Skip to main content
NCBI home page
NIHPA Author Manuscripts logoLink to NIHPA Author Manuscripts
. Author manuscript; available in PMC: 2021 Nov 2.
Published in final edited form as: J Neurosci Res. 2020 Sep 11;98(12):2541–2553. doi: 10.1002/jnr.24724

Sex-specific peripheral and central responses to stress-induced depression and treatment in a mouse model

Kristina Deonaraine 1, Qian Wang 2,3,4, Haoxiang Cheng 2, Kenny L Chan 1, Hsiao-yun Lin 1, Kalena Liu 5, Lyonna F Parise 1, Flurin Cathomas 1, Katherine B Leclair 1, Meghan E Flanigan 1, Long Li 1, Hossein Aleyasin 1, Christopher Guevara 1, Ke Hao 2, Bin Zhang 2,3,4, Scott J Russo 1, Jun Wang 5,6
PMCID: PMC8561614  NIHMSID: NIHMS1740330  PMID: 32918293

Abstract

Major depressive disorder (MDD) affects ~20% of the world population and is characterized by strong sexual dimorphism with females being 2–3 times more likely to develop this disorder. Previously, we demonstrated that a combination therapy with dihydrocaffeic acid (DHCA) and malvidin-glucoside (Mal-gluc) to synergistically target peripheral inflammation and stress-induced synaptic maladaptation in the brain was effective in alleviating chronic social defeat stress (CSDS)-induced depression-like phenotype in male mice. Here, we test the combination therapy in a female CSDS model for depression and compared sex-specific responses to stress in the periphery and the central nervous system. Similar to male mice, the combination treatment is also effective in promoting resilience against the CSDS-induced depression-like behavior in female mice. However, there are sex-specific differences in peripheral immune responses and differential gene regulation in the prefrontal cortex to chronic stress and to the treatment. These data indicate that while therapeutic approaches to combat stress-related disorders may be effective in both sexes, the mechanisms underlying these effects differ, emphasizing the need for inclusion of both sexes in preclinical studies using animal models.

Introduction

The World Health Organization (WHO) estimates, as of 2017, that 322 million people worldwide are affected by Major Depressive Disorder (MDD), and the prevalence of this severe mood disorder is on the rise 1. Despite the broad use of antidepressants, they exhibit limited efficacy and can produce undesirable side effects 2. Although newer antidepressants have been developed such as monoamine reuptake inhibitors, including selective serotonin reuptake inhibitors (SSRIs) and selective serotonin and norepinephrine reuptake inhibitors (SNRIs), the therapeutic efficacy has not improved 3. Moreover, antidepressants must be administered for weeks to months before any clinical benefit is noted 3. Thus, there is an urgent need for the development of new classes of antidepressants.

A vast literature documents the strong sexual dimorphism seen in depression and related stress disorders. Epidemiologic studies of depression consistently show sex differences in prevalence rates with depression being two to three times as common in women as in men 4–7. When compared to men diagnosed with depression, women report more frequent symptoms and greater symptoms severity 6,8,9. Given the differences in the presentation, coping strategies and responses to stress and to treatment 6,7,8,9,4,10, further investigation into the biological mechanisms modulating these pathways in males and females is warranted.

Depression is a multifaceted disease, the etiology of which is believed to be a combination of interactions between genetic and environmental elements. Depression carries genetic risks, although the search for specific genes responsible for its manifestation and the consensus on contributing genes are still unfolding 11,12. Non-genetic risk factors including stressful life events and physical and emotional trauma are implicated in the etiology of depression. Recently, dysregulation of immune response has also been linked to depression. While it is unclear whether inflammation can be a causative agent, several studies support the theory that it plays a contributing role in the development of depression in a subset of patients 13–15. Leukocyte elevation has been observed in patients with depression, possibly explaining the increases in pro-inflammatory circulating cytokines such as tumor necrosis factor-α (TNF-α), IL-1β, and IL-6 detected in this patient population 13,14. Two recent meta-analyses found significantly increased peripheral TNF-α and IL-6 levels in MDD patients when compared to healthy controls 13,16. Investigations into IL-6 suggest it can cross the blood-brain barrier (BBB) and may have some influence on the modulation of microglia and other central nervous system (CNS) immune cells, and perhaps even some role in neuronal plasticity 17,18. Stress-induced structural and functional changes of synaptic plasticity have been reported in the hippocampus 19–22, the prefrontal cortex (PFC) 23–26 and subcortical limbic structures such as the amygdala and nucleus accumbens (NAc) 27–32 in various animal models of stress. In humans, reduced volume in select brain regions are observed in patients with MDD 33–35 and select depression phenotypes such as anhedonia are correlated with a reduction in NAc volume and its response to reward stimuli 36,37.

Both peripheral inflammation and synaptic function play an important role in the pathogenesis of depression. We initiated a high throughput in vitro drug screening study and identified two phytochemicals: Dihydrocaffeic acid (DHCA) can reduce IL-6 generations and malvidin-3-O-glucoside (Mal-gluc) can modulate synaptic plasticity 38. We hypothesized that simultaneously targeting both mechanisms may increase the likelihood of efficacy. Because of the lack of female defeat stress model, in previous studies, we only tested these two compounds in male mice and found that DHCA/Mal-gluc promote resilience against depression-like behaviors in following chronic social defeat stress (CSDS). We found that the two phytochemicals exert their anti-depressant activity through inhibition of peripheral inflammation and prevention of stress-induced synaptic modifications in the brain 38. Given the aforementioned sex differences in depression, in this study, we tested the effect of DHCA/Mal-gluc using a recently developed female model of CSDS 39 and compared the responses to stress and treatment in the periphery as well as the CNS with male mice.

Materials and Methods

Animals and treatment:

Seven-week-old female C57BL/6 (The Jacksons Laboratory) were randomly assigned to one of the four groups: vehicle treatment without exposure to CSDS, DHCA/Mal-gluc treatment without exposure to CSDS, vehicle treatment with exposure to CSDS, and DHCA/Mal-gluc treatment with exposure to CSDS. DHCA (5mg/kg-BW/day, Sigma-Aldrich) and Mal-gluc (0.5μg/kg-BW/day, Extrasynthese, Genay Cedex, France) were administered through their drinking water for 14 days prior to the CSDS and throughout CSDS. All animals had access to regular chow ad lib and were maintained on a 12:12-h light/dark cycle with lights on at 07:00 h in a temperature-controlled (20 ± 2 °C) vivarium. All procedures were approved by the Institutional Animal Care and Use Committee.

Generation of male aggressors for female CSDS:

Male aggressors were generated by breeding homozygous Esr1 (ERa)-Cre males on a C57BL/6J background (The Jackson Laboratory, Bar Harbor, Maine) with wild type CD-1 females (Charles River Laboratories) 39. This breeding strategy ensured that all F1 inherited heterozygous Esr1-Cre alleles that was confirmed by random genotyping of the offspring.

Viral surgery for DREADD expression in male aggressors for female CSDS:

Three to four months old heterozygous Esr1-Cre male mice were anesthetized with intraperitoneal (i.p.) injection of ketamine HCl (100 mg/kg) and xylazine (10 mg/kg). The head was shaved and an incision was made down the midline of the head to expose the skull. The AAV vector encoding AAV2/hSyn-DIO-hM3D(Gq)-Cherry (Gq-DREADD; University of North Carolina, Chapel Hill, NC) was bilaterally injected into the ventromedial hypothalamus (VMHvl) at coordinates (AP, −1.5; ML, ± 0.7; DV, −5.7 mm from bregma) at a controlled rate of 0.3 μl/3 minutes per side 39. Following injection, the needle remained in the targeted brain area for 5 minutes and then was withdrawn slowly to reduce backflow. Mice were then returned to their home cage following the surgery for 4 weeks to allow for recovery and expression of the virus.

Aggressor screening and selection for female CSDS:

One month after surgery, the F1 heterozygous Esr1-Cre male mice with Gq-DREADD viral injection were screened for aggressiveness toward female mice after chemogenetic stimulation. Specifically, the F1 males were i.p. injected with 1.0 mg/kg clozapine-N-oxide (CNO) thirty minutes before screening on each screening day to activate DREADDs expressed in VMHvl neurons. One 7-week old female C57BL/6J “screener” was introduced into the aggressor’s home cage for 3 minutes. The aggressor’s attack latency was recorded each day for 3 consecutive days. Aggressors that demonstrated aggressive behavior during the 3 minutes of intrusion for at least 2 out of the 3 screening days were deemed aggressive and were used for subsequent social defeat experiments. Aggressors that did not demonstrate aggressiveness following CNO injection were used as target mice during social interaction experiments.

CSDS protocol for female defeat:

The female CSDS protocol recently established by our lab was used for this experiment 39. Briefly, the aggressors were i.p. injected with 1.0 mg/kg CNO thirty minutes before initiation of the social defeat bout. Each defeat bout was carried out for 5 minutes over 10 consecutive days, where the vehicle or DHCA/Mal-gluc treated females were introduced into the home cage of a novel aggressor each day. If the male aggressor did not initiate aggressive behavior or initiated sexual behavior toward the intruder during the 5-minute encounter, the intruder female was removed and then introduced into the home cage of another novel aggressor. During the 10-day protocol, each female encountered a novel male aggressor to avoid habituation. All females were returned to their home cage with cage mates (4–5 females per cage) following each defeat bout and remained group-housed in their home cage following the last defeat day.

CSDS protocol for male defeat:

CSDS was performed as previously described 65, 68. CD-1 mice were screened for aggressive characteristics prior to the start of social defeat experiments based on previously described criteria 65, and housed within the social defeat cage (26.7w × 48.3d × 15.2h cm; Allentown Inc) 24 hours prior to the start of defeats on one side of a clear, perforated Plexiglass divider (0.6 × 45.7 × 15.2 cm; Nationwide Plastics). Briefly, male C57BL/6 mice subjected to CSDS were exposed to a novel CD-1 aggressor mouse for 10 minutes once per day, over 10 consecutive days. Following the 10 minutes of interaction, the experimental mice were removed to the opposite side of the social defeat cage and allowed sensory contact with the CD-1 during the following 24 hour period. Control mice without CSDS were housed two mice per cage, on opposite sides of the perforated divider, rotated daily in a manner similar to the defeat group, but never exposed to aggressive CD-1 mice.

Social interaction (SI) test

Twenty-four hours after the last defeat, the SI test was performed in all mice. The SI test was completed in a red-light cubicle containing an open field. The defeated mice were habituated to the SI room outside of the SI cubicles for 1 hour prior to testing. Non-aggressive F1 that had never encountered the defeated mice were used as social targets. The SI protocol consisted of a control and an experimental session. In the control session of the SI test, the test mouse was placed in the center of an open field (42cm (w) × 42 cm (d) × 42cm (h)) with an small empty wire enclosure (10cm (w) × 6.5 cm (d) × 42 cm (h)) within the interaction zone (8 cm wide corridor surrounding the social target) on one side of the open field. The mouse was allowed 150 seconds to explore. The experimental sessions of the SI test were conducted in a similar manner but with a non-aggressive F1 social target mouse placed in the wire enclosure. The mouse’s exploratory behavior was recorded by a CCD camera located above the open field. Video-tracked behaviors were analyzed using Ethovision 3.0 (Noldus Information Technology). Mice were returned to their home cages following the SI test and the open field and wire enclosures were cleaned after each trial. The SI ratio of the mouse was determined by dividing the time spent in the interaction zone with the social target present by the time spent in the same zone without a social target. Mice with an SI ratio greater than 1 were classified as resilient and socially interactive, whereas mice with an SI ratio less than 1 were deemed susceptible and socially avoidant.

Sampling of whole blood following defeat and brain tissue collection upon sacrificing

Eighteen hours after the first bout of defeat, blood samples from all mice were collected via the submandibular vein into heparin-lithium coated tubes (Eppendorf). Blood was centrifuged for 10 minutes at 375 × g at 4°C. Plasma was collected and stored at −80°C until analysis. Upon sacrificing, mouse brains were removed and punches of the PFC were collected, snap frozen, and stored at −80 °C until further processing.

Plasma cytokine measurement

Plasma cytokines were measured using the Multiplex MAP Mouse Cytokine/Chemokine Magnetic Bead Panel (EMD Millipore) as previously described 38. Specifically, plasma samples were incubated with multiplex MAP magnetic beads at 4 °C overnight, washed twice and incubated with detection antibodies for 1 hour at room temperature followed by a 30-minute incubation with streptavidin-phycoerythrin. The samples were washed twice and subjected to the Luminex® 200™ assessments.

RNA isolation, RNA-seq and qRT-PCR

Total RNA from the PFC punches were isolated using the RNeasy Mini Kit (Qiagen, Valencia, CA). All RNA preparations were confirmed with integrity numbers >8.0 by a Bioanalyzer before proceeding to library construction. Libraries were created from pooled mRNA samples (n=3–4 mice/library and 4–5 libraries per test condition). Library construction (LncRNA library, Ribo-Zero), quality assessment and Illumina Novaseq 6000 with 150-pb paired-end reads were conducted by Novogene. The same RNA samples were reverse transcribed and subjected to real-time qRT-PCR as previously described 38.

RNA-seq data analysis and bioinformatics

Quality control was carried out on the raw sequence data coming from the sequencer using the FastQC software 40. This assesses total sequence, reads flagged as low quality, read length, GC content, per base and per tile quality, per sequence quality score, per base content distribution, per sequence GC content, per base N content, sequence length distribution, sequence duplication levels, overrepresented sequence, adaptor content, and Kmer content. Reads of universal low base quality were discarded, and reads with certain low quantity bases were trimmed. Following QC, RNA reads were mapped to mouse reference genome (mm10) with STAR aligner 41. Gene-level read counts in every gene model and all exons were derived using STAR. We removed genes or exons that were not expressed in any sample, where we define expression as at least 20 mapped reads in the entire data set. Read counts within samples and between samples were then normalized using the edgeR R-package 42. Limma model 43 was used to examine the differential expression level (log-transformed) between groups.

Gene Ontology (GO) analysis

GO analyses were performed on differentially expressed genes (DEGs) from different contrasts by using Fisher’s Exact Test (FET) with Benjamini-Hochberg (BH) correction. The annotated genes in the GO biological process were considered as the background. The enriched GO terms with BH-corrected FET p value <0.05 were considered statistically significant.

Power analysis and overall statistics

Group size calculation was based on our previous neurobehavioral studies, employing social avoidance test. Power calculation found that 12 mice/group will have 90% statistical power to detect 25% (0.32 Log2) fold change. All values are expressed as mean and standard deviation (SD). For behavioral (SI) test as well as biochemical analyses comparing control group vs. test group, two-way ANOVAs or one-way ANOVA followed by Post Hoc Bonferroni multiple comparisons. In all studies, outliers (2 SD from the mean) were excluded and the null hypothesis was rejected at the 0.05 level. All statistical analyses were performed using Prism 6 (GraphPad Software, San Diego CA).

Results

DHCA/Mal-gluc treatment promotes resilience in female mice

We injected 45 Esr1-Cre heterozygous F1 males with the AAV virus encoding hM3DGq-DREADDs into the VMHvl. The mice were then screened for aggressive behavior toward females following 4-week recovery. We identified 36 mice that showed robust aggressive activity toward female intruders following i.p. injection of CNO and were therefore used as aggressors for the female CSDS experiment (Fig. 1A). To investigate the potential protective effect of DHCA/Mal-gluc in females, we treated female mice with either vehicle or DHCA/Mal-gluc for 14 days prior to and throughout the 10-day CSDS protocol, followed by social interaction (SI) testing (Fig. 1B).

Fig. 1. DHCA/Mal-gluc promotes resilience in CSDS female mice.

Fig. 1.

Open in a new tab

(A) A schematic of bilateral injections of AAV2-hSyn-DIO-GqDREADD-mCherry into male ERα-Cre mice (n=45) and time course of ERα-Cre males surgery, recovery, and screening process for successful aggressive behavior toward female mice (n=36). (B) Time course of C57BL/6J female treatment and behavioral tests. (C-D) Social interaction test in mice treated with DHCA/Mal-gluc with or without 10 days CSDS (C) Social interaction distribution. Two-way ANOVA, F1,53 =23.79, P<0.0001 for stress effect; F1,53 =5.26, P=0.0259 for treatment effect. The interaction effect was non-significant, F1,53 =3.30, P=0.0752. Data represent mean ± SD. n=13–15 per group. (D) Time spent in the corner zone during the SI. Two-way ANOVA, F1,53 =27.49, P<0.0001 for stress effect; F1,53 =11.97, P=0.0011 for treatment effect. The interaction effect was significant, F1,53 =13.25, P=0.0006. Data represent mean ± SD, n=13–15 per group.

Consistent with previous findings 39, we found that 10-day CSDS led to a significant reduction of social interaction compared to the non-stressed mice (P<0.001, Fig. 1C) while treatment with DHCA/Mal-gluc significantly increased the SI ratio compared to the vehicle-CSDS group (P=0.0114, Fig. 1C). There was no significant difference between the DHCA/Mal-gluc-CSDS and the non-stressed groups suggesting DHCA/Mal-gluc treatment rescued the CSDS-induced social avoidance phenotype in female mice. We then examined the corner occupancy during the social interaction test by two-way-ANOVA, and observed a significant interaction between stress and treatment (P=0.0006, Fig. 1D), suggesting that the effect of the treatment differs between non-stressed and stressed mice. Multiple-comparison Post-Hoc tests demonstrated that there were no differences in corner occupancy between the vehicle and the DHCA/Mal-gluc groups in non-stressed mice. However, in the stressed mice, there were significant differences between the vehicle group and the treatment group (47.6±29.6 seconds vs. 19.6±16.3 seconds, P=0.0002, Fig. 1D), further confirming that DHCA/Mal-gluc attenuated the stress-induced social avoidance phenotype (Fig. 1D). Control studies showed that neither stress nor treatment had any effect on the locomotor activity of the mice (Supplementary Fig. 1A and 1B).

We further dissected the behavioral differences between the two socially defeated female groups. Vehicle-CSDS females showed a significant decrease in interaction zone duration in the presence of a social target (two-tailed paired t-test, t13=2.402, P=0.0320, Supplementary Fig. 2A). We noted a trend toward increased interaction zone duration when the target was present in the DHCA/Mal-gluc treatment group, however it did not reach statistical significance (two-tailed paired t-test, t13=1.983, P=0.0689, Supplementary Fig. 2B). DHCA/Mal-gluc treatment significantly increased the SI ratio (Supplementary Fig. 2D, two-tailed unpaired t-test, t2=3.383, P=0.0023). About 28% of the mice in the vehicle group demonstrated a resilient phenotype (SI ratio ≥ 1) while 71% of the DHCA/Mal-gluc treated mice exhibited the resilient phenotype (Supplement Fig. 2E). Taken together, these data provide strong evidence that DHCA/Mal-gluc is effective in protecting female mice against CSDS-induced social avoidance behavior.

Peripheral inflammatory responses to CSDS and to DHCA/Mal-gluc treatment

To study peripheral inflammatory responses, whole blood from all mice was collected via the submandibular vein 18 hours after the first defeat bout. Peripheral cytokine levels were analyzed by multiplex enzyme-linked immunosorbent assay (ELISA). Consistent with previous findings in males15,38,39, CSDS induced a significant upregulation of the pro-inflammatory cytokine IL-6 in female mice compared to non-CSDS control mice (Fig. 2A). Moreover, we found a significant elevation of additional pro-inflammatory cytokines including IL-1α, IL-1β, IL-12(p70), TNF-α, and granulocyte-colony stimulating factor (G-CSF) (Fig. 2B–2F). We also found a significant increase in select chemokines including monocyte-chemoattractant protein-1 (MCP-1/CCL2) and regulated on activation, normal T cell expressed and secreted (RANTES or CCL5) in the plasma (Fig. 2G–2H). Comparing to the studies we previously conducted in male mice 38, we did not find any of these changes in male mice after the first bout of defeat except for increased IL-6 (supplementary Fig. 3). Posthoc comparison between the two female CSDS groups, we found that the DHCA/Mal-gluc group had significantly lower levels of IL-12(p70) (P=0.0202, Fig. 2D) and RANTES (P=0.0081, Fig. 2H) compared to the vehicle-CSDS group. For all other pro-inflammatory cytokines, the DHCA/Mal-gluc-CSDS group had lower average values compared to the vehicle-CSDS group; however, none reached statistical significance (Fig. 2). In a parallel control study, we did not find any differences in the two non-CSDS groups, suggesting that treatment alone has no effect on peripheral cytokine/chemokine production. We then conducted correlation analyses between plasma cytokine levels and SI behavior in the two groups of mice that were subjected to RSDS. We found that plasma levels of IL-12(p70) (P=0.0038, Fig. 3A) and RANTES (P=0.0003, Fig. 3B) were positively correlated with corner zone duration. Plasma levels of TNF-α (P=0.0053, Fig. 3C) and G-CSF (P=0.0233, Fig. 3D) were also positively correlated with corner zone duration. The levels of IL-1α, IL-1β, IL-6 and MCP-1 in plasma did not correlate with corner zone duration (Fig. 3E–3H).

Fig. 2. Peripheral inflammation assessment 18 hours following first bout of defeat in female mice with or without DHCA/Mal-gluc treatment.

Fig. 2.

Open in a new tab

(A-F) Plasma levels of cytokines 18 hours after the first social defeat bout (A) IL-6, One-way ANOVA, F2,38=3.555, P=0.0384. (B-C) IL-1α, One-way ANOVA, F2,40=7.201, P=0.0021 and IL-1β, One-way ANOVA, F2,42=4.113, P=0.0234. (D) IL-12(p70), One-way ANOVA, F2,41=10.96, P=0.0002. (E) TNF-α, One-way ANOVA, F2,40=8.551, P=0.0008 and (F) G-CSF, One-way ANOVA F2,40=6.177, P=0.0046. (G-H) peripheral levels of chemokines (G) MCP-1, One-way ANOVA F2,40=5.718, P=0.0065 and (H) RANTES, One-way ANOVA F2,40=6.600, P=0.0033. One-way ANOVA Post Hoc Bonferroni multiple comparisons. Data represent mean ± SD, n=13–15 per group.

Fig. 3. Correlation analysis of pro-inflammatory cytokines with CSDS-induced behavior phenotypes in female mice.

Fig. 3.

Open in a new tab

(A-D) Peripheral cytokines/chemokines significantly correlated with time spent in the corner zone during the SI test (A) IL-12(p70), (B) RANTES, (C) TNF-α and (D) G-CSF. (E-H) Peripheral cytokines/chemokines do not correlate with time spent in the corner zone during the SI test (E) IL-1α, (F) IL-1β, (G) IL-6 and (H) MCP-1. Only mice subjected to RSDS are included in the correlation analysis, n=27–29 per analysis, Solid lines show correlations and dotted lines show the 95% CI.

Gene expression assessment in the PFC in response to stress and to DHCA/Mal-gluc treatment

The PFC plays an important role in stress response and chronic stress leads to structural changes such as reduced spine density and altered dendritic arborization in the PFC 44–47. It is a well established brain region involved in stress responses in mice and in depression in humans 48–50. The activity of the PFC is a key determinant of depression phenotype as well as antidepressant responses and transcriptome data from human patients and mouse stress model showed dramatic sex differences in expression profiles51,52. Therefore, we tested whether DHCA/Mal-gluc can modulate stress-induced gene expression changes in the PFC. We collected PFC punches from female mice following the SI test and performed RNA-seq. Heatmaps of transcripts that were significantly regulated are shown in Figs. 4A and 4B. In female mice, there were 1173 stress-induced DEGs (584 stress-upregulated DEGs and 589 stress-downregulated DEGs, Fig. 4A–4D, Supplementary Table 1), and 209 DEGs were reversed by the treatment (Fig. 4C, Supplementary Table 2). Top GO terms enriched with stress-induced upregulated genes were related to response to stimulus, vascular development, cell motility, cell proliferation and cell signaling while stress-induced downregulated pathway are associated with potassium ion transport and regulation of lymphocyte activation (Fig. 4D). Treatment-mediated downregulated pathways are related to tissue development, kinase/phosphatase, response to external stimulus, transcription, and regulation of cell differentiation and cell signaling, and regulation of immune system (Fig. 4E). The stress-induced pathways rescued by DHCA/Mal-gluc treatment were involved in tissue development, cell proliferation, transcription and biosynthesis and regulation of the immune system such as leukocyte differentiation and cytokine production (Fig. 5F).

Fig. 4. Transcriptional assessment of PFC in response to stress and DHCA/Mal-gluc treatment in female mice.

Fig. 4.

Open in a new tab

(A) Heatmap of genes differentially regulated by stress compared with the same genes differentially regulated by treatment. (B) Heatmap of genes differentially regulated by treatment in mice following stress compared with the same genes regulated by stress. (C) Venn diagrams of total number of significantly upregulated and downregulated genes in the stressed mice and the total number regulated by treatment. (D-E) Top 10 GO enrichment pathway analysis of DEGs regulated by (D) stress (E) treatment and (F) treatment-rescued according to biological processes.

Fig. 5. Transcriptional assessment of PFC in response to stress and DHCA/Mal-gluc treatment in male mice.

Fig. 5.

Open in a new tab

(A) Heatmap of genes differentially regulated by stress compared with the same genes differentially regulated by treatment. (B) Heatmap of genes differentially regulated by treatment in mice following stress compared with the same genes regulated by stress. (C) Venn diagrams of total number of significantly upregulated and downregulated genes in the stressed mice and the total number regulated by treatment. (D-E) Top 10 GO enrichment pathway analysis of DEGs regulated by (D) stress (E) treatment and (F) treatment-rescued according to biological processes.

We also assessed the DEGs in male samples collected from previous studies 38, we found there were almost twice as many stress-induced DEGs in the PFC compared to the females (1015 stress-upregulated DEGs and 1020 stress-downregulated DEGs, Fig. 5A–5C, Supplementary Table 3). Among the stress-induced DEGs, 428 DEGs were reversed by the treatment (Fig. 5C, Supplementary Table 4). Biological pathways related to neurogenesis, cell motility, cation and ion transport were significantly enriched in stress-upregulated genes while stress downregulated genes were enriched in pathways associated with nervous system development, adhesion and transcription (Fig. 5D). Treatment-mediated upregulated genes were enriched in pathways related to extracellular structure organization, nervous system development, cytosolic calcium ion, IGF signaling and synapse assembly while treatment-downregulated DEGs were enriched in pathways associated with angiogenesis and oligodendrocyte differentiation (Fig. 5E). Rescue assessment showed that stress-induced downregulated pathways including neurogenesis, guanylate cyclase activity and VEGF signaling were reversed by the treatment (Fig. 5F). Stress-upregulated pathways such as nervous development, response to calcium ion and response to monoamine were reversed by the treatment (Fig. 5F).

Comparing male with female mice, we found 83 upregulated and 106 downregulated genes shared in the PFC of male and female mice (Fig. 6A–6D). Pathways upregulated by stress in male and female mice were those involved in response to steroid hormones, response to oxidative stress, cellular response calcium and response to cytokine while those pathways involved in G-protein coupled receptor signaling, circadian rhythm and regulation of ion transport were downregulated in both males and females (Fig. 6D). DHCA/Mal-gluc treatment rescued stress-induced changes in pathways associated with response to ROS, stress, and inflammation as well as several of the immunity-associated pathways in both male and female CSDS mice (Fig. 6E). Among the common DEGs shared by male and female mice in response to stress, eleven were upregulated by stressed and rescued by DHCA/Mal-gluc treatment. We then conducted real-time qRT-PCR to validate these RNA-seq findings. Among the eleven DEGs, we were able to measure ten with the exception of ZFP189, the expressions of which were too low to be accurately measured in both male and female mice. In female mice, we confirm that nine DEGs were indeed increased by stress with the exception of JUNB that showed no change by PCR (Supplementary Table 5). The treatment rescued all the stress-induced DEGs except for KNCN which showed no differences between the stressed female mice with or without treatment. In male mice, except for KNCN, the other nine stress-induced DEGs were confirmed to be increased by stress and the treatment rescued all of them. There is no differences in the expression of KNCN between the control, the stressed and the stressed male mice with treatment (Supplementary Table 5).

Fig. 6. Comparison of PFC transcription regulation in response to stress between female and male mice.

Fig. 6.

Open in a new tab

(A) Heatmap of stress-mediated DEGs in male compared with the same genes differentially regulated in female. (B) Heatmap of stress-mediated DEGs in male compared with the same genes differentially regulated in female (C) Venn diagrams of total number of significantly upregulated and downregulated genes in the stressed male and female mice. (D-E) GO analysis of common enriched pathways shared by male and female following (D) stress and (E) rescued by the treatment.

Discussion

In this study, we tested the efficacy of the recently identified phytochemical combination, DHCA/Mal-gluc, in protecting against stress-induced depression-like behavior in female mice following CSDS. We found that female mice receiving DHCA/Mal-gluc treatment showed significantly less social avoidance behavior in comparison to mice receiving vehicle treatment. Over 70% of the treated mice exhibited a resilient phenotype while only 28% of the vehicle group displayed resilience. Similar to our previous study in male mice38, our present study demonstrated that the combination treatment is also effective in preventing a CSDS-induced social avoidance phenotype in female mice.

Also consistent with our previous studies 15,53, both male and female mice had a significant increase in peripheral IL-6 following social defeat stress. However, female mice also showed a much broader inflammatory profile than males that included increased IL-1α, IL-1β, IL-12(p70) and TNF-α in the periphery. Chemokines MCP-1 and RANTES were also elevated in female mice following defeat. This is consistent with literature suggesting that there are sex differences in the immune system that might make females more vulnerable to inflammatory diseases 54–56. Previously we reported that DHCA/Mal-gluc treatment significantly reduced stress-induced IL-6 production in male mice 38, but we did not find any significant decrease of IL-6 in females in the treatment group, nor did we observe any correlation of IL-6 with susceptible or resilient phenotypes in female mice in the present study. However, we found that treatment with DHCA/Mal-gluc significantly reduced the levels of IL-12(p70) and RANTES in plasma. Moreover, plasma levels of IL-12(p70) and RANTES correlated strongly with depression-like phenotype. IL-12 is produced by antigen presenting cells and stimulates the differentiation of T0 cells toward T helper 1 cells (TH1) 57 and is comprised of two subunits: an alpha chain (p35 subunit) and a beta chain (p40 subunit). Co-expression of the independently regulated genes encoding the two subunits yields the biologically active compound, IL-12(p70) 58. Elevations of peripheral IL-12(p70) have been associated with depression in humans, but studies of how this specific cytokine influences mood disorders are sparse59. RANTES is a chemokine produced by many cell types and acts as a potent chemoattractant for monocytes, NK cells and T cells. Ogłodek et. al. reported in their study that plasma levels of RANTES were significantly higher in both depressed men and women compared to healthy controls and that levels were highest in patients with the most severe level depression 60. They also observed that women had higher levels of RANTES compared to men 60. Besides IL-12(p70) and RANTES, peripheral TNF-α levels in the DHCA/Mal-gluc treatment group trended downward and strongly correlated with a reduction in depression-related phenotypes. Peripheral elevations of TNF-α have been reported in depressed patients 13,16 and treatments targeting peripheral TNF-α, such as infliximab do exhibit antidepressant properties 61. However, in the current study, stressed-induced changes in TNF-α were not seen in male mice, suggesting that there is likely sex-specific cytokine/chemokine cascades in response to stress that need to be considered. Previous studies by Hodes et al. reported that stress induced the upregulations of IL-1β, IL-6, IL-10 and MCP-1 in male mice 20 minutes after the first defeat bout and the expression of IL-6 in the plasma negatively correlated with stress phenotype 15. Our assessments of the plasma cytokine was measured 18 hours after the first defeat and there is a general trend of increase of almost all of the inflammatory cytokines measured however, did not reach statistical significance. It is possible that social defeat triggers an immediate inflammation response following the first bout and subsequently subsides in male mice. Future study will measure cytokine levels in female mice immediately following the first bout of the defeat and to compare with the levels measured in a later time point to assess whether the female mice respond immediately and sustain the levels or the female mice have a delayed immunological response to acute stress. In summary, our study points to a distinction in the immunological processes following stress and the mechanisms underlying stress-related depression between males and females, with females exhibiting a far more robust immune response to stress than males. It is well established that inflammation contributes to the pathogenesis of depression, but the exact mechanisms are not completely understood. Further studies of the influence of differentially regulated cytokines and chemokines on the CNS of males and females may provide insights into how these elevations are implicated in the pathogenesis of depression.

Stress-induced synaptic maladaptation has been studied in the male CSDS model 30,32,62,63. To better understand the mechanisms of such dysregulation in female mice and the potential benefits of DHCA/Mal-gluc treatment, we examined the transcriptional profile in the PFC, a brain region known to play important roles in stress and depression. We identified specific DEGs and GO pathways that were enriched in stressed female mice and compared to those of male stressed mice. Our studies showed that even though the most highly ranked pathways differ in the PFC between male and female stressed mice, we found some shared DEGs and several enriched pathways that may be common to stress-induced responses in both sexes. Some of the shared pathways, such as inflammatory responses, organic cyclic compounds metabolism and circadian rhythm, have also been reported in human MDD 64–66. Though both male and female mice were similarly treated with DHCA/Mal-gluc, we found that the most highly ranked pathways were different. In females, the highest ranked pathways were associated with tissue development and protein phosphorylation while in male mice, the treatment influenced the extracellular matrix and autonomic nervous system. Assessment of the common rescue enriched pathways shared by male and female mice revealed that in the DHCA/Mal-glu treatment downregulated multiple pathways associated inflammation and immune responses. This is consistent with the role of DHCA as DHCA was originally chosen to target stress-induced inflammatory responses 38. The current study tested the prophylactic effect of these two compounds in preventing social defeat induced depressive behavior. Our previous study showed that the two compounds were also effective in treating male mice with established depression phenotype and the efficacy was similar to standard tricyclic imipramine 38. We also found that the improvement was associated with normalization of synaptic plasticity 38. Future study will test the therapeutic effect of these two compounds in female and male mice following social defeat stress and compare the treatment efficacy and gender specific responses in periphery as well as the CNS. Collectively, our study demonstrates differences in male and female mice in response to social defeat stress and DHCA/Mal-gluc treatment highlighting the importance of sexual dimorphisms when studying depressive disorders using animal models. These data are consistent with those from human studies demonstrating intrinsic sex-differences in MDD subjects 64–67 as well as in other mouse models for the study of depression 68.

Sexual dimorphism in depressive disorders is well documented. Women and men differ in the prevalence, symptom presentation, and responses to antidepressant treatment. However, basic research and drug discovery have mainly been limited to male models. Currently available antidepressants demonstrate disparate effects in males and females. Our studies compare sex differences in peripheral immunological responses and identify distinct molecular and cellular changes in the brain to stress and to DHCA/Mal-gluc treatment, which further advances the goal of elucidating sex differences in depression.

Supplementary Material

Supplementary information
Supplementary Table 2
Supplementary Table 1
Supplementary Table 3
Supplementary Table 4

Significance Statement.

In this study, we tested a combination therapy that targets peripheral as well as central pathophysiology of depression in a newly developed female mouse model for the study of depression. We compared the responses to social stress and a novel antidepressant treatment between male and female mice. Our study demonstrated that combination treatment is effective in modulating stress-induced depression phenotype in both male and female mice. We noted strong sex-specific responses to stress-induced inflammatory cytokine/chemokine expression in the periphery and sex-specific transcriptional regulation in the prefrontal cortex. Our findings emphasize the inclusion of both sexes in the preclinical studies.

Acknowledgments:

Funding was provided by the P50 AT008661-01 from the National Center for complementary and Integrative Health (NCCIH) and the Office of Dietary Supplements (ODS), R01MH090264 and RO1 MH104559 from the National Institute of Mental Health (NIMH). In addition, J.W. holds positions in the Research and Development unit of the Basic and Biomedical Research and Training Program at the James J. Peters Veterans Affairs Medical Center. We acknowledge that the contents of this manuscript are solely the responsibility of the authors and do not necessarily represent the views of the NCCIH, NIH, ODS or the U.S. Department of Veterans Affairs or the United States Government.

Footnotes

Conflict of Interest statement: The authors declare no conflict of interest of any type

Data availability statement:

The RNA-seq data reported in the paper are deposited in GEO with the accession number GSE146845. Other data that support the findings of this study are available from the corresponding author upon reasonable request.

Bibliography/Literature Cited

  • 1.Organization, W.H. Depression and other Common Mental Disorders Global Health Estimates. (2017).
  • 2.Read J, Gee A, Diggle J & Butler H The interpersonal adverse effects reported by 1008 users of antidepressants; and the incremental impact of polypharmacy. Psychiatry Res 256, 423–427 (2017). [DOI] [PubMed] [Google Scholar]
  • 3.Berton O & Nestler EJ New approaches to antidepressant drug discovery: beyond monoamines. Nat Rev Neurosci 7, 137–151 (2006). [DOI] [PubMed] [Google Scholar]
  • 4.Eid RS, Gobinath AR & Galea LAM Sex differences in depression: Insights from clinical and preclinical studies. Progress in neurobiology 176, 86–102 (2019). [DOI] [PubMed] [Google Scholar]
  • 5.Kornstein SG, et al. Gender differences in chronic major and double depression. J. Affect. Disord 60, 1–11 (2000). [DOI] [PubMed] [Google Scholar]
  • 6.Seney ML & Sibille E Sex differences in mood disorders: perspectives from humans and rodent models. Biology of sex differences 5, 17 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7.Silverstein B Gender difference in the prevalence of clinical depression: the role played by depression associated with somatic symptoms. The American journal of psychiatry 156, 480–482 (1999). [DOI] [PubMed] [Google Scholar]
  • 8.Nolen-Hoeksema S Emotion regulation and psychopathology: the role of gender. Annual review of clinical psychology 8, 161–187 (2012). [DOI] [PubMed] [Google Scholar]
  • 9.Parker G & Brotchie H Gender differences in depression. International review of psychiatry (Abingdon, England) 22, 429–436 (2010). [DOI] [PubMed] [Google Scholar]
  • 10.Kornstein SG, et al. Gender differences in treatment response to sertraline versus imipramine in chronic depression. The American journal of psychiatry 157, 1445–1452 (2000). [DOI] [PubMed] [Google Scholar]
  • 11.Fava M & Kendler KS Major depressive disorder. Neuron 28, 335–341 (2000). [DOI] [PubMed] [Google Scholar]
  • 12.Krishnan V & Nestler EJ The molecular neurobiology of depression. Nature 455, 894–902 (2008). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 13.Dowlati Y, et al. A meta-analysis of cytokines in major depression. Biol. Psychiatry 67, 446–457 (2010). [DOI] [PubMed] [Google Scholar]
  • 14.Hodes GE, Kana V, Menard C, Merad M & Russo SJ Neuroimmune mechanisms of depression. Nat. Neurosci 18, 1386–1393 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 15.Hodes GE, et al. Individual differences in the peripheral immune system promote resilience versus susceptibility to social stress. Proc. Natl. Acad. Sci. U. S. A 111, 16136–16141 (2014). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16.Kohler CA, et al. Peripheral cytokine and chemokine alterations in depression: a meta-analysis of 82 studies. Acta psychiatrica Scandinavica 135, 373–387 (2017). [DOI] [PubMed] [Google Scholar]
  • 17.Banks WA, Kastin AJ & Gutierrez EG Penetration of interleukin-6 across the murine blood-brain barrier. Neurosci. Lett 179, 53–56 (1994). [DOI] [PubMed] [Google Scholar]
  • 18.Postal M & Appenzeller S The importance of cytokines and autoantibodies in depression. Autoimmunity reviews 14, 30–35 (2015). [DOI] [PubMed] [Google Scholar]
  • 19.Donohue HS, et al. Chronic restraint stress induces changes in synapse morphology in stratum lacunosum-moleculare CA1 rat hippocampus: a stereological and three-dimensional ultrastructural study. Neuroscience 140, 597–606 (2006). [DOI] [PubMed] [Google Scholar]
  • 20.Magarinos AM & McEwen BS Stress-induced atrophy of apical dendrites of hippocampal CA3c neurons: comparison of stressors. Neuroscience 69, 83–88 (1995). [DOI] [PubMed] [Google Scholar]
  • 21.Foy MR, Stanton ME, Levine S & Thompson RF Behavioral stress impairs long-term potentiation in rodent hippocampus. Behavioral and neural biology 48, 138–149 (1987). [DOI] [PubMed] [Google Scholar]
  • 22.Xu L, Anwyl R & Rowan MJ Behavioural stress facilitates the induction of long-term depression in the hippocampus. Nature 387, 497–500 (1997). [DOI] [PubMed] [Google Scholar]
  • 23.Wellman CL Dendritic reorganization in pyramidal neurons in medial prefrontal cortex after chronic corticosterone administration. Journal of neurobiology 49, 245–253 (2001). [DOI] [PubMed] [Google Scholar]
  • 24.Radley JJ, et al. Chronic behavioral stress induces apical dendritic reorganization in pyramidal neurons of the medial prefrontal cortex. Neuroscience 125, 1–6 (2004). [DOI] [PubMed] [Google Scholar]
  • 25.Radley JJ & Morrison JH Repeated stress and structural plasticity in the brain. Ageing research reviews 4, 271–287 (2005). [DOI] [PubMed] [Google Scholar]
  • 26.Rosenkranz JA, Venheim ER & Padival M Chronic stress causes amygdala hyperexcitability in rodents. Biological psychiatry 67, 1128–1136 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 27.Vyas A, Pillai AG & Chattarji S Recovery after chronic stress fails to reverse amygdaloid neuronal hypertrophy and enhanced anxiety-like behavior. Neuroscience 128, 667–673 (2004). [DOI] [PubMed] [Google Scholar]
  • 28.Mitra R, Jadhav S, McEwen BS, Vyas A & Chattarji S Stress duration modulates the spatiotemporal patterns of spine formation in the basolateral amygdala. Proceedings of the National Academy of Sciences of the United States of America 102, 9371–9376 (2005). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29.Vyas A, Bernal S & Chattarji S Effects of chronic stress on dendritic arborization in the central and extended amygdala. Brain research 965, 290–294 (2003). [DOI] [PubMed] [Google Scholar]
  • 30.Krishnan V, et al. Molecular adaptations underlying susceptibility and resistance to social defeat in brain reward regions. Cell 131, 391–404 (2007). [DOI] [PubMed] [Google Scholar]
  • 31.Pelletier JG, Likhtik E, Filali M & Pare D Lasting increases in basolateral amygdala activity after emotional arousal: implications for facilitated consolidation of emotional memories. Learning & memory (Cold Spring Harbor, N.Y.) 12, 96–102 (2005). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32.Christoffel DJ, et al. IkappaB kinase regulates social defeat stress-induced synaptic and behavioral plasticity. J. Neurosci 31, 314–321 (2011). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 33.Videbech P & Ravnkilde B Hippocampal volume and depression: a meta-analysis of MRI studies. The American journal of psychiatry 161, 1957–1966 (2004). [DOI] [PubMed] [Google Scholar]
  • 34.Koolschijn PC, van Haren NE, Lensvelt-Mulders GJ, Hulshoff Pol HE & Kahn RS Brain volume abnormalities in major depressive disorder: a meta-analysis of magnetic resonance imaging studies. Human brain mapping 30, 3719–3735 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 35.Drevets WC Functional anatomical abnormalities in limbic and prefrontal cortical structures in major depression. Prog. Brain Res 126, 413–431 (2000). [DOI] [PubMed] [Google Scholar]
  • 36.Pizzagalli DA, et al. Reduced caudate and nucleus accumbens response to rewards in unmedicated individuals with major depressive disorder. The American journal of psychiatry 166, 702–710 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37.Wacker J, Dillon DG & Pizzagalli DA The role of the nucleus accumbens and rostral anterior cingulate cortex in anhedonia: integration of resting EEG, fMRI, and volumetric techniques. NeuroImage 46, 327–337 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 38.Wang J, et al. Epigenetic modulation of inflammation and synaptic plasticity promotes resilience against stress in mice. Nat. Commun 9, 477 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39.Takahashi A, et al. Establishment of a repeated social defeat stress model in female mice. Sci. Rep 7, 12838 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40.Babraham Bioinformatics. FastQC. Vol. 2017. [Google Scholar]
  • 41.Dobin A, et al. STAR: ultrafast universal RNA-seq aligner. Bioinformatics (Oxford, England) 29, 15–21 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42.Robinson MD, McCarthy DJ & Smyth GK edgeR: a Bioconductor package for differential expression analysis of digital gene expression data. Bioinformatics (Oxford, England) 26, 139–140 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43.Ritchie ME, et al. limma powers differential expression analyses for RNA-sequencing and microarray studies. Nucleic acids research 43, e47 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44.Cook SC & Wellman CL Chronic stress alters dendritic morphology in rat medial prefrontal cortex. Journal of neurobiology 60, 236–248 (2004). [DOI] [PubMed] [Google Scholar]
  • 45.Liston C, et al. Stress-induced alterations in prefrontal cortical dendritic morphology predict selective impairments in perceptual attentional set-shifting. The Journal of neuroscience : the official journal of the Society for Neuroscience 26, 7870–7874 (2006). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46.Radley JJ, et al. Repeated stress induces dendritic spine loss in the rat medial prefrontal cortex. Cerebral cortex (New York, N.Y. : 1991) 16, 313–320 (2006). [DOI] [PubMed] [Google Scholar]
  • 47.Holmes A & Wellman CL Stress-induced prefrontal reorganization and executive dysfunction in rodents. Neuroscience and biobehavioral reviews 33, 773–783 (2009). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Covington HE 3rd, Maze I, Vialou V & Nestler EJ Antidepressant action of HDAC inhibition in the prefrontal cortex. Neuroscience 298, 329–335 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49.Covington HE 3rd, et al. Antidepressant effect of optogenetic stimulation of the medial prefrontal cortex. The Journal of neuroscience : the official journal of the Society for Neuroscience 30, 16082–16090 (2010). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50.Hare BD & Duman RS Prefrontal cortex circuits in depression and anxiety: contribution of discrete neuronal populations and target regions. Molecular psychiatry (2020). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 51.Labonte B, et al. Sex-specific transcriptional signatures in human depression. Nat. Med 23, 1102–1111 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52.Girgenti MJ, et al. Prefrontal cortex interneurons display dynamic sex-specific stress-induced transcriptomes. Translational psychiatry 9, 292 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 53.Menard C, et al. Social stress induces neurovascular pathology promoting depression. Nat. Neurosci 20, 1752–1760 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54.Birur B, Amrock EM, Shelton RC & Li L Sex Differences in the Peripheral Immune System in Patients with Depression. Frontiers in psychiatry 8, 108 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 55.Rainville JR, Tsyglakova M & Hodes GE Deciphering sex differences in the immune system and depression. Frontiers in neuroendocrinology 50, 67–90 (2018). [DOI] [PubMed] [Google Scholar]
  • 56.Leff-Gelman P, et al. The Immune System and the Role of Inflammation in Perinatal Depression. Neuroscience bulletin 32, 398–420 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57.Elenkov IJ, Chrousos GP & Wilder RL Neuroendocrine regulation of IL-12 and TNF-alpha/IL-10 balance. Clinical implications. Annals of the New York Academy of Sciences 917, 94–105 (2000). [DOI] [PubMed] [Google Scholar]
  • 58.Zundler S & Neurath MF Interleukin-12: Functional activities and implications for disease. Cytokine & growth factor reviews 26, 559–568 (2015). [DOI] [PubMed] [Google Scholar]
  • 59.Himmerich H, Patsalos O, Lichtblau N, Ibrahim MAA & Dalton B Cytokine Research in Depression: Principles, Challenges, and Open Questions. Frontiers in psychiatry 10, 30 (2019). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 60.Oglodek EA, Szota A, Just MJ, Mos D & Araszkiewicz A Comparison of chemokines (CCL-5 and SDF-1), chemokine receptors (CCR-5 and CXCR-4) and IL-6 levels in patients with different severities of depression. Pharmacological reports : PR 66, 920–926 (2014). [DOI] [PubMed] [Google Scholar]
  • 61.Raison CL, et al. A randomized controlled trial of the tumor necrosis factor antagonist infliximab for treatment-resistant depression: the role of baseline inflammatory biomarkers. JAMA Psychiatry 70, 31–41 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 62.Golden SA, et al. Epigenetic regulation of RAC1 induces synaptic remodeling in stress disorders and depression. Nat. Med 19, 337–344 (2013). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63.Christoffel DJ, Golden SA & Russo SJ Structural and synaptic plasticity in stress-related disorders. Rev. Neurosci 22, 535–549 (2011). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64.Labonte B, et al. Sex-specific transcriptional signatures in human depression. Nature medicine 23, 1102–1111 (2017). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Bagot RC, et al. Circuit-wide Transcriptional Profiling Reveals Brain Region-Specific Gene Networks Regulating Depression Susceptibility. Neuron 90, 969–983 (2016). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 66.Lin LC, Lewis DA & Sibille E A human-mouse conserved sex bias in amygdala gene expression related to circadian clock and energy metabolism. Molecular brain 4, 18 (2011). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 67.Lorsch ZS, et al. Estrogen receptor α drives pro-resilient transcription in mouse models of depression. Nature Communications 9, 1116 (2018). [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68.Hodes GE, et al. Sex Differences in Nucleus Accumbens Transcriptome Profiles Associated with Susceptibility versus Resilience to Subchronic Variable Stress. J. Neurosci 35, 16362–16376 (2015). [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Supplementary information
NIHMS1740330-supplement-Supplementary_information.pdf (564.1KB, pdf)
Supplementary Table 2
NIHMS1740330-supplement-Supplementary__Table_2.pdf (324.6KB, pdf)
Supplementary Table 1
NIHMS1740330-supplement-Supplementary_Table_1.pdf (394.6KB, pdf)
Supplementary Table 3
NIHMS1740330-supplement-Supplementary__Table_3.pdf (820.1KB, pdf)
Supplementary Table 4
NIHMS1740330-supplement-Supplementary_Table_4.pdf (609.9KB, pdf)

Data Availability Statement

The RNA-seq data reported in the paper are deposited in GEO with the accession number GSE146845. Other data that support the findings of this study are available from the corresponding author upon reasonable request.

RESOURCES