Molecular characterization of bipolar disorder by comparing gene expression profiles of postmortem brains of major mental disorders

Peripheral and central inflammation in depression: How large is the gap and can we bridge it with PET neuroimaging and neural-derived extracellular vesicles?

Major depressive disorder (MDD) presents as a multifaceted syndrome with complex pathophysiology and variable treatment responses, posing significant challenges in clinical management. Neuroinflammation is known to play pivotal mechanism in depression, linking immune responses with central nervous system (CNS) dysfunction. This review explores the interplay between peripheral and central inflammatory processes in MDD, emphasizing discrepancies in biomarker validity and specificity. While peripheral markers like cytokines have historically been investigated as proxies for neuroinflammation, their reliability remains contentious due to inconsistent findings, lack of correlation with neuroinflammatory markers, the influence of confounding variables, and the role of regulatory mechanism within the CNS. Additionally, the human brain shows a pattern of regionalized inflammation. Current methodologies for investigating neuroinflammation in humans in vivo, including neural-derived extracellular vesicles (EVs) and positron emission tomography (PET) neuroimaging using translocator protein, offer promising avenues while facing substantial limitations. We propose that future research in MDD may benefit from combined microglia-derived EV-TSPO PET neuroimaging analyses to leverage the strengths and mitigate the limitations of both individual methods.

Exploring PDE5A upregulation in bipolar disorder: insights from single-nucleus RNA sequencing of human basal ganglia

Basal ganglia is proposed to mediate symptoms underlying bipolar disorder (BD). To understand the cell type-specific gene expression and network changes of BD basal ganglia, we performed single-nucleus RNA sequencing of 30,752 nuclei from caudate, putamen, globus pallidus, and substantia nigra of control human postmortem brain and 24,672 nuclei from BD brain. Differential expression analysis revealed major difference lying in caudate, with BD medium spiny neurons (MSNs) expressing significantly higher PDE5A, a cGMP-specific phosphodiesterase. Gene co-expression analysis (WGCNA) showed a strong correlation of caudate MSNs and gene module green, with a PDE5A-containing hub gene network. Gene regulatory network analysis (SCENIC) indicated key regulons among different cell types and basal ganglia regions, with downstream targets of key transcriptional factors showing overlapping genes such as PDEs. Upregulation of PDE5A was further validated in 7 pairs of control and BD caudate sections. Overexpression of PDE5A in primary cultured lateral ganglion eminence-derived striatal neurons led to decreased dendrite complexity, increased apoptosis, and enhanced neuronal excitability and membrane resistance. This effect could be rescued by PDE5 specific inhibitor, tadalafil. Overexpression of PDE5A in mouse striatum by stereotaxic injection caused a decreased cGMP level, an increased gene expression profile of neuroinflammation, and BD-like behaviors. Collectively, our findings provided cell type-specific gene expression profile, and indicated a causative role of PDE5A upregulation in BD basal ganglia. This study provides a single-nucleus transcriptomic profile of human control and bipolar disorder (BD) basal ganglia. Differential expression, gene co-expression, and gene regulatory network analyses collectively indicated upregulation of PDE5A in BD caudate medium spiny neurons (MSNs), which was further validated in another cohort of BD brains. The causative role of PDE5A upregulation in BD etiology is supported by the effects of PDE5A overexpression in cultured mouse MSNs in vitro and in adult mouse striatum in vivo. The former led to reduced dendrite complexity, increased apoptosis, and neuronal hyper-excitability, which could be rescued by PDE5 specific inhibitor tadalafil. The latter caused lower cGMP levels, upregulated genes associated with neuroinflammation, and BD-like behaviors.

Unraveling the Role of the Blood-Brain Barrier in the Pathophysiology of Depression: Recent Advances and Future Perspectives

Depression is a highly prevalent psychological disorder characterized by persistent dysphoria, psychomotor retardation, insomnia, anhedonia, suicidal ideation, and a remarkable decrease in overall well-being. Despite the prevalence of accessible antidepressant therapies, many individuals do not achieve substantial improvement. Understanding the multifactorial pathophysiology and the heterogeneous nature of the disorder could lead the way toward better outcomes. Recent findings have elucidated the substantial impact of compromised blood-brain barrier (BBB) integrity on the manifestation of depression. BBB functions as an indispensable defense mechanism, tightly overseeing the transport of molecules from the periphery to preserve the integrity of the brain parenchyma. The dysfunction of the BBB has been implicated in a multitude of neurological disorders, and its disruption and consequent brain alterations could potentially serve as important factors in the pathogenesis and progression of depression. In this review, we extensively examine the pathophysiological relevance of the BBB and delve into the specific modifications of its components that underlie the complexities of depression. A particular focus has been placed on examining the effects of peripheral inflammation on the BBB in depression and elucidating the intricate interactions between the gut, BBB, and brain. Furthermore, this review encompasses significant updates on the assessment of BBB integrity and permeability, providing a comprehensive overview of the topic. Finally, we outline the therapeutic relevance and strategies based on BBB in depression, including COVID-19-associated BBB disruption and neuropsychiatric implications. Understanding the comprehensive pathogenic cascade of depression is crucial for shaping the trajectory of future research endeavors.

One path, two solutions: Network-based analysis identifies targetable pathways for the treatment of comorbid type II diabetes and neuropsychiatric disorders

Comorbid diseases complicate patient outcomes and escalate healthcare costs, necessitating the need for a deeper mechanistic understanding. Neuropsychiatric disorders (NPDs) such as Neurotic Disorder, Major Depression, Bipolar Disorder, Anxiety Disorder, and Schizophrenia significantly exacerbate Type 2 Diabetes Mellitus (DM2), often leading to suboptimal treatment outcomes. The neurobiological mechanisms underlying this comorbidity remain poorly understood. To address this gap, we developed a novel pathway-based network computational framework to identify critical shared disease mechanisms between DM2 and these five prevalent comorbid NPDs. Our approach involves reconstructing an integrated DM2 ∩ NPDs KEGG pathway-pathway network and employs two complementary analytical methods, including the "minimum path to comorbidity" method to identify the shortest path fostering comorbid development. This analysis uncovered shared pathways like the PI3K-Akt signaling pathway and highlighted key nodes such as calcium signaling, MAPK, estrogen signaling, and apoptosis pathways. Dysregulation of these pathways likely contributes to the development of DM2-NPDs comorbidity. These findings have significant clinical implications, as they identify promising therapeutic targets that could lead to more effective treatments addressing both DM2 and NPDs simultaneously. Our model not only elucidates the intricate molecular interactions driving this comorbidity but also identifies promising therapeutic targets, paving the way for innovative treatment strategies. Additionally, the framework developed in this study can be adapted to study other complex comorbid conditions, advancing personalized medicine for comorbidities and improving patient care.

Enhancing Transcriptomic Insights into Neurological Disorders Through the Comparative Analysis of Shapley Values

Neurological disorders such as Autism Spectrum Disorder (ASD), Schizophrenia (SCH), Bipolar Disorder (BD), and Major Depressive Disorder (MDD) affect millions of people worldwide, yet their molecular mechanisms remain poorly understood. This study describes the application of the Comparative Analysis of Shapley values (CASh) to transcriptomic data from nine datasets associated with these complex disorders, demonstrating its effectiveness in identifying differentially expressed genes (DEGs). CASh, which combines Game Theory with Bootstrap resampling, offers a robust alternative to traditional statistical methods by assessing the contribution of each gene in the broader context of the complete dataset. Unlike conventional approaches, CASh is highly effective at detecting subtle but meaningful molecular patterns that are often missed. These findings highlight the potential of CASh to enhance the precision of transcriptomic analysis, providing a deeper understanding of the molecular mechanisms underlying these disorders and establishing a solid basis to improve diagnostic techniques and developing more targeted therapeutic interventions.

Higher levels of AKT-interacting protein in the frontal pole from people with schizophrenia are limited to a sub-group who have a marked deficit in cortical muscarinic M1 receptors

We are studying the molecular pathology of a sub-group within schizophrenia (∼ 25 %: termed Muscarinic Receptor Deficit subgroup of Schizophrenia (MRDS)) who can be separated because they have very low levels of cortical muscarinic M1 receptors (CHRM1). Based on our transcriptomic data from Brodmann's area ((BA) 9, 10 and 33 (controls, schizophrenia and mood disorders) and the cortex of the CHRM1-/- mouse (a molecular model of aberrant CHRM1 signaling), we predicted levels of AKT interacting protein (AKTIP), but not tubulin alpha 1b (TUBA1B) or AKT serine/threonine kinase 1 (AKT1) and pyruvate dehydrogenase kinase 1 (PDK1) (two AKTIP-functionally associated proteins), would be changed in MRDS. Hence, we used Western blotting to measure AKTIP (BA 10: controls, schizophrenia and mood disorders; BA 9: controls and schizophrenia) plus TUBA1B, AKT1 and PDK1 (BA 10: controls and schizophrenia) proteins. The only significant change with diagnosis was higher levels of AKTIP protein in BA 10 (Cohen's d = 0.73; p = 0.02) in schizophrenia compared to controls due to higher levels of AKTIP only in people with MRDS (Cohen's d = 0.80; p = 0.03). As AKTIP is involved in AKT1 signaling, our data suggests that signaling pathway is particularly disturbed in BA 10 in MRDS.

Glymphatic system dysfunction in mood disorders: Evaluation by diffusion magnetic resonance imaging

The glymphatic system, an expansive cerebral waste-disposal network, harbors myriad enigmatic facets necessitating elucidation of their nexus with diverse pathologies. Murine investigations have revealed a relationship between the glymphatic system and affective disorders. This study aimed to illuminate the interplay between bipolar disorder and the glymphatic system. Fifty-eight individuals afflicted with bipolar disorder were identified through meticulous psychiatric assessment. These individuals were juxtaposed with a cohort of 66 comparably aged and sex-matched, mentally stable subjects. Subsequent analysis entailed the application of covariance analysis to evaluate along with the perivascular space (ALPS) index, a novel magnetic resonance imaging method for assessing brain interstitial fluid dynamics via diffusion tensor imaging within the bipolar and control cohorts. We also evaluated the correlation between the ALPS index and clinical parameters, which included the Hamilton Depression scale scores, disease duration, and other clinical assessments. Moreover, partial correlation analyses, incorporating age and sex as covariates, were performed to investigate the relationships between the ALPS index and clinical measures within the two cohorts. A noteworthy adverse correlation was observed between the ALPS index and illness duration. A free-water imaging analysis revealed a substantial elevation in the free-water index within the white-matter tracts, prominently centered on the corpus callosum, within the bipolar cohort relative to that in the control group. In analogous cerebral regions, a conspicuous affirmative correlation was observed between the free-water-corrected radial diffusivity and depression rating scales. Our results showed that the protracted course of bipolar disorder concomitantly exacerbated glymphatic system dysregulation.

NARP-related alterations in the excitatory and inhibitory circuitry of socially isolated mice: developmental insights and implications for autism spectrum disorder

Background

Social isolation during critical periods of development is associated with alterations in behavior and neuronal circuitry. This study aimed to investigate the immediate and developmental effects of social isolation on firing properties, neuronal activity-regulated pentraxin (NARP) and parvalbumin (PV) expression in the prefrontal cortex (PFC), social behavior in juvenile socially isolated mice, and the biological relevance of NARP expression in autism spectrum disorder (ASD).

Methods

Mice were subjected to social isolation during postnatal days 21-35 (P21-P35) and were compared with group-housed control mice. Firing properties in the PFC pyramidal neurons were altered in P35 socially isolated mice, which might be associated with alterations in NARP and PV expression.

Results

In adulthood, mice that underwent juvenile social isolation exhibited difficulty distinguishing between novel and familiar mice during a social memory task, while maintaining similar levels of social interaction as the control mice. Furthermore, a marked decrease in NARP expression in lymphoblastoid cell lines derived from adolescent humans with ASD as compared to typically developing (TD) humans was found.

Conclusion

Our study highlights the role of electrophysiological properties, as well as NARP and PV expression in the PFC in mediating the developmental consequences of social isolation on behavior.

Identification of important gene signatures in schizophrenia through feature fusion and genetic algorithm

Schizophrenia is a debilitating psychiatric disorder that can significantly affect a patient's quality of life and lead to permanent brain damage. Although medical research has identified certain genetic risk factors, the specific pathogenesis of the disorder remains unclear. Despite the prevalence of research employing magnetic resonance imaging, few studies have focused on the gene level and gene expression profile involving a large number of screened genes. However, the high dimensionality of genetic data presents a great challenge to accurately modeling the data. To tackle the current challenges, this study presents a novel feature selection strategy that utilizes heuristic feature fusion and a multi-objective optimization genetic algorithm. The goal is to improve classification performance and identify the key gene subset for schizophrenia diagnostics. Traditional gene screening techniques are inadequate for accurately determining the precise number of key genes associated with schizophrenia. Our innovative approach integrates a filter-based feature selection method to reduce data dimensionality and a multi-objective optimization genetic algorithm for improved classification tasks. By combining the filtering and wrapper methods, our strategy leverages their respective strengths in a deliberate manner, leading to superior classification accuracy and a more efficient selection of relevant genes. This approach has demonstrated significant improvements in classification results across 11 out of 14 relevant datasets. The performance on the remaining three datasets is comparable to the existing methods. Furthermore, visual and enrichment analyses have confirmed the practicality of our proposed method as a promising tool for the early detection of schizophrenia.

Altered Expression of PDE4 Genes in Schizophrenia: Insights from a Brain and Blood Sample Meta-Analysis and iPSC-Derived Neurons

Schizophrenia symptomatology includes negative symptoms and cognitive impairment. Several studies have linked schizophrenia with the PDE4 family of enzymes due to their genetic association and function in cognitive processes such as long-term potentiation. We conducted a systematic gene expression meta-analysis of four PDE4 genes (PDE4A-D) in 10 brain sample datasets (437 samples) and three blood sample datasets (300 samples). Subsequently, we measured mRNA levels in iPSC-derived hippocampal dentate gyrus neurons generated from fibroblasts of three groups: healthy controls, healthy monozygotic twins (MZ), and their MZ siblings with schizophrenia. We found downregulation of PDE4B in brain tissues, further validated by independent data of the CommonMind consortium (515 samples). Interestingly, the downregulation signal was present in a subgroup of the patients, while the others showed no differential expression or even upregulation. Notably, PDE4A, PDE4B, and PDE4D exhibited upregulation in iPSC-derived neurons compared to healthy controls, whereas in blood samples, PDE4B was found to be upregulated while PDE4A was downregulated. While the precise mechanism and direction of altered PDE4 expression necessitate further investigation, the observed multilevel differential expression across the brain, blood, and iPSC-derived neurons compellingly suggests the involvement of PDE4 genes in the pathophysiology of schizophrenia.

Discrete prefrontal neuronal circuits determine repeated stress-induced behavioral phenotypes in male mice

Chronic stress is a major risk factor for psychiatric disorders, including depression. Although depression is a highly heterogeneous syndrome, it remains unclear how chronic stress drives individual differences in behavioral responses. In this study, we developed a subtyping-based approach wherein stressed male mice were divided into four subtypes based on their behavioral patterns of social interaction deficits and anhedonia, the core symptoms of psychiatric disorders. We identified three prefrontal cortical neuronal projections that regulate repeated stress-induced behavioral phenotypes. Among them, the medial prefrontal cortex (mPFC)→anterior paraventricular thalamus (aPVT) pathway determines the specific behavioral subtype that exhibits both social deficits and anhedonia. Additionally, we identified the circuit-level molecular mechanism underlying this subtype: KDM5C-mediated epigenetic repression of Shisa2 transcription in aPVT projectors in the mPFC led to social deficits and anhedonia. Thus, we provide a set of biological aspects at the cellular, molecular, and epigenetic levels that determine distinctive stress-induced behavioral phenotypes.

Exploring the Potential Molecular Mechanism of the Shugan Jieyu Capsule in the Treatment of Depression through Network Pharmacology, Molecular Docking, and Molecular Dynamics Simulation

BACKGROUND

Shugan Jieyu Capsule (SJC) is a pure Chinese medicine compound prepared with Hypericum perforatum and Acanthopanacis senticosi. SJC has been approved for the clinical treatment of depression, but the mechanism of action is still unclear.

OBJECTIVES

Network pharmacology, molecular docking, and molecular dynamics simulation (MDS) were applied in the present study to explore the potential mechanism of SJC in the treatment of depression.

METHODS

TCMSP, BATMAN-TCM, and HERB databases were used, and related literature was reviewed to screen the effective active ingredients of Hypericum perforatum and Acanthopanacis senticosi. TCMSP, BATMAN-TCM, HERB, and STITCH databases were used to predict the potential targets of effective active ingredients. GeneCards database, DisGeNET database, and GEO data set were used to obtain depression targets and clarify the intersection targets of SJC and depression. STRING database and Cytoscape software were used to build a protein-protein interaction (PPI) network of intersection targets and screen the core targets. The enrichment analysis on the intersection targets was conducted. Then the receiver operator characteristic (ROC) curve was constructed to verify the core targets. The pharmacokinetic characteristics of core active ingredients were predicted by SwissADME and pkCSM. Molecular docking was performed to verify the docking activity of the core active ingredients and core targets, and molecular dynamics simulations were performed to evaluate the accuracy of the docking complex.

RESULTS

We obtained 15 active ingredients and 308 potential drug targets with quercetin, kaempferol, luteolin, and hyperforin as the core active ingredients. We obtained 3598 targets of depression and 193 intersection targets of SJC and depression. A total of 9 core targets (AKT1, TNF, IL6, IL1B, VEGFA, JUN, CASP3, MAPK3, PTGS2) were screened with Cytoscape 3.8.2 software. A total of 442 GO entries and 165 KEGG pathways (p <0.01) were obtained from the enrichment analysis of the intersection targets, mainly enriched in IL-17, TNF, and MAPK signaling pathways. The pharmacokinetic characteristics of the 4 core active ingredients indicated that they could play a role in SJC antidepressants with fewer side effects. Molecular docking showed that the 4 core active components could effectively bind to the 8 core targets (AKT1, TNF, IL6, IL1B, VEGFA, JUN, CASP3, MAPK3, PTGS2), which were related to depression by the ROC curve. MDS showed that the docking complex was stable.

CONCLUSION

SJC may treat depression by using active ingredients such as quercetin, kaempferol, luteolin, and hyperforin to regulate targets such as PTGS2 and CASP3 and signaling pathways such as IL-17, TNF, and MAPK, and participate in immune inflammation, oxidative stress, apoptosis, neurogenesis, etc.

Glymphatic System and Psychiatric Disorders: A Rapid Comprehensive Scoping Review

BACKGROUND

Since discovering the glymphatic system, there has been a looming interest in exploring its relationship with psychiatric disorders. Recently, increasing evidence suggests an involvement of the glymphatic system in the pathophysiology of psychiatric disorders. However, clear data are still lacking. In this context, this rapid comprehensive PRISMA-ScR (Preferred Reporting Items for Systematic Reviews and Meta-Analyses extension for Scoping Reviews) scoping review aims to identify and analyze current evidence about the relation between the glymphatic system and psychiatric disorders.

METHODS

We conducted a comprehensive review of the literature and then proceeded to discuss the findings narratively. Tables were then constructed and articles were sorted according to authors, year, title, location of study, sample size, psychiatric disorder, the aim of the study, principal findings, implications.

RESULTS

Twenty papers were identified as eligible, among which 2 articles on Schizophrenia, 1 on Autism Spectrum Disorders, 2 on Depression, 1 on Depression and Trauma-related Disorders, 1 on Depression and Anxiety, 2 on Anxiety and Sleep Disorders, 8 on Sleep Disorders, 2 on Alcohol use disorder and 1 on Cocaine Use Disorder.

CONCLUSION

This review suggests a correlation between the glymphatic system and several psychiatric disorders: Schizophrenia, Depression, Anxiety Disorders, Sleep Disorders, Alcohol Use Disorder, Cocaine Use Disorder, Trauma-Related Disorders, and Autism Spectrum Disorders. Impairment of the glymphatic system could play a role in Trauma-Related Disorders, Alcohol Use Disorders, Cocaine Use Disorders, Sleep Disorders, Depression, and Autism Spectrum Disorders. It is important to implement research on this topic and adopt standardized markers and radio diagnostic tools.

Multiple genes encoding mitochondrial ribosomes are downregulated in brain and blood samples of individuals with schizophrenia

OBJECTIVES

Schizophrenia is a chronic, debilitating mental disorder whose pathophysiology is complex and not fully understood. Numerous studies suggest mitochondrial dysfunction may contribute to the development of schizophrenia. While mitochondrial ribosomes (mitoribosomes) are essential for proper mitochondrial functioning, their gene expression levels have not been studied yet in schizophrenia.

METHODS

We performed a systematic meta-analysis of the expression of 81 mitoribosomes subunits encoding genes, integrating ten brain samples datasets of patients with schizophrenia compared to healthy controls (overall 422 samples, 211 schizophrenia, and 211 controls). We also performed a meta-analysis of their expression in blood, integrating two blood sample datasets (overall 90 samples, 53 schizophrenia, and 37 controls).

RESULTS

Multiple mitoribosomes subunits were significantly downregulated in brain samples (18 genes) and in blood samples (11 genes) of individuals with schizophrenia, where two showed significant downregulation in both brain and blood, MRPL4 and MRPS7.

CONCLUSIONS

Our results support the accumulating evidence of impaired mitochondrial activity in schizophrenia. While further research is needed to validate mitoribosomes' role as biomarkers, this direction has the potential to promote patients' stratification and personalised treatment for schizophrenia.

Aquaporin 4 beyond a water channel; participation in motor, sensory, cognitive and psychological performances, a comprehensive review

Aquaporin 4 (AQP4) is a protein highly expressed in the central nervous system (CNS) and peripheral nervous system (PNS) as well as various other organs, whose different sites of action indicate its importance in various functions. AQP4 has a variety of essential roles beyond water homeostasis. In this article, we have for the first time summarized different roles of AQP4 in motor and sensory functions, besides cognitive and psychological performances, and most importantly, possible physiological mechanisms by which AQP4 can exert its effects. Furthermore, we demonstrated that AQP4 participates in pathology of different neurological disorders, various effects depending on the disease type. Since neurological diseases involve a spectrum of dysfunctions and due to the difficulty of obtaining a treatment that can simultaneously affect these deficits, it is therefore suggested that future studies consider the role of this protein in different functional impairments related to neurological disorders simultaneously or separately by targeting AQP4 expression and/or polarity modulation.

Relationship between circulating mitochondrial DNA and microRNA in patients with major depression

BACKGROUND

MicroRNAs (miRNAs) and circulating cell-free mitochondrial DNA (ccf-mtDNA) have attracted interest as biological markers of affective disorders. In response to stress, it is known that miRNAs in mitochondria diffuse out of the cytoplasm alongside mtDNA; however, this process has not yet been identified. We hypothesized that miRNAs derived from specific cell nuclei cause mitochondrial damage and mtDNA fragmentation under MDD-associated stress conditions.

METHODS

A comprehensive analysis of the plasma miRNA levels and quantification of the plasma ccf-mtDNA copy number were performed in 69 patients with depression to determine correlations and identify genes and pathways interacting with miRNAs. The patients were randomly assigned to receive either selective serotonin reuptake inhibitors (SSRI) or mirtazapine. Their therapeutic efficacy over four weeks was evaluated in relation to miRNAs correlated with ccf-mtDNA copy number.

RESULTS

The expression levels of the five miRNAs showed a significant positive correlation with the ccf-mtDNA copy number after correcting for multiple testing. These miRNAs are involved in gene expression related to thyroid hormone synthesis, the Hippo signaling pathway, vasopressin-regulated water reabsorption, and lysine degradation. Of these five miRNAs, miR-6068 and miR-4708-3p were significantly associated with the SSRI and mirtazapine treatment outcomes, respectively.

LIMITATIONS

This study did not show comparison with a healthy group.

CONCLUSIONS

The expression levels of specific miRNAs were associated with ccf-mtDNA copy number in untreated depressed patients; moreover, these miRNAs were linked to antidepressant treatment outcomes. These findings are expected to lead to the elucidation of new pathological mechanism of depression.

Pleiotropic Association of CACNA1C Variants With Neuropsychiatric Disorders

BACKGROUND

Neuropsychiatric disorders are highly heritable and have overlapping genetic underpinnings. Single nucleotide polymorphisms (SNPs) in the gene CACNA1C have been associated with several neuropsychiatric disorders, across multiple genome-wide association studies.

METHOD

A total of 70,711 subjects from 37 independent cohorts with 13 different neuropsychiatric disorders were meta-analyzed to identify overlap of disorder-associated SNPs within CACNA1C. The differential expression of CACNA1C mRNA in five independent postmortem brain cohorts was examined. Finally, the associations of disease-sharing risk alleles with total intracranial volume (ICV), gray matter volumes (GMVs) of subcortical structures, cortical surface area (SA), and average cortical thickness (TH) were tested.

RESULTS

Eighteen SNPs within CACNA1C were nominally associated with more than one neuropsychiatric disorder (P < .05); the associations shared among schizophrenia, bipolar disorder, and alcohol use disorder survived false discovery rate correction (five SNPs with P < 7.3 × 10-4 and q < 0.05). CACNA1C mRNA was differentially expressed in brains from individuals with schizophrenia, bipolar disorder, and Parkinson's disease, relative to controls (three SNPs with P < .01). Risk alleles shared by schizophrenia, bipolar disorder, substance dependence, and Parkinson's disease were significantly associated with ICV, GMVs, SA, or TH (one SNP with P ≤ 7.1 × 10-3 and q < 0.05).

CONCLUSION

Integrating multiple levels of analyses, we identified CACNA1C variants associated with multiple psychiatric disorders, and schizophrenia and bipolar disorder were most strongly implicated. CACNA1C variants may contribute to shared risk and pathophysiology in these conditions.

Up-Regulation of S100 Gene Family in Brain Samples of a Subgroup of Individuals with Schizophrenia: Meta-analysis

The S100 proteins family is known to affect neuroinflammation and astrocyte activation, which have been suggested to be contributors to the pathogenesis of schizophrenia. We conducted a systematic meta-analysis of S100 genes differential expression in postmortem samples of patients with schizophrenia vs. healthy controls, following the commonly used Preferred Reporting Items for Systematic Reviews and Meta-Analysis (PRISMA) guidelines. Twelve microarray datasets met the inclusion criteria (overall 511 samples, 253 schizophrenia and 258 controls were analyzed). Nine out of 21 genes were significantly up-regulated or with tendency for up-regulation. A per-sample fold change analysis indicated that the S100 genes' up-regulation was concentrated in a subgroup of the patients. None of the genes have been found to be down-regulated. ANXA3, which encodes Annexin 3 protein and was associated with neuroinflammation, was up-regulated and positively correlated with the S100 genes' expression pattern. In addition, astrocytes and endothelial cell markers were significantly correlated with S100A8 expression. S100 correlation with ANXA3 and endothelial cell markers suggests that the up-regulation we detected reflects increased inflammation. However, it might also reflect astrocytes abundance or activation. The fact that S100 proteins were shown to be up-regulated in blood samples and other body fluids of patients with schizophrenia suggests a potential role as biomarkers, which might help disease subtyping, and the development of etiological treatments for immune dysregulation in schizophrenia.

A High-Phosphorus Diet Moderately Alters the Lipidome and Transcriptome in the Skeletal Muscle of Adult Mice

A high phosphorus intake has been associated with various metabolic disorders, including chronic kidney disease, cardiovascular disease, and osteoporosis. Recent studies have demonstrated the effects of dietary phosphorus on lipid and glucose metabolism. This study investigated the impact of a high-phosphorus diet on mouse skeletal muscle lipid composition and gene transcription. Adult male mice (n = 12/group) received either a diet with an adequate (0.3%) or a high (1.2%) phosphorus concentration for 6 weeks. The lipidome analysis showed that among the 17 analyzed lipid classes, the concentrations of three classes were reduced in the high phosphorus group compared to the adequate phosphorus group. These classes were phosphatidylethanolamine (PE), phosphatidylglycerol (PG), and lysophosphatidylcholine (LPC) (p < 0.05). Out of the three hundred and twenty-three individual lipid species analyzed, forty-nine showed reduced concentrations, while three showed increased concentrations in the high phosphorus group compared to the adequate phosphorus group. The muscle transcriptome analysis identified 142 up- and 222 down-regulated transcripts in the high phosphorus group compared to the adequate phosphorus group. Gene set enrichment analysis identified that genes that were up-regulated in the high phosphorus group were linked to the gene ontology terms "mitochondria" and "Notch signaling pathway", whereas genes that were down-regulated were linked to the "PI3K-AKT pathway". Overall, the effects of the high-phosphorus diet on the muscle lipidome and transcriptome were relatively modest, but consistently indicated an impact on lipid metabolism.

The influence of tissue pH and RNA integrity number on gene expression of human postmortem brain

Background

Evaluating and controlling confounders are necessary when investigating molecular pathogenesis using human postmortem brain tissue. Particularly, tissue pH and RNA integrity number (RIN) are valuable indicators for controlling confounders. However, the influences of these indicators on the expression of each gene in postmortem brain have not been fully investigated. Therefore, we aimed to assess these effects on gene expressions of human brain samples.

Methods

We isolated total RNA from occipital lobes of 13 patients with schizophrenia and measured the RIN and tissue pH. Gene expression was analyzed and gene sets affected by tissue pH and RIN were identified. Moreover, we examined the functions of these genes by enrichment analysis and upstream regulator analysis.

Results

We identified 2,043 genes (24.7%) whose expressions were highly correlated with pH; 3,004 genes (36.3%) whose expressions were highly correlated with RIN; and 1,293 genes (15.6%) whose expressions were highly correlated with both pH and RIN. Genes commonly affected by tissue pH and RIN were highly associated with energy production and the immune system. In addition, genes uniquely affected by tissue pH were highly associated with the cell cycle, whereas those uniquely affected by RIN were highly associated with RNA processing.

Conclusion

The current study elucidated the influence of pH and RIN on gene expression profiling and identified gene sets whose expressions were affected by tissue pH or RIN. These findings would be helpful in the control of confounders for future postmortem brain studies.

Ribosome subunits are upregulated in brain samples of a subgroup of individuals with schizophrenia: A systematic gene expression meta-analysis

One of the new theories accounting for the underlying pathophysiology of schizophrenia is excitation/inhibition imbalance. Interestingly, perturbation in protein synthesis machinery as well as oxidative stress can lead to excitation/inhibition imbalance. We thus performed a systematic meta-analysis of the expression of 79 ribosome subunit genes and two oxidative-stress related genes, HIF1A and NQO1, in brain samples of individuals with schizophrenia vs. healthy controls. We integrated 12 gene expression datasets, following the PRISMA guidelines (overall 511 samples, 253 schizophrenia and 258 controls). Five ribosome subunit genes were significantly upregulated in a subgroup of the patients with schizophrenia, while 24 (30%) showed a tendency for upregulation. HIF1A and NQO1 were also found to be significantly upregulated. Moreover, HIF1A and NQO1 showed positive correlation with the expression of the upregulated ribosome subunit genes. Our results, together with previous findings, suggest a possible role for altered mRNA translation in the pathogenesis of schizophrenia, in association with markers of increased oxidative stress in a subgroup of patients. Further studies should define whether the upregulation of ribosome subunits result in altered mRNA translation, which proteins are modulated and how it characterizes a subgroup of the patients with schizophrenia.

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.

Brain Inflammatory Marker Abnormalities in Major Psychiatric Diseases: a Systematic Review of Postmortem Brain Studies

Schizophrenia (SCZ), bipolar disorder (BD), and major depressive disorder (MDD) are common neuropsychiatric disorders that lead to neuroinflammation in the pathogenesis. It is possible to further explore the connection between inflammation in the brain and SCZ, BD, and MDD. Therefore, we systematically reviewed PubMed and Web of Science on brain inflammatory markers measured in SCZ, BD, and MDD postmortem brains. Out of 2166 studies yielded by the search, 46 studies met the inclusion criteria in SCZ, BD, and MDD postmortem brains. The results were variable across inflammatory markers. For example, 26 studies were included to measure the differential expression between SCZ and control subjects. Similarly, seven of the included studies measured the differential expression of inflammatory markers in patients with BD. The heterogeneity from the included studies is not clear at present, which may be caused by several factors, including the measured brain region, disease stage, brain source, medication, and other factors.

Nicotine pretreatment alleviates MK-801-induced behavioral and cognitive deficits in mice by regulating Pdlim5/CRTC1 in the PFC

Increasing evidence shows that smoking-obtained nicotine is indicated to improve cognition and mitigate certain symptoms of schizophrenia. In this study, we investigated whether chronic nicotine treatment alleviated MK-801-induced schizophrenia-like symptoms and cognitive impairment in mice. Mice were injected with MK-801 (0.2 mg/kg, i.p.), and the behavioral deficits were assessed using prepulse inhibition (PPI) and T-maze tests. We showed that MK-801 caused cognitive impairment accompanied by increased expression of PDZ and LIM domain 5 (Pdlim5), an adaptor protein that is critically associated with schizophrenia, in the prefrontal cortex (PFC). Pretreatment with nicotine (0.2 mg · kg-1 · d-1, s.c., for 2 weeks) significantly ameliorated MK-801-induced schizophrenia-like symptoms and cognitive impairment by reversing the increased Pdlim5 expression levels in the PFC. In addition, pretreatment with nicotine prevented the MK-801-induced decrease in CREB-regulated transcription coactivator 1 (CRTC1), a coactivator of CREB that plays an important role in cognition. Furthermore, MK-801 neither induced schizophrenia-like behaviors nor decreased CRTC1 levels in the PFC of Pdlim5-/- mice. Overexpression of Pdlim5 in the PFC through intra-PFC infusion of an adreno-associated virus AAV-Pdlim5 induced significant schizophrenia-like symptoms and cognitive impairment. In conclusion, chronic nicotine treatment alleviates schizophrenia-induced memory deficits in mice by regulating Pdlim5 and CRTC1 expression in the PFC.

SMAD genes are up-regulated in brain and blood samples of individuals with schizophrenia

Schizophrenia is a severe psychiatric disorder, with heritability around 80%, but a not fully understood pathophysiology. Signal transduction through the mothers against decapentaplegic (SMADs) are eight different proteins involved in the regulation of inflammatory processes, cell cycle, and tissue patterning. The literature is not consistent regarding the differential expression of SMAD genes among subjects with schizophrenia. In this article, we performed a systematic meta-analysis of the expression of SMAD genes in 423 brain samples (211 schizophrenia vs. 212 healthy controls), integrating 10 datasets from two public repositories, following the PRISMA guidelines. We found a statistically significant up-regulation of SMAD1, SMAD4, SMAD5, and SMAD7, and a tendency for up-regulation of SMAD3 and SMAD9 in brain samples of patients with schizophrenia. Overall, six of the eight genes showed a tendency for up-regulation, and none of them was found to have a tendency for down-regulation. SMAD1 and SMAD4 were up-regulated also in blood samples of 13 individuals with schizophrenia versus eight healthy controls, suggesting the SMAD genes' potential role as biomarkers of schizophrenia. Furthermore, SMAD genes' expression levels were significantly correlated with those of Sphingosine-1-phosphate receptor-1 (S1PR1), which is known to regulate inflammatory processes. Our meta-analysis supports the involvement of SMAD genes in the pathophysiology of schizophrenia through their role in inflammatory processes, as well as demonstrates the importance of gene expression meta-analysis for improving our understanding of psychiatric diseases.

Screening and identification of key biomarkers of depression using bioinformatics

We aimed to identify the molecular biomarkers of MDD disease progression to uncover potential mechanisms of major depressive disorder (MDD). In this study, three microarray data sets, GSE44593, GSE12654, and GSE54563, were cited from the Gene Expression Omnibus database for performance evaluation. To perform molecular functional enrichment analyses, differentially expressed genes (DEGs) were identified, and a protein-protein interaction network was configured using the Search Tool for the Retrieval of Interacting Genes/Proteins and Cytoscape. To assess multi-purpose functions and pathways, such as signal transduction, plasma membrane, protein binding, and cancer pathways, a total of 220 DEGs, including 143 upregulated and 77 downregulated genes, were selected. Additionally, six central genes were observed, including electron transport system variant transcription factor 6, FMS-related receptor tyrosine kinase 3, carnosine synthetase 1, solute carrier family 22 member 13, prostaglandin endoperoxide synthetase 2, and protein serine kinase H1, which had a significant impact on cell proliferation, extracellular exosome, protein binding, and hypoxia-inducible factor 1 signaling pathway. This study enhances our understanding of the molecular mechanism of the occurrence and progression of MDD and provides candidate targets for its diagnosis and treatment.

Meta-analysis of brain samples of individuals with schizophrenia detects down-regulation of multiple ATP synthase encoding genes in both females and males

Schizophrenia is a chronic and debilitating mental disorder, with unknown pathophysiology. Converging lines of evidence suggest that mitochondrial functioning may be compromised in schizophrenia. Postmortem brain samples of individuals with schizophrenia showed dysregulated expression levels of genes encoding enzyme complexes comprising the mitochondrial electron transport chain (ETC), including ATP synthase, the fifth ETC complex. However, there are inconsistencies regarding the direction of change, i.e., up- or down-regulation, and differences between female and male patients were hardly examined. We have performed a systematic meta-analysis of the expression of 16 ATP synthase encoding genes in postmortem brain samples of individuals with schizophrenia vs. healthy controls of three regions: Brodmann Area 10 (BA10), BA22/Superior Temporal Gyrus (STG) and the cerebellum. Eight independent datasets were integrated (overall 294brain samples, 145 of individuals with schizophrenia and 149 controls). The meta-analysis was applied to all individuals with schizophrenia vs. the controls, and also to female and male patients vs. age-matched controls, separately. A significant down-regulation of two ATP synthase encoding genes was detected in schizophrenia, ATP5A1 and ATP5H, and a trend towards down-regulation of five further ATP synthase genes. The down-regulation tendency was shown for both females and males with schizophrenia. Our findings support the hypothesis that schizophrenia is associated with reduced ATP synthesis via the oxidative phosphorylation system, which is caused by reduced cellular demand of ATP. Abnormal cellular energy metabolism can lead to alterations in neural function and brain circuitry, and thereby to the cognitive and behavioral aberrations characteristic of schizophrenia.

VDAC genes down-regulation in brain samples of individuals with schizophrenia is revealed by a systematic meta-analysis

Mitochondrial dysfunction was shown to be involved in schizophrenia pathophysiology. Abnormal energy states can lead to alterations in neural function and thereby to the cognitive and behavioral aberrations characteristics of schizophrenia. Voltage-dependent anion-selective channels (VDAC) are located in the outer mitochondrial membrane and are involved in mitochondrial energy production. Only few studies explored VDAC genes' expression in schizophrenia, and their results were not consistent. We conducted a systematic meta-analysis of ten brain samples gene expression datasets (overall 368 samples, 179 schizophrenia, 189 controls). In addition, we conducted a meta-analysis of three blood samples datasets (overall 300 samples, 167 schizophrenia, 133 controls). Pairwise correlation analysis was conducted between the VDAC and proteasome subunit genes' expression patterns. VDAC1, VDAC2 and VDAC3 showed significant down-regulation in brain samples of patients with schizophrenia. They also showed significant positive correlations with the proteasome subunit genes' expression levels. Our findings suggest that VDAC genes might play a role in mitochondrial dysfunction in schizophrenia. VDAC1 was down-regulated also in blood samples, which suggests its potential role as a biomarker for schizophrenia. The correlation with proteasome subunits, which were previously shown to be down-regulated in a subgroup of the patients, suggests that our findings might characterize a subgroup of the patients. This direction has the potential to lead to patients' stratification and more precisely-targeted therapy and necessitates further study.

Gene expression meta-analysis in patients with schizophrenia reveals up-regulation of RGS2 and RGS16 in Brodmann Area 10

Regulator of G-protein signalling (RGS) proteins inhibit signalling by G-protein-coupled receptors (GPCRs). GPCRs mediate the functions of several important neurotransmitters and serve as targets of many anti-psychotics. RGS2, RGS4, RGS5 and RGS16 are located on chromosome 1q23.3-31, a locus found to be associated with schizophrenia. Although previous gene expression analysis detected down-regulation of RGS4 expression in brain samples of patients with schizophrenia, the results were not consistent. In the present study, we performed a systematic meta-analysis of differential RGS2, RGS4, RGS5 and RGS16 expression in Brodmann Area 10 (BA10) samples of patients with schizophrenia and from healthy controls. Two microarray datasets met the inclusion criteria (overall, 41 schizophrenia samples and 38 controls were analysed). RGS2 and RGS16 were found to be up-regulated in BA10 samples of individuals with schizophrenia, whereas no differential expression of RGS4 and RGS5 was detected. Analysis of dorso-lateral prefrontal cortex samples of the CommonMind Consortium (258 schizophrenia samples vs. 279 controls) further validated the results. Given their central role in inactivating G-protein-coupled signalling pathways, our results suggest that differential gene expression might lead to enhanced inactivation of G-protein signalling in schizophrenia. This, in turn, suggests that additional studies are needed to further explore the consequences of the differential expression we detected, this time at the protein and functional levels.

Structural variation and eQTL analysis in two experimental populations of chickens divergently selected for feather-pecking behavior

Feather pecking (FP) is a damaging nonaggressive behavior in laying hens with a heritable component. Its occurrence has been linked to the immune system, the circadian clock, and foraging behavior. Furthermore, dysregulation of miRNA biogenesis, disturbance of the gamma-aminobutyric acid (GABAergic) system, as well as neurodevelopmental deficiencies are currently under debate as factors influencing the propensity for FP behavior. Past studies, which focused on the dissection of the genetic factors involved in FP, relied on single nucleotide polymorphisms (SNPs) and short insertions and deletions < 50 bp (InDels). These variant classes only represent a certain fraction of the genetic variation of an organism. Hence, we reanalyzed whole-genome sequencing data from two experimental populations, which have been divergently selected for FP behavior for over more than 15 generations, performed variant calling for structural variants (SVs) as well as tandem repeats (TRs), and jointly analyzed the data with SNPs and InDels. Genotype imputation and subsequent genome-wide association studies, in combination with expression quantitative trait loci analysis, led to the discovery of multiple variants influencing the GABAergic system. These include a significantly associated TR downstream of the GABA receptor subunit beta-3 (GABRB3) gene, two microRNAs targeting several GABA receptor genes, and dystrophin (DMD), a direct regulator of GABA receptor clustering. Furthermore, we found the transcription factor ETV1 to be associated with the differential expression of 23 genes, which points toward a role of ETV1, together with SMAD4 and KLF14, in the disturbed neurodevelopment of high-feather pecking chickens.

Exploring the role of astrocytic dysfunction and AQP4 in depression

Aquaporin-4 (AQP4) is the water regulating channel found in the terminal processes of astrocytes in the brain and is implicated in regulating the astrocyte functions, whereas in neuropathologies, AQP4 performs an important role in astrocytosis and release of proinflammatory cytokines. However, several findings have revealed the modulation of the AQP4 water channel in the etiopathogenesis of various neuropsychiatric diseases. In the current article, we have summarized the recent studies and highlighted the implication of astrocytic dysfunction and AQP4 in the etiopathogenesis of depressive disorder. Most of the studies have measured the AQP4 gene or protein expression in the brain regions, particularly the locus coeruleus, choroid plexus, prefrontal cortex, and hippocampus, and found that in these brain regions, AQP4 gene expression decreased on exposure to chronic mild stress. Few studies also measured the peripheral AQP4 mRNA expression in the blood and AQP4 autoantibodies in the blood serum and revealed no change in the depressed patients in comparison with normal individuals.

Identification of potential biomarkers and their correlation with immune infiltration cells in schizophrenia using combinative bioinformatics strategy

Many studies have identified changes in gene expression in brains of schizophrenia patients and their altered molecular processes, but the findings in different datasets were inconsistent and diverse. Here we performed the most comprehensive analysis of gene expression patterns to explore the underlying mechanisms and the potential biomarkers for early diagnosis in schizophrenia. We focused on 10 gene expression datasets in post-mortem human brain samples of schizophrenia downloaded from gene expression omnibus (GEO) database using the integrated bioinformatics analyses including robust rank aggregation (RRA) algorithm, Weighted gene co-expression network analysis (WGCNA) and CIBERSORT. Machine learning algorithm was used to construct the risk prediction model for early diagnosis of schizophrenia. We identified 15 key genes (SLC1A3, AQP4, GJA1, ALDH1L1, SOX9, SLC4A4, EGR1, NOTCH2, PVALB, ID4, ABCG2, METTL7A, ARC, F3 and EMX2) in schizophrenia by performing multiple bioinformatics analysis algorithms. Moreover, the interesting part of the study is that there is a correlation between the expression of hub genes and the immune infiltrating cells estimated by CIBERSORT. Besides, the risk prediction model was constructed by using both these genes and the immune cells with a high accuracy of 0.83 in the training set, and achieved a high AUC of 0.77 for the test set. Our study identified several potential biomarkers for diagnosis of SCZ based on multiple bioinformatics algorithms, and the constructed risk prediction model using these biomarkers achieved high accuracy. The results provide evidence for an improved understanding of the molecular mechanism of schizophrenia.

General Transcription Factor IIF Polypeptide 2: A Novel Therapeutic Target for Depression Identified Using an Integrated Bioinformatic Analysis

Depression currently affects 4% of the world’s population; it is associated with disability in 11% of the global population. Moreover, there are limited resources to treat depression effectively. Therefore, we aimed to identify a promising novel therapeutic target for depression using bioinformatic analysis. The GSE54568, GSE54570, GSE87610, and GSE92538 gene expression data profiles were retrieved from the Gene Expression Omnibus (GEO) database. We prepared the four GEO profiles for differential analysis, protein–protein interaction (PPI) network construction, and weighted gene co-expression network analysis (WGCNA). Gene Ontology functional enrichment and Kyoto Encyclopedia of Genes and Genomes metabolic pathway analyses were conducted to determine the key functions of the corresponding genes. Additionally, we performed correlation analyses of the hub genes with transcription factors, immune genes, and N6-methyladenosine (m6A) genes to reveal the functional landscape of the core genes associated with depression. Compared with the control samples, the depression samples contained 110 differentially expressed genes (DEGs), which comprised 56 downregulated and 54 upregulated DEGs. Moreover, using the WGCNA and PPI clustering analysis, the blue module and cluster 1 were found to be significantly correlated with depression. GTF2F2 was the only common gene identified using the differential analysis and WGCNA; thus, it was used as the hub gene. According to the enrichment analyses, GTF2F2 was predominantly involved in the cell cycle and JAK-STAT, PI3K-Akt, and p53 signaling pathways. Furthermore, differential and correlation analyses revealed that 9 transcription factors, 12 immune genes, and 2 m6A genes were associated with GTF2F2 in depression samples. GTF2F2 may serve as a promising diagnostic biomarker and treatment target of depression, and this study provides a novel perspective and valuable information to explore the molecular mechanism of depression.

Sex-Specific Brain Transcriptional Signatures in Human MDD and Their Correlates in Mouse Models of Depression

Major depressive disorder (MDD) is amongst the most devastating psychiatric conditions affecting several millions of people worldwide every year. Despite the importance of this disease and its impact on modern societies, still very little is known about the etiological mechanisms. Treatment strategies have stagnated over the last decades and very little progress has been made to improve the efficiency of current therapeutic approaches. In order to better understand the disease, it is necessary for researchers to use appropriate animal models that reproduce specific aspects of the complex clinical manifestations at the behavioral and molecular levels. Here, we review the current literature describing the use of mouse models to reproduce specific aspects of MDD and anxiety in males and females. We first describe some of the most commonly used mouse models and their capacity to display unique but also shared features relevant to MDD. We then transition toward an integral description, combined with genome-wide transcriptional strategies. The use of these models reveals crucial insights into the molecular programs underlying the expression of stress susceptibility and resilience in a sex-specific fashion. These studies performed on human and mouse tissues establish correlates into the mechanisms mediating the impact of stress and the extent to which different mouse models of chronic stress recapitulate the molecular changes observed in depressed humans. The focus of this review is specifically to highlight the sex differences revealed from different stress paradigms and transcriptional analyses both in human and animal models.

Glymphatic System Dysfunction in Central Nervous System Diseases and Mood Disorders

The glymphatic system, a recently discovered macroscopic waste removal system in the brain, has many unknown aspects, especially its driving forces and relationship with sleep, and thus further explorations of the relationship between the glymphatic system and a variety of possible related diseases are urgently needed. Here, we focus on the progress in current research on the role of the glymphatic system in several common central nervous system diseases and mood disorders, discuss the structural and functional abnormalities of the glymphatic system which may occur before or during the pathophysiological progress and the possible underlying mechanisms. We emphasize the relationship between sleep and the glymphatic system under pathological conditions and summarize the common imaging techniques for the glymphatic system currently available. The perfection of the glymphatic system hypothesis and the exploration of the effects of aging and endocrine factors on the central and peripheral regulatory pathways through the glymphatic system still require exploration in the future.

The Genetic Association Identified Between Intervertebral Disc Degeneration and Associated Risk Factors Based on a Systems Biology Approach

STUDY DESIGN

Genetic cross-over study of intervertebral disc degeneration (IDD) and its associated risk factors.

OBJECTIVE

The purpose is to identify molecular biomarkers that may be involved in the IDD process and to provide effective recommendations in combination with drug analysis via systems biology methods.

SUMMARY OF BACKGROUND DATA

The pathogenesis and genetic links of IDD are still unclear. Related research is mainly based on a single data set or gene, and the impact of related risk factors on IDD is often ignored.

METHODS

Identifying disease-associated biomarkers and therapeutic targets through a systems biology approach that Integrative network-based gene and multi-omics analysis. In this study, the differential expression of genes was analyzed through NCBI datasets, followed by enrichment analysis. The central protein was identified through the establishment of protein-protein interaction (PPI) network. Key genes were screened out by VENN diagram and reasonable suggestions were put forward based on gene-chemical drug analysis.

RESULTS

The IDD database analysis revealed 669 differentially expressed genes (DEGs) which were 22, 26, 168, 5, 38, 36, and 16 common DEGs with AG, SM, DEP, NAD, CED, OB, and HFD, respectively. GO and KEGG enrichment analysis may reveal the pathway by which these DEGs were involved. PPI network identified 10 central proteins including CCNB1, RETN, HMMR, BUB1, MPO, OIP5, HP, KIF11, BUB1B, and CDC25A. Three key genes BUB1, BUB1B, and CCNB1 were screened out and their expression might be related to the pathogenesis of IDD. According to the three chemical Dexamethasone, Nicotine, and Resvera-trol obtained from the analysis of genes-chemical drugs, reasonable treatment suggestions were put forward.

CONCLUSION

Genetic association between IDD and risk factors in the general population was revealed by association network. Important gene-related molecular pathways and chemical drugs closely related to IDD have been found. Further study can provide guidance for the treatment and prognosis of IDD.Level of Evidence: N/A.

Bioinformatics Approach to Identify Significant Biomarkers, Drug Targets Shared Between Parkinson's Disease and Bipolar Disorder: A Pilot Study

Parkinson’s disease (PD) is a neurodegenerative disorder responsible for shaking, rigidity, and trouble in walking and patients’ coordination ability and physical stability deteriorate day by day. Bipolar disorder (BD) is a psychiatric disorder which is the reason behind extreme shiftiness in mood, and frequent mood inversion may reach too high called mania. People with BD have a greater chance of developing PD during the follow-up period. A lot of work has been done to understand the key factors for developing these 2 diseases. But the molecular functionalities that trigger the development of PD in people with BD are not clear yet. In our study, we are intended to identify the molecular biomarkers and pathways shared between BD and PD. We have investigated the RNA-Seq gene expression data sets of PD and BD. A total of 45 common unique genes (32 up-regulated and 13 down-regulated) abnormally expressed in both PD and BD were identified by applying statistical methods on the GEO data sets. Gene ontology (GO) and BioCarta, KEGG, and Reactome pathways analysis of these 45 common dysregulated genes identified numerous altered molecular pathways such as mineral absorption, Epstein-Barr virus infection, HTLV-I infection, antigen processing, and presentation. Analysis of protein-protein interactions revealed 9 significant hub-proteins, namely RPL21, RPL34, CKS2, B2M, TNFRSF10A, DTX2, HLA-B, ATP2A3, and TAPBP. Significant transcription factors (IRF8, SPI1, RUNX1, and FOXA1) and posttranscriptional regulator microRNAs (hsa-miR-491-3p and hsa-miR-1246) are also found by analyzing gene-transcription factors and gene-miRNAs interactions, respectively. Protein-drug interaction analysis revealed hub-protein B2M’s interaction with molecular drug candidates like N-formylmethionine, 3-indolebutyric acid, and doxycycline. Finally, a link between pathological processes of PD and BD is identified at transcriptional level. This study may help us to predict the development of PD among the people suffering from BD and gives some clue to understand significant pathological mechanisms.

Evaluation of animal model congruence to human depression based on large-scale gene expression patterns of the CNS

Depression is a complex mental health disorder that is difficult to study. A wide range of animal models exist and for many of these data on large-scale gene expression patterns in the CNS are available. The goal of this study was to evaluate how well animal models match human depression by evaluating congruence and discordance of large-scale gene expression patterns in the CNS between almost 300 animal models and a portrait of human depression created from male and female datasets. Multiple approaches were used, including a hypergeometric based scoring system that rewards common gene expression patterns (e.g., up-up or down-down in both model and human depression), but penalizes opposing gene expression patterns. RRHO heat maps, Uniform Manifold Approximation Plot (UMAP), and machine learning were used to evaluate matching of models to depression. The top ranked model was a histone deacetylase (HDAC2) conditional knockout in forebrain neurons. Also highly ranked were various models for Alzheimer’s, including APPsa knock-in (2nd overall), APP knockout, and an APP/PS1 humanized double mutant. Other top models were the mitochondrial gene HTRA2 knockout (that is lethal in adulthood), a modified acetylcholinesterase, a Huntington’s disease model, and the CRTC1 knockout. Over 30 stress related models were evaluated and while some matched highly with depression, others did not. In most of the top models, a consistent dysregulation of MAP kinase pathway was identified and the genes NR4A1, BDNF, ARC, EGR2, and PDE7B were consistently downregulated as in humans with depression. Separate male and female portraits of depression were also evaluated to identify potential sex specific depression matches with models. Individual human depression datasets were also evaluated to allow for comparisons across the same brain regions. Heatmap, UMAP, and machine learning results supported the hypergeometric ranking findings. Together, this study provides new insights into how large-scale gene expression patterns may be similarly dysregulated in some animals models and humans with depression that may provide new avenues for understanding and treating depression.

Large-Scale Transcriptomics Studies Provide Insight Into Sex Differences in Depression

Major depressive disorder (MDD) is a leading cause of disability, affecting more than 300 million people worldwide. We first review the well-known sex difference in incidence of MDD, with women being twice as likely to be diagnosed as men, and briefly summarize how the impact of MDD varies between men and women, with sex differences in symptoms, severity, and antidepressant drug response. We then attempt to deconstruct the biological bases for MDD and discuss implications for sex differences research. Next, we review findings from human postmortem studies, both from selected candidate gene studies and from well-powered, unbiased transcriptomics studies, which suggest distinct, and possibly opposite, molecular changes in the brains of depressed men and women. We then discuss inherent challenges of research on the human postmortem brain and suggest paths forward that rely on thoughtful cohort design. Although studies indicate that circulating gonadal hormones might underlie the observed sex differences in MDD, we discuss how additional sex-specific factors, such as genetic sex and developmental exposure to gonadal hormones, may also contribute to altered vulnerability, and we highlight various nuances that we believe should be considered when determining mechanisms underlying observed sex differences. Altogether, this review highlights not only how various sex-specific factors might influence susceptibility or resilience to depression, but also how those sex-specific factors might result in divergent pathology in men and women.

Allele-specific DNA methylation maps in monozygotic twins discordant for psychiatric disorders reveal that disease-associated switching at the EIPR1 regulatory loci modulates neural function

The non-Mendelian features of phenotypic variations within monozygotic twins are likely complicated by environmental modifiers of genetic effects that have yet to be elucidated. Here, we performed methylome and genome analyses of blood DNA from psychiatric disorder-discordant monozygotic twins to study how allele-specific methylation (ASM) mediates phenotypic variations. We identified that thousands of genetic variants with ASM imbalances exhibit phenotypic variation-associated switching at regulatory loci. These ASMs have plausible causal associations with psychiatric disorders through effects on interactions between transcription factors, DNA methylations, and other epigenomic markers and then contribute to dysregulated gene expression, which eventually increases disease susceptibility. Moreover, we also experimentally validated the model that the rs4854158 alternative C allele at an ASM switching regulatory locus of EIPR1 encoding endosome-associated recycling protein-interacting protein 1, is associated with demethylation and higher RNA expression and shows lower TF binding affinities in unaffected controls. An epigenetic ASM switching induces C allele hypermethylation and then recruits repressive Polycomb repressive complex 2 (PRC2), reinforces trimethylation of lysine 27 on histone 3 and inhibits its transcriptional activity, thus leading to downregulation of EIPR1 in schizophrenia. Moreover, disruption of rs4854158 induces gain of EIPR1 function and promotes neural development and vesicle trafficking. Our study provides a powerful framework for identifying regulatory risk variants and contributes to our understanding of the interplay between genetic and epigenetic variants in mediating psychiatric disorder susceptibility.

Decreased DNA methylation at promoters and gene-specific neuronal hypermethylation in the prefrontal cortex of patients with bipolar disorder

Bipolar disorder (BD) is a severe mental disorder characterized by repeated mood swings. Although genetic factors are collectively associated with the etiology of BD, the underlying molecular mechanisms, particularly how environmental factors affect the brain, remain largely unknown. We performed promoter-wide DNA methylation analysis of neuronal and nonneuronal nuclei in the prefrontal cortex of patients with BD (N = 34) and controls (N = 35). We found decreased DNA methylation at promoters in both cell types in the BD patients. Gene Ontology (GO) analysis of differentially methylated region (DMR)-associated genes revealed enrichment of molecular motor-related genes in neurons, chemokines in both cell types, and ion channel- and transporter-related genes in nonneurons. Detailed GO analysis further revealed that growth cone- and dendrite-related genes, including NTRK2 and GRIN1, were hypermethylated in neurons of BD patients. To assess the effect of medication, neuroblastoma cells were cultured under therapeutic concentrations of three mood stabilizers. We observed that up to 37.9% of DMRs detected in BD overlapped with mood stabilizer-induced DMRs. Interestingly, mood stabilizer-induced DMRs showed the opposite direction of changes in DMRs, suggesting the therapeutic effects of mood stabilizers. Among the DMRs, 12 overlapped with loci identified in a genome-wide association study (GWAS) of BD. We also found significant enrichment of neuronal DMRs in the loci reported in another GWAS of BD. Finally, we performed qPCR of DNA methylation-related genes and found that DNMT3B was overexpressed in BD. The cell-type-specific DMRs identified in this study will be useful for understanding the pathophysiology of BD.

Downregulation by CNNM2 of ATP5MD expression in the 10q24.32 schizophrenia-associated locus involved in impaired ATP production and neurodevelopment

Genome-wide association studies (GWAS) have accelerated the discovery of numerous genetic variants associated with schizophrenia. However, most risk variants show a small effect size (odds ratio (OR) <1.2), suggesting that more functional risk variants remain to be identified. Here, we employed region-based multi-marker analysis of genomic annotation (MAGMA) to identify additional risk loci containing variants with large OR value from Psychiatry Genomics Consortium (PGC2) schizophrenia GWAS data and then employed summary-data-based mendelian randomization (SMR) to prioritize schizophrenia susceptibility genes. The top-ranked susceptibility gene ATP5MD, encoding an ATP synthase membrane subunit, is observed to be downregulated in schizophrenia by the risk allele of CNNM2-rs1926032 in the schizophrenia-associated 10q24.32 locus. The Atp5md knockout (KO) in mice was associated with abnormal startle reflex and gait, and ATP5MD knockdown (KD) in human induced pluripotent stem cell-derived neurons disrupted the neural development and mitochondrial respiration and ATP production. Moreover, CNNM2-rs1926032 KO could induce downregulation of ATP5MD expression and disruptions of mitochondrial respiration and ATP production. This study constitutes an important mechanistic component that links schizophrenia-associated CNNM2 regions to disruption in energy adenosine system modulation and neuronal function by long-distance chromatin domain downregulation of ATP5MD. This pathogenic mechanism provides therapeutic implications for schizophrenia.

Mitochondrial Alterations in Fibroblasts of Early Stage Bipolar Disorder Patients

This study aims to evaluate whether mitochondrial changes occur in the early stages of bipolar disorder (BD). Using fibroblasts derived from BD patients and matched controls, the levels of proteins involved in mitochondrial biogenesis and dynamics (fission and fusion) were evaluated by Western Blot analysis. Mitochondrial membrane potential (MMP) was studied using the fluorescent probe TMRE. Mitochondrial morphology was analyzed with the probe Mitotracker Green and mitophagy was evaluated by quantifying the co-localization of HSP60 (mitochondria marker) and LC3B (autophagosome marker) by immunofluorescence. Furthermore, the activity of the mitochondrial respiratory chain and the glycolytic capacity of controls and BD patients-derived cells were also studied using the Seahorse technology. BD patient-derived fibroblasts exhibit fragmented mitochondria concomitantly with changes in mitochondrial dynamics and biogenesis in comparison with controls. Moreover, a decrease in the MMP and increased mitophagy was observed in fibroblasts obtained from BD patients when compared with control cells. Impaired energetic metabolism due to inhibition of the mitochondrial electron transport chain (ETC) and subsequent ATP depletion, associated with glycolysis stimulation, was also a feature of BD fibroblasts. Overall, these results support the fact that mitochondrial disturbance is an early event implicated in BD pathophysiology that might trigger neuronal changes and modification of brain circuitry.

Bioinformatics analysis of a TF-miRNA-lncRNA regulatory network in major depressive disorder

Major depressive disorder (MDD) is a highly prevalent disease and one of the main causes of disability worldwide. Although many studies have partially revealed the occurrence and development process of MDD, the pathogeny and molecular mechanisms are not fully understood. Weighted gene coexpression network analysis (WGCNA) was used to explore the co-expression modules and hub genes in MDD. A protein-protein interaction (PPI) network of the most significant module and a TF-miRNA-lncRNA regulatory network of MDD were constructed using bioinformatics analysis tools. A KEGG pathway and gene ontology (GO) functional enrichment analysis of the genes in the significant module was performed using DAVID. Five hub genes in the PPI network and 10 genes in the TF-miRNA-lncRNA regulatory network with high degree values were identified, which may provide new insights for the investigation of key pathways, diagnostic bio-markers, and therapeutic targets of MDD. This study brings a novel perspective and provides valuable information to explore the molecular mechanism of MDD.

Mitochondrial dysfunction as a critical event in the pathophysiology of bipolar disorder

The understanding of the pathophysiology of bipolar disorder (BD) remains modest, despite recent advances in neurobiological research. The mitochondrial dysfunction hypothesis of bipolar disorder has been corroborated by several studies involving postmortem brain analysis, neuroimaging, and specific biomarkers in both rodent models and humans. Evidence suggests that BD might be related to abnormal mitochondrial morphology and dynamics, neuroimmune dysfunction, and atypical mitochondrial metabolism and oxidative stress pathways. Mitochondrial dysfunction in mood disorders is also associated with abnormal Ca2+ levels, glutamate excitotoxicity, an imbalance between pro- and antiapoptotic proteins towards apoptosis, abnormal gene expression of electron transport chain complexes, and decreased ATP synthesis. This paper aims to review and discuss the implications of mitochondrial dysfunction in BD etiology and to explore mitochondria as a potential target for novel therapeutic agents.

Identification of major depressive disorder disease-related genes and functional pathways based on system dynamic changes of network connectivity

BACKGROUND

Major depressive disorder (MDD) is a leading psychiatric disorder that involves complex abnormal biological functions and neural networks. This study aimed to compare the changes in the network connectivity of different brain tissues under different pathological conditions, analyzed the biological pathways and genes that are significantly related to disease progression, and further predicted the potential therapeutic drug targets.

METHODS

Expression of differentially expressed genes (DEGs) were analyzed with postmortem cingulate cortex (ACC) and prefrontal cortex (PFC) mRNA expression profile datasets downloaded from the Gene Expression Omnibus (GEO) database, including 76 MDD patients and 76 healthy subjects in ACC and 63 MDD patients and 63 healthy subjects in PFC. The co-expression network construction was based on system network analysis. The function of the genes was annotated by Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis. Human Protein Reference Database (HPRD, http://www.hprd.org/ ) was used for gene interaction relationship mapping.

RESULTS

We filtered 586 DEGs in ACC and 616 DEGs in PFC for further analysis. By constructing the co-expression network, we found that the gene connectivity was significantly reduced under disease conditions (P = 0.04 in PFC and P = 1.227e-09 in ACC). Crosstalk analysis showed that CD19, PTDSS2 and NDST2 were significantly differentially expressed in ACC and PFC of MDD patients. Among them, CD19 and PTDSS2 have been targeted by several drugs in the Drugbank database. KEGG pathway analysis demonstrated that the function of CD19 and PTDSS2 were enriched with the pathway of Glycerophospholipid metabolism and T cell receptor signaling pathway.

CONCLUSION

Co-expression network and tissue comparing analysis can identify signaling pathways and cross talk genes related to MDD, which may provide novel insight for understanding the molecular mechanisms of MDD.

Creation of a gene expression portrait of depression and its application for identifying potential treatments

Depression is a complex mental health disorder and the goal here was to identify a consistent underlying portrait of expression that ranks all genes from most to least dysregulated and indicates direction of change relative to controls. Using large-scale neural gene expression depression datasets, a combined portrait (for men and women) was created along with one for men and one for women only. The depressed brain was characterized by a "hypo" state, that included downregulation of activity-related genes, including EGR1, FOS, and ARC, and indications of a lower brain temperature and sleep-like state. MAP kinase and BDNF pathways were enriched with overlapping genes. Expression patterns suggested decreased signaling for GABA and for neuropeptides, CRH, SST, and CCK. GWAS depression genes were among depression portrait genes and common genes of interest included SPRY2 and PSEN2. The portraits were used with the drug repurposing approach of signature matching to identify treatments that could reverse depression gene expression patterns. Exercise was identified as the top treatment for depression for the combined and male portraits. Other non-traditional treatments that scored well were: curcumin, creatine, and albiflorin. Fluoxetine scored best among typical antidepressants. The creation of the portraits of depression provides new insights into the complex landscape of depression and a novel platform for evaluating and identifying potential new treatments.

Integrating Clinical and Genomic Analyses of Hippocampal-Prefrontal Circuit Disorder in Depression

Major depressive disorder (MDD) is a prevalent, devastating and recurrent mental disease. Hippocampus (HIP)-prefrontal cortex (PFC) neural circuit abnormalities have been confirmed to exist in MDD; however, the gene-related molecular features of this circuit in the context of depression remain unclear. To clarify this issue, we performed gene set enrichment analysis (GSEA) to comprehensively analyze the genetic characteristics of the two brain regions and used weighted gene correlation network analysis (WGCNA) to determine the main depression-related gene modules in the HIP-PFC network. To clarify the regional differences and consistency for MDD, we also compared the expression patterns and molecular functions of the key modules from the two brain regions. The results showed that candidate modules related to clinical MDD of HIP and PFC, which contained with 363 genes and 225 genes, respectively. Ninety-five differentially expressed genes (DEGs) were identified in the HIP candidate module, and 51 DEGs were identified in the PFC candidate module, with only 11 overlapping DEGs in these two regional modules. Combined with the enrichment results, although there is heterogeneity in the molecular functions in the HIP-PFC network of depression, the regulation of the MAPK cascade, Ras protein signal transduction and Ephrin signaling were significantly enriched in both brain regions, indicating that these biological pathways play important roles in MDD pathogenesis. Additionally, the high coefficient protein–protein interaction (PPI) network was constructed via STRING, and the top-10 coefficient genes were identified as hub genes via the cytoHubba algorithm. In summary, the present study reveals the gene expression characteristics of MDD and identifies common and unique molecular features and patterns in the HIP-PFC network. Our results may provide novel clues from the gene function perspective to explain the pathogenic mechanism of depression and to aid drug development. Further research is needed to confirm these findings and to investigate the genetic regulation mechanisms of different neural networks in depression.

Regulatory effect of lithium on hippocampal blood-brain barrier integrity in a rat model of depressive-like behavior

OBJECTIVES

Recent evidence has associated mood disorders with blood-brain barrier (BBB)/ neurovascular unit (NVU) dysfunction, and reduction in blood vessels coverage by the water channel aquaporin-4 (AQP4) immunoreactive astrocytes. Lithium is an established treatment for mood disorders, yet, its mechanism of action is partially understood. We investigated the effects of lithium on BBB integrity and NVU-related protein expression in chronic mild stress (CMS) rat model of depressive-like behavior.

METHODS

Male Wistar rats were exposed for 5 weeks to unpredictable mild stressors with daily co-administration of lithium chloride to half of the stressed and unstressed groups. Sucrose preference and open field tests were conducted to validate the depressive-like phenotype, and dynamic contrast-enhanced MRI analysis was utilized to assess BBB integrity in brain regions relevant to the pathophysiology of depression. Hippocampal AQP4 and claudin-5 expression were studied using immunofluorescence, western blot, and enzyme-linked immunosorbent assays.

RESULTS

Lithium administration to the stressed rats prevented the reductions in sucrose preference and distance traveled in the open field, and normalized the stress-induced hippocampal BBB hyperpermeability, whereas lithium administration to the unstressed rats increased hippocampal BBB permeability. Additionally, lithium treatment attenuated the decrease in hippocampal AQP4 to glial fibrillary acidic protein immunoreactivity ratio in the stressed rats and upregulated hippocampal claudin-5 and BDNF proteins expression.

CONCLUSIONS

Our findings suggest that lithium administration in a rat CMS model of depressive-like behavior is associated with attenuation of stressed-induced hippocampal BBB/NVU disruption. These protective effects may be relevant to the mode of action of lithium in depression.