SNORA69 is up-regulated in the lateral habenula of individuals with major depressive disorder.

Major depressive disorder (MDD) is a complex and potentially debilitating illness whose etiology and pathology remains unclear. Non-coding RNAs have been implicated in MDD, where they display differential expression in the brain and the periphery. In this study, we quantified small nucleolar RNA (snoRNA) expression by small RNA sequencing in the lateral habenula (LHb) of individuals with MDD (n = 15) and psychiatrically-healthy controls (n = 15). We uncovered five snoRNAs that exhibited differential expression between MDD and controls (FDR < 0.01). Specifically, SNORA69 showed increased expression in MDD and was technically validated via RT-qPCR. We further investigated the expression of Snora69 in the LHb and peripheral blood of an unpredicted chronic mild stress (UCMS) mouse model of depression. Snora69 was specifically up-regulated in mice that underwent the UCMS paradigm. SNORA69 is known to guide pseudouridylation onto 5.8S and 18S rRNAs. We quantified the relative abundance of pseudouridines on 5.8S and 18S rRNA in human post-mortem LHb samples and found increased abundance of pseudouridines in the MDD group. Overall, our findings indicate the importance of brain snoRNAs in the pathology of MDD. Future studies characterizing SNORA69's role in MDD pathology is warranted.

Molecular mapping of a core transcriptional signature of microglia-specific genes in schizophrenia.

Besides playing a central role in neuroinflammation, microglia regulate synaptic development and is involved in plasticity. Converging lines of evidence suggest that these different processes play a critical role in schizophrenia. Furthermore, previous studies reported altered transcription of microglia genes in schizophrenia, while microglia itself seems to be involved in the etiopathology of the disease. However, the regional specificity of these brain transcriptional abnormalities remains unclear. Moreover, it is unknown whether brain and peripheral expression of microglia genes are related. Thus, we investigated the expression of a pre-registered list of 10 genes from a core signature of human microglia both at brain and peripheral levels. We included 9 independent Gene Expression Omnibus datasets (764 samples obtained from 266 individuals with schizophrenia and 237 healthy controls) from 8 different brain regions and 3 peripheral tissues. We report evidence of a widespread transcriptional alteration of microglia genes both in brain tissues (we observed a decreased expression in the cerebellum, associative striatum, hippocampus, and parietal cortex of individuals with schizophrenia compared with healthy controls) and whole blood (characterized by a mixed altered expression pattern). Our results suggest that brain underexpression of microglia genes may represent a candidate transcriptional signature for schizophrenia. Moreover, the dual brain-whole blood transcriptional alterations of microglia/macrophage genes identified support the model of schizophrenia as a whole-body disorder and lend weight to the use of blood samples as a potential source of biological peripheral biomarkers.

Accelerated aging in bipolar disorders: An exploratory study of six epigenetic clocks.

Bipolar disorder (BD) is a chronic and severe psychiatric disorder associated with significant medical morbidity and reduced life expectancy. In this study, we assessed accelerated epigenetic aging in individuals with BD using various DNA methylation (DNAm)-based markers. For this purpose, we used five epigenetic clocks (Horvath, Hannum, EN, PhenoAge, and GrimAge) and a DNAm-based telomere length clock (DNAmTL). DNAm profiles were obtained using Infinium MethylationEPIC Arrays from whole-blood samples of 184 individuals with BD. We also estimated blood cell counts based on DNAm levels for adjustment. Significant correlations between chronological age and each epigenetic age estimated using the six different clocks were observed. Following adjustment for blood cell counts, we found that the six epigenetic AgeAccels (age accelerations) were significantly associated with the body mass index. GrimAge AgeAccel was significantly associated with male sex, smoking status and childhood maltreatment. DNAmTL AgeAccel was significantly associated with smoking status. Overall, this study showed that distinct epigenetic clocks are sensitive to different aspects of aging process in BD. Further investigations with comprehensive epigenetic clock analyses and large samples are required to confirm our findings of potential determinants of an accelerated epigenetic aging in BD.

SNORD90 induces glutamatergic signaling following treatment with monoaminergic antidepressants.

Pharmacotherapies for the treatment of major depressive disorder were serendipitously discovered almost seven decades ago. From this discovery, scientists pinpointed the monoaminergic system as the primary target associated with symptom alleviation. As a result, most antidepressants have been engineered to act on the monoaminergic system more selectively, primarily on serotonin, in an effort to increase treatment response and reduce unfavorable side effects. However, slow and inconsistent clinical responses continue to be observed with these available treatments. Recent findings point to the glutamatergic system as a target for rapid acting antidepressants. Investigating different cohorts of depressed individuals treated with serotonergic and other monoaminergic antidepressants, we found that the expression of a small nucleolar RNA, SNORD90, was elevated following treatment response. When we increased Snord90 levels in the mouse anterior cingulate cortex (ACC), a brain region regulating mood responses, we observed antidepressive-like behaviors. We identified neuregulin 3 (NRG3) as one of the targets of SNORD90, which we show is regulated through the accumulation of N6-methyladenosine modifications leading to YTHDF2-mediated RNA decay. We further demonstrate that a decrease in NRG3 expression resulted in increased glutamatergic release in the mouse ACC. These findings support a molecular link between monoaminergic antidepressant treatment and glutamatergic neurotransmission.

The basolateral amygdala-anterior cingulate pathway contributes to depression-like behaviors and comorbidity with chronic pain behaviors in male mice.

While depression and chronic pain are frequently comorbid, underlying neuronal circuits and their psychopathological relevance remain poorly defined. Here we show in mice that hyperactivity of the neuronal pathway linking the basolateral amygdala to the anterior cingulate cortex is essential for chronic pain-induced depression. Moreover, activation of this pathway in naive male mice, in the absence of on-going pain, is sufficient to trigger depressive-like behaviors, as well as transcriptomic alterations that recapitulate core molecular features of depression in the human brain. These alterations notably impact gene modules related to myelination and the oligodendrocyte lineage. Among these, we show that Sema4a, which was significantly upregulated in both male mice and humans in the context of altered mood, is necessary for the emergence of emotional dysfunction. Overall, these results place the amygdalo-cingulate pathway at the core of pain and depression comorbidity, and unravel the role of Sema4a and impaired myelination in mood control.

Transcriptomic Studies of Antidepressant Action in Rodent Models of Depression: A First Meta-Analysis.

Antidepressants (ADs) are, for now, the best everyday treatment we have for moderate to severe major depressive episodes (MDEs). ADs are among the most prescribed drugs in the Western Hemisphere; however, the trial-and-error prescription strategy and side-effects leave a lot to be desired. More than 60% of patients suffering from major depression fail to respond to the first AD they are prescribed. For those who respond, full response is only observed after several weeks of treatment. In addition, there are no biomarkers that could help with therapeutic decisions; meanwhile, this is already true in cancer and other fields of medicine. For years, many investigators have been working to decipher the underlying mechanisms of AD response. Here, we provide the first systematic review of animal models. We thoroughly searched all the studies involving rodents, profiling transcriptomic alterations consecutive to AD treatment in naïve animals or in animals subjected to stress-induced models of depression. We have been confronted by an important heterogeneity regarding the drugs and the experimental settings. Thus, we perform a meta-analysis of the AD signature of fluoxetine (FLX) in the hippocampus, the most studied target. Among genes and pathways consistently modulated across species, we identify both old players of AD action and novel transcriptional biomarker candidates that warrant further investigation. We discuss the most prominent transcripts (immediate early genes and activity-dependent synaptic plasticity pathways). We also stress the need for systematic studies of AD action in animal models that span across sex, peripheral and central tissues, and pharmacological classes.

The molecular pathophysiology of mood disorders: From the analysis of single molecular layers to multi-omic integration.

Next-generation sequencing now enables the rapid and affordable production of reliable biological data at multiple molecular levels, collectively referred to as "omics". To maximize the potential for discovery, computational biologists have created and adapted integrative multi-omic analytical methods. When applied to diseases with traceable pathophysiology such as cancer, these new algorithms and statistical approaches have enabled the discovery of clinically relevant molecular mechanisms and biomarkers. In contrast, these methods have been much less applied to the field of molecular psychiatry, although diagnostic and prognostic biomarkers are similarly needed. In the present review, we first briefly summarize main findings from two decades of studies that investigated single molecular processes in relation to mood disorders. Then, we conduct a systematic review of multi-omic strategies that have been proposed and used more recently. We also list databases and types of data available to researchers for future work. Finally, we present the newest methodologies that have been employed for multi-omics integration in other medical fields, and discuss their potential for molecular psychiatry studies.

Immune-Related Genetic Overlap Between Regional Gray Matter Reductions and Psychiatric Symptoms in Adolescents, and Gene-Set Validation in a Translational Model.

Adolescence is a period of vulnerability for the maturation of gray matter (GM) and also for the onset of psychiatric disorders such as major depressive disorder (MDD), bipolar disorder and schizophrenia. Chronic neuroinflammation is considered to play a role in the etiology of these illnesses. However, the involvement of neuroinflammation in the observed link between regional GM volume reductions and psychiatric symptoms is not established yet. Here, we investigated a possible common immune-related genetic link between these two phenomena in european adolescents recruited from the community. Hippocampal and medial prefrontal cortex (mPFC) were defined a priori as regions of interest (ROIs). Their GM volumes were extracted in 1,563 14-year-olds from the IMAGEN database. We found a set of 26 SNPs that correlated with the hippocampal volumes and 29 with the mPFC volumes at age 14. We formed two ROI-Related Immune-gene scores (RRI) with the inflammation SNPs that correlated to hippocampal GM volume and to mPFC GM volume. The predictive ability of both RRIs with regards to the presence of psychiatric symptoms at age 18 was investigated by correlating the RRIs with psychometric questionnaires obtained at age 18. The RRIs (but not control scores constructed with random SNPs) correlated with the presence of depressive symptoms, positive psychotic symptoms, and externalizing symptoms in later adolescence. In addition, the effect of childhood maltreatment, one of the major environmental risk factors for depression and other mental disorders, interacted with the RRI effect. We next sought to validate this finding by investigating our set of inflammatory genes in a translational animal model of early life adversity. Mice were subjected to a protocol of maternal separation at an early post-natal age. We evaluated depressive behaviors in separated and non-separated mice at adolescence and their correlations with the concomitant expression of our genes in whole blood samples. We show that in mice, early life adversity affected the expression of our set of genes in peripheral blood, and that levels of expression correlated with symptoms of negative affect in adolescence. Overall, our translational findings in adolescent mice and humans provide a novel validated gene-set of immune-related genes for further research in the early stages of mood disorders.

Blood cytokines differentiate bipolar disorder and major depressive disorder during a major depressive episode: Initial discovery and independent sample replication.

Bipolar disorder (BD) diagnosis currently relies on assessment of clinical symptoms, mainly retrospective and subject to memory bias. BD is often misdiagnosed as Major Depressive Disorder (MDD) resulting in ineffective treatment and worsened clinical outcome. The primary purpose of this study was to identify blood biomarkers that discriminate MDD from BD patients when in a depressed state. We have used clinical data and serum samples from two independent naturalistic cohorts of patients with a Major Depressive Episode (MDE) who fulfilled the criteria of either BD or MDD at inclusion. The discovery and replication cohorts consisted of 462 and 133 patients respectively. Patients were clinically assessed using standard diagnostic interviews, and clinical variables including current treatments were recorded. Blood was collected and serum assessed for levels of 31 cytokines using a sensitive multiplex assay. A penalized logistic regression model combined with nonparametric bootstrap was subsequently used to identify cytokines associated with BD. Interleukin (IL)-6, IL-10, IL-15, IL-27 and C-X-C ligand chemokine (CXCL)-10 were positively associated with BD in the discovery cohort. Of the five cytokines identified as discriminant features in the discovery cohort, IL-10, IL-15 and IL-27 were also positively associated with BD in the replication cohort therefore providing an external validation to our finding. Should our results be validated in a prospective cohort, they could provide new insights into the pathophysiological mechanisms of mood disorders.

RNA therapeutics for mood disorders: current evidence toward clinical trials.

INTRODUCTION: Mood disorders are severe yet frequent psychiatric disorders worldwide, comprising major depressive disorder (MDD) and bipolar disorders (BD). Their treatment remains poorly effective. Recently, growing evidence for epigenetic mechanisms has emerged. Consequently, a great interest in a novel pharmacological class arose: RNA therapeutics. AREAS COVERED: We conducted a systematic review of RNA therapeutics -antisense oligonucleotides (ASOs), small interfering RNAs (siRNAs), short hairpin RNAs (shRNAs), and micro-RNA (miRNA) therapeutics- for the treatment of mood disorders studied in pre-clinical animal models listed in PubMed, in clinical trials registered in ClinicalTrials.gov and available on the market by combining literature search and Food and Drug Administration and European Medicine Agency online databases. Eighteen pre-clinical studies investigated the antidepressant effects of RNA therapeutics. However, even though there is an increasing number of marketing authorizations and clinical trials for the past twenty years, no RNA therapeutic has reached the clinical development pipeline for the treatment of psychiatric disorders yet. EXPERT OPINION: Several promising RNA therapeutics have been tested in pre-clinical studies for MDD, whereas no molecule has been developed for BD. There are several issues to address before reaching clinical development and new challenges include stratifying patient population and predicting therapeutic response.

miR-323a regulates ERBB4 and is involved in depression.

Major depressive disorder (MDD) is a complex and debilitating illness whose etiology remains unclear. Small RNA molecules, such as micro RNAs (miRNAs) have been implicated in MDD, where they display differential expression in the brain and the periphery. In this study, we quantified miRNA expression by small RNA sequencing in the anterior cingulate cortex and habenula of individuals with MDD and psychiatrically-healthy controls. Thirty-two miRNAs showed significantly correlated expression between the two regions (False Discovery Rate < 0.05), of which four, miR-204-5p, miR-320b, miR-323a-3p, and miR-331-3p, displayed upregulated expression in MDD. We assessed the expression of predicted target genes of differentially expressed miRNAs in the brain, and found that the expression of erb-b2 receptor tyrosine kinase 4 (ERBB4), a gene encoding a neuregulin receptor, was downregulated in both regions, and was influenced by miR-323a-3p in vitro. Finally, we assessed the effects of manipulating miRNA expression in the mouse ACC on anxiety- and depressive-like behaviors. Mice in which miR-323-3p was overexpressed or knocked-down displayed increased and decreased emotionality, respectively. Additionally, these mice displayed significantly downregulated and upregulated expression of Erbb4, respectively. Overall, our findings indicate the importance of brain miRNAs in the pathology of MDD, and emphasize the involvement of miR-323a-3p and ERBB4 in this phenotype. Future studies further characterizing miR-323a-3p and neuregulin signaling in depression are warranted.

GPR56/ADGRG1 is associated with response to antidepressant treatment.

It remains unclear why many patients with depression do not respond to antidepressant treatment. In three cohorts of individuals with depression and treated with serotonin-norepinephrine reuptake inhibitor (N = 424) we show that responders, but not non-responders, display an increase of GPR56 mRNA in the blood. In a small group of subjects we also show that GPR56 is downregulated in the PFC of individuals with depression that died by suicide. In mice, we show that chronic stress-induced Gpr56 downregulation in the blood and prefrontal cortex (PFC), which is accompanied by depression-like behavior, and can be reversed by antidepressant treatment. Gpr56 knockdown in mouse PFC is associated with depressive-like behaviors, executive dysfunction and poor response to antidepressant treatment. GPR56 peptide agonists have antidepressant-like effects and upregulated AKT/GSK3/EIF4 pathways. Our findings uncover a potential role of GPR56 in antidepressant response.

Suicide and suicide behaviors: A review of transcriptomics and multiomics studies in psychiatric disorders.

Aberrant gene expression can contribute to brain and nervous system dysfunction that causes many psychiatric illnesses. Here, we review how transcriptomic approaches have deepened our understanding of the neurobiological underpinnings of psychiatric disorders and how they have to the identification of biomarkers for these disorders, with a focus on their relevance to suicide and suicide behaviors. We begin by providing an overview of the genetic, transcriptomic, and epigenetic factors (including non-coding RNAs) implicated in suicide and their roles in the regulation of gene expression. Then, we highlight the unique benefits and limitations of using either postmortem brain or peripheral tissues in transcriptomic analyses. We examine the current shift from candidate gene to genome-wide approaches in psychiatric research, which are concurrently emerging with the increased consideration of the Research Domain Criteria (RDoC) framework for classifying mental illnesses. Furthermore, we discuss the use of transcription networks and how they can be integrated into multiomic analyses. Finally, we end by highlighting recent findings of peripheral markers of suicide risk identified through the use of transcriptomic tools. Technological advancements and increased accessibility of these technologies are drastically shaping the current research landscape. We present an overview of the significant changes currently taking place to usher in a new era of psychiatric research.

Deficits in Social Behavior Precede Cognitive Decline in Middle-Aged Mice.

An extensive literature details deterioration of multiple brain functions, especially memory and learning, during aging in humans and in rodents. In contrast, the decline of social functions is less well understood. It is presently not clear whether age-dependent deficits observed in social behavior mainly reflect the disruption of social networks activity or are simply secondary to a more general impairment of cognitive and executive functions in older individuals. To address this issue, we carried out a battery of behavioral tasks exploring different brain functions in young (3 months) and middle-aged wild-type mice (9 months). Consistent with previous reports, our results show no obvious differences between these two groups in most of the domains investigated including learning and memory. Surprisingly, in social tasks, middle-aged animals showed significantly reduced levels of interactions when exposed to a new juvenile mouse. In the absence of overt cognitive decline, our findings suggest that social impairments may precede the disruption of other brain functions and argue for a selective vulnerability of social circuits during aging.

Antidepressive effects of targeting ELK-1 signal transduction.

Depression, a devastating psychiatric disorder, is a leading cause of disability worldwide. Current antidepressants address specific symptoms of the disease, but there is vast room for improvement 1 . In this respect, new compounds that act beyond classical antidepressants to target signal transduction pathways governing synaptic plasticity and cellular resilience are highly warranted2-4. The extracellular signal-regulated kinase (ERK) pathway is implicated in mood regulation5-7, but its pleiotropic functions and lack of target specificity prohibit optimal drug development. Here, we identified the transcription factor ELK-1, an ERK downstream partner 8 , as a specific signaling module in the pathophysiology and treatment of depression that can be targeted independently of ERK. ELK1 mRNA was upregulated in postmortem hippocampal tissues from depressed suicides; in blood samples from depressed individuals, failure to reduce ELK1 expression was associated with resistance to treatment. In mice, hippocampal ELK-1 overexpression per se produced depressive behaviors; conversely, the selective inhibition of ELK-1 activation prevented depression-like molecular, plasticity and behavioral states induced by stress. Our work stresses the importance of target selectivity for a successful approach for signal-transduction-based antidepressants, singles out ELK-1 as a depression-relevant transducer downstream of ERK and brings proof-of-concept evidence for the druggability of ELK-1.

Serotonin transporter gene expression predicts the worsening of suicidal ideation and suicide attempts along a long-term follow-up of a Major Depressive Episode.

The quest for biomarkers in suicidal behaviors has been elusive so far, despite their potential utility in clinical practice. One of the most robust biological findings in suicidal behaviors is the alteration of the serotonin transporter function in suicidal individuals. Our main objective was to investigate the predictive value of the serotonin transporter gene expression (SLC6A4) for suicidal ideation and as secondary, for suicide attempts in individuals with a major depressive episode (MDE). A 30-week prospective study was conducted on 148 patients with a MDE and 100 healthy controls including 4 evaluation times (0, 2, 8 and 30 weeks). Blood samples and clinical data were collected and SLC6A4 mRNA levels were measured from peripheral blood mononuclear cells using RT-qPCR. We first demonstrated the stability and reproducibility of SLC6A4 mRNA expression measures over time in healthy controls (F=0.658; p=0.579; η2=0.008; ICC=0.91, 95% CI [0.87-0.94]). Baseline SLC6A4 expression level (OR=0.563 [0.340-0.932], p=0.026) as well as early changes in SLC6A4 expression between baseline and the 2nd week (ß=0.200, p=0.042) predicted the worsening of suicidal ideation (WSI) in the following 8 weeks. Moreover, changes in SLC6A4 expression between the 2nd and 8th weeks predicted the occurrence of a suicide attempt within 30 weeks (OR=10.976 [1.438-83.768], p=0.021). Altogether, the baseline level and the changes in SLC6A4 mRNA expression during a MDE might predict the WSI and the occurrence of suicidal attempts and could be a useful biomarker in clinical practice.

Impaired cortico-limbic functional connectivity in schizophrenia patients during emotion processing.

Functional dysconnection is increasingly recognized as a core pathological feature in schizophrenia. Aberrant interactions between regions of the cortico-limbic circuit may underpin the abnormal emotional processing associated with this illness. We used a functional magnetic resonance imaging (fMRI) paradigm designed to dissociate the various components of the cortico-limbic circuit (i.e. a ventral automatic circuit that is intertwined with a dorsal cognitive circuit), in order to explore bottom-up appraisal as well as top-down control during emotion processing. In schizophrenia patients compared to healthy controls, bottom-up processes were associated with reduced interaction between the amygdala and both the anterior cingulate cortex (ACC) and the dorsolateral prefrontal cortex (DLPFC). Contrariwise, top-down control processes led to stronger connectivity between the ventral affective and the dorsal cognitive circuits, i.e. heightened interactions between the ventral ACC and the DLPFC as well as between dorsal and ventral ACC. These findings offer a comprehensive view of the cortico-limbic dysfunction in schizophrenia. They confirm previous results of impaired propagation of information between the amygdala and the prefrontal cortex and suggest a defective functional segregation in the dorsal cognitive part of the cortico-limbic circuit.

Modeling a linkage between blood transcriptional expression and activity in brain regions to infer the phenotype of schizophrenia patients.

Hundreds of genetic loci participate to schizophrenia liability. It is also known that impaired cerebral connectivity is directly related to the cognitive and affective disturbances in schizophrenia. How genetic susceptibility and brain neural networks interact to specify a pathological phenotype in schizophrenia remains elusive. Imaging genetics, highlighting brain variations, has proven effective to establish links between vulnerability loci and associated clinical traits. As previous imaging genetics works in schizophrenia have essentially focused on structural DNA variants, these findings could be blurred by epigenetic mechanisms taking place during gene expression. We explored the meaningful links between genetic data from peripheral blood tissues on one hand, and regional brain reactivity to emotion task assayed by blood oxygen level-dependent functional magnetic resonance imaging on the other hand, in schizophrenia patients and matched healthy volunteers. We applied Sparse Generalized Canonical Correlation Analysis to identify joint signals between two blocks of variables: (i) the transcriptional expression of 33 candidate genes, and (ii) the blood oxygen level-dependent activity in 16 region of interest. Results suggested that peripheral transcriptional expression is related to brain imaging variations through a sequential pathway, ending with the schizophrenia phenotype. Generalization of such an approach to larger data sets should thus help in outlining the pathways involved in psychiatric illnesses such as schizophrenia. IMAGING: SEARCHING FOR LINKS TO AID DIAGNOSIS: Researchers explore links between the expression of genes associated with schizophrenia in blood cells and variations in brain activity during emotion processing. El Chérif Ibrahim and Eric Fakra at Aix-Marseille Université, France, and colleagues have developed a method to relate the expression levels of 33 schizophrenia susceptibility genes in blood cells and functional magnetic resonance imaging (fMRI) data obtained as individuals carry out a task that triggers emotional responses. Although they found no significant differences in the expression of genes between the 26 patients with schizophrenia and 26 healthy controls they examined, variations in activity in the superior temporal gyrus were strongly linked to schizophrenia-associated gene expression and presence of disease. Similar analyses of larger data sets will shed further light on the relationship between peripheral molecular changes and disease-related behaviors and ultimately, aid the diagnosis of neuropsychiatric disease.

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.