Transcriptional signatures of early-life stress and antidepressant treatment efficacy.

Individuals with a history of early-life stress (ELS) tend to have an altered course of depression and lower treatment response rates. Research suggests that ELS alters brain development, but the molecular changes in the brain following ELS that may mediate altered antidepressant response have not been systematically studied. Sex and gender also impact the risk of depression and treatment response. Here, we leveraged existing RNA sequencing datasets from 1) blood samples from depressed female- and male-identifying patients treated with escitalopram or desvenlafaxine and assessed for treatment response or failure; 2) the nucleus accumbens (NAc) of female and male mice exposed to ELS and/or adult stress; and 3) the NAc of mice after adult stress, antidepressant treatment with imipramine or ketamine, and assessed for treatment response or failure. We find that transcriptomic signatures of adult stress after a history of ELS correspond with transcriptomic signatures of treatment nonresponse, across species and multiple classes of antidepressants. Transcriptomic correspondence with treatment outcome was stronger among females and weaker among males. We next pharmacologically tested these predictions in our mouse model of early-life and adult social defeat stress and treatment with either chronic escitalopram or acute ketamine. Among female mice, the strongest predictor of behavior was an interaction between ELS and ketamine treatment. Among males, however, early experience and treatment were poor predictors of behavior, mirroring our bioinformatic predictions. These studies provide neurobiological evidence for molecular adaptations in the brain related to sex and ELS that contribute to antidepressant treatment response.

Profiling Small RNA From Brain Extracellular Vesicles in Individuals With Depression.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability with significant mortality risk. Despite progress in our understanding of the etiology of MDD, the underlying molecular changes in the brain remain poorly understood. Extracellular vesicles (EVs) are lipid-bound particles that can reflect the molecular signatures of the tissue of origin. We aimed to optimize a streamlined EV isolation protocol from postmortem brain tissue and determine whether EV RNA cargo, particularly microRNAs (miRNAs), have an MDD-specific profile. METHODS: EVs were isolated from postmortem human brain tissue. Quality was assessed using western blots, transmission electron microscopy, and microfluidic resistive pulse sensing. EV RNA was extracted and sequenced on Illumina platforms. Functional follow-up was performed in silico. RESULTS: Quality assessment showed an enrichment of EV markers, as well as a size distribution of 30 to 200 nm in diameter, and no contamination with cellular debris. Small RNA profiling indicated the presence of several RNA biotypes, with miRNAs and transfer RNAs being the most prominent. Exploring miRNA levels between groups revealed decreased expression of miR-92a-3p and miR-129-5p, which was validated by qPCR and was specific to EVs and not seen in bulk tissue. Finally, in silico functional analyses indicate potential roles for these 2 miRNAs in neurotransmission and synaptic plasticity. CONCLUSION: We provide a streamlined isolation protocol that yields EVs of high quality that are suitable for molecular follow-up. Our findings warrant future investigations into brain EV miRNA dysregulation in MDD.

Integrative Genetic Variation, DNA Methylation, and Gene Expression Analysis of Escitalopram and Aripiprazole Treatment Outcomes in Depression: A CAN-BIND-1 Study.

INTRODUCTION: Little is known about the interplay between genetics and epigenetics on antidepressant treatment (1) response and remission, (2) side effects, and (3) serum levels. This study explored the relationship among single nucleotide polymorphisms (SNPs), DNA methylation (DNAm), and mRNA levels of four pharmacokinetic genes, CYP2C19, CYP2D6, CYP3A4, and ABCB1, and its effect on these outcomes. METHODS: The Canadian Biomarker Integration Network for Depression-1 dataset consisted of 177 individuals with major depressive disorder treated for 8 weeks with escitalopram (ESC) followed by 8 weeks with ESC monotherapy or augmentation with aripiprazole. DNAm quantitative trait loci (mQTL), identified by SNP-CpG associations between 20 SNPs and 60 CpG sites in whole blood, were tested for associations with our outcomes, followed by causal inference tests (CITs) to identify methylation-mediated genetic effects. RESULTS: Eleven cis-SNP-CpG pairs (q<0.05) constituting four unique SNPs were identified. Although no significant associations were observed between mQTLs and response/remission, CYP2C19 rs4244285 was associated with treatment-related weight gain (q=0.027) and serum concentrations of ESCadj (q<0.001). Between weeks 2-4, 6.7% and 14.9% of those with *1/*1 (normal metabolizers) and *1/*2 (intermediate metabolizers) genotypes, respectively, reported ≥2 lbs of weight gain. In contrast, the *2/*2 genotype (poor metabolizers) did not report weight gain during this period and demonstrated the highest ESCadj concentrations. CITs did not indicate that these effects were epigenetically mediated. DISCUSSION: These results elucidate functional mechanisms underlying the established associations between CYP2C19 rs4244285 and ESC pharmacokinetics. This mQTL SNP as a marker for antidepressant-related weight gain needs to be further explored.

DNA Methylation Signatures of Functional Somatic Syndromes: Systematic Review.

OBJECTIVE: Functional somatic syndromes (FSS) are highly prevalent across all levels of health care. The fact that they are characterized by medically unexplained symptoms, such as fatigue and pain, raises the important question of their underlying pathophysiology. Psychosocial stress represents a significant factor in the development of FSS and can induce long-term modifications at the epigenetic level. The aim of this review was to systematically review, for the first time, whether individuals with FSS are characterized by specific alterations in DNA methylation. METHODS: MEDLINE and PsycINFO were searched from the first available date to September 2022. The inclusion criteria were as follows: a) adults fulfilling the research diagnostic criteria for chronic fatigue syndrome, fibromyalgia syndrome, and/or irritable bowel syndrome; b) healthy control group; and c) candidate-gene or genome-wide study of DNA methylation. RESULTS: Sixteen studies ( N = 957) were included. In candidate-gene studies, specific sites within NR3C1 were identified, which were hypomethylated in individuals with chronic fatigue syndrome compared with healthy controls. In genome-wide studies in chronic fatigue syndrome, a hypomethylated site located to LY86 and hypermethylated sites within HLA-DQB1 were found. In genome-wide studies in fibromyalgia syndrome, differential methylation in sites related to HDAC4 , TMEM44 , KCNQ1 , SLC17A9 , PRKG1 , ALPK3 , TFAP2A , and LY6G5C was found. CONCLUSIONS: Individuals with chronic fatigue syndrome and fibromyalgia syndrome seem to be characterized by altered DNA methylation of genes regulating cellular signaling and immune functioning. In chronic fatigue syndrome, there is preliminary evidence for these to be implicated in key pathophysiological alterations, such as hypocortisolism and low-grade inflammation, and to contribute to the debilitating symptoms these individuals experience. PREREGISTRATION: PROSPERO identifier: CRD42022364720.

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.

Neuron-derived extracellular vesicles enriched from plasma show altered size and miRNA cargo as a function of antidepressant drug response.

Previous work has demonstrated that microRNAs (miRNAs) change as a function of antidepressant treatment (ADT) response. However, it is unclear how representative these peripherally detected miRNA changes are to those occurring in the brain. This study aimed to use peripherally extracted neuron-derived extracellular vesicles (NDEV) to circumvent these limitations and investigate neuronal miRNA changes associated with antidepressant response. Samples were collected at two time points (baseline and after 8 weeks of follow-up) from depressed patients who responded (N = 20) and did not respond (N = 20) to escitalopram treatment, as well as controls (N = 20). Total extracellular vesicles (EVs) were extracted from plasma, and then further enriched for NDEV by immunoprecipitation with L1CAM. EVs and NDEVs were characterized, and NDEV miRNA cargo was extracted and sequenced. Subsequently, studies in cell lines and postmortem tissue were conducted. Characterization of NDEVs revealed that they were smaller than other EVs isolated from plasma (p < 0.0001), had brain-specific neuronal markers, and contained miRNAs enriched for brain functions (p < 0.0001) Furthermore, NDEVs from depressed patients were smaller than controls (p < 0.05), and NDEV size increased with ADT response (p < 0.01). Finally, changes in NDEV cargo, specifically changes in miR-21-5p, miR-30d-5p, and miR-486-5p together (p < 0.01), were associated with ADT response. Targets of these three miRNAs were altered in brain tissue from depressed individuals (p < 0.05). Together, this study indicates that changes in peripherally isolated NDEV can act as both a clinically accessible and informative biomarker of ADT response specifically through size and cargo.

Machine Learning Analysis of Blood microRNA Data in Major Depression: A Case-Control Study for Biomarker Discovery.

BACKGROUND: There is a lack of reliable biomarkers for major depressive disorder (MDD) in clinical practice. However, several studies have shown an association between alterations in microRNA levels and MDD, albeit none of them has taken advantage of machine learning (ML). METHOD: Supervised and unsupervised ML were applied to blood microRNA expression profiles from a MDD case-control dataset (n = 168) to distinguish between (1) case vs control status, (2) MDD severity levels defined based on the Montgomery-Asberg Depression Rating Scale, and (3) antidepressant responders vs nonresponders. RESULTS: MDD cases were distinguishable from healthy controls with an area-under-the receiver-operating characteristic curve (AUC) of 0.97 on testing data. High- vs low-severity cases were distinguishable with an AUC of 0.63. Unsupervised clustering of patients, before supervised ML analysis of each cluster for MDD severity, improved the performance of the classifiers (AUC of 0.70 for cluster 1 and 0.76 for cluster 2). Antidepressant responders could not be successfully separated from nonresponders, even after patient stratification by unsupervised clustering. However, permutation testing of the top microRNA, identified by the ML model trained to distinguish responders vs nonresponders in each of the 2 clusters, showed an association with antidepressant response. Each of these microRNA markers was only significant when comparing responders vs nonresponders of the corresponding cluster, but not using the heterogeneous unclustered patient set. CONCLUSIONS: Supervised and unsupervised ML analysis of microRNA may lead to robust biomarkers for monitoring clinical evolution and for more timely assessment of treatment in MDD patients.

Association Between Side Effects and Blood microRNA Expression Levels and Their Targeted Pathways in Patients With Major Depressive Disorder Treated by a Selective Serotonin Reuptake Inhibitor, Escitalopram: A CAN-BIND-1 Report.

INTRODUCTION: Antidepressant drugs are effective therapies for major depressive disorder; however, they are frequently associated with side effects. Although there is some evidence for a relationship between genetic variation and side effects, little is known regarding the role of dynamic molecular factors as moderators of side effects. The aim of this study was to assess microRNA (miRNA) changes associated with side effects during escitalopram treatment and their downstream effects on target gene expression. METHODS: A total 160 patients with major depressive disorder from the CAN-BIND-1 cohort were included. Side effects were assessed with the Toronto Side Effect Scale after 2 weeks of treatment with escitalopram. We assessed the relationship between side effects and changes in peripheral expression of miRNAs between baseline and week 2. For miRNA whose expression changed, we used target prediction algorithms to identify putative messenger RNA (mRNA) targets and assessed their expression. RESULTS: Nausea was experienced by 42.5% of patients. We identified 45 miRNAs whose expression changed on initiation of escitalopram treatment, of which 10 displayed a negative association with intensity of nausea (miR15b-5p, miR17-5p, miR20a-5p, miR20b-5p, miR103a-3p, miR103b, miR106a-5p, miR182-5p, miR185-5p, and miR660-5p). Additionally, we found negative associations between 4 microRNAs (miR20a-5p, miR106a-5p, miR185-5p, miR660-5p) and mRNA targets. The expression of the miR185-5p target, CAMK2δ was significantly decreased [log 2 mean = -0.048 (0.233)] between weeks 0 and 2 (P = .01)]. CONCLUSIONS: We identified an overexpression of miR185-5p during escitalopram treatment of major depressive disorder, which was negatively associated with intensity of nausea, and identified a potential mRNA target that may mediate this effect.

Investigation of miR-1202, miR-135a, and miR-16 in Major Depressive Disorder and Antidepressant Response.

Background: Major depressive disorder is a debilitating illness, which is most commonly treated with antidepressant drugs. As the majority of patients do not respond on their first trial, there is great interest in identifying biological factors that indicate the most appropriate treatment for each patient. Studies suggest that microRNA represent excellent biomarkers to predict antidepressant response. Methods: We investigated the expression of miR-1202, miR-135a, and miR-16 in peripheral blood from 2 cohorts of depressed patients who received 8 weeks of antidepressant therapy. Expression was quantified at baseline and after treatment, and its relationship to treatment response and depressive symptoms was assessed. Results: In both cohorts, responders displayed lower baseline miR-1202 levels compared with nonresponders, which increased following treatment. Conclusions: Ultimately, our results support the involvement of microRNA in antidepressant response and suggest that quantification of their levels in peripheral samples represents a valid approach to informing treatment decisions.

Regulatory role of miRNAs in polyamine gene expression in the prefrontal cortex of depressed suicide completers.

MicroRNAs (miRNAs) are small, non-coding RNA molecules that play an important role in the post-transcriptional regulation of mRNA. These molecules have been the subject of growing interest as they are believed to control the regulation of a large number of genes, including those expressed in the brain. Evidence suggests that miRNAs could be involved in the pathogenesis of neuropsychiatric disorders. Alterations in metabolic enzymes of the polyamine system have been reported to play a role in predisposition to suicidal behaviour. We have previously shown the expression of the polyamine genes SAT1 and SMOX to be down-regulated in the brains of suicide completers. In this study, we hypothesized that the dysregulation of these genes in depressed suicide completers could be influenced by miRNA post-transcriptional regulation. Using a stringent target prediction analysis, we identified several miRNAs that target the 3'UTR of SAT1 and SMOX. We profiled the expression of 10 miRNAs in the prefrontal cortex (BA44) of suicide completers (N = 15) and controls (N = 16) using qRT-PCR. We found that several miRNAs showed significant up-regulation in the prefrontal cortex of suicide completers compared to psychiatric healthy controls. Furthermore, we demonstrated a significant correlation between these miRNAs and the expression levels of both SAT1 and SMOX. Our results suggest a relationship between miRNAs and polyamine gene expression in the suicide brain, and postulate a mechanism for SAT1 and SMOX down-regulation by post-transcriptional activity of miRNAs.

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.

Relation of hippocampal volume and SGK1 gene expression to treatment remission in major depression is moderated by childhood maltreatment: A CAN-BIND-1 report.

Preclinical research implicates stress-induced upregulation of the enzyme, serum- and glucocorticoid-regulated kinase 1 (SGK1), in reduced hippocampal volume. In the current study, we tested the hypothesis that greater SGK1 mRNA expression in humans would be associated with lower hippocampal volume, but only among those with a history of prolonged stress exposure, operationalized as childhood maltreatment (physical, sexual, and/or emotional abuse). Further, we examined whether baseline levels of SGK1 and hippocampal volume, or changes in these markers over the course of antidepressant treatment, would predict treatment outcomes in adults with major depression [MDD]. We assessed SGK1 mRNA expression from peripheral blood, and left and right hippocampal volume at baseline, as well as change in these markers over the first 8 weeks of a 16-week open-label trial of escitalopram as part of the Canadian Biomarker Integration Network in Depression program (MDD [n = 161] and healthy comparison participants [n = 91]). Childhood maltreatment was assessed via contextual interview with standardized ratings. In the full sample at baseline, greater SGK1 expression was associated with lower hippocampal volume, but only among those with more severe childhood maltreatment. In individuals with MDD, decreases in SGK1 expression predicted lower remission rates at week 16, again only among those with more severe maltreatment. Decreases in hippocampal volume predicted lower week 16 remission for those with low childhood maltreatment. These results suggest that both glucocorticoid-related neurobiological mechanisms of the stress response and history of childhood stress exposure may be critical to understanding differential treatment outcomes in MDD. ClinicalTrials.gov: NCT01655706 Canadian Biomarker Integration Network for Depression Study.

Multi-omic modeling of antidepressant response implicates dynamic immune and inflammatory changes in individuals who respond to treatment.

BACKGROUND: Major depressive disorder (MDD) is a leading cause of disability worldwide, and is commonly treated with antidepressant drugs (AD). Although effective, many patients fail to respond to AD treatment, and accordingly identifying factors that can predict AD response would greatly improve treatment outcomes. In this study, we developed a machine learning tool to integrate multi-omic datasets (gene expression, DNA methylation, and genotyping) to identify biomarker profiles associated with AD response in a cohort of individuals with MDD. MATERIALS AND METHODS: Individuals with MDD (N = 111) were treated for 8 weeks with antidepressants and were separated into responders and non-responders based on the Montgomery-Åsberg Depression Rating Scale (MADRS). Using peripheral blood samples, we performed RNA-sequencing, assessed DNA methylation using the Illumina EPIC array, and performed genotyping using the Illumina PsychArray. To address this rich multi-omic dataset with high dimensional features, we developed integrative Geneset-Embedded non-negative Matrix factorization (iGEM), a non-negative matrix factorization (NMF) based model, supplemented with auxiliary information regarding gene sets and gene-methylation relationships. In particular, we factorize the subjects by features (i.e., gene expression or DNA methylation) into subjects-by-factors and factors-by-features. We define the factors as the meta-phenotypes as they represent integrated composite scores of the molecular measurements for each subject. RESULTS: Using our model, we identified a number of meta-phenotypes which were related to AD response. By integrating geneset information into the model, we were able to relate these meta-phenotypes to biological processes, including a meta-phenotype related to immune and inflammatory functions as well as other genes related to depression or AD response. The meta-phenotype identified several genes including immune interleukin 1 receptor like 1 (IL1RL1) and interleukin 5 receptor (IL5) subunit alpha (IL5RA), AKT/PIK3 pathway related phosphoinositide-3-kinase regulatory subunit 6 (PIK3R6), and sphingomyelin phosphodiesterase 3 (SMPD3), which has been identified as a target of AD treatment. CONCLUSIONS: The derived meta-phenotypes and associated biological functions represent both biomarkers to predict response, as well as potential new treatment targets. Our method is applicable to other diseases with multi-omic data, and the software is open source and available on Github (https://github.com/li-lab-mcgill/iGEM).

Cell type specific transcriptomic differences in depression show similar patterns between males and females but implicate distinct cell types and genes.

Major depressive disorder (MDD) is a common, heterogenous, and potentially serious psychiatric illness. Diverse brain cell types have been implicated in MDD etiology. Significant sexual differences exist in MDD clinical presentation and outcome, and recent evidence suggests different molecular bases for male and female MDD. We evaluated over 160,000 nuclei from 71 female and male donors, leveraging new and pre-existing single-nucleus RNA-sequencing data from the dorsolateral prefrontal cortex. Cell type specific transcriptome-wide threshold-free MDD-associated gene expression patterns were similar between the sexes, but significant differentially expressed genes (DEGs) diverged. Among 7 broad cell types and 41 clusters evaluated, microglia and parvalbumin interneurons contributed the most DEGs in females, while deep layer excitatory neurons, astrocytes, and oligodendrocyte precursors were the major contributors in males. Further, the Mic1 cluster with 38% of female DEGs and the ExN10_L46 cluster with 53% of male DEGs, stood out in the meta-analysis of both sexes.

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.

Broadening our horizons: gene expression profiling to help better understand the neurobiology of suicide and depression.

The complexity of the neurobiological alterations underlying major depression and suicide is significant. Gene expression studies using high-throughput genomic technologies have provided important insight into novel genes and pathways displaying alterations associated with major depression and suicide, thereby providing a global view of the pathological changes taking place, as well as indicating potential new targets for therapeutic interventions. This review discusses the methodologies which have been used to profile gene expression patterns in depression and suicide, as well as examines several of the metabolic pathways which have been frequently implicated by studies using this approach. Future directions to be taken towards increasing our understanding of the origin and downstream effects of altered gene expression are also discussed.

Effects of histone modifications on increased expression of polyamine biosynthetic genes in suicide.

Altered polyamine metabolism has been consistently observed as underlying the suicide process. We recently performed a global analysis of polyamine gene expression across the brains of suicide completers, and identified up-regulation of four genes, arginase II (ARG2), S-adenosylmethionine decarboxylase (AMD1), and antizymes 1 and 2 (OAZ1 and OAZ2), which play essential roles in polyamine biosynthesis. To determine if a shared epigenetic mechanism is involved in their overexpression in the prefrontal cortex, we measured promoter levels of tri-methyl modified histone-3-lysine-4 (H3K4me3), a marker of open chromatin, and assessed its association with suicide and gene expression. We identified increased H3K4me3 in the promoter region of OAZ1 in suicide, and found that H3K4me3 was correlated with the expression of OAZ1 and ARG2. Overall, our findings indicate that the H3K4me3 modification plays an important role in the regulation of polyamine biosynthesis, and that this mechanism may be involved in the neurobiology of suicide.

Oxytocin receptor expression and epigenetic regulation in the anterior cingulate cortex of individuals with a history of severe childhood abuse.

Childhood abuse significantly increases the lifetime risk of negative mental health outcomes. The oxytocinergic system, which plays a role in complex social and emotional behaviors, has been shown to be sensitive to early-life experiences. While previous studies have investigated the relationship between early-life adversity and oxytocin, they did so with peripheral samples. We, therefore, aimed to characterize the relationship between early-life adversity and oxytocin receptor (OXTR) expression in the brain, using post-mortem human samples, as well as a rodent model of naturally occurring variation in early-life environment. Focusing on the dorsal anterior cingulate cortex, we compared OXTR expression and epigenetic regulation between MDD suicides with (N = 26) and without history of childhood abuse (N = 24), as well as psychiatrically healthy controls (N = 23). We also compared Oxtr expression in the cingulate cortex of adult rats raised by dams displaying high (N = 13) and low levels (N = 12) of licking and grooming (LG) behavior. Overall, our results indicate that childhood abuse associates with an upregulation of OXTR expression, and that similarly, this relationship is also observed in the cingulate cortex of adult rats raised by low-LG dams. Additionally, we found an effect of rs53576 genotype on expression, showing that carriers of the A variant also show upregulated OXTR expression. The effects of early-life adversity and rs53576 genotype on OXTR expression are, however, not explained by differences in DNA methylation within and around the MT region of the OXTR gene.

Global gene expression profiling of the polyamine system in suicide completers.

In recent years, gene expression, genetic association, and metabolic studies have implicated the polyamine system in psychiatric conditions, including suicide. Given the extensive regulation of genes involved in polyamine metabolism, as well as their interconnections with the metabolism of other amino acids, we were interested in further investigating the expression of polyamine-related genes across the brain in order to obtain a more comprehensive view of the dysregulation of this system in suicide. To this end, we examined the expression of genes related to polyamine metabolism across 22 brain regions in a sample of 29 mood-disordered suicide completers and 16 controls, and identified 14 genes displaying differential expression. Among these, altered expression of spermidine/spermine N1-acetyltransferase, spermine oxidase, and spermine synthase, has previously been observed in brains of suicide completers, while the remainder of the genes represent novel findings. In addition to genes with direct involvement in polyamine metabolism, including S-adenosylmethionine decarboxylase, ornithine decarboxylase antizymes 1 and 2, and arginase II, we identified altered expression of several more distally related genes, including aldehyde dehydrogenase 3 family, member A2, brain creatine kinase, mitochondrial creatine kinase 1, glycine amidinotransferase, glutamic-oxaloacetic transaminase 1, and arginyl-tRNA synthetase-like. Many of these genes displayed altered expression across several brain regions, strongly implying that dysregulated polyamine metabolism is a widespread phenomenon in the brains of suicide completers. This study provides a broader view of the nature and extent of the dysregulation of the polyamine system in suicide, and highlights the importance of this system in the neurobiology of suicide.