Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia part I: Neurophysiology

Sleep spindles as neurophysiological biomarkers of schizophrenia

Schizophrenia (SCZ) is a complex psychiatric disorder characterized by a wide range of clinical symptoms, including disrupted sleep. In recent years, there has been growing interest in assessing alterations in sleep parameters in patients with SCZ. Sleep spindles are brief (0.5-2 s) bursts of 12- to 16-Hz rhythmic electroencephalogram (EEG) oscillatory activity occurring during non-rapid eye movement (NREM) sleep. Spindles have been implicated in several critical brain functions, including learning, memory and plasticity, and are thought to reflect the integrity of underlying thalamocortical circuits. This review aims to provide an overview of the current research investigating sleep spindles in SCZ. After briefly describing the neurophysiological features of sleep spindles, I will discuss alterations in spindle characteristics observed in SCZ, their associations with the clinical symptomatology of these patients and their putative underlying neuronal and molecular mechanisms. I will then discuss the utility of sleep spindle measures as predictors of treatment response and disease progression. Finally, I will highlight future directions for research in this emerging field, including the prospect of utilizing sleep spindles as neurophysiological biomarkers of SCZ.

Unique Challenges in Biomarkers for Psychotic Disorders

Biomarkers are observations that provide information about the risk of certain conditions (predictive) or their underlying mechanisms (explanatory) [...].

Altered Sleep Oscillations as Neurophysiological Biomarkers of Schizophrenia

Sleep spindles and slow waves are the two main oscillatory activities occurring during nonrapid eye movement (NREM) sleep. Here, we will first describe the electrophysiological characteristics of these sleep oscillations along with the neurophysiological and molecular mechanisms underlying their generation and synchronization in the healthy brain. We will then review the extant evidence of deficits in sleep spindles and, to a lesser extent, slow waves, including in slow wave-spindle coupling, in patients with Schizophrenia (SCZ) across the course of the disorder, from at-risk to chronic stages. Next, we will discuss how these sleep oscillatory deficits point to defects in neuronal circuits within the thalamocortical network as well as to alterations in molecular neurotransmission implicating the GABAergic and glutamatergic systems in SCZ. Finally, after explaining how spindle and slow waves may represent neurophysiological biomarkers with predictive, diagnostic, and prognostic potential, we will present novel pharmacological and neuromodulatory interventions aimed at restoring sleep oscillatory deficits in SCZ, which in turn may serve as target engagement biomarkers to ameliorate the clinical symptoms and the quality of life of individuals affected by this devastating brain disorder.

Electrophysiological biomarkers in dual pathology

INTRODUCTION

The co-occurrence of substance use disorder with at least one other mental disorder is called dual pathology, which in turn is characterised by heterogeneous symptoms that are difficult to diagnose and have a poor response to treatment. For this reason, the identification and validation of biomarkers is necessary. Within this group, possible electroencephalographic biomarkers have been reported to be useful in diagnosis, treatment and follow-up, both in neuropsychiatric conditions and in substance use disorders. This article aims to review the existing literature on electroencephalographic biomarkers in dual pathology.

METHODS

A narrative review of the literature. A bibliographic search was performed on the PubMed, Science Direct, OVID, BIREME and Scielo databases, with the keywords: electrophysiological biomarker and substance use disorder, electrophysiological biomarker and mental disorders, biomarker and dual pathology, biomarker and substance use disorder, electroencephalography, and substance use disorder or comorbid mental disorder.

RESULTS

Given the greater amount of literature found in relation to electroencephalography as a biomarker of mental illness and substance use disorders, and the few articles found on dual pathology, the evidence is organised as a biomarker in psychiatry for the diagnosis and prediction of risk and as a biomarker for dual pathology.

CONCLUSIONS

Although the evidence is not conclusive, it suggests the existence of a subset of sites and mechanisms where the effects of psychoactive substances and the neurobiology of some mental disorders could overlap or interact.

Sleep Abnormalities in Schizophrenia: State of the Art and Next Steps

Sleep disturbances are commonly observed in schizophrenia, including in chronic, early-course, and first-episode patients. This has generated considerable interest, both in clinical and research endeavors, in characterizing the relationship between disturbed sleep and schizophrenia. Sleep features can be objectively assessed with EEG recordings. Traditionally, EEG studies have focused on sleep architecture, which includes non-REM and REM sleep stages. More recently, numerous studies have investigated alterations in sleep-specific rhythms, including EEG oscillations, such as sleep spindles and slow waves, in individuals with schizophrenia compared with control subjects. In this article, the author reviews state-of-the-art evidence of disturbed sleep in schizophrenia, starting from the relationship between sleep disturbances and clinical symptoms. First, the author presents studies demonstrating abnormalities in sleep architecture and sleep-oscillatory rhythms in schizophrenia and related psychotic disorders, with an emphasis on recent work demonstrating sleep spindles and slow-wave deficits in early-course and first-episode schizophrenia. Next, the author shows how these sleep abnormalities relate to the cognitive impairments in patients diagnosed with schizophrenia and point to dysfunctions in underlying thalamocortical circuits, Ca+ channel activity, and GABA-glutamate neurotransmission. Finally, the author discusses some of the next steps needed to further establish the role of altered sleep in schizophrenia, including the need to investigate sleep abnormalities across the psychotic spectrum and to establish their relationship with circadian disturbances, which in turn will contribute to the development of novel sleep-informed treatment interventions.

Sleep spindle and slow wave abnormalities in schizophrenia and other psychotic disorders: Recent findings and future directions

Sleep spindles and slow waves are the two main oscillatory activities occurring during NREM sleep. Slow waves are ∼1 Hz, high amplitude, negative-positive deflections that are primarily generated and coordinated within the cortex, whereas sleep spindles are 12-16 Hz, waxing and waning oscillations that are initiated within the thalamus and regulated by thalamo-cortical circuits. In healthy subjects, these oscillations are thought to be responsible for the restorative aspects of sleep and have been increasingly shown to be involved in learning, memory and plasticity. Furthermore, deficits in sleep spindles and, to lesser extent, slow waves have been reported in both chronic schizophrenia (SCZ) and early course psychosis patients. In this article, we will first describe sleep spindle and slow wave characteristics, including their putative functional roles in the healthy brain. We will then review electrophysiological, genetic, and cognitive studies demonstrating spindle and slow wave impairments in SCZ and other psychotic disorders, with particularly emphasis on recent findings in early course patients. Finally, we will discuss how future work, including sleep studies in individuals at clinical high risk for psychosis, may help position spindles and slow waves as candidate biomarkers, as well as novel treatment targets, for SCZ and related psychotic disorders.

Current challenges and possible future developments in personalized psychiatry with an emphasis on psychotic disorders

A personalized medicine approach seems to be particularly applicable to psychiatry. Indeed, considering mental illness as deregulation, unique to each patient, of molecular pathways, governing the development and functioning of the brain, seems to be the most justified way to understand and treat disorders of this medical category. In order to extract correct information about the implicated molecular pathways, data can be drawn from sampling phenotypic and genetic biomarkers and then analyzed by a machine learning algorithm. This review describes current difficulties in the field of personalized psychiatry and gives several examples of possibly actionable biomarkers of psychotic and other psychiatric disorders, including several examples of genetic studies relevant to personalized psychiatry. Most of these biomarkers are not yet ready to be introduced in clinical practice. In a next step, a perspective on the path personalized psychiatry may take in the future is given, paying particular attention to machine learning algorithms that can be used with the goal of handling multidimensional datasets.

Accuracy of diagnostic classification algorithms using cognitive-, electrophysiological-, and neuroanatomical data in antipsychotic-naïve schizophrenia patients

BACKGROUND

A wealth of clinical studies have identified objective biomarkers, which separate schizophrenia patients from healthy controls on a group level, but current diagnostic systems solely include clinical symptoms. In this study, we investigate if machine learning algorithms on multimodal data can serve as a framework for clinical translation.

METHODS

Forty-six antipsychotic-naïve, first-episode schizophrenia patients and 58 controls underwent neurocognitive tests, electrophysiology, and magnetic resonance imaging (MRI). Patients underwent clinical assessments before and after 6 weeks of antipsychotic monotherapy with amisulpride. Nine configurations of different supervised machine learning algorithms were applied to first estimate the unimodal diagnostic accuracy, and next to estimate the multimodal diagnostic accuracy. Finally, we explored the predictability of symptom remission.

RESULTS

Cognitive data significantly classified patients from controls (accuracies = 60-69%; p values = 0.0001-0.009). Accuracies of electrophysiology, structural MRI, and diffusion tensor imaging did not exceed chance level. Multimodal analyses with cognition plus any combination of one or more of the remaining three modalities did not outperform cognition alone. None of the modalities predicted symptom remission.

CONCLUSIONS

In this multivariate and multimodal study in antipsychotic-naïve patients, only cognition significantly discriminated patients from controls, and no modality appeared to predict short-term symptom remission. Overall, these findings add to the increasing call for cognition to be included in the definition of schizophrenia. To bring about the full potential of machine learning algorithms in first-episode, antipsychotic-naïve schizophrenia patients, careful a priori variable selection based on independent data as well as inclusion of other modalities may be required.

Future paths in psychopharmacology

Drug development in psychiatry is gradually moving from serendipity to personalized medicine. Some promising paths will be reviewed in this issue.


The phenolic interactome and gut microbiota: opportunities and challenges in developing applications for schizophrenia and autism

Schizophrenia and autism spectrum disorder have long been associated with elevated levels of various small phenolic molecules (SPMs). In turn, the gut microbiota (GMB) has been implicated in the kinetics of many of these analytes. Unfortunately, research into the possible relevance of GMB-mediated SPMs to neuropsychiatry continues to be limited by heterogeneous study design, numerous sources of variance and technical challenges. Some SPMs have multiple structural isomers and most have conjugates. Without specialized approaches, SPMs can be incorrectly assigned or inaccurately quantified. In addition, SPM levels can be affected by dietary polyphenol or protein consumption and by various medications and diseases. Nonetheless, heterotypical excretion of various SPMs in association with schizophrenia or autism continues to be reported in independent samples. Recent studies in human cerebrospinal fluid demonstrate the presence of many SPMs A large number of these are bioactive in experimental models. Whether such mechanisms are relevant to the human brain in health or disease is not known. Systematic metabolomic and microbiome studies of well-characterized populations, an appreciation of multiple confounds, and implementation of standardized approaches across platforms and sites are needed to delineate the potential utility of the phenolic interactome in neuropsychiatry.

Inflexible eye fixation pattern in schizophrenia affecting decision-making on daily life

Patients with schizophrenia have difficulties in real life due to impairment in ability to make decisions. The purpose of this study was to elucidate the relationship between impaired decision-making processes with real life stimuli and abnormal eye gaze patterns in patients with schizophrenia. Each of 23 patients with schizophrenia and 23 healthy controls performed an apparel purchase decision task including the influencing factors such as preference, fit, and price, during which the eye gaze was traced. Fixation time and fixation time ratio on areas of interest, which were set for participant faces and clothing, were compared between the two groups. Compared with controls, patients made purchase decisions at a higher rate and showed significantly shorter fixation time on clothing in the preference, fit, and price phases and on faces in the purchase phase. Fixation time ratio of face over clothing did not change over purchase decisions in patients, whereas controls showed significantly higher fixation time ratio in not-to-buy decisions than in to-buy decisions. These results suggest that aberrant decision-making behaviors in patients with schizophrenia are closely related to inflexible visual information gathering patterns because they apportion the same amount of attention to objects regardless of purchase intention.

Peripheral Biomarkers for First-Episode Psychosis-Opportunities from the Neuroinflammatory Hypothesis of Schizophrenia

OBJECTIVE

Schizophrenia is a disabling disorder of unknown aetiology, lacking definite diagnostic method and cure. A reliable biological marker of schizophrenia is highly demanded, for which traceable immune mediators in blood could be promising candidates. We aimed to gather the best findings of neuroinflammatory markers for first-episode psychosis (FEP).

METHODS

We performed an extensive narrative review of online literature on inflammation-related markers found in human FEP patients only.

RESULTS

Changes to cytokine levels have been increasingly reported in schizophrenia. The peripheral levels of IL-1 (or its receptor antagonist), soluble IL-2 receptor, IL-4, IL-6, IL-8, and TNF-α have been frequently reported as increased in FEP, in a suggestive continuum from high-risk stages for psychosis. Microglia and astrocytes establish the link between this immune signalling and the synthesis of noxious tryptophan catabolism products, that cause structural damage and directly hamper normal neurotransmission. Amongst these, only 3-hydroxykynurenine has been consistently described in the blood of FEP patients.

CONCLUSION

Peripheral molecules stemming from brain inflammation might provide insightful biomarkers of schizophrenia, as early as FEP or even prodromal phases, although more time- and clinically-adjusted studies are essential for their validation.

Evoked Potentials Investigations of Deficit Versus Nondeficit Schizophrenia: EEG-MEG Preliminary Data

Heterogeneity of schizophrenia is a major obstacle toward understanding the disorder. One likely subtype is the deficit syndrome (DS) where patients suffer from predominantly negative symptoms. This study investigated the evoked responses and the evoked magnetic fields to identify the neurophysiological deviations associated with the DS. Ten subjects were recruited for each group (Control, DS, and Nondeficit schizophrenia [NDS]). Subjects underwent magnetoencephalography (MEG) and electroencephalography (EEG) testing while listening to an oddball paradigm to generate the P300 as well as a paired click paradigm to generate the mid-latency auditory-evoked responses (MLAER) in a sensory gating paradigm. MEG-coherence source imaging (CSI) during P300 task revealed a significantly higher average coherence value in DS than NDS subjects in the gamma band (30-80 Hz), when listening to standard stimuli but only NDS subjects had a higher average coherence level in the gamma band than controls when listening to the novel sounds. P50, N100, and P3a ERP amplitudes (EEG analysis) were significantly decreased in NDS compared with DS subjects. The data suggest that the deviations in the 2 patient groups are qualitatively different. Deviances in NDS patients suggest difficulty in both early (as in the gating paradigm), as well as later top-down processes (P300 paradigm). The main deviation in the DS group was an exaggerated responsiveness to ongoing irrelevant stimuli detected by EEG whereas NDS subjects had an exaggerated response to novelty.

Potential Mechanisms for the Ketamine-Induced Reduction of P3b Amplitudes

In specific dosages, the N-methyl-D-aspartate receptor (NMDA) antagonist ketamine can be used to model transient psychotic symptoms in healthy individuals that resemble those of schizophrenia. Ketamine administration also temporarily impairs cognitive functions, which can be studied by event-related potentials (ERPs). ERPs also allow dissecting what stages of information processing are affected by ketamine and what stages remain functional. For tasks requiring the differentiation of targets and non-targets, it has repeatedly been shown that ketamine administration in healthy individuals leads to decreased amplitudes of the ERP component P3b in response to target stimuli. However, it could be argued that this ketamine-induced P3b reduction is the consequence of an increased difficulty to differentiate targets from non-targets, primarily mediated by ketamine's psychotomimetic rather than pharmacological effects. The current review of ERP studies seeks to clarify the issue whether P3b effects of ketamine may indeed be explained as the consequence of an experienced increase in task difficulty or whether alternative mechanisms are perhaps more plausible. The review first summarizes the effects of task difficulty on ERP components related to intentional stimulus categorization (P3b), involuntary attention switches to distractors (P3a), as well as sensory processing (P1, N1). Secondly, the ERP effects of task difficulty are contrasted with those observed in ketamine studies in healthy individuals. Findings show that P3b amplitudes are consistently diminished by an increased task difficulty, as well as after ketamine administration. In contrast and as most important difference, increased task difficulty leads to increased P3a amplitudes to distractors presented in same modality as targets, whereas ketamine leads to reduced P3a amplitudes for such distractors. This dissociation indicates that the decreased P3b amplitudes after ketamine cannot be explained by a drug-induced increase in task difficulty. The conjoint reductions of P3a and P3b amplitudes instead suggest that working memory operations, in particular working memory updating are impaired after ketamine, which is in line with previous behavioral findings.

Controversies in psychiatry

Neuroimaging and recent genetics discoveries have raised many questions regarding the current diagnostic criteria of psychiatric diseases and the current classifications used, which are still based on subjective clinical assessment. Despite high-quality research in brain neuroscience and evidence-based guidelines in many psychiatric diseases, some therapeutic issues are still a matter of debate. These controversial issues will be discussed in this 20th anniversary issue.

Retinal abnormatilites as a diagnostic or prognostic marker of schizophrenia

The review is a summary of structural and functional changes in the human retina observed in patients with schizophrenia. The main focus is on the potential of these changes to serve as schizophrenia-specific biomarkers accessible to clinicians. We identified three features of the retina that can be detected non-invasively in humans and which appear to show charateristic changes in schizophrenia: (1) retinal microvasculature displaying abnormally wide venules; (2) electroretinograms indicating altered function of photoreceptors or other cells in the retinal component of the visual pathway; (3) optical coherence tomography pointing to structural differences between the retinae of patients with schizophrenia and those of healthy volunteers. We propose that the most feasible approach to evaluating the data would be to study the genetic and epigenetic background of the schizophrenia-associated retinal abnormalities and establish their significance and specificity as potential biomarkers for the disease. The studies should include longitudinal observations focusing on the possible involvement of medication and comorbid conditions in the mechanism of the disease; a comparison of schizophrenia with other mental disorders; and investigating retinal abnormalities in animal models of psychoses. Biomarkers identified in the process could represent an important addition to the arsenal of non-invasive techniques available to both clinicians and researchers. These novel biomarkers could facilitate research of the biological basis of psychosis and help to address the diagnostic, predicitive, preventative, prophylactic and therapeutic aspects of schizophrenia.

Interactions Between Variation in Candidate Genes and Environmental Factors in the Etiology of Schizophrenia and Bipolar Disorder: a Systematic Review

Schizophrenia and bipolar disorder (BD) are complex and multidimensional disorders with high heritability rates. The contribution of genetic factors to the etiology of these disorders is increasingly being recognized as the action of multiple risk variants with small effect sizes, which might explain only a minor part of susceptibility. On the other site, numerous environmental factors have been found to play an important role in their causality. Therefore, in recent years, several studies focused on gene × environment interactions that are believed to bridge the gap between genetic underpinnings and environmental insults. In this article, we performed a systematic review of studies investigating gene × environment interactions in BD and schizophrenia spectrum phenotypes. In the majority of studies from this field, interacting effects of variation in genes encoding catechol-O-methyltransferase (COMT), brain-derived neurotrophic factor (BDNF), and FK506-binding protein 5 (FKBP5) have been explored. Almost consistently, these studies revealed that polymorphisms in COMT, BDNF, and FKBP5 genes might interact with early life stress and cannabis abuse or dependence, influencing various outcomes of schizophrenia spectrum disorders and BD. Other interactions still require further replication in larger clinical and non-clinical samples. In addition, future studies should address the direction of causality and potential mechanisms of the relationship between gene × environment interactions and various categories of outcomes in schizophrenia and BD.

Dissociable auditory mismatch response and connectivity patterns in adolescents with schizophrenia and adolescents with bipolar disorder with psychosis: A magnetoencephalography study

BACKGROUND

There is overlap between schizophrenia and bipolar disorder regarding genetic risk as well as neuropsychological and structural brain deficits. Finding common and distinct event-response potential (ERP) responses and connectivity patterns may offer potential biomarkers to distinguish the disorders.

OBJECTIVE

To examine the neuronal auditory response elicited by a roving mismatch negativity (MMN) paradigm using magnetoencephalography (MEG).

PARTICIPANTS

15 Adolescents with schizophrenia (ASZ), 16 adolescents with bipolar disorder with psychosis (ABP), and 14 typically developing individuals (TD) METHODS: The data were analysed using time-series techniques and dynamic causal modelling (DCM).

OUTCOME MEASURES

MEG difference wave (deviant - standard) at primary auditory (~90ms), MMN (~180ms) and long latency (~300ms).

RESULTS

The amplitude of difference wave showed specific patterns at all latencies. Most notably, it was significantly reduced ABP compared to both controls and ASZ at early latencies. In contrast, the amplitude was significantly reduced in ASZ compared to both controls and ABP. The DCM analysis showed differential connectivity patterns in all three groups. Most notably, inter-hemispheric connections were strongly dominated by the right side in ASZ only.

CONCLUSIONS

Dissociable patterns of the primary auditory response and MMN response indicate possible developmentally sensitive, but separate biomarkers for schizophrenia and bipolar disorder.

Shifting the focus toward rare variants in schizophrenia to close the gap from genotype to phenotype

Schizophrenia (SZ) is a disorder with a high heritability and a complex architecture. Several dozen genetic variants have been identified as risk factors through genome-wide association studies including large population-based samples. However, the bulk of the risk cannot be accounted for by the genes associated to date. Rare mutations have been historically seen as relevant only for some infrequent, Mendelian forms of psychosis. Recent findings, however, show that the subset of patients that present a mutation with major effect is larger than expected. We discuss some of the molecular findings of these studies. SZ is clinically and genetically heterogeneous. To identify the genetic variation underlying the disorder, research should be focused on features that are more likely a product of genetic heterogeneity. Based on the phenotypical correlations with rare variants, cognition emerges as a relevant domain to study. Cognitive disturbances could be useful in selecting cases that have a higher probability of carrying deleterious mutations, as well as on the correct ascertainment of sporadic cases for the identification of de novo variants.

Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia, part III: Molecular mechanisms

OBJECTIVES

Despite progress in identifying molecular pathophysiological processes in schizophrenia, valid biomarkers are lacking for both the disease and treatment response.

METHODS

This comprehensive review summarises recent efforts to identify molecular mechanisms on the level of protein and gene expression and epigenetics, including DNA methylation, histone modifications and micro RNA expression. Furthermore, it summarises recent findings of alterations in lipid mediators and highlights inflammatory processes. The potential that this research will identify biomarkers of schizophrenia is discussed.

RESULTS

Recent studies have not identified clear biomarkers for schizophrenia. Although several molecular pathways have emerged as potential candidates for future research, a complete understanding of these metabolic pathways is required to reveal better treatment modalities for this disabling condition.

CONCLUSIONS

Large longitudinal cohort studies are essential that pair a thorough phenotypic and clinical evaluation for example with gene expression and proteome analysis in blood at multiple time points. This approach might identify biomarkers that allow patients to be stratified according to treatment response and ideally also allow treatment response to be predicted. Improved knowledge of molecular pathways and epigenetic mechanisms, including their potential association with environmental influences, will facilitate the discovery of biomarkers that could ultimately be effective tools in clinical practice.

Sensory processing in autism spectrum disorders and Fragile X syndrome-From the clinic to animal models

Brains are constantly flooded with sensory information that needs to be filtered at the pre-attentional level and integrated into endogenous activity in order to allow for detection of salient information and an appropriate behavioral response. People with Autism Spectrum Disorder (ASD) or Fragile X Syndrome (FXS) are often over- or under-reactive to stimulation, leading to a wide range of behavioral symptoms. This altered sensitivity may be caused by disrupted sensory processing, signal integration and/or gating, and is often being neglected. Here, we review translational experimental approaches that are used to investigate sensory processing in humans with ASD and FXS, and in relevant rodent models. This includes electroencephalographic measurement of event related potentials, neural oscillations and mismatch negativity, as well as habituation and pre-pulse inhibition of startle. We outline robust evidence of disrupted sensory processing in individuals with ASD and FXS, and in respective animal models, focusing on the auditory sensory domain. Animal models provide an excellent opportunity to examine common mechanisms of sensory pathophysiology in order to develop therapeutics.

Experimentally induced psychosocial stress in schizophrenia spectrum disorders: A systematic review

BACKGROUND

There is evidence that exposure to social stress plays a crucial role in the onset and relapse of schizophrenia; however, the reaction of patients with schizophrenia spectrum disorder (SSD) to experimentally induced social stress is not yet fully understood.

METHOD

Original research published between January 1993 and August 2015 was included in this systematic literature research. Social stress paradigms, reporting subjective responses to stress measures, plasma or saliva cortisol, or heart rate (HR) in patients with SSD were included. 1528 articles were screened, 11 papers (390 patients) were included.

RESULTS

Three main findings were attained concerning chronically ill patients: (1) overall similar subjective responses to stress ratings between SDD patients and controls, (2) no group differences in cortisol response to psychosocial stress and (3) an increase in HR after the stress exposure was seen in patients and controls. The study examining first-episode patients found higher subjective responses to stress and lower stress-induced cortisol levels.

CONCLUSION

The results indicate that first-onset medication free patients may show differences in subjective responses to stress measures and cortisol release while chronically ill patients display no differences in subjective and cortisol response. This may be the correlate of a pathophysiological dysfunction of the hypothalamic-pituitary-adrenal axis prior or at the onset of SSD and a subsequent change in dysregulation during the course of the illness. Given the paucity of studies investigating psychosocial stress in SSD and the pathophysiological relevance of psychosocial stress for the illness, there is need for further research. (PROSPERO registration number: CRD42015026525).

Two subgroups of antipsychotic-naive, first-episode schizophrenia patients identified with a Gaussian mixture model on cognition and electrophysiology

Deficits in information processing and cognition are among the most robust findings in schizophrenia patients. Previous efforts to translate group-level deficits into clinically relevant and individualized information have, however, been non-successful, which is possibly explained by biologically different disease subgroups. We applied machine learning algorithms on measures of electrophysiology and cognition to identify potential subgroups of schizophrenia. Next, we explored subgroup differences regarding treatment response. Sixty-six antipsychotic-naive first-episode schizophrenia patients and sixty-five healthy controls underwent extensive electrophysiological and neurocognitive test batteries. Patients were assessed on the Positive and Negative Syndrome Scale (PANSS) before and after 6 weeks of monotherapy with the relatively selective D₂ receptor antagonist, amisulpride (280.3±159 mg per day). A reduced principal component space based on 19 electrophysiological variables and 26 cognitive variables was used as input for a Gaussian mixture model to identify subgroups of patients. With support vector machines, we explored the relation between PANSS subscores and the identified subgroups. We identified two statistically distinct subgroups of patients. We found no significant baseline psychopathological differences between these subgroups, but the effect of treatment in the groups was predicted with an accuracy of 74.3% (P=0.003). In conclusion, electrophysiology and cognition data may be used to classify subgroups of schizophrenia patients. The two distinct subgroups, which we identified, were psychopathologically inseparable before treatment, yet their response to dopaminergic blockade was predicted with significant accuracy. This proof of principle encourages further endeavors to apply data-driven, multivariate and multimodal models to facilitate progress from symptom-based psychiatry toward individualized treatment regimens.

From basic research to personalized medicine

In the future, precision medicine will enable every clinician to tailor treatment and even prevention strategies to an individual's unique characteristics. In order to reach this goal, we need to collect and analyze many different types of data, from many different sources, including symptoms, genomics, and brain circuitry, as well as family dynamics, environmental exposures, and cultural background.

Consensus paper of the WFSBP Task Force on Biological Markers: Criteria for biomarkers and endophenotypes of schizophrenia part II: Cognition, neuroimaging and genetics

OBJECTIVES

Schizophrenia is a group of severe psychiatric disorders with high heritability but only low odds ratios of risk genes. Despite progress in the identification of pathophysiological processes, valid biomarkers of the disease are still lacking.

METHODS

This comprehensive review summarises recent efforts to identify genetic underpinnings, clinical and cognitive endophenotypes and symptom dimensions of schizophrenia and presents findings from neuroimaging studies with structural, functional and spectroscopy magnetic resonance imaging and positron emission tomography. The potential of findings to be biomarkers of schizophrenia is discussed.

RESULTS

Recent findings have not resulted in clear biomarkers for schizophrenia. However, we identified several biomarkers that are potential candidates for future research. Among them, copy number variations and links between genetic polymorphisms derived from genome-wide analysis studies, clinical or cognitive phenotypes, multimodal neuroimaging findings including positron emission tomography and magnetic resonance imaging, and the application of multivariate pattern analyses are promising.

CONCLUSIONS

Future studies should address the effects of treatment and stage of the disease more precisely and apply combinations of biomarker candidates. Although biomarkers for schizophrenia await validation, knowledge on candidate genomic and neuroimaging biomarkers is growing rapidly and research on this topic has the potential to identify psychiatric endophenotypes and in the future increase insight on individual treatment response in schizophrenia.

Biological markers for anxiety disorders, OCD and PTSD - a consensus statement. Part I: Neuroimaging and genetics

OBJECTIVES

Biomarkers are defined as anatomical, biochemical or physiological traits that are specific to certain disorders or syndromes. The objective of this paper is to summarise the current knowledge of biomarkers for anxiety disorders, obsessive-compulsive disorder (OCD) and post-traumatic stress disorder (PTSD).

METHODS

Findings in biomarker research were reviewed by a task force of international experts in the field, consisting of members of the World Federation of Societies for Biological Psychiatry Task Force on Biological Markers and of the European College of Neuropsychopharmacology Anxiety Disorders Research Network.

RESULTS

The present article (Part I) summarises findings on potential biomarkers in neuroimaging studies, including structural brain morphology, functional magnetic resonance imaging and techniques for measuring metabolic changes, including positron emission tomography and others. Furthermore, this review reports on the clinical and molecular genetic findings of family, twin, linkage, association and genome-wide association studies. Part II of the review focuses on neurochemistry, neurophysiology and neurocognition.

CONCLUSIONS

Although at present, none of the putative biomarkers is sufficient and specific as a diagnostic tool, an abundance of high-quality research has accumulated that will improve our understanding of the neurobiological causes of anxiety disorders, OCD and PTSD.

Prioritizing schizophrenia endophenotypes for future genetic studies: An example using data from the COGS-1 family study

Past studies describe numerous endophenotypes associated with schizophrenia (SZ), but many endophenotypes may overlap in information they provide, and few studies have investigated the utility of a multivariate index to improve discrimination between SZ and healthy community comparison subjects (CCS). We investigated 16 endophenotypes from the first phase of the Consortium on the Genetics of Schizophrenia, a large, multi-site family study, to determine whether a subset could distinguish SZ probands and CCS just as well as using all 16. Participants included 345 SZ probands and 517 CCS with a valid measure for at least one endophenotype. We used both logistic regression and random forest models to choose a subset of endophenotypes, adjusting for age, gender, smoking status, site, parent education, and the reading subtest of the Wide Range Achievement Test. As a sensitivity analysis, we re-fit models using multiple imputations to determine the effect of missing values. We identified four important endophenotypes: antisaccade, Continuous Performance Test-Identical Pairs 3-digit version, California Verbal Learning Test, and emotion identification. The logistic regression model that used just these four endophenotypes produced essentially the same results as the model that used all 16 (84% vs. 85% accuracy). While a subset of endophenotypes cannot replace clinical diagnosis nor encompass the complexity of the disease, it can aid in the design of future endophenotypic and genetic studies by reducing study cost and subject burden, simplifying sample enrichment, and improving the statistical power of locating those genetic regions associated with schizophrenia that may be the easiest to identify initially.

Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for the management of schizophrenia and related disorders

OBJECTIVES

This guideline provides recommendations for the clinical management of schizophrenia and related disorders for health professionals working in Australia and New Zealand. It aims to encourage all clinicians to adopt best practice principles. The recommendations represent the consensus of a group of Australian and New Zealand experts in the management of schizophrenia and related disorders. This guideline includes the management of ultra-high risk syndromes, first-episode psychoses and prolonged psychoses, including psychoses associated with substance use. It takes a holistic approach, addressing all aspects of the care of people with schizophrenia and related disorders, not only correct diagnosis and symptom relief but also optimal recovery of social function.

METHODS

The writing group planned the scope and individual members drafted sections according to their area of interest and expertise, with reference to existing systematic reviews and informal literature reviews undertaken for this guideline. In addition, experts in specific areas contributed to the relevant sections. All members of the writing group reviewed the entire document. The writing group also considered relevant international clinical practice guidelines. Evidence-based recommendations were formulated when the writing group judged that there was sufficient evidence on a topic. Where evidence was weak or lacking, consensus-based recommendations were formulated. Consensus-based recommendations are based on the consensus of a group of experts in the field and are informed by their agreement as a group, according to their collective clinical and research knowledge and experience. Key considerations were selected and reviewed by the writing group. To encourage wide community participation, the Royal Australian and New Zealand College of Psychiatrists invited review by its committees and members, an expert advisory committee and key stakeholders including professional bodies and special interest groups.

RESULTS

The clinical practice guideline for the management of schizophrenia and related disorders reflects an increasing emphasis on early intervention, physical health, psychosocial treatments, cultural considerations and improving vocational outcomes. The guideline uses a clinical staging model as a framework for recommendations regarding assessment, treatment and ongoing care. This guideline also refers its readers to selected published guidelines or statements directly relevant to Australian and New Zealand practice.

CONCLUSIONS

This clinical practice guideline for the management of schizophrenia and related disorders aims to improve care for people with these disorders living in Australia and New Zealand. It advocates a respectful, collaborative approach; optimal evidence-based treatment; and consideration of the specific needs of those in adverse circumstances or facing additional challenges.

Deficits in GABAA receptor function and working memory in non-smokers with schizophrenia

BACKGROUND

Although altered gamma-aminobutyric acid (GABA) neurotransmission has been implicated in the pathophysiology of schizophrenia, it is unclear whether the influence of GABA on working memory processes is confounded by nicotine use in this population. It is therefore crucial to evaluate working memory and its underlying mechanisms in non-smokers with schizophrenia to eliminate the confounding effects of nicotine on behavior and neurophysiology.

METHODS

In this cross-sectional study, working memory was assessed using the verbal N-back task, while GABAergic function was assessed through motor cortical inhibition using single and paired-pulse transcranial magnetic stimulation (TMS) to the left primary motor cortex in 11 non-smokers with schizophrenia and 13 non-smoker healthy subjects.

RESULTS

Similar to previously published studies, working memory performance was significantly impaired in the 3-back condition in patients with schizophrenia compared to healthy subjects (p=0.036). In addition, GABAA receptor function was significantly reduced in schizophrenia as assessed by short interval cortical inhibition (SICI) (p=0.005). A positive correlation was found between GABAA inhibition and working memory performance on the 3-back task (r(23)=0.55, p=0.006), suggesting that greater GABAA inhibition is associated with better performance on tasks of working memory.

CONCLUSIONS

Our findings highlight the role of GABAA receptor dysfunction in working memory and the pathophysiology of schizophrenia, and may represent a selective characteristic of schizophrenia. Moreover, these findings suggest a potential therapeutic role for targeting GABA receptor activity to improve cognition and quality of life in patients with schizophrenia.