Schizophrenia: A review of potential biomarkers

Cross-cohort replicable resting-state functional connectivity in predicting symptoms and cognition of schizophrenia

Schizophrenia (SZ) is a debilitating mental illness characterized by adolescence or early adulthood onset of psychosis, positive and negative symptoms, as well as cognitive impairments. Despite a plethora of studies leveraging functional connectivity (FC) from functional magnetic resonance imaging (fMRI) to predict symptoms and cognitive impairments of SZ, the findings have exhibited great heterogeneity. We aimed to identify congruous and replicable connectivity patterns capable of predicting positive and negative symptoms as well as cognitive impairments in SZ. Predictable functional connections (FCs) were identified by employing an individualized prediction model, whose replicability was further evaluated across three independent cohorts (BSNIP, SZ = 174; COBRE, SZ = 100; FBIRN, SZ = 161). Across cohorts, we observed that altered FCs in frontal-temporal-cingulate-thalamic network were replicable in prediction of positive symptoms, while sensorimotor network was predictive of negative symptoms. Temporal-parahippocampal network was consistently identified to be associated with reduced cognitive function. These replicable 23 FCs effectively distinguished SZ from healthy controls (HC) across three cohorts (82.7%, 90.2%, and 86.1%). Furthermore, models built using these replicable FCs showed comparable accuracies to those built using the whole-brain features in predicting symptoms/cognition of SZ across the three cohorts (r = .17-.33, p < .05). Overall, our findings provide new insights into the neural underpinnings of SZ symptoms/cognition and offer potential targets for further research and possible clinical interventions.

Striatal Functional Hypoconnectivity in Patients With Schizophrenia Suffering From Negative Symptoms, Longitudinal Findings

BACKGROUND

Negative symptoms in schizophrenia (SZ), such as apathy and diminished expression, have limited treatments and significantly impact daily life. Our study focuses on the functional division of the striatum: limbic-motivation and reward, associative-cognition, and sensorimotor-sensory and motor processing, aiming to identify potential biomarkers for negative symptoms.

STUDY DESIGN

This longitudinal, 2-center resting-state-fMRI (rsfMRI) study examines striatal seeds-to-whole-brain functional connectivity. We examined connectivity aberrations in patients with schizophrenia (PwSZ), focusing on stable group differences across 2-time points using intra-class-correlation and associated these with negative symptoms and measures of cognition. Additionally, in PwSZ, we used negative symptoms to predict striatal connectivity aberrations at the baseline and used the striatal aberration to predict symptoms 9 months later.

STUDY RESULTS

A total of 143 participants (77 PwSZ, 66 controls) from 2 centers (Berlin/Geneva) participated. We found sensorimotor-striatum and associative-striatum hypoconnectivity. We identified 4 stable hypoconnectivity findings over 3 months, revealing striatal-fronto-parietal-cerebellar hypoconnectivity in PwSZ. From those findings, we found hypoconnectivity in the bilateral associative striatum with the bilateral paracingulate-gyrus and the anterior cingulate cortex in PwSZ. Additionally, hypoconnectivity between the associative striatum and the superior frontal gyrus was associated with lower cognition scores in PwSZ, and weaker sensorimotor striatum connectivity with the superior parietal lobule correlated negatively with diminished expression and could predict symptom severity 9 months later.

CONCLUSIONS

Importantly, patterns of weaker sensorimotor striatum and superior parietal lobule connectivity fulfilled the biomarker criteria: clinical significance, reflecting underlying pathophysiology, and stability across time and centers.

Potential mechanisms of action of resveratrol in prevention and therapy for mental disorders

There is a growing body of evidence about the potential of diet and nutrients to improve the population's mental health and the treatment of psychiatric disorders. Some studies have suggested that resveratrol has therapeutic properties in mental disorders, such as major depressive disorder, bipolar disorder, Alzheimer's disease, and autism. In addition, resveratrol is known to induce several benefits modulated by multiple synergistic pathways, which control oxidative stress, inflammation, and cell death. This review collects the currently available data from animal and human studies and discusses the potential mechanisms of action of resveratrol in prevention and therapy for psychiatric disorders.

Lipid Biomarker Research in Bipolar Disorder: A Scoping Review of Trends, Challenges, and Future Directions

Bipolar disorder (BD) is a disabling disorder with heterogeneous symptom profiles and trajectories. Like many other neuropsychiatric disorders, clinical decision making related to diagnoses and choice of treatment is based on clinical assessments alone, and risk prediction for treatment success or resistance at an individual level remains sparse. An enormous effort to add biological markers to this risk prediction is ongoing. The role of lipids in normal brain functioning is well established, and several hypotheses about the role of lipids in the pathogenesis of neuropsychiatric disorders, including BD, have been made. The frequent comorbidity between neuropsychiatric disorders and cardiovascular disease, the genetic overlap of risk genes for severe mental disorders and genes involved in lipid regulation, and the lipid-altering effects of antipsychotics and mood stabilizers indicate that lipids could hold promise as biomarkers for neuropsychiatric disorders, including BD. To date, reviews of lipid biomarkers in schizophrenia and major depression have noted caveats for future investigations, while reviews of lipid biomarker research in BD is missing. In the current scoping review, we present a comprehensive overview of trends in previous research on lipid biomarkers in BD. The current literature varies greatly in the phenotypes investigated and study designs, leading to divergent findings. Small sample size; potential confounders related to physical activity, nutritional status, and medication use; and cross-sectional designs were frequently reported limitations. Future research may benefit from pivoting toward utilization of newer laboratory techniques such as lipidomics, but consistent use of study methods across cohorts is also needed.

Alterations in grey matter structure linked to frequency-specific cortico-subcortical connectivity in schizophrenia via multimodal data fusion

Schizophrenia (SZ) is a complex psychiatric disorder that is currently defined by symptomatic and behavioral, rather than biological, criteria. Neuroimaging is an appealing avenue for SZ biomarker development, as several neuroimaging-based studies comparing individuals with SZ to healthy controls (HC) have shown measurable group differences in brain structure, as well as functional brain alterations in both static and dynamic functional network connectivity (sFNC and dFNC, respectively). The recently proposed filter-banked connectivity (FBC) method extends the standard dFNC sliding-window approach to estimate FNC within an arbitrary number of distinct frequency bands. The initial implementation used a set of filters spanning the full connectivity spectral range, providing a unified approach to examine both sFNC and dFNC in a single analysis. Initial FBC results found that individuals with SZ spend more time in a less structured, more disconnected low-frequency (i.e., static) FNC state than HC, as well as preferential SZ occupancy in high-frequency connectivity states, suggesting a frequency-specific component underpinning the functional dysconnectivity observed in SZ. Building on these findings, we sought to link such frequency-specific patterns of FNC to covarying data-driven structural brain networks in the context of SZ. Specifically, we employ a multi-set canonical correlation analysis + joint independent components analysis (mCCA + jICA) data fusion framework to study the connection between grey matter volume (GMV) maps and FBC states across the full connectivity frequency spectrum. Our multimodal analysis identified two joint sources that captured co-varying patterns of frequency-specific functional connectivity and alterations in GMV with significant group differences in loading parameters between the SZ group and HC. The first joint source linked frequency-modulated connections between the subcortical and sensorimotor networks and GMV alterations in the frontal and temporal lobes, while the second joint source identified a relationship between low-frequency cerebellar-sensorimotor connectivity and structural changes in both the cerebellum and motor cortex. Together, these results show a strong connection between cortico-subcortical functional connectivity at both high and low frequencies and alterations in cortical GMV that may be relevant to the pathogenesis and pathophysiology of SZ.

A systematic review of multimodal brain age studies: Uncovering a divergence between model accuracy and utility

Brain aging is a complex, multifaceted process that can be challenging to model in ways that are accurate and clinically useful. One of the most common approaches has been to apply machine learning to neuroimaging data with the goal of predicting age in a data-driven manner. Building on initial brain age studies that were derived solely from T1-weighted scans (i.e., unimodal), recent studies have incorporated features across multiple imaging modalities (i.e., "multimodal"). In this systematic review, we show that unimodal and multimodal models have distinct advantages. Multimodal models are the most accurate and sensitive to differences in chronic brain disorders. In contrast, unimodal models from functional magnetic resonance imaging were most sensitive to differences across a broad array of phenotypes. Altogether, multimodal imaging has provided us valuable insight for improving the accuracy of brain age models, but there is still much untapped potential with regard to achieving widespread clinical utility.

Insulin-like Growth Factor 2 (IGF-2) and Insulin-like Growth Factor Binding Protein 7 (IGFBP-7) Are Upregulated after Atypical Antipsychotics in Spanish Schizophrenia Patients

Insulin-like growth factor 2 (IGF-2) and IGF binding protein 7 (IGFBP-7) have been related to schizophrenia (SZ) due to their implication in neurodevelopment. The purpose of this study was to assess whether the alterations in IGF-2 and IGFBP-7 in SZ patients are intrinsically related to the psychiatric disorder itself or are a secondary phenomenon due to antipsychotic treatment. In order to test this hypothesis, we measured plasma IGF-2 and IGFBP-7 in drug-naïve first episode (FE) and multiple episodes or chronic (ME) SZ Caucasian patients who have been following treatment for years. A total of 55 SZ patients (FE = 15, ME = 40) and 45 healthy controls were recruited. The Positive and Negative Syndrome Scale (PANSS) and the Self-Assessment Anhedonia Scale (SAAS) were employed to check schizophrenic symptomatology and anhedonia, respectively. Plasma IGF-2 and IGFBP-7 levels were measured by Enzyme-Linked Immunosorbent Assay (ELISA). The FE SZ patients had much lower IGF-2, but not IGFBP-7, than controls. Moreover, both IGF-2 and IGFBP-7 significantly increased after atypical antipsychotic treatment (aripiprazole, olanzapine, or risperidone) in these patients. On the other hand, chronic patients showed higher levels of both proteins when compared to controls. Our study suggests that circulatory IGF-2 and IGFBP-7 increase after antipsychotic treatment, regardless of long-term conditions and being lower in drug-naïve FE patients.

Linking Inflammation, Aberrant Glutamate-Dopamine Interaction, and Post-synaptic Changes: Translational Relevance for Schizophrenia and Antipsychotic Treatment: a Systematic Review

Evidence from clinical, preclinical, and post-mortem studies supports the inflammatory/immune hypothesis of schizophrenia pathogenesis. Less evident is the link between the inflammatory background and two well-recognized functional and structural findings of schizophrenia pathophysiology: the dopamine-glutamate aberrant interaction and the alteration of dendritic spines architecture, both believed to be the “quantal” elements of cortical-subcortical dysfunctional network. In this systematic review, we tried to capture the major findings linking inflammation, aberrant glutamate-dopamine interaction, and post-synaptic changes under a direct and inverse translational perspective, a paramount picture that at present is lacking. The inflammatory effects on dopaminergic function appear to be bidirectional: the inflammation influences dopamine release, and dopamine acts as a regulator of discrete inflammatory processes involved in schizophrenia such as dysregulated interleukin and kynurenine pathways. Furthermore, the link between inflammation and glutamate is strongly supported by clinical studies aimed at exploring overactive microglia in schizophrenia patients and maternal immune activation models, indicating impaired glutamate regulation and reduced N-methyl-D-aspartate receptor (NMDAR) function. In addition, an inflammatory/immune-induced alteration of post-synaptic density scaffold proteins, crucial for downstream NMDAR signaling and synaptic efficacy, has been demonstrated. According to these findings, a significant increase in plasma inflammatory markers has been found in schizophrenia patients compared to healthy controls, associated with reduced cortical integrity and functional connectivity, relevant to the cognitive deficit of schizophrenia. Finally, the link between altered inflammatory/immune responses raises relevant questions regarding potential new therapeutic strategies specifically for those forms of schizophrenia that are resistant to canonical antipsychotics or unresponsive to clozapine.

Sex differences in the blood-brain barrier: Implications for mental health

Prevalence of mental disorders, including major depressive disorder (MDD), bipolar disorder (BD) and schizophrenia (SZ) are increasing at alarming rates in our societies. Growing evidence points toward major sex differences in these conditions, and high rates of treatment resistance support the need to consider novel biological mechanisms outside of neuronal function to gain mechanistic insights that could lead to innovative therapies. Blood-brain barrier alterations have been reported in MDD, BD and SZ. Here, we provide an overview of sex-specific immune, endocrine, vascular and transcriptional-mediated changes that could affect neurovascular integrity and possibly contribute to the pathogenesis of mental disorders. We also identify pitfalls in current literature and highlight promising vascular biomarkers. Better understanding of how these adaptations can contribute to mental health status is essential not only in the context of MDD, BD and SZ but also cardiovascular diseases and stroke which are associated with higher prevalence of these conditions.

The clinical relevance of formal thought disorder in the early stages of psychosis: results from the PRONIA study

BACKGROUND

Formal thought disorder (FTD) has been associated with more severe illness courses and functional deficits in patients with psychotic disorders. However, it remains unclear whether the presence of FTD characterises a specific subgroup of patients showing more prominent illness severity, neurocognitive and functional impairments. This study aimed to identify stable and generalizable FTD-subgroups of patients with recent-onset psychosis (ROP) by applying a comprehensive data-driven clustering approach and to test the validity of these subgroups by assessing associations between this FTD-related stratification, social and occupational functioning, and neurocognition.

METHODS

279 patients with ROP were recruited as part of the multi-site European PRONIA study (Personalised Prognostic Tools for Early Psychosis Management; www.pronia.eu). Five FTD-related symptoms (conceptual disorganization, poverty of content of speech, difficulty in abstract thinking, increased latency of response and poverty of speech) were assessed with Positive and Negative Symptom Scale (PANSS) and the Scale for the Assessment of Negative Symptoms (SANS).

RESULTS

The results with two patient subgroups showing different levels of FTD were the most stable and generalizable clustering solution (predicted clustering strength value = 0.86). FTD-High subgroup had lower scores in social (p_fdr < 0.001) and role (p_fdr < 0.001) functioning, as well as worse neurocognitive performance in semantic (p_fdr < 0.001) and phonological verbal fluency (p_fdr < 0.001), short-term verbal memory (p_fdr = 0.002) and abstract thinking (p_fdr = 0.010), in comparison to FTD-Low group.

CONCLUSIONS

Clustering techniques allowed us to identify patients with more pronounced FTD showing more severe deficits in functioning and neurocognition, thus suggesting that FTD may be a relevant marker of illness severity in the early psychosis pathway.

Identification of key long non-coding RNA-associated competing endogenous RNA axes in Brodmann Area 10 brain region of schizophrenia patients

Schizophrenia (SCZ) is a serious mental condition with an unknown cause. According to the reports, Brodmann Area 10 (BA10) is linked to the pathology and cortical dysfunction of SCZ, which demonstrates a number of replicated findings related to research on SCZ and the dysfunction in tasks requiring cognitive control in particular. Genetics' role in the pathophysiology of SCZ is still unclear. Therefore, it may be helpful to understand the effects of these changes on the onset and progression of SCZ to find novel mechanisms involved in the regulation of gene transcription. In order to determine the molecular regulatory mechanisms affecting the SCZ, the long non-coding RNA (lncRNA)-associated competing endogenous RNAs (ceRNAs) axes in the BA10 area were determined using a bioinformatics approach in the present work. A microarray dataset (GSE17612) consisted of brain post-mortem tissues of the BA10 area from SCZ patients and matched healthy subjects was downloaded from the Gene Expression Omnibus (GEO) database. This dataset included probes for both lncRNAs and mRNAs. Using the R software's limma package, the differentially expressed lncRNAs (DElncRNAs) and mRNAs (DEmRNAs) were found. The RNA interactions were also discovered using the DIANA-LncBase and miRTarBase databases. In the ceRNA network, positive correlations between DEmRNAs and DElncRNAs were evaluated using the Pearson correlation coefficient. Finally, lncRNA-associated ceRNA axes were built by using the co-expression and DElncRNA-miRNA-DEmRNA connections. We identified the DElncRNA-miRNA-DEmRNA axes, which included two key lncRNAs (PEG3-AS1, MIR570HG), seven key miRNAs (hsa-miR-124-3p, hsa-miR-17-5p, hsa-miR-181a-5p, hsa-miR-191-5p, hsa-miR-26a-5p, hsa-miR-29a-3p, hsa-miR-29b-3p), and eight key mRNAs (EGR1, ETV1, DUSP6, PLOD2, CD93, SERPINB9, ANGPTL4, TGFB2). Furthermore, DEmRNAs were found to be enriched in the "AGE-RAGE signaling pathway in diabetic complications", "Amoebiasis", "Transcriptional misregulation in cancer", "Human T-cell leukemia virus 1 infection", and "MAPK signaling pathway". This study offers research targets for examining significant molecular pathways connected to the pathogenesis of SCZ, even though the function of these ceRNA axes still needs to be investigated.

Oxidative Stress Biomarkers as a Predictor of Stage Illness and Clinical Course of Schizophrenia

Pro/antioxidant imbalance has been reported in schizophrenia (SZ). However, the results of studies are inconsistent and usually do not include other factors that are highly affected by oxidative stress (OS).This cross-sectional study aimed to determine the serum levels of OS markers and their potential connection with schizophrenia. The total sample comprised 147: 98 individuals with SZ -47 first-episode (FS) and 49 chronic patients (CS)-and 49 healthy individuals (HC) as a control group. The examination included clinical variables and serum levels of antioxidants and oxidative damage products. The significant changes were observed in concentrations of all examined markers, without any specific direction of the pro/antioxidant balance shift between SZ and HC. In the regression model adjusted for cofounders, catalase: OR = 0.81 (95%CI: 0.74-0.88); glutathione peroxidase: OR = 1.06 (95%CI: 1.02-1.10); total antioxidant capacity: OR = 0.85 (95%CI: 0.75-0.98); oxidative stress index: OR = 1.25 (95%CI: 1.03-1.52); ferric reducing ability of plasma: OR = 0.79 (95%CI: 0.69-0.89); advanced glycation end products: OR = 1.03 (95%CI: 1.01-1.04); and advanced oxidation protein products (AOPP): OR = 1.05 (95%CI: 1.03-1.07) turned out to be significant predictors of schizophrenia. In the multiple stepwise regression model, pro/antioxidant status and their interaction with the duration of illness-related factors affected schizophrenia symptoms: positive symptoms (FRAPxKYN), negative (DITYR, FRAP, CAT), general (KYN), and over-all psychopathology (KYNxNFK). The results confirm differences in serum levels of oxidative biomarkers between SZ patients and healthy individuals. The pro/antioxidant status could be considered a predictor of schizophrenia and the factor affects patients' symptom severity.

Nanotechnology Approaches for Enhanced CNS Drug Delivery in the Management of Schizophrenia

Schizophrenia is a neuropsychiatric disorder mainly affecting the central nervous system, presented with auditory and visual hallucinations, delusion and withdrawal from society. Abnormal dopamine levels mainly characterise the disease; various theories of neurotransmitters explain the pathophysiology of the disease. The current therapeutic approach deals with the systemic administration of drugs other than the enteral route, altering the neurotransmitter levels within the brain and providing symptomatic relief. Fluid biomarkers help in the early detection of the disease, which would improve the therapeutic efficacy. However, the major challenge faced in CNS drug delivery is the blood-brain barrier. Nanotherapeutic approaches may overcome these limitations, which will improve safety, efficacy, and targeted drug delivery. This review article addresses the main challenges faced in CNS drug delivery and the significance of current therapeutic strategies and nanotherapeutic approaches for a better understanding and enhanced drug delivery to the brain, which improve the quality of life of schizophrenia patients.

The role of dopamine receptors in lymphocytes and their changes in schizophrenia

Dopamine and its 5 receptors, which are grouped into two families (D1-like and D2-like), modulate functions at a systemic level in both the central nervous system and periphery. The central nervous system and the immune system are the main adaptive systems, which participate in a continuous and functional crosstalk to guarantee homeostasis. On binding to its 5 dopamine receptors, dopamine acts as a co-regulator of the immune system, contributing to the interaction of the central nervous system and inflammatory events and as a source of communication between the different immune cells. Dopaminergic perturbations in the central nervous system are observed in several neurological and psychiatric disorders. Schizophrenia is one of the most common mental disorders with a poorly understood pathoaetiology that includes genetic and environmental components that promote alterations in the dopaminergic system. Interestingly, abnormalities in dopamine receptors expression in lymphocytes of schizophrenia patients have been reported, often significantly correlating with the severity of the psychotic illness. Here, we review the current literature regarding the dopaminergic system in human lymphocytes and its alterations in schizophrenia.

1.

The existence of DA in the bloodstream suggests the presence of dopaminergic components that modulate functions at a systemic level; therefore, its effects are not limited to the CNS and the signalling in the neuronal dopaminergic system should be independent from that of the peripheral systems.

2.

The effects by DA-mediated activation of different DRs on immune cells show different sensitivities to DA, but binding profiles of DA on T cells are similar to those in neuronal membranes, suggesting receptors act similarly to those found in neurons.

3.

All DRs are expressed on the LYM membrane. However, more detailed information is required on the expression patterns of DR in immune cells in healthy conditions and in pathologies.

4.

DA has been observed to influence LYM functions acting in a variety of important processes, like cytokine secretion, cell adhesion, chemotaxis, and cytotoxicity.

5.

In human LYM, DA on D1-like receptors decreases oxidative metabolism and apoptosis, activates the selective secretion of IL-10 and TNFα, and facilitates NK cells. In contrast, most of the immunostimulatory DA effects on LYM depend on stimulation of D2-like receptors including activation, proliferation, differentiation, and suppression of NK cells.

6.

To date, an altered expression or signalling of neurotransmitter receptors is observed in immune cells during psychiatric disorders and, consequently, these cells also markedly respond to antipsychotics.

7.

Numerous technologies have been used in search of biomarkers for SCZ. However, after a century of studying SCZ their application in psychiatry remains rare and there are currently no validated biomarkers for the diagnosis and prognosis of patients with SCZ or the prediction of treatment efficacy.

Pro/Antioxidant State as a Potential Biomarker of Schizophrenia

To allow better diagnosis and management of psychiatric illnesses, the use of easily accessible biomarkers are proposed. Therefore, recognition of some diseases by a set of related pathogenesis biomarkers is a promising approach. The study aims to assess the usefulness of examining oxidative stress (OS) in schizophrenia as a potential biomarker of illness using the commonly used data mining decision tree method. The study group was comprised of 147 participants: 98 patients with schizophrenia (SZ group), and the control group (n = 49; HC). The patients with schizophrenia were divided into two groups: first-episode schizophrenia (n = 49; FS) and chronic schizophrenia (n = 49; CS). The assessment included the following biomarkers in sera of patients: catalase (CAT), glutathione peroxidase (GPx), superoxide dismutase-1 (SOD-1), glutathione reductase (GR), reduced glutathione (GSH), total antioxidant capacity (TAC), ferric reducing ability of plasma (FRAP), advanced glycation end products (AGEs), advanced oxidation protein products (AOPP), dityrosine (DITYR), kynurenine (KYN), N-formylkynurenine (NFK), tryptophan (TRY), total oxidant status (TOS), nitric oxide (NO) and total protein. Maximum accuracy (89.36%) for distinguishing SZ from HC was attained with TOS and GPx (cut-off points: 392.70 and 15.33). For differentiating between FS and CS, the most promising were KYN, AOPP, TAC and NO (100%; cut-off points: 721.20, 0.55, 64.76 and 2.59). To distinguish FS from HC, maximum accuracy was found for GSH and TOS (100%; cut-off points: 859.96 and 0.31), and in order to distinguish CS from HC, the most promising were GSH and TOS (100%; cut-off points: 0.26 and 343.28). Using redox biomarkers would be the most promising approach for discriminating patients with schizophrenia from healthy individuals and, in the future, could be used as an add-on marker to diagnose and/or respond to treatment.

Subtyping Schizophrenia Patients Based on Patterns of Structural Brain Alterations

Schizophrenia is a complex and heterogeneous syndrome. Whether quantitative imaging biomarkers can identify discrete subgroups of patients as might be used to foster personalized medicine approaches for patient care remains unclear. Cross-sectional structural MR images of 163 never-treated first-episode schizophrenia patients (FES) and 133 chronically ill patients with midcourse schizophrenia from the Bipolar and Schizophrenia Network for Intermediate Phenotypes (B-SNIP) consortium and a total of 403 healthy controls were recruited. Morphometric measures (cortical thickness, surface area, and subcortical structures) were extracted for each subject and then the optimized subtyping results were obtained with nonsupervised cluster analysis. Three subgroups of patients defined by distinct patterns of regional cortical and subcortical morphometric features were identified in FES. A similar three subgroup pattern was identified in the independent dataset of patients from the multi-site B-SNIP consortium. Similarities of classification patterns across these two patient cohorts suggest that the 3-group typology is relatively stable over the course of illness. Cognitive functions were worse in subgroup 1 with midcourse schizophrenia than those in subgroup 3. These findings provide novel insight into distinct subgroups of patients with schizophrenia based on structural brain features. Findings of different cognitive functions among the subgroups support clinical differences in the MRI-defined illness subtypes. Regardless of clinical presentation and stage of illness, anatomic MR subgrouping biomarkers can separate neurobiologically distinct subgroups of schizophrenia patients, which represent an important and meaningful step forward in differentiating subtypes of patients for studies of illness neurobiology and potentially for clinical trials.

Stress and the Role of the Gut-Brain Axis in the Pathogenesis of Schizophrenia: A Literature Review

Schizophrenia is a severe neuropsychiatric disorder, and its etiology remains largely unknown. Environmental factors have been reported to play roles in the pathogenesis of schizophrenia, and one of the major environmental factors identified for this disorder is psychosocial stress. Several studies have suggested that stressful life events, as well as the chronic social stress associated with city life, may lead to the development of schizophrenia. The other factor is the gut–brain axis. The composition of the gut microbiome and alterations thereof may affect the brain and may lead to schizophrenia. The main interest of this review article is in overviewing the major recent findings on the effects of stress and the gut–brain axis, as well as their possible bidirectional effects, in the pathogenesis of schizophrenia.

Hidden Role of Gut Microbiome Dysbiosis in Schizophrenia: Antipsychotics or Psychobiotics as Therapeutics?

Schizophrenia is a chronic, heterogeneous neurodevelopmental disorder that has complex symptoms and uncertain etiology. Mounting evidence indicates the involvement of genetics and epigenetic disturbances, alteration in gut microbiome, immune system abnormalities, and environmental influence in the disease, but a single root cause and mechanism involved has yet to be conclusively determined. Consequently, the identification of diagnostic markers and the development of psychotic drugs for the treatment of schizophrenia faces a high failure rate. This article surveys the etiology of schizophrenia with a particular focus on gut microbiota regulation and the microbial signaling system that correlates with the brain through the vagus nerve, enteric nervous system, immune system, and production of postbiotics. Gut microbially produced molecules may lay the groundwork for further investigations into the role of gut microbiota dysbiosis and the pathophysiology of schizophrenia. Current treatment of schizophrenia is limited to psychotherapy and antipsychotic drugs that have significant side effects. Therefore, alternative therapeutic options merit exploration. The use of psychobiotics alone or in combination with antipsychotics may promote the development of novel therapeutic strategies. In view of the individual gut microbiome structure and personalized response to antipsychotic drugs, a tailored and targeted manipulation of gut microbial diversity naturally by novel prebiotics (non-digestible fiber) may be a successful alternative therapeutic for the treatment of schizophrenia patients.

Hidden Role of Gut Microbiome Dysbiosis in Schizophrenia: Antipsychotics or Psychobiotics as Therapeutics?

Schizophrenia is a chronic, heterogeneous neurodevelopmental disorder that has complex symptoms and uncertain etiology. Mounting evidence indicates the involvement of genetics and epigenetic disturbances, alteration in gut microbiome, immune system abnormalities, and environmental influence in the disease, but a single root cause and mechanism involved has yet to be conclusively determined. Consequently, the identification of diagnostic markers and the development of psychotic drugs for the treatment of schizophrenia faces a high failure rate. This article surveys the etiology of schizophrenia with a particular focus on gut microbiota regulation and the microbial signaling system that correlates with the brain through the vagus nerve, enteric nervous system, immune system, and production of postbiotics. Gut microbially produced molecules may lay the groundwork for further investigations into the role of gut microbiota dysbiosis and the pathophysiology of schizophrenia. Current treatment of schizophrenia is limited to psychotherapy and antipsychotic drugs that have significant side effects. Therefore, alternative therapeutic options merit exploration. The use of psychobiotics alone or in combination with antipsychotics may promote the development of novel therapeutic strategies. In view of the individual gut microbiome structure and personalized response to antipsychotic drugs, a tailored and targeted manipulation of gut microbial diversity naturally by novel prebiotics (non-digestible fiber) may be a successful alternative therapeutic for the treatment of schizophrenia patients.

Haloperidol elicits oxidative damage in the brain of rats submitted to the ketamine-induced model of schizophrenia

The present study aims to evaluate the effects of haloperidol, an important first-generation antipsychotic, on the antioxidant system parameters in the brain of animals subjected to a model of schizophrenia induced by ketamine. Adult rats intraperitoneally received saline (1 mL/kg) or ketamine (25 mg/kg body weight) for 15 days, and saline or haloperidol (0.1 mg/kg body weight) via gavage once a day, between the 9th and 14th days. In the frontal cortex, hippocampus, and striatum, assessments of lipid (4-hydroxy-2-nonenal and 8-isoprostane levels) and protein (protein carbonyl content) oxidative damage were conducted. It was also measured the glutathione peroxidase and glutathione reductase activities in the same cerebral structures. Increases in the 4-hydroxy-2-nonenal and 8-isoprostane levels were detected in rats receiving haloperidol and ketamine. An increase in the carbonyl content was also observed in animals receiving ketamine, haloperidol, or a combination thereof. In animals receiving the antipsychotic, there was a decrease in the activity of the enzymes. Therefore, both ketamine and haloperidol induced oxidative damage. A possible energy dysfunction or a haloperidol effect targeting the glutathione enzymes, and then disrupting the redox homeostasis in neurons, could not be ruled out, although further studies are required to confirm or refute a direct interaction.

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.

Methylome-wide association study of first-episode schizophrenia reveals a hypermethylated CpG site in the promoter region of the TNIK susceptibility gene

Accumulating evidence suggests that epigenetics plays an important role in the etiology of schizophrenia. Here, we performed a methylome-wide association study (MWAS) of first-onset schizophrenia patients and controls from the Han Chinese population using microarray technology. The DNA methylation profiles revealed 4494 differentially methylated CpG sites. Gene ontology (GO) analysis showed that the functions of differentially methylated genes were primarily involved in enzymatic activity, cytoskeleton organization and cell adhesion, and the TNIK (encoding TRAF2- and NCK-interacting kinase) gene was enriched in most of these terms. By combining the MWAS results with those of previous genome-wide association studies (GWASs), we identified 72 candidate genes located in 49 human genome loci. Among the overlapping genes, the most significantly methylated CpG sites were in the transcriptional start site (TSS) 200 region (cg21413905, P_unadjusted = 3.20 × 10^-5) of TNIK. TNIK was listed in the top 50 differentially methylated loci. The results of pyrosequencing and TNIK mRNA expression were consistent with those of the microarray study. Bioinformatics analyses, dual-luciferase reporter assays and chromatin immunoprecipitation (ChIP) studies showed that TNIK interacted with genes associated with schizophrenia and NRF1 was identified as a novel transcription factor (TF) that binds to TNIK in its TSS200 region. Thus, the regulatory function of NRF1 may be influenced by the status of the methylated CpG site in this region. In summary, our study provides new insights into the epigenetic mechanisms that regulate schizophrenia. Studies of the functions of TNIK methylation should be performed in vitro and in vivo to provide a better understanding of the pathophysiology of schizophrenia.

Advanced EEG-based learning approaches to predict schizophrenia: Promises and pitfalls

The complexity and heterogeneity of schizophrenia symptoms challenge an objective diagnosis, which is typically based on behavioral and clinical manifestations. Moreover, the boundaries of schizophrenia are not precisely demarcated from other nosologic categories, such as bipolar disorder. The early detection of schizophrenia can lead to a more effective treatment, improving patients' quality of life. Over the last decades, hundreds of studies aimed at specifying the neurobiological mechanisms that underpin clinical manifestations of schizophrenia, using techniques such as electroencephalography (EEG). Changes in event-related potentials of the EEG have been associated with sensory and cognitive deficits and proposed as biomarkers of schizophrenia. Besides contributing to a more effective diagnosis, biomarkers can be crucial to schizophrenia onset prediction and prognosis. However, any proposed biomarker requires substantial clinical research to prove its validity and cost-effectiveness. Fueled by developments in computational neuroscience, automatic classification of schizophrenia at different stages (prodromal, first episode, chronic) has been attempted, using brain imaging pattern recognition methods to capture differences in functional brain activity. Advanced learning techniques have been studied for this purpose, with promising results. This review provides an overview of recent machine learning-based methods for schizophrenia classification using EEG data, discussing their potentialities and limitations. This review is intended to serve as a starting point for future developments of effective EEG-based models that might predict the onset of schizophrenia, identify subjects at high-risk of psychosis conversion or differentiate schizophrenia from other disorders, promoting more effective early interventions.

Concordance of Immune-Related Markers in Lymphocytes and Prefrontal Cortex in Schizophrenia

Schizophrenia is a severe neuropsychiatric disorder associated with a wide array of transcriptomic and neurobiochemical changes. Genome-wide transcriptomic profiling conducted in postmortem brain have provided novel insights into the pathophysiology of this disorder, and identified biological processes including immune/inflammatory-related responses, metabolic, endocrine, and synaptic function. However, few studies have investigated whether similar changes are present in peripheral tissue. Here, we used RNA-sequencing to characterize transcriptomic profiles of lymphocytes in 18 nonpsychotic controls and 19 individuals with schizophrenia. We identified 2819 differentially expressed transcripts (P nominal < .05) in the schizophrenia group when compared to controls. Bioinformatic analyses conducted on a subset of 293 genes (P nominal < .01 and |log2 FC| > 0.5) highlighted immune/inflammatory responses as key biological processes in our dataset. Differentially expressed genes in lymphocytes were highly enriched in gene expression profiles associated with cortex layer 5a and immune cells. Thus, we investigated whether the changes in transcripts levels observed in lymphocytes could also be detected in the prefrontal cortex (PFC, BA10) in a second replication cohort of schizophrenia subjects. Remarkably, mRNA levels detected in the PFC and lymphocytes were in strong agreement, and measurements obtained using RNA-sequencing positively correlated with data obtained by reverse transcriptase-quantitative polymerase chain reaction analysis. Collectively, our work supports a role for immune dysfunction in the pathogenesis of schizophrenia and suggests that peripheral markers can be used as accessible surrogates to investigate putative central nervous system disruptions.

Cytokine Imbalance in Schizophrenia. From Research to Clinic: Potential Implications for Treatment

Cytokines are one of the most important components of the immune system. They orchestrate the brain's response to infectious and other exogenous insults and are crucial mediators of the cross-talk between the nervous and immune systems. Epidemiological studies have demonstrated that severe infections and autoimmune disorders, in addition to genetic predisposition, are risk factors for schizophrenia. Furthermore, maternal infection during pregnancy appears to increase the risk of schizophrenia, and proinflammatory cytokines may be negatively involved in the neurodevelopmental process. A cytokine imbalance has been described in the blood and cerebrospinal fluid of schizophrenia patients, particularly in the T helper type 1 [Th1] and type 2 [Th2] cytokines, albeit the results of such studies appear to be contradictory. Chronic stress, likewise, appears to contribute to a lasting proinflammatory state and likely also promotes the disorder. The aim of this mini-review is to investigate the roles of different cytokines in the pathophysiology of schizophrenia and define how cytokines may represent key molecular targets to regulate for the prevention and treatment of schizophrenia. How current antipsychotic drugs impact cytokine networks is also evaluated. In this context, we propose to change the focus of schizophrenia from a traditionally defined brain disorder, to one that is substantially impacted by the periphery and immune system.

Metabolomic Identification of Exosome-Derived Biomarkers for Schizophrenia: A Large Multicenter Study

Exosomes have been suggested as promising targets for the diagnosis and treatment of neurological diseases, including schizophrenia (SCZ), but the potential role of exosome-derived metabolites in these diseases was rarely studied. Using ultra-performance liquid chromatography-tandem mass spectrometry, we performed the first metabolomic study of serum-derived exosomes from patients with SCZ. Our sample comprised 385 patients and 332 healthy controls recruited from 3 clinical centers and 4 independent cohorts. We identified 25 perturbed metabolites in patients that can be used to classify samples from patients and control participants with 95.7% accuracy (95% CI: 92.6%-98.9%) in the training samples (78 patients and 66 controls). These metabolites also showed good to excellent performance in differentiating between patients and controls in the 3 test sets of participants, with accuracies 91.0% (95% CI: 85.7%-96.3%; 107 patients and 62 controls), 82.7% (95% CI: 77.6%-87.9%; 104 patients and 142 controls), and 99.0% (95% CI: 97.7%-100%; 96 patients and 62 controls), respectively. Bioinformatic analysis suggested that these metabolites were enriched in pathways implicated in SCZ, such as glycerophospholipid metabolism. Taken together, our findings support a role for exosomal metabolite dysregulation in the pathophysiology of SCZ and indicate a strong potential for exosome-derived metabolites to inform the diagnosis of SCZ.

EEG microstates as biomarker for psychosis in ultra-high-risk patients

Resting-state EEG microstates are brief (50-100 ms) periods, in which the spatial configuration of scalp global field power remains quasi-stable before rapidly shifting to another configuration. Changes in microstate parameters have been described in patients with psychotic disorders. These changes have also been observed in individuals with a clinical or genetic high risk, suggesting potential usefulness of EEG microstates as a biomarker for psychotic disorders. The present study aimed to investigate the potential of EEG microstates as biomarkers for psychotic disorders and future transition to psychosis in patients at ultra-high-risk (UHR). We used 19-channel clinical EEG recordings and orthogonal contrasts to compare temporal parameters of four normative microstate classes (A-D) between patients with first-episode psychosis (FEP; n = 29), UHR patients with (UHR-T; n = 20) and without (UHR-NT; n = 34) later transition to psychosis, and healthy controls (HC; n = 25). Microstate A was increased in patients (FEP & UHR-T & UHR-NT) compared to HC, suggesting an unspecific state biomarker of general psychopathology. Microstate B displayed a decrease in FEP compared to both UHR patient groups, and thus may represent a state biomarker specific to psychotic illness progression. Microstate D was significantly decreased in UHR-T compared to UHR-NT, suggesting its potential as a selective biomarker of future transition in UHR patients.

Does genetic mouse model of constitutive Hint1 deficiency exhibit schizophrenia-like behaviors?

The histidine triad nucleotide binding protein 1 (HINT1) is closely related to many neuropsychiatric disorders. Clinical studies supported that mutations in the Hint1 gene correlated potentially with schizophrenia. In addition, Hint1 gene knockout (KO) mice exhibited hyperactivity induced by amphetamine and apomorphine. However, it is still unclear whether this animal model exhibits schizophrenia-like behaviors and, if so, their underlying mechanisms remain to be elucidated. Thus, our study sought to evaluate schizophrenia-like behaviors in Hint1-KO mice, and explore the associated changes in neuronal structural plasticity and schizophrenia-related molecules. A series of behavioral tests were used to compare Hint1-KO and their wild-type (WT) littermates, alongside a number of morphological and molecular biological methods. Relative to WT mice, Hint1-KO mice exhibited reduced social interaction behaviors, aggressive behavior, sensorimotor gating deficits, apathetic and self-neglect behaviors, and increased MK-801-induced hyperactivity. Hint1-KO mice also showed partly increased dendritic complexity in the hippocampus (Hip) relative to WT mice. Total glutamate was decreased in the medial prefrontal cortex, nucleus accumbens (NAc), and Hip of KO mice. Expression of NR₁, NR_2A, and D₄R was decreased whereas that of D₁R was increased in the NAc of KO relative to WT mice. The expression level of NR_2B was increased whereas that of D₁R was decreased in the Hip of KO mice. Hint1-KO mice exhibited schizophrenia-like behaviors. Partly increased dendritic complexity and dysfunction in both the dopaminergic and glutamatergic systems may be involved in the abnormalities in Hint1-KO mice.

S100A7/Ran-binding protein 9 coevolution in mammals

S100A7 has been suggested to interact with Ran-binding protein 9. Both proteins are nowadays considered key effectors in immune response. Functional interaction between proteins is ensured by coevolution. The mechanisms of vertebrate coevolution between S100A7 and RanBP9 remain unclear. Several approaches for studying coevolution have been developed. Protein coevolution was inferred by calculating the linear correlation coefficients between inter-protein distance matrices using Mirrortree. We found an overall moderate correlation value (R = 0.53, p < 1e-06). Moreover, owing to the high conservation of RanBP9 protein among vertebrates, we chose to utilize a recent version of Blocks in Sequences (BIS2) algorithm implemented in BIS2Analyzer webserver. A coevolution cluster was identified between the two proteins (p < 8.10e-05). In conclusion, our coevolutionary analysis suggests that amino acid variations may modulate S100A7/RanBP9 interaction with potential pathogenic effects. Such findings could guide further analysis to better elucidate the function of S100A7 and RanBP9 and to design drugs targeting for these molecules in diseases.

Predicting Symptomatic and Functional Improvements over 1 Year in Patients with First-Episode Psychosis Using Resting-State Electroencephalography

OBJECTIVE

Although early intervention from the beginning of a psychotic episode is essential for a better prognosis, biomarkers predictive of symptomatic and functional improvement in early psychotic disorders are lacking. This study aimed to investigate whether the spectral power of resting-state electroencephalography (EEG) can be used as a predictive marker of the 1-year prognosis in patients with first-episode psychosis (FEP).

METHODS

Twenty-four patients with FEP and matched healthy control (HC) subjects were examined with resting-state EEG at baseline. The symptomatic severity and functional status of FEP patients were assessed at baseline and reassessed after 1 year of usual treatment. Repeated measures analysis of variance was conducted to compare EEG spectral powers across the groups. Multiple regression analysis revealed EEG spectral powers predictive of symptomatic and functional improvement in FEP patients at the 1-year follow-up.

RESULTS

Delta band power in the frontal and posterior regions was significantly higher in patients with FEP than in HCs. Higher delta band power in the posterior region predicted later improvement of positive symptoms and general functional status. Lower delta band power in the frontal region predicted improvement of negative symptoms and general functioning after 1 year.

CONCLUSION

These results suggest that increased delta absolute power is observed from the beginning of psychotic disorders. Furthermore, decreased delta power in the frontal region and increased delta power in the posterior region might be used as a predictive marker of a better prognosis of FEP, which would aid early intervention in clinical practice.

Design of novel dopamine D2 and serotonin 5-HT2A receptors dual antagonists toward schizophrenia: An integrated study with QSAR, molecular docking, virtual screening and molecular dynamics simulations

The extrapyramidal side effects of schizophrenia treatment can be significantly reduced by simultaneously targeting dopamine D₂ and serotonin 5-HT_2A receptors. In this study, three-dimensional quantitative structure-activity relationship (3D-QSAR) models of D₂ receptor (CoMFA-1, q² = 0.767, r² = 0.969; CoMSIA-1, q² = 0.717, r² = 0.978) and 5-HT_2A receptor antagonists (CoMFA-2, q² = 0.703, r² = 0.946; CoMSIA-2, q² = 0.675, r² = 0.916) were successfully constructed using 35 tetrahydropyridopyrimidinone derivatives. Topomer CoMFA and HQSAR models were then constructed to further validate and supplement above models. Results showed that all models had good predictive power and stability. Contour map analysis revealed that the electrostatic and hydrophobic fields played vital roles in the bioactivity of dual antagonists. Molecular docking and molecular dynamic studies also suggested that the hydrogen bonding, electrostatic and hydrophobic interactions played key roles in the formation of stable binding sites. Meanwhile, several key residues like ASP114, TRP100, PHE389 of dopamine D₂ receptor and ASP134, PHE328, TRP324 of serotonin 5-HT_2A receptor were identified. Based on above findings, seven compounds were obtained through bioisostere replacement and ten compounds were designed by contour map analysis, in which the predicted activity of compounds S6 and DS2 were equivalent to that of the template compound 15. 3D-QSAR and ADMET predictions indicated that all newly designed compounds had great biological activity and physicochemical properties. Moreover, based on the best pharmacophore model, four compounds (Z1, Z2, Z3 and Z4) with new backbones were obtained by virtual screening. Overall, this study could provide theoretical guidance for the structural optimization, design and synthesis of novel dopamine D₂ and serotonin 5-HT_2A receptors dual antagonists. Abbreviations3D-QSARThree-dimensional quantitative structure-activity relationship5-HT_2ARSerotonin 5-hydroxytryptamine 5-HT_2A receptor5-HT_2CRSerotonin 5-hydroxytryptamine 5-HT_2C receptor receptorCADDComputer-aided drug designCoMFAComparative molecular field analysisCoMSIAComparative molecular similarity index analysisD₂RDopamine D(2) receptorGPCRG-protein coupled receptorPLSPartial least squares regressionHQSARHologram quantitative structure-activity relationship. Communicated by Ramaswamy H. Sarma.

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

OBJECTIVE

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

METHODS

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

RESULTS

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

CONCLUSION

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

Making Sense of the Epigenome Using Data Integration Approaches

Epigenetic research involves examining the mitotically heritable processes that regulate gene expression, independent of changes in the DNA sequence. Recent technical advances such as whole-genome bisulfite sequencing and affordable epigenomic array-based technologies, allow researchers to measure epigenetic profiles of large cohorts at a genome-wide level, generating comprehensive high-dimensional datasets that may contain important information for disease development and treatment opportunities. The epigenomic profile for a certain disease is often a result of the complex interplay between multiple genetic and environmental factors, which poses an enormous challenge to visualize and interpret these data. Furthermore, due to the dynamic nature of the epigenome, it is critical to determine causal relationships from the many correlated associations. In this review we provide an overview of recent data analysis approaches to integrate various omics layers to understand epigenetic mechanisms of complex diseases, such as obesity and cancer. We discuss the following topics: (i) advantages and limitations of major epigenetic profiling techniques, (ii) resources for standardization, annotation and harmonization of epigenetic data, and (iii) statistical methods and machine learning methods for establishing data-driven hypotheses of key regulatory mechanisms. Finally, we discuss the future directions for data integration that shall facilitate the discovery of epigenetic-based biomarkers and therapies.

The role of the gut microbiota in schizophrenia: Current and future perspectives

OBJECTIVES

Schizophrenia is a poorly understood chronic disease. Its pathophysiology is complex, dynamic, and linked to epigenetic mechanisms and microbiota involvement. Nowadays, correlating schizophrenia with the environment makes sense owing to its multidimensional implications: temporal and spatial variability. Microbiota involvement and epigenetic mechanisms are factors that are currently being considered to better understand another dimension of schizophrenia.

METHODS

This review summarises and discusses currently available information, focussing on the microbiota, epigenetic mechanisms, technological approaches aimed at performing exhaustive analyses of the microbiota, and psychotherapies, to establish future perspectives.

RESULTS

The connection between the microbiota, epigenetic mechanisms and technological developments allows for formulating new approaches objectively oriented towards the development of alternative psychotherapies that may help treat schizophrenia.

CONCLUSIONS

In this review, the gut microbiota and epigenetic mechanisms were considered as key regulators, revealing a potential new aetiology of schizophrenia. Likewise, continuous technological advances (e.g. culturomics), aimed at the microbiota-gut-brain axis generate new evidence on this concept.

The neurobiological hypothesis of neurotrophins in the pathophysiology of schizophrenia: A meta-analysis

BACKGROUND

Schizophrenia is associated with patterns of aberrant neurobiological circuitry. The disease complexity is mirrored by multiple biological interactions known to contribute to the disease pathology. One potential contributor is the family of neurotrophins which are proteins involved in multiple functional processes in the nervous system, with crucial roles in neurodevelopment, synaptogenesis and neuroplasticity. With these roles in mind, abnormal neurotrophin profiles have been hypothesized to contribute to the pathology of schizophrenia.

METHODS

We performed a systematic review and a meta-analysis to scrutinize the neurobiological hypothesis of neurotrophins in schizophrenia, examining the correlation between peripheral levels of brain-derived neurotrophic factor (BDNF), nerve growth factor (NGF), neurotrophin-3 (NT-3) and neurotrophin 4/5 (NT-4/5) associated with schizophrenia.

RESULTS

Fifty-two studies were reviewed and twenty-two studies were included in this meta-analysis. Using a random effects model, we confirmed that decreased levels of neurotrophins (BDNF, NGF and NT-4/5) were associated with schizophrenia (Hedges's g = -0.846; SE = 0.058; 95% confidence interval: -0.960 to -0.733; Z-value = -14.632; p-value = 0.000). Subgroup analysis indicated that neurotrophin levels are significantly decreased in both medicated and drug-näive patients. Meta-regression of continuous variables such as mean age, duration of illness and PANSS total score did not show significant effects (p > 0.05) in relation to neurotrophins levels.

DISCUSSION

We confirm that decreased peripheral neurotrophin levels are significantly associated with schizophrenia, thereby confirming the neurobiological hypothesis of neurotrophins in schizophrenia. Low levels of neurotrophins in peripheral blood of patients with schizophrenia may explain, in part, the pathophysiology of schizophrenia.

Cytokines dysregulation in schizophrenia: A systematic review of psychoneuroimmune relationship

INTRODUCTION

Schizophrenia is a multifactorial psychiatric disease with complex interactions among the brain and the immune system. A psycho-immune relationship underling schizophrenia is supported by several studies and integrates a specific area of knowledge - psychoneuroimmunology.

METHODS

A systematic review was performed by 2009 Preferred Reporting Items (PRISMA) recommendations. Based on the inclusion/exclusion criteria, publications with relevant information (evaluated by the Joanna Briggs Institute Critical Appraisals tools to quality assessment) were included.

RESULTS

In this review, we considered the inflammatory activity promoted by cytokine alterations in schizophrenia aetiology, which reflects the systemic comprehension of this disease in opposition to the traditional approach focused solely on the brain. We focus on the analysis of several specific outcomes, such as proinflammatory cytokines, sample sort, laboratory techniques, diagnosis scales and results of each publication.

CONCLUSION

This systematic review confirms the existence of cytokines abnormalities in schizophrenia disease. Immune imbalances such as increased levels of some cytokines (either at protein level or at mRNA expression), cytokine mRNAs, as well as cytokine gene polymorphisms have been reported with a large support in schizophrenia. These findings provide a strong evidence of a concomitant process of inflammatory activity in schizophrenia illness course.

An Update on Promising Biomarkers in Schizophrenia

Given the heterogeneity of symptoms in patients with schizophrenia and current treatment limitations, biomarkers may play an important role in diagnosis, subtype stratification, and the assessment of treatment response. Though many potential biomarkers have been studied, we have chosen to focus on some of the most promising and potentially clinically relevant biomarkers to review herein. These include markers of inflammation, neuroimaging biomarkers, brain-derived neurotrophic factor, genetic/epigenetic markers, and speech analysis. This will provide a broad overview of putative biomarkers that could become clinically relevant in the future, though none currently appear ready to assist the clinician in identifying cases of schizophrenia, subtypes of the disorder, treatment choice, or response. Nonetheless, some biomarkers, such as C-reactive protein (CRP), may be useful at identifying individuals who may be more highly inflamed, which could drive treatment choice. Though checking CRP is not a standard of practice, this is one example of how biomarkers may drive treatment decisions in the future, supporting precision medicine. Similarly, technological advances may one day allow clinicians to detect changes in speech patterns, which could represent a noninvasive, clinically useful tool in the future. We conclude the review by highlighting two important potential clinical uses for biomarkers in schizophrenia: the identification of individuals who may convert from clinical high risk and the stratification of patients via different biomarkers that may supersede clinical diagnosis. Given the enormous burden of illness of schizophrenia, the search for clinically relevant biomarkers is of great importance to improve the lives of patients with the disorder.

An OMIC biomarker detection algorithm TriVote and its application in methylomic biomarker detection

Aim: Transcriptomic and methylomic patterns represent two major OMIC data sources impacted by both inheritable genetic information and environmental factors, and have been widely used as disease diagnosis and prognosis biomarkers. Materials & methods: Modern transcriptomic and methylomic profiling technologies detect the status of tens of thousands or even millions of probing residues in the human genome, and introduce a major computational challenge for the existing feature selection algorithms. This study proposes a three-step feature selection algorithm, TriVote, to detect a subset of transcriptomic or methylomic residues with highly accurate binary classification performance. Results & conclusion: TriVote outperforms both filter and wrapper feature selection algorithms with both higher classification accuracy and smaller feature number on 17 transcriptomes and two methylomes. Biological functions of the methylome biomarkers detected by TriVote were discussed for their disease associations. An easy-to-use Python package is also released to facilitate the further applications.

Constructing the Immune Signature of Schizophrenia for Clinical Use and Research; An Integrative Review Translating Descriptives Into Diagnostics

Schizophrenia is considered a syndrome comprised by several disease phenotypes, covering a range of underlying pathologies. One of these disease mechanisms seems to involve immune dysregulation and neuroinflammation. While the current dopamine receptor-blocking antipsychotic drugs decrease psychotic symptoms and prevent relapse in the majority of patients with schizophrenia, there is a huge need to explore new treatment options that target other pathophysiological pathways. Such studies should aim at identifying robust biomarkers in order to diagnose and monitor the immune biophenotype in schizophrenia and develop better selection procedures for clinical trials with anti-inflammatory and immune-modulating drugs. In this focused review, we describe available methods to assess inflammatory status and immune disturbances in vivo. We also outline findings of immune disturbances and signs of inflammation at cellular, protein, and brain imaging levels in patients with schizophrenia. Furthermore, we summarize the results from studies with anti-inflammatory or other immune-modulating drugs, highlighting how such studies have dealt with participant selection. Finally, we propose a strategy to construct an immune signature that may be helpful in selecting and monitoring participants in studies with immune modulating drugs and also applicable in regular clinical work.