Assessment of human stress and depression by DNA microarray analysis

Gene expression-based biological test for major depressive disorder: an advanced study

PURPOSE

Recently, we could distinguished patients with major depressive disorder (MDD) from nonpsychiatric controls with high accuracy using a panel of five gene expression markers (ARHGAP24, HDAC5, PDGFC, PRNP, and SLC6A4) in leukocyte. In the present study, we examined whether this biological test is able to discriminate patients with MDD from those without MDD, including those with schizophrenia and bipolar disorder.

PATIENTS AND METHODS

We measured messenger ribonucleic acid expression levels of the aforementioned five genes in peripheral leukocytes in 17 patients with schizophrenia and 36 patients with bipolar disorder using quantitative real-time polymerase chain reaction (PCR), and we combined these expression data with our previous expression data of 25 patients with MDD and 25 controls. Subsequently, a linear discriminant function was developed for use in discriminating between patients with MDD and without MDD.

RESULTS

This expression panel was able to segregate patients with MDD from those without MDD with a sensitivity and specificity of 64% and 67.9%, respectively.

CONCLUSION

Further research to identify MDD-specific markers is needed to improve the performance of this biological test.

Alterations in leukocyte transcriptional control pathway activity associated with major depressive disorder and antidepressant treatment

Major depressive disorder (MDD) is associated with a significantly elevated risk of developing serious medical illnesses such as cardiovascular disease, immune impairments, infection, dementia and premature death. Previous work has demonstrated immune dysregulation in subjects with MDD. Using genome-wide transcriptional profiling and promoter-based bioinformatic strategies, we assessed leukocyte transcription factor (TF) activity in leukocytes from 20 unmedicated MDD subjects versus 20 age-, sex- and ethnicity-matched healthy controls, before initiation of antidepressant therapy, and in 17 of the MDD subjects after 8 weeks of sertraline treatment. In leukocytes from unmedicated MDD subjects, bioinformatic analysis of transcription control pathway activity indicated an increased transcriptional activity of cAMP response element-binding/activating TF (CREB/ATF) and increased activity of TFs associated with cellular responses to oxidative stress (nuclear factor erythroid-derived 2-like 2, NFE2l2 or NRF2). Eight weeks of antidepressant therapy was associated with significant reductions in Hamilton Depression Rating Scale scores and reduced activity of NRF2, but not in CREB/ATF activity. Several other transcriptional regulation pathways, including the glucocorticoid receptor (GR), nuclear factor kappa-B cells (NF-κB), early growth response proteins 1-4 (EGR1-4) and interferon-responsive TFs, showed either no significant differences as a function of disease or treatment, or activities that were opposite to those previously hypothesized to be involved in the etiology of MDD or effective treatment. Our results suggest that CREB/ATF and NRF2 signaling may contribute to MDD by activating immune cell transcriptome dynamics that ultimately influence central nervous system (CNS) motivational and affective processes via circulating mediators.

Biological tests for major depressive disorder that involve leukocyte gene expression assays

BACKGROUND

Development of easy-to-use biological diagnostic tests for major depressive disorder (MDD) may facilitate MDD diagnosis and delivery of optimal treatment. Here, we examined leukocyte gene expression to develop a biological diagnostic test for MDD.

METHODS

25 drug-naive MDD patients (MDDs) and 25 age- and sex-matched healthy subjects (Controls) participated in a pilot study. A subsequent replication study involved 20 MDDs and 18 Controls. We used custom-made PCR array plates to examine mRNA levels of 40 candidate genes in leukocyte samples to assess whether any combination of these genes could be used to differentiate MDDs from Controls based on expression profiles.

RESULTS

Among 40 candidate genes, we identified a set of seven genes (PDGFC, SLC6A4, PDLIM5, ARHGAP24, PRNP, HDAC5, and IL1R2), each of which had expression levels that differed significantly between MDD and Control samples in the pilot study. To identify genes whose expression best differentiated between MDDs and Controls, a linear discriminant function was developed to discriminate between MDDs and Controls based on the standardized values of gene expression after Z-score transformation. Ultimately, five genes (PDGFC, SLC6A4, ARHGAP24, PRNP, and HDAC5) were selected for a multi-assay diagnostic test. In the pilot study, this diagnostic test demonstrated sensitivity and specificity of 80% and 92%, respectively. The replication study yielded nearly identical results, sensitivity of 85% and specificity of 89%.

CONCLUSIONS

Using leukocyte gene expression profiles, we could differentiate MDDs from Controls with adequate sensitivity and specificity. Additional markers not yet identified might further improve the performance of this test.

IL-1 receptor 2 (IL-1R2) and its role in immune regulation

The cytokine IL-1 is critical to the pathogenesis of a variety of human conditions and diseases. Unlike most other cytokines, IL-1 is counterbalanced by two endogenous inhibitors. The functional significance of IL-1 receptor antagonist (IL-1RA) is well documented due to the clinical utilization of the recombinant human IL-1RA analog, anakinra. In contrast, much less is known about the type 2 IL-1 receptor (IL-1R2), which acts as a decoy receptor for IL-1. While IL-1R2 is structurally similar to the type 1 IL-1 receptor (IL-1R1) responsible for IL-1 signal transduction, its truncated cytoplasmic domain and lack of Toll-IL-1 receptor (TIR) region renders IL-1R2 incapable of transmembrane signaling. IL-1R2 competes with IL-1R1 for ligands and for the IL-1R1 co-receptor, IL-1 receptor accessory protein (IL-1RAP). Additionally, IL-1R2 exists in both a membrane bound and soluble form (sIL-1R2) that has biological properties similar to both a decoy receptor and a binding protein. Thus far, IL-1R2 has been implicated in arthritis, endometriosis, organ transplantation, sepsis/sickness behavior, diabetes, atherosclerosis, autoimmune inner ear disease (AIED), Alzheimer's disease and ulcerative colitis. In this review, we will detail the functional properties of IL-1R2 and examine its role in human disease.

Nervous system regulation of the cancer genome

Genomics-based analyses have provided deep insight into the basic biology of cancer and are now clarifying the molecular pathways by which psychological and social factors can regulate tumor cell gene expression and genome evolution. This review summarizes basic and clinical research on neural and endocrine regulation of the cancer genome and its interactions with the surrounding tumor microenvironment, including the specific types of genes subject to neural and endocrine regulation, the signal transduction pathways that mediate such effects, and therapeutic approaches that might be deployed to mitigate their impact. Beta-adrenergic signaling from the sympathetic nervous system has been found to up-regulated a diverse array of genes that contribute to tumor progression and metastasis, whereas glucocorticoid-regulated genes can inhibit DNA repair and promote cancer cell survival and resistance to chemotherapy. Relationships between socio-environmental risk factors, neural and endocrine signaling to the tumor microenvironment, and transcriptional responses by cancer cells and surrounding stromal cells are providing new mechanistic insights into the social epidemiology of cancer, new therapeutic approaches for protecting the health of cancer patients, and new molecular biomarkers for assessing the impact of behavioral and pharmacologic interventions.

Transcriptomics identifies differences between ultrapure non-dioxin-like polychlorinated biphenyls (PCBs) and dioxin-like PCB126 in cultured peripheral blood mononuclear cells

Polychlorinated biphenyls (PCBs) remain ubiquitously present in human lipids despite the ban on their production and use. Their presence can be chemically monitored in peripheral blood samples of the general population. We tested whether in vitro exposure to different PCB congeners induced different gene expression profiles in peripheral blood cells. We have isolated peripheral blood mononuclear cells (PBMC) from whole blood of 8 healthy individuals and exposed these cells in vitro to individual non-dioxin-like (NDL)-PCB congeners (PCB52, 138 or 180; 10μM) or dioxin-like (DL)-PCB congener PCB126 (1μM) during 18h. Differential gene expression response was measured using Agilent whole-human genome microarrays. Two-way ANOVA analysis of the data showed that both gender and PCB exposure are important factors influencing gene expression responses in blood cells. Hierarchical cluster analysis of genes influenced by PCB exposure, revealed that DL-PCB126 induced a different gene expression response compared to the NDL-PCBs. Biological interpretation of the results revealed that exposure to PCB126 induced the AhR signaling pathway, whereas the induction of nuclear receptor pathways by the NDL-PCBs was limited in blood cells. Nevertheless, molecular responses of blood cells to individual PCB congeners revealed significantly expressed genes that play a role in biological functions and processes known to be affected by PCB exposure in vivo. Observed gene expression changes in this in vitro model were found to be related to hepatotoxicity, immune and inflammatory response and disturbance of lipid and cholesterol homeostasis.

Convergent functional genomics of anxiety disorders: translational identification of genes, biomarkers, pathways and mechanisms

Anxiety disorders are prevalent and disabling yet understudied from a genetic standpoint, compared with other major psychiatric disorders such as bipolar disorder and schizophrenia. The fact that they are more common, diverse and perceived as embedded in normal life may explain this relative oversight. In addition, as for other psychiatric disorders, there are technical challenges related to the identification and validation of candidate genes and peripheral biomarkers. Human studies, particularly genetic ones, are susceptible to the issue of being underpowered, because of genetic heterogeneity, the effect of variable environmental exposure on gene expression, and difficulty of accrual of large, well phenotyped cohorts. Animal model gene expression studies, in a genetically homogeneous and experimentally tractable setting, can avoid artifacts and provide sensitivity of detection. Subsequent translational integration of the animal model datasets with human genetic and gene expression datasets can ensure cross-validatory power and specificity for illness. We have used a pharmacogenomic mouse model (involving treatments with an anxiogenic drug--yohimbine, and an anti-anxiety drug--diazepam) as a discovery engine for identification of anxiety candidate genes as well as potential blood biomarkers. Gene expression changes in key brain regions for anxiety (prefrontal cortex, amygdala and hippocampus) and blood were analyzed using a convergent functional genomics (CFG) approach, which integrates our new data with published human and animal model data, as a translational strategy of cross-matching and prioritizing findings. Our work identifies top candidate genes (such as FOS, GABBR1, NR4A2, DRD1, ADORA2A, QKI, RGS2, PTGDS, HSPA1B, DYNLL2, CCKBR and DBP), brain-blood biomarkers (such as FOS, QKI and HSPA1B), pathways (such as cAMP signaling) and mechanisms for anxiety disorders--notably signal transduction and reactivity to environment, with a prominent role for the hippocampus. Overall, this work complements our previous similar work (on bipolar mood disorders and schizophrenia) conducted over the last decade. It concludes our programmatic first pass mapping of the genomic landscape of the triad of major psychiatric disorder domains using CFG, and permitted us to uncover the significant genetic overlap between anxiety and these other major psychiatric disorders, notably the under-appreciated overlap with schizophrenia. PDE10A, TAC1 and other genes uncovered by our work provide a molecular basis for the frequently observed clinical co-morbidity and interdependence between anxiety and other major psychiatric disorders, and suggest schizo-anxiety as a possible new nosological domain.

Suppressed monocyte gene expression profile in men versus women with PTSD

There have been several attempts to use gene microarrays from peripheral blood mononuclear cells to identify new biological pathways or targets for therapy in Posttraumatic Stress Disorder (PTSD). The few studies conducted to date have yielded an unclear pattern of findings, perhaps reflecting the use of heterogeneous samples of circulating immune cells for analysis. We used gene microarrays on a homogeneous sample of circulating monocytes to test the hypothesis that chronic PTSD would be associated with elevated inflammatory activity and to identify new pathways dysregulated in the disorder. Forty-nine men (24 PTSD+ and 25 age-matched trauma-exposed PTSD- controls) and 18 women (10 PTSD+ and 8 age-matched PTSD- controls) were recruited. Gene expression microarray analysis was performed on CD14+ monocytes, immune cells that initiate and respond to inflammatory signaling. Male subjects with PTSD had an overall pattern of under-expression of genes on monocytes (47 under-expressed versus 4 over-expressed genes). A rigorous correction for multiple comparisons and verification with qPCR showed that of only 3 genes that were differentially expressed, all were under-expressed. There was no transcriptional evidence of chronic inflammation in male PTSD+ subjects. In contrast, preliminary data from our pilot female PTSD+ subjects showed a relatively balanced pattern of increased and decreased expression of genes and an increase in activity of pathways related to immune activation. The results indicate differential patterns of monocyte gene expression in PTSD, and the preliminary data from our female pilot subjects are suggestive of gender dimorphism in biologic pathways activated in PTSD. Changes in immune cell gene expression may contribute to medical morbidity in PTSD.

Elevating the perspective on human stress genomics

Functional genomics strategies have been slow to penetrate research on human stress and coping, but recent conceptual advances have yielded a raft of new findings relating social and psychological conditions to broad alterations in human gene expression. This article reviews the field of human stress genomics, analyzes some of the conceptual and technical issues that initially hampered its progress, and outlines an abstractionist approach to genomic data analysis that has revealed a surprisingly consistent pattern of human transcriptional responses to diverse types of socio-environmental adversity. This field is now poised for another round of significant advances as research begins to incorporate the effects of DNA polymorphism, target a broader array of healthy and diseased tissues, and identify general teleologic and regulatory themes by pooling results over a growing body of studies analyzing the human transcriptional response to stress.

Diagnostic classification of schizophrenia by neural network analysis of blood-based gene expression signatures

Gene expression profiling with microarray technology suggests that peripheral blood cells might be a surrogate for postmortem brain tissue in studies of schizophrenia. The development of an accessible peripheral biomarker would substantially help in the diagnosis of this disease. We used a bioinformatics approach to examine whether the gene expression signature in whole blood contains enough information to make a specific diagnosis of schizophrenia. Unpaired t-tests of gene expression datasets from 52 antipsychotics-free schizophrenia patients and 49 normal controls identified 792 differentially expressed probes. Functional profiling with DAVID revealed that eleven of these genes were previously reported to be associated with schizophrenia, and 73 of them were expressed in the brain tissue. We analyzed the datasets with one of the supervised classifiers, artificial neural networks (ANNs). The samples were subdivided into training and testing sets. Quality filtering and stepwise forward selection identified 14 probes as predictors of the diagnosis. ANNs were then trained with the selected probes as the input and the training set for known diagnosis as the output. The constructed model achieved 91.2% diagnostic accuracy in the training set and 87.9% accuracy in the hold-out testing set. On the other hand, hierarchical clustering, a standard but unsupervised classifier, failed to separate patients and controls. These results suggest analysis of a blood-based gene expression signature with the supervised classifier, ANNs, might be a diagnostic tool for schizophrenia.

Phenomic, convergent functional genomic, and biomarker studies in a stress-reactive genetic animal model of bipolar disorder and co-morbid alcoholism

We had previously identified the clock gene D-box binding protein (Dbp) as a potential candidate gene for bipolar disorder and for alcoholism, using a Convergent Functional Genomics (CFG) approach. Here we report that mice with a homozygous deletion of DBP have lower locomotor activity, blunted responses to stimulants, and gain less weight over time. In response to a chronic stress paradigm, these mice exhibit a diametric switch in these phenotypes. DBP knockout mice are also activated by sleep deprivation, similar to bipolar patients, and that activation is prevented by treatment with the mood stabilizer drug valproate. Moreover, these mice show increased alcohol intake following exposure to stress. Microarray studies of brain and blood reveal a pattern of gene expression changes that may explain the observed phenotypes. CFG analysis of the gene expression changes identified a series of novel candidate genes and blood biomarkers for bipolar disorder, alcoholism, and stress reactivity.

Molecular assessment of depression from mRNAs in the peripheral leukocytes

Depression is a disorder not only in the central nervous system (CNS), but also in the systemic neuroendocrine, autonomic nervous, and immune systems. The changes in these systems have been widely studied in depression by using serum proteins because they are easily and repetitively studied before, during, and after treatment. Recently, gene expressions in the peripheral blood leukocytes have been used to assess the depressive changes in the CNS by DNA microarrays and/or real-time polymerase chain reaction (PCR) methods. These studies will give us clues to assess depression because circulating peripheral leukocytes are influenced by systems that underlie depression, and the quantification of mRNAs in them is methodologically precise and easier than that of protein. In this paper, we review the studies on the leukocyte gene expression, including our own, and discuss the limitations and strengths of the current gene expression-based molecular assessment of depression by the leukocyte mRNA expression.