CD14++CD16+ Monocytes Are Enriched by Glucocorticoid Treatment and Are Functionally Attenuated in Driving Effector T Cell Responses

Baoying Liu, Ashwin Dhanda, Sima Hirani, Emily L. Williams, H. Nida Sen, Fernando Martinez Estrada, Diamond Ling, Ian Thompson, Megan Casady, Zhiyu Li, Han Si, William Tucker, Lai Wei, Shayma Jawad, Amol Sura, Jennifer Dailey, Susan Hannes, Ping Chen, Jason L. Chien, Siamon Gordon, Richard W. J. Lee and Robert B. Nussenblatt
J Immunol June 1, 2015, 194 (11) 5150-5160; DOI: https://doi.org/10.4049/jimmunol.1402409

Abstract

Human peripheral monocytes have been categorized into three subsets based on differential expression levels of CD14 and CD16. However, the factors that influence the distribution of monocyte subsets and the roles that each subset plays in autoimmunity are not well studied. In this study, we show that circulating monocytes from patients with autoimmune uveitis exhibit a skewed phenotype toward intermediate CD14++CD16+ cells, and that this is associated with glucocorticoid therapy. We further demonstrate that CD14++CD16+ monocytes from patients and healthy control donors share a similar cell-surface marker and gene expression profile. Comparison of the effects of intermediate CD14++CD16+ monocytes with classical CD14++CD16− and nonclassical CD14+CD16++ monocytes revealed that the intermediate CD14++CD16+ subset had an attenuated capacity to promote both naive CD4+ T cell proliferation and polarization into a Th1 phenotype, and memory CD4+ T cell proliferation and IL-17 expression. Furthermore, CD14++CD16+ cells inhibit CD4+ T cell proliferation induced by other monocyte subsets and enhance CD4+ T regulatory cell IL-10 expression. These data demonstrate the impact of glucocorticoids on monocyte phenotype in the context of autoimmune disease and the differential effects of monocyte subsets on effector T cell responses.

Introduction

Human peripheral monocytes act as APCs to activate T cells during inflammatory conditions (1, 2), and they also secrete cytokines that shape T cell differentiation (3). Monocyte heterogeneity has long been recognized, and they have consequently been categorized into three subsets: classical CD14++CD16−, intermediate CD14++CD16+, and nonclassical CD14+CD16++, based on differential expression levels of CD14 (LPS receptor) and CD16 (FcγRIII) (4). Recent gene profiling analyses suggest that the intermediate CD14++CD16+ subset plays a critical role in Ag presentation (5, 6), but controversy still remains over their cytokine profile with contradictory reports of high expression of proinflammatory (5, 6) and anti-inflammatory cytokines (7).

CD14++CD16+ cells are of clinical interest because they are expanded in many inflammatory and autoimmune conditions including sepsis, liver disease, active rheumatoid arthritis, coronary artery disease, acute Kawasaki disease, and sarcoidosis (8–18). Although adaptive immune responses are the main driver of autoimmune diseases, these are strongly affected by innate immune cells (19). In mouse, there is a substantial literature demonstrating the critical contribution myeloid-derived cells make to the control of autoreactive T cells (19–22), and in human, the number of tissue-infiltrating monocytes has been correlated with disease severity (23, 24). Furthermore, therapies that target monocyte-derived cytokines such as TNFα, IL-1, and IL-6 have very successfully translated into clinical practice, revolutionizing clinical outcomes in a number of autoimmune conditions (25–28).

Glucocorticoids have been the mainstay therapy for autoimmunity for decades. However, their effect on monocyte phenotype and function in this context is not well characterized. It has nonetheless been demonstrated that glucocorticoid treatment in vitro induces an upregulation of transcripts associated with an anti-inflammatory phenotype in monocytes from healthy donors (29). Also, glucocorticoid-treated ex vivo monocytes have shown enhanced survival, phagocytosis, and chemotaxis, and displayed an anti-inflammatory phenotype (29), which cannot be mimicked by combinations of cytokines (30). However, the in vivo action of glucocorticoids on human monocytes in the setting of autoimmunity, and the consequences of this for T cell responses, has not been fully investigated.

The aim of this study was to determine the factors that influence the distribution of monocyte subsets in the peripheral blood of patients with the autoimmune disease noninfectious uveitis. Given the expansion of CD14++CD16+ cells in patients with other inflammatory conditions and the known effects of glucocorticoids in changing monocyte phenotype, we particularly interrogated the proportion of this intermediate subset of monocytes in the context of patients’ glucocorticoid treatment and compared this with age-matched healthy control donors taking no medication. In addition, we compared the cell-surface marker expression and gene expression profile of CD14++CD16+ cells from patients and healthy control donors. Furthermore, we hypothesized that glucocorticoids directly affect CD16 expression and intracellular cytokine expression in CD14++ cells, and in turn that this could influence T cell activation, proliferation, and differentiation. This was tested in vitro using human monocyte/T cell cocultures.

Materials and Methods

Subjects

The study was approved by the Institutional Review Board of the National Institutes of Health (NIH) and University of Bristol, and conformed to the tenets of the Declaration of Helsinki. Written, informed consent was obtained from all subjects. A total of 104 patients with autoimmune uveitis were recruited in the National Eye Institute Clinic and University of Bristol, and 60 healthy control samples were collected from the NIH Blood Bank.

Cell purifications

Human PBMCs were isolated from the blood of healthy donors and uveitis patients using a Ficoll gradient centrifugation protocol. Untouched naive and memory CD4+ T cells were isolated based on magnetic depletion protocols (Miltenyi Biotec) or by flow cytometry (BD Influx). Monocytes or lymphocyte fractions were obtained either by elutriation from the NIH Blood Bank, by magnetic bead isolation (Miltenyi Biotec), or by flow-cytometric sorting of donor PBMCs. Subsets of monocytes were further purified by flow cytometry (BD FACSAria II or BD Influx) based on CD14 and CD16 staining.

CD4+CD25+ T regulatory cells (Tregs) from healthy donors were isolated using the CD4+CD25+CD127dim/− Treg isolation kit II (Miltenyi Biotech) according to the manufacturer’s instructions. Labeled CD4+CD25+ T cells were obtained by passing cells through MACS and MS Separation columns twice (Miltenyi Biotech). Both the positive and negative fractions were assessed for purity using CD4-allophycocyanin-Cy7 (eBioscience), CD25-allophycocyanin (Miltenyi Biotech), FOXP3-PE (eBioscience), CTLA-4–BV421 (BD Biosciences), and CD127-BV510 (eBioscience).

Cell staining and flow-cytometric analysis

Flow-cytometric analysis was performed according to our standard institutional protocols. Cell-surface monocyte phenotypic analysis was performed using 100 μl whole-blood samples after staining with human anti-CD14 (BD Biosciences) and anti-CD16 (BD Biosciences). Abs for phenotypic monocyte staining to CD11b, CD11c, HLA-DR, CX3CR1, CXCR4, and CD163 were purchased from BD Biosciences Pharmingen. Intracellular detection of IFN-γ, IL-17, and IL-10 in T cells was performed using sorted naive or memory T cells after stimulation with Leukocyte Activation Cocktail with BD GolgiPlug (BD Biosciences) for 4 h. Cells were then restained with anti-CD4, fixed, and permeabilized with Cytofix/Cytoperm according to the manufacturer’s instructions (BD Biosciences), followed by staining with anti–IFN-γ (BD Biosciences), anti–IL-17 (eBioscience), and anti–IL-10 (BD Biosciences).

Cell culture and stimulations

PBMCs were treated both with and without LPS (100 ng/ml) and dexamethasone (1 μM) for 3 d, followed by anti-CD14 and anti-CD16 staining. Each monocyte subset was cocultured in the presence of anti-CD3 (1 μg/ml) with naive or memory T cells (ratio 1:5) for 5 d, after which T cells were assessed by intracellular staining with anti–IFN-γ (IFN-γ, Th1) and anti–IL-17 (Th17). T cell activation was also monitored by CD25 (clone M-A251; BD Biosciences) and CD40L (clone TRAP1; BD Biosciences) surface staining. T cell proliferation was defined as CFSE low population as detected by flow cytometry or through [3H] incorporation assay.

For Treg and monocyte subset coculture, flow sorted purified monocyte subsets were cocultured in an equal cell ratio with purified CD4+CD25+ and CD4+CD25− cells. Cultures were stimulated with anti-CD3 (UCHT1, 1 μg/ml) in the presence of recombinant human IL-2 (100 U/ml; Peprotech) for 3 or 5 d, with the addition of GolgiPlug (BD Biosciences) for the last 5 h. Intracellular Ki67-FITC (BD Biosciences) and IL-10–PE (BD Biosciences) expression were quantified by flow cytometry after 3 and 5 d, respectively.

Real-time PCR

Half a million monocyte subsets with or without LPS stimulation for 1 h were collected and then lysed in 250 μl lysis/binding buffer. RNA was isolated using mirVana miRNA isolation kit (Ambion). Total RNA was converted to cDNA using TaqMan reverse transcription reagents (Applied Biosystems). Quantitative PCR was performed using a 7500 Fast Real-time PCR system (Applied Biosystems). IL-10, TNF-α, IL-8, IL-12, and 18S rRNA primers and probes were obtained from Applied Biosystems and used according to standard methodologies.

Microarray

Approximately 10 μg RNA was labeled and hybridized to a GeneChip human genome U133 plus 2.0 array (Affymetrix) in compliance with the manufacturer’s protocols. CD14+CD16+, CD14++CD16+, and CD14++CD16− monocyte subsets, isolated by flow-cytometric cell sorting from patients and healthy control donors, were used for microarray analysis. Expression values were determined with either affy package or GeneChip Operating Software (GCOS) v1.1.1 software. TIGR Multiexperiment Viewer (MeV) was used for K-means clustering. All data analysis was performed either with GeneSpring software GX 7.3.1 (Agilent Technologies) or R package limma. R package limma was particularly used to analyze CD14++CD16+ dataset in which data were fitted into a linear model and differentially expressed transcripts were selected if the adjusted p value was ≤0.05. The microarray data have been deposited to Gene Expression Omnibus with an accession number of GSE66936 (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE66936).

Classification of patient characteristics

The medical records of the patients were reviewed for demographic information, ocular inflammatory activity based on the Standardization of Uveitis Nomenclature working group criteria, and immunomodulatory therapy. For the purpose of subgroup analyses, cells ≥+0.5 cells in the anterior chamber or ≥+0.5 vitreous haze were considered “active” disease. Systemic immunomodulatory therapy for uveitis treatment included glucocorticoids and other treatments, such as methotrexate, mycophenolate mofetil, cyclosporine, azathioprine, and infliximab.

Statistical analysis

Nonparametric methods were used to compare differences in CD14++CD16+ expression, phenotypic biomarker expression, and RNA expression in monocyte subsets. Analysis by the χ2 test was used to compare the sex and race differences between patients and control donors.

Results

CD14++CD16+ monocyte subset was enriched in autoimmune uveitis patients and this was associated with glucocorticoid treatment

Three subsets of human monocytes, including CD14+CD16++, CD14++CD16−, and CD14++CD16+, were defined according to the expression of CD14 and CD16. Representative dot plots showing the CD14 and CD16 expression on monocytes are shown in Fig. 1A. Skewed monocyte subsets have been reported in autoimmune inflammatory diseases such as rheumatoid arthritis (10–18). To investigate whether this relationship also exists in the context of autoimmune uveitis, we measured the distribution of monocyte subsets in a cohort of 98 patients and 57 healthy control donors (Table I). Compared with control donors, monocytes from uveitis patients exhibited a significantly higher percentage of CD14++CD16+ cells (p < 0.01; Fig. 1B), which was independent of sex, race, and disease activity (p = 0.231, 0.123, and 0.931; Supplemental Fig. 1). However, this CD14++CD16+ cell enrichment was associated with glucocorticoid use (Fig. 1C). There were no significant differences when the patient group with immunosuppression not including glucocorticoid therapy (Fig. 1C, Rx w/o GCS) and the group without any treatment (Fig. 1C, No Rx) were compared with control donors, suggesting that the elevation of CD14++CD16+ was solely associated with the treatment effect of glucocorticoids. Starting at a low dose of systemic glucocorticoid treatment (3–15 mg/d), the elevation of CD14++CD16+ was significant in comparison with control donors (p = 0.013), but this change was not statistically enhanced as the glucocorticoid dose increased (Fig. 1D).

FIGURE 1.
FIGURE 1.

CD14++CD16+ monocyte enrichment in autoimmune uveitis patients was associated with glucocorticoid treatment. (A) Representative dot plots of forward and side scatter in whole blood cells showing the monocyte gating strategy that was used based on CD14 and CD16 expression. (B) The proportion of CD14++CD16+ monocytes in 98 uveitis patients and 57 age-matched healthy control donors (box and whiskers Tukey plot). (C) The proportion of CD14++CD16+ monocytes was categorized according to treatment with systemic glucocorticoids and other immunosuppressive treatment (glucocorticoids [GCS], glucocorticoids taken together with other immunosuppressive treatment [GCS+others], receiving other immunosuppressive treatment but no glucocorticoids [Rx w/o GCS], age-matched healthy control donors on no treatment [controls]). The numbers of individuals in each group are indicated in parentheses. (D) The proportion of CD14++CD16+ monocytes from uveitis patients and age-matched healthy control donors when further grouped based on glucocorticoid dose (mg/d of oral prednisone). The numbers of individuals in each group are indicated in parentheses. *p ≤ 0.05, **p ≤ 0.01.

View this table:
Table I. Baseline characteristics of the study participants

CD14++CD16+ monocytes share a similar cell-surface marker and gene expression profile in uveitis patients and healthy control donors

To determine whether CD14++CD16+ cells were the same in autoimmune uveitis patients and healthy control donors, we analyzed by flow cytometry a panel of established surface markers previously described for monocyte subsets (5, 7), and it was similar when each monocyte subset was compared in healthy donors and uveitis patients (Fig. 2A), with the exception that the expression of CD163, a scavenger receptor protein, was significantly higher on both CD14++CD16+ and CD14++CD16− cells in patients as compared with that in control donors (Supplemental Fig. 2A, left). Further analysis indicated the increase of CD163 was associated with glucocorticoid therapy (Supplemental Fig. 2A, right). To investigate possible differences in monocyte subsets between patients and control donors, and to identify any candidate genes, we conducted gene expression analysis by microarray. No significant dissimilarity in gene expression profiling was observed across the patient and control groups by the dendrogram analysis (Fig. 2B). Specifically, there were no statistically significant differences in the gene expression of cytokine/chemokine and receptor between uveitis patients and control donors (Supplemental Table 1). Furthermore, quantitative real-time PCR was used to detect the gene expression levels of key glucocorticoid receptor targets, including FKBP5, SGK, GILZ, and MKP-1. As shown in Supplemental Fig. 2B, there was no significant difference in the expression levels of these genes between patients and control donors.

FIGURE 2.
FIGURE 2.

CD14++CD16+ monocytes from autoimmune uveitis patients and control donors share a similar phenotype in terms of cell-surface marker and gene expression. (A) Expression of monocyte surface markers quantified by mean fluorescence intensity, including CD11b, CD11c, CXCR4, CX3CR1, and HLA-DR is shown for 75 uveitis patients and 52 age-matched healthy control donors (box and whiskers Tukey plot). There was no significant difference between these markers in any of the monocyte subsets. (B) Dendrogram of hierarchical clustering of all gene expression probes for CD14++CD16+ monocytes from five autoimmune uveitis patients and four healthy control donors. The clustering analysis used Manhattan distance metric and complete linkage method. The clustering result suggests that there is no systemic difference at transcriptional level in CD14++CD16+ monocytes between healthy control donors and uveitis patients. C1–4, control donors 1–4; P1–5, patients 1–5.

Glucocorticoid treatment of classical CD14++CD16− monocytes induced CD16+ expression

Because the enrichment of CD14++CD16+ monocytes in autoimmune uveitis was associated with glucocorticoid therapy, we examined whether glucocorticoids could influence monocyte subset distribution in vitro. Elutriated monocytes were cultured in the presence of increasing concentrations of the synthetic glucocorticoid, dexamethasone, for 2 d and CD14 and CD16 expression was quantified. Compared with untreated monocytes, the proportion of CD14++CD16+ cells increased in a dose-dependent manner in the presence of 10−9 to 10−6 M dexamethasone (Fig. 3A). Because 10−6 M dexamethasone consistently enhanced CD16 expression in vitro and has previously been widely used for in vitro studies (31, 32), we used this concentration in our subsequent studies. As shown in Fig. 3B and 3C, CD16 expression was increased in dexamethasone-treated cultures (from 66 to 90%) but reduced after LPS treatment (increasing the CD14++CD16− fraction from 34 to 84%; Fig. 3B, 3C). Conversely, the intensity of CD14 expression was enhanced in monocytes cultured with LPS but decreased in the presence of dexamethasone (Supplemental Fig. 2C). We then tested whether dexamethasone could induce CD16 expression in CD14++CD16− cells. CD14++CD16− monocytes were purified and cultured in the presence of dexamethasone. After 2 d, CD16 expression increased, and on day 3 most cells were CD16+ (Fig. 3D). This is likely to reflect a shift in phenotype rather than an alteration in proportions as cell death and apoptosis were excluded by staining for 7-AAD and Annexin V. To investigate the plasticity between monocyte subsets, we first treated monocytes with LPS and IFN-γ for 3 d, then washed the cells and cultured them in the presence of dexamethasone for another 3 d. On day 3 of LPS and IFN-γ treatment, 20% was CD14++CD16+, increasing to 52% after dexamethasone treatment (Fig. 3E, left panels). Conversely, monocytes initially treated with dexamethasone for 3 d followed by LPS treatment for another 3 d showed the opposite phenotypic shift. CD14 expression was not significantly altered after secondary stimulation either with LPS/IFN-γ or dexamethasone (Fig. 3E, right panels).

FIGURE 3.
FIGURE 3.

LPS and glucocorticoid treatment have opposite effects on CD16 expression in human CD14++ monocytes in vitro. (A) CD14 and CD16 expression in elutriated monocytes treated with increasing concentrations of the synthetic glucocorticoid dexamethasone (representative graphs shown are from three independent donors). (B) Elutriated monocytes from healthy control donors were treated with LPS (100 ng/ml) or dexamethasone (1 μg/ml) for 2 d; then CD14 and CD16 expression were quantified by flow cytometry. A representative graph is shown in (B), and the summary results from five different donors are shown in (C). **p ≤ 0.01. (D) Purified CD14++CD16− monocytes were cultured in the presence of dexamethasone. CD14 and CD16 expression were then assessed over 3 d. (E) Human monocytes were first treated with LPS and IFN-γ (10 ng/ml) for 3 d; then the LPS/IFN-γ was washed off, and the cells were cultured in the presence of dexamethasone for another 3 d (upper left panels). The mean florescence intensity (MFI) of CD14 is shown in the upper right panel. Conversely, monocytes initially treated with dexamethasone for 3 d were then washed and given LPS/IFN-γ for another 3 d (lower left panels; the representative contour plots shown are from four independent donors). MFI of CD14 is shown in the lower right panel.

CD14++CD16+ monocytes expressed more IL-10 and induced fewer T cell responses than CD14++CD16− monocytes

To evaluate the effect of CD14++CD16+ monocytes on T cell function, we cultured highly purified monocyte subsets with CD4+ T cells from the same donor in the presence of an anti-CD3 Ab. CD40L on CD4+ T cells plays a vital role in the activation of APCs, thus catalyzing a positive feedback loop for T cell activation. CD4+ T cells in the absence of monocytes expressed a very low level of CD40L, which was enhanced when cocultured with CD14++CD16− monocytes. Coculture with the CD14++CD16+ subset resulted in a significantly lower expression of CD40L on CD4+ T cells (p < 0.05; Fig. 4A, 4B). Consistent with lower CD40L expression, fewer CD4+ T cells proliferated in the presence of CD14++CD16+ monocytes compared with CD14++CD16− cells (Fig. 4C, 4D). In addition, quantitative PCR showed that CD14++CD16+ monocytes exhibited the lowest levels of TNF-α and the highest level of IL-10 as compared with the other monocyte subsets (Fig. 4E). Furthermore, CD4+ T cells cocultured with CD14++CD16+ monocytes tended to express more IL-10 as compared with the other subsets (Fig. 4F). CD14++CD16− and CD14++CD16+ monocytes were then cultured with allogeneic PBMCs, respectively; the latter had an attenuated effect on T cell proliferation compared with the former (p < 0.05; Fig. 4G).

FIGURE 4.
FIGURE 4.

CD14++CD16+ monocytes expressed more IL-10 and attenuated allogeneic T cell proliferation. (A) A representative dot plot of CD40L expression on CD4+ T cells from healthy control donors after coculture with each monocyte subset in the presence of anti-CD3 Ab and (B) pooled results from three individuals. (C) A representative histogram of CFSE fluorescence in CD4+ T cells from healthy control donors after coculture with each monocyte subset. Markers indicate the proportion of divided (left) and undivided (right) cells. (D) Scatterplot of the proportion of dividing (proliferating) CD4+ T cells (monocyte–T cell cocultures from five independent healthy control donors). (E) Each monocyte subset was purified from five healthy control donors, and the expression of TNF-α and IL10 was detected by quantitative PCR. (F) Bar graph showing the proportion of CD4+ T cells expressing intracellular IL-10 in cocultures with each monocyte subset, quantified by flow cytometry (three healthy control donors). (G) PBMCs were stimulated with 3 μg/ml anti-CD3 and anti-CD28 Abs in the presence of allogeneic CD14++CD16+ or CD14++CD16− monocytes for 5 d. T cell proliferation was measured by [3H]thymidine incorporation. Experiments were conducted in triplicate (from three control donors), and one representative result is shown. Throughout this figure, error bars represent SEMs. *p ≤ 0.05, **p ≤ 0.01.

CD14++CD16+ monocytes were functionally attenuated in promoting naive T cell activation and IFN-γ expression

To specifically evaluate the effect of CD14++CD16+ monocytes on naive T cell activation, we cocultured purified monocyte subsets with naive CD4+ T cells from the same healthy control donors in the presence of anti-CD3 Ab. Naive CD4+ T cells exhibited less proliferation in the presence of CD14++CD16+ monocytes as compared with the CD14+CD16++ subset. The proliferation of these naive T cells was suppressed when the same number of CD14++CD16+ cells was added into the CD14+CD16++ and T cell coculture (p < 0.01; Fig. 5A). After 5 d, naive CD4+ T cells cocultured with CD14++CD16+ cells had lower expression of CD25 and CD45RO compared with those cultured with CD14+CD16++ monocytes (Fig. 5B, 5C). Intracellular cytokine staining indicated that CD4+ T cells cocultured with CD14++CD16+ monocytes also expressed less IFN-γ than the CD14+CD16++ cocultures (Fig. 5D, 5E). As expected, there was minimal CD4+ cell IL-17 expression.

FIGURE 5.
FIGURE 5.

CD14++CD16+ monocytes induced less naive CD4+ T cell proliferation and IFN-γ expression than CD14+CD16++ cells. (A) [3H]thymidine incorporation in naive CD4+ T cells from healthy control donors after coculture with individual or combined subsets of autologous monocytes in the presence of anti-CD3 Ab for 5 d. A representative graph of three experiments from three independent individuals is shown. Expression of (B) CD25 and (C) CD45RO 5 d after naive CD4+ T cells were cocultured with autologous monocyte subsets was quantified by flow cytometry. (D) A representative dot plot of intracellular IFN-γ+ expression in naive CD4+ T cells after coculture with each monocyte subset. (E) Scatterplot of the proportion of IFN-γ+ CD4+ cells after naive T cell coculture with autologous subsets of monocytes from four healthy control donors. (F) IL12 expression, quantified by PCR, in each subset of monocyte after 100 ng/ml LPS treatment for 1 h. Results from three healthy control donors. (G) Percentage of CD4+ cells expressing the IL-12R after naive T cells were cocultured with autologous subsets of monocytes for 1 and 4 d (quantified by flow cytometry). (H) Flow-cytometric histogram of T-bet expression after naive CD4+ T cells were cocultured with subsets of monocytes for 5 d. Black represents coculture with no monocytes, blue denotes with CD14+CD16++ monocytes, red denotes with CD14++CD16+ monocytes, and green denotes with CD14++CD16− monocytes. *p ≤ 0.05, **p ≤ 0.01.

IL-12 is known to influence naive T cell differentiation into Th1 cells (33), and its expression mirrored that of IL-12 in LPS-treated monocyte subsets with lower amounts in CD14++CD16+ than CD14+CD16++ monocytes (Fig. 5F). Accordingly, after 1 d of coculture with CD14+CD16++ monocytes, naive T cells started to express the IL-12R (4.7%), increasing to 10.7% at day 4 (Fig. 5G). Consistent with their IFN-γ expression, intracellular staining of CD14++CD16+ monocyte cocultured naive T cells also showed the lower levels of T-bet expression, a transcriptional factor that directs Th1 lineage commitment, compared with the CD14+CD16++ subset (Fig. 5H).

CD14++CD16+ monocytes induced less memory CD4+ T cell proliferation and IL-17 expression compared with classical CD14++CD16− monocytes

To evaluate the effect of monocyte subsets on memory T cell activation, we purified and cocultured each with memory CD4+ T cells from the same donor in the presence of anti-CD3 Ab. Memory CD4+ T cell proliferation was lower in the presence of CD14++CD16+ monocytes compared with CD14++CD16− cells. Proliferation of memory T cells cocultured with CD14++CD16− monocytes was suppressed when the same number of CD14++CD16+ monocytes was added (Fig. 6A). After 5 d, T cells cultured with either CD14++CD16− or CD14++CD16+ monocytes expressed increased CD25 (Fig. 6B). We observed similar suppression of memory T cell proliferation in cocultures with CD14++CD16+ monocytes from uveitis patients under glucocorticoid treatment. The proliferation of memory T cells cocultured with CD14++CD16+ cells alone or mixed cocultures (CD14++CD16+ and CD14++CD16− [4:1] ratio) was significantly decreased when compared with cocultures with CD14++CD16− monocytes alone (Fig. 6C). Intracellular cytokine expression in memory T cells after 5 d of coculture also varied according to the monocyte subset; 22.1% of CD4+ memory T cells cocultured with CD14++CD16+ monocytes expressed IFN-γ, compared with 33.3% for those cultured with CD14+CD16++. Conversely, 8.6% of memory CD4+ T cells cultured with CD14++CD16+ monocytes expressed IL-17, compared with 13.2% for those cultured with CD14++CD16− monocytes (Fig. 6D). The ratio of IL-17 and IFN-γ expression similarly reflected this bias to relatively high IL-17 and low IFN-γ in memory CD4+ T cells cultured with classical CD14++CD16− monocytes, low IL-17 and high IFN-γ in memory CD4+ T cells cultured with nonclassical CD14+CD16++ monocytes, and an intermediate expression of IL-17 and high IFN-γ cultured with CD14++CD16+ cells (Fig. 6E, 6G). IL-17 expression from memory CD4+ T cells cocultured with CD14++CD16+ monocytes isolated from uveitis patients under glucocorticoid treatment was also reduced compared with CD14++CD16− cell cocultures (Fig. 6F, 6H).

FIGURE 6.
FIGURE 6.

CD14++CD16+ monocytes induced less memory CD4+ T cell proliferation and IL-17 expression than CD14++CD16− cells. (A) [3H]thymidine incorporation in memory CD4+ T cells from healthy control donors after coculture with individual or combined subsets of monocytes in the presence of anti-CD3 Ab for 5 d. A representative graph of three experiments from three independent individuals is shown. (B) CD25 expression 5 d after memory CD4+ T cells were cocultured with autologous monocyte subsets, quantified by flow cytometry. Black represents coculture with no monocytes, blue denotes with CD14+CD16++ monocytes, red denotes with CD14++CD16+ monocytes, and green denotes with CD14++CD16− monocytes. (C) CFSE low staining of memory CD4+ T cells from uveitis patients under glucocorticoid treatment after coculture with individual or combined subsets of monocytes in the presence of anti-CD3 Ab for 5 d (n = 6 for individual monocyte subset/T cocultures [3 left bars]; n = 4 for dual monocyte subset/T cell cocultures [2 right bars]; the numbers on the x-axis indicate the ratio of CD14++CD16+ to CD14++CD16− cells in the dual monocyte subset/T cell cocultures, either 4:1 or 1:4). (D and E) Intracellular IFN-γ and IL-17 expression in memory CD4+ T cells from healthy control donors after coculture with each monocyte subset. (D) Representative dot plot. (E) Scatterplot from multiple donors. (F) Summary scatterplot of intracellular IFN-γ and IL-17 expression in memory CD4+ T cells from uveitis patients under glucocorticoid treatment after coculture with individual and combined monocyte subsets [n = 6 for individual monocyte subset/T cocultures, n = 4 for dual monocyte subset/T cell cocultures; the numbers on the x-axis indicate the ratios as in (C)]. (G and H) The ratio of IL-17 versus IFN-γ expression in cocultured memory T cells for healthy donors [(G), n = 6] and uveitis patients [(H), n = 6 or 4 as indicated earlier]. *p ≤ 0.05, **p ≤ 0.01.

CD14++CD16+ monocytes induced more IL-10 production in CD4+CD25+ Tregs

Because CD14++CD16+ monocytes were functionally attenuated in driving both naive and memory T cell responses, we then interrogated their effect on CD4+CD25+ Tregs. Both CD4+CD25− non-Tregs and CD4+CD25+ Tregs were isolated from elutriated lymphocytes and confirmed phenotypically (Fig. 7A). They were then cocultured with CD14+CD16++, CD14++CD16+, or CD14++CD16− monocytes. CD14++CD16+ monocytes induced more IL-10 production in CD4+CD25+ Tregs, compared with the other two subsets (Fig. 7B, 7C). In addition, we observed increased proliferation in Tregs cocultured with CD14++CD16+ monocytes, but this did not reach statistical significance with our sample size (Supplemental Fig. 2D).

FIGURE 7.
FIGURE 7.

CD14++CD16+ monocytes induced more IL-10 production in CD4+CD25+ Tregs. (A) Representative histograms showing expression of CD4, CD25, CD127, FOXP3, and CTLA-4 in purified CD4+CD25− non-Treg and CD4+CD25+ Treg fractions (n = 3). (B and C) IL-10 expression in CD4+CD25− non-Tregs and CD4+CD25+ Tregs after coculture with purified monocyte subsets for 5 d in the presence of 1 μg/ml anti-CD3. (B) Representative histograms. (C) Bar chart of compiled data from three individual experiments. *p ≤ 0.05.

Discussion

In this study, we have demonstrated that an enrichment of CD14++CD16+ intermediate monocytes in the peripheral blood of patients with autoimmune uveitis is associated with glucocorticoid treatment, and that glucocorticoids mimic this induction of CD16 expression in CD14++ cells in vitro. However, once generated, the characteristics of CD14++CD16+ cells from patients and healthy control donors were similar. Furthermore, the three main monocyte subsets had differential effects on naive and memory CD4+ T cells. In particular, CD14++CD16+ cells expressed less TNF-α, more IL10, and were restricted in their capacity to induce T cell activation and proliferation, and correspondingly increased Treg IL-10 expression. They also attenuated both the proliferation of naive CD4+ cells in cocultures with CD14+CD16++ cells, and memory CD4+cells in cocultures with CD14++CD16− cells.

Several explanations have been proposed for the increase in circulating CD14++CD16+ cells in autoimmune conditions (16, 34, 35): a transitory stage of differentiation from CD14++CD16− to CD14+CD16++ (5, 36, 37), the maturation of CD16− cells into CD16+ cells (38), or the depletion of CD16− monocytes in circulation as they move into tissues (38). In this study, we have similarly observed an enrichment of CD14++CD16+ cells in autoimmune uveitis patients and shown that these cells have a comparable phenotype, in terms of multiparameter flow cytometry and microarray gene expression profiling, as CD14++CD16+ cells from healthy control donors (Fig. 2, Supplemental Table 1). Furthermore, we have demonstrated that this was associated with glucocorticoid therapy, suggesting that the observed expansion of intermediate CD14++CD16+ cells is a consequence of treatment rather than a characteristic of the disease. Indeed, we found no difference in the proportion of CD14++CD16+ cells between patients with active and controlled (quiet) uveitis (Supplemental Fig. 1C). Notably, endogenous glucocorticoid production may be affected by exogenous glucocorticoid therapy; however, our in vitro observations that glucocorticoids enhanced CD16+ expression (Fig. 3D) corroborates the correlation between glucocorticoid dose and CD16 expression we observed in treated patients. Although previous studies have demonstrated that in vitro treatment of monocytes with glucocorticoids enhances CD16, IL-10, and CD163 expression (29, 39), to our knowledge, this is the first time glucocorticoids have been shown to specifically induce intermediate CD14++CD16+ monocytes.

CD14++CD16+ cells were also restricted in their ability to drive T cell responses in that they suppressed CD14+CD16++-induced naive T cell proliferation (Fig. 5A) and CD14++CD16−-induced memory CD4+ T cell proliferation (Fig. 6A). Consistent with this, compared with the other two subsets, CD14++CD16+ cells exhibited the highest expression of CD163 (Supplemental Fig. 2A), a scavenger receptor that is usually highly expressed on alternatively activated macrophages. This supports previous in vitro findings that glucocorticoids enhance CD163 expression, which is associated with an anti-inflammatory phenotype (29, 40). Furthermore, CD14++CD16+ monocytes also produced significantly more IL10 than the other monocyte subsets (Fig. 4E) and significantly enhanced more intracellular IL-10 expression in CD4+ Tregs (Fig. 7B, 7C). These data suggest a potential immunoregulatory role for CD14++CD16+ cells. Thus, we propose that glucocorticoid treatment in autoimmunity results in a CD14++CD16+ cell bias that attenuates effector T cell responses. Hence the immunosuppressive effects of glucocorticoids may rely not only on their direct action on T cells (31, 32, 41, 42), but also on their ability to shift the balance between different monocyte subsets.

Human monocytes are known to influence CD4+ cell differentiation into discrete Th cell subsets (1, 35, 43, 44). In this study, we have extended this to demonstrate the effects that different subsets of human peripheral monocytes have on naive and memory CD4+ T cell polarization. A strikingly differential gene expression profile of nonclassical CD14+CD16++ monocytes as compared with CD14++CD16+ and CD14++CD16− subsets (Supplemental Fig. 3) supports the mature and proinflammatory roles of nonclassical CD14+CD16++ monocytes (45–48). We further showed that they also significantly promoted naive T cell proliferation, expressed IL12, and polarized naive T cells into IL-12R+IFN-γ+ Th1 cells (Fig. 5). This suggests that nonclassical CD14+CD162+ cells play a key role in initiating human naive T cell responses. Conversely, classical CD14++CD16− monocytes were most potent in promoting memory CD4+ T cell proliferation (Fig. 6A) and expanding Th17 memory cells (Fig. 6C–H). By comparison, intermediate CD14+CD16++ monocytes were less able to drive proliferation and differentiation of naive CD4+ T cells into Th1 cells, and memory CD4+ T cells into Th17 cells, than nonclassical CD14+CD16++ monocytes and classical CD14++CD16− monocytes, respectively (Figs. 5, 6). Furthermore, the addition of intermediate CD14+CD16++ monocytes to CD14+CD16++ cell/naive T cell cocultures and CD14++CD16− cell/memory T cell cocultures attenuated T cell proliferation (Figs. 5A, 6A). Taken together, this demonstrates that CD14++CD16+ cells are functionally attenuated in driving effector T cell response, which is consistent with their reduced TNF-α expression, increased IL10 expression, and greater induction of IL-10 in Tregs (Figs. 4E, 4F, 7).

In summary, this study has demonstrated that glucocorticoid treatment is associated with an enrichment of CD4++CD16+ cells in patients with autoimmune uveitis, and induces the expansion of this intermediate monocyte subset in vitro. It has also further characterized the phenotype of human monocytes and identified the distinctive role of monocyte subsets in orchestrating CD4+ T cell activation and differentiation. These results contribute to our knowledge in understanding the complex interaction between innate and adaptive immunity in human disease.

Disclosures

R.W.J.L. and R.B.N. are named inventors on a U.S. patent application (no. 61/919,404) that incorporates treatments for steroid-resistant inflammatory diseases and the identification of patients likely to benefit from such treatment. The other authors have no financial conflicts of interest.

Acknowledgments

We thank Rafael Villasmil from the flow-cytometry core facility of the National Eye Institute (Bethesda, MD) in helping sort monocyte subsets.

Footnotes

  • This work was supported by the Intramural Research Program of the National Eye Institute, National Institutes of Health. A.D., E.L.W., and R.W.J.L. also received support from the National Institute for Health Research Biomedical Research Centre based at Moorfields Eye Hospital National Health Service Foundation Trust and University College London Institute of Ophthalmology, United Kingdom.

  • The microarray data presented in this article have been submitted to Gene Expression Omnibus (http://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE66936) under accession number GSE66936.

  • The views expressed are those of the authors and not necessarily those of the National Health Service, the National Institute for Health Research, or the Department of Health.

  • The online version of this article contains supplemental material.

  • Abbreviations used in this article:

    NIH
    National Institutes of Health
    Treg
    T regulatory cell.

  • Received September 23, 2014.
  • Accepted March 30, 2015.

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