Peripheral inflammation is associated with impaired sadness recognition in euthymic bipolar patients.

BACKGROUND: Inflammation impairs cognitive function in healthy individuals and people with psychiatric disorders, such as bipolar disorder (BD). This effect may also impact emotion recognition, a fundamental element of social cognition. Our study aimed to investigate the relationships between pro-inflammatory cytokines and emotion recognition in euthymic BD patients and healthy controls (HCs). METHODS: We recruited forty-four euthymic BD patients and forty healthy controls (HCs) and measured their inflammatory markers, including high-sensitivity C-reactive protein (hs-CRP), interleukin-6 (IL-6), and TNF-α. We applied validated cognitive tasks, the Wisconsin Card-Sorting Test (WCST) and Continuous Performance Test (CPT), and a social cognitive task for emotion recognition, Diagnostic Analyses of Nonverbal Accuracy, Taiwanese Version (DANVA-2-TW). We analyzed the relationships between cytokines and cognition and then explored possible predictive factors of sadness recognition accuracy. RESULTS: Regarding pro-inflammatory cytokines, TNF-α was elevated in euthymic BD patients relative to HCs. In euthymic BD patients only, higher TNF-α levels were associated with lower accuracy of sadness recognition. Regression analysis revealed that TNF-α was an independent predictive factor of sadness recognition in patients with euthymic BD when neurocognition was controlled for. CONCLUSIONS: We demonstrated that enhanced inflammation, indicated by increased TNF-α, was an independent predictive factor of impaired sadness recognition in BD patients but not in HCs. Our findings suggested a direct influence of TNF-α on sadness recognition and indicated vulnerability to depression in euthymic BD patients with chronic inflammation.

Identifying plasma metabolic characteristics of major depressive disorder, bipolar disorder, and schizophrenia in adolescents.

Major depressive disorder (MDD), bipolar disorder (BD), and schizophrenia (SCZ) are classified as major mental disorders and together account for the second-highest global disease burden, and half of these patients experience symptom onset in adolescence. Several studies have reported both similar and unique features regarding the risk factors and clinical symptoms of these three disorders. However, it is still unclear whether these disorders have similar or unique metabolic characteristics in adolescents. We conducted a metabolomics analysis of plasma samples from adolescent healthy controls (HCs) and patients with MDD, BD, and SCZ. We identified differentially expressed metabolites between patients and HCs. Based on the differentially expressed metabolites, correlation analysis, metabolic pathway analysis, and potential diagnostic biomarker identification were conducted for disorders and HCs. Our results showed significant changes in plasma metabolism between patients with these mental disorders and HCs; the most distinct changes were observed in SCZ patients. Moreover, the metabolic differences in BD patients shared features with those in both MDD and SCZ, although the BD metabolic profile was closer to that of MDD than to SCZ. Additionally, we identified the metabolites responsible for the similar and unique metabolic characteristics in multiple metabolic pathways. The similar significant differences among the three disorders were found in fatty acid, steroid-hormone, purine, nicotinate, glutamate, tryptophan, arginine, and proline metabolism. Interestingly, we found unique characteristics of significantly altered glycolysis, glycerophospholipid, and sphingolipid metabolism in SCZ; lysine, cysteine, and methionine metabolism in MDD and BD; and phenylalanine, tyrosine, and aspartate metabolism in SCZ and BD. Finally, we identified five panels of potential diagnostic biomarkers for MDD-HC, BD-HC, SCZ-HC, MDD-SCZ, and BD-SCZ comparisons. Our findings suggest that metabolic characteristics in plasma vary across psychiatric disorders and that critical metabolites provide new clues regarding molecular mechanisms in these three psychiatric disorders.

Coexpression network analysis of the adult brain sheds light on the pathogenic mechanism of DDR1 in schizophrenia and bipolar disorder.

DDR1 has been linked to schizophrenia (SCZ) and bipolar disorder (BD) in association studies. DDR1 encodes 58 distinct transcripts, which can be translated into five isoforms (DDR1a-e) and are expressed in the brain. However, the transcripts expressed in each brain cell type, their functions and their involvement in SCZ and BD remain unknown. Here, to infer the processes in which DDR1 transcripts are involved, we used transcriptomic data from the human brain dorsolateral prefrontal cortex of healthy controls (N = 936) and performed weighted gene coexpression network analysis followed by enrichment analyses. Then, to explore the involvement of DDR1 transcripts in SCZ (N = 563) and BD (N = 222), we studied the association of coexpression modules with disease and performed differential expression and transcript significance analyses. Some DDR1 transcripts were distributed across five coexpression modules identified in healthy controls (MHC). MHC1 and MHC2 were enriched in the cell cycle and proliferation of astrocytes and OPCs; MHC3 and MHC4 were enriched in oligodendrocyte differentiation and myelination; and MHC5 was enriched in neurons and synaptic transmission. Most of the DDR1 transcripts associated with SCZ and BD pertained to MHC1 and MHC2. Altogether, our results suggest that DDR1 expression might be altered in SCZ and BD via the proliferation of astrocytes and OPCs, suggesting that these processes are relevant in psychiatric disorders.

Using the Bayesian variational spike and slab model in a genome-wide association study for finding associated loci with bipolar disorder.

OBJECTIVE: The genome-wide association studies (GWAS) analysis, the most successful technique for discovering disease-related genetic variation, has some statistical concerns, including multiple testing, the correlation among variants (single-nucleotide polymorphisms) based on linkage disequilibrium and omitting the important variants when fitting the model with just one variant. To eliminate these problems in a small sample-size study, we used a sparse Bayesian learning model for finding bipolar disorder (BD) genetic variants. METHODS: This study used the Wellcome Trust Case Control Consortium data set, including 1998 BD cases and 1500 control samples, and after quality control, 380,628 variants were analysed. In this GWAS, a Bayesian logistic model with hierarchical shrinkage spike and slab priors was used, with all variants considered simultaneously in one model. In order to decrease the computational burden, an alternative inferential method, Bayesian variational inference, has been used. RESULTS: Thirteen variants were selected as associated with BD. The three of them (rs7572953, rs1378850 and rs4148944) were reported in previous GWAS. Eight of which were related to hemogram parameters, such as lymphocyte percentage, plateletcrit and haemoglobin concentration. Among selected related genes, GABPA, ELF3 and JAM2 were enriched in the platelet-derived growth factor pathway. These three genes, along with APP, ARL8A, CDH23 and GPR37L1, could be differential diagnostic variants for BD. CONCLUSIONS: By reducing the statistical restrictions of GWAS analysis, the application of the Bayesian variational spike and slab models can offer insight into the genetic link with BD even with a small sample size. To uncover related variations with other traits, this model needs to be further examined.

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.

Evaluation of a Nondepleted Plasma Multiprotein-Based Model for Discriminating Psychiatric Disorders Using Multiple Reaction Monitoring-Mass Spectrometry: Proof-of-Concept Study.

Psychiatric evaluation relies on subjective symptoms and behavioral observation, which sometimes leads to misdiagnosis. Despite previous efforts to utilize plasma proteins as objective markers, the depletion method is time-consuming. Therefore, this study aimed to enhance previous quantification methods and construct objective discriminative models for major psychiatric disorders using nondepleted plasma. Multiple reaction monitoring-mass spectrometry (MRM-MS) assays for quantifying 453 peptides in nondepleted plasma from 132 individuals [35 major depressive disorder (MDD), 47 bipolar disorder (BD), 23 schizophrenia (SCZ) patients, and 27 healthy controls (HC)] were developed. Pairwise discriminative models for MDD, BD, and SCZ, and a discriminative model between patients and HC were constructed by machine learning approaches. In addition, the proteins from nondepleted plasma-based discriminative models were compared with previously developed depleted plasma-based discriminative models. Discriminative models for MDD versus BD, BD versus SCZ, MDD versus SCZ, and patients versus HC were constructed with 11 to 13 proteins and showed reasonable performances (AUROC = 0.890-0.955). Most of the shared proteins between nondepleted and depleted plasma models had consistent directions of expression levels and were associated with neural signaling, inflammatory, and lipid metabolism pathways. These results suggest that multiprotein markers from nondepleted plasma have a potential role in psychiatric evaluation.

An overview of metabolomic and proteomic profiling in bipolar disorder and its clinical value.

INTRODUCTION: Bipolar disorder (BD) is a complex psychiatric disease characterized by alternating mood episodes. As for any other psychiatric illness, currently there is no biochemical test that is able to support diagnosis or therapeutic decisions for BD. In this context, the discovery and validation of biomarkers are interesting strategies that can be achieved through proteomics and metabolomics. AREAS COVERED: In this descriptive review, a literature search including original articles and systematic reviews published in the last decade was performed with the objective to discuss the results of BD proteomic and metabolomic profiling analyses and indicate proteins and metabolites (or metabolic pathways) with potential clinical value. EXPERT OPINION: A large number of proteins and metabolites have been reported as potential BD biomarkers; however, most studies do not reach biomarker validation stages. An effort from the scientific community should be directed toward the validation of biomarkers and the development of simplified bioanalytical techniques or protocols to determine them in biological samples, in order to translate proteomic and metabolomic findings into clinical routine assays.

Reverse cholesterol transport and lipid peroxidation biomarkers in major depression and bipolar disorder: A systematic review and meta-analysis.

BACKGROUND: Major depression (MDD) and bipolar disorder (BD) are linked to immune activation, increased oxidative stress, and lower antioxidant defenses. OBJECTIVES: To systematically review and meta-analyze all data concerning biomarkers of reverse cholesterol transport (RCT), lipid-associated antioxidants, lipid peroxidation products, and autoimmune responses to oxidatively modified lipid epitopes in MDD and BD. METHODS: Databases including PubMed, Google scholar and SciFinder were searched to identify eligible studies from inception to January 10th, 2023. Guidelines of Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. RESULTS: The current meta-analysis included 176 studies (60 BD and 116 MDD) and examined 34,051 participants, namely 17,094 with affective disorders and 16,957 healthy controls. Patients with MDD and BD showed a) significantly decreased RCT (mainly lowered high-density lipoprotein cholesterol and paraoxonase 1); b) lowered lipid soluble vitamins (including vitamin A, D, and coenzyme Q10); c) increased lipid peroxidation and aldehyde formation, mainly increased malondialdehyde (MDA), 4-hydroxynonenal, peroxides, and 8-isoprostanes; and d) Immunoglobulin (Ig)G responses to oxidized low-density lipoprotein and IgM responses to MDA. The ratio of all lipid peroxidation biomarkers/all lipid-associated antioxidant defenses was significantly increased in MDD (standardized mean difference or SMD = 0.433; 95% confidence intervals (CI): 0.312; 0.554) and BD (SMD = 0.653; CI: 0.501-0.806). This ratio was significantly greater in BD than MDD (p = 0.027). CONCLUSION: In MDD/BD, lowered RCT, a key antioxidant and anti-inflammatory pathway, may drive increased lipid peroxidation, aldehyde formation, and autoimmune responses to oxidative specific epitopes, which all together cause increased immune-inflammatory responses and neuro-affective toxicity.

Gene expression alterations in the postmortem hippocampus from older patients with bipolar disorder - A hypothesis generating study.

Bipolar disorder (BD) presents with a progressive course in a subset of patients. However, our knowledge of molecular changes in older BD is limited. In this study, we examined gene expression changes in the hippocampus of BD from the Biobank of Aging Studies to identify genes of interest that warrant further exploration. RNA was extracted from the hippocampus from 11 subjects with BD and 11 age and sex-matched controls. Gene expression data was generated using the SurePrint G3 Human Gene Expression v3 microarray. Rank feature selection was performed to identify a subset of features that can optimally differentiate BD and controls. Genes ranked in the top 0.1% with log2 fold change >1.2 were identified as genes of interest. Average age of the subjects was 64 years old; duration of disease was 21 years and 82% were female. Twenty-five genes were identified, of which all but one was downregulated in BD. Of these, CNTNAP4, MAP4, SLC4A1, COBL, and NEURL4 had been associated with BD and other psychiatric conditions in previous studies. We believe our findings have identified promising targets to inform future studies aiming to understand the pathophysiology of BD in later life.

Deregulation of NF-κB associated long non-coding RNAs in bipolar disorder.

Long non-coding RNAs (lncRNAs) are major genetic factors whose disruption lead to many diseases, including nervous system diseases. Bipolar disorder (BD) is a neuro-psychiatric disease with no definitive diagnosis and incomplete treatment. Regarding the role of NF-κB-associated lncRNAs in the neuro-psychiatric disorders, we examined the expression of three lncRNAs, DICER1-AS1, DILC, and CHAST, in BD patients. To assess lncRNA expression in peripheral blood mononuclear cells (PBMCs) of 50 BD patients and 50 healthy individuals, Real-time PCR was used. Additionally, some clinical characteristics of BD patients were investigated via an analysis of ROC curves and correlations. Based on our results, the expression level of CHAST increased significantly in BD patients in comparison with healthy people, in BD men compared with healthy men, as well as in BD women in comparison with control females (p < 0.05). A similar increase in expression was observed for DILC and DICER1-AS1 lncRNAs in female patients compared with healthy women. Whereas compared to healthy men, DILC was decreased in diseased men. Based on the results of the ROC curve, the area under the curve (AUC) for CHAST lncRNA was 0.83 with a P value of 0.0001. So, the expression level of CHAST lncRNA could play a role in the pathobiology of the BD and be considered a good putative biomarker for individuals with bipolar disorder.

Psychiatric polygenic risk as a predictor of COVID-19 risk and severity: insight into the genetic overlap between schizophrenia and COVID-19.

Despite the high contagion and mortality rates that have accompanied the coronavirus disease-19 (COVID-19) pandemic, the clinical presentation of the syndrome varies greatly from one individual to another. Potential host factors that accompany greater risk from COVID-19 have been sought and schizophrenia (SCZ) patients seem to present more severe COVID-19 than control counterparts, with certain gene expression similarities between psychiatric and COVID-19 patients reported. We used summary statistics from the last SCZ, bipolar disorder (BD), and depression (DEP) meta-analyses available on the Psychiatric Genomics Consortium webpage to calculate polygenic risk scores (PRSs) for a target sample of 11,977 COVID-19 cases and 5943 subjects with unknown COVID-19 status. Linkage disequilibrium score (LDSC) regression analysis was performed when positive associations were obtained from the PRS analysis. The SCZ PRS was a significant predictor in the case/control, symptomatic/asymptomatic, and hospitalization/no hospitalization analyses in the total and female samples; and of symptomatic/asymptomatic status in men. No significant associations were found for the BD or DEP PRS or in the LDSC regression analysis. SNP-based genetic risk for SCZ, but not for BD or DEP, may be associated with higher risk of SARS-CoV-2 infection and COVID-19 severity, especially among women; however, predictive accuracy barely exceeded chance level. We believe that the inclusion of sexual loci and rare variations in the analysis of genomic overlap between SCZ and COVID-19 will help to elucidate the genetic commonalities between these conditions.

Role of microtubule actin crosslinking factor 1 (MACF1) in bipolar disorder pathophysiology and potential in lithium therapeutic mechanism.

Bipolar affective disorder (BPAD) are life-long disorders that account for significant morbidity in afflicted patients. The etiology of BPAD is complex, combining genetic and environmental factors to increase the risk of disease. Genetic studies have pointed toward cytoskeletal dysfunction as a potential molecular mechanism through which BPAD may arise and have implicated proteins that regulate the cytoskeleton as risk factors. Microtubule actin crosslinking factor 1 (MACF1) is a giant cytoskeletal crosslinking protein that can coordinate the different aspects of the mammalian cytoskeleton with a wide variety of actions. In this review, we seek to highlight the functions of MACF1 in the nervous system and the molecular mechanisms leading to BPAD pathogenesis. We also offer a brief perspective on MACF1 and the role it may be playing in lithium's mechanism of action in treating BPAD.

Contributions of circadian clock genes to cell survival in fibroblast models of lithium-responsive bipolar disorder.

Bipolar disorder (BD) is characterized by mood episodes, disrupted circadian rhythms and gray matter reduction in the brain. Lithium is an effective pharmacotherapy for BD, but not all patients respond to treatment. Lithium has neuroprotective properties and beneficial effects on circadian rhythms that may distinguish lithium responders (Li-R) from non-responders (Li-NR). The circadian clock regulates molecular pathways involved in apoptosis and cell survival, but how this overlap impacts BD and/or lithium responsiveness is unknown. In primary fibroblasts from Li-R/Li-NR BD patients and controls, we found patterns of co-expression among circadian clock and cell survival genes that distinguished BD vs. control, and Li-R vs. Li-NR cells. In cellular models of apoptosis using staurosporine (STS), lithium preferentially protected fibroblasts against apoptosis in BD vs. control samples, regardless of Li-R/Li-NR status. When examining the effects of lithium treatment of cells in vitro, caspase activation by lithium correlated with period alteration, but the relationship differed in control, Li-R and Li-NR samples. Knockdown of Per1 and Per3 in mouse fibroblasts altered caspase activity, cell death and circadian rhythms in an opposite manner. In BD cells, genetic variation in PER1 and PER3 predicted sensitivity to apoptosis in a manner consistent with knockdown studies. We conclude that distinct patterns of coordination between circadian clock and cell survival genes in BD may help predict lithium response.

Patients with schizophrenia and bipolar disorder display a similar global gene expression signature in whole blood that reflects elevated proportion of immature neutrophil cells with association to lipid changes.

Schizophrenia (SCZ) and bipolar disorder (BD) share clinical characteristics, genetic susceptibility, and immune alterations. We aimed to identify differential transcriptional patterns in peripheral blood cells of patients with SCZ or BD versus healthy controls (HC). We analyzed microarray-based global gene expression data in whole blood from a cohort of SCZ (N = 329), BD (N = 203) and HC (N = 189). In total, 65 genes were significantly differentially expressed in SCZ and 125 in BD, as compared to HC, with similar ratio of up- and downregulated genes in both disorders. Among the top differentially expressed genes, we found an innate immunity signature that was shared between SCZ and BD, consisting of a cluster of upregulated genes (e.g., OLFM4, ELANE, BPI and MPO) that indicate an increased fraction of immature neutrophils. Several of these genes displayed sex differences in the expression pattern, and post-hoc analysis demonstrated a positive correlation with triglyceride and a negative correlation with HDL cholesterol. We found that many of the downregulated genes in SCZ and BD were associated with smoking. These findings of neutrophil granulocyte-associated transcriptome signatures in both SCZ and BD point at altered innate immunity pathways with association to lipid changes and potential for clinical translation.

Deep proteomics identifies shared molecular pathway alterations in synapses of patients with schizophrenia and bipolar disorder and mouse model.

Synaptic dysfunction is implicated in the pathophysiology of schizophrenia (SCZ) and bipolar disorder (BP). We use quantitative mass spectrometry to carry out deep, unbiased proteomic profiling of synapses purified from the dorsolateral prefrontal cortex of 35 cases of SCZ, 35 cases of BP, and 35 controls. Compared with controls, SCZ and BP synapses show substantial and similar proteomic alterations. Network analyses reveal upregulation of proteins associated with autophagy and certain vesicle transport pathways and downregulation of proteins related to synaptic, mitochondrial, and ribosomal function in the synapses of individuals with SCZ or BP. Some of the same pathways are similarly dysregulated in the synaptic proteome of mutant mice deficient in Akap11, a recently discovered shared risk gene for SCZ and BP. Our work provides biological insights into molecular dysfunction at the synapse in SCZ and BP and serves as a resource for understanding the pathophysiology of these disorders.

Alterations in pituitary adenylate cyclase-activating polypeptide in major depressive disorder, bipolar disorder, and comorbid depression in Alzheimer's disease in the human hypothalamus and prefrontal cortex.

BACKGROUND: Pituitary Adenylate Cyclase-Activating Polypeptide (PACAP) is involved in the stress response and may play a key role in mood disorders, but no information is available on PACAP for the human brain in relation to mood disorders. METHODS: PACAP-peptide levels were determined in a major stress-response site, the hypothalamic paraventricular nucleus (PVN), of people with major depressive disorder (MDD), bipolar disorder (BD) and of a unique cohort of Alzheimer's disease (AD) patients with and without depression, all with matched controls. The expression of PACAP-(Adcyap1mRNA) and PACAP-receptors was determined in the MDD and BD patients by qPCR in presumed target sites of PACAP in stress-related disorders, the dorsolateral prefrontal cortex (DLPFC) and anterior cingulate cortex (ACC). RESULTS: PACAP cell bodies and/or fibres were localised throughout the hypothalamus with differences between immunocytochemistry and in situ hybridisation. In the controls, PACAP-immunoreactivity-(ir) in the PVN was higher in women than in men. PVN-PACAP-ir was higher in male BD compared to the matched male controls. In all AD patients, the PVN-PACAP-ir was lower compared to the controls, but higher in AD depressed patients compared to those without depression. There was a significant positive correlation between the Cornell depression score and PVN-PACAP-ir in all AD patients combined. In the ACC and DLPFC, alterations in mRNA expression of PACAP and its receptors were associated with mood disorders in a differential way depending on the type of mood disorder, suicide, and psychotic features. CONCLUSION: The results support the possibility that PACAP plays a role in mood disorder pathophysiology.

Neurotransmission-related gene expression in the frontal pole is altered in subjects with bipolar disorder and schizophrenia.

The frontal pole (Brodmann area 10, BA10) is the largest cytoarchitectonic region of the human cortex, performing complex integrative functions. BA10 undergoes intensive adolescent grey matter pruning prior to the age of onset for bipolar disorder (BP) and schizophrenia (SCHIZ), and its dysfunction is likely to underly aspects of their shared symptomology. In this study, we investigated the role of BA10 neurotransmission-related gene expression in BP and SCHIZ. We performed qPCR to measure the expression of 115 neurotransmission-related targets in control, BP, and SCHIZ postmortem samples (n = 72). We chose this method for its high sensitivity to detect low-level expression. We then strengthened our findings by performing a meta-analysis of publicly released BA10 microarray data (n = 101) and identified sources of convergence with our qPCR results. To improve interpretation, we leveraged the unusually large database of clinical metadata accompanying our samples to explore the relationship between BA10 gene expression, therapeutics, substances of abuse, and symptom profiles, and validated these findings with publicly available datasets. Using these convergent sources of evidence, we identified 20 neurotransmission-related genes that were differentially expressed in BP and SCHIZ in BA10. These results included a large diagnosis-related decrease in two important therapeutic targets with low levels of expression, HTR2B and DRD4, as well as other findings related to dopaminergic, GABAergic and astrocytic function. We also observed that therapeutics may produce a differential expression that opposes diagnosis effects. In contrast, substances of abuse showed similar effects on BA10 gene expression as BP and SCHIZ, potentially amplifying diagnosis-related dysregulation.

Changes in neurofilament light chain protein (NEFL) in children and adolescents with Schizophrenia and Bipolar Disorder: Early period neurodegeneration.

AIM: Neurofilament light chain protein (NEFL), is defined as a structural protein which exists particularly in axones of neurons and is released to the cerum in consequence of neuroaxonal damage. The aim of this study is to investigate the peripheral cerumNEFLlevels of children and adolescents with early onset schizophrenia and bipolar disorder. METHOD: In this study, we evaluated serum levels of NEFL in children and adolescents (13-17 years) with schizophrenia, bipolar disorder and healthy control group. The study is conducted with 35 schizophrenia, 38 bipolar disorder manic episode patients and 40 healthy controls. RESULTS: The median age of the patient and control groups was 16 (IQR- Interquartile Range: 2). There was no statistical difference in median age (p = 0.52) and gender distribution(p = 0.53) between groups. NEFL levels of the patients with schizophrenia were significantly higher than the controls. NEFL levels of the patients with bipolar disorder were significantly higher than the controls. Serum levels of NEFL of the schizophrenia were higher than the bipolar disorder; however, the difference was not statistically significant. CONCLUSION: In conclusion, serum NEFL level, as a confidential marker of neural damage, is increased in the children and adolescents with bipolar disorder and schizophrenia. This result may indicatea degenerative period in neurons of children and adolescents with schizophrenia or bipolar disorder and may play a role in the pathophisiology of these disorders. This result shows that there is neuronal damage in both diseases, but neuronal damage may be more in schizophrenia.

A comparative meta-analysis of peripheral 8-hydroxy-2'-deoxyguanosine (8-OHdG) or 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxo-dG) levels across mood episodes in bipolar disorder.

OBJECTIVE: Oxidative DNA damage has been associated with the pathophysiology of bipolar disorder (BD) as one of the common pathways between increased medical comorbidity and premature aging in BD. Previous evidence shows increased levels of oxidatively induced DNA damage markers, 8-hydroxy-2'-deoxyguanosine (8-OHdG) or its tautomer 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxo-dG), in patients with BD in comparison to healthy individuals. With the current research, we aim to analyze data on peripheral (blood or urine) 8-OHdG/8-oxo-dG levels across mood states of BD using a meta-analytical approach. METHOD: A literature search was conducted using the databases PubMed, Scopus, and Web of Science to identify eligible studies (January 1989 to July 2022). Relevant studies were systematically reviewed; a random-effects meta-analysis and a meta-regression analysis were conducted. RESULTS: The current meta-analysis included 12 studies consisting of 808 BD patients (390 in euthymia, 156 in mania, 137 in depression, 16 in mixed episode, 109 not specified) and 563 healthy controls. BD patients that were currently depressed had significantly higher levels of 8-OHdG/8-oxo-dG than healthy controls, while euthymic or manic patients did not differ from healthy controls. A meta-regression analysis showed sex distribution (being female) and older age to be significantly related to increased 8-OHdG/8-oxo-dG levels. CONCLUSION: Our findings suggest that 8-OHdG/8-oxo-dG may be a state-related marker of depression in BD and may be affected by older age and female gender.

Glial-Neuronal Interaction in Synapses: A Possible Mechanism of the Pathophysiology of Bipolar Disorder.

Bipolar disorder (BD) is a severe and chronic psychiatric disorder that affects approximately 1-4% of the world population and is characterized by recurrent episodes of mania or hypomania and depression. BD is also associated with illnesses marked by immune activation, such as metabolic syndrome, obesity, type 2 diabetes mellitus, and cardiovascular diseases. Indeed, a connection has been suggested between neuroinflammation and peripheral inflammatory markers in the pathophysiology of BD, which can be associated with the modulation of many dysfunctional processes, including synaptic plasticity, neurotransmission, neurogenesis, neuronal survival, apoptosis, and even cognitive/behavioral functioning. Rising evidence suggests that synaptic dysregulations, especially glutamatergic system dysfunction, are directly involved in mood disorders. It is becoming clear that dysregulations in connection and structural changes of glial cells play a central role in the BD pathophysiology. This book chapter highlighted the latest findings that support the theory of synaptic dysfunction in BD, providing an overview of the alterations in neurotransmitters release, astrocytic uptake, and receptor signaling, as well as the role of inflammation on glial cells in mood disorders. Particular emphasis is given to the alterations in presynaptic and postsynaptic neurons and glial cells, all cellular elements of the "tripartite synapse," compromising the neurotransmitters system, excitatory-inhibitory balance, and neurotrophic states of local networks in mood disorders. Together, these studies provide a foundation of knowledge about the exact role of the glial-neuronal interaction in mood disorders.