Objective Treatment resistance complicates the management of schizophrenia. Research and clinical translation is limited by inconsistent definitions. To address this we evaluated current approaches and then developed consensus criteria and guidelines. Method A systematic review of randomized antipsychotic clinical trials in treatment resistant schizophrenia was performed. Definitions of treatment resistance were extracted. Subsequently, consensus operationalized criteria were developed by a working group of researchers and clinicians through i) a multi-phase, mixed methods approach; ii) identifying key criteria via an online survey; and iii) meetings to achieve consensus. Results 42 studies met inclusion criteria. Of these, 21 (50%) studies did not provide operationalized criteria, whilst in others, criteria varied considerably, particularly regarding symptom severity, prior treatment duration and antipsychotic dose thresholds. Important for the inability to compare results, only two (5%) studies utilized the same criteria. The consensus group identified minimum and optimal criteria, employing the following principles: 1) current symptoms of a minimum duration and severity determined by a standardized rating scale; 2) ≥moderate functional impairment; 3) prior treatment consisting of ≥2 different antipsychotic trials, each for a minimum duration and dose; 4) adherence systematically assessed and meeting minimum criteria; 5) ideally at least one prospective treatment trial; 6) criteria that clearly separated responsive from treatment resistant patients. Conclusions There is considerable variation in current approaches to defining treatment resistance in schizophrenia. We present consensus guidelines that operationalize criteria for determining and reporting treatment resistance, adequate treatment and treatment response in schizophrenia, providing a benchmark for research and clinical translation.

Take-down policy If you believe that this document breaches copyright please contact us providing details, and we will remove access to the work immediately and investigate your claim. Heritability and polygenic predictionIn the EUR sample, the SNP-based heritability (h 2 SNP ) (that is, the proportion of variance in liability attributable to all measured SNPs)

The association between internalizing symptoms and biased orienting varies with the nature of developmental psychopathology. Both the form and severity of psychopathology moderates threat-related attention biases in children.

Neuroimaging-based models contribute to increasing our understanding of schizophrenia pathophysiology and can reveal the underlying characteristics of this and other clinical conditions. However, the considerable variability in reported neuroimaging results mirrors the heterogeneity of the disorder. Machine learning methods capable of representing invariant features could circumvent this problem. In this structural MRI study, we trained a deep learning model known as deep belief network (DBN) to extract features from brain morphometry data and investigated its performance in discriminating between healthy controls (N = 83) and patients with schizophrenia (N = 143). We further analysed performance in classifying patients with a first-episode psychosis (N = 32). The DBN highlighted differences between classes, especially in the frontal, temporal, parietal, and insular cortices, and in some subcortical regions, including the corpus callosum, putamen, and cerebellum. The DBN was slightly more accurate as a classifier (accuracy = 73.6%) than the support vector machine (accuracy = 68.1%). Finally, the error rate of the DBN in classifying first-episode patients was 56.3%, indicating that the representations learned from patients with schizophrenia and healthy controls were not suitable to define these patients. Our data suggest that deep learning could improve our understanding of psychiatric disorders such as schizophrenia by improving neuromorphometric analyses.

ObjectiveInvestigating dimensions of oppositional symptoms may help to explain heterogeneity of etiology and outcomes for mental disorders across development and provide further empirical justification for the DSM-5–proposed modifications of oppositional defiant disorder (ODD). However, dimensions of oppositionality have not previously been tested in samples outside Europe or the United States. In this study, we used a large Brazilian community sample to compare the fit of different models for dimensions of oppositional symptoms; to examine the association of psychiatric diagnoses and symptoms with dimensions of oppositionality; and to examine the associations between dimensions of oppositionality and parental history of mental disorders.MethodA Brazilian community sample of 2,512 children 6 through 12 years old were investigated in this study. Confirmatory factorial analyses were performed to compare the fit of alternative models, followed by linear and logistic regression analyses of associations with psychiatric diagnosis and parental history of psychopathology.ResultsA three-factor model with irritable, headstrong, and hurtful dimensions fitted best. The irritable dimension showed a strong association with emotional disorders in the child (p<.001) and history of depression (p<.01) and suicidality (p<.05) in the mother. The headstrong dimension was uniquely associated with attention-deficit/hyperactivity disorder (ADHD) in the child (p<.001) and with maternal history of ADHD symptoms (p<.05). The hurtful dimension was specifically associated with conduct disorder (p< .05).ConclusionsOur findings from a large community sample of Brazilian children support a distinction between dimensions of oppositionality consistent with current DSM-5 recommendations and provide further evidence for etiological distinctions between these dimensions.

Background:There is robust evidence that schizophrenia is characterized by immune-inflammatory abnormalities, including variations on cytokine levels. The results of previous studies, however, are heterogeneous due to several confounding factors, such as the effects of antipsychotic drugs. Therefore, research on drug-naïve first-episode psychosis (FEP) patients is essential to elucidate the role of immune processes in that disorder.Methods:The aim of this study is to compare cytokine levels (IL-2, IL-10, IL-4, IL-6, IFN-γ, TNF-α, and IL-17) in drug-naïve FEP patients both before and after treatment with risperidone for 10 weeks, and to investigate possible associations between cytokine levels and clinical responses to treatment and presence of depressive symptoms. It this study, we included 55 drug-naïve FEP patients who had repeated measurements of cytokine levels and 57 healthy controls.Results:We found that FEP patients had significantly higher IL-6, IL-10 and TNF-α levels than healthy controls. After risperidone treatment, these three cytokines and additionally IL-4 decreased significantly. No significant difference was found between the post-treatment cytokine levels in FEP patients and in healthy controls, suggesting that these alterations in cytokine profiles are a state marker of FEP. No significant association was found between risperidone-induced changes in cytokines and the clinical response to treatment or the presence of depression. There was a significant inverse association between the risperidone-induced changes in IL-10 and the negative symptoms.Conclusions:In conclusion, our results show a specific cytokine profile in FEP patients (monocytic and regulatory T-cell activation) and suggest immunoregulatory effects of risperidone treatment, characterized by suppressant effects on monocytic, Th2, and T-regulatory functions.

Genetic risk for Alzheimer's disease may affect early-life cognition and hippocampal volumes, as shown in two independent samples. These data support previous evidence that some forms of late-life dementia may represent developmental conditions with roots in childhood. This result may vary depending on a sample's genetic risk and may be specific to some types of memory tasks.

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