The potential of baicalin to enhance neuroprotection and mitochondrial function in a human neuronal cell model.

Baicalin is a flavone glycoside derived from flowering plants belonging to the Scutellaria genus. Previous studies have reported baicalin's anti-inflammatory and neuroprotective properties in rodent models, indicating the potential of baicalin in neuropsychiatric disorders where alterations in numerous processes are observed. However, the extent of baicalin's therapeutic effects remains undetermined in a human cell model, more specifically, neuronal cells to mimic the brain environment in vitro. As a proof of concept, we treated C8-B4 cells (murine cell model) with three different doses of baicalin (0.1, 1 and 5 µM) and vehicle control (DMSO) for 24 h after liposaccharide-induced inflammation and measured the levels of TNF-α in the medium by ELISA. NT2-N cells (human neuronal-like cell model) underwent identical baicalin treatment, followed by RNA extraction, genome-wide mRNA expression profiles and gene set enrichment analysis (GSEA). We also performed neurite outgrowth assays and mitochondrial flux bioanalysis (Seahorse) in NT2-N cells. We found that in C8-B4 cells, baicalin at ≥ 1 µM exhibited anti-inflammatory effects, lowering TNF-α levels in the cell culture media. In NT2-N cells, baicalin positively affected neurite outgrowth and transcriptionally up-regulated genes in the tricarboxylic acid cycle and the glycolysis pathway. Similarly, Seahorse analysis showed increased oxygen consumption rate in baicalin-treated NT2-N cells, an indicator of enhanced mitochondrial function. Together, our findings have confirmed the neuroprotective and mitochondria enhancing effects of baicalin in human-neuronal like cells. Given the increased prominence of mitochondrial mechanisms in diverse neuropsychiatric disorders and the paucity of mitochondrial therapeutics, this suggests the potential therapeutic application of baicalin in human neuropsychiatric disorders where these processes are altered.

Network-based drug repurposing for schizophrenia.

Despite recent progress, the challenges in drug discovery for schizophrenia persist. However, computational drug repurposing has gained popularity as it leverages the wealth of expanding biomedical databases. Network analyses provide a comprehensive understanding of transcription factor (TF) regulatory effects through gene regulatory networks, which capture the interactions between TFs and target genes by integrating various lines of evidence. Using the PANDA algorithm, we examined the topological variances in TF-gene regulatory networks between individuals with schizophrenia and healthy controls. This algorithm incorporates binding motifs, protein interactions, and gene co-expression data. To identify these differences, we subtracted the edge weights of the healthy control network from those of the schizophrenia network. The resulting differential network was then analysed using the CLUEreg tool in the GRAND database. This tool employs differential network signatures to identify drugs that potentially target the gene signature associated with the disease. Our analysis utilised a large RNA-seq dataset comprising 532 post-mortem brain samples from the CommonMind project. We constructed co-expression gene regulatory networks for both schizophrenia cases and healthy control subjects, incorporating 15,831 genes and 413 overlapping TFs. Through drug repurposing, we identified 18 promising candidates for repurposing as potential treatments for schizophrenia. The analysis of TF-gene regulatory networks revealed that the TFs in schizophrenia predominantly regulate pathways associated with energy metabolism, immune response, cell adhesion, and thyroid hormone signalling. These pathways represent significant targets for therapeutic intervention. The identified drug repurposing candidates likely act through TF-targeted pathways. These promising candidates, particularly those with preclinical evidence such as rimonabant and kaempferol, warrant further investigation into their potential mechanisms of action and efficacy in alleviating the symptoms of schizophrenia.

Use of gene regulatory network analysis to repurpose drugs to treat bipolar disorder.

BACKGROUND: Bipolar disorder (BD) presents significant challenges in drug discovery, necessitating alternative approaches. Drug repurposing, leveraging computational techniques and expanding biomedical data, holds promise for identifying novel treatment strategies. METHODS: This study utilized gene regulatory networks (GRNs) to identify significant regulatory changes in BD, using network-based signatures for drug repurposing. Employing the PANDA algorithm, we investigated the variations in transcription factor-GRNs between individuals with BD and unaffected individuals, incorporating binding motifs, protein interactions, and gene co-expression data. The differences in edge weights between BD and controls were then used as differential network signatures to identify drugs potentially targeting the disease-associated gene signature, employing the CLUEreg tool in the GRAND database. RESULTS: Using a large RNA-seq dataset of 216 post-mortem brain samples from the CommonMind consortium, we constructed GRNs based on co-expression for individuals with BD and unaffected controls, involving 15,271 genes and 405 TFs. Our analysis highlighted significant influences of these TFs on immune response, energy metabolism, cell signalling, and cell adhesion pathways in the disorder. By employing drug repurposing, we identified 10 promising candidates potentially repurposed as BD treatments. LIMITATIONS: Non-drug-naïve transcriptomics data, bulk analysis of BD samples, potential bias of GRNs towards well-studied genes. CONCLUSIONS: Further investigation into repurposing candidates, especially those with preclinical evidence supporting their efficacy, like kaempferol and pramocaine, is warranted to understand their mechanisms of action and effectiveness in treating BD. Additionally, novel targets such as PARP1 and A2b offer opportunities for future research on their relevance to the disorder.

Effects of antipsychotic drugs on energy metabolism.

Schizophrenia (SCZ) is a complex neuropsychiatric disorder associated with altered bioenergetic pathways and mitochondrial dysfunction. Antipsychotic medications, both first and second-generation, are commonly prescribed to manage SCZ symptoms, but their direct impact on mitochondrial function remains poorly understood. In this study, we investigated the effects of commonly prescribed antipsychotics on bioenergetic pathways in cultured neurons. We examined the impact of risperidone, aripiprazole, amisulpride, and clozapine on gene expression, mitochondrial bioenergetic profile, and targeted metabolomics after 24-h treatment, using RNA-seq, Seahorse XF24 Flux Analyser, and gas chromatography-mass spectrometry (GC-MS), respectively. Risperidone treatment reduced the expression of genes involved in oxidative phosphorylation, the tricarboxylic acid cycle, and glycolysis pathways, and it showed a tendency to decrease basal mitochondrial respiration. Aripiprazole led to dose-dependent reductions in various mitochondrial function parameters without significantly affecting gene expression. Aripiprazole, amisulpride and clozapine treatment showed an effect on the tricarboxylic acid cycle metabolism, leading to more abundant metabolite levels. Antipsychotic drug effects on mitochondrial function in SCZ are multifaceted. While some drugs have greater effects on gene expression, others appear to exert their effects through enzymatic post-translational or allosteric modification of enzymatic activity. Understanding these effects is crucial for optimising treatment strategies for SCZ. Novel therapeutic interventions targeting energy metabolism by post-transcriptional pathways might be more effective as these can more directly and efficiently regulate energy production.

Metergoline Shares Properties with Atypical Antipsychotic Drugs Identified by Gene Expression Signature Screen.

Novel approaches are required to find new treatments for schizophrenia and other neuropsychiatric disorders. This study utilised a combination of in vitro transcriptomics and in silico analysis with the BROAD Institute's Connectivity Map to identify drugs that can be repurposed to treat psychiatric disorders. Human neuronal (NT2-N) cells were treated with a combination of atypical antipsychotic drugs commonly used to treat psychiatric disorders (such as schizophrenia, bipolar disorder, and major depressive disorder), and differential gene expression was analysed. Biological pathways with an increased gene expression included circadian rhythm and vascular endothelial growth factor signalling, while the adherens junction and cell cycle pathways were transcriptionally downregulated. The Connectivity Map (CMap) analysis screen highlighted drugs that affect global gene expression in a similar manner to these psychiatric disorder treatments, including several other antipsychotic drugs, confirming the utility of this approach. The CMap screen specifically identified metergoline, an ergot alkaloid currently used to treat seasonal affective disorder, as a drug of interest. In mice, metergoline dose-dependently reduced MK-801- or methamphetamine-induced locomotor hyperactivity confirming the potential of metergoline to treat positive symptoms of schizophrenia in an animal model. Metergoline had no effects on prepulse inhibition deficits induced by MK-801 or methamphetamine. Taken together, metergoline appears a promising drug for further studies to be repurposed as a treatment for schizophrenia and possibly other psychiatric disorders.

Metabolic regulation to treat bipolar depression: mechanisms and targeting by trimetazidine.

Bipolar disorder's core feature is the pathological disturbances in mood, often accompanied by disrupted thinking and behavior. Its complex and heterogeneous etiology implies that a range of inherited and environmental factors are involved. This heterogeneity and poorly understood neurobiology pose significant challenges to existing drug development paradigms, resulting in scarce treatment options, especially for bipolar depression. Therefore, novel approaches are needed to discover new treatment options. In this review, we first highlight the main molecular mechanisms known to be associated with bipolar depression-mitochondrial dysfunction, inflammation and oxidative stress. We then examine the available literature for the effects of trimetazidine in said alterations. Trimetazidine was identified without a priori hypothesis using a gene-expression signature for the effects of a combination of drugs used to treat bipolar disorder and screening a library of off-patent drugs in cultured human neuronal-like cells. Trimetazidine is used to treat angina pectoris for its cytoprotective and metabolic effects (improved glucose utilization for energy production). The preclinical and clinical literature strongly support trimetazidine's potential to treat bipolar depression, having anti-inflammatory and antioxidant properties while normalizing mitochondrial function only when it is compromised. Further, trimetazidine's demonstrated safety and tolerability provide a strong rationale for clinical trials to test its efficacy to treat bipolar depression that could fast-track its repurposing to address such an unmet need as bipolar depression.

Use of a gene expression signature to identify trimetazidine for repurposing to treat bipolar depression.

OBJECTIVES: The aim of this study was to repurpose a drug for the treatment of bipolar depression. METHODS: A gene expression signature representing the overall transcriptomic effects of a cocktail of drugs widely prescribed to treat bipolar disorder was generated using human neuronal-like (NT2-N) cells. A compound library of 960 approved, off-patent drugs were then screened to identify those drugs that affect transcription most similar to the effects of the bipolar depression drug cocktail. For mechanistic studies, peripheral blood mononuclear cells were obtained from a healthy subject and reprogrammed into induced pluripotent stem cells, which were then differentiated into co-cultured neurons and astrocytes. Efficacy studies were conducted in two animal models of depressive-like behaviours (Flinders Sensitive Line rats and social isolation with chronic restraint stress rats). RESULTS: The screen identified trimetazidine as a potential drug for repurposing. Trimetazidine alters metabolic processes to increase ATP production, which is thought to be deficient in bipolar depression. We showed that trimetazidine increased mitochondrial respiration in cultured human neuronal-like cells. Transcriptomic analysis in induced pluripotent stem cell-derived neuron/astrocyte co-cultures suggested additional mechanisms of action via the focal adhesion and MAPK signalling pathways. In two different rodent models of depressive-like behaviours, trimetazidine exhibited antidepressant-like activity with reduced anhedonia and reduced immobility in the forced swim test. CONCLUSION: Collectively our data support the repurposing of trimetazidine for the treatment of bipolar depression.

Minocycline as Treatment for Psychiatric and Neurological Conditions: A Systematic Review and Meta-Analysis.

Minocycline has anti-inflammatory, antioxidant, and anti-apoptotic properties that explain the renewed interest in its use as an adjunctive treatment for psychiatric and neurological conditions. Following the completion of several new clinical trials using minocycline, we proposed an up-to-date systematic review and meta-analysis of the data available. The PICO (patient/population, intervention, comparison and outcomes) framework was used to search 5 databases aiming to identify randomized controlled trials that used minocycline as an adjunctive treatment for psychiatric and neurological conditions. Search results, data extraction, and risk of bias were performed by two independent authors for each publication. Quantitative meta-analysis was performed using RevMan software. Literature search and review resulted in 32 studies being included in this review: 10 in schizophrenia, 3 studies in depression, and 7 in stroke, with the benefit of minocycline being used in some of the core symptoms evaluated; 2 in bipolar disorder and 2 in substance use, without demonstrating a benefit for using minocycline; 1 in obsessive-compulsive disorder, 2 in brain and spinal injuries, 2 in amyotrophic lateral sclerosis, 1 in Alzheimer's disease, 1 in multiple systems atrophy, and 1 in pain, with mixes results. For most of the conditions included in this review the data is still limited and difficult to interpret, warranting more well-designed and powered studies. On the other hand, the studies available for schizophrenia seem to suggest an overall benefit favoring the use of minocycline as an adjunctive treatment.

Metformin is Protective Against the Development of Mood Disorders.

INTRODUCTION: Mood disorders are a major cause of disability, and current treatment options are inadequate for reducing the burden on a global scale. The aim of this project was to identify drugs suitable for repurposing to treat mood disorders. METHODS: This mixed-method study utilized gene expression signature technology and pharmacoepidemiology to investigate drugs that may be suitable for repurposing to treat mood disorders. RESULTS: The transcriptional effects of a combination of drugs commonly used to treat mood disorders included regulation of the steroid and terpenoid backbone biosynthesis pathways, suggesting a mechanism involving cholesterol biosynthesis, and effects on the thyroid hormone signaling pathway. Connectivity Map analysis highlighted metformin, an FDA-approved treatment for type 2 diabetes, as a drug having global transcriptional effects similar to the mood disorder drug combination investigated. In a retrospective cohort study, we found evidence that metformin is protective against the onset of mood disorders. DISCUSSION: These results provide proof-of-principle of combining gene expression signature technology with pharmacoepidemiology to identify potential novel drugs for treating mood disorders. Importantly, metformin may have utility in the treatment of mood disorders, warranting future randomized controlled trials to test its efficacy.

Effects of Psychotropic Drugs on Ribosomal Genes and Protein Synthesis.

Altered protein synthesis has been implicated in the pathophysiology of several neuropsychiatric disorders, particularly schizophrenia. Ribosomes are the machinery responsible for protein synthesis. However, there remains little information on whether current psychotropic drugs affect ribosomes and contribute to their therapeutic effects. We treated human neuronal-like (NT2-N) cells with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), valproate (0.5 mM) or vehicle control for 24 h. Transcriptomic and gene set enrichment analysis (GSEA) identified that the ribosomal pathway was altered by these drugs. We found that three of the eight drugs tested significantly decreased ribosomal gene expression, whilst one increased it. Most changes were observed in the components of cytosolic ribosomes and not mitochondrial ribosomes. Protein synthesis assays revealed that aripiprazole, clozapine and lithium all decreased protein synthesis. Several currently prescribed psychotropic drugs seem to impact ribosomal gene expression and protein synthesis. This suggests the possibility of using protein synthesis inhibitors as novel therapeutic agents for neuropsychiatric disorders.

Repurposing Drugs via Network Analysis: Opportunities for Psychiatric Disorders.

Despite advances in pharmacology and neuroscience, the path to new medications for psychiatric disorders largely remains stagnated. Drug repurposing offers a more efficient pathway compared with de novo drug discovery with lower cost and less risk. Various computational approaches have been applied to mine the vast amount of biomedical data generated over recent decades. Among these methods, network-based drug repurposing stands out as a potent tool for the comprehension of multiple domains of knowledge considering the interactions or associations of various factors. Aligned well with the poly-pharmacology paradigm shift in drug discovery, network-based approaches offer great opportunities to discover repurposing candidates for complex psychiatric disorders. In this review, we present the potential of network-based drug repurposing in psychiatry focusing on the incentives for using network-centric repurposing, major network-based repurposing strategies and data resources, applications in psychiatry and challenges of network-based drug repurposing. This review aims to provide readers with an update on network-based drug repurposing in psychiatry. We expect the repurposing approach to become a pivotal tool in the coming years to battle debilitating psychiatric disorders.

Integrative Analyses of Transcriptomes to Explore Common Molecular Effects of Antipsychotic Drugs.

There is little understanding of the underlying molecular mechanism(s) involved in the clinical efficacy of antipsychotics for schizophrenia. This study integrated schizophrenia-associated transcriptional perturbations with antipsychotic-induced gene expression profiles to detect potentially relevant therapeutic targets shared by multiple antipsychotics. Human neuronal-like cells (NT2-N) were treated for 24 h with one of the following antipsychotic drugs: amisulpride, aripiprazole, clozapine, risperidone, or vehicle controls. Drug-induced gene expression patterns were compared to schizophrenia-associated transcriptional data in post-mortem brain tissues. Genes regulated by each of four antipsychotic drugs in the reverse direction to schizophrenia were identified as potential therapeutic-relevant genes. A total of 886 genes were reversely expressed between at least one drug treatment (versus vehicle) and schizophrenia (versus healthy control), in which 218 genes were commonly regulated by all four antipsychotic drugs. The most enriched biological pathways include Wnt signaling and action potential regulation. The protein-protein interaction (PPI) networks found two main clusters having schizophrenia expression quantitative trait loci (eQTL) genes such as PDCD10, ANK2, and AKT3, suggesting further investigation on these genes as potential novel treatment targets.

Co-Expression Networks Unveiled Long Non-Coding RNAs as Molecular Targets of Drugs Used to Treat Bipolar Disorder.

Long non-coding RNAs (lncRNAs) may play a role in psychiatric diseases including bipolar disorder (BD). We investigated mRNA-lncRNA co-expression patterns in neuronal-like cells treated with widely prescribed BD medications. The aim was to unveil insights into the complex mechanisms of BD medications and highlight potential targets for new drug development. Human neuronal-like (NT2-N) cells were treated with either lamotrigine, lithium, quetiapine, valproate or vehicle for 24 h. Genome-wide mRNA expression was quantified for weighted gene co-expression network analysis (WGCNA) to correlate the expression levels of mRNAs with lncRNAs. Functional enrichment analysis and hub lncRNA identification was conducted on key co-expressed modules associated with the drug response. We constructed lncRNA-mRNA co-expression networks and identified key modules underlying these treatments, as well as their enriched biological functions. Processes enriched in key modules included synaptic vesicle cycle, endoplasmic reticulum-related functions and neurodevelopment. Several lncRNAs such as GAS6-AS1 and MIR100HG were highlighted as driver genes of key modules. Our study demonstrates the key role of lncRNAs in the mechanism(s) of action of BD drugs. Several lncRNAs have been suggested as major regulators of medication effects and are worthy of further investigation as novel drug targets to treat BD.

Common effects of bipolar disorder medications on expression quantitative trait loci genes.

The molecular mechanism(s) underpinning the clinical efficacy of the current drugs for bipolar disorder (BD) are largely unknown. This study evaluated the transcriptional perturbations potentially playing roles in the therapeutic efficacy of four commonly prescribed psychotropic drugs used to treat BD. NT2-N cells were treated with lamotrigine, lithium, quetiapine, valproate or vehicle control for 24 h. Genome-wide mRNA expression was quantified by RNA-sequencing. Incorporating drug-induced gene expression profiles with BD-associated transcriptional changes from post-mortem brains, we identified potential therapeutic-relevant genes associated with both drug treatments and BD pathophysiology and focused on expression quantitative trait loci (eQTL) genes with genome-wide association with BD. Each eQTL gene was ranked based on its potential role in the therapeutic effect across multiple drugs. The expression of highest-ranked eQTL genes were measured by RT-qPCR to confirm their transcriptional changes observed in RNA-seq. We found 775 genes for which at least 2 drugs reversed expression levels relative to the differential expression in post-mortem brains. Pathway analysis identified enriched biological processes highlighting mitochondrial and endoplasmic reticulum function. Differential expression of SRPK2 and CHDH was confirmed by RT-qPCR following multiple-dose treatments. We pinpointed potential genes involved in the beneficial effects of drugs used for BD and their main associated biological pathways. CHDH, which encodes a mitochondrial protein, had a significant dose-responsive downregulation following treatment with increasing doses of quetiapine and lamotrigine, which in combination with the enriched mitochondrial pathways suggests potential therapeutic roles and demand more studies on mitochondrial involvement in BD to identify novel treatment targets.

Cannabinoid receptor gene polymorphisms and cognitive performance in patients with schizophrenia and controls

Objective: To test the hypothesis that genetic variations of cannabinoid receptors contribute to the pathophysiology of cognitive deficits in schizophrenia. Methods: In this genetic association case-control study, cannabinoid receptor polymorphisms CNR1 rs12720071 and CNR2 rs2229579 were tested for association with neurocognitive performance in 69 patients with schizophrenia and 45 healthy controls. Neurocognition was assessed by the Brief Assessment of Cognition in Schizophrenia (BACS). Results: We found a consistent association between CNR1 rs12720071 polymorphism and the cognitive performance of patients in several cognitive domains. Patients with C/C polymorphism presented significantly worse performance in motor speed, verbal fluency, attention/processing speed and reasoning/problem solving. Conclusion: Although limited, our data support the hypothesis that CNR1 variations may be associated with the pathogenesis of cognitive deficits of schizophrenia.

Cannabinoid receptor gene polymorphisms and cognitive performance in patients with schizophrenia and controls.

OBJECTIVE: To test the hypothesis that genetic variations of cannabinoid receptors contribute to the pathophysiology of cognitive deficits in schizophrenia. METHODS: In this genetic association case-control study, cannabinoid receptor polymorphisms CNR1 rs12720071 and CNR2 rs2229579 were tested for association with neurocognitive performance in 69 patients with schizophrenia and 45 healthy controls. Neurocognition was assessed by the Brief Assessment of Cognition in Schizophrenia (BACS). RESULTS: We found a consistent association between CNR1 rs12720071 polymorphism and the cognitive performance of patients in several cognitive domains. Patients with C/C polymorphism presented significantly worse performance in motor speed, verbal fluency, attention/processing speed and reasoning/problem solving. CONCLUSION: Although limited, our data support the hypothesis that CNR1 variations may be associated with the pathogenesis of cognitive deficits of schizophrenia.

Biological Mechanism(s) Underpinning the Association between Antipsychotic Drugs and Weight Gain.

Weight gain and consequent metabolic alterations are common side-effects of many antipsychotic drugs. Interestingly, several studies have suggested that improvement in symptoms and adverse metabolic effects are correlated. We used next generation sequencing data from NT-2 (human neuronal) cells treated with aripiprazole, amisulpride, risperidone, quetiapine, clozapine, or vehicle control, and compared with the Pillinger P-score (ranked from 0 to 1, indicating greater increase in weight gain and related metabolic parameters) to identify the genes most associated with the drugs' propensity to cause weight gain. The top 500 genes ranked for their correlation with the drugs' propensity to cause weight gain were subjected to pathway analysis using DAVID (NIH). We further investigated transcription factors (TFs) that are more likely to regulate the genes involved in these processes using the prediction tool of key TFs from TRRUST. The results suggest an enrichment for genes involved in lipid biosynthesis and metabolism, which are of interest for mechanisms underpinning weight-gain. The list of genes involved in the lipid pathways that correlated with weight gain was enriched for genes transcriptionally regulated by SREBF1 and SREBF2. Furthermore, quetiapine significantly increased the expression of SREBF1 and SREBF2 in NT-2 cells. Our results suggest that the effects of these antipsychotic drugs on lipid metabolism may be mediated, at least in part, via regulation of SREBF1/SREBF2 expression, with evidence of a direct effect of quetiapine on the expression of SREBF1/2. The effects of antipsychotic drugs on lipid metabolism may influence white matter structure (therapeutic effect) and the risk of weight gain, lipid disturbances, and, consequently, metabolic syndrome (adverse effects). Understanding the different molecular effects of these drugs could inform a personalized medicine approach in treating patients with schizophrenia.

Transcriptional Modulation of the Hippo Signaling Pathway by Drugs Used to Treat Bipolar Disorder and Schizophrenia.

Recent reports suggest a link between positive regulation of the Hippo pathway with bipolar disorder (BD), and the Hippo pathway is known to interact with multiple other signaling pathways previously associated with BD and other psychiatric disorders. In this study, neuronal-like NT2 cells were treated with amisulpride (10 µM), aripiprazole (0.1 µM), clozapine (10 µM), lamotrigine (50 µM), lithium (2.5 mM), quetiapine (50 µM), risperidone (0.1 µM), valproate (0.5 mM), or vehicle control for 24 h. Genome-wide mRNA expression was quantified and analyzed using gene set enrichment analysis (GSEA), with genes belonging to Hippo, Wnt, Notch, TGF- ß, and Hedgehog retrieved from the KEGG database. Five of the eight drugs downregulated the genes of the Hippo pathway and modulated several genes involved in the interacting pathways. We speculate that the regulation of these genes, especially by aripiprazole, clozapine, and quetiapine, results in a reduction of MAPK and NFκB pro-inflammatory signaling through modulation of Hippo, Wnt, and TGF-ß pathways. We also employed connectivity map analysis to identify compounds that act on these pathways in a similar manner to the known psychiatric drugs. Thirty-six compounds were identified. The presence of antidepressants and antipsychotics validates our approach and reveals possible new targets for drug repurposing.

Cortical volume is inversely correlated with interleukin-6 serum levels in patients with schizophrenia

Introduction: It is well established that cortical volume are decreased in patients with schizophrenia. One possible explanation is that the increased pro-inflammatory status in schizophrenia is related to volumetric decrease of gray matter. The aim of this study was to correlate interleukin 6 (IL-6) with cortical volume in patients with schizophrenia and controls. Methods: We selected 36 patients with schizophrenia and 35 controls. Interleukin 6 (IL-6) was correlated with cortical volume in patients with schizophrenia and controls. Results: IL-6 was negatively correlated with cortical volume (p = 0.027; rho = −0.370) in patients, but not in controls (p = 0.235). Discussion: Our results are in line with previous studies suggesting that chronic inflammatory activation in patients with schizophrenia could be one plausible mechanism that could contribute for the cortical volumetric decrease often seen in this population. However, this cross-sectional study with a small number of patients does not allow us to establish causal relations. (AU)

Aleitamento materno e quimiocinas: diferenças entre esquizofrenia e controles / Breastfeeding and chemokines: differences in schizophrenia and controls

Introdução: Avaliar a associação entre níveis plasmáticos da quimiocina CCL11, coeficiente de inteligência e prática da amamentação em homens com esquizofrenia em condições psiquiátricas estáveis sob acompanhamento ambulatorial em um serviço de saúde pública. Métodos: Foi realizado estudo caso-controle com 60 indivíduos: 30 pacientes com esquizofrenia e 30 controles saudáveis, dos quais 15 de cada grupo foram expostos ao aleitamento materno e 15 não foram. Foi aplicado questionário abordando questões socioeconômicas, história ao nascer, dados clínicos e alimentação ao nascer. Foi dosada a quimiocina CCL11 e aplicados testes psicológicos para avaliar quociente de inteligência, funcionalidade, sintomas psiquiátricos, curso da doença e diagnóstico. Para os controles, foi utilizada uma escala para descartar doença psiquiátrica. Resultados: A quimiocina CCL11 apresentou valores significativamente mais altos (> 0,5) em pacientes com esquizofrenia quando comparados aos controles. No grupo de amamentados, os esquizofrênicos apresentaram valores significativamente mais altos a nível intermediário (entre 0.106 e 0.5). Não houve correlação da CCL11 com o número de hospitalizações, idade, tempo de diagnóstico e escolaridade. Não foi evidenciada correlação entre tempo de aleitamento materno em relação aos fatores do Brief Psychiatric Rating Scale. Houve uma tendência de correlação entre a idade de início da doença e o aleitamento materno. Foi encontrada correlação positiva do CCL11 com o tempo de aleitamento materno. Ao comparar os pacientes esquizofrênicos que foram aleitados com os que não foram, foi encontrada diferença estatisticamente significativa apenas para o quociente de inteligência. Conclusão: O aleitamento materno está associado a níveis mais baixos de CCL11, escores mais altos de quociente de inteligência e a esquizofrenia. A quimiocina CCL11 é mais alta em quem não amamentou, especialmente nos esquizofrênicos. (AU)

Introduction: To evaluate the association between plasma levels of chemokine CCL11, intelligence quotient, and exposure to breastfeeding in men with schizophrenia under stable psychiatric condition and monitored as outpatients in a public health care unit. Methods: A case-control study of 60 individuals, 30 patients with schizophrenia and 30 healthy controls; in each group, 15 were exposed to breastfeeding and 15 were not. A questionnaire addressing socioeconomic issues, history at birth, clinical data, and feeding at birth was administered. Chemokine CCL11 levels were measured, and psychological tests were applied to assess intelligence quotient, functional status, psychiatric symptoms, disease course, and diagnosis. A scale to rule psychiatric illness was used for the controls. Results: Chemokine CCL11 levels were significantly higher (> 0.5) in patients with schizophrenia than in controls. In the breastfed group, patients with schizophrenia also had significantly higher CCL11 levels, but at an intermediate level (between 0.106 and 0.5). There was no correlation between CCL11 and number of hospitalizations, age, time since diagnosis, or level of education, nor between duration of breastfeeding and the Brief Psychiatric Rating Scale factors. A trend toward a correlation was observed between age at disease onset and breastfeeding. There was a positive correlation between CCL11 and duration of breastfeeding. The comparison of patients with schizophrenia who were breastfed vs those who were not breastfed showed a statistically significant difference only in intelligence quotient. Conclusion: Breastfeeding is associated with lower CCL11 levels, higher intelligence quotient scores, and schizophrenia. Chemokine CCL11 levels are higher in those not exposed to breastfeeding, especially in patients with schizophrenia. (AU)