Enriched pathways for major depressive disorder identified from a genome-wide association study

Bacillus coagulans and Clostridium butyricum synergistically alleviate depression in a chronic unpredictable mild stress mouse model through altering gut microbiota and prefrontal cortex gene expression

Introduction: The prevalence of major depressive disorder (MDD) has gradually increased and has attracted widespread attention. The aim of this study was to investigate the effect of a probiotic compound consisting of Bacillus coagulans and Clostridium butyricum, on a mouse depression model. Methods: Mice were subjected to chronic unpredictable mild stress (CUMS) and then treated with the probiotics at different concentrations. And mice received behavior test such as forced swimming test and tail suspension test. After that, all mice were sacrificed and the samples were collected for analysis. Moreover, prefrontal cortex (PFC) gene expression and the gut microbiota among different groups were also analyzed. Results: Probiotics improved depressive-like behavior in CUMS mice, as indicated by decreased immobility time (p < 0.05) in the forced swimming test and tail suspension test. probiotics intervention also increased the level of 5-hydroxytryptamine (5-HT) in the prefrontal cortex and decreased the adrenocorticotropic hormone (ACTH) level in serum. In addition, by comparing the PFC gene expression among different groups, we found that the genes upregulated by probiotics were enriched in the PI3K-Akt signaling pathway in the prefrontal cortex. Moreover, we found that downregulated genes in prefrontal cortex of CUMS group such as Sfrp5 and Angpt2, which were correlated with depression, were reversed by the probiotics. Furthermore, the probiotics altered the structure of the gut microbiota, and reversed the reduction of cob(II)yrinate a,c-diamide biosynthesis I pathway in CUMS group. Several species like Bacteroides caecimuris and Parabacteroides distasoni, whose abundance was significantly decreased in the CUMS group but reversed after the probiotics intervention, showed significantly positive correlation with depression associated genes such as Tbxas1 and Cldn2. Discussion: These findings suggested that CUMS-induced depression-like behavior can be alleviated by the probiotics, possibly through alterations in the PFC gene expression and gut microbiota.

TBX21, the Master regulator of the type 1 immune response, overexpresses in the leukocytes of peripheral blood in patients with late-onset Alzheimer's disease

BACKGROUND

The involvement of the peripheral immune system in the etiology of neurodegenerative diseases has recently been emphasized. Genome-wide association studies (GWAS) have recently identified several candidate immune genes linked to development of both Alzheimer's disease (AD) and depression. TBX21 (T-bet) which drives the Th1 immune response, is linked to the major depressive disorder (MDD) phenotype. This study investigated the association between the TBX21 immune gene and the possibility of late-onset Alzheimer's disease (LOAD) incidence in 194 LOAD and 200 control subjects using the real-time qPCR and the Tetra-ARMS-PCR methods. We also used an in silico approach to analyze the potential effects imparted by TBX21 rs17244587 and rs41515744 polymorphisms in LOAD pathogenesis.

RESULTS

We found that the TBX21 "immune gene" had significantly elevated mRNA expression levels in the leukocytes of peripheral blood in patients with LOAD (P < 0.0001). We also found an upward trend in TBX21 expression with increasing age in LOAD patients compared to the control group (P < 0.05; CI = 95%). We noticed that the TT genotype of rs41515744 plays a protective role in LOAD incidence, as it attenuates the expression of TBX21 in the control group. We observed that the dominant model of rs41515744 represented a substantial association with LOAD (P = 0.019).

CONCLUSIONS

Our results show for the first time the likely impact of the TBX21 (T-bet) immune gene in LOAD development and that the elevated TBX21 mRNAs in the WBCs of LOAD patients may represent a new easy diagnostic test for Alzheimer's disease.

Validating methods for testing natural molecules on molecular pathways of interest in silico and in vitro

Differentially expressed genes can serve as drug targets and are used to predict drug response and disease progression. In silico drug analysis based on the expression of these genetic biomarkers allows the detection of putative therapeutic agents, which could be used to reverse a pathological gene expression signature. Indeed, a set of bioinformatics tools can increase the accuracy of drug discovery, helping in biomarker identification. Once a drug target is identified, in vitro cell line models of disease are used to evaluate and validate the therapeutic potential of putative drugs and novel natural molecules. This study describes the development of efficacious PCR primers that can be used to identify gene expression of specific genetic pathways, which can lead to the identification of natural molecules as therapeutic agents in specific molecular pathways. For this study, genes involved in health conditions and processes were considered. In particular, the expression of genes involved in obesity, xenobiotics metabolism, endocannabinoid pathway, leukotriene B4 metabolism and signaling, inflammation, endocytosis, hypoxia, lifespan, and neurotrophins were evaluated. Exploiting the expression of specific genes in different cell lines can be useful in in vitro to evaluate the therapeutic effects of small natural molecules.

Gene Expression Profile Associated with Asmt Knockout-Induced Depression-Like Behaviors and Exercise Effects in Mouse Hypothalamus

Sleep disorder caused by abnormal circadian rhythm is one of the main symptoms and risk factors of depression. As a known hormone regulating circadian rhythms, melatonin (MT) is also namely N-acetyl-5-methoxytryptamine. N-acetylserotonin methyltransferase (Asmt) is the key rate-limiting enzyme of MT synthesis and has been reportedly associated with depression. Although 50–90% of patients with depression have sleep disorders, there are no effective treatment ways in the clinic. Exercise can regulate circadian rhythm and play an important role in depression treatment. In the present study, we showed that Asmt knockout induced depression-like behaviors, which were ameliorated by swimming exercise. Moreover, swimming exercise increased serum levels of MT and 5-hydroxytryptamine (5-HT) in Asmt knockout mice. In addition, the microarray data identified 10 differentially expressed genes (DEGs) in KO mice compared with WT mice and 29 DEGs in KO mice after swimming exercise. Among the DEGs, the direction and magnitude of change in epidermal growth factor receptor pathway substrate 8-like 1 (Eps8l1) and phospholipase C-β 2 (Plcb2) were confirmed by qRT-PCR partly. Subsequent bioinformatic analysis showed that these DEGs were enriched significantly in the p53 signaling pathway, long-term depression and estrogen signaling pathway. In the protein–protein interaction (PPI) networks, membrane palmitoylated protein 1 (Mpp1) and p53-induced death domain protein 1 (Pidd1) were hub genes to participate in the pathological mechanisms of depression and exercise intervention. These findings may provide new targets for the treatment of depression.

Orexin 1 Receptor Antagonism in the Basolateral Amygdala Shifts the Balance From Pro- to Antistress Signaling and Behavior

BACKGROUND

Stress produces differential behavioral responses through select molecular modifications to specific neurocircuitry elements. The orexin (Orx) system targets key components of this neurocircuitry in the basolateral amygdala (BLA).

METHODS

We assessed the contribution of intra-BLA Orx1 receptors (Orx1Rs) in the expression of stress-induced phenotypes of mice. Using the Stress Alternatives Model, a social stress paradigm that produces two behavioral phenotypes, we characterized the role of intra-BLA Orx1R using acute pharmacological inhibition (SB-674042) and genetic knockdown (AAV-U6-Orx1R-shRNA) strategies.

RESULTS

In the BLA, we observed that Orx1R (Hcrtr1) messenger RNA is predominantly expressed in CamKIIα+ glutamatergic neurons and rarely in GABAergic (gamma-aminobutyric acidergic) cells. While there is a slight overlap in Hcrtr1 and Orx2 receptor (Hcrtr2) messenger RNA expression in the BLA, we find that these receptors are most often expressed in separate cells. Antagonism of intra-BLA Orx1R after phenotype formation shifted behavioral expression from stress-sensitive (Stay) to stress-resilient (Escape) responses, an effect that was mimicked by genetic knockdown. Acute inhibition of Orx1R in the BLA also reduced contextual and cued fear freezing responses in Stay animals. This phenotype-specific behavioral change was accompanied by biased molecular transcription favoring Hcrtr2 over Hcrtr1 and Mapk3 over Plcb1 cell signaling cascades and enhanced Bdnf messenger RNA.

CONCLUSIONS

Functional reorganization of intra-BLA gene expression is produced by antagonism of Orx1R, which promotes elevated Hcrtr2, greater Mapk3, and increased Bdnf expression. Together, these results provide evidence for a receptor-driven mechanism that balances pro- and antistress responses within the BLA.

Impact of phospholipase C β1 in glioblastoma: a study on the main mechanisms of tumor aggressiveness

Glioblastoma represents the most lethal brain tumor in adults. Several studies have shown the key role of phospholipase C β1 (PLCβ1) in the regulation of many mechanisms within the central nervous system suggesting PLCβ1 as a novel signature gene in the molecular classification of high-grade gliomas. This study aims to determine the pathological impact of PLCβ1 in glioblastoma, confirming that PLCβ1 gene expression correlates with glioma's grade, and it is lower in 50 glioblastoma samples compared to 20 healthy individuals. PLCβ1 silencing in cell lines and primary astrocytes, leads to increased cell migration and invasion, with the increment of mesenchymal transcription factors and markers, as Slug and N-Cadherin and metalloproteinases. Cell proliferation, through increased Ki-67 expression, and the main survival pathways, as β-catenin, ERK1/2 and Stat3 pathways, are also affected by PLCβ1 silencing. These data suggest a potential role of PLCβ1 in maintaining a normal or less aggressive glioma phenotype.

Genetic Pathways and Functional Subnetworks for the Complex Nature of Bipolar Disorder in Genome-Wide Association Study

Bipolar disorder is a complex psychiatric trait that is also recognized as a high substantial heritability from a worldwide distribution. The success in identifying susceptibility loci for bipolar disorder (BPD) has been limited due to its complex genetic architecture. Growing evidence from association studies including genome-wide association (GWA) studies points to the need of improved analytic strategies to pinpoint the missing heritability for BPD. More importantly, many studies indicate that BPD has a strong association with dementia. We conducted advanced pathway analytics strategies to investigate synergistic effects of multilocus within biologically functional pathways, and further demonstrated functional effects among proteins in subnetworks to examine mechanisms underlying the complex nature of bipolarity using a GWA dataset for BPD. We allowed bipolar susceptible loci to play a role that takes larger weights in pathway-based analytic approaches. Having significantly informative genes identified from enriched pathways, we further built function-specific subnetworks of protein interactions using MetaCore. The gene-wise scores (i.e., minimum p-value) were corrected for the gene-length, and the results were corrected for multiple tests using Benjamini and Hochberg’s method. We found 87 enriched pathways that are significant for BPD; of which 36 pathways were reported. Most of them are involved with several metabolic processes, neural systems, immune system, molecular transport, cellular communication, and signal transduction. Three significant and function-related subnetworks with multiple hotspots were reported to link with several Gene Ontology processes for BPD. Our comprehensive pathway-network frameworks demonstrated that the use of prior knowledge is promising to facilitate our understanding between complex psychiatric disorders (e.g., BPD) and dementia for the access to the connection and clinical implications, along with the development and progression of dementia.

Genetic Variations and Health-Related Quality of Life (HRQOL): A Genome-Wide Study Approach

Simple Summary

Health-related quality of life (HRQOL) is associated with cancer prognosis as well as with age, sex, race, and lifestyle factors, including diet and physical activity. To investigate the hypothesis that HRQOL has genetic underpinnings in patients with cancer, we performed a genome-wide association study to evaluate genetic variants (single nucleotide polymorphisms, SNPs) associated with mental and physical QOL as measured by the PROMIS assessment tool in breast cancer survivors participating in a longitudinal cohort study, the Mayo Clinic Breast Disease Registry (MCBDR). Age and financial concerns were associated with worse physical and mental health, and previous receipt of chemotherapy was associated with worse mental health. SNPs in SCN10A, LMX1B, SGCD, PARP12, and SEMA5A were associated with physical and mental QOL, but none at the genome-wide significance thresholds of p < 5 × 10⁻⁸.

Abstract

Health-related quality of life (HRQOL) is an important prognostic patient-reported outcome in oncology. Because prior studies suggest that HRQOL is, in part, heritable, we performed a GWAS to elucidate genetic factors associated with HRQOL in breast cancer survivors. Physical and mental HRQOL were measured via paper surveys that included the PROMIS-10 physical and mental health domain scales in 1442 breast cancer survivors participating in the Mayo Clinic Breast Disease Registry (MCBDR). In multivariable regression analyses, age and financial concerns were significantly associated with global physical health (age: p = 1.6 × 10⁻²³; financial concerns: p = 4.8 × 10⁻⁴⁰) and mental health (age: p = 3.5 × 10⁻⁷; financial concerns: p = 2.0 × 10⁻⁶⁹⁾. Chemotherapy was associated with worse global mental health (p = 0.01). In the GWAS, none of the SNPs reached the genome-wide association significance threshold of 5 × 10⁻⁸ for associations with either global physical or global mental health, however, a cluster of SNPs in SCN10A, particularly rs112718371, appeared to be linked to worse global physical health (p = 5.21 × 10⁻⁸). Additionally, SNPs in LMX1B, SGCD, PARP12 and SEMA5A were also moderately associated with worse physical and mental health (p < 10⁻⁶). These biologically plausible candidate SNPs warrant further study as possible predictors of HRQOL.

Location-dependent role of phospholipase C signaling in the brain: Physiology and pathology

Phosphoinositide-specific phospholipases C (PI-PLCs) are a class of enzymes involved in the phosphatidylinositol metabolism, which is implicated in the activation of several signaling pathways and which controls several cellular processes. The scientific community has long accepted the existence of a nuclear phosphoinositide (PI) metabolism, independent from the cytoplasmic one, critical in nuclear function control. Indeed, nuclear PIs are involved in many activities, such as cell cycle regulation, cell proliferation, cell differentiation, membrane transport, gene expression and cytoskeletal dynamics. There are several types of PIs and enzymes implicated in brain activities and among these enzymes, PI-PLCs contribute to a specific and complex network in the developing nervous system. Moreover, considering the abundant presence of PI-PLCβ1, PI-PLCγ1 and PI-PLCβ4 in the brain, a specific role for each PLC subtype has been suggested in the control of neuronal activity, which is important for synapse function, development and other mechanisms. The focus of this review is to describe the latest research about the involvement of PI-PLC signaling in the nervous system, both physiologically and in pathological conditions. Indeed, PI-PLC signaling imbalance seems to be also linked to several brain disorders including epilepsy, movement and behavior disorders, neurodegenerative diseases and, in addition, some PI-PLC subtypes could become potential novel signature genes for high-grade gliomas.

Cross-sectional metabolic profiles of mental health in population-based cohorts of 11- to 12-year-olds and mid-life adults: The Longitudinal Study of Australian Children

OBJECTIVE

Poorer mental health in adulthood is associated with increased risk of cardiovascular disease and reduced life expectancy. However, little is known of the molecular pathways underpinning this relationship and how early in life adverse metabolite profiles relate to self-reported variation in mental health. We examined cross-sectional associations between mental health and serum metabolites indicative of cardiovascular health, in large Australian population-based cohorts at two stages of the life-course.

METHODS

We characterised cross-sectional serum nuclear magnetic resonance metabolite profiles of positively and negatively framed mental health in a large population-based sample of Australian 11- to 12-year-olds (n = 1172; 51% girls) and mid-life adults (n = 1322; mean age 45 years; 87% women). We examined multiple standard self-report mental health scales, spanning psychosocial health, general well-being, life satisfaction, and health-related quality of life. Linear regression was used to investigate the cross-sectional association between mental health and each metabolite (n = 73) in children and adults separately, unadjusted and adjusted for age, sex, socioeconomic position and body mass index.

RESULTS

Better child and adult mental health were associated with lower levels of the inflammatory marker glycoprotein acetyls, and a favourable, less atherogenic lipid/lipoprotein profile. Patterns of association in children were generally weaker than in adults. Associations were generally modest and partially attenuated when adjusted for body mass index.

CONCLUSIONS

In general, metabolite profiles associated with better child and adult mental health closely aligned with those predictive of better cardiovascular health in adults. Our findings support previous evidence for the likely bidirectional relationship between mental health and cardiovascular disease risk, by extending this evidence base to the molecular level and in children.

Citalopram-induced pathways regulation and tentative treatment-outcome-predicting biomarkers in lymphoblastoid cell lines from depression patients

Antidepressant therapy is still associated with delays in symptomatic improvement and low response rates. Incomplete understanding of molecular mechanisms underlying antidepressant effects hampered the identification of objective biomarkers for antidepressant response. In this work, we studied transcriptome-wide expression followed by pathway analysis in lymphoblastoid cell lines (LCLs) derived from 17 patients documented for response to SSRI antidepressants from the Munich Antidepressant Response Signatures (MARS) study upon short-term incubation (24 and 48 h) with citalopram. Candidate transcripts were further validated with qPCR in MARS LCLs from responders (n = 33) vs. non-responders (n = 36) and afterward in an independent cohort of treatment-resistant patients (n = 20) vs. first-line responders (n = 24) from the STAR*D study. In MARS cohort we observed significant associations of GAD1 (glutamate decarboxylase 1; p = 0.045), TBC1D9 (TBC1 Domain Family Member 9; p = 0.014-0.021) and NFIB (nuclear factor I B; p = 0.015-0.025) expression with response status, remission status and improvement in depression scale, respectively. Pathway analysis of citalopram-altered gene expression indicated response-status-dependent transcriptional reactions. Whereas in clinical responders neural function pathways were primarily up- or downregulated after incubation with citalopram, deregulated pathways in non-responders LCLs mainly involved cell adhesion and immune response. Results from the STAR*D study showed a marginal association of treatment-resistant depression with NFIB (p = 0.068) but not with GAD1 (p = 0.23) and TBC1D9 (p = 0.27). Our results propose the existence of distinct pathway regulation mechanisms in responders vs. non-responders and suggest GAD1, TBC1D9, and NFIB as tentative predictors for clinical response, full remission, and improvement in depression scale, respectively, with only a weak overlap in predictors of different therapy outcome phenotypes.

Targeted exome sequencing identifies five novel loci at genome-wide significance for modulating antidepressant response in patients with major depressive disorder

In order to determine the role of single nucleotide variants (SNVs) in modulating antidepressant response, we conducted a study, consisting of 929 major depressive disorder (MDD) patients, who were treated with antidepressant drugs (drug-only) or in combination with a repetitive transcranial magnetic stimulation (plus-rTMS), followed by targeted exome sequencing analysis. We found that the "plus-rTMS" patients presented a more effective response to the treatment when compared to the 'drug-only' group. Our data firstly demonstrated that the SNV burden had a significant impact on the antidepressant response presented in the "drug-only" group, but was limited in the "plus-rTMS" group. Further, after controlling for overall SNV burden, seven single nucleotide polymorphisms (SNPs) at five loci, IL1A, GNA15, PPP2CB, PLA2G4C, and GBA, were identified as affecting the antidepressant response at genome-wide significance (P < 5 × 10^-08). Additional multiple variants achieved a level of correction for multiple testing, including GNA11, also shown as a strong signal for MDD risk. Our study showed some promising evidence on genetic variants that could be used as individualized therapeutic guides for MDD patients.

Investigation of multi-trait associations using pathway-based analysis of GWAS summary statistics

Background

Genome-wide association studies (GWAS) have been successful in identifying disease-associated genetic variants. Recently, an increasing number of GWAS summary statistics have been made available to the research community, providing extensive repositories for studies of human complex diseases. In particular, cross-trait associations at the genetic level can be beneficial from large-scale GWAS summary statistics by using genetic variants that are associated with multiple traits. However, direct assessment of cross-trait associations using susceptibility loci has been challenging due to the complex genetic architectures in most diseases, calling for advantageous methods that could integrate functional interpretation and imply biological mechanisms.

Results

We developed an analytical framework for systematic integration of cross-trait associations. It incorporates two different approaches to detect enriched pathways and requires only summary statistics. We demonstrated the framework using 25 traits belonging to four phenotype groups. Our results revealed an average of 54 significantly associated pathways (ranged between 18 and 175) per trait. We further proved that pathway-based analysis provided increased power to estimate cross-trait associations compared to gene-level analysis. Based on Fisher’s Exact Test (FET), we identified a total of 24 (53) pairs of trait-trait association at adjusted p_FET < 1 × 10^− 3 (p_FET < 0.01) among the 25 traits. Our trait-trait association network revealed not only many relationships among the traits within the same group but also novel relationships among traits from different groups, which warrants further investigation in future.

Conclusions

Our study revealed that risk variants for 25 different traits aggregated in particular biological pathways and that these pathways were frequently shared among traits. Our results confirmed known mechanisms and also suggested several novel insights into the etiology of multi-traits.

Electronic supplementary material

The online version of this article (10.1186/s12864-018-5373-7) contains supplementary material, which is available to authorized users.

Integrative Analyses of Genes Associated with Subcutaneous Insulin Resistance

Insulin resistance is present in the majority of patients with non-insulin-dependent diabetes mellitus (NIDDM) and obesity. In this study, we aimed to investigate the key genes and potential molecular mechanism in insulin resistance. Expression profiles of the genes were extracted from the Gene Expression Omnibus (GEO) database. Pathway and Gene Ontology (GO) enrichment analyses were conducted at Enrichr. The protein–protein interaction (PPI) network was settled and analyzed using the Search Tool for the Retrieval of Interacting Genes (STRING) database constructed by Cytoscape software. Modules were extracted and identified by the PEWCC1 plugin. The microRNAs (miRNAs) and transcription factors (TFs) which control the expression of differentially expressed genes (DEGs) were analyzed using the NetworkAnalyst algorithm. A database (GSE73108) was downloaded from the GEO databases. Our results identified 873 DEGs (435 up-regulated and 438 down-regulated) genetically associated with insulin resistance. The pathways which were enriched were pathways in complement and coagulation cascades and complement activation for up-regulated DEGs, while biosynthesis of amino acids and the Notch signaling pathway were among the down-regulated DEGs. Showing GO enrichment were cardiac muscle cell–cardiac muscle cell adhesion and microvillus membrane for up-regulated DEGs and negative regulation of osteoblast differentiation and dendrites for down-regulated DEGs. Subsequently, myosin VB (MYO5B), discs, large homolog 2(DLG2), axin 2 (AXIN2), protein tyrosine kinase 7 (PTK7), Notch homolog 1 (NOTCH1), androgen receptor (AR), cyclin D1 (CCND1) and Rho family GTPase 3 (RND3) were diagnosed as the top hub genes in the up- and down-regulated PPI network and modules. In addition, GATA binding protein 6 (GATA6), ectonucleotide pyrophosphatase/phosphodiesterase 5 (ENPP5), cyclin D1 (CCND1) and tubulin, beta 2A (TUBB2A) were diagnosed as the top hub genes in the up- and down-regulated target gene–miRNA network, while tubulin, beta 2A (TUBB2A), olfactomedin-like 1 (OLFML1), prostate adrogen-regulated mucin-like protein 1 (PARM1) and aldehyde dehydrogenase 4 family, member A1 (ALDH4A1)were diagnosed as the top hub genes in the up- and down-regulated target gene–TF network. The current study based on the GEO database provides a novel understanding regarding the mechanism of insulin resistance and may provide novel therapeutic targets.

Identification of target genes of cediranib in alveolar soft part sarcoma using a gene microarray

The aim of the present study was to identify the target genes of cediranib and the associated signaling pathways in alveolar soft part sarcoma (ASPS). A microarray dataset (GSE32569) was obtained from the Gene Expression Omnibus database. The R software package was used for data normalization and screening of differentially expressed genes (DEGs). The Database for Annotation, Visualization and Integrated Discovery was used to perform Gene Ontology analysis. Gene Set Enrichment Analysis was performed to obtain the up- and downregulated pathways in ASPS. The Distant Regulatory Elements of co-regulated genes database was used to identify the transcription factors (TFs) that were enriched in the signaling pathways. A protein-protein interaction (PPI) network was constructed using the Search Tool for the Retrieval of Interacting Genes/Proteins database and was visualized using Cytoscape software. A total of 71 DEGs, including 59 upregulated genes and 12 downregulated genes, were identified. Gene sets associated with ASPS were enriched primarily in four signaling pathways: The phenylalanine metabolism pathway, the mitogen-activated protein kinase (MAPK) signaling pathway, the taste transduction pathway and the intestinal immune network for the production of immunoglobulin A. Furthermore, 107 TFs were identified to be enriched in the MAPK signaling pathway. Certain genes, including those coding for Fms-like tyrosine kinase 1, kinase insert domain receptor, E-selectin and platelet-derived growth factor receptor D, that were associated with other genes in the PPI network, were identified. The present study identified certain potential target genes and the associated signaling pathways of cediranib action in ASPS, which may be helpful in understanding the efficacy of cediranib and the development of new targets for cediranib.

Genetic Contributions of Inflammation to Depression

This paper describes the effects of immune genes genetic variants and mRNA expression on depression's risk, severity, and response to antidepressant treatment, through a systematic review on all papers published between 2000 and 2016. Our results, based largely on case-control studies, suggest that common genetic variants and gene-expression pathways are involved in both immune activation and depression. The most replicated and relevant genetic variants include polymorphisms in the genes for interleukin (IL)-1β, IL-6, IL-10, monocyte chemoattractant protein-1, tumor necrosis factor-alpha, C-reactive protein, and phospholipase A2. Moreover, increased blood cytokines mRNA expression (especially of IL-1β) identifies patients that are less likely to respond to conventional antidepressants. However, even for the most replicated findings there are inconsistent results, not only between studies, but also between the immune effects of the genetic variants and the resulting effects on depression. We find evidence that these discrepant findings may be explained, at least in part, by the heterogeneity of the depression immunophenotype, by environmental influences and gene × environment interactions, and by the complex interfacing of genetic variants with gene expression. Indeed, some of the most robust findings have been obtained in patients developing depression in the context of treatment with interferon-alpha, a widely used model to mimic depression in the context of inflammation. Further 'omics' approaches, through GWAS and transcriptomics, will finally shed light on the interaction between immune genes, their expression, and the influence of the environment, in the pathogenesis of depression.

Pathway analysis of complex diseases for GWAS, extending to consider rare variants, multi-omics and interactions

BACKGROUND

Genome-wide association studies (GWAS) is a major method for studying the genetics of complex diseases. Finding all sequence variants to explain fully the aetiology of a disease is difficult because of their small effect sizes. To better explain disease mechanisms, pathway analysis is used to consolidate the effects of multiple variants, and hence increase the power of the study. While pathway analysis has previously been performed within GWAS only, it can now be extended to examining rare variants, other "-omics" and interaction data.

SCOPE OF REVIEW

1. Factors to consider in the choice of software for GWAS pathway analysis. 2. Examples of how pathway analysis is used to analyse rare variants, other "-omics" and interaction data.

MAJOR CONCLUSIONS

To choose appropriate software tools, factors for consideration include covariate compatibility, null hypothesis, one- or two-step analysis required, curation method of gene sets, size of pathways, and size of flanking regions to define gene boundaries. For rare variants, analysis performance depends on consistency between assumed and actual effect distribution of variants. Integration of other "-omics" data and interaction can better explain gene functions.

GENERAL SIGNIFICANCE

Pathway analysis methods will be more readily used for integration of multiple sources of data, and enable more accurate prediction of phenotypes.

Alterations of microRNA-124 expression in peripheral blood mononuclear cells in pre- and post-treatment patients with major depressive disorder

Recently, increasing evidence has indicated that dysfunction of microRNA-124 (miR-124) might be involved in the pathophysiology and treatment of major depressive disorder (MDD) in some animal models of depression. However, the role of miR-124 in MDD patients remains unclear. The objective of this study was to investigate whether the miR-124 expression levels in peripheral blood mononuclear cells (PBMCs) were associated with MDD and to evaluate the effects of antidepressant treatment on miR-124 levels. Quantitative real-time PCR was applied to detect miR-124 expression in 32 pre- and post-treatment MDD patients and 30 healthy controls. Our results showed that expression levels of miR-124 from PBMCs in MDD patients were significantly higher than those in healthy controls (p < 0.001), and that the area under the curve of miR-124 from ROC analysis was 0.762 with a sensitivity of 83.33% and specificity of 66.67% in distinguishing MDD patients from healthy controls. In addition, the expression levels of miR-124 were significantly down-regulated after eight weeks of treatment (p < 0.001). MiRNA target gene prediction and functional annotation analysis indicated that altered miR-124 was involved in affecting some important biological processes and pathways related to MDD. These results provide new information on miR-124 involvement in the biological alterations of MDD and in antidepressant effects.

The Genetics of Stress-Related Disorders: PTSD, Depression, and Anxiety Disorders

Research into the causes of psychopathology has largely focused on two broad etiologic factors: genetic vulnerability and environmental stressors. An important role for familial/heritable factors in the etiology of a broad range of psychiatric disorders was established well before the modern era of genomic research. This review focuses on the genetic basis of three disorder categories-posttraumatic stress disorder (PTSD), major depressive disorder (MDD), and the anxiety disorders-for which environmental stressors and stress responses are understood to be central to pathogenesis. Each of these disorders aggregates in families and is moderately heritable. More recently, molecular genetic approaches, including genome-wide studies of genetic variation, have been applied to identify specific risk variants. In this review, I summarize evidence for genetic contributions to PTSD, MDD, and the anxiety disorders including genetic epidemiology, the role of common genetic variation, the role of rare and structural variation, and the role of gene-environment interaction. Available data suggest that stress-related disorders are highly complex and polygenic and, despite substantial progress in other areas of psychiatric genetics, few risk loci have been identified for these disorders. Progress in this area will likely require analysis of much larger sample sizes than have been reported to date. The phenotypic complexity and genetic overlap among these disorders present further challenges. The review concludes with a discussion of prospects for clinical translation of genetic findings and future directions for research.

Systems Genomics Support for Immune and Inflammation Hypothesis of Depression

BACKGROUND

Immune system plays an important role in brain development and function. With the discovery of increased circulating inflammatory cytokine levels in depression over two decades ago, evidence implicating immune system alterations in the disease has increasingly accumulated.

OBJECTIVE

To assess the underlying etiology and pathophysiology, a brief overview of the hypothesis free genomic, transcriptomic and proteomic studies in depression is presented here in order to specifically examine if the immune and inflammation hypothesis of depression is supported.

RESULTS

It is observed that genes identified in genome-wide association studies, and genes showing differential expression in transcriptomic studies in human depression do separately overrepresent processes related to both development as well as functioning of the immune system, and inflammatory response. These processes are also enriched in differentially expressed genes reported in animal models of antidepressant treatment. It is further noted that some of the genes identified in genome sequencing and proteomic analyses in human depression, and transcriptomic studies in chronic social defeat stress, an established animal model of depression, relate to immune and inflammatory pathways.

CONCLUSION

In conclusion, integrative genomics evidence supports the immune and inflammation hypothesis of depression.

Primary phospholipase C and brain disorders

In the brain, the primary phospholipase C (PLC) proteins, PLCβ, and PLCγ, are activated primarily by neurotransmitters, neurotrophic factors, and hormones through G protein-coupled receptors (GPCRs) and receptor tyrosine kinases (RTKs). Among the primary PLC isozymes, PLCβ1, PLCβ4, and PLCγ1 are highly expressed and differentially distributed, suggesting a specific role for each PLC subtype in different regions of the brain. Primary PLCs control neuronal activity, which is important for synapse function and development. In addition, dysregulation of primary PLC signaling is linked to several brain disorders including epilepsy, schizophrenia, bipolar disorder, Huntington's disease, depression and Alzheimer's disease. In this review, we included current knowledge regarding the roles of primary PLC isozymes in brain disorders.

Discovery of serum biomarkers predicting development of a subsequent depressive episode in social anxiety disorder

Although social anxiety disorder (SAD) is strongly associated with the subsequent development of a depressive disorder (major depressive disorder or dysthymia), no underlying biological risk factors are known. We aimed to identify biomarkers which predict depressive episodes in SAD patients over a 2-year follow-up period. One hundred sixty-five multiplexed immunoassay analytes were investigated in blood serum of 143 SAD patients without co-morbid depressive disorders, recruited within the Netherlands Study of Depression and Anxiety (NESDA). Predictive performance of identified biomarkers, clinical variables and self-report inventories was assessed using receiver operating characteristics curves (ROC) and represented by the area under the ROC curve (AUC). Stepwise logistic regression resulted in the selection of four serum analytes (AXL receptor tyrosine kinase, vascular cell adhesion molecule 1, vitronectin, collagen IV) and four additional variables (Inventory of Depressive Symptomatology, Beck Anxiety Inventory somatic subscale, depressive disorder lifetime diagnosis, BMI) as optimal set of patient parameters. When combined, an AUC of 0.86 was achieved for the identification of SAD individuals who later developed a depressive disorder. Throughout our analyses, biomarkers yielded superior discriminative performance compared to clinical variables and self-report inventories alone. We report the discovery of a serum marker panel with good predictive performance to identify SAD individuals prone to develop subsequent depressive episodes in a naturalistic cohort design. Furthermore, we emphasise the importance to combine biological markers, clinical variables and self-report inventories for disease course predictions in psychiatry. Following replication in independent cohorts, validated biomarkers could help to identify SAD patients at risk of developing a depressive disorder, thus facilitating early intervention.

The genetic basis of quality of life in healthy Swedish women: a candidate gene approach

BACKGROUND

Quality of life (QoL) is an increasingly important parameter in clinical practice as it predicts mortality and poor health outcomes. It is hypothesized that one may have a genetic predisposition for QoL. We therefore related 139 candidate genes, selected through a literature search, to QoL in healthy females.

METHODS

In 5,142 healthy females, background characteristics (i.e. demographic, clinical, lifestyle, and psychological factors) were assessed. QoL was measured by the EORTC QLQ-C30, which consists of 15 domains. For all women genotype information was available. For each candidate gene, single nucleotide polymorphisms (SNPs) were identified based on their functional (n = 2,663) and physical annotation (n = 10,649). SNPs were related to each QoL-domain, while controlling for background characteristics and population stratification. Finally, gene-based analyses were performed relating the combined effect of 10,649 SNPs (selected based on physical annotation) for each gene, to QoL using the statistical software package VEGAS.

RESULTS

Overall, we found no relation between genetic variations (SNPs and genes) and 14 out of 15 QoL-domains. The strongest association was found between cognitive functioning and the top SNP rs1468951 (p = 1.21E-05) in the GSTZ1 gene. Furthermore, results of the gene-based test showed that the combined effect of 11 SNPs within the GSTZ1 gene is significantly associated with cognitive functioning (p = 2.60E-05).

CONCLUSION

If validated, the involvement of GSTZ1 in cognitive functioning underscores its heritability which is likely the result of differences in the dopamine pathway, as GSTZ1 contributes to the equilibrium between dopamine and its neurotoxic metabolites via the glutathione redox cycle.

Detecting key genes regulated by miRNAs in dysfunctional crosstalk pathway of myasthenia gravis

Myasthenia gravis (MG) is a neuromuscular autoimmune disorder resulting from autoantibodies attacking components of the neuromuscular junction. Recent studies have implicated the aberrant expression of microRNAs (miRNAs) in the pathogenesis of MG; however, the underlying mechanisms remain largely unknown. This study aimed to identify key genes regulated by miRNAs in MG. Six dysregulated pathways were identified through differentially expressed miRNAs and mRNAs in MG, and significant crosstalk was detected between five of these. Notably, crosstalk between the "synaptic long-term potentiation" pathway and four others was mediated by five genes involved in the MAPK signaling pathway. Furthermore, 14 key genes regulated by miRNAs were detected, of which six-MAPK1, RAF1, PGF, PDGFRA, EP300, and PPP1CC-mediated interactions between the dysregulated pathways. MAPK1 and RAF1 were responsible for most of this crosstalk (80%), likely reflecting their central roles in MG pathogenesis. In addition, most key genes were enriched in immune-related local areas that were strongly disordered in MG. These results provide new insight into the pathogenesis of MG and offer new potential targets for therapeutic intervention.

Genetic determinants of depression: recent findings and future directions

LEARNING OBJECTIVES

After participating in this activity, learners should be better able to: 1. Evaluate current evidence regarding the genetic determinants of depression 2. Assess findings from studies of gene-environment interaction 3. Identify challenges to gene discovery in depression Depression is one of the most prevalent, disabling, and costly mental health conditions in the United States and also worldwide. One promising avenue for preventing depression and informing its clinical treatment lies in uncovering the genetic and environmental determinants of the disorder as well as their interaction (G × E). The overarching goal of this review article is to translate recent findings from studies of genetic association and G × E related to depression, particularly for readers without in-depth knowledge of genetics or genetic methods. The review is organized into three major sections. In the first, we summarize what is currently known about the genetic determinants of depression, focusing on findings from genome-wide association studies (GWAS). In the second section, we review findings from studies of G × E, which seek to simultaneously examine the role of genes and exposure to specific environments or experiences in the etiology of depression. In the third section, we describe the challenges to genetic discovery in depression and promising strategies for future progress.

Targeting glia cells: novel perspectives for the treatment of neuropsychiatric diseases

Neuropsychiatric disorders are devastating mental illnesses with a high economic burden. The additional morbidity associated with social issues that arises along with the course of these diseases increases the need for a clear understanding of their etiopathogenesis to allow an implementation of novel pharmacological strategies. Yet a poor knowledge about interactions occurring at the glia-neuron interface in health and disease still hampers innovative discoveries, despite the fact that glia cells have been long described to actively participate in the regulation of brain circuits.

The purpose of this review was to collect the scattered literature on the involvement of glia cells in neuropsychiatric disorders and to describe how also these cells besides neurons might be responsive to current pharmacological interventions. We hope thereby to offer alternative approaches for investigations that may open avenues to search for new potential targets for drug discovery.

A genome-wide association study of a sustained pattern of antidepressant response

Genome-wide association studies (GWAS) have failed to replicate common genetic variants associated with antidepressant response, as defined using a single endpoint. Genetic influences may be discernible by examining individual variation between sustained versus unsustained patterns of response, which may distinguish medication effects from non-specific, or placebo responses to active medication. We conducted a GWAS among 1116 subjects with Major Depressive Disorder from the Sequenced Treatment Alternatives to Relieve Depression (STAR*D) trial who were characterized using Growth Mixture Modeling as showing a sustained versus unsustained pattern of clinical response over 12 weeks of treatment with citalopram. Replication analyses examined 585 subjects from the Genome-based Therapeutic Drugs for Depression (GENDEP) trial. The strongest association with sustained as opposed to unsustained response in STAR*D involved a single nucleotide polymorphism (SNP; rs10492002) within the acyl-CoA synthetase short-chain family member 3 gene (ACSS3, p-value=4.5×10(-6), odds ratio=0.61). No SNPs met our threshold for genome-wide significance. SNP data were available in GENDEP for 18 of the top 25 SNPs in STAR*D. The most replicable association was with SNP rs7816924 (p=0.008, OR=1.58); no SNP met the replication p-value threshold of 0.003. Joint analysis of these 18 SNPs resulted in the strongest signal coming from rs7816924 (p=2.11×10(-7)), which resides in chondroitin sulfate N-acetylgalactosaminyltransferase 1 gene (CSGALNACT1). An exploratory genetic pathway analysis revealed evidence for an involvement of the KEGG pathway of long-term potentiation (FDR=.02). Results suggest novel genetic associations to sustained response.

Postgwas: advanced GWAS interpretation in R

We present a comprehensive toolkit for post-processing, visualization and advanced analysis of GWAS results. In the spirit of comparable tools for gene-expression analysis, we attempt to unify and simplify several procedures that are essential for the interpretation of GWAS results. This includes the generation of advanced Manhattan and regional association plots including rare variant display as well as novel interaction network analysis tools for the investigation of systems-biology aspects. Our package supports virtually all model organisms and represents the first cohesive implementation of such tools for the popular language R. Previous software of that range is dispersed over a wide range of platforms and mostly not adaptable for custom work pipelines. We demonstrate the utility of this package by providing an example workflow on a publicly available dataset.

Association signals unveiled by a comprehensive gene set enrichment analysis of dental caries genome-wide association studies

Gene set-based analysis of genome-wide association study (GWAS) data has recently emerged as a useful approach to examine the joint effects of multiple risk loci in complex human diseases or phenotypes. Dental caries is a common, chronic, and complex disease leading to a decrease in quality of life worldwide. In this study, we applied the approaches of gene set enrichment analysis to a major dental caries GWAS dataset, which consists of 537 cases and 605 controls. Using four complementary gene set analysis methods, we analyzed 1331 Gene Ontology (GO) terms collected from the Molecular Signatures Database (MSigDB). Setting false discovery rate (FDR) threshold as 0.05, we identified 13 significantly associated GO terms. Additionally, 17 terms were further included as marginally associated because they were top ranked by each method, although their FDR is higher than 0.05. In total, we identified 30 promising GO terms, including ‘Sphingoid metabolic process,’ ‘Ubiquitin protein ligase activity,’ ‘Regulation of cytokine secretion,’ and ‘Ceramide metabolic process.’ These GO terms encompass broad functions that potentially interact and contribute to the oral immune response related to caries development, which have not been reported in the standard single marker based analysis. Collectively, our gene set enrichment analysis provided complementary insights into the molecular mechanisms and polygenic interactions in dental caries, revealing promising association signals that could not be detected through single marker analysis of GWAS data.

Pathway analysis using information from allele-specific gene methylation in genome-wide association studies for bipolar disorder

Bipolar disorder (BPD) is a complex psychiatric trait with high heritability. Despite efforts through conducting genome-wide association (GWA) studies, the success of identifying susceptibility loci for BPD has been limited, which is partially attributed to the complex nature of its pathogenesis. Pathway-based analytic strategy is a powerful tool to explore joint effects of gene sets within specific biological pathways. Additionally, to incorporate other aspects of genomic data into pathway analysis may further enhance our understanding for the underlying mechanisms for BPD. Patterns of DNA methylation play important roles in regulating gene expression and function. A commonly observed phenomenon, allele-specific methylation (ASM) describes the associations between genetic variants and DNA methylation patterns. The present study aimed to identify biological pathways that are involve in the pathogenesis of BPD while incorporating brain specific ASM information in pathway analysis using two large-scale GWA datasets in Caucasian populations. A weighting scheme was adopted to take ASM information into consideration for each pathway. After multiple testing corrections, we identified 88 and 15 enriched pathways for their biological relevance for BPD in the Genetic Association Information Network (GAIN) and the Wellcome Trust Case Control Consortium dataset, respectively. Many of these pathways were significant only when applying the weighting scheme. Three ion channel related pathways were consistently identified in both datasets. Results in the GAIN dataset also suggest for the roles of extracellular matrix in brain for BPD. Findings from Gene Ontology (GO) analysis exhibited functional enrichment among genes of non-GO pathways in activity of gated channel, transporter, and neurotransmitter receptor. We demonstrated that integrating different data sources with pathway analysis provides an avenue to identify promising and novel biological pathways for exploring the underlying molecular mechanisms for bipolar disorder. Further basic research can be conducted to target the biological mechanisms for the identified genes and pathways.

Incorporating Information of microRNAs into Pathway Analysis in a Genome-Wide Association Study of Bipolar Disorder

MicroRNAs (miRNAs) are known to be important post-transcriptional regulators that are involved in the etiology of complex psychiatric traits. The present study aimed to incorporate miRNAs information into pathway analysis using a genome-wide association dataset to identify relevant biological pathways for bipolar disorder (BPD). We selected psychiatric- and neurological-associated miRNAs (N = 157) from PhenomiR database. The miRNA target genes (miTG) predictions were obtained from microRNA.org. Canonical pathways (N = 4,051) were downloaded from the Molecule Signature Database. We employed a novel weighting scheme for miTGs in pathway analysis using methods of gene set enrichment analysis and sum-statistic. Under four statistical scenarios, 38 significantly enriched pathways (P-value < 0.01 after multiple testing correction) were identified for the risk of developing BPD, including pathways of ion channels associated (e.g., gated channel activity, ion transmembrane transporter activity, and ion channel activity) and nervous related biological processes (e.g., nervous system development, cytoskeleton, and neuroactive ligand receptor interaction). Among them, 19 were identified only when the weighting scheme was applied. Many miRNA-targeted genes were functionally related to ion channels, collagen, and axonal growth and guidance that have been suggested to be associated with BPD previously. Some of these genes are linked to the regulation of miRNA machinery in the literature. Our findings provide support for the potential involvement of miRNAs in the psychopathology of BPD. Further investigations to elucidate the functions and mechanisms of identified candidate pathways are needed.

Responder and nonresponder patients exhibit different peripheral transcriptional signatures during major depressive episode

To date, it remains impossible to guarantee that short-term treatment given to a patient suffering from a major depressive episode (MDE) will improve long-term efficacy. Objective biological measurements and biomarkers that could help in predicting the clinical evolution of MDE are still warranted. To better understand the reason nearly half of MDE patients respond poorly to current antidepressive treatments, we examined the gene expression profile of peripheral blood samples collected from 16 severe MDE patients and 13 matched controls. Using a naturalistic and longitudinal design, we ascertained mRNA and microRNA (miRNA) expression at baseline, 2 and 8 weeks later. On a genome-wide scale, we detected transcripts with roles in various biological processes as significantly dysregulated between MDE patients and controls, notably those involved in nucleotide binding and chromatin assembly. We also established putative interactions between dysregulated mRNAs and miRNAs that may contribute to MDE physiopathology. We selected a set of mRNA candidates for quantitative reverse transcriptase PCR (RT-qPCR) to validate that the transcriptional signatures observed in responders is different from nonresponders. Furthermore, we identified a combination of four mRNAs (PPT1, TNF, IL1B and HIST1H1E) that could be predictive of treatment response. Altogether, these results highlight the importance of studies investigating the tight relationship between peripheral transcriptional changes and the dynamic clinical progression of MDE patients to provide biomarkers of MDE evolution and prognosis.

A comprehensive network and pathway analysis of candidate genes in major depressive disorder

BACKGROUND

Numerous genetic and genomic datasets related to complex diseases have been made available during the last decade. It is now a great challenge to assess such heterogeneous datasets to prioritize disease genes and perform follow up functional analysis and validation. Among complex disease studies, psychiatric disorders such as major depressive disorder (MDD) are especially in need of robust integrative analysis because these diseases are more complex than others, with weak genetic factors at various levels, including genetic markers, transcription (gene expression), epigenetics (methylation), protein, pathways and networks.

RESULTS

In this study, we proposed a comprehensive analysis framework at the systems level and demonstrated it in MDD using a set of candidate genes that have recently been prioritized based on multiple lines of evidence including association, linkage, gene expression (both human and animal studies), regulatory pathway, and literature search. In the network analysis, we explored the topological characteristics of these genes in the context of the human interactome and compared them with two other complex diseases. The network topological features indicated that MDD is similar to schizophrenia compared to cancer. In the functional analysis, we performed the gene set enrichment analysis for both Gene Ontology categories and canonical pathways. Moreover, we proposed a unique pathway crosstalk approach to examine the dynamic interactions among biological pathways. Our pathway enrichment and crosstalk analyses revealed two unique pathway interaction modules that were significantly enriched with MDD genes. These two modules are neuro-transmission and immune system related, supporting the neuropathology hypothesis of MDD. Finally, we constructed a MDD-specific subnetwork, which recruited novel candidate genes with association signals from a major MDD GWAS dataset.

CONCLUSIONS

This study is the first systematic network and pathway analysis of candidate genes in MDD, providing abundant important information about gene interaction and regulation in a major psychiatric disease. The results suggest potential functional components underlying the molecular mechanisms of MDD and, thus, facilitate generation of novel hypotheses in this disease. The systems biology based strategy in this study can be applied to many other complex diseases.