A conserved BDNF, glutamate- and GABA-enriched gene module related to human depression identified by coexpression meta-analysis and DNA variant genome-wide association studies

Transcription-Driven Repurposing of Cardiotonic Steroids for Lithium Treatment of Severe Depression

Lithium is prescribed as a mood stabilizer for bipolar disorder and severe depression. However, the mechanism of action of lithium is unknown and there are major side effects associated with prolonged medication. This motivates a search for safer alternative drug repurposing candidates. Given that the drug mechanism may be encoded in transcriptional changes, we generated the gene expression profile for acute lithium treatment of cortical neuronal cultures. We found that the lithium-associated transcription response harbors a significant component that is the reverse of that seen in human brain samples from patients with major depression, bipolar disorder, and a mouse model of depression. Interrogating publicly available drug-driven expression data, we found that cardiotonic steroids drive gene expression in a correlated manner to our acute lithium profile. An analysis of the psychiatric medication cohort of the Norwegian Prescription Database showed that cardiotonic prescription is associated with a lower incidence of lithium prescription. Our transcriptional and epidemiological observations point towards cardiotonic steroids as possible repurposing candidates for lithium. These observations motivate a controlled trial to establish a causal connection and genuine therapeutic benefit in the context of depression.

Common Regulatory Mechanisms Mediated by Cuproptosis Genes in Inflammatory Bowel Disease and Major Depressive Disorder

BACKGROUND

The prevalence of major depressive disorder (MDD) among patients with inflammatory bowel disease (IBD) is significantly higher compared to the general population, suggesting a potential link between their pathogeneses. Cuproptosis, defined as cell death caused by intracellular copper accumulation, has not been thoroughly investigated in the context of IBD and MDD. This study aims to uncover the molecular mechanisms of cuproptosis-related genes (CRGs) in both conditions and to explore novel therapeutic strategies by the modulation of CRGs.

METHODS

In this study, we identified differentially expressed CRGs between normal and disease samples. We calculated the correlation among CRGs and between CRGs and immune cell infiltrations across various tissues. Four machine learning algorithms were employed to identify key CRGs associated with IBD and MDD. Additionally, drug sensitivity, molecular docking, and molecular dynamics simulations were conducted to predict therapeutic drugs for IBD and MDD.

RESULTS

We identified DLD, DLAT, DLST, PDHB, and DBT as common DE-CRGs, and DLD, LIAS, SLC31A1, SCO2, and CDKN2A as key CRGs associated with both IBD and MDD. Consequently, DLD was recognized as a shared biomarker in both diseases. A total of 37 potential therapeutic drugs were identified for IBD and MDD. Based on the molecular docking and molecular dynamics simulation analyses, barasertib and NTP-TAE684, which target DLAT, were predicted to be the most effective compounds.

CONCLUSIONS

These findings have substantially enhanced our understanding of the similarities and differences in the regulatory mechanisms of CRGs within brain-gut axis diseases. Key biomarkers have been identified, and potential therapeutic drugs have been predicted to effectively target IBD and MDD.

A single-nuclei paired multiomic analysis of the human midbrain reveals age- and Parkinson's disease-associated glial changes

Age is the primary risk factor for Parkinson's disease (PD), but how aging changes the expression and regulatory landscape of the brain remains unclear. Here we present a single-nuclei multiomic study profiling shared gene expression and chromatin accessibility of young, aged and PD postmortem midbrain samples. Combined multiomic analysis along a pseudopathogenesis trajectory reveals that all glial cell types are affected by age, but microglia and oligodendrocytes are further altered in PD. We present evidence for a disease-associated oligodendrocyte subtype and identify genes lost over the aging and disease process, including CARNS1, that may predispose healthy cells to develop a disease-associated phenotype. Surprisingly, we found that chromatin accessibility changed little over aging or PD within the same cell types. Peak-gene association patterns, however, are substantially altered during aging and PD, identifying cell-type-specific chromosomal loci that contain PD-associated single-nucleotide polymorphisms. Our study suggests a previously undescribed role for oligodendrocytes in aging and PD.

Exploring potential genes and mechanisms linking erectile dysfunction and depression

Background

The clinical correlation between erectile dysfunction (ED) and depression has been revealed in cumulative studies. However, the evidence of shared mechanisms between them was insufficient. This study aimed to explore common transcriptomic alterations associated with ED and depression.

Materials and methods

The gene sets associated with ED and depression were collected from the Gene Expression Omnibus (GEO) database. Comparative analysis was conducted to obtain common genes. Using R software and other appropriate tools, we conducted a range of analyses, including function enrichment, interactive network creation, gene cluster analysis, and transcriptional and post-transcriptional signature profiling. Candidate hub crosslinks between ED and depression were selected after external validation and molecular experiments. Furthermore, subpopulation location and disease association of hub genes were explored.

Results

A total of 85 common genes were identified between ED and depression. These genes strongly correlate with cell adhesion, redox homeostasis, reactive oxygen species metabolic process, and neuronal cell body. An interactive network consisting of 80 proteins and 216 interactions was thereby developed. Analysis of the proteomic signature of common genes highlighted eight major shared genes: CLDN5, COL7A1, LDHA, MAP2K2, RETSAT, SEMA3A, TAGLN, and TBC1D1. These genes were involved in blood vessel morphogenesis and muscle cell activity. A subsequent transcription factor (TF)-miRNA network showed 47 TFs and 88 miRNAs relevant to shared genes. Finally, CLDN5 and TBC1D1 were well-validated and identified as the hub crosslinks between ED and depression. These genes had specific subpopulation locations in the corpus cavernosum and brain tissue, respectively.

Conclusion

Our study is the first to investigate common transcriptomic alterations and the shared biological roles of ED and depression. The findings of this study provide insights into the referential molecular mechanisms underlying the co-existence between depression and ED.

Th17 Cells, Glucocorticoid Resistance, and Depression

Depression is a severe mental disorder that disrupts mood and social behavior and is one of the most common neuropsychological symptoms of other somatic diseases. During the study of the disease, a number of theories were put forward (monoamine, inflammatory, vascular theories, etc.), but none of those theories fully explain the pathogenesis of the disease. Steroid resistance is a characteristic feature of depression and can affect not only brain cells but also immune cells. T-helper cells 17 type (Th17) are known for their resistance to the inhibitory effects of glucocorticoids. Unlike the inhibitory effect on other subpopulations of T-helper cells, glucocorticoids can enhance the differentiation of Th17 lymphocytes, their migration to the inflammation, and the production of IL-17A, IL-21, and IL-23 in GC-resistant disease. According to the latest data, in depression, especially the treatment-resistant type, the number of Th17 cells in the blood and the production of IL-17A is increased, which correlates with the severity of the disease. However, there is still a significant gap in knowledge regarding the exact mechanisms by which Th17 cells can influence neuroinflammation in depression. In this review, we discuss the mutual effect of glucocorticoid resistance and Th17 lymphocytes on the pathogenesis of depression.

Awakening the dormant: Role of axonal guidance cues in stress-induced reorganization of the adult prefrontal cortex leading to depression-like behavior

Major depressive disorder (MDD) is a chronic and disabling disorder affecting roughly 280 million people worldwide. While multiple brain areas have been implicated, dysfunction of prefrontal cortex (PFC) circuitry has been consistently documented in MDD, as well as in animal models for stress-induced depression-like behavioral states. During brain development, axonal guidance cues organize neuronal wiring by directing axonal pathfinding and arborization, dendritic growth, and synapse formation. Guidance cue systems continue to be expressed in the adult brain and are emerging as important mediators of synaptic plasticity and fine-tuning of mature neural networks. Dysregulation or interference of guidance cues has been linked to depression-like behavioral abnormalities in rodents and MDD in humans. In this review, we focus on the emerging role of guidance cues in stress-induced changes in adult prefrontal cortex circuitry and in precipitating depression-like behaviors. We discuss how modulating axonal guidance cue systems could be a novel approach for precision medicine and the treatment of depression.

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.

Identification of novel targets and pathways to distinguish suicide dependent or independent on depression diagnosis

In recent years, postmortem brain studies have revealed that some molecular, cellular, and circuit changes associated with suicide, have an independent or additive effect on depression. The aim of the present study is to identify potential phenotypic, tissue, and sex-specific novel targets and pathways to distinguish depression or suicide from major depressive disorder (MDD) comorbid with suicide. The mRNA expression profiling datasets from two previous independent postmortem brain studies of suicide and depression (GSE102556 and GSE101521) were retrieved from the GEO database. Machine learning analysis was used to differentiate three regrouped gene expression profiles, i.e., MDD with suicide, MDD without suicide, and suicide without depression. Weighted correlation network analysis (WGCNA) was further conducted to identify the key modules and hub genes significantly associated with each of these three sub-phenotypes. TissueEnrich approaches were used to find the essential brain tissues and the difference of tissue enriched genes between depression with or without suicide. Dysregulated gene expression cross two variables, including phenotypes and tissues, were determined by global analysis with Vegan. RRHO analysis was applied to examine the difference in global expression pattern between male and female groups. Using the optimized machine learning model, several ncRNAs and mRNAs with higher AUC and MeanDecreaseGini, including GCNT1P1 and AC092745.1, etc., were identified as potential molecular targets to distinguish suicide with, or without MDD and depression without suicide. WGCNA analysis identified some key modules significantly associated with these three phenotypes, and the gene biological functions of the key modules mainly relate to ncRNA and miRNA processing, as well as oxidoreductase and dehydrogenase activity. Hub genes such as RP11-349A22.5, C20orf196, MAPK8IP3 and RP11-697N18.2 were found in these key modules. TissueEnrich analysis showed that nucleus accumbens and subiculum were significantly changed among the 6 brain regions studied. Global analysis with Vegan and RRHO identified PRS26, ARNT and SYN3 as the most significantly differentially expressed genes across phenotype and tissues, and there was little overlap between the male and female groups. In this study, we have identified novel gene targets, as well as annotated functions of co-expression patterns and hub genes that are significantly distinctive between depression with suicide, depression without suicide, and suicide without depression. Moreover, global analysis across three phenotypes and tissues confirmed the evidence of sex difference in mood disorders.

Genome-wide association studies on Northern Italy isolated populations provide further support concerning genetic susceptibility for major depressive disorder

OBJECTIVES

Major depressive disorder (MDD) is a psychiatric disorder with pathogenesis influenced by both genetic and environmental factors. To date, the molecular-level understanding of its aetiology remains unclear. Thus, we aimed to identify genetic variants and susceptibility genes for MDD with a genome-wide association study (GWAS) approach.

METHODS

We performed a meta-analysis of GWASs and a gene-based analysis on two Northern Italy isolated populations (cases/controls n = 166/472 and 33/320), followed by replication and polygenic risk score (PRS) analyses in Italian independent samples (cases n = 464, controls n = 339).

RESULTS

We identified two novel MDD-associated genes, KCNQ5 (lead SNP rs867262, p = 3.82 × 10^-9) and CTNNA2 (rs6729523, p = 1.25 × 10^-8). The gene-based analysis revealed another six genes (p < 2.703 × 10^-6): GRM7, CTNT4, SNRK, SRGAP3, TRAPPC9, and FHIT. No replication of the genome-wide significant SNPs was found in the independent cohort, even if 14 SNPs around CTNNA2 showed association with MDD and related phenotypes at the nominal level of p (<0.05). Furthermore, the PRS model developed in the discovery cohort discriminated cases and controls in the replication cohort.

CONCLUSIONS

Our work suggests new possible genes associated with MDD, and the PRS analysis confirms the polygenic nature of this disorder. Future studies are required to better understand the role of these findings in MDD.

Neuroimmune transcriptome changes in patient brains of psychiatric and neurological disorders

Neuroinflammation has been implicated in multiple brain disorders but the extent and the magnitude of change in immune-related genes (IRGs) across distinct brain disorders has not been directly compared. In this study, 1275 IRGs were curated and their expression changes investigated in 2467 postmortem brains of controls and patients with six major brain disorders, including schizophrenia (SCZ), bipolar disorder (BD), autism spectrum disorder (ASD), major depressive disorder (MDD), Alzheimer's disease (AD), and Parkinson's disease (PD). There were 865 IRGs present across all microarray and RNA-seq datasets. More than 60% of the IRGs had significantly altered expression in at least one of the six disorders. The differentially expressed immune-related genes (dIRGs) shared across disorders were mainly related to innate immunity. Moreover, sex, tissue, and putative cell type were systematically evaluated for immune alterations in different neuropsychiatric disorders. Co-expression networks revealed that transcripts of the neuroimmune systems interacted with neuronal-systems, both of which contribute to the pathology of brain disorders. However, only a few genes with expression changes were also identified as containing risk variants in genome-wide association studies. The transcriptome alterations at gene and network levels may clarify the immune-related pathophysiology and help to better define neuropsychiatric and neurological disorders.

CIP2A deficiency promotes depression-like behaviors in mice through inhibition of dendritic arborization

Major depressive disorder (MDD) is a severe mental illness. Decreased brain plasticity and dendritic fields have been consistently found in MDD patients and animal models; however, the underlying molecular mechanisms remain to be clarified. Here, we demonstrate that the deletion of cancerous inhibitor of PP2A (CIP2A), an endogenous inhibitor of protein phosphatase 2A (PP2A), leads to depression-like behaviors in mice. Hippocampal RNA sequencing analysis of CIP2A knockout mice shows alterations in the PI3K-AKT pathway and central nervous system development. In primary neurons, CIP2A stimulates AKT activity and promotes dendritic development. Further analysis reveals that the effect of CIP2A in promoting dendritic development is dependent on PP2A-AKT signaling. In vivo, CIP2A deficiency-induced depression-like behaviors and impaired dendritic arborization are rescued by AKT activation. Decreased CIP2A expression and impaired dendrite branching are observed in a mouse model of chronic unpredictable mild stress (CUMS). Indicative of clinical relevance to humans, CIP2A expression is found decreased in transcriptomes from MDD patients. In conclusion, we discover a novel mechanism that CIP2A deficiency promotes depression through the regulation of PP2A-AKT signaling and dendritic arborization.

Gene Signatures Associated with Temporal Rhythm as Diagnostic Markers of Major Depressive Disorder and Their Role in Immune Infiltration

Temporal rhythm (TR) is involved in the pathophysiology and treatment response of major depressive disorder (MDD). However, there have been few systematic studies on the relationship between TR-related genes (TRRGs) and MDD. This study aimed to develop a novel prognostic gene signature based on the TRRGs in MDD. We extracted expression information from the Gene Expression Omnibus (GEO) database and retrieved TRRGs from GeneCards. Expressed genes (TRRDEGs) were identified differentially, and their potential biological functions were analyzed. Subsequently, association analysis and receiver operating characteristic (ROC) curves were adopted for the TRRDEGs. Further, upstream transcription factor (TF)/miRNA and potential drugs targeting MDD were predicted. Finally, the CIBERSORT algorithm was used to estimate the proportions of immune cell subsets. We identified six TRRDEGs that were primarily involved in malaria, cardiac muscle contraction, and the calcium-signaling pathway. Four genes (CHGA, CCDC47, ACKR1, and FKBP11) with an AUC of >0.70 were considered TRRDEGs hub genes for ROC curve analysis. Outcomes showed that there were a higher ratio of T cells, gamma-delta T cells, monocytes, and neutrophils, and lower degrees of CD8+ T cells, and memory resting CD4+ T cells in TRRDEGs. Four new TRRDEG signatures with excellent diagnostic performance and a relationship with the immune microenvironment were identified.

Discovery of 1-(Hetero)aryl-β-carboline Derivatives as IDO1/TDO Dual Inhibitors with Antidepressant Activity

Depression is the leading cause of global burden of disease and disability. Abnormalities in the kynurenine pathway of tryptophan degradation have been closely linked to the pathogenesis of depression. An integrative bioinformatics analysis demonstrated that indoleamine 2,3-dioxygenase 1 (IDO1) and tryptophan 2,3-dioxygenase (TDO) are potential targets for the development of antidepressants. A series of 1-(hetero)aryl-β-carboline derivatives were designed, synthesized, and evaluated as novel IDO1/TDO dual inhibitors. Among them, compound 28 displayed potent inhibition of both IDO1 (IC₅₀ = 3.53 μM) and TDO (IC₅₀ = 1.15 μM) and had an acceptable safety profile and pharmacokinetic properties. Compound 28 also rescued lipopolysaccharide-induced depressive-like behavior in mice. Further studies revealed that 28 likely had unique antidepressant mechanisms involving suppressing microglial activation, lowering IDO1 expression, and reducing proinflammatory cytokine and kynurenine levels in the mouse brain. Overall, this work provides practical guidance for the development of IDO1/TDO dual inhibitors to treat inflammation-induced depression.

Brain differential gene expression and blood cross-validation of a molecular signature of patients with major depressive disorder

INTRODUCTION

The agreement between clinicians diagnosing major depressive disorder (MDD) is poor. The objective of this study was to identify a reproducible and robust gene expression marker capable of differentiating MDD from healthy control (HC) subjects.

MATERIALS AND METHODS

Brain and blood gene expression datasets were searched, which included subjects with MDD and HC. The largest database including different areas of brain samples (GSE80655) was used to identify an initial gene expression marker. Tests of robustness and reproducibility were then implemented in 13 brain and 7 blood independent datasets. Correlations between expression in brain and blood samples were also examined. Finally, an enrichment analysis to explore the marker biological meaning was completed.

RESULTS

Twenty-eight genes were differentially expressed in GSE80655, of which 23 were critical to differentiate MDD from HC. The accuracy obtained using the 23 genes was 0.77 and 0.8, before and after the forward selection model, respectively. The gene marker's robustness and reproducibility were between the range of 0.46 and 0.63 in the other brain datasets and between 0.45 and 0.78 for the blood datasets. Brain and blood expression tended to correlate in some samples. Thirteen of the 23 genes were related to stress and immune response.

CONCLUSION

A 23 gene expression marker was able to distinguish subjects with MDD from HC, with adequate reproducibility and low robustness in the independent databases investigated. This gene set was similarly expressed in the brain and blood and involved genes related to stress and immune response.

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.

BDNF Genetic Variant and Its Genotypic Fluctuation in Major Depressive Disorder

Major depressive disorder (MDD) still has an unknown etiology and mechanisms. Many studies have been conducted seeking to associate and understand the connection of different genetic variants to this disease. Researchers have extensively studied the brain-derived neurotrophic factor (BDNF) Val66Met genetic variant in MDD; yet, their findings remain inconsistent. This systematic review sought to verify the GG (Val/Val) genotype frequency fluctuation in different populations with MDD. For this, we searched in different databases and, after applying the eligibility criteria, selected 17 articles. Most studies demonstrate the higher frequency of the ancestral (wild) GG (Val/Val) genotype, although associations of the polymorphic A (Met) allele, changes in BDNF protein serum levels, or both were also found in MDD, whether related to the disease's development or other factors. Nevertheless, despite these findings, disagreements between several studies are seen. For this reason, further BDNF Val66Met genetic variant studies should not only bridge the gap in the knowledge of this polymorphism's role in MDD's different facets but also analyze the genotypic and phenotypic heterogeneity in different populations to help provide a better quality of life for patients.

Transcriptome Profiling of Dysregulated GPCRs Reveals Overlapping Patterns across Psychiatric Disorders and Age-Disease Interactions

G-protein-coupled receptors (GPCRs) play an integral role in the neurobiology of psychiatric disorders. Almost all neurotransmitters involved in psychiatric disorders act through GPCRs, and GPCRs are the most common targets of therapeutic drugs currently used in the treatment of psychiatric disorders. However, the roles of GPCRs in the etiology and pathophysiology of psychiatric disorders are not fully understood. Using publically available datasets, we performed a comprehensive analysis of the transcriptomic signatures of G-protein-linked signaling across the major psychiatric disorders: autism spectrum disorder (ASD), schizophrenia (SCZ), bipolar disorder (BP), and major depressive disorder (MDD). We also used the BrainSpan transcriptomic dataset of the developing human brain to examine whether GPCRs that exhibit chronological age-associated expressions have a higher tendency to be dysregulated in psychiatric disorders than age-independent GPCRs. We found that most GPCR genes were differentially expressed in the four disorders and that the GPCR superfamily as a gene cluster was overrepresented in the four disorders. We also identified a greater amplitude of gene expression changes in GPCRs than other gene families in the four psychiatric disorders. Further, dysregulated GPCRs overlapped across the four psychiatric disorders, with SCZ exhibiting the highest overlap with the three other disorders. Finally, the results revealed a greater tendency of age-associated GPCRs to be dysregulated in ASD than random GPCRs. Our results substantiate the central role of GPCR signaling pathways in the etiology and pathophysiology of psychiatric disorders. Furthermore, our study suggests that common GPCRs' signaling may mediate distinct phenotypic presentations across psychiatric disorders. Consequently, targeting these GPCRs could serve as a common therapeutic strategy to treat specific clinical symptoms across psychiatric disorders.

Patterns of cilia gene dysregulations in major psychiatric disorders

Primary cilia function as cells' antennas to detect and transduce external stimuli and play crucial roles in cell signaling and communication. The vast majority of cilia genes that are causally linked with ciliopathies are also associated with neurological deficits, such as cognitive impairments. Yet, the roles of cilia dysfunctions in the pathogenesis of psychiatric disorders have not been studied. Our aim is to identify patterns of cilia gene dysregulation in the four major psychiatric disorders: schizophrenia (SCZ), autism spectrum disorder (ASD), bipolar disorder (BP), and major depressive disorder (MDD). For this purpose, we acquired differentially expressed genes (DEGs) from the largest and most recent publicly available databases. We found that 42%, 24%, 17%, and 15% of brain-expressed cilia genes were significantly differentially expressed in SCZ, ASD, BP, and MDD, respectively. Several genes exhibited cross-disorder overlap, suggesting that typical cilia signaling pathways' dysfunctions determine susceptibility to more than one psychiatric disorder or may partially underlie their pathophysiology. Our study revealed that genes encoding proteins of almost all sub-cilia structural and functional compartments were dysregulated in the four psychiatric disorders. Strikingly, the genes of 75% of cilia GPCRs and 50% of the transition zone proteins were differentially expressed in SCZ. The present study is the first to draw associations between cilia and major psychiatric disorders, and is the first step toward understanding the role that cilia components play in their pathophysiological processes, which may lead to novel therapeutic targets for these disorders.

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.

Machine learning and bioinformatic analysis of brain and blood mRNA profiles in major depressive disorder: A case-control study

This study analyzed gene expression messenger RNA data, from cases with major depressive disorder (MDD) and controls, using supervised machine learning (ML). We built on the methodology of prior studies to obtain more generalizable/reproducible results. First, we obtained a classifier trained on gene expression data from the dorsolateral prefrontal cortex of post-mortem MDD cases (n = 126) and controls (n = 103). An average area-under-the-receiver-operating-characteristics-curve (AUC) from 10-fold cross-validation of 0.72 was noted, compared to an average AUC of 0.55 for a baseline classifier (p = .0048). The classifier achieved an AUC of 0.76 on a previously unused testing-set. We also performed external validation using DLPFC gene expression values from an independent cohort of matched MDD cases (n = 29) and controls (n = 29), obtained from Affymetrix microarray (vs. Illumina microarray for the original cohort) (AUC: 0.62). We highlighted gene sets differentially expressed in MDD that were enriched for genes identified by the ML algorithm. Next, we assessed the ML classification performance in blood-based microarray gene expression data from MDD cases (n = 1,581) and controls (n = 369). We observed a mean AUC of 0.64 on 10-fold cross-validation, which was significantly above baseline (p = .0020). Similar performance was observed on the testing-set (AUC: 0.61). Finally, we analyzed the classification performance in covariates subgroups. We identified an interesting interaction between smoking and recall performance in MDD case prediction (58% accurate predictions in cases who are smokers vs. 43% accurate predictions in cases who are non-smokers). Overall, our results suggest that ML in combination with gene expression data and covariates could further our understanding of the pathophysiology in MDD.

Transcriptional markers of excitation-inhibition balance in germ-free mice show region-specific dysregulation and rescue after bacterial colonization

BACKGROUND

Studies of germ-free (GF) mice demonstrate that gut microbiota can influence behaviour by modulating neurochemical pathways in the brain, and that bacterial colonization normalizes behavioural deficits in GF-mice. Since disrupted GABAergic and glutamatergic signaling are reported in mood disorders, this study investigated the effect of gut microbiota manipulations on EIB-relevant gene expression in the brain.

METHODS

GF Swiss-Webster mice were colonized with E. coli JM83, complex microbiota (specific-pathogen-free; SPF), or no microbiota, and compared with controls (n = 6/group). 21 synaptic genes representing GABAergic, glutamatergic, BDNF, and astrocytic functions were measured in the hippocampus, amygdala, and prefrontal cortex using quantitative PCR. Gene co-expression analysis was used to identify gene modules related to colonization status, and compared by permutation analysis. Gene expression profiles were compared to existing post-mortem cohorts of depressed subjects (n = 28 cases vs 28 controls).

RESULTS

Region-specific alterations in gene expression were observed in GF-mice compared to controls. 58% of all genes (14/24) altered in GF-mice were normalized following SPF-colonization. GF-mice displayed disorganization of gene co-expression networks in all three brain regions (hippocampus, p = 0.0003; amygdala, p = 0.0012; mPFC, p = 0.0069), which was restored by SPF colonization in hippocampus (p v.s. GF = 0.0003, p v.s. control = 0.60). The hippocampal gene expression profile in GF-mice was significantly correlated with that in human depression (ρ = 0.51, p = 0.027), and this correlation was not observed after colonization.

CONCLUSION

Together, we show that the absence of gut microbiota disrupts the expression of EIB-relevant genes in mice, and colonization restores EIB-relevant expression, in ways that are relevant to human depression.

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.

Modulation of DNA Methylation and Gene Expression in Rodent Cortical Neuroplasticity Pathways Exerts Rapid Antidepressant-Like Effects

BACKGROUND

Stress increases DNA methylation, primarily a suppressive epigenetic mechanism catalyzed by DNA methyltransferases (DNMT), and decreases the expression of genes involved in neuronal plasticity and mood regulation. Despite chronic antidepressant treatment decreases stress-induced DNA methylation, it is not known whether inhibition of DNMT would convey rapid antidepressant-like effects.

AIM

This work tested such a hypothesis and evaluated whether a behavioral effect induced by DNMT inhibitors (DNMTi) corresponds with changes in DNA methylation and transcript levels in genes consistently associated with the neurobiology of depression and synaptic plasticity (BDNF, TrkB, 5-HT1A, NMDA, and AMPA).

METHODS

Male Wistar rats received intraperitoneal (i.p.) injection of two pharmacologically different DNMTi (5-AzaD 0.2 and 0.6 mg/kg or RG108 0.6 mg/kg) or vehicle (1 ml/kg), 1 h or 7 days before the learned helplessness test (LH). DNA methylation in target genes and the correspondent transcript levels were measured in the hippocampus (HPC) and prefrontal cortex (PFC) using meDIP-qPCR. In parallel separate groups, the antidepressant-like effect of 5-AzaD and RG108 was investigated in the forced swimming test (FST). The involvement of cortical BDNF-TrkB-mTOR pathways was assessed by intra-ventral medial PFC (vmPFC) injections of rapamycin (mTOR inhibitor), K252a (TrkB receptor antagonist), or vehicle (0.2 μl/side).

RESULTS

We found that both 5-AzaD and RG108 acutely and 7 days before the test decreased escape failures in the LH. LH stress increased DNA methylation and decreased transcript levels of BDNF IV and TrkB in the PFC, effects that were not significantly attenuated by RG108 treatment. The systemic administration of 5-AzaD (0.2 mg/kg) and RG108 (0.2 mg/kg) induced an antidepressant-like effect in FST, which was, however, attenuated by TrkB and mTOR inhibition into the vmPFC.

CONCLUSION

These findings suggest that acute inhibition of stress-induced DNA methylation promotes rapid and sustained antidepressant effects associated with increased BDNF-TrkB-mTOR signaling in the PFC.

Altered GABA-mediated information processing and cognitive dysfunctions in depression and other brain disorders

Cognitive dysfunctions, including impaired attention, learning, memory, planning and problem solving, occur in depressive episodes, often persist during remission, predict relapse, worsen with recurrent episodes, and are not treated by current antidepressants or other medications. Cognitive symptoms are also present in other psychiatric disorders, are a hallmark of aging, and define several late-life disorders, including Alzheimer's disease. This pervasive occurrence suggests either a non-specific outcome of a diseased brain, or a shared underlying pathology contributing to this symptom dimension. Recent findings suggest a role for altered GABAergic inhibition in cognitive symptoms. Cellular, molecular and biochemical studies in human subjects report changes affecting the gamma-amino butyric acid (GABA) system, specifically somatostatin-expressing (SST+) GABAergic interneurons, across brain disorders and during aging. SST+ neurons gate excitatory input onto pyramidal neurons within cortical microcircuits. Experimentally reducing the function of these neurons affects excitatory signal-to-noise ratio, reduces synchronized cellular and neural activity, and leads to cognitive dysfunctions. Conversely, augmenting SST+ cell post-synaptic α5-GABA-A receptor activity has pro-cognitive efficacy in stress and aging models. Together, this suggests that reduced signaling of the SST+ neuron/α5-GABA-A receptor pathway contributes to cognitive dysfunctions, and that it represents a novel therapeutic target for remediating mood and cognitive symptoms in depression, other psychiatric disorders and during aging.

A Comprehensive Analysis of Unique and Recurrent Copy Number Variations in Alzheimer's Disease and its Related Disorders

BACKGROUND

Copy number variations (CNVs) play an important role in the genetic etiology of various neurological disorders, including Alzheimer's disease (AD). Type 2 diabetes mellitus (T2DM) and major depressive disorder (MDD) were shown to have share mechanisms and signaling pathways with AD.

OBJECTIVE

We aimed to assess CNVs regions that may harbor genes contributing to AD, T2DM, and MDD in 67 Saudi familial and sporadic AD patients, with no alterations in the known genes of AD and genotyped previously for APOE.

METHODS

DNA was analyzed using the CytoScan-HD array. Two layers of filtering criteria were applied. All the identified CNVs were checked in the Database of Genomic Variants (DGV).

RESULTS

A total of 1086 CNVs (565 gains and 521 losses) were identified in our study. We found 73 CNVs harboring genes that may be associated with AD, T2DM or MDD. Nineteen CNVs were novel. Most importantly, 42 CNVs were unique in our studied cohort existing only in one patient. Two large gains on chromosomes 1 and 13 harbored genes implicated in the studied disorders. We identified CNVs in genes that encode proteins involved in the metabolism of amyloid-β peptide (AGRN, APBA2, CR1, CR2, IGF2R, KIAA0125, MBP, RER1, RTN4R, VDR and WISPI) or Tau proteins (CACNAIC, CELF2, DUSP22, HTRA1 and SLC2A14).

CONCLUSION

The present work provided information on the presence of CNVs related to AD, T2DM, and MDD in Saudi Alzheimer's patients.

Association Between FoxO1, A2M, and TGF-β1, Environmental Factors, and Major Depressive Disorder

INTRODUCTION

Investigations of gene-environment (G×E) interactions in major depressive disorder (MDD) have been limited to hypothesis testing of candidate genes while poly-gene-environmental causation has not been adequately address. To this end, the present study analyzed the association between three candidate genes, two environmental factors, and MDD using a hypothesis-free testing approach.

METHODS

A logistic regression model was used to analyze interaction effects; a hierarchical regression model was used to evaluate the effects of different genotypes and the dose-response effects of the environment; genetic risk score (GRS) was used to estimate the cumulative contribution of genetic factors to MDD; and protein-protein interaction (PPI) analyses were carried out to evaluate the relationship between candidate genes and top MDD susceptibility genes.

RESULTS

Allelic association analyses revealed significant effects of the interaction between the candidate genes Forkhead box (Fox)O1, α2-macroglobulin (A2M), and transforming growth factor (TGF)-β1 genes and the environment on MDD. Gene-gene (G×G) and gene-gene-environment (G×G×E) interactions in MDD were also included in the model. Hierarchical regression analysis showed that the effect of environmental factors on MDD was greater in homozygous than in heterozygous mutant genotypes of the FoxO1 and TGF-β1 genes; a dose-response effect between environment and MDD on genotypes was also included in this model. Haplotype analyses revealed significant global and individual effects of haplotypes on MDD in the whole sample as well as in subgroups. There was a significant association between GRS and MDD (P = 0.029) and a GRS and environment interaction effect on MDD (P = 0.009). Candidate and top susceptibility genes were connected in PPI networks.

CONCLUSIONS

FoxO1, A2M, and TGF-β1 interact with environmental factors and with each other in MDD. Multi-factorial G×E interactions may be responsible for a higher explained variance and may be associated with causal factors and mechanisms that could inform new diagnosis and therapeutic strategies, which can contribute to the personalized medicine of MDD.

Gene Regulatory Network of Dorsolateral Prefrontal Cortex: a Master Regulator Analysis of Major Psychiatric Disorders

Despite the strong genetic component of psychiatric disorders, traditional genetic studies have failed to find individual genes of large effect size. Thus, alternative methods, using bioinformatics, have been proposed to solve these biological puzzles. Of these, here we employ systems biology-based approaches to identify potential master regulators (MRs) of bipolar disorder (BD), schizophrenia (SZ), and major depressive disorder (MDD), their association with biological processes and their capacity to differentiate disorders' phenotypes. High-throughput gene expression data was used to reconstruct standard human dorsolateral prefrontal cortex regulatory transcriptional network, which was then queried for regulatory units and MRs associated with the psychiatric disorders of interest. Furthermore, the activity status (active or repressed) of MR candidates was obtained and used in cluster analysis to characterize disease phenotypes. Finally, we explored the biological processes modulated by the MRs using functional enrichment analysis. Thirty-one, thirty-four, and fifteen MR candidates were identified in BD, SZ, and MDD, respectively. The activity state of these MRs grouped the illnesses in three clusters: MDD only, mostly BD, and a third one with BD and SZ. While BD and SZ share several biological processes related to ion transport and homeostasis, synapse, and immune function, SZ showed peculiar enrichment of processes related to cytoskeleton and neuronal structure. Meanwhile, MDD presented mostly processes related to glial development and fatty acid metabolism. Our findings suggest notable differences in functional enrichment between MDD and BD/SZ. Furthermore, similarities between BD and SZ may impose particular challenges in attempts to discriminate these pathologies based solely on their transcriptional profiles. Nevertheless, we believe that systems-oriented approaches are promising strategies to unravel the pathophysiology peculiarities underlying mental illnesses and reveal therapeutic targets.

Using literature-based discovery to identify candidate genes for the interaction between myocardial infarction and depression

Background

A multidirectional relationship has been demonstrated between myocardial infarction (MI) and depression. However, the causal genetic factors and molecular mechanisms underlying this interaction remain unclear. The main purpose of this study was to identify potential candidate genes for the interaction between the two diseases.

Methods

Using a bioinformatics approach and existing gene expression data in the biomedical discovery support system (BITOLA), we defined the starting concept X as “Myocardial Infarction” and end concept Z as “Major Depressive Disorder” or “Depressive disorder”. All intermediate concepts relevant to the “Gene or Gene Product” for MI and depression were searched. Gene expression data and tissue-specific expression of potential candidate genes were evaluated using the Human eFP (electronic Fluorescent Pictograph) Browser, and intermediate concepts were filtered by manual inspection.

Results

Our analysis identified 128 genes common to both the “MI” and “depression” text mining concepts. Twenty-three of the 128 genes were selected as intermediates for this study, 9 of which passed the manual filtering step. Among the 9 genes, LCAT, CD4, SERPINA1, IL6, and PPBP failed to pass the follow-up filter in the Human eFP Browser, due to their low levels in the heart tissue. Finally, four genes (GNB3, CNR1, MTHFR, and NCAM1) remained.

Conclusions

GNB3, CNR1, MTHFR, and NCAM1 are putative new candidate genes that may influence the interactions between MI and depression, and may represent potential targets for therapeutic intervention.

Neural cell adhesion molecule Negr1 deficiency in mouse results in structural brain endophenotypes and behavioral deviations related to psychiatric disorders

Neuronal growth regulator 1 (NEGR1) belongs to the immunoglobulin (IgLON) superfamily of cell adhesion molecules involved in cortical layering. Recent functional and genomic studies implicate the role of NEGR1 in a wide spectrum of psychiatric disorders, such as major depression, schizophrenia and autism. Here, we investigated the impact of Negr1 deficiency on brain morphology, neuronal properties and social behavior of mice. In situ hybridization shows Negr1 expression in the brain nuclei which are central modulators of cortical-subcortical connectivity such as the island of Calleja and the reticular nucleus of thalamus. Brain morphological analysis revealed neuroanatomical abnormalities in Negr1^−/− mice, including enlargement of ventricles and decrease in the volume of the whole brain, corpus callosum, globus pallidus and hippocampus. Furthermore, decreased number of parvalbumin-positive inhibitory interneurons was evident in Negr1^−/− hippocampi. Behaviorally, Negr1^−/− mice displayed hyperactivity in social interactions and impairments in social hierarchy. Finally, Negr1 deficiency resulted in disrupted neurite sprouting during neuritogenesis. Our results provide evidence that NEGR1 is required for balancing the ratio of excitatory/inhibitory neurons and proper formation of brain structures, which is prerequisite for adaptive behavioral profiles. Therefore, Negr1^−/− mice have a high potential to provide new insights into the neural mechanisms of neuropsychiatric disorders.

Meta-analysis of expression and methylation signatures indicates a stress-related epigenetic mechanism in multiple neuropsychiatric disorders

Similar environmental risk factors have been implicated in different neuropsychiatric disorders (including major psychiatric and neurodegenerative diseases), indicating the existence of common epigenetic mechanisms underlying the pathogenesis shared by different illnesses. To investigate such commonality, we applied an unsupervised computational approach identifying several consensus co-expression and co-methylation signatures from a data cohort of postmortem prefrontal cortex (PFC) samples from individuals with six different neuropsychiatric disorders-schizophrenia, bipolar disorder, major depression, alcoholism, Alzheimer's and Parkinson's-as well as healthy controls. Among our results, we identified a pair of strongly interrelated co-expression and co-methylation (E-M) signatures showing consistent and significant disease association in multiple types of disorders. This E-M signature was enriched for interneuron markers, and we further demonstrated that it is unlikely for this enrichment to be due to varying subpopulation abundance of normal interneurons across samples. Moreover, gene set enrichment analysis revealed overrepresentation of stress-related biological processes in this E-M signature. Our integrative analysis of expression and methylation profiles, therefore, suggests a stress-related epigenetic mechanism in the brain, which could be associated with the pathogenesis of multiple neuropsychiatric diseases.

Identification of evolutionarily conserved gene networks mediating neurodegenerative dementia

Identifying the mechanisms through which genetic risk causes dementia is an imperative for new therapeutic development. Here, we apply a multistage, systems biology approach to elucidate the disease mechanisms in frontotemporal dementia. We identify two gene coexpression modules that are preserved in mice harboring mutations in MAPT, GRN and other dementia mutations on diverse genetic backgrounds. We bridge the species divide via integration with proteomic and transcriptomic data from the human brain to identify evolutionarily conserved, disease-relevant networks. We find that overexpression of miR-203, a hub of a putative regulatory microRNA (miRNA) module, recapitulates mRNA coexpression patterns associated with disease state and induces neuronal cell death, establishing this miRNA as a regulator of neurodegeneration. Using a database of drug-mediated gene expression changes, we identify small molecules that can normalize the disease-associated modules and validate this experimentally. Our results highlight the utility of an integrative, cross-species network approach to drug discovery.

wTO: an R package for computing weighted topological overlap and a consensus network with integrated visualization tool

BACKGROUND

Network analyses, such as of gene co-expression networks, metabolic networks and ecological networks have become a central approach for the systems-level study of biological data. Several software packages exist for generating and analyzing such networks, either from correlation scores or the absolute value of a transformed score called weighted topological overlap (wTO). However, since gene regulatory processes can up- or down-regulate genes, it is of great interest to explicitly consider both positive and negative correlations when constructing a gene co-expression network.

RESULTS

Here, we present an R package for calculating the weighted topological overlap (wTO), that, in contrast to existing packages, explicitly addresses the sign of the wTO values, and is thus especially valuable for the analysis of gene regulatory networks. The package includes the calculation of p-values (raw and adjusted) for each pairwise gene score. Our package also allows the calculation of networks from time series (without replicates). Since networks from independent datasets (biological repeats or related studies) are not the same due to technical and biological noise in the data, we additionally, incorporated a novel method for calculating a consensus network (CN) from two or more networks into our R package. To graphically inspect the resulting networks, the R package contains a visualization tool, which allows for the direct network manipulation and access of node and link information. When testing the package on a standard laptop computer, we can conduct all calculations for systems of more than 20,000 genes in under two hours. We compare our new wTO package to state of art packages and demonstrate the application of the wTO and CN functions using 3 independently derived datasets from healthy human pre-frontal cortex samples. To showcase an example for the time series application we utilized a metagenomics data set.

CONCLUSION

In this work, we developed a software package that allows the computation of wTO networks, CNs and a visualization tool in the R statistical environment. It is publicly available on CRAN repositories under the GPL -2 Open Source License ( https://cran.r-project.org/web/packages/wTO/ ).

Identification and replication of RNA-Seq gene network modules associated with depression severity

Genomic variation underlying major depressive disorder (MDD) likely involves the interaction and regulation of multiple genes in a network. Data-driven co-expression network module inference has the potential to account for variation within regulatory networks, reduce the dimensionality of RNA-Seq data, and detect significant gene-expression modules associated with depression severity. We performed an RNA-Seq gene co-expression network analysis of mRNA data obtained from the peripheral blood mononuclear cells of unmedicated MDD (n = 78) and healthy control (n = 79) subjects. Across the combined MDD and HC groups, we assigned genes into modules using hierarchical clustering with a dynamic tree cut method and projected the expression data onto a lower-dimensional module space by computing the single-sample gene set enrichment score of each module. We tested the single-sample scores of each module for association with levels of depression severity measured by the Montgomery-Åsberg Depression Scale (MADRS). Independent of MDD status, we identified 23 gene modules from the co-expression network. Two modules were significantly associated with the MADRS score after multiple comparison adjustment (adjusted p = 0.009, 0.028 at 0.05 FDR threshold), and one of these modules replicated in a previous RNA-Seq study of MDD (p = 0.03). The two MADRS-associated modules contain genes previously implicated in mood disorders and show enrichment of apoptosis and B cell receptor signaling. The genes in these modules show a correlation between network centrality and univariate association with depression, suggesting that intramodular hub genes are more likely to be related to MDD compared to other genes in a module.

Cross-species systems analysis identifies gene networks differentially altered by sleep loss and depression

To understand the transcriptomic organization underlying sleep and affective function, we studied a population of (C57BL/6J × 129S1/SvImJ) F2 mice by measuring 283 affective and sleep phenotypes and profiling gene expression across four brain regions. We identified converging molecular bases for sleep and affective phenotypes at both the single-gene and gene-network levels. Using publicly available transcriptomic datasets collected from sleep-deprived mice and patients with major depressive disorder (MDD), we identified three cortical gene networks altered by the sleep/wake state and depression. The network-level actions of sleep loss and depression were opposite to each other, providing a mechanistic basis for the sleep disruptions commonly observed in depression, as well as the reported acute antidepressant effects of sleep deprivation. We highlight one particular network composed of circadian rhythm regulators and neuronal activity-dependent immediate-early genes. The key upstream driver of this network, Arc, may act as a nexus linking sleep and depression. Our data provide mechanistic insights into the role of sleep in affective function and MDD.

Shared molecular neuropathology across major psychiatric disorders parallels polygenic overlap

The predisposition to neuropsychiatric disease involves a complex, polygenic, and pleiotropic genetic architecture. However, little is known about how genetic variants impart brain dysfunction or pathology. We used transcriptomic profiling as a quantitative readout of molecular brain-based phenotypes across five major psychiatric disorders-autism, schizophrenia, bipolar disorder, depression, and alcoholism-compared with matched controls. We identified patterns of shared and distinct gene-expression perturbations across these conditions. The degree of sharing of transcriptional dysregulation is related to polygenic (single-nucleotide polymorphism-based) overlap across disorders, suggesting a substantial causal genetic component. This comprehensive systems-level view of the neurobiological architecture of major neuropsychiatric illness demonstrates pathways of molecular convergence and specificity.

Altered Expression Profile of IgLON Family of Neural Cell Adhesion Molecules in the Dorsolateral Prefrontal Cortex of Schizophrenic Patients

Neural adhesion proteins are crucial in the development and maintenance of functional neural connectivity. Growing evidence suggests that the IgLON family of neural adhesion molecules LSAMP, NTM, NEGR1, and OPCML are important candidates in forming the susceptibility to schizophrenia (SCZ). IgLON proteins have been shown to be involved in neurite outgrowth, synaptic plasticity and neuronal connectivity, all of which have been shown to be altered in the brains of patients with the diagnosis of schizophrenia. Here we optimized custom 5'-isoform-specific TaqMan gene-expression analysis for the transcripts of human IgLON genes to study the expression of IgLONs in the dorsolateral prefrontal cortex (DLPFC) of schizophrenic patients (n = 36) and control subjects (n = 36). Uniform 5'-region and a single promoter was confirmed for the human NEGR1 gene by in silico analysis. IgLON5, a recently described family member, was also included in the study. We detected significantly elevated levels of the NEGR1 transcript (1.33-fold increase) and the NTM 1b isoform transcript (1.47-fold increase) in the DLPFC of schizophrenia patients compared to healthy controls. Consequent protein analysis performed in male subjects confirmed the increase in NEGR1 protein content both in patients with the paranoid subtype and in patients with other subtypes. In-group analysis of patients revealed that lower expression of certain IgLON transcripts, mostly LSAMP 1a and 1b, could be related with concurrent depressive endophenotype in schizophrenic patients. Additionally, our study cohort provides further evidence that cannabis use may be a relevant risk factor associated with suicidal behaviors in psychotic patients. In conclusion, we provide clinical evidence of increased expression levels of particular IgLON family members in the DLPFC of schizophrenic patients. We propose that alterations in the expression profile of IgLON neural adhesion molecules are associated with brain circuit disorganization in neuropsychiatric disorders, such as schizophrenia. In the light of previously published data, we suggest that increased level of NEGR1 in the frontal cortex may serve as molecular marker for a wider spectrum of psychiatric conditions.

Engaging homeostatic plasticity to treat depression

Major depressive disorder (MDD) is a complex and heterogeneous mood disorder, making it difficult to develop a generalized, pharmacological therapy that is effective for all who suffer from MDD. Through the fortuitous discovery of N-methyl-D-aspartate receptor (NMDAR) antagonists as effective antidepressants, we have gained key insights into how antidepressant effects can be produced at the circuit and molecular levels. NMDAR antagonists act as rapid-acting antidepressants such that relief from depressive symptoms occurs within hours of a single injection. The mode of action of NMDAR antagonists seemingly relies on their ability to activate protein-synthesis-dependent homeostatic mechanisms that restore top-down excitatory connections. Recent evidence suggests that NMDAR antagonists relieve depressive symptoms by forming new synapses resulting in increased excitatory drive. This event requires the mammalian target of rapamycin complex 1 (mTORC1), a signaling pathway that regulates synaptic protein synthesis. Herein, we review critical studies that shed light on the action of NMDAR antagonists as rapid-acting antidepressants and how they engage a neuron's or neural network's homeostatic mechanisms to self-correct. Recent studies notably demonstrate that a shift in γ-amino-butyric acid receptor B (GABA_BR) function, from inhibitory to excitatory, is required for mTORC1-dependent translation with NMDAR antagonists. Finally, we discuss how GABA_BR activation of mTORC1 helps resolve key discrepancies between rapid-acting antidepressants and local homeostatic mechanisms.

A novel relationship for schizophrenia, bipolar and major depressive disorder Part 3: Evidence from chromosome 3 high density association screen

Familial clustering of schizophrenia (SCZ), bipolar disorder (BPD), and major depressive disorder (MDD) was systematically reported (Aukes et al, Genet Med 2012, 14, 338-341) and convergent evidence from genetics, symptomatology, and psychopharmacology imply that there are intrinsic connections between these three major psychiatric disorders, for example, any two or even three of these disorders could co-exist in some families. A total of 60, 838 single-nucleotide polymorphisms (SNPs) on chromosome 3 were genotyped by Affymetrix Genome-Wide Human SNP array 6.0 on 119 SCZ, 253 BPD (type-I), 177 MDD patients and 1,000 controls. The population of Shandong province was formed in 14 century and believed that it belongs to homogenous population. Associated SNPs were systematically revealed and outstanding susceptibility genes (CADPS, GRM7,KALRN, LSAMP, NLGN1, PRICKLE2, ROBO2) were identified. Unexpectedly, flanking genes for the associated SNPs distinctive for BPD and/or MDD were replicated in an enlarged cohort of 986 SCZ patients. The evidence from this chromosome 3 analysis supports the notion that both of bipolar and MDD might be subtypes of schizophrenia rather than independent disease entity. Also, a similar finding was detected on chromosome 5, 6, 7, and 8 (Chen et al. Am J Transl Res 2017;9 (5):2473-2491; Curr Mol Med 2016;16(9):840-854; Behav Brain Res 2015;293:241-251; Mol Neurobiol 2016. doi: 10.1007/s12035-016-0102-1). Furthermore, PRICKLE2 play an important role in the pathogenesis of three major psychoses in this population.

Transcriptome Alterations in Prefrontal Pyramidal Cells Distinguish Schizophrenia From Bipolar and Major Depressive Disorders

BACKGROUND

Impairments in certain cognitive processes (e.g., working memory) are typically most pronounced in schizophrenia (SZ), intermediate in bipolar disorder, and least in major depressive disorder. Given that working memory depends, in part, on neural circuitry that includes pyramidal cells in layer 3 (L3) and layer 5 (L5) of the dorsolateral prefrontal cortex (DLPFC), we sought to determine if transcriptome alterations in these neurons were shared or distinctive for each diagnosis.

METHODS

Pools of L3 and L5 pyramidal cells in the DLPFC were individually captured by laser microdissection from 19 matched tetrads of unaffected comparison subjects and subjects with SZ, bipolar disorder, and major depressive disorder, and the messenger RNA was subjected to transcriptome profiling by microarray.

RESULTS

In DLPFC L3 and L5 pyramidal cells, transcriptome alterations were numerous in subjects with SZ, but rare in subjects with bipolar disorder and major depressive disorder. The leading molecular pathways altered in subjects with SZ involved mitochondrial energy production and the regulation of protein translation. In addition, we did not find any significant transcriptome signatures related to psychosis or suicide.

CONCLUSIONS

In concert, these findings suggest that molecular alterations in DLPFC L3 and L5 pyramidal cells might be characteristic of the disease processes operative in individuals diagnosed with SZ and thus might contribute to the circuitry alterations underlying cognitive dysfunction in individuals with SZ.

Potential contribution of the neurodegenerative disorders risk loci to cognitive performance in an elderly male gout population

Cognitive impairment has been described in elderly subjects with high normal concentrations of serum uric acid. However, it remains unclear if gout confers an increased poorer cognition than those in individuals with asymptomatic hyperuricemia. The present study aimed at evaluating cognitive function in patients suffering from gout in an elderly male population, and further investigating the genetic contributions to the risk of cognitive function.This study examined the cognitive function as assessed by Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA) in 205 male gout patients and 204 controls. The genetic basis of these cognitive measures was evaluated by genome-wide association study (GWAS) data in 102 male gout patients. Furthermore, 7 loci associated with cognition in GWAS were studied for correlation with gout in 1179 male gout patients and 1848 healthy male controls.Compared with controls, gout patients had significantly lower MoCA scores [22.78 ± 3.01 vs 23.42 ± 2.95, P = .023, adjusted by age, body mass index (BMI), education, and emotional disorder]. GWAS revealed 7 single-nucleotide polymorphisms (SNPs) associations with MoCA test at a level of conventional genome-wide significance (P < 9.6 × 10). The most significant association was observed between rs12895072 and rs12434554 within the KTN1 gene (Padjusted = 4.2 × 10, Padjusted = 4.7 × 10) at 14q22. The next best signal was in RELN gene (rs155333, Padjusted = 1.3 × 10) at 7q22, while the other variants at rs17458357 (Padjusted = 3.98 × 10), rs2572683 (Padjusted = 8.9 × 10), rs12555895 (Padjusted = 2.6 × 10), and rs3764030 (Padjusted = 9.4 × 10) were also statistically significant. The 7 SNPs were not associated with gout in further analysis (all P > .05).Elderly male subjects with gout exhibit accelerated decline in cognition performance. Several neurodegenerative disorders risk loci were identified for genetic contributors to cognitive performance in our Chinese elderly male gout population. Larger prospective studies of the cognitive performance and genetic analysis in gout subjects are recommended.

A comprehensive regional analysis of genome-wide expression profiles for major depressive disorder

BACKGROUND

Major depressive disorder (MDD) is a global health challenge. In recent years, a large number of genome-wide expression studies (GWES) have been carried out to identify the transcriptomic profiles for MDD. The objective of this work was to carry out a comprehensive meta-analysis of available GWES for MDD.

METHODS

GWES for MDD with available raw data were searched in NCBI GEO, Array Express and Stanley databases. Raw GWES data were preprocessed and normalized and meta-analytical procedures were carried out with the Network Analyst program. 743 samples from 24 primary studies were included in our meta-analyses for blood (Blo), amygdala (Amy), cerebellum (Cer), anterior cingulate cortex (ACC) and prefrontal cortex (PFC) regions. A functional enrichment analysis was carried out.

RESULTS

We identified 35, 793, 231, 668 and 252 differentially expressed (DE) genes for Blo, Amy, Cer, ACC and PFC regions. A region-dependent significant enrichment for several functional categories, such as gene ontologies, signaling pathways and topographic parameters, was identified. There was convergence with other available genome-wide studies, such as GWAS, DNA methylation analyses and miRNA expression studies.

LIMITATIONS

Raw data were not available for several primary studies that have been published previously.

CONCLUSIONS

This is the largest meta-analysis for GWES in MDD. The examination of convergence of genome-wide evidence and of the functional enrichment analysis provides a global overview of potential neural signaling mechanisms dysregulated in MDD. Our comprehensive analysis of several brain regions identified lists of DE genes for MDD that are interesting candidates for further studies.

Mechanisms of Brain Glucocorticoid Resistance in Stress-Induced Psychopathologies

Exposure to stress activates the hypothalamic-pituitary-adrenal axis and leads to increased levels of glucocorticoid (GC) hormones. Prolonged elevation of GC levels causes neuronal dysfunction, decreases the density of synapses, and impairs neuronal plasticity. Decreased sensitivity to glucocorticoids (glucocorticoid resistance) that develops as a result of chronic stress is one of the characteristic features of stress-induced psychopathologies. In this article, we reviewed the published data on proposed molecular mechanisms that contribute to the development of glucocorticoid resistance in brain, including changes in the expression of the glucocorticoid receptor (GR) gene, biosynthesis of GR isoforms, and GR posttranslational modifications. We also present data on alterations in the expression of the FKBP5 gene encoding the main component of cell ultra-short negative feedback loop of GC signaling regulation. Recent discoveries on stress- and GR-induced changes in epigenetic modification patterns as well as normalizing action of antidepressants are discussed. GR and FKBP5 gene polymorphisms associated with stress-induced psychopathologies are described, and their role in glucocorticoid resistance is discussed.

Using the BITOLA system to identify candidate molecules in the interaction between oral lichen planus and depression

Exacerbations of oral lichen planus (OLP) have been linked to the periods of psychological stress, anxiety and depression. The specific mechanism of the interaction is unclear. The aim of this study was to explore the candidate genes or molecules that play important roles in the interaction between OLP and depression. The BITOLA system was used to search all intermediate concepts relevant to the "Gene or Gene Product" for OLP and depression, and the gene expression data and tissue-specific gene data along with manual checking were then employed to filter the intermediate concepts. Finally, two genes (NCAM1, neural cell adhesion molecule 1; CD4, CD4 molecule) passed the follow-up inspection. By using the text mining can formulate a new hypothesis: NCAM1 and CD4 were identified as involved or potentially involved in the interaction between OLP and depression. These results offer a new clue for the experimenters and hold promise for developing innovative therapeutic strategies for these two diseases.

Ketamine and Imipramine Reverse Transcriptional Signatures of Susceptibility and Induce Resilience-Specific Gene Expression Profiles

BACKGROUND

Examining transcriptional regulation by antidepressants in key neural circuits implicated in depression and understanding the relation to transcriptional mechanisms of susceptibility and natural resilience may help in the search for new therapeutic agents. Given the heterogeneity of treatment response in human populations, examining both treatment response and nonresponse is critical.

METHODS

We compared the effects of a conventional monoamine-based tricyclic antidepressant, imipramine, and a rapidly acting, non-monoamine-based antidepressant, ketamine, in mice subjected to chronic social defeat stress, a validated depression model, and used RNA sequencing to analyze transcriptional profiles associated with susceptibility, resilience, and antidepressant response and nonresponse in the prefrontal cortex (PFC), nucleus accumbens, hippocampus, and amygdala.

RESULTS

We identified similar numbers of responders and nonresponders after ketamine or imipramine treatment. Ketamine induced more expression changes in the hippocampus; imipramine induced more expression changes in the nucleus accumbens and amygdala. Transcriptional profiles in treatment responders were most similar in the PFC. Nonresponse reflected both the lack of response-associated gene expression changes and unique gene regulation. In responders, both drugs reversed susceptibility-associated transcriptional changes and induced resilience-associated transcription in the PFC.

CONCLUSIONS

We generated a uniquely large resource of gene expression data in four interconnected limbic brain regions implicated in depression and its treatment with imipramine or ketamine. Our analyses highlight the PFC as a key site of common transcriptional regulation by antidepressant drugs and in both reversing susceptibility- and inducing resilience-associated molecular adaptations. In addition, we found region-specific effects of each drug, suggesting both common and unique effects of imipramine versus ketamine.

Completed suicide, depression, and RELN polymorphisms

OBJECTIVE

Suicidal behavior is a complex phenomenon, an outcome of both environmental and genetic factors. In the present study, we looked for a potential association between suicide and the reelin gene as reelin has been associated previously with several psychiatric disorders, including depression.

MATERIALS AND METHODS

We analyzed three single nucleotide polymorphisms (SNPs) in the reelin gene, rs2965087, rs7341475, and rs362691, in a population of 483 suicide victims and 332 healthy controls, all Caucasians. An analysis was carried out according to sex and the method of suicide. In a group of 77 suicide victims with psychological autopsy data, suicide threats, suicide in the family, and number of depression symptoms were also considered.

RESULTS

Analysis of all three polymorphisms did not confirm an association with suicide in general. However, for subjects included in psychological autopsy study, association with previous announcement of suicide in the group of subjects with TT genotype for polymorphism rs2965087 was determined. Furthermore, the results pointed to an association with reported suicide in the family of suicide victims in case of the TT genotype. In contrast, the number of depressive symptoms, besides suicidal threats, was lower in the group with the TT genotype.

LIMITATIONS

Psychological autopsies can be associated with recall bias and the sample was rather small and therefore underpowered.

CONCLUSION

The present investigation, performed on a study sample from a population with one of the highest suicide rates in the world, indicated an association between rs2965087 in the reelin gene and the expression of suicidal threats a month before suicide in contrast to other symptoms of depression.