinically at high-risk for psychosis (CHR). Participants completed structured interviews and self-report measures including the Childhood Trauma Questionnaire, SCID diagnostic interview, BDI-II, PANSS, Schizophrenia Proneness Instrument, Structured Interview for Prodromal Symptoms and structural MRI, analyzed by voxel-based morphometry. RESULTS: (i) Patients and HC could be distinguished by their CT pattern with a reasonable precision [balanced accuracy of 71.2% (sensitivity = 72.1%, specificity = 70.4%, p ≤ 0.001]. (ii) Subdomains 'emotional neglect' and 'emotional abuse' were most predictive for CHR and ROP, while in ROD 'physical abuse' and 'sexual abuse' were most important. The CT pattern was significantly associated with the severity of depressive symptoms in ROD, ROP, and CHR, as well as with the PANSS total and negative domain scores in the CHR patients. No associations between group-separating CT patterns and brain structure were found. CONCLUSIONS: These results indicate that CT poses a transdiagnostic risk factor for mental health disorders, possibly related to depressive symptoms. While differences in the quality of CT exposure exist, diagnostic differentiation was not possible suggesting a multi-factorial pathogenesis.

Prevalence of cognitive impairments and strengths in the early course of psychosis and depression.

BACKGROUND: Studies investigating cognitive impairments in psychosis and depression have typically compared the average performance of the clinical group against healthy controls (HC), and do not report on the actual prevalence of cognitive impairments or strengths within these clinical groups. This information is essential so that clinical services can provide adequate resources to supporting cognitive functioning. Thus, we investigated this prevalence in individuals in the early course of psychosis or depression. METHODS: A comprehensive cognitive test battery comprising 12 tests was completed by 1286 individuals aged 15-41 (mean age 25.07, s.d. 5.88) from the PRONIA study at baseline: HC (N = 454), clinical high risk for psychosis (CHR; N = 270), recent-onset depression (ROD; N = 267), and recent-onset psychosis (ROP; N = 295). Z-scores were calculated to estimate the prevalence of moderate or severe deficits or strengths (>2 s.d. or 1-2 s.d. below or above HC, respectively) for each cognitive test. RESULTS: Impairment in at least two cognitive tests was as follows: ROP (88.3% moderately, 45.1% severely impaired), CHR (71.2% moderately, 22.4% severely impaired), ROD (61.6% moderately, 16.2% severely impaired). Across clinical groups, impairments were most prevalent in tests of working memory, processing speed, and verbal learning. Above average performance (>1 s.d.) in at least two tests was present for 40.5% ROD, 36.1% CHR, 16.1% ROP, and was >2 SDs in 1.8% ROD, 1.4% CHR, and 0% ROP. CONCLUSIONS: These findings suggest that interventions should be tailored to the individual, with working memory, processing speed, and verbal learning likely to be important transdiagnostic targets.

Novel Gyrification Networks Reveal Links with Psychiatric Risk Factors in Early Illness.

Adult gyrification provides a window into coordinated early neurodevelopment when disruptions predispose individuals to psychiatric illness. We hypothesized that the echoes of such disruptions should be observed within structural gyrification networks in early psychiatric illness that would demonstrate associations with developmentally relevant variables rather than specific psychiatric symptoms. We employed a new data-driven method (Orthogonal Projective Non-Negative Matrix Factorization) to delineate novel gyrification-based networks of structural covariance in 308 healthy controls. Gyrification within the networks was then compared to 713 patients with recent onset psychosis or depression, and at clinical high-risk. Associations with diagnosis, symptoms, cognition, and functioning were investigated using linear models. Results demonstrated 18 novel gyrification networks in controls as verified by internal and external validation. Gyrification was reduced in patients in temporal-insular, lateral occipital, and lateral fronto-parietal networks (pFDR < 0.01) and was not moderated by illness group. Higher gyrification was associated with better cognitive performance and lifetime role functioning, but not with symptoms. The findings demonstrated that gyrification can be parsed into novel brain networks that highlight generalized illness effects linked to developmental vulnerability. When combined, our study widens the window into the etiology of psychiatric risk and its expression in adulthood.

Effects of Early Clozapine Treatment on Remission Rates in Acute Schizophrenia (The EARLY Trial): Protocol of a Randomized-Controlled Multicentric Trial.

BACKGROUND: Quick symptomatic remission after the onset of psychotic symptoms is critical in schizophrenia treatment, determining the subsequent disease course and recovery. In this context, only every second patient with acute schizophrenia achieves symptomatic remission within three months of initiating antipsychotic treatment. The potential indication extension of clozapine-the most effective antipsychotic-to be introduced at an earlier stage (before treatment-resistance) is supported by several lines of evidence, but respective clinical trials are lacking. METHODS: Two hundred-twenty patients with acute non-treatment-resistant schizophrenia will be randomized in this double-blind, 8-week parallel-group multicentric trial to either clozapine or olanzapine. The primary endpoint is the number of patients in symptomatic remission at the end of week 8 according to international consensus criteria ('Andreasen criteria'). Secondary endpoints and other assessments comprise a comprehensive safety assessment (i. e., myocarditis screening), changes in psychopathology, global functioning, cognition, affective symptoms and quality of life, and patients' and relatives' views on treatment. DISCUSSION: This multicentre trial aims to examine whether clozapine is more effective than a highly effective second-generation antipsychotics (SGAs), olanzapine, in acute schizophrenia patients who do not meet the criteria for treatment-naïve or treatment-resistant schizophrenia. Increasing the likelihood to achieve symptomatic remission in acute schizophrenia can improve the overall outcome, reduce disease-associated burden and potentially prevent mid- and long-term disease chronicity.

Using combined environmental-clinical classification models to predict role functioning outcome in clinical high-risk states for psychosis and recent-onset depression.

BACKGROUND: Clinical high-risk states for psychosis (CHR) are associated with functional impairments and depressive disorders. A previous PRONIA study predicted social functioning in CHR and recent-onset depression (ROD) based on structural magnetic resonance imaging (sMRI) and clinical data. However, the combination of these domains did not lead to accurate role functioning prediction, calling for the investigation of additional risk dimensions. Role functioning may be more strongly associated with environmental adverse events than social functioning. AIMS: We aimed to predict role functioning in CHR, ROD and transdiagnostically, by adding environmental adverse events-related variables to clinical and sMRI data domains within the PRONIA sample. METHOD: Baseline clinical, environmental and sMRI data collected in 92 CHR and 95 ROD samples were trained to predict lower versus higher follow-up role functioning, using support vector classification and mixed k-fold/leave-site-out cross-validation. We built separate predictions for each domain, created multimodal predictions and validated them in independent cohorts (74 CHR, 66 ROD). RESULTS: Models combining clinical and environmental data predicted role outcome in discovery and replication samples of CHR (balanced accuracies: 65.4% and 67.7%, respectively), ROD (balanced accuracies: 58.9% and 62.5%, respectively), and transdiagnostically (balanced accuracies: 62.4% and 68.2%, respectively). The most reliable environmental features for role outcome prediction were adult environmental adjustment, childhood trauma in CHR and childhood environmental adjustment in ROD. CONCLUSIONS: Findings support the hypothesis that environmental variables inform role outcome prediction, highlight the existence of both transdiagnostic and syndrome-specific predictive environmental adverse events, and emphasise the importance of implementing real-world models by measuring multiple risk dimensions.

The clinical relevance of formal thought disorder in the early stages of psychosis: results from the PRONIA study.

BACKGROUND: Formal thought disorder (FTD) has been associated with more severe illness courses and functional deficits in patients with psychotic disorders. However, it remains unclear whether the presence of FTD characterises a specific subgroup of patients showing more prominent illness severity, neurocognitive and functional impairments. This study aimed to identify stable and generalizable FTD-subgroups of patients with recent-onset psychosis (ROP) by applying a comprehensive data-driven clustering approach and to test the validity of these subgroups by assessing associations between this FTD-related stratification, social and occupational functioning, and neurocognition. METHODS: 279 patients with ROP were recruited as part of the multi-site European PRONIA study (Personalised Prognostic Tools for Early Psychosis Management; www.pronia.eu). Five FTD-related symptoms (conceptual disorganization, poverty of content of speech, difficulty in abstract thinking, increased latency of response and poverty of speech) were assessed with Positive and Negative Symptom Scale (PANSS) and the Scale for the Assessment of Negative Symptoms (SANS). RESULTS: The results with two patient subgroups showing different levels of FTD were the most stable and generalizable clustering solution (predicted clustering strength value = 0.86). FTD-High subgroup had lower scores in social (pfdr < 0.001) and role (pfdr < 0.001) functioning, as well as worse neurocognitive performance in semantic (pfdr < 0.001) and phonological verbal fluency (pfdr < 0.001), short-term verbal memory (pfdr = 0.002) and abstract thinking (pfdr = 0.010), in comparison to FTD-Low group. CONCLUSIONS: Clustering techniques allowed us to identify patients with more pronounced FTD showing more severe deficits in functioning and neurocognition, thus suggesting that FTD may be a relevant marker of illness severity in the early psychosis pathway.

Predicting the role of coping factors on pandemic-related anxiety.

The year 2020 saw the emergence of a worldwide pandemic caused by the novel coronavirus COVID-19. Measures against further spread of the virus were taken nearly everywhere in the world. Many countries also imposed social distancing rules and lockdowns on their population. This situation has caused a lot of fear and insecurity, along with reactance and even unrest in some countries. In this study, we measured the psychological concepts of resilience, reactance, positive schemas, social solidarity, and anxiety among psychiatric patients and in how far these factors influence their psychopathological anxiety during the pandemic. The aim was to better understand in what ways these factors influence pandemic anxiety to be able to reduce its negative psychological effects. Findings show a significant effect of positive schemas and social solidarity on the level of pandemic anxiety in a sample of psychiatric patients, but no correlation between resilience or reactance and pandemic anxiety. Based on these insights, the inclusion of positive schemas and social solidarity for therapy should be considered. Looking deeper into the relation between positive schemas and pandemic anxiety could provide insight into the different ways that schemas influence people's anxiety and determine whether some of them are particularly important.

Detailed clinical phenotyping and generalisability in prognostic models of functioning in at-risk populations.

Personalised prediction of functional outcomes is a promising approach for targeted early intervention in psychiatry. However, generalisability and resource efficiency of such prognostic models represent challenges. In the PRONIA study (German Clinical Trials Register: DRKS00005042), we demonstrate excellent generalisability of prognostic models in individuals at clinical high-risk for psychosis or with recent-onset depression, and substantial contributions of detailed clinical phenotyping, particularly to the prediction of role functioning. These results indicate that it is possible that functioning prediction models based only on clinical data could be effectively applied in diverse healthcare settings, so that neuroimaging data may not be needed at early assessment stages.

Two distinct neuroanatomical subtypes of schizophrenia revealed using machine learning.

Neurobiological heterogeneity in schizophrenia is poorly understood and confounds current analyses. We investigated neuroanatomical subtypes in a multi-institutional multi-ethnic cohort, using novel semi-supervised machine learning methods designed to discover patterns associated with disease rather than normal anatomical variation. Structural MRI and clinical measures in established schizophrenia (n = 307) and healthy controls (n = 364) were analysed across three sites of PHENOM (Psychosis Heterogeneity Evaluated via Dimensional Neuroimaging) consortium. Regional volumetric measures of grey matter, white matter, and CSF were used to identify distinct and reproducible neuroanatomical subtypes of schizophrenia. Two distinct neuroanatomical subtypes were found. Subtype 1 showed widespread lower grey matter volumes, most prominent in thalamus, nucleus accumbens, medial temporal, medial prefrontal/frontal and insular cortices. Subtype 2 showed increased volume in the basal ganglia and internal capsule, and otherwise normal brain volumes. Grey matter volume correlated negatively with illness duration in Subtype 1 (r = -0.201, P = 0.016) but not in Subtype 2 (r = -0.045, P = 0.652), potentially indicating different underlying neuropathological processes. The subtypes did not differ in age (t = -1.603, df = 305, P = 0.109), sex (chi-square = 0.013, df = 1, P = 0.910), illness duration (t = -0.167, df = 277, P = 0.868), antipsychotic dose (t = -0.439, df = 210, P = 0.521), age of illness onset (t = -1.355, df = 277, P = 0.177), positive symptoms (t = 0.249, df = 289, P = 0.803), negative symptoms (t = 0.151, df = 289, P = 0.879), or antipsychotic type (chi-square = 6.670, df = 3, P = 0.083). Subtype 1 had lower educational attainment than Subtype 2 (chi-square = 6.389, df = 2, P = 0.041). In conclusion, we discovered two distinct and highly reproducible neuroanatomical subtypes. Subtype 1 displayed widespread volume reduction correlating with illness duration, and worse premorbid functioning. Subtype 2 had normal and stable anatomy, except for larger basal ganglia and internal capsule, not explained by antipsychotic dose. These subtypes challenge the notion that brain volume loss is a general feature of schizophrenia and suggest differential aetiologies. They can facilitate strategies for clinical trial enrichment and stratification, and precision diagnostics.

[Psychotic disorders in ICD-11: the revisions]. / Psychotische Störungen in der ICD-11: Die Revisionen.

Psychotic disorders in ICD-11: the revisions Abstract. This article provides an overview of the main changes to the chapter "Schizophrenia or Other Primary Psychotic Disorders" (6A2) from ICD-10 to ICD-11 and compares them with the psychosis chapter of DSM-5. These changes include abandoning the classical subtypes of Schizophrenia as well as of the special significance of Schneider's first-rank symptoms, resulting in the general requirement of two key features (one must be a positive symptom) in the definition of "Schizophrenia" (6A20) and the allowance for bizarre contents in "Delusional Disorder" (6A24), which now includes "Induced Delusional Disorder" (F24). Further introduced are the focus on the current episode, the restriction of "Acute and Transient Psychotic Disorder" (6A23) to the former Polymorphic Disorder Without Schizophrenic Symptoms (F23.0), the diagnosis of delusional "Obsessive-Compulsive or Related Disorders" (6B2) exclusively as Obsessive-Compulsive Disorders, the specification of "Schizoaffective Disorder" (6A21), and the formulation of a distinct subchapter "Catatonia" (6A4) for the assessment of catatonic features in the context of several disorders. In analogy to DSM-5, ICD-11 now includes the optional category "Symptomatic Manifestations of Primary Psychotic Disorders" (6A25) for the dimensional quantification of symptoms. Again, developmental aspects remain unattended in in the ICD-11-definitions of psychotic disorders.

Serotonergic influence on depressive symptoms and trait anxiety is mediated by negative life events and frontal activation in children and adolescents.

Depression and anxiety are common in childhood and adolescence. Even though cardinal symptoms differ, there is a considerable overlap regarding the pathogenic influence of serotonergic innervation, negative life experience, disturbed emotion perception/affect regulation, and impaired neural functioning in the fronto-limbic circuit. In this study, we examined the effect of the 5-HTTLPR/rs25531 genotype on depressive symptoms and trait anxiety under the consideration of the amount of negative life events in healthy children and adolescents (N = 389). In a subsample of 49 subjects, we performed fMRI to add fronto-limbic brain activation as a second interacting factor. Across all subjects, negative life events moderated the influence of the 5-HTTLPR/rs25531 genotype on both depressive symptoms and trait anxiety. In the fMRI subsample, 5-HTTLPR/rs25531 S + S/LG + S/LA + LGLA + LGLG genotype-associated left middle frontal gyrus (MFG) activation mediated the influence of 5-HTTLPR/rs25531 genotype on depressive symptoms, however, only in combination with negative life events. Genetic influence on trait anxiety was predominantly mediated by negative life events; only LALA genotype-specific activation in the right MFG worked as a mediator in combination with negative life events. The present findings hint towards distinct mechanisms mediating the influence of 5-HTTLPR/rs25531 genotype on depressive symptoms and anxiety, with negative life events playing a crucial role in both phenotypes. With regard to depressive symptoms, however, this influence was only visible in combination with MFG activation, whereas, in anxiety, it was independent of brain activation.

The European DTI Study on Dementia - A multicenter DTI and MRI study on Alzheimer's disease and Mild Cognitive Impairment.

The European DTI Study on Dementia (EDSD) is a multicenter framework created to study the diagnostic accuracy and inter-site variability of DTI-derived markers in patients with manifest and prodromal Alzheimer's disease (AD). The dynamically growing database presently includes 493 DTI, 512 T1-weighted MRI, and 300 FLAIR scans from patients with AD dementia, patients with Mild Cognitive Impairment (MCI) and matched Healthy Controls, acquired on 13 different scanner platforms. The imaging data is publicly available, along with the subjects' demographic and clinical characterization. Detailed neuropsychological information, cerebrospinal fluid information on biomarkers and clinical follow-up diagnoses are included for a subset of subjects. This paper describes the rationale and structure of the EDSD, summarizes the available data, and explains how to gain access to the database. The EDSD is a useful database for researchers seeking to investigate the contribution of DTI to dementia diagnostics.

Individualized differential diagnosis of schizophrenia and mood disorders using neuroanatomical biomarkers.

Magnetic resonance imaging-based markers of schizophrenia have been repeatedly shown to separate patients from healthy controls at the single-subject level, but it remains unclear whether these markers reliably distinguish schizophrenia from mood disorders across the life span and generalize to new patients as well as to early stages of these illnesses. The current study used structural MRI-based multivariate pattern classification to (i) identify and cross-validate a differential diagnostic signature separating patients with first-episode and recurrent stages of schizophrenia (n = 158) from patients with major depression (n = 104); and (ii) quantify the impact of major clinical variables, including disease stage, age of disease onset and accelerated brain ageing on the signature's classification performance. This diagnostic magnetic resonance imaging signature was then evaluated in an independent patient cohort from two different centres to test its generalizability to individuals with bipolar disorder (n = 35), first-episode psychosis (n = 23) and clinically defined at-risk mental states for psychosis (n = 89). Neuroanatomical diagnosis was correct in 80% and 72% of patients with major depression and schizophrenia, respectively, and involved a pattern of prefronto-temporo-limbic volume reductions and premotor, somatosensory and subcortical increments in schizophrenia versus major depression. Diagnostic performance was not influenced by the presence of depressive symptoms in schizophrenia or psychotic symptoms in major depression, but earlier disease onset and accelerated brain ageing promoted misclassification in major depression due to an increased neuroanatomical schizophrenia likeness of these patients. Furthermore, disease stage significantly moderated neuroanatomical diagnosis as recurrently-ill patients had higher misclassification rates (major depression: 23%; schizophrenia: 29%) than first-episode patients (major depression: 15%; schizophrenia: 12%). Finally, the trained biomarker assigned 74% of the bipolar patients to the major depression group, while 83% of the first-episode psychosis patients and 77% and 61% of the individuals with an ultra-high risk and low-risk state, respectively, were labelled with schizophrenia. Our findings suggest that neuroanatomical information may provide generalizable diagnostic tools distinguishing schizophrenia from mood disorders early in the course of psychosis. Disease course-related variables such as age of disease onset and disease stage as well alterations of structural brain maturation may strongly impact on the neuroanatomical separability of major depression and schizophrenia.