Identification of genes and gene pathways associated with major depressive disorder by integrative brain analysis of rat and human prefrontal cortex transcriptomes

Novel Insights into Changes in Gene Expression within the Hypothalamus in Two Asthma Mouse Models: A Transcriptomic Lung-Brain Axis Study

Patients with asthma experience elevated rates of mental illness. However, the molecular links underlying such lung-brain crosstalk remain ambiguous. Hypothalamic dysfunction is observed in many psychiatric disorders, particularly those with an inflammatory component due to many hypothalamic regions being unprotected by the blood-brain barrier. To gain a better insight into such neuropsychiatric sequelae, this study investigated gene expression differences in the hypothalamus following lung inflammation (asthma) induction in mice, using RNA transcriptome profiling. BALB/c mice were challenged with either bacterial lipopolysaccharide (LPS, E. coli) or ovalbumin (OVA) allergens or saline control (n = 7 per group), and lung inflammation was confirmed via histological examination of postmortem lung tissue. The majority of the hypothalamus was micro-dissected, and total RNA was extracted for sequencing. Differential expression analysis identified 31 statistically significant single genes (false discovery rate FDR5%) altered in expression following LPS exposure compared to controls; however, none were significantly changed following OVA treatment, suggesting a milder hypothalamic response. When gene sets were examined, 48 were upregulated and 8 were downregulated in both asthma groups relative to controls. REACTOME enrichment analysis suggests these gene sets are involved in signal transduction metabolism, immune response and neuroplasticity. Interestingly, we identified five altered gene sets directly associated with neurotransmitter signaling. Intriguingly, many of these altered gene sets can influence mental health and or/neuroinflammation in humans. These findings help characterize the links between asthma-induced lung inflammation and the brain and may assist in identifying relevant pathways and therapeutic targets for future intervention.

Neuroimaging Genomics a Predictor of Major Depressive Disorder (MDD)

Depression is a complex psychiatric disorder influenced by various genetic and environmental factors. Strong evidence has established the contribution of genetic factors in depression through twin studies and the heritability rate for depression has been reported to be 37%. Genetic studies have identified genetic variations associated with an increased risk of developing depression. Imaging genetics is an integrated approach where imaging measures are combined with genetic information to explore how specific genetic variants contribute to brain abnormalities. Neuroimaging studies allow us to examine both structural and functional abnormalities in individuals with depression. This review has been designed to study the correlation of the significant genetic variants with different regions of neural activity, connectivity, and structural alteration in the brain as detected by imaging techniques to understand the scope of biomarkers in depression. This might help in developing novel therapeutic interventions targeting specific genetic pathways or brain circuits and the underlying pathophysiology of depression based on this integrated approach can be established at length.

Cellular Organelle-Related Transcriptomic Profile Abnormalities in Neuronopathic Types of Mucopolysaccharidosis: A Comparison with Other Neurodegenerative Diseases

Mucopolysaccharidoses (MPS) are a group of diseases caused by mutations in genes encoding lysosomal enzymes that catalyze reactions of glycosaminoglycan (GAG) degradation. As a result, GAGs accumulate in lysosomes, impairing the proper functioning of entire cells and tissues. There are 14 types/subtypes of MPS, which are differentiated by the kind(s) of accumulated GAG(s) and the type of a non-functional lysosomal enzyme. Some of these types (severe forms of MPS types I and II, MPS III, and MPS VII) are characterized by extensive central nervous system disorders. The aim of this work was to identify, using transcriptomic methods, organelle-related genes whose expression levels are changed in neuronopathic types of MPS compared to healthy cells while remaining unchanged in non-neuronopathic types of MPS. The study was conducted with fibroblast lines derived from patients with neuronopathic and non-neuronopathic types of MPS and control (healthy) fibroblasts. Transcriptomic analysis has identified genes related to cellular organelles whose expression is altered. Then, using fluorescence and electron microscopy, we assessed the morphology of selected structures. Our analyses indicated that the genes whose expression is affected in neuronopathic MPS are often associated with the structures or functions of the cell nucleus, endoplasmic reticulum, or Golgi apparatus. Electron microscopic studies confirmed disruptions in the structures of these organelles. Special attention was paid to up-regulated genes, such as PDIA3 and MFGE8, and down-regulated genes, such as ARL6IP6, ABHD5, PDE4DIP, YIPF5, and CLDN11. Of particular interest is also the GM130 (GOLGA2) gene, which encodes golgin A2, which revealed an increased expression in neuronopathic MPS types. We propose to consider the levels of mRNAs of these genes as candidates for biomarkers of neurodegeneration in MPS. These genes may also become potential targets for therapies under development for neurological disorders associated with MPS and candidates for markers of the effectiveness of these therapies. Although fibroblasts rather than nerve cells were used in this study, it is worth noting that potential genetic markers characteristic solely of neurons would be impractical in testing patients, contrary to somatic cells that can be relatively easily obtained from assessed persons.

Immune transcriptional profiles in mothers with clinically elevated depression and anxiety symptoms several years post-delivery

BACKGROUND

Most research on maternal mental health focuses on the perinatal period and does not extend beyond 12 months postpartum. However, emerging evidence suggests that for some women (30%-50%), psychological symptoms may persist beyond the first year postpartum or even emerge later increasing the risk of chronic mood and anxiety symptoms. Despite the high prevalence rates and devastating maternal-child consequences, studies examining maternal depression, anxiety, and post-traumatic stress disorder (PTSD) beyond the first year postpartum are rare and our understanding of the underlying biological mechanisms is incomplete. Inflammatory processes are thought to be involved in the pathophysiology of depression, anxiety, & PTSD outside of the postpartum period. Therefore, the purpose of the current investigation was to examine the relationship between depression, anxiety, and PTSD two to three years post-delivery, and transcriptional control pathways relevant to inflammatory and antiviral processes.

METHODS

Women over 18 years of age enrolled in ongoing research studies at Cedars Sinai Medical Center who were 2-3 years postpartum were invited to participate in the current study. Women (N = 33) reported on their levels of depression, anxiety, and PTSD and provided a blood sample approximately 2-3 years post-delivery. Bioinformatic analyses of differential gene expression (DGEs) to infer transcription factor activity were used. Gene expression was assayed by RNA sequencing and TELiS bioinformatics analysis of transcription factor-binding motifs in the promoters of differentially expressed genes.

RESULTS

DGE analyses revealed that women with clinically elevated symptoms of depression, anxiety and PTSD (n = 16) showed upregulation of genes activated by transcription control pathways associated with inflammation (NF-_Κ B, p = 0.004; JUN, p = 0.02), including ꞵ-adrenergic responsive CREB (p = 0.01) and reduced activation of genes associated with the antiviral response (IRFs, p = 0.02) and the glucocorticoid signaling pathway (GR, p = 0.02) compared to women without clinical symptoms (n = 17).

CONCLUSIONS

This is one of the first investigations into the immune signaling pathways involved in depression, anxiety, and PTSD two to three years post-delivery. The results of this study suggest that clinically elevated symptoms of depression, anxiety, and PTSD two to three years post-delivery are associated with a gene expression profile characterized by upregulated expression of pro-inflammatory genes and downregulated expression of antiviral genes. The data also point to two potential stress responsive pathways linking symptoms to increased inflammatory signaling in immune cells: sympathetic nervous system mediated ꞵ-adrenergic signaling and reduced hypothalamic pituitary adrenal axis activity. Together, these findings highlight the need for investigations into maternal mental health beyond the first year postpartum. This article is protected by copyright. All rights reserved.

Toll-Like Receptor 4 Gene Polymorphisms and Susceptibility to Schizophrenia: A Case-Control Study

Schizophrenia is a common psychiatric disorder that exhibits a variety of symptoms. The exact etiology and pathogenesis are still doubtful. However, genetic and environmental factors seem to have a role. Years ago, the role of the immune system was focused on auto-antibodies, cytokines, different types of immune cells and immune genes. The Toll-like receptors (TLR) are a cornerstone of the innate immune system, particularly TLR4. TLR4 primarily recognises gram-negative lipopolysaccharides bacteria. This case-control study, for the first time to our knowledge, examined the role of TLR4 gene polymorphisms in 142 Egyptian schizophrenic patients and 175 healthy controls. Using polymerase chain reaction-restriction fragment length polymorphism (PCR-RFLP), four single nucleotide polymorphisms (SNPs) were investigated in the TLR4 gene rs11536889, rs10759931, rs1927911, and rs1927914. The Positive and Negative Syndrome Scale (PANSS) was used in diagnosis and assessment. A statistically significant association was observed between rs11536889, rs1927911 and rs1927914, but no association was found between rs10759931. There was no association between the different SNP genotypes and PANSS, except between rs1927914 and general psychopathologic symptoms. This study shows a strong association between TLR4 rs11356889 and rs1927911 minor alleles and schizophrenia. These findings could be additional evidence for the immune system's role in schizophrenia development. However, more studies with a more significant sample number, TLR4 protein assessment, and a larger number of SNPs are recommended.

A Systematic Review of Circulatory microRNAs in Major Depressive Disorder: Potential Biomarkers for Disease Prognosis

Major depressive disorder (MDD) is a neuropsychiatric disorder, which remains challenging to diagnose and manage due to its complex endophenotype. In this aspect, circulatory microRNAs (cimiRNAs) offer great potential as biomarkers and may provide new insights for MDD diagnosis. Therefore, we systemically reviewed the literature to explore various cimiRNAs contributing to MDD diagnosis and underlying molecular pathways. A comprehensive literature survey was conducted, employing four databases from 2012 to January 2021. Out of 1004 records, 157 reports were accessed for eligibility criteria, and 32 reports meeting our inclusion criteria were considered for in-silico analysis. This study identified 99 dysregulated cimiRNAs in MDD patients, out of which 20 cimiRNAs found in multiple reports were selected for in-silico analysis. KEGG pathway analysis indicated activation of ALS, MAPK, p53, and P13K-Akt signaling pathways, while gene ontology analysis demonstrated that most protein targets were associated with transcription. In addition, chromosomal location analysis showed clustering of dysregulated cimiRNAs at proximity 3p22-p21, 9q22.32, and 17q11.2, proposing their coregulation with specific transcription factors primarily involved in MDD physiology. Further analysis of transcription factor sites revealed the existence of HIF-1, REST, and TAL1 in most cimiRNAs. These transcription factors are proposed to target genes linked with MDD, hypothesizing that first-wave cimiRNA dysregulation may trigger the second wave of transcription-wide changes, altering the protein expressions of MDD-affected cells. Overall, this systematic review presented a list of dysregulated cimiRNAs in MDD, notably miR-24-3p, let 7a-5p, miR-26a-5p, miR135a, miR-425-3p, miR-132, miR-124 and miR-16-5p as the most prominent cimiRNAs. However, various constraints did not permit us to make firm conclusions on the clinical significance of these cimiRNAs, suggesting the need for more research on single blood compartment to identify the biomarker potential of consistently dysregulated cimiRNAs in MDD, as well as the therapeutic implications of these in-silico insights.

The ERK phosphorylation levels in the amygdala predict anxiety symptoms in humans and MEK/ERK inhibition dissociates innate and learned defensive behaviors in rats

We demonstrate that the rate of extracellular signal-related kinase phosphorylation (P-ERK1,2/Total-ERK1,2) in the amygdala is negatively and independently associated with anxiety symptoms in 23 consecutive patients with drug-resistant mesial temporal lobe epilepsy that was surgically treated. In naive Wistar rats, the P-ERK1,2/Total-ERK1,2 ratio in the amygdala correlates negatively with innate anxiety-related behavior on the elevated plus maze (n = 20) but positively with expression of defensive-learned behavior (i.e., freezing) on Pavlovian aversive (fear) conditioning (n = 29). The microinfusion of ERK1/2 inhibitor (FR180204, n = 8-13/group) or MEK inhibitor (U0126, n = 8-9/group) into the basolateral amygdala did not affect anxiety-related behavior but impaired the evocation (anticipation) of conditioned-defensive behavior (n = 9-11/group). In conclusion, the P-ERK1,2/Total-ERK1,2 ratio in the amygdala predicts anxiety in humans and the innate anxiety- and conditioned freezing behaviors in rats. However, the ERK1/2 in the basolateral AMY is only required for the expression of defensive-learned behavior. These results support a dissociate ERK-dependent mechanism in the amygdala between innate anxiety-like responses and the anticipation of learned-defensive behavior. These findings have implications for understanding highly prevalent psychiatric disorders related to the defensive circuit manifested by anxiety and fear. HIGHLIGHTS: The P-ERK1,2/Total-ERK1,2 ratio in the amygdala (AMY) correlates negatively with anxiety symptoms in patients with mesial temporal lobe epilepsy. The P-ERK1,2/Total-ERK1,2 in the amygdala correlates negatively with the anxiety-like behavior and positively with freezing-learned behavior in naive rats. ERK1,2 in the basolateral amygdala is required for learned-defensive but not for the anxiety-like behavior expression in rats.

Behavioral disorders caused by nonylphenol and strategies for protection

Nonylphenol (NP) is widely used in daily production and life due to its good emulsification. In this review, we discuss toxicology studies that examined behavioral disorders caused by NP, the corresponding toxicological mechanisms in the central nervous system (CNS), and strategies for protection. Available in vitro and in vivo evidence suggests that exposure to NP during adulthood or early childhood is associated with cognitive dysfunction, including depression-like behaviors, anxiety-like behaviors, and impaired learning and memory. The main mechanisms underlying NP-related cognitive disorders include inflammation, destruction of synaptic plasticity, and destruction of important signaling pathways that affect the synthesis and secretion of neurotransmitters. The effects and mechanisms of NP exposure on CNS-mediated reproductive function, including interference with the expression of hormones, proteins, and enzymes, are discussed. Other abnormal behaviors such as locomotor activity and swimming behavior are also described. Several measures to prevent NP neurotoxicity are summarized. These measures are based on the toxicological mechanisms underlying NP exposure and include external protection and internal self-regulation of the nervous system. Finally, a new treatment idea is proposed based on the gut-brain axis. Characterizing the behavioral changes and underlying toxicity mechanisms associated with NP exposure and investigating the possible methods of treatment will help to expand the understanding of these mechanisms and could lead to more effective treatments.

Chronic unpredictable stress negatively regulates hippocampal neurogenesis and promote anxious depression-like behavior via upregulating apoptosis and inflammatory signals in adult rats

Psychological and physical stress play a pivotal role in etiology of anxiety and depression. Chronic psychological and physical stress modify various physiological phenomena, as a consequence of which oxidative stress, decreased neurotransmitter level, elevated corticosterone level and altered NSC homeostasis is observed. However, the precise mechanism by which chronic stress induce anxious depression and modify internal milieu is still unknown. Herein, we show that exposure to CUS increase oxidative stress, microgliosis, astrogliosis while it reduces hippocampal NSC proliferation, neuronal differentiation and maturation in adult rats. CUS exposure in rats reduce dopamine and serotonin level in cortex and hippocampus, which result in increased anxiety and depression-like phenotypes. We also found elevated level of NF-κB and TNF-α while decreased anti-inflammatory cytokine IL-10 level, that led to increased expression of Bax and cleaved Caspase-3 whereas down regulation of antiapoptotic protein Bcl2. Additionally, CUS altered adult hippocampal neurogenesis, increased gliosis and neuronal apoptosis in cerebral cortex and hippocampus which might be associated with reduced AKT and increased ERK signaling, as seen in the rat brain tissue. Taken together, these results indicate that CUS induce oxidative stress and neuroinflammation which directly affects NSC dynamics, monoamines levels and behavioral functions in adult rats.

Transcriptomic signaling pathways involved in a naturalistic model of inflammation-related depression and its remission

This study aimed at identifying molecular biomarkers of inflammation-related depression in order to improve diagnosis and treatment. For this, we performed whole-genome expression profiling from peripheral blood in a naturalistic model of inflammation-associated major depressive disorder (MDD) represented by comorbid depression in obese patients. We took advantage of the marked reduction of depressive symptoms and inflammation following bariatric surgery to test the robustness of the identified biomarkers. Depression was assessed during a clinical interview using Mini-International Neuropsychiatric Interview and the 10-item, clinician-administered, Montgomery-Asberg Depression Rating Scale. From a cohort of 100 massively obese patients, we selected 33 of them for transcriptomic analysis. Twenty-four of them were again analyzed 4-12 months after bariatric surgery. We conducted differential gene expression analyses before and after surgery in unmedicated MDD and non-depressed obese subjects. We found that TP53 (Tumor Protein 53), GR (Glucocorticoid Receptor), and NFκB (Nuclear Factor kappa B) pathways were the most discriminating pathways associated with inflammation-related MDD. These signaling pathways were processed in composite z-scores of gene expression that were used as biomarkers in regression analyses. Results showed that these transcriptomic biomarkers highly predicted depressive symptom intensity at baseline and their remission after bariatric surgery. While inflammation was present in all patients, GR signaling over-activation was found only in depressed ones where it may further increase inflammatory and apoptosis pathways. In conclusion, using an original model of inflammation-related depression and its remission without antidepressants, we provide molecular predictors of inflammation-related MDD and new insights in the molecular pathways involved.

Cortical structural differences in major depressive disorder correlate with cell type-specific transcriptional signatures

Major depressive disorder (MDD) has been shown to be associated with structural abnormalities in a variety of spatially diverse brain regions. However, the correlation between brain structural changes in MDD and gene expression is unclear. Here, we examine the link between brain-wide gene expression and morphometric changes in individuals with MDD, using neuroimaging data from two independent cohorts and a publicly available transcriptomic dataset. Morphometric similarity network (MSN) analysis shows replicable cortical structural differences in individuals with MDD compared to control subjects. Using human brain gene expression data, we observe that the expression of MDD-associated genes spatially correlates with MSN differences. Analysis of cell type-specific signature genes suggests that microglia and neuronal specific transcriptional changes account for most of the observed correlation with MDD-specific MSN differences. Collectively, our findings link molecular and structural changes relevant for MDD.

The correlation between brain structural changes in major depressive disorder (MDD) and gene expression is unclear. Here, the authors explore the correlation between cell type-specific gene expression changes and cortical structural difference in individuals with major depressive disorder.

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.

Network-based approach to identify molecular signatures in the brains of depressed suicides

BACKGROUND

Suicide is a serious and global health problem that has a strong association with major depressive disorder (MDD). Weighted gene co-expression network analysis (WGCNA) was performed for the construction of a co-expression network to get important gene modules associated with depressed suicide.

METHODS

Transcriptome sequencing data from dorsolateral prefrontal cortex was used, which included 29 non-psychiatric controls (CON), 21 MDD suicides (MDD-S) and 9 MDD non-suicides (MDD-NS) of medication-free sudden death individuals.

RESULTS

The highest correlation in the module-traits relationship was discovered between the black module and suicide (r = -0.30, p = 0.024) as well as MDD (r = -0.34, p = 0.010).Furthermore, the expression levels of genes decreased progressively across the three groups (CON>MDD-NS>MDD-S). Therefore, the genes in the black module was selected for subsequent analyses. Protein-Protein Interaction Network found that the top 10 hub genes were somehow involved in depressed suicide including JUN, FOS, ATF3, MYC, EGR1, FOSB, DUSP1, NFKBIA, TLR2, NR4A1. Most of the GO terms were enriched in cell death and apoptosis and KEGG was mainly enriched in MAPK pathway. Cell Type-Specific Analysis found these genes were significantly enriched in endothelial and microglia (p<0.000) cell types. In addition, 92 genes in this module had at least one highly significant differentially methylated positions between MDD-S and controls.

CONCLUSION

Cell death and apoptosis may participate in the interplay between depressed suicide and neuro-inflammation system.

Molecular and neuronal mechanisms underlying the effects of adolescent nicotine exposure on anxiety and mood disorders

Tobacco addiction is highly co-morbid with a variety of mental health conditions, including schizophrenia, mood and anxiety disorders. Nicotine, the primary psychoactive compound in tobacco-related products is known to functionally modulate brain circuits that are disturbed in these disorders. Nicotine can potently regulate the transmission of various neurochemicals, including dopamine (DA), γ-amino-butyric acid (GABA) and glutamate, within various mesocorticolimbic structures, such as the ventral tegmental area (VTA), nucleus accumbens (NAc) and prefrontal cortex (PFC), all of which show pathologies in these disorders. Many neuropsychiatric diseases have etiological origins during neurodevelopment, typically occurring during vulnerable periods of adolescent or pre-natal brain development. During these neurodevelopmental periods, exposure to extrinsic drug insults can induce enduring and long-term pathophysiological sequelae that ultimately increase the risk of developing chronic mental health disorders in later life. These vulnerability factors are of growing concern given rising rates of adolescent nicotine exposure via traditional tobacco use and the increasing use of alternative nicotine delivery formats such as vaping and e-cigarettes. A large body of clinical and pre-clinical evidence points to an important role for adolescent exposure to nicotine and increased vulnerability to developing mood and anxiety disorders in later life. This review will examine current clinical and pre-clinical evidence that pinpoints specific mechanisms within the mesocorticolimbic circuitry and molecular biomarkers linked to the association between adolescent nicotine exposure and increased risk of developing mood and anxiety-related disorders. This article is part of the special issue on 'Vulnerabilities to Substance Abuse'.

Altered miRNA landscape of the anterior cingulate cortex is associated with potential loss of key neuronal functions in depressed brain

MicroRNAs (miRNAs), a family of non-coding RNAs, have recently gained a considerable attention in neuropsychiatric disorders. Being a pleiotropic modulator of target gene(s), miRNA has been recognized as central to downstream gene regulatory networks. In the recent past, reports have suggested their role in changing the epigenetic landscape in brain of subjects with major depressive disorder (MDD). Anterior cingulate cortex (ACC) is a brain area implicated in several complex cognitive functions, such as impulse control, emotion, and decision-making and is associated with psychopathology associated with mood regulation. In this study, we examined whether MDD is associated with altered miRNA transcriptome in ACC and whether altered miRNA landscape is associated with modifications in specific gene network(s) at the functional level. Using next generation sequencing (NGS), it was observed that 117 miRNAs (4.61%) were significantly upregulated and 54 (2.13%) were downregulated in MDD subjects (n = 22) compared with non-psychiatric controls (n = 25). Using 24 most significantly upregulated miRNAs in the MDD group, we determined functional enrichment of target genes and found them to be associated with long-term potentiation, neurotrophin signaling, and axon guidance. Intra- and inter-cluster similarities of enriched terms based on overrepresented gene list showed neurobiological functions associated with neuronal growth and survival. Web centric parameters and ontology enrichment functions identified two major domains related to phosphatidyl signaling, GTPase signaling, neuronal migration, and neurotrophin signaling. Our findings of altered miRNA landscape along with a shift in targetome relate to previously reported morphometric changes and neuronal atrophy in ACC of MDD subjects.

Molecular mechanisms of psychiatric diseases

For most psychiatric diseases, pathogenetic concepts as well as paradigms underlying neuropsychopharmacologic approaches currently revolve around neurotransmitters such as dopamine, serotonin, and norepinephrine. However, despite the fact that several generations of neurotransmitter-based psychotropics including atypical antipsychotics, selective serotonin reuptake inhibitors, and serotonin-norepinephrine reuptake inhibitors are available, the effectiveness of these medications is limited, and relapse rates in psychiatric diseases are relatively high, indicating potential involvement of other pathogenetic pathways. Indeed, recent high-throughput studies in genetics and molecular biology have shown that pathogenesis of major psychiatric illnesses involves hundreds of genes and numerous pathways via such fundamental processes as DNA methylation, transcription, and splicing. Current review summarizes these and other molecular mechanisms of such psychiatric illnesses as schizophrenia, major depressive disorder, and alcohol use disorder and suggests a conceptual framework for future studies.

Exploring the neuropsychiatric spectrum using high-content functional analysis of single-cell signaling networks

Neuropsychiatric disorders overlap in symptoms and share genetic risk factors, challenging their current classification into distinct diagnostic categories. Novel cross-disorder approaches are needed to improve our understanding of the heterogeneous nature of neuropsychiatric diseases and overcome existing bottlenecks in their diagnosis and treatment. Here we employ high-content multi-parameter phospho-specific flow cytometry, fluorescent cell barcoding and automated sample preparation to characterize ex vivo signaling network responses (n = 1764) measured at the single-cell level in B and T lymphocytes across patients diagnosed with four major neuropsychiatric disorders: autism spectrum condition (ASC), bipolar disorder (BD), major depressive disorder (MDD), and schizophrenia (SCZ; n = 25 each), alongside matched healthy controls (n = 100). We identified 25 nodes (individual cell subtype-epitope-ligand combinations) significantly altered relative to the control group, with variable overlap between different neuropsychiatric diseases and heterogeneously expressed at the level of each individual patient. Reconstruction of the diagnostic categories from the altered nodes revealed an overlapping neuropsychiatric spectrum extending from MDD on one end, through BD and SCZ, to ASC on the other end. Network analysis showed that although the pathway structure of the epitopes was broadly preserved across the clinical groups, there were multiple discrete alterations in network connectivity, such as disconnections within the antigen/integrin receptor pathway and increased negative regulation within the Akt1 pathway in CD4⁺ T cells from ASC and SCZ patients, in addition to increased correlation of Stat1 (pY701) and Stat5 (pY694) responses in B cells from BD and MDD patients. Our results support the "dimensional" approach to neuropsychiatric disease classification and suggest potential novel drug targets along the neuropsychiatric spectrum.

Proteomics and Metabolomics Approaches towards a Functional Insight onto AUTISM Spectrum Disorders: Phenotype Stratification and Biomarker Discovery

Autism spectrum disorders (ASDs) are neurodevelopmental disorders characterized by behavioral alterations and currently affect about 1% of children. Significant genetic factors and mechanisms underline the causation of ASD. Indeed, many affected individuals are diagnosed with chromosomal abnormalities, submicroscopic deletions or duplications, single-gene disorders or variants. However, a range of metabolic abnormalities has been highlighted in many patients, by identifying biofluid metabolome and proteome profiles potentially usable as ASD biomarkers. Indeed, next-generation sequencing and other omics platforms, including proteomics and metabolomics, have uncovered early age disease biomarkers which may lead to novel diagnostic tools and treatment targets that may vary from patient to patient depending on the specific genomic and other omics findings. The progressive identification of new proteins and metabolites acting as biomarker candidates, combined with patient genetic and clinical data and environmental factors, including microbiota, would bring us towards advanced clinical decision support systems (CDSSs) assisted by machine learning models for advanced ASD-personalized medicine. Herein, we will discuss novel computational solutions to evaluate new proteome and metabolome ASD biomarker candidates, in terms of their recurrence in the reviewed literature and laboratory medicine feasibility. Moreover, the way to exploit CDSS, performed by artificial intelligence, is presented as an effective tool to integrate omics data to electronic health/medical records (EHR/EMR), hopefully acting as added value in the near future for the clinical management of ASD.

Impact of Expression and Genetic Variation of microRNA-34b/c on Cognitive Dysfunction in Patients with Major Depressive Disorder

BACKGROUND

Patients suffering from major depressive disorder (MDD) commonly demonstrate lower performance across multiple cognitive domains. Cognitive impairment is an intrinsic characteristic of MDD status and is often influenced by genetic factors. microRNAs (miRNAs or miRs) have been shown to have important implications in the etiology of MDD. Therefore, we aimed to identify and analyze the impact of expression and genetic variation of miR-34b/c on cognitive dysfunction in MDD.

METHODS

First, we analyzed miR-34c-5p expression in 48 cases of MDD and 54 healthy controls in a Chinese population using qRT-PCR. We assessed the relationship between the level of miR-34c-5p expression and cognitive performance by Repeatable Battery for the Assessment of Neuropsychological Status (RBANS) and the Trail Making Test (TMT). Second, in order to characterize allelic effects of miR-34b/c on cognitive performance in MDD patients, we performed genetic association analysis of single-nucleotide polymorphism (SNP) loci of the MIR34B/C genes with cognitive function in a second group consisting of 531 MDD patients and 267 healthy controls.

RESULTS

We found a significant negative correlation between the level of miR-34c-5p expression and both the language and delayed memory index scores in patients with MDD. We also found a significant positive correlation between the level of miR-34c-5p expression and the time required to complete tests A and B of the TMT. The interaction between the rs2187473 genotype and the disease was significant for both immediate memory and delayed memory. In the patient group, the rs2187473 CC genotype was significantly associated with higher performance on immediate memory (F = 6.683, p < 0.05) and delayed memory tasks (F = 4.221, p < 0.05).

CONCLUSION

Our findings suggest that changes in miR-34c expression level have important impacts on cognitive function in patients with MDD. In particular, the polymorphism rs2187473 is a potential genetic risk factor for cognitive function in MDD, which may be of clinical use.

Stress resilience is promoted by a Zfp189-driven transcriptional network in prefrontal cortex

Understanding the transcriptional changes that are engaged in stress resilience may reveal novel antidepressant targets. Here we use gene co-expression analysis of RNA-sequencing data from brains of resilient mice to identify a gene network that is unique to resilience. Zfp189, which encodes a previously unstudied zinc finger protein, is the highest-ranked key driver gene in the network, and overexpression of Zfp189 in prefrontal cortical neurons preferentially activates this network and promotes behavioral resilience. The transcription factor CREB is a predicted upstream regulator of this network and binds to the Zfp189 promoter. To probe CREB-Zfp189 interactions, we employ CRISPR-mediated locus-specific transcriptional reprogramming to direct CREB or G9a (a repressive histone methyltransferase) to the Zfp189 promoter in prefrontal cortex neurons. Induction of Zfp189 with site-specific CREB is pro-resilient, whereas suppressing Zfp189 expression with G9a increases susceptibility. These findings reveal an essential role for Zfp189 and CREB-Zfp189 interactions in mediating a central transcriptional network of resilience.

Ketamine ameliorates severe traumatic event-induced antidepressant-resistant depression in a rat model through ERK activation

Treatment-resistant depression (TRD) is a major public health issue, as it is common for patients with depression to fail to respond to adequate trials of antidepressants. However, a well-established animal model of TRD is still warranted. The present study focused on selective serotonin reuptake inhibitor (SSRI) resistance, and aimed to investigate whether higher levels of traumatic stress caused by greater numbers of foot-shocks may lead to severe depression and to examine the feasibility of this as an animal model of SSRI-resistant depression. To reveal the correlation between traumatic stress and severe depression, rats received 3, 6 and 10 tone (conditioned stimulus, CS)-shock (unconditioned stimulus, US) pairings to mimic mild, moderate, and severe traumatic events, and subsequent depressive-like behaviors and protein immunocontents were analyzed. The antidepressant efficacy was assessed for ketamine and SSRI (i.e., fluoxetine) treatment. We found that only the severe stress group presented depressive-like behaviors. Phosphorylation of extracellular signal-regulated kinases (ERKs) was decreased in the amygdala and prefrontal cortex (PFC). The immunocontents of GluA1 and PSD 95 were increased in the amygdala and decreased in the PFC. Moreover, the glutamate-related abnormalities in the amygdala and PFC were normalized by single-dose (10 mg/kg, i.p.) ketamine treatment. In contrast, the depressive-like behaviors were not reversed by 28 days of fluoxetine treatment (10 mg/kg, i.p.) in the severe stress group. Our data demonstrated that high levels of traumatic stress could lead to SSRI-resistant depressive symptoms through impacts on the glutamatergic system, and that this rat model has the potential to be a feasible animal model of SSRI-resistant depression.

Transcriptomic predictors of inflammation-induced depressed mood

Inflammation plays a significant role in the pathophysiology of depression. However, not all individuals exposed to inflammatory challenge develop depression, and identifying those at risk is necessary to develop targeted monitoring, prevention, and treatment strategies. Within a randomized double-blind placebo-controlled study (n = 115), we examined whether leukocyte transcriptome profiles predicted inflammation-induced depressed mood in volunteers who received low-dose intravenous endotoxin (n = 58; aged 18-50). At baseline, transcription factor (TF) activities were assessed using genome-wide transcriptional profiling of peripheral blood mononuclear cells and promoter-based bioinformatic analyses. Then, participants were administered endotoxin. Self-reported depressed mood was assessed using the Profile of Mood States. Based on extant studies linking transcriptional profiles to depressive disorder, we examined whether post-endotoxin depressed mood is predicted by baseline activity of TFs related to immune activation, sympathetic activation, and glucocorticoid insensitivity: respectively, nuclear factor kappa B (NF-kB), cAMP response element-binding protein (CREB), and glucocorticoid receptor (GR). Twenty-one participants (36%) experienced an increase in depressed mood from baseline to 2 h post endotoxin, when depressive response peaks. Bioinformatics analyses controlling for age, sex, ethnicity, body mass index, and physical sickness response revealed that post-endotoxin depressed mood was predicted by increased baseline activity of TFs related to inflammation (NF-kB) and beta-adrenergic signaling (CREB) and by decreased activity of GR-related TFs (P's < 0.001). Inflammation-induced depressed mood is predicted by peripheral transcriptome profiles related to immune activation, sympathetic activation, and glucocorticoid insensitivity. With further replication, these stress-related molecular profiles could be used for a novel genomic approach for identifying individuals at high-risk for the inflammatory subtype of depression.

Interactome Studies of Psychiatric Disorders

High comorbidity and complexity have precluded reliable diagnostic assessment and treatment of psychiatric disorders. Impaired molecular interactions may be relevant for underlying mechanisms of psychiatric disorders but by and large remain unknown. With the help of a number of publicly available databases and various technological tools, recent research has filled the paucity of information by generating a novel dataset of psychiatric interactomes. Different technological platforms including yeast two-hybrid screen, co-immunoprecipitation-coupled with mass spectrometry-based proteomics, and transcriptomics have been widely used in combination with cellular and molecular techniques to interrogate the psychiatric interactome. Novel molecular interactions have been identified in association with different psychiatric disorders including autism spectrum disorders, schizophrenia, bipolar disorder, and major depressive disorder. However, more extensive and sophisticated interactome research needs to be conducted to overcome the current limitations such as incomplete interactome databases and a lack of functional information among components. Ultimately, integrated psychiatric interactome databases will contribute to the implementation of biomarkers and therapeutic intervention.

Approaching to the Essence of Major Depressive Disorder

Major Depressive Disorder (MDD) is a serious neuropsychic disease. It destroys person’s family relationship and social connections seriously. Latest WHO investigation disclosed nearly 4.4% of the population worldwide (approximately 322 million people) were being affected by MDD extensively [1]. While in China, Dong M, et al. reported the occurrence rate of suicide attempt during hospitalization and after the onset of MDD were 17.3% (95% CI: 12.4-23.7%) and 42.1% (95% CI: 26.1-60.0%) respectively [2]. Another research made by Grupta S, et al. announced MDD in urban China might be under-diagnosed and untreated [3].

Adolescent Nicotine Exposure Induces Dysregulation of Mesocorticolimbic Activity States and Depressive and Anxiety-like Prefrontal Cortical Molecular Phenotypes Persisting into Adulthood

Considerable evidence demonstrates strong comorbidity between nicotine dependence and mood and anxiety disorders. Nevertheless, the neurobiological mechanisms linking adolescent nicotine exposure to mood and anxiety disorders are not known. Disturbances in the mesocorticolimbic dopamine (DA) system, comprising the prefrontal cortex (PFC), ventral tegmental area (VTA), and nucleus accumbens (NAc), are correlates of mood and anxiety-related symptoms and this circuitry is strongly influenced by acute or chronic nicotine exposure. Using a combination of behavioral pharmacology, in vivo neuronal electrophysiology and molecular analyses, we examined and compared the effects of chronic nicotine exposure in rats during adolescence versus adulthood to characterize the mechanisms by which adolescent nicotine may selectively confer increased risk of developing mood and anxiety-related symptoms in later life. We report that exposure to nicotine, selectively during adolescence, induces profound and long-lasting neuronal, molecular and behavioral disturbances involving PFC DA D1R and downstream extracellular-signal-related kinase 1-2 (ERK 1-2) signaling. Remarkably, adolescent nicotine induced a persistent state of hyperactive DA activity in the ventral tegmental area (VTA) concomitant with hyperactive neuronal activity states in the PFC. Our findings identify several unique neuronal and molecular biomarkers that may serve as functional risk mechanisms for the long-lasting neuropsychiatric effects of adolescent smoking behaviors.

Integration of transcriptomic and cytoarchitectonic data implicates a role for MAOA and TAC1 in the limbic-cortical network

Decoding the chain from genes to cognition requires detailed insights how areas with specific gene activities and microanatomical architectures contribute to brain function and dysfunction. The Allen Human Brain Atlas contains regional gene expression data, while the JuBrain Atlas offers three-dimensional cytoarchitectonic maps reflecting interindividual variability. To date, an integrated framework that combines the analytical benefits of both scientific platforms towards a multi-level brain atlas of adult humans was not available. We have, therefore, developed JuGEx, a new method for integrating tissue transcriptome and cytoarchitectonic segregation. We investigated differential gene expression in two JuBrain areas of the frontal pole that we have structurally and functionally characterized in previous studies. Our results show a significant upregulation of MAOA and TAC1 in the medial area frontopolaris which is a node in the limbic-cortical network and known to be susceptible for gray matter loss and behavioral dysfunction in patients with depression. The MAOA gene encodes an enzyme which is involved in the catabolism of dopamine, norepinephrine, serotonin, and other monoaminergic neurotransmitters. The TAC1 locus generates hormones that play a role in neuron excitations and behavioral responses. Overall, JuGEx provides a new tool for the scientific community that empowers research from basic, cognitive and clinical neuroscience in brain regions and disease models with regard to gene expression.

Translational Identification of Transcriptional Signatures of Major Depression and Antidepressant Response

Major depressive disorder (MDD) is a highly prevalent mental illness whose therapy management remains uncertain, with more than 20% of patients who do not achieve response to antidepressants. Therefore, identification of reliable biomarkers to predict response to treatment will greatly improve MDD patient medical care. Due to the inaccessibility and lack of brain tissues from living MDD patients to study depression, researches using animal models have been useful in improving sensitivity and specificity of identifying biomarkers. In the current study, we used the unpredictable chronic mild stress (UCMS) model and correlated stress-induced depressive-like behavior (n = 8 unstressed vs. 8 stressed mice) as well as the fluoxetine-induced recovery (n = 8 stressed and fluoxetine-treated mice vs. 8 unstressed and fluoxetine-treated mice) with transcriptional signatures obtained by genome-wide microarray profiling from whole blood, dentate gyrus (DG), and the anterior cingulate cortex (ACC). Hierarchical clustering and rank-rank hypergeometric overlap (RRHO) procedures allowed us to identify gene transcripts with variations that correlate with behavioral profiles. As a translational validation, some of those transcripts were assayed by RT-qPCR with blood samples from 10 severe major depressive episode (MDE) patients and 10 healthy controls over the course of 30 weeks and four visits. Repeated-measures ANOVAs revealed candidate trait biomarkers (ARHGEF1, CMAS, IGHMBP2, PABPN1 and TBC1D10C), whereas univariate linear regression analyses uncovered candidates state biomarkers (CENPO, FUS and NUBP1), as well as prediction biomarkers predictive of antidepressant response (CENPO, NUBP1). These data suggest that such a translational approach may offer new leads for clinically valid panels of biomarkers for MDD.

Highly polygenic architecture of antidepressant treatment response: Comparative analysis of SSRI and NRI treatment in an animal model of depression

Response to antidepressant (AD) treatment may be a more polygenic trait than previously hypothesized, with many genetic variants interacting in yet unclear ways. In this study we used methods that can automatically learn to detect patterns of statistical regularity from a sparsely distributed signal across hippocampal transcriptome measurements in a large-scale animal pharmacogenomic study to uncover genomic variations associated with AD. The study used four inbred mouse strains of both sexes, two drug treatments, and a control group (escitalopram, nortriptyline, and saline). Multi-class and binary classification using Machine Learning (ML) and regularization algorithms using iterative and univariate feature selection methods, including InfoGain, mRMR, ANOVA, and Chi Square, were used to uncover genomic markers associated with AD response. Relevant genes were selected based on Jaccard distance and carried forward for gene-network analysis. Linear association methods uncovered only one gene associated with drug treatment response. The implementation of ML algorithms, together with feature reduction methods, revealed a set of 204 genes associated with SSRI and 241 genes associated with NRI response. Although only 10% of genes overlapped across the two drugs, network analysis shows that both drugs modulated the CREB pathway, through different molecular mechanisms. Through careful implementation and optimisations, the algorithms detected a weak signal used to predict whether an animal was treated with nortriptyline (77%) or escitalopram (67%) on an independent testing set. The results from this study indicate that the molecular signature of AD treatment may include a much broader range of genomic markers than previously hypothesized, suggesting that response to medication may be as complex as the pathology. The search for biomarkers of antidepressant treatment response could therefore consider a higher number of genetic markers and their interactions. Through predominately different molecular targets and mechanisms of action, the two drugs modulate the same Creb1 pathway which plays a key role in neurotrophic responses and in inflammatory processes. © 2016 The Authors. American Journal of Medical Genetics Part B: Neuropsychiatric Genetics Published by Wiley Periodicals, Inc.

Identification of MicroRNA-124-3p as a Putative Epigenetic Signature of Major Depressive Disorder

Major depressive disorder (MDD) is predicted to be the second leading cause of global disease burden by 2030. A large number of MDD patients do not respond to the currently available medication because of its poorly understood etiology. Recently, studies of microRNAs (miRNAs), which act as a molecular switch of gene expression, have shown promise in identifying a molecular network that could provide significant clues to various psychiatric illnesses. Using an in vitro system, a rodent depression model, and a human postmortem brain, we investigated the role of a brain-enriched, neuron-specific miRNA, miR-124-3p, whose expression is highly dysregulated in stressed rodents, and identified a set of target genes involved in stress response and neural plasticity. We also found that miR-124-3p is epigenetically regulated and its interaction with the RNA-induced silencing complex (RISC) is compromised in MDD. Using blood serum, we found similar dysregulation of miR-124-3p in antidepressant-free MDD subjects. Altogether, our study demonstrates potential contribution of miR-124-3p in the pathophysiology of MDD and suggests that this miRNA may serve as a novel target for drug development and a biomarker for MDD pathogenesis.

NLRP3 gene knockout blocks NF-κB and MAPK signaling pathway in CUMS-induced depression mouse model

BACKGROUND

Abundant researches indicate that neuroinflammation has important roles in the pathophysiology of depression. Our previous study found that the NLRP3 inflammasome mediated stress-induced depression-like behavior in mice via regulating neuroinflammation. However, it still remains unclear that how the NLRP3 inflammasome influences related inflammatory signaling pathway to contribute to neuroinflammation in depression.

METHODS

We used wild-type mice and NLRP3 gene knockout mice to explore the role of NLRP3 inflammasome and related inflammatory signaling pathways in chronic unpredictable mild stress (CUMS) induced depression mouse model.

RESULTS

Both wild-type and NLRP3 knockout stress group mice gained less weight than control group mice after 4 weeks CUMS exposure. The wild-type mice subjected to 4 weeks CUMS displayed depression-like behaviors, including decreased sucrose preference and increased immobility time in the tail suspension test. The NLRP3 knockout stress group mice didn't demonstrate depression-like behaviors. The levels of interleukin-1β protein in serum and hippocampi of CUMS exposed wild-type mice were significantly higher, while the NLRP3 knockout stress group mice didn't show an elevation of interleukin-1β levels. Similarly to early researches, we found that CUMS led to promoted NLRP3 expression in hippocampi. In addition, the hippocampi in CUMS exposed wild-type mice had higher p-JNK and p-p38 protein expression, which indicated activation of the mitogen-activated protein kinases (MAPK) pathway. The knockout of NLRP3 gene inhibited CUMS-induced activation of the MAPK pathway. The nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) protein complex was activated in the hippocampi of wild-type mice after CUMS exposure, while knockout of NLRP3 gene hindered its activation.

CONCLUSIONS

These data further proved that the NLRP3 inflammasome mediated CUMS-induced depression-like behavior. The NLRP3 inflammasome regulated CUMS-induced MAPK pathway and NF-κB protein complex activation in depression mouse model. Further researches targeting the NLRP3 inflammasome-signaling pathway might be under a promising future in the prevention and treatment of depression.

NPAS3 Regulates Transcription and Expression of VGF: Implications for Neurogenesis and Psychiatric Disorders

Neuronal PAS domain protein 3 (NPAS3) and VGF (VGF Nerve Growth Factor (NGF) Inducible) are important for neurogenesis and psychiatric disorders. Previously, we have demonstrated that NPAS3 regulates VGF at the transcriptional level. In this study, VGF (non-acronymic) was found regulated by NPAS3 in neuronal stem cells. However, the underlying mechanism of this regulation remains unclear. The aim of this study was to explore the correlation of NPAS3 and VGF, and their roles in neural cell proliferation, in the context of psychiatric illnesses. First, we focused on the structure of NPAS3, to identify the functional domain of NPAS3. Truncated NPAS3 lacking transactivation domain was also found to activate VGF, which suggested that not only transactivation domain but other structural motifs were also involved in the regulation. Second, Mutated enhancer box (E-box) of VGF promoter showed a significant response to this basic helix-loop-helix (bHLH) transcription factor, which suggested an indirect regulatory mechanism for controlling VGF expression by NPAS3. κB site within VGF promoter was identified for VGF activation induced by NPAS3, apart from direct binding to E-box. Furthermore, ectopically expressed NPAS3 in PC12 cells produced parallel responses for nuclear factor kappa-light-chain-enhancer of activated B cells [NF-κB (P65)] expression, which specifies that NPAS3 regulates VGF through the NF-κB signaling pathway. Over-expression of NPAS3 also enhances the cell proliferation, which can be blocked by knockdown of VGF. Finally, NPAS3 was found to influence proliferation of neural cells through VGF. Therefore, downstream signaling pathways that are responsible for NPAS3-VGF induced proliferation via glutamate receptors were explored. Combining this work and published literature, a potential network composed by NPAS3, NF-κB, Brain-Derived Neurotrophic Factor (BDNF), NGF and VGF, was proposed. This network collectively detailed how NPAS3 connects with VGF and intersected neural cell proliferation, synaptic activity and psychiatric disorders.

Transcriptome analysis of genes and gene networks involved in aggressive behavior in mouse and zebrafish

Despite moderate heritability estimates, the molecular architecture of aggressive behavior remains poorly characterized. This study compared gene expression profiles from a genetic mouse model of aggression with zebrafish, an animal model traditionally used to study aggression. A meta-analytic, cross-species approach was used to identify genomic variants associated with aggressive behavior. The Rankprod algorithm was used to evaluated mRNA differences from prefrontal cortex tissues of three sets of mouse lines (N = 18) selectively bred for low and high aggressive behavior (SAL/LAL, TA/TNA, and NC900/NC100). The same approach was used to evaluate mRNA differences in zebrafish (N = 12) exposed to aggressive or non-aggressive social encounters. Results were compared to uncover genes consistently implicated in aggression across both studies. Seventy-six genes were differentially expressed (PFP < 0.05) in aggressive compared to non-aggressive mice. Seventy genes were differentially expressed in zebrafish exposed to a fight encounter compared to isolated zebrafish. Seven genes (Fos, Dusp1, Hdac4, Ier2, Bdnf, Btg2, and Nr4a1) were differentially expressed across both species 5 of which belonging to a gene-network centred on the c-Fos gene hub. Network analysis revealed an association with the MAPK signaling cascade. In human studies HDAC4 haploinsufficiency is a key genetic mechanism associated with brachydactyly mental retardation syndrome (BDMR), which is associated with aggressive behaviors. Moreover, the HDAC4 receptor is a drug target for valproic acid, which is being employed as an effective pharmacological treatment for aggressive behavior in geriatric, psychiatric, and brain-injury patients. © 2016 Wiley Periodicals, Inc.

Epigenetic differences in monozygotic twins discordant for major depressive disorder

Although monozygotic (MZ) twins share the majority of their genetic makeup, they can be phenotypically discordant on several traits and diseases. DNA methylation is an epigenetic mechanism that can be influenced by genetic, environmental and stochastic events and may have an important impact on individual variability. In this study we explored epigenetic differences in peripheral blood samples in three MZ twin studies on major depressive disorder (MDD). Epigenetic data for twin pairs were collected as part of a previous study using 8.1-K-CpG microarrays tagging DNA modification in white blood cells from MZ twins discordant for MDD. Data originated from three geographical regions: UK, Australia and the Netherlands. Ninety-seven MZ pairs (194 individuals) discordant for MDD were included. Different methods to address non independently-and-identically distributed (non-i.i.d.) data were evaluated. Machine-learning methods with feature selection centered on support vector machine and random forest were used to build a classifier to predict cases and controls based on epivariations. The most informative variants were mapped to genes and carried forward for network analysis. A mixture approach using principal component analysis (PCA) and Bayes methods allowed to combine the three studies and to leverage the increased predictive power provided by the larger sample. A machine-learning algorithm with feature reduction classified affected from non-affected twins above chance levels in an independent training-testing design. Network analysis revealed gene networks centered on the PPAR-γ (NR1C3) and C-MYC gene hubs interacting through the AP-1 (c-Jun) transcription factor. PPAR-γ (NR1C3) is a drug target for pioglitazone, which has been shown to reduce depression symptoms in patients with MDD. Using a data-driven approach we were able to overcome challenges of non-i.i.d. data when combining epigenetic studies from MZ twins discordant for MDD. Individually, the studies yielded negative results but when combined classification of the disease state from blood epigenome alone was possible. Network analysis revealed genes and gene networks that support the inflammation hypothesis of MDD.

Evidence of activation of the Toll-like receptor-4 proinflammatory pathway in patients with schizophrenia

BACKGROUND

Alterations in the innate immune/inflammatory system may underlie the pathophysiology of schizophrenia, but we do not understand the mechanisms involved. The main agents of innate immunity are the Toll-like receptors (TLRs), which detect molecular patterns associated with damage and pathogens. The TLR first reported was TLR4, and it is still the most studied one.

METHODS

We aimed to describe putative modifications to the TLR4 proinflammatory pathway using 2 different strategies in 2 cohorts of patients with schizophrenia and matched controls: 1) quantification of protein and mRNA expression in postmortem prefrontal cortex samples from 30 patients with schizophrenia and 30 controls, and 2) identification of single nucleotide polymorphisms associated with the risk of schizophrenia using whole blood samples from 214 patients with schizophrenia and 216 controls.

RESULTS

We found evidence of alterations in the expression of the initial elements of the TLR4 signalling pathway (TLR4, Myeloid differentiation primary response gene 88 [MyD88] and nuclear factor-κ B [NF-κB]) in the PFC of patients with schizophrenia. These alterations seem to depend on the presence/absence of antipsychotic treatment at death. Moreover, a polymorphism within the MyD88 gene was significantly associated with schizophrenia risk.

LIMITATIONS

The use of 2 different approaches in 2 different cohorts, the lack of a complementary neuropsychiatric group, the possible confounding effects of antipsychotic treatment and suicide are the main limitations of our study.

CONCLUSION

The evidence from this dual approach suggests there is an altered innate immune response in patients with chronic schizophrenia in which the TLR4 proinflammatory pathway could be affected. Improved understanding of the stimuli and mechanisms responsible for this response could lead to improved schizophrenia treatment and better control of the side effects of current antipsychotics.

Altered ERK1/2 Signaling in the Brain of Learned Helpless Rats: Relevance in Vulnerability to Developing Stress-Induced Depression

Extracellular signal-regulated kinase 1/2- (ERK1/2-) mediated cellular signaling plays a major role in synaptic and structural plasticity. Although ERK1/2 signaling has been shown to be involved in stress and depression, whether vulnerability to develop depression is associated with abnormalities in ERK1/2 signaling is not clearly known. The present study examined ERK1/2 signaling in frontal cortex and hippocampus of rats that showed vulnerability (learned helplessness, (LH)) or resiliency (non-learned helplessness, (non-LH)) to developing stress-induced depression. In frontal cortex and hippocampus of LH rats, we found that mRNA and protein expressions of ERK1 and ERK2 were significantly reduced, which was associated with their reduced activation and phosphorylation in cytosolic and nuclear fractions, where ERK1 and ERK2 target their substrates. In addition, ERK1/2-mediated catalytic activities and phosphorylation of downstream substrates RSK1 (cytosolic and nuclear) and MSK1 (nuclear) were also lower in the frontal cortex and hippocampus of LH rats without any change in their mRNA or protein expression. None of these changes were evident in non-LH rats. Our study indicates that ERK1/2 signaling is differentially regulated in LH and non-LH rats and suggests that abnormalities in ERK1/2 signaling may be crucial in the vulnerability to developing depression.

Pervasive and opposing effects of Unpredictable Chronic Mild Stress (UCMS) on hippocampal gene expression in BALB/cJ and C57BL/6J mouse strains

Background

BALB/cJ is a strain susceptible to stress and extremely susceptible to a defective hedonic impact in response to chronic stressors. The strain offers much promise as an animal model for the study of stress related disorders. We present a comparative hippocampal gene expression study on the effects of unpredictable chronic mild stress on BALB/cJ and C57BL/6J mice. Affymetrix MOE 430 was used to measure hippocampal gene expression from 16 animals of two different strains (BALB/cJ and C57BL/6J) of both sexes and subjected to either unpredictable chronic mild stress (UCMS) or no stress. Differences were statistically evaluated through supervised and unsupervised linear modelling and using Weighted Gene Coexpression Network Analysis (WGCNA). In order to gain further understanding into mechanisms related to stress response, we cross-validated our results with a parallel study from the GENDEP project using WGCNA in a meta-analysis design.

Results

The effects of UCMS are visible through Principal Component Analysis which highlights the stress sensitivity of the BALB/cJ strain. A number of genes and gene networks related to stress response were uncovered including the Creb1 gene. WGCNA and pathway analysis revealed a gene network centered on Nfkb1. Results from the meta-analysis revealed a highly significant gene pathway centred on the Ubiquitin C (Ubc) gene. All pathways uncovered are associated with inflammation and immune response.

Conclusions

The study investigated the molecular mechanisms underlying the response to adverse environment in an animal model using a GxE design. Stress-related differences were visible at the genomic level through PCA analysis highlighting the high sensitivity of BALB/cJ animals to environmental stressors. Several candidate genes and gene networks reported are associated with inflammation and neurogenesis and could serve to inform candidate gene selection in human studies and provide additional insight into the pathology of Major Depressive Disorder.

Electronic supplementary material

The online version of this article (doi:10.1186/s12864-015-1431-6) contains supplementary material, which is available to authorized users.