Identification of a blood-based biological signature in subjects with psychiatric disorders prior to clinical manifestation

Decreased oxytocin levels related to social cognition impairment in borderline personality disorder

INTRODUCTION

Dysfunctions in the oxytocin system have been reported in patients with borderline personality disorder (BPD). Deficits could be related to interpersonal hypersensitivity, which has been previously associated with failures in social cognition (SC) in this disorder, especially in Theory of Mind (ToM) skills. The aim of this work is to study the links between the oxytocin system and SC impairments in patients with BPD.

METHOD

Plasma oxytocin levels (OXT) and protein expression of oxytocin receptors in blood mononuclear cells (OXTR) were examined in 33 patients with a diagnosis of BPD (age: M 28.85, DT = 8.83). Social cognition was assessed using the Movie for the Assessment of Social Cognition (MASC). Statistical associations between biochemical factors and different response errors in MASC were analyzed through generalized linear regression controlling for relevant clinical factors.

RESULTS

Generalized linear regression showed a significant relationship between lower OXTR and overmentalization in BPD patients (OR = 0.90).

CONCLUSIONS

This work supports the relationship between alterations in the oxytocin system and ToM impairments observed in BPD patients, enhancing the search for endophenotypes related to the phenotypic features of the disorder to improve current clinical knowledge and address more specific therapeutic targets.

Putative Risk Biomarkers of Bipolar Disorder in At-risk Youth

Bipolar disorder is a highly heritable and functionally impairing disease. The recognition and intervention of BD especially that characterized by early onset remains challenging. Risk biomarkers for predicting BD transition among at-risk youth may improve disease prognosis. We reviewed the more recent clinical studies to find possible pre-diagnostic biomarkers in youth at familial or (and) clinical risk of BD. Here we found that putative biomarkers for predicting conversion to BD include findings from multiple sample sources based on different hypotheses. Putative risk biomarkers shown by perspective studies are higher bipolar polygenetic risk scores, epigenetic alterations, elevated immune parameters, front-limbic system deficits, and brain circuit dysfunction associated with emotion and reward processing. Future studies need to enhance machine learning integration, make clinical detection methods more objective, and improve the quality of cohort studies.

Transdiagnostic inflammatory and oxidative biomarkers with predictive capacity of self-injurious behavior in impulsive and unstable disorders

INTRODUCTION

Alterations in inflammatory processes have previously been reported in impulsive and unstable disorders, as well as in other psychiatric conditions. In order to investigate transdiagnostic biomarkers associated with various phenotypic features of these disorders, this study is designed to identify biomarkers of inflammatory and oxidative endophenotypes related to autolytic behavior.

METHODS

Peripheral blood mononuclear cells were collected from 35 patients with borderline personality disorder (BPD), 29 patients with restrictive eating disorder (rED), 21 patients with purging eating disorder (pED) and 23 control subjects. Plasma levels of different inflammatory and oxidative factors were measured by ELISA and the expression of selected proteins was by Western Blot. Principal component analysis (PCA) was performed to categorize the different inflammatory factors. Additionally, Ancova was performed to observe the differences in the principal components among the different groups and logistic regression analysis was conducted to assess the predictive capacity of these components for autolytic behaviors.

RESULTS

We found two inflammatory/oxidative components were associated with BPD, characterized by high levels of JNK and ERK and low levels of GPx, SOD and Keap1; and two other inflammatory/oxidative components were linked to pED, associated with more JNK, TBARS and TNF-α and less GPx and SOD. Two components, with more JNK and ERK and less GPx, SOD and Keap1, predicted non-suicidal self-injury and three components, with higher JNK, TBARS and TNF-α levels and lower GPx, SOD and iNOS levels, predicted suicide attempts.

CONCLUSIONS

These results strongly support the endophenotypic characterization of impulsivity and the identification of transdiagnostic inflammatory/oxidative biomarkers relevant to autolytic behavior in impulsive and unstable disorders. These dates lay the groundwork for developing of screening tests for these biomarker components to rapidly detect biological risk factors for specific impulse control disorders and future self-injurious behaviors.

Inflammatory and oxidative endophenotypes in borderline personality disorder: A biomarker cluster analysis

OBJECTIVES

This study is designed to search for aggrupation of inflammatory/oxidative biomarker alterations in borderline personality disorder (BPD) and their association with phenotypic features.

METHODOLOGY

Inflammatory/nitrosative proteins were measures in plasma and peripheral blood mononuclear cells obtained from BPD patients. Patients were assessed on different clinical dimensions of BPD. Oxidative damage was tested by measuring TBARS, nitrites, catalase, GPx and SOD. Protein expression of IκBα, NFκB, iNOS, COX-2, PPARγ, Keap1, NQO1, Nrf2 and α7nAChR was also determined. Western blot and ELISA were used for measurements and a cluster analysis of inflammatory/oxidative biomarkers alterations was performed to investigate subgroups of patients with similar alterations and its relationship with clinical features of BPD.

RESULTS

69 patients were included in the study. Two inflammatory/nitrosative clusters of patients were found: Cluster 1 patients showed significantly higher levels of GPx, IκBα, keap1, NQO1, PPARγ, α7nAChR and Nrf2 than cluster 2 patients. These patients had significantly longer duration of illness, milder anxiety symptoms and lower prescription of antipsychotic drugs than cluster 2.

CONCLUSIONS

Two clusters of BPD patients according to the inflammatory/nitrosative profiles were identified. Cluster 1 had increased antioxidant and anti-inflammatory biomarkers and was characterised by greater chronicity of illness but less acute symptomatic severity.

Paternal age and specific neurological soft signs as reliable and valid neurobiological markers for the diagnosis of patients with schizophrenia

Advanced parental age at delivery and neurological soft signs (NSS) constitute risk factors for schizophrenia. The aim of the current study was to develop a neurobiological diagnostic index by combining them, and without the contribution of clinical symptomatology. The study sample included 133 patients suffering from schizophrenia according to DSM-IV-TR (77 males and 56 females; aged 33.55 ± 11.22 years old) and 122 normal controls (66 males and 56 females; aged 32.89 ± 9.91 years old). The assessment included the Neurological Evaluation Scale (NES), and a number of scales assessing the clinical symptoms and adverse effects. The statistical analysis included exploratory t-test, Pearson Correlation coefficient (R) and Discriminant Function Analysis (DFA). Exploratory t-tests and Pearson's R suggested that sex, parental age and NSS constitute independent components. On the basis of DFA results, the Psychotic Neurological Index was developed. At the cut-off PNI score of 8.5, sensitivity was equal to 94.74 and specificity to 93.44. The current is probably the first study to report on an easily obtainable diagnostic neurobiological marker with identifiable properties which is absolutely independent from the clinical manifestations and could serve in distinguishing between patients with schizophrenia and healthy controls with high efficacy.

Predictive protein markers for depression severity in mood disorders: A preliminary trans-diagnostic approach study

Depression is a common symptom of many mental disorders, especially major depressive disorder (MDD) and bipolar disorder (BD). Previous studies have reported that these diseases share common pathophysiological pathways; therefore, this study elucidated whether the plasma levels of protein markers related to common depressive symptoms differed between patients with BD and those with MDD. Plasma samples of 71 patients with mood disorders and clinical manifestations were analyzed in this study. After depleting the abundant proteins, liquid chromatography-tandem mass spectrometry and label-free quantification were performed. Five proteins, viz., cholesteryl ester transfer protein (CETP), apolipoprotein D (APOD), mannan-binding lectin serine protease 2 (MASP2), Ig lambda chain V-II region BO (IGLV2-8) and Ig kappa chain V-III region NG9 (IGKV3-20) were negatively associated with the total scores of the Hamilton depression rating scale (HAM-D), after adjusting for the covariates. CETP and APOD also showed significant negative correlations with the anhedonia/retardation and guilt/agitation scores of the HAM-D. Four proteins, namely, Ig kappa chain V-II region TEW (IGKC; IGKV2D-28), Ig lambda variable 5-45 (IGLV5-45), complement factor H (CFH) and attractin (ATRN), showed significant associations with anhedonia/retardation after adjusting for covariates. Proteins that significantly correlated with the symptoms could predict the remission state of depression (area under the curve [AUC], 0.83) and anhedonia/retardation (AUC, 0.80). Bioinformatics analysis revealed that complement activation, immune response, and lipid metabolism were significantly enriched pathways. Although our study design was cross-sectional and no controls were included, protein markers identified in this preliminary study will be further investigated in our subsequent longitudinal study.

An integrated machine learning framework for a discriminative analysis of schizophrenia using multi-biological data

Finding effective and objective biomarkers to inform the diagnosis of schizophrenia is of great importance yet remains challenging. Relatively little work has been conducted on multi-biological data for the diagnosis of schizophrenia. In this cross-sectional study, we extracted multiple features from three types of biological data, including gut microbiota data, blood data, and electroencephalogram data. Then, an integrated framework of machine learning consisting of five classifiers, three feature selection algorithms, and four cross validation methods was used to discriminate patients with schizophrenia from healthy controls. Our results show that the support vector machine classifier without feature selection using the input features of multi-biological data achieved the best performance, with an accuracy of 91.7% and an AUC of 96.5% (p < 0.05). These results indicate that multi-biological data showed better discriminative capacity for patients with schizophrenia than single biological data. The top 5% discriminative features selected from the optimal model include the gut microbiota features (Lactobacillus, Haemophilus, and Prevotella), the blood features (superoxide dismutase level, monocyte-lymphocyte ratio, and neutrophil count), and the electroencephalogram features (nodal local efficiency, nodal efficiency, and nodal shortest path length in the temporal and frontal-parietal brain areas). The proposed integrated framework may be helpful for understanding the pathophysiology of schizophrenia and developing biomarkers for schizophrenia using multi-biological data.

A pilot study indicating the dysregulation of the complement and coagulation cascades in treated schizophrenia and bipolar disorder patients

A better understanding of the proteome profile after bipolar disorder (BD) and schizophrenia (SCZ) treatment, besides monitoring disease progression, may assist on the development of novel therapeutic strategies with the ability to reduce or control possible side effects. In this pilot study, proteomics analysis employing nano liquid chromatography coupled to mass spectrometry (nLC-MS) and bioinformatic tools were applied to identify differentially abundant proteins in serum of treated BD and SCZ patients. In total, 10 BD patients, 10 SCZ patients, and 14 healthy controls (HC) were included in this study. 24 serum proteins were significantly altered (p < 0.05) in BD and SCZ treated patients and, considering log₂FC > 0.58, 8 proteins presented lower abundance in the BD group, while 7 proteins presented higher abundance and 2 lower abundance in SCZ group when compared against HC. Bioinformatics analysis based on these 24 proteins indicated two main altered pathways previously described in the literature; furthermore, it revealed that opposite abundances of the complement and coagulation cascades were the most significant biological processes involved in these pathologies. Moreover, we describe disease-related proteins and pathways associations suggesting the necessity of clinical follow-up improvement besides treatment, as a precaution or safety measure, along with the disease progression. Further biological validation and investigations are required to define whether there is a correlation between complement and coagulation cascade expression for BD and SCZ and cardiovascular diseases.

Immuno-inflammatory changes across phases of early psychosis: The impact of antipsychotic medication and stage of illness

INTRODUCTION

Research examining the role of inflammation in psychosis has produced inconsistent results. Variables that influence inflammation, including antipsychotic medication, are inconsistently controlled across studies and variation of inflammatory analytes across stages of psychosis may also influence findings. The purpose of this study was to assess for evidence of immuno-inflammatory dysregulation across the stages of early psychosis. We examined a immuno-inflammatory analytes in subjects at clinical high risk (CHR) for developing a psychotic disorder, antipsychotic-naïve (-n) and antipsychotic treated (-a) subjects in their first episode of psychosis (FEP), and healthy control (HC) subjects.

METHODS

A total of 11 subjects at CHR, 50 subjects within their FEP (40 FEP-n, 10 FEP-a), and 10 HC subjects were recruited from early psychosis programs in San Diego and Mexico City. Plasma was collected for biomarker assay.

RESULTS

Immuno-inflammatory analytes significantly differed between groups: Interferon-gamma (IFN-γ), Interleukin-10 (IL-10), Eotaxin-1, Interferon Gamma-Induced Protein-10 (IP-10), Monocyte Chemotactic Protein-1 (MCP-1), Macrophage-Derived Chemokine (MDC), Macrophage Inflammatory Protein-1 beta (MIP-1β), Thymus and Activation Regulated Chemokine (TARC), and Brain Derived Neurotropic Factor (BDNF). Post-hoc analyses revealed an overall pattern of higher levels of IL-10, MCP-1, MIP-1β, TARC, and BDNF in CHR as compared to FEP-a, FEP-n, and HC subjects.

CONCLUSIONS

Results reveal a profile of immuno-inflammatory dysregulation in early stages of psychosis prior to psychotic conversion and treatment with antipsychotic medication. The CHR phase of early psychosis may represent a period of increased immuno-inflammatory activation, but due to limited sample size, these results deserve replication in a well characterized early psychosis population.

The Discovery of Clinically Applicable Biomarkers for Bipolar Disorder: A Review of Candidate and Proteomic Approaches

Bipolar disorder (BD) is a severe psychiatric condition which affects innumerable people across the globe. The etiopathogenesis of BD is multi-faceted with genetic, environmental and psychosocial factors playing a role. Hitherto, the diagnosis and management of BD are purely on empirical grounds as we lack confirmed biomarkers for this condition. In this regard, hypothesis-driven investigations have been unable to identify clinically applicable biomarkers, steering the field towards newer technologies. Innovative, state-of-the-art techniques like multiplex immunoassays and mass spectrometry can potentially investigate the entire proteome. By detecting up or down regulated proteins, novel biomarkers are identified and new postulates about the etiopathogenesis of BD are specified. Hence, biological pathways are uncovered which are involved in the initiation and advancement of the disease and new therapeutic targets are identified. In this manuscript, the extant literature is thoroughly reviewed and the latest findings on candidate BD biomarkers are provided, followed by an overview of the proteomic approaches. It was found that due to the heterogeneous nature of BD no single biomarker is feasible, instead a panel of tests is more likely to be useful. With the application of latest technologies, it is expected that validated biomarkers will be discovered which will be useful as diagnostic tools and help in the delivery of individually tailored therapies to the patients.

Precision psychiatry with immunological and cognitive biomarkers: a multi-domain prediction for the diagnosis of bipolar disorder or schizophrenia using machine learning

Precision psychiatry is attracting increasing attention lately as a recognized priority. One of the goals of precision psychiatry is to develop tools capable of aiding a clinically informed psychiatric diagnosis objectively. Cognitive, inflammatory and immunological factors are altered in both bipolar disorder (BD) and schizophrenia (SZ), however, most of these alterations do not respect diagnostic boundaries from a phenomenological perspective and possess great variability in different individuals with the same phenotypic diagnosis and, consequently, none so far has proven to have the ability of reliably aiding in the differential diagnosis of BD and SZ. We developed a probabilistic multi-domain data integration model consisting of immune and inflammatory biomarkers in peripheral blood and cognitive biomarkers using machine learning to predict diagnosis of BD and SZ. A total of 416 participants, being 323, 372, and 279 subjects for blood, cognition and combined biomarkers analysis, respectively. Our multi-domain model performances for the BD vs. control (sensitivity 80% and specificity 71%) and for the SZ vs. control (sensitivity 84% and specificity 81%) pairs were high in general, however, our multi-domain model had only moderate performance for the differential diagnosis of BD and SZ (sensitivity 71% and specificity 73%). In conclusion, our results show that the diagnosis of BD and of SZ, and that the differential diagnosis of BD and SZ can be predicted with possible clinical utility by a computational machine learning algorithm employing blood and cognitive biomarkers, and that their integration in a multi-domain outperforms algorithms based in only one domain. Independent studies are needed to validate these findings.

Inflammatory and antioxidant pathway dysfunction in borderline personality disorder

INTRODUCTION

This study investigates the alteration of the inflammatory/oxidative pathway in patients with borderline personality disorder (BPD) and its relationship with clinical features of the disorder.

METHODS

49 BPD patients and 33 healthy control subjects were studied. Plasma levels of TBARS, nitrites, and the antioxidant enzymes CAT, GPx and SOD were measured. In addition, peripheral blood mononuclear cells were obtained to investigate levels of intracellular components of the inflammatory/oxidative pathway including the IκBα, NFκB, iNOS, COX2, Keap1, NQO1, and HO1. Western Blot and ELISA were used to measure protein expression. Patients were assessed for different clinical dimensions of BPD with scales for depression, anxiety, impulsivity and functioning.

RESULTS

A significant decrease of IκBα levels and a significant increase of inflammatory factors, including NFκB, COX2 and iNOS levels were found in patients. On the other hand, a significant decrease was observed for all antioxidant enzymes in patients with BPD, except for HO1. The inflammatory factor NFκB showed a significant positive correlation with impulsivity scores.

CONCLUSIONS

Patients with BPD presented an increased activation of several components of the inflammatory pathways, as well as an inhibition of the antioxidant path. These alterations appear partially correlated with the impulsivity scores in these patients.

The difference in serum proteomes in schizophrenia and bipolar disorder

BACKGROUND

Purpose of study is revealing significant differences in serum proteomes in schizophrenia and bipolar disorder (BD).

RESULTS

Quantitative mass-spectrometry based proteomic analysis was used to quantify proteins in the blood serum samples after the depletion of six major blood proteins. Comparison of proteome profiles of different groups revealed 27 proteins being specific for schizophrenia, and 18 - for BD. Protein set in schizophrenia was mostly associated with immune response, cell communication, cell growth and maintenance, protein metabolism and regulation of nucleic acid metabolism. Protein set in BD was mostly associated with immune response, regulating transport processes across cell membrane and cell communication, development of neurons and oligodendrocytes and cell growth. Concentrations of ankyrin repeat domain-containing protein 12 (ANKRD12) and cadherin 5 in serum samples were determined by ELISA. Significant difference between three groups was revealed in ANKRD12 concentration (p = 0.02), with maximum elevation of ANKRD12 concentration (median level) in schizophrenia followed by BD. Cadherin 5 concentration differed significantly (p = 0.035) between schizophrenic patients with prevailing positive symptoms (4.78 [2.71, 7.12] ng/ml) and those with prevailing negative symptoms (1.86 [0.001, 4.11] ng/ml).

CONCLUSIONS

Our results are presumably useful for discovering the new pathways involved in endogenous psychotic disorders.

hsa_circRNA_104597: a novel potential diagnostic and therapeutic biomarker for schizophrenia

Aim: To assess whether expression of circular RNAs (circRNAs) in peripheral blood mononuclear cells can serve as a biomarker for diagnosis and/or therapeutic response in people living with schizophrenia (SZ). Materials & methods: Differentially expressed circRNAs were screened via microarray in nine individuals living with SZ and nine healthy controls, then quantified using real-time quantitative reverse transcription PCR in SZ (n = 102) and healthy control (n = 103) groups. CircRNAs were re-assessed twice in 30 randomly selected individuals living with SZ after 4- and 8-week antipsychotic treatments. Results: Five circRNAs were differentially expressed between groups. Only hsa_circRNA_104597, which was downregulated in the SZ group, was significantly upregulated after 8-week treatment. Conclusion: Dysregulation of hsa_circRNA_104597 may serve as a novel potential diagnostic and therapeutic biomarker for SZ.

Proteomics for blood biomarker exploration of severe mental illness: pitfalls of the past and potential for the future

Recent improvements in high-throughput proteomic approaches are likely to constitute an essential advance in biomarker discovery, holding promise for improved personalized care and drug development. These methodologies have been applied to study multivariate protein patterns and provide valuable data of peripheral tissues. To highlight findings of the last decade for three of the most common psychiatric disorders, namely schizophrenia (SZ), bipolar disorder (BD), and major depressive disorder (MDD), we queried PubMed. Here we delve into the findings from thirty studies, which used proteomics and multiplex immunoassay approaches for peripheral blood biomarker exploration. In an explorative approach, we ran enrichment analyses in peripheral blood according to these results and ascertained the overlap between proteomic findings and genetic loci identified in genome-wide association studies (GWAS). The studies we appraised demonstrate that proteomics for psychiatric research has been heterogeneous in aims and methods and limited by insufficient sample sizes, poorly defined case definitions, methodological inhomogeneity, and confounding results constraining the conclusions that can be extracted from them. Here, we discuss possibilities for overcoming methodological challenges for the implementation of proteomic signatures in psychiatric diagnosis and offer an outlook for future investigations. To fulfill the promise of proteomics in mental disease diagnostics, future research will need large, well-defined cohorts in combination with state-of-the-art technologies.

Elevated heat shock proteins in bipolar disorder patients with hypothalamic pituitary adrenal axis dysfunction

BACKGROUND

Heat shock proteins (HSP) might be useful as biomarkers for bipolar disorder (BD) which would be clinically valuable since no reliable biomarker for BD has so far been identified. The purpose of this study was to assess the heat shock proteins CPN10, CPN60, and CPN70 as potential biomarkers of BD.

METHODS

The study included 100 BD patients recruited from a hospital during 2012 and 2013. The study also included 94 healthy controls. Among the BD patients, 33 had abnormal hypothalamic-pituitary-adrenal (HPA) axis activity. Blood samples were obtained from the patients and controls. The chemiluminescence method, mass spectrometry, and flow cytometry were used for analysis.

RESULTS

The BD patients compared with the controls had a significantly lower level of CPN10 and significantly higher levels of CPN60 and CPN70. The BD patients with abnormal HPA axis activity had a significantly lower level of CPN60 compared with the normal HPA axis activity group of BD patients. The CPN60 level significantly inversely correlated with adrenocorticotropic hormone (ACTH) level in patients with bipolar depression and in patients with bipolar hypomania, and CPN70 significantly correlated with ACTH level in patients with bipolar depression and hypomania.

CONCLUSIONS

Our findings suggest that the heat shock proteins CPN10, CPN60, and CPN70 might have potential as biomarkers for BD and CPN60 blood level might distinguish patients with abnormal HPA axis activity from those with normal HPA axis activity.

Developing tomorrow's antipsychotics: the need for a more personalised approach

There has been little pharmacological advance in the treatment of schizophrenia since the introduction of chlorpromazine in the 1950s. This may be set to change as recent advances in molecular biology offer the prospect of a better understanding of the pathophysiology of the disorder and allow investigation of the complex interplay of genetic and environmental risk factors. In this review I discuss future approaches to antipsychotic drug development, highlighting the need to better define symptom areas and develop drugs based on an understanding of neurobiological mechanisms. The development of biomarkers has the potential in future to improve differential diagnosis and help predict response to treatment. These developments herald the possibility of a more integrated drug discovery approach and the subsequent provision of more stratified healthcare, and hopefully significant improvements in patient care and improved long-term outcomes.

On the transdiagnostic nature of peripheral biomarkers in major psychiatric disorders: A systematic review

The search for biomarkers has been a leading endeavor in biological psychiatry. To analyze its evolution over the years, we performed a systematic review to evaluate (a) the most studied peripheral molecular markers in major psychiatric disorders, (b) the main features of studies proposing them as biomarkers and (c) whether their patterns of variation are similar across disorders. Of the six molecules most commonly studied as plasmatic markers of schizophrenia, major depressive disorder or bipolar disorder, five (BDNF, TNF-alpha, IL-6, C-reactive protein and cortisol) were the same across diagnoses. An analysis of this literature showed that, while 66% of studies compared patients and controls, only 34% were longitudinal, and only 10% presented a measure of diagnostic or prognostic efficacy. Meta-analyses showed variation in the levels of these molecules to be robust across studies, but similar among disorders, suggesting them to reflect transdiagnostic systemic consequences of psychiatric illness. Based on this, we discuss how current publication practices have led to research fragmentation across diagnoses, and suggest approaches to face this issue.

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.

Theranostic Biomarkers for Schizophrenia

Schizophrenia is a highly heritable, chronic, severe, disabling neurodevelopmental brain disorder with a heterogeneous genetic and neurobiological background, which is still poorly understood. To allow better diagnostic procedures and therapeutic strategies in schizophrenia patients, use of easy accessible biomarkers is suggested. The most frequently used biomarkers in schizophrenia are those associated with the neuroimmune and neuroendocrine system, metabolism, different neurotransmitter systems and neurotrophic factors. However, there are still no validated and reliable biomarkers in clinical use for schizophrenia. This review will address potential biomarkers in schizophrenia. It will discuss biomarkers in schizophrenia and propose the use of specific blood-based panels that will include a set of markers associated with immune processes, metabolic disorders, and neuroendocrine/neurotrophin/neurotransmitter alterations. The combination of different markers, or complex multi-marker panels, might help in the discrimination of patients with different underlying pathologies and in the better classification of the more homogenous groups. Therefore, the development of the diagnostic, prognostic and theranostic biomarkers is an urgent and an unmet need in psychiatry, with the aim of improving diagnosis, therapy monitoring, prediction of treatment outcome and focus on the personal medicine approach in order to improve the quality of life in patients with schizophrenia and decrease health costs worldwide.

Depletion of Highly Abundant Proteins of the Human Blood Plasma: Applications in Proteomics Studies of Psychiatric Disorders

Psychiatric disorders are complex diseases involving exogenous and endogenous factors. Biomarkers for diagnosis or prediction of successful treatment are not existent. In addition, the molecular basis of these diseases is still poorly understood. Blood plasma represents the most complex proteome as it contains subproteomes from several body tissues. However, the high abundance of some little proteins can obscure the analysis of hundreds of low abundance proteins, which are potential biomarkers. Therefore, removal of these high abundance proteins is pivotal in any proteomic study of plasma. Here, we present a method of depleting these proteins using immunoaffinity liquid chromatography.

The DSM5/RDoC debate on the future of mental health research: implication for studies on human stress and presentation of the signature bank

In 2008, the National Institute of Mental Health (NIMH) announced that in the next few decades, it will be essential to study the various biological, psychological and social "signatures" of mental disorders. Along with this new "signature" approach to mental health disorders, modifications of DSM were introduced. One major modification consisted of incorporating a dimensional approach to mental disorders, which involved analyzing, using a transnosological approach, various factors that are commonly observed across different types of mental disorders. Although this new methodology led to interesting discussions of the DSM5 working groups, it has not been incorporated in the last version of the DSM5. Consequently, the NIMH launched the "Research Domain Criteria" (RDoC) framework in order to provide new ways of classifying mental illnesses based on dimensions of observable behavioral and neurobiological measures. The NIMH emphasizes that it is important to consider the benefits of dimensional measures from the perspective of psychopathology and environmental influences, and it is also important to build these dimensions on neurobiological data. The goal of this paper is to present the perspectives of DSM5 and RDoC to the science of mental health disorders and the impact of this debate on the future of human stress research. The second goal is to present the "Signature Bank" developed by the Institut Universitaire en Santé Mentale de Montréal (IUSMM) that has been developed in line with a dimensional and transnosological approach to mental illness.

Neuroimmune biomarkers in schizophrenia

Schizophrenia is a heterogeneous psychiatric disorder with a broad spectrum of clinical and biological manifestations. Due to the lack of objective tests, the accurate diagnosis and selection of effective treatments for schizophrenia remains challenging. Numerous technologies have been employed in search of schizophrenia biomarkers. These studies have suggested that neuroinflammatory processes may play a role in schizophrenia pathogenesis, at least in a subgroup of patients. The evidence indicates alterations in both pro- and anti-inflammatory molecules in the central nervous system, which have also been found in peripheral tissues and may correlate with schizophrenia symptoms. In line with these findings, certain immunomodulatory interventions have shown beneficial effects on psychotic symptoms in schizophrenia patients, in particular those with distinct immune signatures. In this review, we evaluate these findings and their potential for more targeted drug interventions and the development of companion diagnostics. Although currently no validated markers exist for schizophrenia patient stratification or the prediction of treatment efficacy, we propose that utilisation of inflammatory markers for diagnostic and theranostic purposes may lead to novel therapeutic approaches and deliver more effective care for schizophrenia patients.

Proteomics Research in Schizophrenia

Despite intense scientific efforts, the neuropathology and pathophysiology of schizophrenia are poorly understood. Proteomic studies, by testing large numbers of proteins for associations with disease, may contribute to the understanding of the molecular mechanisms of schizophrenia. They may also indicate the types and locations of cells most likely to harbor pathological alterations. Investigations using proteomic approaches have already provided much information on quantitative and qualitative protein patterns in postmortem brain tissue, peripheral tissues and body fluids. Different proteomic technologies such as 2-D PAGE, 2-D DIGE, SELDI-TOF, shotgun proteomics with label-based (ICAT), and label-free (MS^E) quantification have been applied to the study of schizophrenia for the past 15 years. This review summarizes the results, mostly from brain but also from other tissues and bodily fluids, of proteomics studies in schizophrenia. Emphasis is given to proteomics platforms, varying sources of material, proposed candidate biomarkers emerging from comparative proteomics studies, and the specificity of the putative markers in terms of other mental illnesses. We also compare proteins altered in schizophrenia with reports of protein or mRNA sequences that are relatively enriched in specific cell types. While proteomic studies of schizophrenia find abnormalities in the expression of many proteins that are not cell type-specific, there appears to be a disproportionate representation of proteins whose synthesis and localization are highly enriched in one or more brain cell type compared with other types of brain cells. Two of the three proteins most commonly altered in schizophrenia are aldolase C and glial fibrillary acidic protein, astrocytic proteins with entirely different functions, but the studies are approximately evenly divided with regard to the direction of the differences and the concordance or discordance between the two proteins. Alterations of common myelin-associated proteins were also frequently observed, and in four studies that identified alterations in at least two, all differences were downwards in schizophrenia, consistent with earlier studies examining RNA or targeting myelin-associated proteins.

Serum biomarkers predictive of depressive episodes in panic disorder

Panic disorder with or without comorbid agoraphobia (PD/PDA) has been linked to an increased risk to develop subsequent depressive episodes, yet the underlying pathophysiology of these disorders remains poorly understood. We aimed to identify a biomarker panel predictive for the development of a depressive disorder (major depressive disorder and/or dysthymia) within a 2-year-follow-up period. Blood serum concentrations of 165 analytes were evaluated in 120 PD/PDA patients without depressive disorder baseline diagnosis (6-month-recency) in the Netherlands Study of Depression and Anxiety (NESDA). We assessed the predictive performance of serum biomarkers, clinical, and self-report variables using receiver operating characteristics curves (ROC) and the area under the ROC curve (AUC). False-discovery-rate corrected logistic regression model selection of serum analytes and covariates identified an optimal predictive panel comprised of tetranectin and creatine kinase MB along with patient gender and scores from the Inventory of Depressive Symptomatology (IDS) rating scale. Combined, an AUC of 0.87 was reached for identifying the PD/PDA patients who developed a depressive disorder within 2 years (n = 44). The addition of biomarkers represented a significant (p = 0.010) improvement over using gender and IDS alone as predictors (AUC = 0.78). For the first time, we report on a combination of biological serum markers, clinical variables and self-report inventories that can detect PD/PDA patients at increased risk of developing subsequent depressive disorders with good predictive performance in a naturalistic cohort design. After an independent validation our proposed biomarkers could prove useful in the detection of at-risk PD/PDA patients, allowing for early therapeutic interventions and improving clinical outcome.

Multianalyte markers of schizophrenia and bipolar disorder: A preliminary study

Previous studies have identified altered molecular profiles in blood samples from individuals with schizophrenia and with bipolar disorder using multianalyte immunoassay platforms but there has been little comparison of the two groups in the same investigation. A total of 337 participants including 146 with schizophrenia, 79 with bipolar disorder, and 112 non-psychiatric controls had a blood sample drawn from which 166 analytes were measured. The initial dataset was split; classification models were developed in a training dataset and their performance evaluated in a test dataset. Principal component analysis was used to generate factor scores that were then compared between the groups. In a training set, a total of 7 independent factors were generated using 29 markers that were both normally distributed and significantly associated with diagnosis. Many of these analytes are components of the immune system and involved in the inflammatory response to infectious agents and foreign antigens. Two of the seven principal component scores discriminated between individuals with schizophrenia and with bipolar disorder; additional factors distinguished individuals with either schizophrenia or bipolar disorder from control individuals, while two factors were not significantly different between any of the diagnostic groups. In a test dataset, the schizophrenia vs. control Receiver Operating Curve (ROC) analysis shows an overall accuracy of 77% for schizophrenia vs. bipolar disorder, 84% for schizophrenia vs. controls, and 72% for bipolar disorder vs.

CONTROLS

An increased understanding of the role of altered pathways in serious psychiatric disorders may lead to novel methods for disease diagnosis and therapy.

Discovery of serum biomarkers predicting development of a subsequent depressive episode in social anxiety disorder

Although social anxiety disorder (SAD) is strongly associated with the subsequent development of a depressive disorder (major depressive disorder or dysthymia), no underlying biological risk factors are known. We aimed to identify biomarkers which predict depressive episodes in SAD patients over a 2-year follow-up period. One hundred sixty-five multiplexed immunoassay analytes were investigated in blood serum of 143 SAD patients without co-morbid depressive disorders, recruited within the Netherlands Study of Depression and Anxiety (NESDA). Predictive performance of identified biomarkers, clinical variables and self-report inventories was assessed using receiver operating characteristics curves (ROC) and represented by the area under the ROC curve (AUC). Stepwise logistic regression resulted in the selection of four serum analytes (AXL receptor tyrosine kinase, vascular cell adhesion molecule 1, vitronectin, collagen IV) and four additional variables (Inventory of Depressive Symptomatology, Beck Anxiety Inventory somatic subscale, depressive disorder lifetime diagnosis, BMI) as optimal set of patient parameters. When combined, an AUC of 0.86 was achieved for the identification of SAD individuals who later developed a depressive disorder. Throughout our analyses, biomarkers yielded superior discriminative performance compared to clinical variables and self-report inventories alone. We report the discovery of a serum marker panel with good predictive performance to identify SAD individuals prone to develop subsequent depressive episodes in a naturalistic cohort design. Furthermore, we emphasise the importance to combine biological markers, clinical variables and self-report inventories for disease course predictions in psychiatry. Following replication in independent cohorts, validated biomarkers could help to identify SAD patients at risk of developing a depressive disorder, thus facilitating early intervention.

What Have Mass Spectrometry-Based Proteomics and Metabolomics (Not) Taught Us about Psychiatric Disorders?

Understanding the molecular causes and finding appropriate therapies for psychiatric disorders are challenging tasks for research; -omics technologies are used to elucidate the molecular mechanisms underlying brain dysfunction in a hypothesis-free manner. In this review, we will focus on mass spectrometry-based proteomics and metabolomics and address how these approaches have contributed to our understanding of psychiatric disorders. Specifically, we will discuss what we have learned from mass spectrometry-based proteomics and metabolomics studies in rodent models and human cohorts, outline current limitations and discuss the potential of these methods for future applications in psychiatry.

Can proteomics-based diagnostics aid clinical psychiatry?

Despite major advances in infrastructure and instrumentation, proteomics-driven translational applications have not yet yielded the results that the scientific community has envisaged. In this viewpoint, the perspective of proteomics-based diagnostics in the field of clinical psychiatry is explored. The challenges that proteomics faces in the context of translational approaches are outlined and directions toward a successful clinical implementation are provided. Additional challenges that psychiatric disorders pose for clinical proteomics are highlighted and the potential of proteomics-based, blood tests for psychiatric disorders is being assessed. Proteomics offers a valuable toolkit for clinical translation that needs to be handled in a pragmatic manner and with realistic expectations.

The proteome of schizophrenia

On observing schizophrenia from a clinical point of view up to its molecular basis, one may conclude that this is likely to be one of the most complex human disorders to be characterized in all aspects. Such complexity is the reflex of an intricate combination of genetic and environmental components that influence brain functions since pre-natal neurodevelopment, passing by brain maturation, up to the onset of disease and disease establishment. The perfect function of tissues, organs, systems, and finally the organism depends heavily on the proper functioning of cells. Several lines of evidence, including genetics, genomics, transcriptomics, neuropathology, and pharmacology, have supported the idea that dysfunctional cells are causative to schizophrenia. Together with the above-mentioned techniques, proteomics have been contributing to understanding the biochemical basis of schizophrenia at the cellular and tissue level through the identification of differentially expressed proteins and consequently their biochemical pathways, mostly in the brain tissue but also in other cells. In addition, mass spectrometry-based proteomics have identified and precisely quantified proteins that may serve as biomarker candidates to prognosis, diagnosis, and medication monitoring in peripheral tissue. Here, we review all data produced by proteomic investigation in the last 5 years using tissue and/or cells from schizophrenic patients, focusing on postmortem brain tissue and peripheral blood serum and plasma. This information has provided integrated pictures of the biochemical systems involved in the pathobiology, and has suggested potential biomarkers, and warrant potential targets to alternative treatment therapies to schizophrenia.

Towards a psychosis risk blood diagnostic for persons experiencing high-risk symptoms: preliminary results from the NAPLS project

INTRODUCTION

A barrier to preventative treatments for psychosis is the absence of accurate identification of persons at highest risk. A blood test that could substantially increase diagnostic accuracy would enhance development of psychosis prevention interventions.

METHODS

The North American Prodrome Longitudinal Study project is a multisite endeavor that aims to better understand predictors and mechanisms for the development of psychosis. In this study, we measured expression of plasma analytes reflecting inflammation, oxidative stress, hormones, and metabolism. A "greedy algorithm" selected analytes that best distinguished persons with clinical high-risk symptoms who developed psychosis (CHR-P; n = 32) from unaffected comparison (UC) subjects (n = 35) and from those who did not develop psychosis during a 2-year follow-up (CHR-NP; n = 40).

RESULTS

The classifier included 15 analytes (selected from 117), with an area under the receiver operating curve for CHR-P vs UC of 0.91 and CHR-P vs CHR-NP of 0.88. Randomly scrambled group membership followed by reconstructions of the entire classifier method yielded consistently weak classifiers, indicating that the true classifier is highly unlikely to be a chance occurrence. Such randomization methods robustly imply the assays contain consistent information distinguishing the groups which was not obscured by the data normalization method and was revealed by classifier construction. These results support the hypothesis that inflammation, oxidative stress, and dysregulation of hypothalamic-pituitary axes may be prominent in the earliest stages of psychosis.

CONCLUSION

If confirmed in other groups of persons at elevated risk of psychosis, a multiplex blood assay has the potential for high clinical utility.

Description and utilization of the United States department of defense serum repository: a review of published studies, 1985-2012

Specimens in the United States Department of Defense (DoD) Serum Repository have accumulated in frozen storage since 1985 when the DoD began universal screening for human immunodeficiency virus. Use of the stored serum for health research has been carefully controlled, but the resulting publications have never been systematically identified or described. The Armed Forces Health Surveillance Center (AFHSC) information systems and open (online) sites were used as data sources. Through 2012, the repository contained 54,542,658 serum specimens, of which 228,610 (0.42%) have been accessed for any purpose. Between 2001 (the first year that comprehensive, digital records were available) and 2012, 65.2% of all approved requests for serum were for healthcare or public health investigations, but greater than 99% of all shipped samples were for research. Using two different methods – a structure search of PubMed and an exhaustive online search based on records from AFHSC – we identified 76 articles published between October 1988 and March 2013 that covered a multitude of infectious diseases, injuries, environmental exposures and mental health conditions through analysis of antibodies, biological metabolic, signaling and regulatory substances, Vitamin D, organochlorines, dioxin, omega-3-fatty acid, and portions of human deoxyribonucleic acid. Despite its operational and scientific value, it appears that the DoD Serum Repository has been underutilized. Changes to policy and increased capacity for specimen processing could increase use of the repository without risking privacy or the availability of specimens for the healthcare of individual service members in the future.

Applications of blood-based protein biomarker strategies in the study of psychiatric disorders

Major psychiatric disorders such as schizophrenia, major depressive and bipolar disorders are severe, chronic and debilitating, and are associated with high disease burden and healthcare costs. Currently, diagnoses of these disorders rely on interview-based assessments of subjective self-reported symptoms. Early diagnosis is difficult, misdiagnosis is a frequent occurrence and there are no objective tests that aid in the prediction of individual responses to treatment. Consequently, validated biomarkers are urgently needed to help address these unmet clinical needs. Historically, psychiatric disorders are viewed as brain disorders and consequently only a few researchers have as yet evaluated systemic changes in psychiatric patients. However, promising research has begun to challenge this concept and there is an increasing awareness that disease-related changes can be traced in the peripheral system which may even be involved in the precipitation of disease onset and course. Converging evidence from molecular profiling analysis of blood serum/plasma have revealed robust molecular changes in psychiatric patients, suggesting that these disorders may be detectable in other systems of the body such as the circulating blood. In this review, we discuss the current clinical needs in psychiatry, highlight the importance of biomarkers in the field, and review a representative selection of biomarker studies to highlight opportunities for the implementation of personalized medicine approaches in the field of psychiatry. It is anticipated that the implementation of validated biomarker tests will not only improve the diagnosis and more effective treatment of psychiatric patients, but also improve prognosis and disease outcome.

Advancing biomarker research: utilizing 'Big Data' approaches for the characterization and prevention of bipolar disorder

OBJECTIVE

To provide a strategic framework for the prevention of bipolar disorder (BD) that incorporates a 'Big Data' approach to risk assessment for BD.

METHODS

Computerized databases (e.g., Pubmed, PsychInfo, and MedlinePlus) were used to access English-language articles published between 1966 and 2012 with the search terms bipolar disorder, prodrome, 'Big Data', and biomarkers cross-referenced with genomics/genetics, transcriptomics, proteomics, metabolomics, inflammation, oxidative stress, neurotrophic factors, cytokines, cognition, neurocognition, and neuroimaging. Papers were selected from the initial search if the primary outcome(s) of interest was (were) categorized in any of the following domains: (i) 'omics' (e.g., genomics), (ii) molecular, (iii) neuroimaging, and (iv) neurocognitive.

RESULTS

The current strategic approach to identifying individuals at risk for BD, with an emphasis on phenotypic information and family history, has insufficient predictive validity and is clinically inadequate. The heterogeneous clinical presentation of BD, as well as its pathoetiological complexity, suggests that it is unlikely that a single biomarker (or an exclusive biomarker approach) will sufficiently augment currently inadequate phenotypic-centric prediction models. We propose a 'Big Data'- bioinformatics approach that integrates vast and complex phenotypic, anamnestic, behavioral, family, and personal 'omics' profiling. Bioinformatic processing approaches, utilizing cloud- and grid-enabled computing, are now capable of analyzing data on the order of tera-, peta-, and exabytes, providing hitherto unheard of opportunities to fundamentally revolutionize how psychiatric disorders are predicted, prevented, and treated. High-throughput networks dedicated to research on, and the treatment of, BD, integrating both adult and younger populations, will be essential to sufficiently enroll adequate samples of individuals across the neurodevelopmental trajectory in studies to enable the characterization and prevention of this heterogeneous disorder.

CONCLUSIONS

Advances in bioinformatics using a 'Big Data' approach provide an opportunity for novel insights regarding the pathoetiology of BD. The coordinated integration of research centers, inclusive of mixed-age populations, is a promising strategic direction for advancing this line of neuropsychiatric research.

Search for peripheral biomarkers in patients affected by acutely psychotic bipolar disorder: a proteomic approach

Data on neurobiological mechanisms underlying mood disorders are elusive; the aetiology of such states is multifactorial, including genetic predisposition and environmental factors. Diagnosis is currently being made only on an interview-based methodology. Biological markers, which could improve the current classification, and in perspective, stratify patients on a biological basis into more homogeneous clinically distinct subgroups, are highly needed. We describe here a comparative proteomic analysis of peripheral lymphocytes from patients affected by acute psychotic bipolar disorder (PBD) (n = 15), major depressive episode (MDE) with no personal or family history of psychosis (n = 11), and a group of demographically matched healthy controls (HC) (n = 15). All patients were evaluated by means of Structured Clinical Interview for DSM-IV-Patient version (SCID-I-P), Positive and Negative Symptoms Scale (PANSS), Young Mania Rating Scale (YMRS), Hamilton Anxiety Rating Scale (HAM-A) and Hamilton Depression Rating Scale (HAM-D-17) questionnaires. Blood lymphocytes were obtained by gradient separation, and 2-DE was carried out on protein extracts. Significant differences in protein patterns among the three groups were observed. Thirty-six protein spots were found to be differentially expressed in patients compared to controls, which collapsed into 25 different proteins after mass spectrometry identification. Twenty-one of these proteins failed to discriminate between PBD and MDE, suggesting common signatures for these disorders. Nevertheless, after the western blot validation only two of the remaining proteins, namely LIM and SH3 domain protein1, and short-chain specific acyl-CoA dehydrogenase mitochondrial protein, resulted in being significantly upregulated in PBD samples suggesting additional mechanisms that could be associated with the psychotic features of bipolar disorder.

Biomarkers of pediatric brain tumors

Background and Need for Novel Biomarkers: Brain tumors are the leading cause of death by solid tumors in children. Although improvements have been made in their radiological detection and treatment, our capacity to promptly diagnose pediatric brain tumors in their early stages remains limited. This contrasts several other cancers where serum biomarkers such as cancer antigen (CA) 19-9 and CA 125 facilitate early diagnosis and treatment.

AIM

The aim of this article is to review the latest literature and highlight biomarkers which may be of clinical use in the common types of primary pediatric brain tumor.

METHODS

A PubMed search was performed to identify studies reporting biomarkers in the bodily fluids of pediatric patients with brain tumors. Details regarding the sample type [serum, cerebrospinal fluid (CSF), or urine], biomarkers analyzed, methodology, tumor type, and statistical significance were recorded.

RESULTS

A total of 12 manuscripts reporting 19 biomarkers in 367 patients vs. 397 controls were identified in the literature. Of the 19 biomarkers identified, 12 were isolated from CSF, 2 from serum, 3 from urine, and 2 from multiple bodily fluids. All but one study reported statistically significant differences in biomarker expression between patient and control groups.

CONCLUSION

This review identifies a panel of novel biomarkers for pediatric brain tumors. It provides a platform for the further studies necessary to validate these biomarkers and, in addition, highlights several techniques through which new biomarkers can be discovered.

Activation of the cholinergic anti-inflammatory system in peripheral blood mononuclear cells from patients with borderline personality disorder

A case-control study including patients (n = 20) with Borderline Personality Disorder (BPD) and healthy controls (n = 33) was carried out. To avoid interferences of other clinical conditions on biological findings, patients were free of current major depressive episodes or substance dependence disorders, and had no life history of schizophrenia, bipolar or neuropsychiatric disorders. Patients were free of medication for at least two weeks at the time of the study. Studies carried out in peripheral mononuclear blood cells and plasma evidence a systemic inflammatory condition in unstable-impulsive BPD patients. Specifically, a significant increase in some intracellular components of two main pro-inflammatory pathways such as iNOS and COX-2, as well as an increase in the plasma levels of the inflammatory cytokine IL1β. Interestingly, patients have an increase in the protein expression of the anti-inflammatory subtype of nicotinic receptor α7nAChR. This finding may reflect a possible mechanism trying to maintain intracellular inflammation pathways under control. All together, these results describe an imbalanced, pro-inflammatory and oxidant phenotype in BPD patients independent of plasma cotinine levels. Although more scientific evidence is needed, the determination of multiple components of pro- and anti-inflammatory cellular pathways have interesting potential as biological markers for BPD and other generalized impulsive syndromes, specially data obtained with α7nAChR and its lack of correlation with plasma levels of nicotine metabolites. Their pharmacological modulation with receptor modulators can be a promising therapeutic target to take into account in mental health conditions associated with inflammatory or oxido/nitrosative consequences. Also, identifying at-risk individuals would be of importance for early detection and intervention in adolescent subjects before they present severe behavioural problems.

Blood test for schizophrenia

Schizophrenia is a complex disease with mostly unknown aetiology. Rapid development of molecular profiling technologies in recent years has facilitated identification of physiological processes associated with schizophrenia. In particular, changes have been found in the blood of schizophrenia patients, and this offers an accessible and efficient alternative to brain samples for research purposes. Here, we review the metabolic, immune and hormonal imbalances characterised in subgroups of schizophrenia patients and discuss potential applications in differential diagnosis, prognosis and early intervention. We also describe development of the first validated biological blood test for diagnosis of schizophrenia, and the challenges involved after introduction of this into clinical practice. Moreover, we discuss possibilities for further research on biomarkers for diagnostic applications in schizophrenia. Promising research avenues include extension to functional analysis of blood cells and applications in prediction of drug response and novel drug discovery.