Skip to main content
NCBI home page
British Journal of Pharmacology logoLink to British Journal of Pharmacology
. 2017 Nov 28;175(1):113–124. doi: 10.1111/bph.14074

Vortioxetine exerts anti‐inflammatory and immunomodulatory effects on human monocytes/macrophages

Maria Talmon 1, Silvia Rossi 1, Anna Pastore 1, Carlo Ignazio Cattaneo 1,2, Sandra Brunelleschi 1, Luigia Grazia Fresu 1,✉
PMCID: PMC5740236  PMID: 29057467

Abstract

Background and Purpose

A crosstalk between the immune system and depression has been postulated, with monocytes/macrophages and cytokines having a key role in this interaction. In this study, we examined whether vortioxetine, a multimodal anti‐depressive drug, was endowed with anti‐inflammatory and antioxidative activity, leading to immunomodulatory effects on human monocytes and macrophages.

Experimental Approach

Human monocytes were isolated from buffy coats and used as such or differentiated into M1 and M2 macrophages. Cells were treated with vortioxetine before or after differentiation, and their responsiveness was evaluated. This included oxy‐radical and TNFα production, TNFα and PPARγ gene expression and NF‐κB translocation.

Key Results

Vortioxetine significantly reduced the PMA‐induced oxidative burst in monocytes and in macrophages (M1 and M2), causing a concomitant shift of macrophages from the M1 to the M2 phenotype, demonstrated by a significant decrease in the expression of the surface marker CD86 and an increase in CD206. Moreover, treatment of monocytes with vortioxetine rendered macrophages derived from this population less sensitive to PMA, as it reduced the oxidative burst, NF‐kB translocation, TNFα release and expression while inducing PPARγ gene expression. FACS analysis showed a significant decrease in the CD14+/CD16+/CD86+ M1 population.

Conclusions and Implications

These results demonstrate that in human monocytes/macrophages, vortioxetine has antioxidant activity and anti‐inflammatory effects driving the polarization of macrophages towards their alternative phenotype. These findings suggest that vortioxetine, alongside its antidepressive effect, may have immunomodulatory properties.

Abbreviations

CytC

cytochrome C

GM‐CSF

granulocyte macrophage colony‐stimulating factor

M‐CSF

macrophage colony‐stimulating factor

MDD

major depressive disorder

NK

neurokinin

SERT

5‐HT transporter

Introduction

There is much evidence pointing to an association between the immune system and depression, and this may be driven by high levels of pro‐inflammatory cytokines and by increased oxidative stress, both arising from active monocytes/macrophages. An involvement of cytokines in psychiatric diseases was first postulated through the observation that patients treated with the pro‐inflammatory cytokine IFN‐α developed several depressive symptoms that disappeared when treatment was interrupted, leading to the formulation of ‘the monocyte/macrophage theory’ of depression and schizophrenia (Smith, 1991; Maes, 1995). Since then, more evidence has emerged that supports the involvement of pro‐inflammatory markers and immune cells in the pathogenesis of depression (Dantzer et al., 2008; Miller and Raison, 2016). Elevated levels of cytokines in the plasma of patients affected by major depressive disorders (MDDs) have been confirmed in a number of meta‐analyses (Haapakoski et al., 2015; Goldsmith et al., 2016). Similarly, a recent meta‐analysis has shown that anti‐cytokine drugs (adalimumab, tocilizumab, etc.) are associated with an antidepressant effect and increase the response to antidepressants (Kappelmann et al., 2016). This is true also for anti‐inflammatory agents (Rosenblat et al., 2016). Hence, monocytes/macrophages together with their counterpart in the CNS, microglia, can be considered the bridge between inflammation and depression (Nazimek et al., 2016b). In fact, the expression of genes involved in inflammation and immunity are up‐regulated in monocytes from MDD patients compared to healthy volunteers (Grosse et al., 2015), while glucocorticoid receptor expression is reduced (Carvalho et al., 2014). Moreover, we have described a significant imbalance between neurokinin NK1 receptor and NK2 receptor expression in monocytes isolated from MDD patients under stable therapy (Bardelli et al., 2013) and in patients affected by bipolar disorders (Amoruso et al., 2015) compared to monocytes from healthy subjects.

Peripheral monocytes can differentiate into macrophages and dendritic cells (Tacke and Randolph, 2006) that share similarities with microglia. Macrophages and microglia are characterized by a distinct plasticity that leads to the identification of two functional states, depending on the extracellular environment: M1 or M2. M1 macrophages, which in vitro can be induced by exposure to LPS, granulocyte macrophage colony‐stimulating factor (GM‐CSF) and IFN‐γ, express and release pro‐inflammatory cytokines/mediators and ROS/nitrogen species. M2 macrophages, that in vitro can be induced by exposure to macrophage CSF (M‐CSF), IL‐4 and IL‐13 express and release anti‐inflammatory cytokines that are involved in tissue repair (Sica and Mantovani, 2012; Murray et al., 2014). The two phenotypes can be distinguished by the different surface markers that they express (e.g. CD86/CD80 for M1 and CD206 for M2). Macrophages can continuously switch from one state to the other according to the environmental cues (Porcheray et al., 2005), and the possibility that microglia M1/M2 polarization contribute to relapse and remission, respectively, of MDD has recently been suggested (Nakagawa and Chiba, 2014). Moreover, Torres‐Platas et al. (2014) showed an increased number of microglia cells/macrophages in post‐mortem brain samples from suicide patients, and a dysregulation of the microglia transcriptome has been demonstrated in a murine model of inflammation‐associated depressive behaviour (Gonzalez‐Pena et al., 2016) and in a mouse microglia cell line stimulated with toll‐like receptor ligands (Das et al., 2015). Interestingly, various antidepressants have been shown to induce immunomodulatory effects on peritoneal mice macrophages (Nazimek et al., 2016a) and on microglia polarization (Kalkman and Feuerbach, 2016).

Vortioxetine is a novel antidepressant agent approved by the FDA and EMA for treatment of MDD (Frampton, 2016), endowed with a multimodal pharmacodynamic profile that combines inhibition of the 5‐HT (serotonin) transporter SERT with direct effects on 5‐HT receptors (Sanchez et al., 2015). As well as being a CNS neurotransmitter, 5‐HT is an important peripheral mediator (Shajib and Khan, 2015) that, for example, skews human macrophage polarization towards the M2 phenotype via 5‐HT2B and 5‐HT7 receptors, contributing to the maintenance of an anti‐inflammatory state (de Las Casas‐Engel and Corbi, 2014). Yet Soga et al. (2007) demonstrated that 5‐HT activates monocytes inducing the expression of CD80/86 surface markers (characteristic of the M1 pro‐inflammatory phenotype), potentiates LPS‐cytokine release and protects monocytes from apoptosis, leading to the amplification and chronicity of an inflammatory state.

Due to its unique activity, we used vortioxetine to investigate the crosstalk between the immune system and depression, evaluating human monocytes/macrophages from healthy donors. We demonstrated that vortioxetine has the ability to direct monocytes/macrophages towards an anti‐inflammatory phenotype.

Methods

Isolation and differentiation of monocytes

Human monocytes were isolated from 20 healthy anonymous human buffy coats (provided by the Transfusion Service of Ospedale Maggiore della Carità, Novara, Italy) by the standard technique of dextran sedimentation and Histopaque (density = 1.077 g·cm−3, Sigma‐Aldrich, Milano, Italy) gradient centrifugation (400× g, 30 min, room temperature) and recovered by fine suction at the interface, as described previously (Lavagno et al., 2004). Purified monocytes populations were obtained by adhesion (90 min, 37°C, 5% CO2) in serum‐free RPMI 1640 medium (Sigma‐Aldrich) supplemented with 2 mM glutamine and antibiotics. Cell viability (trypan blue dye exclusion) was usually >98%. To differentiate monocytes into M1 macrophages, cells were cultured in 10% FBS‐enriched medium with human (hr)GM‐CSF (50 ng·mL−1) for 5 days, and then IFN‐γ (20 ng·mL−1) and LPS (50 ng·mL−1) were added for an additional 24 h. To obtain M2 macrophages, monocytes were cultured in 10% FBS‐enriched medium containing hrM‐CSF (50 ng·mL−1) for 5 days, and then hrIL4, hrIL13 and hrIL10 (20 ng·mL−1) were added for an additional 24 h. Cell phenotype characterization was evaluated by the expression of specific surface marker CD86 (M1) and CD206 (M2). Cells were treated with vortioxetine at 2.5, 5 and 7.5 nM, concentrations equivalent to those found in the plasma of treated patients 10, 20 and 30 ng·mL−1 respectively. Moreover, cells were always treated with 5‐HT (1 μM), rosiglitazone (1 μM) and 15‐deoxy‐Δ12,14‐PGJ2 (PGJ2) (10 μM), used as reference drugs. Rosiglitazone (an antidiabetic drug) and PGJ2 are both agonists of PPARγ , which is well known to mediate an anti‐inflammatory effect. 5‐HT was used because it is directly involved in the pharmacodynamic action of vortioxetine. Monocytes were treated and analysed as such, or treated as requested by each specific assay, washed and left to differentiate into macrophages, and then analysed. Macrophages M1 and M2 were treated and analysed.

All the experiments were performed in triplicate using cells isolated (and consequently differentiated into macrophages) from each single donor.

Cell viability

To assess any potential toxicity of the drugs in monocytes and MDM, cell viability was evaluated using the methylthiazolyldiphenyl‐tetrazolium bromide (MTT) assay. Cells (1 × 104 cells) were treated for 1 and 24 h with vortioxetine in a concentrations range between 1 nM to 10 μM, and 5‐HT 1 μM; then, the medium was replaced by the MTT assay solution (1 mg·mL−1; 2 h, 37°C 5% CO2; Sigma‐Aldrich). The supernatant was removed and DMSO (Sigma‐Aldrich) was added in order to dissolve the purple formazan; the absorbance was read at 580 and 675 nm.

Superoxide anion (O2 −) production

Cells (1 × 106 cells per plate) were treated for 1 h with drugs and then stimulated with PMA (Sigma‐Aldrich) 1 μM for 30 min. PMA is a well‐known stimulus that induces a strong and significant respiratory burst via PKC activation (Myers et al., 1985). Therefore, it can be used to explore the anti‐inflammatory efficacy of any substance. Superoxide anion production was then evaluated by the SOD‐sensitive cytochrome C (CytC) reduction assay and expressed as nmol CytC reduced.10‐6 cells·30 min−1, using an extinction coefficient of 21.1 mM. To avoid interference with spectrophotometrical recordings, cells were incubated with RPMI 1640 without phenol red, antibiotics and FBS.

Moreover, we evaluated the percentage of cells producing O2 − using the Cellular ROS/Superoxide Detection Assay Kit (AbCam, Cambridge, UK) according to the manufacturer's instructions. Results were analysed by Windows Multiple Document Interface for Flow Cytometry (winMDI, v. 2.9; Joseph Trotter, The Scripps Institute) and expressed as percentage of cells positive to O2 − staining.

Quantitative real‐time RT‐PCR

Cells were evaluated for PPARγ and TNFα expression after a 6 h treatment with vortioxetine at 2.5, 5 and 7.5 nM, serotonin 1 μM, rosiglitazone 1 μM and PGJ2 10 μM. Total RNA was isolated by Tri‐Reagent (Sigma‐Aldrich). The amount and purity of total RNA were spectrophotometrically quantified by measuring the optical density at 260 and 280 nm. cDNA synthesis was performed using a high‐capacity cDNA reverse transcription kit (Applied Biosystems, Foster City, CA, USA) according to the manufacturer's instructions. Real‐time PCR was carried out in a volume of 10 μL per well in a 96‐well optical reaction plate (Biorad, Milano, Italy) containing 0.5 μL of TaqMan Expression Assay (PPARγ or TNFα; Applied Biosystems, USA), 2.5 μL of RNase‐free water, 5 μL of TaqMan Universal PCR MasterMix (2×) (without AmpErase UNG; Applied Biosystems) and 2 μL of cDNA template, as described previously (Amoruso et al., 2009a). The plate was run on the 7000 ABI Prism system (Applied Biosystems). To compensate for variations in cDNA concentrations and PCR efficiency between tubes, an endogenous gene control (β‐glucuronidase) was included for each sample and used for normalization. The relative quantification was determined by the ΔΔCT method (Livak and Schmittgen, 2001).

ELISA

Commercially available kits were used to test the presence of cytokine and transcription factors. Cell supernatants were tested for the presence of TNFα (Human TNFα‐Elisa Kit‐Ready‐SET‐Gol eBioscience Bender, Milano, Italy); cell lysates were tested for the presence of activated NF‐kB p65 (NF‐kB p65 – total/phospho – InstantOne, eBioscience Bender).

Flow cytometry analysis

Measurement of the expression of surface markers was performed by multiparametric analysis by flow cytometry (FACS Calibur, BD) and analysed by Windows Multiple Document Interface for Flow Cytometry (winMDI, v. 2.9; Joseph Trotter, The Scripps Institute). The following antibody panels were used: FITC anti‐CD16, FITC anti‐CD36, PE anti‐CD86, PE anti‐CD163, PerCp anti‐CD206 and APC anti‐CD14. The monocytes and macrophage populations were defined as CD14+ cells. Data are, therefore, expressed as the number of CD16+, CD86+, CD36+, CD163+ or CD206+ cells over the number of CD14+ cells. CD16 and CD86 are M1‐like markers, while CD36, CD163 and CD206 are M2‐like markers. A comparison between treated and untreated cells was performed, and data are expressed as a percentage of positive events.

Statistical analysis

The data and statistical analysis comply with the recommendations on experimental design and analysis in pharmacology (Curtis et al., 2015). Statistical analysis was performed using GraphPad Prism 6. Data are expressed as mean ± SEM of ‘n’ independent experiments performed in triplicate. Statistical significance among different cell treatments was assessed by Student's paired t‐test, or one‐way repeated measures ANOVA with Kruskal–Wallis multiple comparisons test if more than two treatment groups were compared. Statistical significance was defined as P < 0.05.

Antibodies and reagents

Vortioxetine was kindly provided by Lundbeck, Italy. Rosiglitazone and PGJ2 were purchased from Cayman Chemicals (Milan, Italy). Hystopaque, PBS, RPMI 1640 medium (with or without phenol red), glutamine, HEPES, streptomycin, penicillin, PMA, SOD, CytC, RIPA buffer, LPS, protease inhibitor cocktail and phosphatase inhibitor cocktail were obtained from Sigma (Milan, Italy); all cytokines were purchased from Immunotools (Friesoythe, Germany); FACS antibodies were purchased from eBioscience.

Nomenclature of targets and ligands

Key protein targets and ligands in this article are hyperlinked to corresponding entries in http://www.guidetopharmacology.org, the common portal for data from the IUPHAR/BPS Guide to PHARMACOLOGY (Southan et al., 2016), and are permanently archived in the Concise Guide to PHARMACOLOGY 2017/18 (Alexander et al., 2017a,b,c,d).

Results

Effects of vortioxetine on cell viability

In order to avoid confounding effects attributable to cell toxicity, we evaluated the effects of vortioxetine and of 5‐HT on cell viability by using the MTT assay. No significant differences, compared to control untreated cells, were found in the viability of monocytes or macrophages after treatment for 6 or 24 h with vortioxetine (2.5–10 nM) or 5‐HT (1 μM; data not shown). Similarly, rosiglitazone or PGJ2, used as controls in the present experiments, had no effect on cell viability as previously reported (Amoruso et al., 2009a,b).

Effect of vortioxetine on monocytes, M1 and M2 macrophages

Vortioxetine reduced the PMA‐induced burst in monocytes, M1 and M2 macrophages

Monocytes and macrophages, as major phagocytes, release basal amounts of O2 − that increase after stimulation. We therefore analysed the effect of vortioxetine on this parameter by evaluating the nmol of reduced CytC.

Basal O2 − production from unstimulated monocytes (ctrl) was unaffected by vortioxetine at the highest concentration tested (10 nM) (data not shown). PMA 1 μM treatment for 30 min (Figure 1A) led to a 10‐fold increase. Pretreatment of cells with vortioxetine dose‐dependently decreased this response, with a significant reduction already at 0.1 nM; at a concentration of 2.5 nM, the effect was comparable to that of the PPARγ agonist rosiglitazone and to 5‐HT, while treatment with PGJ2 at 10 μM resulted in greater inhibition. Vortioxetine was very efficacious at inhibiting PMA‐induced bursts in monocytes, achieving about 90% inhibition at the maximal concentration used, with an IC50 of 0.033 ± 0.009 nM. Moreover, by use of flow cytometry analysis, we evaluated the percentage of cells producing O2 −. As shown in Figure 1B, the number of monocytes producing superoxide anion significantly increased after PMA treatment, and vortioxetine significantly reduced the percentage of responsive cells, as did rosiglitazone.

Figure 1.

Figure 1

Open in a new tab

Effect of vortioxetine on superoxide anion production in monocytes. Human monocytes were pre‐incubated for 1 h with the indicated drugs (Ctrl, control untreated cell) and then stimulated with PMA 1 μM for 30 min. (A) Dose‐dependent decrease of the PMA‐oxidative burst by vortioxetine in stimulated cells. Data are means ± SEM of six independent experiments from distinct donors, analysed by one‐way ANOVA with Kruskal–Wallis test for multiple comparison. (B) FACS analysis of O2 − positive cells in the presence or absence of the indicated drugs (vortioxetine, v; rosiglitazone, rosig). Data are means ± SEM of six independent experiments from distinct donors, analysed by one‐way ANOVA with Kruskal–Wallis test for multiple comparison. Significance levels: °P < 0.05 versus Ctrl; *P < 0.05 versus PMA.

We then tested macrophages differentiated into M1 or M2 phenotypes. As expected, M1 macrophages (Figure 2A) had a higher level of basal superoxide anions (Figure 2B) compared to M2 macrophages. PMA 1 μM induced superoxide anion production in both phenotypes and vortioxetine potently reduced the responsiveness of both M1 and M2 macrophages, totally reversing the effect of PMA with an IC50 of 2.27 ± 0.37 nM in M1 and 0.37 ± 0.10 nM in M2 macrophages. While these IC50s were fitted as a single component, visual inspection of the results suggests that two inhibitory components exist, one in the pM and one in the nM range. Inhibition of PMA‐induced bursts was seen also with the PPARγ agonists and 5‐HT on both cell populations.

Figure 2.

Figure 2

Open in a new tab

Effect of vortioxetine on superoxide anion production in M1 and M2 macrophages. Macrophages were pre‐incubated for 1 h with the indicated drugs (Ctrl, control untreated cell) and then stimulated with PMA 1 μM for 30 min. Vortioxetine decreased the level of reduced CytC on PMA stimulated M1 (A) and M2 (B) macrophages in a dose‐dependent manner. Significance levels: °P < 0.05 versus Ctrl; *P < 0.05 versus respective PMA. Data are means ± SEM of five independent experiments from distinct donors, analysed by one‐way ANOVA with Kruskal–Wallis test for multiple comparison.

We then evaluated the PMA‐induced burst‐responsiveness (Figure 3) in the M1 and M2 populations via FACS analysis. As shown in Figure 3A, the median fluorescence intensity of untreated O2 −‐labelled M1 cells was significantly higher than that in M2 cells, as expected, and the M1 responsiveness to PMA was also higher. Interestingly, vortioxetine was able to completely abolish the PMA effect restoring the basal intensity of O2 − in both macrophage populations, even at a concentration of 1 nM.

Figure 3.

Figure 3

Open in a new tab

FACS analysis of phenotype/superoxide anion production in M1 and M2 macrophages. Macrophages differentiated from human monocytes were pre‐incubated with the indicated drugs [Ctrl, (control) untreated cells; 5‐HT, 1 μM; rosiglitazone (rosig), 1 μM; PGJ2, 10 μM] and then stimulated with PMA 1 μM for 30 min. Cells were then stained with antibodies anti‐CD86, anti‐CD206 and anti‐O2 −. (A) Mean fluorescence intensity (MFI) of cells stained with the O2 − detection probe. Significance level: °P < 0.05 versus Ctrl; *P < 0.05 versus PMA. (B) Percentage of M1 macrophages positive for the O2 − staining correlated to CD86 and CD206 expression. Significance level: *P < 0.05 versus PMA, referred to O2 −. # P < 0.05 versus PMA, referred to CD206. (C) Percentage of M2 macrophages positive for the O2 − staining correlated to the CD86 and CD206 expression. Significance level: *P < 0.05 versus PMA, referred to CD86 curve. All data are expressed as means ± SEM of five independent experiments from distinct donors analysed by one‐way ANOVA with Kruskal–Wallis test for multiple comparison.

Moreover, as shown in Figure 3B, we found that in the M1 population, the staining for CD86 and O2 − were overlaid both at rest and after PMA, while vortioxetine was able to reverse the pro‐oxidant stimulus and, surprisingly, to reduce the expression of CD86 skewing the phenotype against M2, as demonstrated by the increased expression of the CD206 marker (Figure 3B). The effect was bell‐shaped, with a peak at 5 nM; vice versa, in the M2 resting population (Figure 3C), we found a very low percentage of CD206+/O2 − stained cells, but after PMA stimulation these cells switched against an M1 phenotype, demonstrated by an increase in CD86 with a contemporary decrease in CD206. Vortioxetine again re‐addressed the macrophage polarization towards the M2 phenotype.

Effects of drugs on the basal expression of PPARγ and TNFα genes

We then analysed whether vortioxetine was able to modulate the gene expression of PPARγ, a recognized anti‐inflammatory factor, and TNFα, a recognized inflammatory cytokine. As expected, resting cells were characterized by a different expression of PPARγ: monocytes and M1 macrophages expressed approximately threefold lower levels of PPARγ compared to M2 macrophages (data not shown). In contrast, TNFα expression was significantly higher in M1 macrophages and lowest in M2 macrophages (data not shown). As shown in Figure 4, PPARγ mRNA expression was increased by vortioxetine even at the lowest concentration both in monocytes (Figure 4A) and M2 macrophages (Figure 4C), while TNFα was not modified. In the M1 phenotype (Figure 4B), PPARγ and TNFα mRNA expressions were less affected by vortioxetine. Interestingly, in monocytes, 5‐HT and PGJ2 were unable to modulate either PPARγ or TNFα. In M1 macrophages, 5‐HT decreased the expression of TNFα and increased that of PPARγ, while in M2 macrophages, a significant decrease in TNFα was evident while the effect on PPARγ was blunted.

Figure 4.

Figure 4

Open in a new tab

Real‐time analysis of PPARγ and TNFα expression. PPARγ and TNFα gene expression in (A) monocytes, (B) M1 and (C) M2 macrophages, challenged for 6 h with vortioxetine, 5‐HT or PGJ2, 10 μM. Data are means ± SEM of eight independent experiments from distinct donors analysed by one‐way ANOVA with Kruskal–Wallis test for multiple comparison. Significance level: °P < 0.05 versus respective control; *P < 0.05 versus respective control.

Effect of vortioxetine on monocyte differentiation to M1 or M2 macrophages

We then felt it was noteworthy to evaluate the effect of vortioxetine on monocyte differentiation towards M1 or M2 macrophages. Therefore, we treated monocytes for 6 h with vortioxetine (0.01–10 nM), 5‐HT 1 μM, rosiglitazone 1 μM or PGJ2 10 μM. Cells were then differentiated versus M1 (GM‐CSF, IFN‐γ and LPS) or M2 (M‐CSF plus IL‐4, IL‐10 and IL‐13) phenotypes for 6 days in the absence of vortioxetine. Macrophages were then analysed under basal conditions or after stimulation with PMA 1 μM for 30 min.

Vortioxetine inhibited PMA‐induced oxidative burst

PMA induced a significant response in control M1 (Figure 5A) and M2 (Figure 5B) macrophages, as expected. Interestingly, both M1 and M2 macrophages derived from vortioxetine‐treated monocytes were resistant in a dose‐dependent manner to the PMA‐induced oxidative burst (Figure 5). The IC50s for inhibition were in the nM range for both cell types (0.44 ± 0.16 nM for M1 and 1.71 ± 0.51 nM for M2).

Figure 5.

Figure 5

Open in a new tab

Superoxide anion production in M1 and M2 macrophages differentiated from vortioxetine‐treated monocytes. M1 (A) and M2 (B) macrophages were differentiated for 6 days, in the presence of the specific cytokine cocktail, from monocytes treated for 6 h with vortioxetine, 5‐HT 1 μM, rosiglitazone 1 μM or PGJ2 10 μM. On the day of the experiment, macrophages were stimulated with PMA 1 μM for 30 min. Results are expressed as nmol of reduced cytochrome C (CytC) in response to PMA. Significance level: °P < 0.05 versus Ctrl; *P < 0.05 versus PMA alone. Data are means ± SEM of five independent experiments from distinct donors, analysed by one‐way ANOVA with Kruskal–Wallis test for multiple comparison.

Vortioxetine modulated PPARγ and TNFα expression

To evaluate the possibility that vortioxetine drives macrophage polarization towards an anti‐inflammatory state, we used RT‐PCR to analyse the expression of the anti‐inflammatory nuclear factor PPARγ in M1 and M2 macrophages derived from monocytes pretreated with vortioxetine. As shown in Figure 6, vortioxetine pretreatment was able to significantly increase PPARγ mRNA expression in both M1 (Figure 6A) and M2 populations (Figure 6B). Concomitantly, vortioxetine was able to significantly reduce the gene expression of the strong pro‐inflammatory cytokine TNFα both in M1 (Figure 6A) and in M2 (Figure 6B) populations at the maximal concentration.

Figure 6.

Figure 6

Open in a new tab

Real‐time analysis of PPARγ and TNFα expression. M1 (A) and M2 (B) macrophages were differentiated for 6 days, in the presence of the specific cytokine cocktail, from monocytes treated for 6 h with vortioxetine, 5‐HT or PGJ2 10 μM. Data are means ± SEM of six independent experiments from distinct donors, analysed by one‐way ANOVA with Kruskal–Wallis test for multiple comparison. Significance levels: *P < 0.05 versus Ctrl.

Effects of vortioxetine on TNFα release and NF‐κB activity

We next used these cells, differentiated in response to vortioxetine treatment, to evaluate PMA‐induced NF‐κB activity and TNFα release. As depicted in Figure 7A (M1) and B (M2), PMA‐treatment of macrophages led to a significant increase in NF‐κB activity (left Y axis) which was significantly reduced by pretreatment with vortioxetine in M1 macrophages and by vortioxetine and rosiglitazone in M2 macrophages. In our experimental conditions, resting M1 macrophages released very high levels of TNFα (Figure 7A, right Y axis); therefore, their responsiveness to PMA was quite weak and slightly modulated by vortioxetine, by 5‐HT and PPARγ agonists. Vice versa, PMA‐treatment of M2 induced a strong TNFα release (Figure 7B, right Y axis) that vortioxetine significantly reduced with an inverse bell‐shaped curve. PPARγ agonists and 5‐HT also significantly reduced PMA‐induced TNFα release.

Figure 7.

Figure 7

Open in a new tab

Effect of vortioxetine on NF‐κB activity and TNFα secretion in PMA‐stimulated cells. ELISAs were performed in M1 (A) and M2 (B) macrophages differentiated for 6 days, in the presence of the specific cytokine cocktail, from monocytes treated for 6 h with vortioxetine (v), 5‐HT 1 μM, rosiglitazone (rosig) 1 μM and PGJ2 10 μM. On the day of the experiment, macrophages were stimulated with PMA 1 μM for 30 min. NF‐κB activity is expressed as optical density (O.D.) at 450 nm and secreted TNFα as pg·mL−1. Data are means ± SEM of six independent experiments from distinct donors analysed by one‐way ANOVA with Kruskal–Wallis test for multiple comparison. Significance levels: °P < 0.05; *P < 0.05 versus respective control.

Vortioxetine inhibited M1 polarization of macrophages induced by M‐CSF/LPS/IFN‐γ

To confirm our data demonstrating a trend of vortioxetine to prevent M1 polarization, we analysed the expression of specific surface marker such as CD86 for M1, and CD206 for M2 macrophages. As shown in Figure 8, vortioxetine at 7.5 nM, as well as 5‐HT, significantly decreased the % of CD14+/CD16+/CD86+ cells in the M1 population, demonstrating its ability to inhibit the effect of the cytokine cocktail used to differentiate vortioxetine‐treated monocytes. In contrast, vortioxetine and 5‐HT did not influence the CD14+/CD163+/CD206+ M2 population.

Figure 8.

Figure 8

Open in a new tab

Effect of vortioxetine on surface marker expression. M1 and M2 macrophages were obtained from differentiating monocytes treated for 6 h with vortioxetine (vortio) 7.5 nM or 5‐HT 1 μM. Cells were stained with the indicated antibodies and the co‐expression of CD14/CD16/CD86 and CD14/CD163/CD206 in the two populations was analysed. Vortioxetine significantly reduced the M1 population (CD14+/CD16+/CD86+ cells), while the M2 population (CD14+/CD163+/CD206+) was not influenced by the drug treatment. Data are expressed as mean ± SEM of six independent experiments from distinct donors, analysed by one‐way ANOVA with Kruskal–Wallis test for multiple comparison. Significance level: *P < 0.05 versus macrophages differentiated from untreated monocytes (Ctrl).

Discussion

Vortioxetine is an antidepressant with a unique activity on serotoninergic transmission: as well as being a potent inhibitor of SERT, it acts as a 5‐HT3, 5‐HT1D and 5‐HT7 receptor antagonist, a 5‐HT1A agonist and as a 5‐HT1B partial agonist (Sanchez et al., 2015). The IC50 and EC50 values for these actions are in the low nanomolar range (D'Agostino et al., 2015). Human monocytes/macrophages express SERT and the following 5‐HT receptors: 5‐HT1E, 5‐HT2A, 5‐HT3A, 5‐HT4, 5‐HT7 (Fiebich et al., 2004; Durk et al., 2005) through which 5‐HT exerts its immunomodulatory effects (Arreola et al., 2015).

In our study, ex vivo experiments were carried out to evaluate the possible immunomodulatory and anti‐inflammatory effects of vortioxetine in human monocytes/macrophages. We used two different experimental approaches: we evaluated the effect of vortioxetine on modulating the responsiveness of monocytes/macrophages and in reversing macrophage polarization, as well as its ability to modulate monocyte differentiation induced by cytokine cocktails. Alongside, we used rosiglitazone and/or PGJ2 as positive controls, and 5‐HT.

We firstly demonstrated that vortioxetine is endowed with the ability to reduce PMA‐induced oxidative bursts in monocytes and M1 and M2 macrophages, with a potency a thousand times superior to that of 5‐HT or rosiglitazone. Under our experimental conditions, we also demonstrated that both PMA‐treated M1 and M2 macrophages undergo phenotypic adaptations (i.e. an increase in the surface marker CD86 and a decrease in CD206), and vortioxetine restored the basal conditions towards the M2 phenotype. Moreover, vortioxetine increased the gene expression of PPARγ in resting monocytes and in both macrophage populations and induced a negative trend in the expression of TNFα. It is well known that the expression of PPARγ increases during the differentiation of monocytes to macrophages (Chinetti et al., 1998), exerts important anti‐inflammatory (Chinetti et al., 2000) and immunomodulatory effects (Chinetti et al., 2003), and its activation is able to prime monocytes towards the M2 phenotype (Bouhlel et al., 2015). Hence, our results demonstrate that vortioxetine is able to provoke monocytes towards an anti‐inflammatory state by increasing PPARγ gene expression, while 5‐HT and PGJ2 did not modify the low physiological level of this receptor. To further understand the immunomodulatory potential of vortioxetine, we next evaluated its ability to prime resting monocytes towards differentiation in response to a cocktail of cytokines. Also in this case, treatment of monocytes with vortioxetine strongly reduced the PMA‐induced burst in the resulting M1 and M2 cells, even 6 days after treatment. This suggests that pretreating monocytes with vortioxetine made the resulting M1 cells resistant to PMA stimulation, therefore, preventing the induction of the pro‐inflammatory phenotype, meanwhile supporting the differentiation towards the M2 population. The predisposition of vortioxetine‐challenged monocytes to acquire an anti‐inflammatory phenotype was also demonstrated by the significant increase in PPARγ gene expression in the M2 population as well as in, surprisingly, the M1 cells. Indeed, PPARγ activation suppresses the induction of the inflammatory genes by interfering with different signal transduction pathways, such as the NF‐κB, STAT and AP1 pathways, in turn directly involved in the expression and release of TNFα in activated monocytes/macrophages (Chinetti et al., 1998; 2000; Ricote et al., 1998; Delerive et al., 1999).

All the results highlighted above were paralleled, with minor exceptions, by 5‐HT, suggesting that (i) the effects observed are unlikely to result from an off‐target effect of vortioxetine (i.e. the serotoninergic system is involved) and (ii) the effects observed are either the result of an increase in 5‐HT (due to the inhibition of SERT), a direct agonistic effect at one of its receptors, or a mixed effect due to vortioxetine's multi‐modal action. Given that 5‐HT alone was able to induce PPARγ gene expression and reduce NF‐κB activation and TNFα release, this would suggest the involvement of a signalling cascade event. Indeed, these observations are in keeping with previous findings, which demonstrated that the levels of pro‐inflammatory cytokines were reduced by inhibition of the 5‐HT3 receptor (Fiebich et al., 2004; Stratz et al., 2012) or of SERT (Lanquillon et al., 2000; Kagaya et al., 2001), two targets inhibited by vortioxetine. An effect of vortioxetine mediated in part by the 5‐HT3 receptor is also in line with the findings of Gupta et al. (2016), who demonstrated that antagonism of 5‐HT3 receptors has a neuroprotective effect against oxidative stress. However, this explanation does not accord with the findings of Durk et al. (2005), which demonstrated that 5‐HT is able to modulate inflammation and cytokine release via activation of 5‐HT3, 5‐HT4 and 5‐HT7 receptors. The possibility that vortioxetine, in this respect, is different from other SSRIs is supported by the atypical nature of the dose–response curves observed in the present investigation. For example, when investigating PMA‐induced oxidative bursts (Figure 2), a reproducible plateau after low doses was observed with higher doses eliciting further effects, and when investigating CD86/CD206 ratios in M1 macrophages (Figure 3B): a reproducible bell‐shaped curve was observed that peaked around 5 nM. We hypothesize that these findings can be attributed to the sequential recruitment of the diverse mechanisms that characterize this antidepressant.

This working hypothesis postulates that vortioxetine, via a serotoninergic mechanism, activates PPARγ signalling, which in turn is responsible for the anti‐inflammatory effects observed. This would be consistent with the parallel effects seen with 5‐HT and PPARγ agonists. Nonetheless, it is also possible that vortioxetine activates PPARγ directly in a 5‐HT‐independent fashion. This alternative hypothesis would be consistent with reports suggesting that PPARγ agonists may have antidepressant activity via their ability to reduce the levels of inflammatory cytokines such as IL‐6 and TNFα both in depressed patients and murine models of depression (Kemp et al., 2014; Colle et al., 2016; 2017; Liao et al., 2017).

The anti‐inflammatory and immunomodulatory drugs fluoxetine and citalopram have also been shown to have similar effects on microglia in vitro (Su et al., 2015). Furthermore, 5‐HT has been demonstrated to induce M2 polarization previously (de Las Casas‐Engel and Corbi, 2014). However, the present results show for the first time that the priming of monocytes before differentiation with 5‐HT or vortioxetine is able to skew their polarization towards an M2 phenotype.

We recognize that the present investigation was performed in monocytes from healthy volunteers. Given that an impairment of serotoninergic transmission is the basis of depression, the effect of antidepressants in this population might be different. Future studies should therefore aim at replicating these results in a clinical trial employing monocytes/macrophages from patients treated with vortioxetine. Furthermore, we only evaluated the effect of vortioxetine on human monocytes/macrophages and are at present unable to determine whether the effect observed is involved in the drug's action. Lastly, we only investigated the effects of vortioxetine, a 5‐HT reuptake inhibitor with a peculiar pharmacodynamic profile and are unable to determine whether traditional SSRIs act differently in our models.

Overall our findings indicate that vortioxetine has an antioxidative and anti‐inflammatory effect, which is long‐lasting in directing macrophages towards the alternative phenotype. Therefore, drugs that can affect the serotoninergic pathway and the innate immune system should be further investigated for their potential to be used in the clinic, also in a disease‐specific context.

Author contributions

S.B. conceived the project; L.G.F. conceived and designed the experiments; M.T., S.R. and A.P. performed the experiments; L.G.F., M.T and C.I.C. analysed the data and wrote the manuscript.

Conflict of interest

S.B. received an unrestricted grant from Lundbeck (IT) that partially covered the costs of this research. Neither Lundbeck nor any of its employees participated in the design of the experiments, in the interpretation of the results or in the writing of the manuscript. All other authors declare no conflicts of interest.

Declaration of transparency and scientific rigour

This Declaration acknowledges that this paper adheres to the principles for transparent reporting and scientific rigour of preclinical research recommended by funding agencies, publishers and other organisations engaged with supporting research.

Talmon, M. , Rossi, S. , Pastore, A. , Cattaneo, C. I. , Brunelleschi, S. , and Fresu, L. G. (2018) Vortioxetine exerts anti‐inflammatory and immunomodulatory effects on human monocytes/macrophages. British Journal of Pharmacology, 175: 113–124. doi: 10.1111/bph.14074.

References

  1. Alexander SPH, Kelly E, Marrion NV, Peters JA, Faccenda E, Harding SD et al (2017a). The Concise Guide To PHARMACOLOGY 2017/18: Overview. Br J Pharmacol 174: S1–S16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Alexander SPH, Christopoulos A, Davenport AP, Kelly E, Marrion NV, Peters JA et al (2017b). The Concise Guide To PHARMACOLOGY 2017/18: G protein‐coupled receptors. Br J Pharmacol 174: S17–S129. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Alexander SPH, Cidlowski JA, Kelly E, Marrion NV, Peters JA, Faccenda E et al (2017c). The Concise Guide To PHARMACOLOGY 2017/18: Nuclear hormone receptors. Br J Pharmacol 174: S208–S224. [DOI] [PMC free article] [PubMed] [Google Scholar]
  4. Alexander SPH, Kelly E, Marrion NV, Peters JA, Faccenda E, Harding SD et al (2017d). The Concise Guide To PHARMACOLOGY 2017/18: Transporters. Br J Pharmacol 174: S360–S446. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. Amoruso A, Bardelli C, Fresu LG, Palma A, Vidali M, Ferrero V et al (2009a). Enhanced peroxisome proliferator‐activated receptor‐gamma expression in monocyte/macrophages from coronary artery disease patients and possible gender differences. J Pharmacol Exp Ther 331: 531–538. [DOI] [PubMed] [Google Scholar]
  6. Amoruso A, Gunella G, Rondano E, Bardelli C, Fresu LG, Ferrero V et al (2009b). Tobacco smoke affects expression of peroxisome proliferator‐activated receptor‐gamma in monocyte/macrophages of patients with coronary heart disease. Br J Pharmacol 158: 1276–1284. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Amoruso A, Bardelli C, Cattaneo CI, Fresu LG, Manzetti E, Brunelleschi S (2015). Neurokinin (NK)‐1 receptor expression in monocytes from bipolar disorder patients: a pilot study. J Affect Disord 178: 188–192. [DOI] [PubMed] [Google Scholar]
  8. Arreola R, Becerril‐Villanueva E, Cruz‐Fuentes C, Velasco‐Velazquez MA, Garces‐Alvarez ME, Hurtado‐Alvarado G et al (2015). Immunomodulatory effects mediated by serotonin. J Immunol Res 2015: 354957. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Bardelli C, Amoruso A, Manzetti E, Fresu LG, Valsesia R, Zeppegno P et al (2013). Recurrent major depressive disorder: imbalance of neurokinin (NK)‐1 and NK‐2 receptor expression in monocytes. Pharmacol Res 68: 24–30. [DOI] [PubMed] [Google Scholar]
  10. Bouhlel MA, Lambert M, David‐Cordonnier MH (2015). Targeting Transcription Factor Binding to DNA by Competing with DNA Binders as an Approach for Controlling Gene Expression. Curr Top Med Chem 15: 1323–1358. [DOI] [PubMed] [Google Scholar]
  11. Carvalho LA, Bergink V, Sumaski L, Wijkhuijs J, Hoogendijk WJ, Birkenhager TK et al (2014). Inflammatory activation is associated with a reduced glucocorticoid receptor alpha/beta expression ratio in monocytes of inpatients with melancholic major depressive disorder. Transl Psychiatry 4: e344. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Chinetti G, Griglio S, Antonucci M, Torra IP, Delerive P, Majd Z et al (1998). Activation of proliferator‐activated receptors alpha and gamma induces apoptosis of human monocyte‐derived macrophages. J Biol Chem 273: 25573–25580. [DOI] [PubMed] [Google Scholar]
  13. Chinetti G, Fruchart JC, Staels B (2000). Peroxisome proliferator‐activated receptors (PPARs): nuclear receptors at the crossroads between lipid metabolism and inflammation. Inflamm Res 49: 497–505. [DOI] [PubMed] [Google Scholar]
  14. Chinetti G, Fruchart JC, Staels B (2003). Peroxisome proliferator‐activated receptors: new targets for the pharmacological modulation of macrophage gene expression and function. Curr Opin Lipidol 14: 459–468. [DOI] [PubMed] [Google Scholar]
  15. Colle R, De Larminat D, Rotenberg S, Hozer F, Hardy P, Verstuyft C et al (2016). Pioglitazone could induce remission in major depression: a meta‐analysis. Neuropsychiatr Dis Treat 13: 9–16. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Colle R, De Larminat D, Rotenberg S, Hozer F, Hardy P, Verstuyft C et al (2017). PPAR‐γ Agonsts for the treatment of major depression: a review. Pharmacopsychiatry 50: 49–55. [DOI] [PubMed] [Google Scholar]
  17. Curtis MJ, Bond RA, Spina D, Ahluwalia A, Alexander SP, Giembycz MA et al (2015). Experimental design and analysis and their reporting: new guidance for publication in BJP. Br J Pharmacol 172: 3461–3471. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. D'Agostino A, English CD, Rey JA (2015). Vortioxetine (brintellix): a new serotonergic antidepressant. P T 40: 36–40. [PMC free article] [PubMed] [Google Scholar]
  19. Dantzer R, O'connor JC, Freund GG, Johnson RW, Kelley KW (2008). From inflammation to sickness and depression: when the immune system subjugates the brain. Nat Rev Neurosci 9: 46–56. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Das A, Chai JC, Kim SH, Lee YS, Park KS, Jung KH et al (2015). Transcriptome sequencing of microglial cells stimulated with TLR3 and TLR4 ligands. BMC Genomics 16: 517. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Delerive P, De Bosscher K, Besnard S, Vanden Berghe W, Peters JM, Gonzalez FJ et al (1999). Peroxisome proliferator‐activated receptor alpha negatively regulates the vascular inflammatory gene response by negative cross‐talk with transcription factors NF‐kappaB and AP‐1. J Biol Chem 274: 32048–32054. [DOI] [PubMed] [Google Scholar]
  22. Durk T, Panther E, Muller T, Sorichter S, Ferrari D, Pizzirani C et al (2005). 5‐Hydroxytryptamine modulates cytokine and chemokine production in LPS‐primed human monocytes via stimulation of different 5‐HTR subtypes. Int Immunol 17: 599–606. [DOI] [PubMed] [Google Scholar]
  23. Fiebich BL, Akundi RS, Lieb K, Candelario‐Jalil E, Gmeiner D, Haus U et al (2004). Antiinflammatory effects of 5‐HT3 receptor antagonists in lipopolysaccharide‐stimulated primary human monocytes. Scand J Rheumatol Suppl 119: 28–32. [PubMed] [Google Scholar]
  24. Frampton JE (2016). Vortioxetine: a review in cognitive dysfunction in depression. Drugs 76: 1675–1682. [DOI] [PubMed] [Google Scholar]
  25. Goldsmith DR, Rapaport MH, Miller BJ (2016). A meta‐analysis of blood cytokine network alterations in psychiatric patients: comparisons between schizophrenia, bipolar disorder and depression. Mol Psychiatry 21: 1696–1709. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Gonzalez‐Pena D, Nixon SE, O'connor JC, Southey BR, Lawson MA, Mccusker RH et al (2016). Microglia transcriptome changes in a model of depressive behavior after immune challenge. PLoS One 11: e0150858. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Grosse L, Carvalho LA, Wijkhuijs AJ, Bellingrath S, Ruland T, Ambree O et al (2015). Clinical characteristics of inflammation‐associated depression: monocyte gene expression is age‐related in major depressive disorder. Brain Behav Immun 44: 48–56. [DOI] [PubMed] [Google Scholar]
  28. Gupta D, Prabhakar V, Radhakrishnan M (2016). 5HT3 receptors: target for new antidepressant drugs. Neurosci Biobehav Rev 64: 311–325. [DOI] [PubMed] [Google Scholar]
  29. Haapakoski R, Mathieu J, Ebmeier KP, Alenius H, Kivimaki M (2015). Cumulative meta‐analysis of interleukins 6 and 1beta, tumour necrosis factor alpha and C‐reactive protein in patients with major depressive disorder. Brain Behav Immun 49: 206–215. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Kagaya A, Kugaya A, Takebayashi M, Fukue‐Saeki M, Saeki T, Yamawaki S et al (2001). Plasma concentrations of interleukin‐1beta, interleukin‐6, soluble interleukin‐2 receptor and tumor necrosis factor alpha of depressed patients in Japan. Neuropsychobiology 43: 59–62. [DOI] [PubMed] [Google Scholar]
  31. Kalkman HO, Feuerbach D (2016). Antidepressant therapies inhibit inflammation and microglial M1‐polarization. Pharmacol Ther 163: 82–93. [DOI] [PubMed] [Google Scholar]
  32. Kappelmann N, Lewis G, Dantzer R, Jones PB, Khandaker GM (2016). Antidepressant activity of anti‐cytokine treatment: a systematic review and meta‐analysis of clinical trials of chronic inflammatory conditions. Mol Psychiatry. https://doi.org/10.1038/mp.2016.167. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Kemp DE, Schinagle M, Gao K, Conroy C, Ganocy SJ, Ismail‐Beigi F et al (2014). PPAR‐γ agonism as a modulator of mood: proof‐of‐concept for pioglitazone in bipolar depression. CNS Drugs 28: 571–581. [DOI] [PMC free article] [PubMed] [Google Scholar]
  34. Lanquillon S, Krieg JC, Bening‐Abu‐Shach U, Vedder H (2000). Cytokine production and treatment response in major depressive disorder. Neuropsychopharmacology 22: 370–379. [DOI] [PubMed] [Google Scholar]
  35. de Las Casas‐Engel M, Corbi AL (2014). Serotonin modulation of macrophage polarization: inflammation and beyond. Adv Exp Med Biol 824: 89–115. [DOI] [PubMed] [Google Scholar]
  36. Lavagno L, Gunella G, Bardelli C, Spina S, Fresu LG, Viano I et al (2004). Antiinflammatory drugs and tumor necrosis factor‐alpha production from monocytes: role of transcription factor NF‐kappa B and implication for rheumatoid arthritis therapy. Eur J Pharmacol 501: 199–208. [DOI] [PubMed] [Google Scholar]
  37. Liao L, Zhang XD, Li J, Zhang ZW, Yang CC, Rao CL (2017). Pioglitazone attenuates lipopolysaccharide‐induced depression‐like behaviors, modulates NF‐κB/IL‐6/STAT3, CREB/BDNF pathways and central serotonergic neurotransmission in mice. Int Immunopharmacol 49: 178–186. [DOI] [PubMed] [Google Scholar]
  38. Livak KJ, Schmittgen TD (2001). Analysis of relative gene expression data using real‐time quantitative PCR and the 2(−Delta Delta C(T)) Method. Methods 25: 402–408. [DOI] [PubMed] [Google Scholar]
  39. Maes M (1995). Evidence for an immune response in major depression: a review and hypothesis. Prog Neuropsychopharmacol Biol Psychiatry 19: 11–38. [DOI] [PubMed] [Google Scholar]
  40. Miller AH, Raison CL (2016). The role of inflammation in depression: from evolutionary imperative to modern treatment target. Nat Rev Immunol 16: 22–34. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Murray PJ, Allen JE, Biswas SK, Fisher EA, Gilroy DW, Goerdt S et al (2014). Macrophage activation and polarization: nomenclature and experimental guidelines. Immunity 41: 14–20. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Myers MA, Mcphail LC, Snyderman R (1985). Redistribution of protein kinase C activity in human 13 monocytes: correlation with activation of the respiratory burst. J Immunol 135: 3411–3416. [PubMed] [Google Scholar]
  43. Nakagawa Y, Chiba K (2014). Role of microglial m1/m2 polarization in relapse and remission of psychiatric disorders and diseases. Pharmaceuticals (Basel) 7: 1028–1048. [DOI] [PMC free article] [PubMed] [Google Scholar]
  44. Nazimek K, Kozlowski M, Bryniarski P, Strobel S, Bryk A, Myszka M et al (2016a). Repeatedly administered antidepressant drugs modulate humoral and cellular immune response in mice through action on macrophages. Exp Biol Med (Maywood) 241: 1540–1550. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Nazimek K, Strobel S, Bryniarski P, Kozlowski M, Filipczak‐Bryniarska I, Bryniarski K (2016b). The role of macrophages in antiinflammatory activity of antidepressant drugs. Immunobiology . https://doi.org/10.1016/j.imbio.2016.07.001. [DOI] [PubMed] [Google Scholar]
  46. Porcheray F, Viaud S, Rimaniol AC, Leone C, Samah B, Dereuddre‐Bosquet N et al (2005). Macrophage activation switching: an asset for the resolution of inflammation. Clin Exp Immunol 142: 481–489. [DOI] [PMC free article] [PubMed] [Google Scholar]
  47. Ricote M, Li AC, Willson TM, Kelly CJ, Glass CK (1998). The peroxisome proliferator‐activated receptor‐gamma is a negative regulator of macrophage activation. Nature 391: 79–82. [DOI] [PubMed] [Google Scholar]
  48. Rosenblat JD, Kakar R, Berk M, Kessing LV, Vinberg M, Baune BT et al (2016). Antiinflammatory agents in the treatment of bipolar depression: a systematic review and meta‐analysis. Bipolar Disord 18: 89–101. [DOI] [PubMed] [Google Scholar]
  49. Sanchez C, Asin KE, Artigas F (2015). Vortioxetine, a novel antidepressant with multimodal activity: review of preclinical and clinical data. Pharmacol Ther 145: 43–57. [DOI] [PubMed] [Google Scholar]
  50. Shajib MS, Khan WI (2015). The role of serotonin and its receptors in activation of immune responses and inflammation. Acta Physiol (Oxf) 213: 561–574. [DOI] [PubMed] [Google Scholar]
  51. Sica A, Mantovani A (2012). Macrophage plasticity and polarization: in vivo veritas. J Clin Invest 122: 787–795. [DOI] [PMC free article] [PubMed] [Google Scholar]
  52. Smith RS (1991). The macrophage theory of depression. Med Hypotheses 35: 298–306. [DOI] [PubMed] [Google Scholar]
  53. Soga F, Katoh N, Inoue T, Kishimoto S (2007). Serotonin activates human monocytes and prevents apoptosis. J Invest Dermatol 127: 1947–1955. [DOI] [PubMed] [Google Scholar]
  54. Southan C, Sharman JL, Benson HE, Faccenda E, Pawson AJ, Alexander SPH et al. (2016). The IUPHAR/BPS guide to PHARMACOLOGY in 2016: towards curated quantitative interactions between 1300 protein targets and 6000 ligands. Nucl Acids Res 44: D1054‐D1068. [DOI] [PMC free article] [PubMed] [Google Scholar]
  55. Stratz C, Bhatia HS, Akundi RS, Nuhrenberg T, Trenk D, Munoz E et al (2012). The antiinflammatory effects of the 5‐HT(3) receptor antagonist tropisetron are mediated by the inhibition of p38 MAPK activation in primary human monocytes. Int Immunopharmacol 13: 398–402. [DOI] [PubMed] [Google Scholar]
  56. Su F, Yi H, Xu L, Zhang Z (2015). Fluoxetine and S‐citalopram inhibit M1 activation and promote M2 activation of microglia in vitro. Neuroscience 294: 60–68. [DOI] [PubMed] [Google Scholar]
  57. Tacke F, Randolph GJ (2006). Migratory fate and differentiation of blood monocyte subsets. Immunobiology 211: 609–618. [DOI] [PubMed] [Google Scholar]
  58. Torres‐Platas SG, Cruceanu C, Chen GG, Turecki G, Mechawar N (2014). Evidence for increased microglial priming and macrophage recruitment in the dorsal anterior cingulate white matter of depressed suicides. Brain Behav Immun 42: 50–59. [DOI] [PubMed] [Google Scholar]

Articles from British Journal of Pharmacology are provided here courtesy of The British Pharmacological Society

RESOURCES