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Accumulating evidence suggests that neuroinflammation is involved in bipolar disorder (BD) pathogenesis. The tumor necrosis factor-alpha (TNF-α) antagonist infliximab was recently reported to improve depressive symptoms in a subpopulation of individuals with BD and history of childhood maltreatment. To explore the mechanistic mediators of infliximab's effects, we investigated its engagement with biomarkers of cellular response to inflammation derived from plasma extracellular vesicles enriched for neuronal origin (NEVs). We hypothesized that infliximab, compared to placebo, would decrease TNF-α receptors (TNFRs) and nuclear factor-kappa B (NF-κB) pathway signaling biomarkers, and that history of childhood abuse would moderate infliximab's effects. We immunocaptured NEVs from plasma samples collected at baseline and at weeks 2, 6, and 12 (endpoint) from 55 participants of this clinical trial and measured NEV biomarkers using immunoassays. A subset of participants ( n = 27) also underwent whole-brain magnetic resonance imaging at baseline and endpoint. Childhood physical abuse moderated treatment by time interactions for TNFR1 (χ 2 = 9.275, p = 0.026), NF-κB (χ 2 = 13.825, p = 0.003), and inhibitor of NF-κB (IκBα) (χ 2 = 7.990, p = 0.046), indicating that higher levels of physical abuse were associated with larger biomarker decreases over time. Moreover, the antidepressant response to infliximab was moderated by TNFR1 (χ 2 = 7.997, p = 0.046). In infliximab-treated participants, reductions in TNFR1 levels were associated with improvement of depressive symptoms, an effect not detected in the placebo group. Conversely, reductions in TNFR1 levels were associated with increased global cortical thickness in infliximab- (r = -0.581, p = 0.029), but not placebo-treated, patients (r = 0.196, p = 0.501). In conclusion, we report that NEVs revealed that infliximab engaged the TNFR/NF-κB neuro-inflammatory pathway in individuals with BD, in a childhood trauma-dependent manner, which was associated with clinical response and brain structural changes.

Major Depressive Disorder (MDD) and bipolar disorder (BD) are still under recognized and undertreated, especially in primary care settings. One of the challenges faced by clinicians is the remarkable inter-individual variability among patients with these conditions. In addition, each patient with MDD and BD experiences a unique pattern of longitudinal changes across time, i.e., intra-individual variability can also be problematic. The immense amount of data generated and collected through the use of smartphones or personal devices offers an opportunity to obtain continuous and reliable information on each individual's behavior, a less burdensome way to capture both intra and inter-individual variability over time. Digital phenotypes (DP) are a promising strategy to be integrated with other "Omics" platforms for prediction of relevant outcomes in mood disorders, including but not restricted to, relapse, recurrence, cognitive decline and functional impairment. Despite existing limitations and some skepticism, digital phenotyping represents a field in great expansion and might eventually constitute a feasible strategy in biomarkers research for mood disorders., (Copyright © 2019 Elsevier Ltd. All rights reserved.)

Objectives: In this review, the authors discuss an overview of lipidomics followed by in-depth discussion of its application to the study of human diseases, including extraction methods of lipids, analytical techniques and clinical research in neuropsychiatric disorders., Methods: Lipidomics is a lipid-targeted metabolomics approach aiming at the comprehensive analysis of lipids in biological systems. Recent technological advancements in mass spectrometry and chromatography have greatly enhanced the development and applications of metabolic profiling of diverse lipids in complex biological samples., Results: An effective evaluation of the clinical course of diseases requires the application of very precise diagnostic and assessment approaches as early as possible. In order to achieve this, "omics" strategies offer new opportunities for biomarker identification and/or discovery in complex diseases and may provide pathological pathways understanding for diseases beyond traditional methodologies., Conclusions: This review highlights the importance of lipidomics for the future perspectives as a tool for biomarker identification and discovery and its clinical application.

Using 1 H NMR-based metabolomics in association to chemometrics analysis, we analyzed here the metabolic differences between schizophrenia patients (SCZ) compared to healthy controls (HCs). HCs and SCZ patients underwent clinical interview using the Structured Clinical Interview for DSM Disorders (SCID). SCZ patients were further assessed by Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale, Global Assessment of Functioning Scale (GAF), and Clinical Global Impressions Scale (CGI). Using the principal component analysis (PCA) and supervised partial least-squares discriminate analysis (PLS-DA) in obtained NMR data, a clear group separation between HCs and SCZ patients was achieved. Interestingly, all metabolite compounds identified as exclusively present in the SCZ group, except for the gamma-aminobutyric acid (GABA), were never previously associated with mental disorders. Although the initial perception of an absence of obvious biological link among the different key molecules exclusively observed in each group, and no identification of any specific pathway yet, the present work represents an important contribution for the identification of potential biomarkers to inform diagnosis, as it was possible to completely separate the affected SCZ patients from HCs, with no outliers or exceptions. In addition, the data presented here reinforced the role of the modulation of glycolysis pathway and the loss of GABA interneuron/hyperglutamate hypothesis in SCZ., (Copyright © 2016 Elsevier B.V. All rights reserved.)

Lipidomics is a lipid-targeted metabolomics approach aiming at comprehensive analysis of lipids in biological systems. Recent technological progresses in mass spectrometry, nuclear magnetic resonance spectroscopy, and chromatography have significantly enhanced the developments and applications of metabolic profiling of lipids in more complex biological samples. As many diseases reveal a notable change in lipid profiles compared with that of healthy people, lipidomics have also been broadly introduced to scientific research on diseases. Exploration of lipid biochemistry by lipidomics approach will not only provide insights into specific roles of lipid molecular species in health and disease, but it will also support the identification of potential biomarkers for establishing preventive or therapeutic approaches for human health. This chapter aims to illustrate how lipidomics can contribute for understanding the biological mechanisms inherent to schizophrenia and why lipids are relevant biomarkers of schizophrenia. The application of lipidomics in clinical studies has the potential to provide new insights into lipid profiling and pathophysiological mechanisms underlying schizophrenia. The future perspectives of lipidomics in mental disorders are also discussed herein.

Background: Studies investigating inflammatory markers in post-traumatic stress disorder (PTSD) have yielded mixed results. The aim of our study was to compare concentrations of inflammatory markers in patients with PTSD compared with healthy controls., Methods: We did a meta-analysis and meta-regression of studies comparing inflammatory markers between patients with PTSD and healthy controls by searching PubMed, Embase, Scopus, Web of Science, and PsycINFO for articles published between Jan 1, 1960, and April 7, 2015. From eligible studies (ie, cross-sectional studies or baseline data from longitudinal studies of peripheral blood cytokine concentrations that compared adults with PTSD with healthy controls), we extracted outcomes of interest, such as mean and SD of peripheral blood cytokines, the time of day blood was collected, whether the study allowed patients with comorbid major depressive disorder in the PTSD group, whether patients were medication free, and severity of PTSD symptoms. We undertook meta-analyses whenever values of inflammatory markers were available in two or more studies. A random-effects model with restricted maximum-likelihood estimator was used to synthesise the effect size (assessed by standardised mean difference [SMD]) across studies., Findings: 8057 abstracts were identified and 20 studies were included. Interleukin 6 (SMD 0.88; p=0.0003), interleukin 1β (SMD 1.42; p=0.045), and interferon γ (SMD 0.49; p=0.002) levels were higher in the PTSD group than in healthy controls. Subgroup meta-analysis of patients who were not given medication showed higher tumour necrosis factor α (TNFα; SMD 0.69, 95% CI 0.35-1.02; p<0.0001) in the PTSD group than the control group in addition to the aforementioned cytokines. TNFα (SMD 1.32, 0.13-2.50; p=0.003), interleukin 1β (SMD 2.35, 0.01-4.68; p=0.048), and interleukin 6 (SMD 1.75, 0.97-2.53; p<0.0001) levels remained increased in the PTSD group in a subgroup meta-analysis of studies that excluded comorbid major depressive disorder. Illness duration was positively associated with interleukin 1β levels (b=0.33, p<0.0001) and severity with interleukin 6 (b=0.02, p=0.042). A model composed of several variables-presence of comorbid major depressive disorder, use of psychotropic medications, assay used, and time of day blood was collected-explained the large amount of heterogeneity between interleukin 1β, interleukin 6, and C-reactive protein studies. Egger's linear regression test revealed a potential publication bias for interleukin 1β. Additionally, for most inflammatory markers, study heterogeneity was reported to be high (I(2)>75%)., Interpretation: PTSD is associated with increased interleukin 6, interleukin 1β, TNFα, and interferon γ levels. This information might be useful for consideration of chronic low-grade inflammation as a potential target or biomarker in PTSD treatment. Use of psychotropic medication and presence of comorbid major depressive disorder were important moderators that might explain the inconsistency between results of previous studies. Our search strategy used a range of databases and we made exhaustive effort to acquire data by contacting the authors. Notably, high levels of between-study heterogeneity were recorded for most cytokine variables measured in our analysis. However, meta-regression analysis could explain a large amount of this heterogeneity., Funding: None., (Copyright © 2015 Elsevier Ltd. All rights reserved.)

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., (© 2013 John Wiley & Sons A/S. Published by John Wiley & Sons Ltd.)

Emergence of depressive symptoms in schizophrenia results in a deteriorating course and poor prognosis. Schizophrenia and depressive disorder are both associated with low levels of brain-derived neurotrophic factor (BDNF) and with a longstanding low grade inflammatory state. The objective of this study is to analyze the relationship between these serum biomarkers and depressive and psychotic symptoms in schizophrenic patients. Thirty-nine individuals diagnosed with schizophrenia or schizoaffective disorder by Diagnostic and Statistical Manual of Mental Disorders (DSM-IV), assessed by Structured Clinical Interview for DSM-IV (SCID), were included. Interviews were conducted with The Positive and Negative Syndrome Scale (PANSS) and The Calgary Depression Scale for Schizophrenia (CDSS). Blood samples were collected for determination of BDNF, IL-1beta, IL-6, IL-8, IL-10, IL-12 and TNF-alpha measurements. Positive correlations between BDNF and CDSS and between IL-1beta and severity in PANSS scores were found. BDNF levels were not correlated with any cytokine or with PANSS scores. The results of this study suggest that depressive and psychotic symptoms may be associated with different profiles of biomarkers in the association between schizophrenia and depression., (Copyright © 2011 Elsevier Ireland Ltd. All rights reserved.)

Recent data show that biomarkers differ in early and late-stage bipolar disorder (BD). Here we propose a model of staging for bipolar disorder that emphasizes the potential use of biomarkers for differentiating early and late-stage BD patients in the inter-episodic period. The proposed model includes a Latent phase: patients at "ultra-high-risk" for developing BD, characterized by a family history of BD, temperament traits, mood, and anxiety symptoms as well as genetic vulnerability for developing the disorder; Stage I: patients who return to their baseline level of functioning when mood episodes resolve; Stage II: biomarkers and functioning impairment are related to comorbidities or rapid-cycling presentations; Stage III: persistent cognitive and functioning impairment in the inter-episode period as well as changes in biomarkers; and Stage IV: same findings as in Stage III associated with extreme cognitive and functioning impairment, to the point that patients are unable to live autonomously. Empirical testing will determine the ability of the present model to inform patients and clinicians about both prognosis and response to treatment.

We identified biologically relevant moderators of response to tumor necrosis factor (TNF)-α inhibitor, infliximab, among 60 individuals with bipolar depression. Data were derived from a 12-week, randomized, placebo-controlled clinical trial secondarily evaluating the efficacy of infliximab on a measure of anhedonia (i.e., Snaith-Hamilton Pleasure Scale). Three inflammatory biotypes were derived from peripheral cytokine measurements using an iterative, machine learning-based approach. Infliximab-randomized participants classified as biotype 3 exhibited lower baseline concentrations of pro- and anti-inflammatory cytokines and soluble TNF receptor-1 and reported greater pro-hedonic improvements, relative to those classified as biotype 1 or 2. Pretreatment biotypes also moderated changes in neuroinflammatory substrates relevant to infliximab's hypothesized mechanism of action. Neuronal origin-enriched extracellular vesicle (NEV) protein concentrations were reduced to two factors using principal axis factoring: phosphorylated nuclear factorκB (p-NFκB), Fas-associated death domain (p-FADD), and IκB kinase (p-IKKα/β) and TNF receptor-1 (TNFR1) comprised factor "NEV1," whereas phosphorylated insulin receptor substrate-1 (p-IRS1), p38 mitogen-activated protein kinase (p-p38), and c-Jun N-terminal kinase (p-JNK) constituted "NEV2". Among infliximab-randomized subjects classified as biotype 3, NEV1 scores were decreased at weeks 2 and 6 and increased at week 12, relative to baseline, and NEV2 scores increased over time. Decreases in NEV1 scores and increases in NEV2 scores were associated with greater reductions in anhedonic symptoms in our classification and regression tree model (r2 = 0.22, RMSE = 0.08). Our findings provide preliminary evidence supporting the hypothesis that the pro-hedonic effects of infliximab require modulation of multiple TNF-α signaling pathways, including NF-κB, IRS1, and MAPK.

Nuclear distribution element like-1 (Ndel1) is a cytosolic oligopeptidase, which was suggested as a potential biomarker of aberrant neurodevelopment and early stage of schizophrenia (SCZ). The involvement of Ndel1 in neurite outgrowth, neuronal migration and neurodevelopment was demonstrated. Moreover, Ndel1 cleaves neuropeptides, including the endogenous antipsychotic peptide neurotensin, and lower Ndel1 activity was reported in SCZ patients compared with healthy controls (HCs). Changes in brain-derived neurotrophic factor (BDNF) and inflammatory cytokines levels were also implicated in SCZ. This preliminary study aimed to investigate the interactions between these immune and neurodevelopmental/neurotrophic biomarkers, namely BDNF and the recently identified SCZ biomarker Ndel1. We observed lower Ndel1 activity and IL-4 levels, and higher BDNF levels, in plasma of SCZ (N = 23) compared with HCs (N = 29). Interestingly, significant correlation between Ndel1 activity and IL-4 levels was observed in SCZ, while no correlation with any other evaluated interleukins (namely IL-2, IL-8, IL-10 and IL-17A) or BDNF levels was noticed. Although this hypothesis needs to be further explored for a better understanding of the mechanisms by which these altered pathways are associated to each other in SCZ, we suggest that Ndel1 and the inflammatory marker IL-4 are directly correlated. [ABSTRACT FROM AUTHOR]

Objectives: Diagnosis and management of bipolar disorder (BD) are limited by the absence of available biomarkers. Allostatic load (AL) represents the strain that stress, including the effects of acute phases and inter‐episode chronic mood instability, exerts on interconnected biological systems. This study aimed to operationalize an AL index and explore whether it could be relevant to better characterize BD patients with and without emotional hyper‐reactivity particularly those at higher risk of immune‐cardiometabolic dysregulation and functional impairment. Methods: Levels of biomarkers of chronic inflammation (hsCRP and albumin), cardiovascular (systolic/diastolic blood pressure) and metabolic functions (fasting glucose, glycosylated hemoglobin, total cholesterol, LDL, HDL, and triglycerides) were measured in 1072 adult BD outpatients. Patients were classified in two groups (with/without emotional hyper‐reactivity) assessed by the Multidimensional Assessment of Thymic States scale. An Allostatic Load Index for BD (BALLI), comprising six biomarkers, was constructed using data‐driven biomarker selection. Results: BALLI showed 81.1% accuracy with good sensitivity (81%) and specificity (81.2%) for characterizing BD patients presenting emotional hyper‐reactivity, elevated risk of inflammation (increased hsCRP, hypoalbuminemia) and cardiometabolic disturbances (hypertension, hyperglycemia, and hypertriglyceridemia). Patients classified by the BALLI as presenting emotional hyper‐reactivity had significantly lower global and cognitive functioning than those without emotional hyper‐reactivity (P <.0001). Conclusions: A multidimensional approach based on a simple AL score (eg, BALLI) and dimensions of behavior (eg, emotional hyper‐reactivity) alongside mood is clinically relevant. AL index could be a useful tool to detect multisystemic physiological dysregulations in BD patients with/without emotional hyper‐reactivity particularly those at higher risk of immune‐cardiometabolic disturbances and functional impairment. [ABSTRACT FROM AUTHOR]

Objectives: Objective measures integrated with clinical symptoms may improve early prevention and detection of schizophrenia. Herein we aim to evaluate potential water-soluble metabolic biomarkers in schizophrenia. Methods: We recruited adults with schizophrenia (n = 113) who had not received pharmacological treatment for at least 1 month prior to enrollment and 111 age- and sex-matched healthy subjects from Weifang, Shandong province, China. All serum samples were analysed using liquid chromatography-tandem mass spectrometry coupled with a hydrophilic interaction liquid chromatography column. Results: Eleven metabolites, namely carnitines (oleoylcarnitine, l-palmitoylcarnitine, 9-decenoylcarnitine and 2-trans,4-cis-decadienoylcarnitine), polar lipids (lysophosphatidylcholine (LPC)(P-16:0), LPC (16:0), LPC (15:0) and LPC(14:0)), amino acids (taurine and l-arginine), and organic acid (2,5-dichloro-4-oxohex-2-enedioate), separated the patients and healthy controls. Compared with healthy controls, taurine, l-palmitoylcarnitine and oleoylcarnitine levels were higher, whereas the remaining eight metabolites were lower in patients with schizophrenia. A combination of four metabolites, i.e., oleoylcarnitine, 9-decenoylcarnitine, LPC (15:0) and LPC (14:0), provided the most robust between-group separation. Conclusions: This study appears to distinguish between groups of patients and controls, which should be considered as a contribution to putative potential biomarkers. The water-soluble metabolites were determined to be significantly different between the groups in the current study, and were primarily related to cellular bioenergetics, notably oxidative stress. [ABSTRACT FROM AUTHOR]

Background: The objective of this study was to identify molecular alterations in the human blood serum related to bipolar disorder, using nuclear magnetic resonance (NMR) spectroscopy and chemometrics. Methods: Metabolomic profiling, employing H-NMR, H-NMR T-edited, and 2D-NMR spectroscopy and chemometrics of human blood serum samples from patients with bipolar disorder ( n = 26) compared with healthy volunteers ( n = 50) was performed. Results: The investigated groups presented distinct metabolic profiles, in which the main differential metabolites found in the serum sample of bipolar disorder patients compared with those from controls were lipids, lipid metabolism-related molecules (choline, myo-inositol), and some amino acids ( N-acetyl- l-phenyl alanine, N-acetyl- l-aspartyl- l-glutamic acid, l-glutamine). In addition, amygdalin, α-ketoglutaric acid, and lipoamide, among other compounds, were also present or were significantly altered in the serum of bipolar disorder patients. The data presented herein suggest that some of these metabolites differentially distributed between the groups studied may be directly related to the bipolar disorder pathophysiology. Conclusions: The strategy employed here showed significant potential for exploring pathophysiological features and molecular pathways involved in bipolar disorder. Thus, our findings may contribute to pave the way for future studies aiming at identifying important potential biomarkers for bipolar disorder diagnosis or progression follow-up. [ABSTRACT FROM AUTHOR]

Replicated evidence indicates that perinatal complications are associated with increased markers of oxidative stress and with mental health problems in children. However, there are fewer reports on the impact of perinatal complications in later phases of development. We aimed to investigate the estimated effects of perinatal complications on levels of lipid peroxidation and on psychopathology in children and adolescents. The study is part of the High Risk Cohort Study for Psychiatric Disorders; the population was composed by 554 students, 6-14 years of age. Serum levels of malondialdehyde, a product of lipid peroxidation, were measured by the TBARS method. A household interview with parents and caregivers was conducted and included inquiries about perinatal history, the Child Behavior Checklist (CBCL), and parent's evaluation, using the Mini International Psychiatric Interview (MINI). We created a cumulative risk index, conceptualized as each individual's cumulative exposure to perinatal complications. Results indicate that perinatal complications were associated with higher levels of TBARS. After adjusting for age, gender, socio-economic status, CBCL total problems score, parental psychopathology, and childhood maltreatment, children exposed to 3 or more perinatal complications had an 26.9% (95% CI 9.9%, 46.6%) increase in TBARS levels, relative to the unexposed group. Exploratory mediation analysis indicated that TBARS levels partially mediated the association between perinatal complications and externalizing problems. In conclusion, an adverse intrauterine and/or early life environment, as proxied by the cumulative exposure to perinatal complications, was independently associated with higher levels of lipid peroxidation in children and adolescents. [ABSTRACT FROM AUTHOR]

Lipidomics or lipid-profiling is a lipid-targeted metabolomics approach aiming at comprehensive analysis of lipids in biological systems. The extent of information in the genomic and proteomic fields is greater than that in the lipidomics field, because of the complex nature of lipids and the limitations of tools for analysis. Modern technological advances in mass spectrometry and chromatography have greatly improved the developments and applications of metabolic profiling of diverse lipids in complex biological samples. Lipidomics will not only provide insights into the specific functions of lipid species in health and disease, but will also identify potential biomarkers for establishing preventive or therapeutic programs for human diseases. In this review, emphasis is given to the current advances in lipidomics technologies and their applications in disease biomarker discovery, and its clinical application. The application of lipidomics in clinical studies may provide new insights into lipid profiling and pathophysiological mechanisms. We also discuss the lipidomics for the future perspectives and their potential problems. [ABSTRACT FROM AUTHOR]

Objectives The neurotrophin brain-derived neurotrophic factor ( BDNF) has been proposed as a potential biomarker in bipolar disorder ( BD). However, current evidence is limited and results have been highly heterogeneous. This study aimed to assess the moderating effect of impaired glucose metabolism ( IGM) on plasma levels of BDNF in individuals with BD, and on the relationship between BDNF and variables of illness course. Methods We measured and compared the plasma levels of BDNF in individuals with BD (n=57) and healthy controls (n=26). IGM was operationalized as pre-diabetes or type 2 diabetes mellitus. Information related to current and past psychiatric/medical history, as well as prescription of pharmacological treatments was also captured. Results Individuals with BD had lower levels of BDNF, relative to healthy controls, after adjustment for age, gender, current medications, smoking, alcohol use, and IGM ( P=.046). There was no effect of IGM ( P=.860) and no interaction between BD diagnosis and IGM ( P=.893). Peripheral BDNF levels were positively correlated with lifetime depressive episodes ( P<.001), psychiatric hospitalizations ( P=.001) and suicide attempts ( P=.021). IGM moderated the association between BDNF and the number of previous mood episodes ( P<.001), wherein there was a positive correlation in euglycemic participants and a negative correlation in individuals with IGM. Conclusions BD is independently associated with lower levels of BDNF; IGM may modify the relationship between BDNF and BD course, suggesting an interactive effect of BDNF with metabolic status on illness progression. [ABSTRACT FROM AUTHOR]

One of the major concerns of modern society is to identify putative biomarkers that serve as a valuable early diagnostic tool to identify a subset of patients with increased risk to develop neuropsychiatric disorders. Biomarker identification in neuropsychiatric disorders is proposed to offer a number of important benefits to patient well-being, including prediction of forthcoming disease, diagnostic precision, and a level of disease description that would guide treatment choice. Nowadays, the metabolomics approach has unlocked new possibilities in diagnostics of devastating disorders like neuropsychiatric disorders. Metabolomics-based technologies have the potential to map early biochemical changes in disease and hence provide an opportunity to develop predictive biomarkers that can be used as indicators of pathological abnormalities prior to development of clinical symptoms of neuropsychiatric disorders. This review highlights different -omics strategies for biomarker discovery in neuropsychiatric disorders. We also highlight initial outcomes from metabolomics studies in psychiatric disorders such as schizophrenia, bipolar disorder, and addictive disorders. This review will also present issues and challenges regarding the implementation of the metabolomics approach as a routine diagnostic tool in the clinical laboratory in context with neuropsychiatric disorders. [ABSTRACT FROM AUTHOR]

Objectives. Recent schizophrenia (SCZ) research aims to establish biomarkers with high predictive value for the diagnosis, severity of illness or treatment resistance. SCZ is accompanied by activated immune-inflammatory pathways, including increased levels of cytokines and chemokines, but few studies tried to identify predictive properties of such measures. Methods. We included 54 medicated SCZ patients and 118 healthy controls and examined 15 cytokines and chemokines. Possible associations between these immune-inflammatory biomarkers and the diagnosis of SCZ, severity of illness and treatment resistance were investigated. Results. SCZ is associated with a specific cytokine – chemokine profile, i.e., increased CCL11, MIP-1α, sTNF-R1 and sTNF-R2 levels, and decreased levels of IP-10, TNF-α, IL-2 and IL-4. The combination of five biomarkers (sTNF-R1, sTNF-R2, CCL11, IP-10, IL-4) may predict the diagnosis of SCZ with a sensitivity of 70.0% and a specificity of 89.4%. There was a weak association between the negative symptoms and biomarkers, i.e., IL-2 (inversely) and CCL11 (positively). Patients with treatment resistance showed increased levels of sTNF-R1, sTNF-R2 and MCP-1. Conclusions. The findings of this study reinforce that SCZ is associated with a pro-inflammatory profile and suggest that some immune mediators may be used as reliable biomarkers for the diagnosis of SCZ and treatment resistance. [ABSTRACT FROM AUTHOR]

Abstract: Background: The high prevalence, recurrence rate, chronicity, and illness burden in bipolar disorder (BD) are well documented. Moreover, insufficient response with conventional pharmacological and manual-based psychosocial interventions, as well as evidence of illness progression and acceleration, invite the need for early detection and primary prevention. Methods: Herein we comprehensively review extant studies reporting on a bipolar prodrome. The overarching aim is to propose a predictive algorithm (i.e. prediction of BD in at-risk populations) integrating genetic (i.e. family history), environmental (e.g. childhood maltreatment) and biological markers (i.e. BDNF, inflammatory and oxidative stress markers). Computerized databases i.e. Pubmed, PsychInfo, Cochrane Library and Scielo were searched using the followed terms: bipolar disorder cross-referenced with prodromal, preclinical, at risk mental states, clinical high risk, ultra high risk, biomarkers, brain-derived neurotrophic factor, inflammation, cytokines, oxidative stress, prediction and predictive model. Results: Available evidence indicates that a prodrome to bipolar disorder exists. Commonly encountered features preceding the onset of a manic episode are affective lability, irritability, anger, depression, anxiety, substance use disorders, sleep disorders, as well as disturbances in attention and cognition. Non-specificity and insufficient sensitivity have hampered the development of an adequate prediction algorithm. Limitations: Limitations include biases associated with retrospective studies, poor characterization of clinical high risk, inadequacy of prospective studies regarding sample selection and absence of specificity of risk states. Conclusion: We propose a hypothetical prediction algorithm that is combinatorial in approach that attempts to integrate family history, early adversity, and selected biomarkers. [Copyright &y& Elsevier]

Schizophrenia (SCZ) and bipolar disorder (BD) are severe mental disorders that pose important challenges for diagnosis by sharing common symptoms, such as delusions and hallucinations. The underlying pathophysiology of both disorders remains largely unknown, and the identification of biomarkers with potential to support diagnosis is highly desirable. In a previous study, we successfully discriminated SCZ and BD patients from healthy control (HC) individuals by employing proton magnetic resonance spectroscopy (1H-NMR). In this study, 1H-NMR data treated by chemometrics, principal component analysis (PCA) and supervised partial least-squares discriminant analysis (PLS-DA), provided the identification of metabolites present only in BD (as for instance the 2,3-diphospho-D-glyceric acid, N -acetyl aspartyl-glutamic acid, monoethyl malonate) or only in SCZ (as isovaleryl carnitine, pantothenate, mannitol, glycine, GABA). This may represent a set of potential biomarkers to support the diagnosis of these mental disorders, enabling the discrimination between SCZ and BD, and among these psychiatric patients and HC (as 6-hydroxydopamine was present in BD and SCZ but not in HC). The presence or absence of these metabolites in blood allowed the categorization of 182 independent subjects into one of these three groups. In addition, the presented data suggest disturbances in metabolic pathways in SCZ and BD, which may provide new and important information to support the elucidation and/or new insights into the neurobiology underlying these mental disorders. Image 1 [ABSTRACT FROM AUTHOR]

The present study aimed at investigating possible alterations in the serum lipid profile of euthymic patients with bipolar disorder type I (BD) compared to healthy controls (HC). Thirty-five individuals from both genders were recruited, with 14 diagnosed and treated as BD patients (BD group) and 21 healthy subjects (HC group). Clinical assessment was based on the Structured Clinical Interview for DSM-IV Axis I Disorders (SCID-I), Young Mania Rating Scale (YMRS), and 17-items of Hamilton Depression Rating Scale (HDRS-17) data, which were used to confirm diagnosis, to verify psychiatric comorbidities, and to estimate the severity of manic and depressive symptoms. Ultra-high performance liquid chromatography (UHPLC) coupled to high resolution mass spectrometry (HRMS) was applied to analyze the lipids extracted from all serum samples from both studied groups. In this pioneer and exploratory study, we observed different serum lipid profiles for BD and HC groups, especially regarding glycerophospholipid, glycerolipid, and sphingolipid distribution. Multivariate statistical analyses indicated that 121 lipids were significantly different between BD and HC. Phosphatidylinositols were identified as the most altered lipids in BD patient sera. The results of this preliminary study reinforce the role of lipid abnormalities in BD and offer additional methodological possibilities for investigation in the field. [ABSTRACT FROM AUTHOR]

Using 1H NMR-based metabolomics in association to chemometrics analysis, we analyzed here the metabolic differences between schizophrenia patients (SCZ) compared to healthy controls (HCs). HCs and SCZ patients underwent clinical interview using the Structured Clinical Interview for DSM Disorders (SCID). SCZ patients were further assessed by Positive and Negative Syndrome Scale (PANSS), Calgary Depression Scale, Global Assessment of Functioning Scale (GAF), and Clinical Global Impressions Scale (CGI). Using the principal component analysis (PCA) and supervised partial least-squares discriminate analysis (PLS-DA) in obtained NMR data, a clear group separation between HCs and SCZ patients was achieved. Interestingly, all metabolite compounds identified as exclusively present in the SCZ group, except for the gamma-aminobutyric acid (GABA), were never previously associated with mental disorders. Although the initial perception of an absence of obvious biological link among the different key molecules exclusively observed in each group, and no identification of any specific pathway yet, the present work represents an important contribution for the identification of potential biomarkers to inform diagnosis, as it was possible to completely separate the affected SCZ patients from HCs, with no outliers or exceptions. In addition, the data presented here reinforced the role of the modulation of glycolysis pathway and the loss of GABA interneuron/hyperglutamate hypothesis in SCZ. [ABSTRACT FROM AUTHOR]

Backgroound Schizophrenia is accompanied by increased lipid peroxidation and nitric oxide (NO) levels and by lowered antioxidant levels. However, the effect of antipsychotic agents on these processes remains unclear. The objective of this study is to determine the oxidative stress (OS) status in drug naïve first-episode psychotic patients (FEP) compared to healthy controls and to delineate the effects of risperidone on these biomarkers. Methods 51 drug naive FEP patients and 61 healthy controls were enrolled; FEP patients were reassessed 11 weeks after risperidone treatment. Three OS biomarkers, i.e. lipid hydroperoxides – LOOH, NO metabolites – NOx, and advanced oxidation protein products – AOPP, and two antioxidant biomarkers, i.e. total radical-trapping antioxidant parameter – TRAP, and paraoxonase 1 – PON1, were measured. The Positive and Negative Syndrome Scale (PANSS) and the Calgary Depression Scale for Schizophrenia (CDSS) were used to measure symptoms severity. Results Significantly lower PON1 activity and increased TRAP values were found in FEP patients. There were no significant associations between any of the OS/antioxidant biomarkers and clinical data. Risperidone treatment significantly increased PON1 activity and decreased LOOH levels. These effects of risperidone were not significantly associated with the clinical response and risperidone dosage. Discussion Changes in antioxidant profile, but not in lipid or protein oxidation or increased NO production, were found in drug-naive FEP. Risperidone may have antioxidant effects by lowering lipid peroxidation and increasing the antioxidant defenses against lipid peroxidation related to PON1. None of the biomarkers predicted treatment outcome. [ABSTRACT FROM AUTHOR]

Highlights: [•] Pathophysiological changes observed in BD converge on a model of premature aging. [•] Individuals with BD present high rates of age related medical illnesses. [•] Dysregulation in immune system and neurotrophins are present in both conditions. [•] Recognition of BD as an accelerated aging disease opens a new avenue of investigation. [Copyright &y& Elsevier]

Abstract: Objective: To investigate possible differences in peripheral levels of chemokines, BDNF and oxidative markers between patients with Schizophrenia (SZ) and matched healthy controls, and investigate the correlation of these biomarkers with cognitive performance. Methods: Thirty individuals with SZ and 27 healthy controls were included and the following plasmatic biomarkers' levels were determined according to manufacturers' instructions: BDNF, TBARS, protein carbonyl content (PCC) and the chemokines CXCL-10/IP-10, CXCL-8/IL-8, CCL-11, CCL-24/Eotaxin-2, CCL-2/MCP-1, CCL-3/MIP-1. Selected neuropsychological tasks were administered to assess verbal learning (Hopkins Verbal Learning Test), verbal fluency (FAS test), working memory (Visual Working Memory Task, Keep Track Task, Letter Memory Task), set shifting (Plus–minus task, Number–letter task), inhibition (Computerized Stroop Task, Semantic Generation Task) and complex executive function tasks (Tower of London and the shortened version of the WCST-64). Results: Compared with the healthy control group, individuals with SZ presented significantly higher levels of BDNF and the chemokine CCL-11, and lower levels of TBARS and the chemokine CXCL-10/IP-10. When we examined only the SZ group, BDNF levels were positively correlated with semantic generation tasks. Working memory ability was negatively correlated with PCC. Regarding chemokines, CCL-11 was negatively correlated to performance in working memory test, and positively correlated with cognitive flexibility task. CXCL-8/IL-8 was positively correlated with verbal fluency. CCL-24/Eotaxin-2 was positively correlated with semantic generation ability and letter memory task. Conclusions: Our results indicate that cognitive performance in SZ is associated with mediators of neuroplasticity that can be measured peripherally. [Copyright &y& Elsevier]

Abstract: Background: Schizophrenia (SZ) has been associated with an imbalance in the inflammatory cytokine TNF-α. The objectives of this study were to compare TNF-α and its soluble receptors'' serum levels in individuals with SZ with the levels found in a group of healthy volunteers and to investigate the possible association between these biomarkers and the dimensions and severity of symptoms, clinical outcomes and response to treatment in patients with SZ. Methods: Fifty-four chronically medicated SZ outpatients and 118 healthy controls were included in the study. TNF-α levels were measured by Cytometric Bead Assay (CBA), and serum levels of soluble tumor necrosis factor receptor 1 (sTNFR1) and soluble tumor necrosis factor receptor 2 (sTNFR2) were measured by ELISA. Results: sTNFR1 and sTNFR2 were significantly elevated in patients with SZ as compared to the healthy control group. In the group of individuals with SZ, the levels of both types of soluble TNF receptors showed a negative correlation with global functioning. sTNFR1 levels were higher in the treatment-resistant patients as compared to the non-treatment-resistant patients and the controls. sTNFR1 levels were also heightened in patients with SZ and concomitant depression. Conclusion: Our findings reinforce that SZ is associated with an inflammatory profile and suggest that sTNFR1 is a marker of a treatment-resistance and severe clinical course in SZ. [Copyright &y& Elsevier]