Subsets of activated monocytes and markers of inflammation in incipient and progressed multiple sclerosis

Abstract

Multiple sclerosis (MS) is an immune mediated, inflammatory and demyelinating disease of the central nervous system (CNS). Substantial evidence points toward monocytes and macrophages playing prominent roles early in disease, mediating both pro- and anti-inflammatory responses. Monocytes are subdivided into three subsets depending on the expression of CD14 and CD16, representing different stages of inflammatory activation. To investigate their involvement in MS, peripheral blood mononuclear cells from 40 patients with incipient or progressed MS and 20 healthy controls were characterized ex vivo. In MS samples, we demonstrate a highly significant increase in nonclassical monocytes (CD14+CD16++), with a concomitant significant reduction in classical monocytes (CD14++CD16-) compared with healthy controls. Also, a significant reduction in the surface expression of CD40, CD163, and CD192 was found, attributable to the upregulation of the nonclassical monocytes. In addition, significantly increased levels of human endogenous retrovirus (HERV) envelope (Env) epitopes, encoded by both HERV-H/F and HERV-W, were specifically found on nonclassical monocytes from patients with MS; emphasizing their involvement in MS disease. In parallel, serum and cerebrospinal fluid (CSF) samples were analyzed for soluble biomarkers of inflammation and neurodegeneration. For sCD163 versus CD163, no significant correlations were found, whereas highly significant correlations between levels of soluble neopterine and the intermediate monocyte (CD14++CD16+) population was found, as were correlations between levels of soluble osteopontin and the HERV Env expression on nonclassical monocytes. The results from this study emphasize the relevance of further focus on monocyte subsets, particularly the nonclassical monocytes in monitoring of inflammatory diseases.

Keywords: ELISA; MS; Biomarkers; FLOW Cytometry; HERVs; monocyte subsets; monocytes; multiple sclerosis.

© 2017 The Authors Immunology and Cell Biology published by John Wiley & Sons Australia, Ltd on behalf of Australasian Society for Immunology Inc.

Figures

Figure 1

Gating strategy used in the flow cytometric analysis of patient and healthy control samples. A sample from a representative patient with RRMS was used for this figure. (a) From left to right: Total monocytes (> 20,000 events) were gated according to their size and granularity in forward scatter‐height (FSC‐H)/side scatter‐height (SSC‐H), aggregated cells were removed according to forward scatter‐area (FSC‐A)/FSC‐H and side scatter‐area (SSC‐A)/SSC‐H, and finally dead cells were removed according to staining with a LIVE/DEAD ® cell stain. (b) From left to right: The tree monocyte subsets (classical, intermediate, nonclassical) were gated on the “Live Cells” gate, as were the CD40+, CD163+, and CD192+ cells (blue). Appropriate isotype controls (red) were used to determine the unspecific antibody binding. (c, d) From left to right: Human endogenous retrovirus (HERV) expression was determined on the total monocyte population (Live cells) and the three monocyte subsets (classical, intermediate, nonclassical) by incubation with sera from rabbits immunized with HERV H3 Env (c) or HERV W3 Env (d) peptide antigens (blue) as described previously36 and with the appropriate control (pre‐immune sera) (red) to determine the median fluorescence index (MFI).

Figure 2

Differences in the expression of CD40, CD163, CD192, and of the three monocyte subsets in the patient group normalised to the median of the healthy controls. The differences in expression of CD40, CD163, and CD192 on the total monocyte population (Live cells, Figure 1) (a) and the three monocyte sub‐populations; classical, intermediate, and nonclassical (b) were determined as % positive cells of the monocytes, divided by the respective median levels of the healthy control samples to give the fold change. Bars represent the median of the populations and braces indicate a significant difference (Mann–Whitney U‐test) between the median of the patient group (n = 40) and the median of the healthy control group (n = 20). P‐values are listed. Pt, patients; HC, healthy controls.

Figure 3

Differences in the expression of HERV H3 Env and HERV W3 Env on the three monocyte subsets in the patient group and the HC group. The differences in expression of HERV H3 Env (a) and HERV W3 Env (b) on the three monocyte subsets; classical, intermediate, and nonclassical were determined as the median fluorescence index by calculating the median fluorescence for each sample and dividing by the median fluorescence of the appropriate control (pre‐immune sera). Bars represent the median of the subsets and braces indicate a significant difference (Mann–Whitney U‐test) between the median of the patient group (n = 40) and the median of the HC group (n = 20). P‐values are listed. Pt, patients, HC, healthy controls.

Figure 4

Logistic regression analyses with ROC curve output of patients with CIS or MS plotted against the HC group. AUC, with 95% CI, is given for each parameter. The surface expression of each parameter for patients with CIS or MS (n = 40) are combined as true positives and plotted against HC as true negatives (n = 20). The diagonal dividing the ROC space represents the random event. A logistic regression analysis with combined parameter results has been performed for “all parameters”, parameters with AUC > 0.70, and AUC > 0.75. ROC, receiver operating characteristic; AUC, Area under the curve; RRMS, relapsing‐remitting MS; PPMS, primary‐progressive MS; CIS, clinically isolated syndrome; HCs,healthy controls.