Evidence from comprehensive independent validation studies for smooth pursuit dysfunction as a sensorimotor biomarker for psychosis.

Smooth pursuit eye movements are considered a well-established and quantifiable biomarker of sensorimotor function in psychosis research. Identifying psychotic syndromes on an individual level based on neurobiological markers is limited by heterogeneity and requires comprehensive external validation to avoid overestimation of prediction models. Here, we studied quantifiable sensorimotor measures derived from smooth pursuit eye movements in a large sample of psychosis probands (N = 674) and healthy controls (N = 305) using multivariate pattern analysis. Balanced accuracies of 64% for the prediction of psychosis status are in line with recent results from other large heterogenous psychiatric samples. They are confirmed by external validation in independent large samples including probands with (1) psychosis (N = 727) versus healthy controls (N = 292), (2) psychotic (N = 49) and non-psychotic bipolar disorder (N = 36), and (3) non-psychotic affective disorders (N = 119) and psychosis (N = 51) yielding accuracies of 65%, 66% and 58%, respectively, albeit slightly different psychosis syndromes. Our findings make a significant contribution to the identification of biologically defined profiles of heterogeneous psychosis syndromes on an individual level underlining the impact of sensorimotor dysfunction in psychosis.

Cortical and Subcortical Brain Alterations in Specific Phobia and Its Animal and Blood-Injection-Injury Subtypes: A Mega-Analysis From the ENIGMA Anxiety Working Group.

OBJECTIVE: Specific phobia is a common anxiety disorder, but the literature on associated brain structure alterations exhibits substantial gaps. The ENIGMA Anxiety Working Group examined brain structure differences between individuals with specific phobias and healthy control subjects as well as between the animal and blood-injection-injury (BII) subtypes of specific phobia. Additionally, the authors investigated associations of brain structure with symptom severity and age (youths vs. adults). METHODS: Data sets from 31 original studies were combined to create a final sample with 1,452 participants with phobia and 2,991 healthy participants (62.7% female; ages 5-90). Imaging processing and quality control were performed using established ENIGMA protocols. Subcortical volumes as well as cortical surface area and thickness were examined in a preregistered analysis. RESULTS: Compared with the healthy control group, the phobia group showed mostly smaller subcortical volumes, mixed surface differences, and larger cortical thickness across a substantial number of regions. The phobia subgroups also showed differences, including, as hypothesized, larger medial orbitofrontal cortex thickness in BII phobia (N=182) compared with animal phobia (N=739). All findings were driven by adult participants; no significant results were observed in children and adolescents. CONCLUSIONS: Brain alterations associated with specific phobia exceeded those of other anxiety disorders in comparable analyses in extent and effect size and were not limited to reductions in brain structure. Moreover, phenomenological differences between phobia subgroups were reflected in diverging neural underpinnings, including brain areas related to fear processing and higher cognitive processes. The findings implicate brain structure alterations in specific phobia, although subcortical alterations in particular may also relate to broader internalizing psychopathology.

Elevated accuracy in recognition of subliminal happy facial expressions in patients with panic disorder after psychotherapy.

Background: Individuals with anxiety disorders (ADs) often display hypervigilance to threat information, although this response may be less pronounced following psychotherapy. This study aims to investigate the unconscious recognition performance of facial expressions in patients with panic disorder (PD) post-treatment, shedding light on alterations in their emotional processing biases. Methods: Patients with PD (n=34) after (exposure-based) cognitive behavior therapy and healthy controls (n=43) performed a subliminal affective recognition task. Emotional facial expressions (fearful, happy, or mirrored) were displayed for 33 ms and backwardly masked by a neutral face. Participants completed a forced choice task to discriminate the briefly presented facial stimulus and an uncovered condition where only the neutral mask was shown. We conducted a secondary analysis to compare groups based on their four possible response types under the four stimulus conditions and examined the correlation of the false alarm rate for fear responses to non-fearful (happy, mirrored, and uncovered) stimuli with clinical anxiety symptoms. Results: The patient group showed a unique selection pattern in response to happy expressions, with significantly more correct "happy" responses compared to controls. Additionally, lower severity of anxiety symptoms after psychotherapy was associated with a decreased false fear response rate with non-threat presentations. Conclusion: These data suggest that patients with PD exhibited a "happy-face recognition advantage" after psychotherapy. Less symptoms after treatment were related to a reduced fear bias. Thus, a differential facial emotion detection task could be a suitable tool to monitor response patterns and biases in individuals with ADs in the context of psychotherapy.

Lack of evidence for predictive utility from resting state fMRI data for individual exposure-based cognitive behavioral therapy outcomes: A machine learning study in two large multi-site samples in anxiety disorders.

Data-based predictions of individual Cognitive Behavioral Therapy (CBT) treatment response are a fundamental step towards precision medicine. Past studies demonstrated only moderate prediction accuracy (i.e. ability to discriminate between responders and non-responders of a given treatment) when using clinical routine data such as demographic and questionnaire data, while neuroimaging data achieved superior prediction accuracy. However, these studies may be considerably biased due to very limited sample sizes and bias-prone methodology. Adequately powered and cross-validated samples are a prerequisite to evaluate predictive performance and to identify the most promising predictors. We therefore analyzed resting state functional magnet resonance imaging (rs-fMRI) data from two large clinical trials to test whether functional neuroimaging data continues to provide good prediction accuracy in much larger samples. Data came from two distinct German multicenter studies on exposure-based CBT for anxiety disorders, the Protect-AD and SpiderVR studies. We separately and independently preprocessed baseline rs-fMRI data from n = 220 patients (Protect-AD) and n = 190 patients (SpiderVR) and extracted a variety of features, including ROI-to-ROI and edge-functional connectivity, sliding-windows, and graph measures. Including these features in sophisticated machine learning pipelines, we found that predictions of individual outcomes never significantly differed from chance level, even when conducting a range of exploratory post-hoc analyses. Moreover, resting state data never provided prediction accuracy beyond the sociodemographic and clinical data. The analyses were independent of each other in terms of selecting methods to process resting state data for prediction input as well as in the used parameters of the machine learning pipelines, corroborating the external validity of the results. These similar findings in two independent studies, analyzed separately, urge caution regarding the interpretation of promising prediction results based on neuroimaging data from small samples and emphasizes that some of the prediction accuracies from previous studies may result from overestimation due to homogeneous data and weak cross-validation schemes. The promise of resting-state neuroimaging data to play an important role in the prediction of CBT treatment outcomes in patients with anxiety disorders remains yet to be delivered.

Higher body weight-dependent neural activation during reward processing.

Obesity is associated with alterations in brain structure and function, particularly in areas related to reward processing. Although brain structural investigations have demonstrated a continuous association between higher body weight and reduced gray matter in well-powered samples, functional neuroimaging studies have typically only contrasted individuals from the normal weight and obese body mass index (BMI) ranges with modest sample sizes. It remains unclear, whether the commonly found hyperresponsiveness of the reward circuit can (a) be replicated in well-powered studies and (b) be found as a function of higher body weight even below the threshold of clinical obesity. 383 adults across the weight spectrum underwent functional magnetic resonance imaging during a common card-guessing paradigm simulating monetary reward. Multiple regression was used to investigate the association of BMI and neural activation in the reward circuit. In addition, a one-way ANOVA model comparing three weight groups (normal weight, overweight, obese) was calculated. Higher BMI was associated with higher reward response in the bilateral insula. This association could no longer be found when participants with obesity were excluded from the analysis. The ANOVA revealed higher activation in obese vs. lean, but no difference between lean and overweight participants. The overactivation of reward-related brain areas in obesity is a consistent finding that can be replicated in large samples. In contrast to brain structural aberrations associated with higher body weight, the neurofunctional underpinnings of reward processing in the insula appear to be more pronounced in the higher body weight range.

Effective-and Tolerable: Acceptance and Side Effects of Intensified Exposure for Anxiety Disorders.

Despite striking empirical support, exposure-based treatments for anxiety disorders are underutilized. This is partially due to clinicians' concerns that patients may reject exposure or experience severe side effects, particularly in intensive forms of exposure. We examined acceptance and side effects of two randomly assigned variants of prediction error-based exposure treatment differing in temporal density (1 vs. 3 sessions/week) in 681 patients with panic disorder, agoraphobia, social anxiety disorder, and multiple specific phobias. Treatment acceptance included treatment satisfaction and credibility, engagement (i.e., homework completion), and tolerability (i.e., side effects, dropout, and perceived treatment burden). Side effects were measured with the Inventory for the Balanced Assessment of Negative Effects of Psychotherapy (INEP). We found treatment satisfaction, credibility, and engagement to be equally high in both variants of exposure-based treatment, despite higher treatment burden (ß = 0.25) and stronger side effects (ß = 0.15) in intensified treatment. 94.1% of patients reported positive effects in the INEP. 42.2% reported side effects, with treatment stigma (16.6%), low mood (14.8%) and the experience to depend on the therapist (10.9%) being the most frequently reported. The mean intensity of side effects was low. We conclude that prediction error-based exposure treatment is well accepted by patients with different anxiety disorders and that patients also tolerate temporally intensified treatment, despite higher perceived treatment burden and stronger side effects. Clinicians should be aware of the most frequent side effects to take appropriate countermeasures. In sum, temporal intensification appears to be an acceptable strategy to achieve faster symptom reduction, given patients' well-informed consent.

Association between mitochondria-related genes and cognitive performance in the PsyCourse Study.

BACKGROUND: Mitochondria generate energy through oxidative phosphorylation (OXPHOS). The function of key OXPHOS proteins can be altered by variation in mitochondria-related genes, which may increase the risk of mental illness. We investigated the association of mitochondria-related genes and their genetic risk burden with cognitive performance. METHODS: We leveraged cross-sectional data from 1320 individuals with a severe psychiatric disorder and 466 neurotypical individuals from the PsyCourse Study. The cognitive tests analyzed were the Trail-Making Test, Verbal Digit Span Test, Digit-Symbol Test, and Multiple Choice Vocabulary Intelligence Test. Association analyses between the cognitive tests, and single-nucleotide polymorphisms (SNPs) mapped to mitochondria-related genes, and their polygenic risk score (PRS) for schizophrenia (SCZ) were performed with PLINK 1.9 and R program. RESULTS: We found a significant association (FDR-adjusted p < 0.05) in the Cytochrome C Oxidase Assembly Factor 8 (COA8) gene locus of the OXPHOS pathway with the Verbal Digit Span (forward) test. Mitochondrial PRS was not significantly associated with any of the cognitive tests. LIMITATIONS: Moderate statistical power due to relatively small sample size. CONCLUSIONS: COA8 encodes a poorly characterized mitochondrial protein involved in apoptosis. Here, this gene was associated with the Verbal Digit Span (forward) test, which evaluates short-term memory. Our results warrant replication and may lead to better understanding of cognitive impairment in mental disorders.

[The Well-informed Patient: a Survey on Patients' Initiative in Seeking Disease-related Information]. / Der gut informierte Patient: Wie stationär behandelte psychiatrische Patienten die Suche nach Informationen über ihre Erkrankung erleben.

Internet and print media are frequently used by laypersons to learn about health issues. The objective of this study was to find out whether people with mental disorders showed a special pattern of usage. Where and why do they seek for information about their disorder? How do they experience their search? In semi-standardized interviews, we surveyed 200 psychiatric inpatients. Only patients of the following diagnostic groups were included: 1. Schizophrenia, schizotypal and delusional disorders (F20-F29), 2. Affective disorders (F30-F39) and 3. Disorders of adult personality and behavior (F60-F69). We focused on the sources the patients had used and the experiences they had in the course of their internet search. The vast majority had already searched for information about psychiatry, psychology or medication via internet or in print media. Most participants described positive emotions while reading. More than two-thirds rated the information as useful. Only 10 participants discontinued or rejected therapeutic measures due to information they had gained. Patients with personality disorders were significantly more likely than other patients to attribute their symptoms to a wrong diagnosis after seeking for information. Overall, psychiatric patients mostly experience helpful effects of reading medical information. In rare cases there are negative effects, e. g. negative emotions, discontinuation of therapy or an incorrect assessment of one's own illness. Further research is required in order to find out how the use of internet by people with mental disorders, which is already successful in many cases, can be improved even further.

Expression of CXCR4 on CD4+ T cells predicts body composition parameters in female adolescents with anorexia nervosa.

Anorexia nervosa (AN) is a severe eating disorder characterized by excessive weight loss and lack of recognition of the seriousness of the current low body weight. Individuals with AN frequently exhibit an enhanced inflammatory state and altered blood levels of cytokines and chemokines. However, the expression of chemokine receptors in AN and the association with body composition parameters and treatment effects are still unknown. In this study, we examined the expression of CCR4, CCR6, CXCR3, and CXCR4 on peripheral blood T cells in female adolescents with AN before (T0, n = 24) and after 6 weeks of multimodal therapy (T1, n = 20). We also investigated their value to predict body mass index (BMI) and fat mass index (FMI) at baseline. Using multi-parameter flow cytometry, we found increased expression of CCR4, CXCR3, and CXCR4, but not CCR6, on CD4+ T cells in AN at T0 when compared to healthy controls (HC, n = 20). At T1, CXCR3 and CXCR4 expression decreased in AN. We found a close link between CCR4, CCR6 and CXCR4 expression and the adolescent mental health status in the study cohort as determined by the Strengths and Difficulties Questionnaire (SDQ). Specifically, CXCR4 expression correlated positively with emotional symptoms and peer relationship problems, as well as with the total sum score of the SDQ. In addition, CXCR4 expression on CD4+ T cells was a significant predictor of BMI and FMI in female adolescents. Our findings that CXCR4 expression on T cells is altered in adolescents with AN and predicts body composition parameters in adolescents suggest an impact of this chemokine receptor in the pathogenesis of AN.

Diagnostic model development for schizophrenia based on peripheral blood mononuclear cell subtype-specific expression of metabolic markers.

A significant proportion of the personal and economic burden of schizophrenia can be attributed to the late diagnosis or misdiagnosis of the disorder. A novel, objective diagnostic approaches could facilitate the early detection and treatment of schizophrenia and improve patient outcomes. In the present study, we aimed to identify robust schizophrenia-specific blood biomarkers, with the goal of developing an accurate diagnostic model. The levels of selected serum and peripheral blood mononuclear cell (PBMC) markers relevant to metabolic and immune function were measured in healthy controls (n = 26) and recent-onset schizophrenia patients (n = 36) using multiplexed immunoassays and flow cytometry. Analysis of covariance revealed significant upregulation of insulin receptor (IR) and fatty acid translocase (CD36) levels in T helper cells (F = 10.75, P = 0.002, Q = 0.024 and F = 21.58, P = 2.8 × 10-5, Q = 0.0004, respectively), as well as downregulation of glucose transporter 1 (GLUT1) expression in monocytes (F = 21.46, P = 2.9 × 10-5, Q = 0.0004). The most robust predictors, monocyte GLUT1 and T helper cell CD36, were used to develop a diagnostic model, which showed a leave-one-out cross-validated area under the receiver operating characteristic curve (AUC) of 0.78 (95% CI: 0.66-0.92). The diagnostic model was validated in two independent datasets. The model was able to distinguish first-onset, drug-naïve schizophrenia patients (n = 34) from healthy controls (n = 39) with an AUC of 0.75 (95% CI: 0.64-0.86), and also differentiated schizophrenia patients (n = 22) from patients with other neuropsychiatric conditions, including bipolar disorder, major depressive disorder and autism spectrum disorder (n = 68), with an AUC of 0.83 (95% CI: 0.75-0.92). These findings indicate that PBMC-derived biomarkers have the potential to support an accurate and objective differential diagnosis of schizophrenia.

Sometimes I feel the fear of uncertainty: How intolerance of uncertainty and trait anxiety impact fear acquisition, extinction and the return of fear.

It is hypothesized that the ability to discriminate between threat and safety is impaired in individuals with high dispositional negativity, resulting in maladaptive behavior. A large body of research investigated differential learning during fear conditioning and extinction protocols depending on individual differences in intolerance of uncertainty (IU) and trait anxiety (TA), two closely-related dimensions of dispositional negativity, with heterogenous results. These might be due to varying degrees of induced threat/safety uncertainty. Here, we compared two groups with high vs. low IU/TA during periods of low (instructed fear acquisition) and high levels of uncertainty (delayed non-instructed extinction training and reinstatement). Dependent variables comprised subjective (US expectancy, valence, arousal), psychophysiological (skin conductance response, SCR, and startle blink), and neural (fMRI BOLD) measures of threat responding. During fear acquisition, we found strong threat/safety discrimination for both groups. During early extinction (high uncertainty), the low IU/TA group showed an increased physiological response to the safety signal, resulting in a lack of CS discrimination. In contrast, the high IU/TA group showed strong initial threat/safety discrimination in physiology, lacking discriminative learning on startle, and reduced neural activation in regions linked to threat/safety processing throughout extinction training indicating sustained but non-adaptive and rigid responding. Similar neural patterns were found after the reinstatement test. Taken together, we provide evidence that high dispositional negativity, as indicated here by IU and TA, is associated with greater responding to threat cues during the beginning of delayed extinction, and, thus, demonstrates altered learning patterns under changing environments.

Behavioural and functional evidence revealing the role of RBFOX1 variation in multiple psychiatric disorders and traits.

Common variation in the gene encoding the neuron-specific RNA splicing factor RNA Binding Fox-1 Homolog 1 (RBFOX1) has been identified as a risk factor for several psychiatric conditions, and rare genetic variants have been found causal for autism spectrum disorder (ASD). Here, we explored the genetic landscape of RBFOX1 more deeply, integrating evidence from existing and new human studies as well as studies in Rbfox1 knockout mice. Mining existing data from large-scale studies of human common genetic variants, we confirmed gene-based and genome-wide association of RBFOX1 with risk tolerance, major depressive disorder and schizophrenia. Data on six mental disorders revealed copy number losses and gains to be more frequent in ASD cases than in controls. Consistently, RBFOX1 expression appeared decreased in post-mortem frontal and temporal cortices of individuals with ASD and prefrontal cortex of individuals with schizophrenia. Brain-functional MRI studies demonstrated that carriers of a common RBFOX1 variant, rs6500744, displayed increased neural reactivity to emotional stimuli, reduced prefrontal processing during cognitive control, and enhanced fear expression after fear conditioning, going along with increased avoidance behaviour. Investigating Rbfox1 neuron-specific knockout mice allowed us to further specify the role of this gene in behaviour. The model was characterised by pronounced hyperactivity, stereotyped behaviour, impairments in fear acquisition and extinction, reduced social interest, and lack of aggression; it provides excellent construct and face validity as an animal model of ASD. In conclusion, convergent translational evidence shows that common variants in RBFOX1 are associated with a broad spectrum of psychiatric traits and disorders, while rare genetic variation seems to expose to early-onset neurodevelopmental psychiatric disorders with and without developmental delay like ASD, in particular. Studying the pleiotropic nature of RBFOX1 can profoundly enhance our understanding of mental disorder vulnerability.

Identifying the Common Genetic Basis of Antidepressant Response.

Background: Antidepressants are a first-line treatment for depression. However, only a third of individuals experience remission after the first treatment. Common genetic variation, in part, likely regulates antidepressant response, yet the success of previous genome-wide association studies has been limited by sample size. This study performs the largest genetic analysis of prospectively assessed antidepressant response in major depressive disorder to gain insight into the underlying biology and enable out-of-sample prediction. Methods: Genome-wide analysis of remission (n remit = 1852, n nonremit = 3299) and percentage improvement (n = 5218) was performed. Single nucleotide polymorphism-based heritability was estimated using genome-wide complex trait analysis. Genetic covariance with eight mental health phenotypes was estimated using polygenic scores/AVENGEME. Out-of-sample prediction of antidepressant response polygenic scores was assessed. Gene-level association analysis was performed using MAGMA and transcriptome-wide association study. Tissue, pathway, and drug binding enrichment were estimated using MAGMA. Results: Neither genome-wide association study identified genome-wide significant associations. Single nucleotide polymorphism-based heritability was significantly different from zero for remission (h 2 = 0.132, SE = 0.056) but not for percentage improvement (h 2 = -0.018, SE = 0.032). Better antidepressant response was negatively associated with genetic risk for schizophrenia and positively associated with genetic propensity for educational attainment. Leave-one-out validation of antidepressant response polygenic scores demonstrated significant evidence of out-of-sample prediction, though results varied in external cohorts. Gene-based analyses identified ETV4 and DHX8 as significantly associated with antidepressant response. Conclusions: This study demonstrates that antidepressant response is influenced by common genetic variation, has a genetic overlap schizophrenia and educational attainment, and provides a useful resource for future research. Larger sample sizes are required to attain the potential of genetics for understanding and predicting antidepressant response.

Chemokine receptor 4 expression on blood T lymphocytes predicts severity of major depressive disorder.

BACKGROUND: Chemokines and their receptors regulate inflammatory processes in major depressive disorder (MDD). Here, we characterize the expression pattern of the C-C chemokine receptor 4 (CCR4) and its ligands CCL17 and CCL22 in MDD and its clinical relevance in predicting disease severity. METHODS: Expression of CCR4 on peripheral blood lymphocytes and serum CCL17/CCL22 levels were measured using multiparameter flow cytometry and multiplex assays in 33 depressed inpatients at baseline (T0) and after 6-week multimodal treatment (T1) compared with 21 healthy controls (HC). Using stratified and correlation analysis, we examined the associations of CCR4-CCL17/CCL22 expression with depression severity and symptoms according to standard clinical rating scales and questionnaires. Additionally, we assessed whether polygenic risk score (PRS) for psychiatric disorders and chronotype are associated with disease status or CCR4-CCL17/CCL22 expression. Regression analysis was performed to assess the capacity of CCR4 and PRS in predicting disease severity. RESULTS: Compared with HC, MDD patients showed significantly decreased CCR4 expression on T cells (T0 and T1), whereas CCL17/CCL22 serum levels were increased. Stratified and correlation analysis revealed an association of CCR4 expression on CD4+ T cells with depression severity as well as Beck Depression Inventory-II items including loss of pleasure, agitation and cognitive deficits. CCR4 expression levels on CD4+ T cells together with cross-disorder and chronotype PRS significantly predicted disease severity. LIMITATIONS: This exploratory study with small sample size warrants future studies. CONCLUSIONS: This newly identified CCR4-CCL17/CCL22 signature and its predictive capacity for MDD severity suggest its potential functional involvement in the pathophysiology of MDD.

Virtual Ontogeny of Cortical Growth Preceding Mental Illness.

BACKGROUND: Morphology of the human cerebral cortex differs across psychiatric disorders, with neurobiology and developmental origins mostly undetermined. Deviations in the tangential growth of the cerebral cortex during pre/perinatal periods may be reflected in individual variations in cortical surface area later in life. METHODS: Interregional profiles of group differences in surface area between cases and controls were generated using T1-weighted magnetic resonance imaging from 27,359 individuals including those with attention-deficit/hyperactivity disorder, autism spectrum disorder, bipolar disorder, major depressive disorder, schizophrenia, and high general psychopathology (through the Child Behavior Checklist). Similarity of interregional profiles of group differences in surface area and prenatal cell-specific gene expression was assessed. RESULTS: Across the 11 cortical regions, group differences in cortical area for attention-deficit/hyperactivity disorder, schizophrenia, and Child Behavior Checklist were dominant in multimodal association cortices. The same interregional profiles were also associated with interregional profiles of (prenatal) gene expression specific to proliferative cells, namely radial glia and intermediate progenitor cells (greater expression, larger difference), as well as differentiated cells, namely excitatory neurons and endothelial and mural cells (greater expression, smaller difference). Finally, these cell types were implicated in known pre/perinatal risk factors for psychosis. Genes coexpressed with radial glia were enriched with genes implicated in congenital abnormalities, birth weight, hypoxia, and starvation. Genes coexpressed with endothelial and mural genes were enriched with genes associated with maternal hypertension and preterm birth. CONCLUSIONS: Our findings support a neurodevelopmental model of vulnerability to mental illness whereby prenatal risk factors acting through cell-specific processes lead to deviations from typical brain development during pregnancy.

Mapping genomic loci implicates genes and synaptic biology in schizophrenia.

Schizophrenia has a heritability of 60-80%1, much of which is attributable to common risk alleles. Here, in a two-stage genome-wide association study of up to 76,755 individuals with schizophrenia and 243,649 control individuals, we report common variant associations at 287 distinct genomic loci. Associations were concentrated in genes that are expressed in excitatory and inhibitory neurons of the central nervous system, but not in other tissues or cell types. Using fine-mapping and functional genomic data, we identify 120 genes (106 protein-coding) that are likely to underpin associations at some of these loci, including 16 genes with credible causal non-synonymous or untranslated region variation. We also implicate fundamental processes related to neuronal function, including synaptic organization, differentiation and transmission. Fine-mapped candidates were enriched for genes associated with rare disruptive coding variants in people with schizophrenia, including the glutamate receptor subunit GRIN2A and transcription factor SP4, and were also enriched for genes implicated by such variants in neurodevelopmental disorders. We identify biological processes relevant to schizophrenia pathophysiology; show convergence of common and rare variant associations in schizophrenia and neurodevelopmental disorders; and provide a resource of prioritized genes and variants to advance mechanistic studies.

A Delphi-method-based consensus guideline for definition of treatment-resistant depression for clinical trials.

Criteria for treatment-resistant depression (TRD) and partially responsive depression (PRD) as subtypes of major depressive disorder (MDD) are not unequivocally defined. In the present document we used a Delphi-method-based consensus approach to define TRD and PRD and to serve as operational criteria for future clinical studies, especially if conducted for regulatory purposes. We reviewed the literature and brought together a group of international experts (including clinicians, academics, researchers, employees of pharmaceutical companies, regulatory bodies representatives, and one person with lived experience) to evaluate the state-of-the-art and main controversies regarding the current classification. We then provided recommendations on how to design clinical trials, and on how to guide research in unmet needs and knowledge gaps. This report will feed into one of the main objectives of the EUropean Patient-cEntric clinicAl tRial pLatforms, Innovative Medicines Initiative (EU-PEARL, IMI) MDD project, to design a protocol for platform trials of new medications for TRD/PRD.

Polygenic risk scores across the extended psychosis spectrum.

As early detection of symptoms in the subclinical to clinical psychosis spectrum may improve health outcomes, knowing the probabilistic susceptibility of developing a disorder could guide mitigation measures and clinical intervention. In this context, polygenic risk scores (PRSs) quantifying the additive effects of multiple common genetic variants hold the potential to predict complex diseases and index severity gradients. PRSs for schizophrenia (SZ) and bipolar disorder (BD) were computed using Bayesian regression and continuous shrinkage priors based on the latest SZ and BD genome-wide association studies (Psychiatric Genomics Consortium, third release). Eight well-phenotyped groups (n = 1580; 56% males) were assessed: control (n = 305), lower (n = 117) and higher (n = 113) schizotypy (both groups of healthy individuals), at-risk for psychosis (n = 120), BD type-I (n = 359), BD type-II (n = 96), schizoaffective disorder (n = 86), and SZ groups (n = 384). PRS differences were investigated for binary traits and the quantitative Positive and Negative Syndrome Scale. Both BD-PRS and SZ-PRS significantly differentiated controls from at-risk and clinical groups (Nagelkerke's pseudo-R2: 1.3-7.7%), except for BD type-II for SZ-PRS. Out of 28 pairwise comparisons for SZ-PRS and BD-PRS, 9 and 12, respectively, reached the Bonferroni-corrected significance. BD-PRS differed between control and at-risk groups, but not between at-risk and BD type-I groups. There was no difference between controls and schizotypy. SZ-PRSs, but not BD-PRSs, were positively associated with transdiagnostic symptomology. Overall, PRSs support the continuum model across the psychosis spectrum at the genomic level with possible irregularities for schizotypy. The at-risk state demands heightened clinical attention and research addressing symptom course specifiers. Continued efforts are needed to refine the diagnostic and prognostic accuracy of PRSs in mental healthcare.