Effects of Azithromycin on Blood Inflammatory Gene Expression and Cytokine Production in Sarcoidosis

Abstract

Introduction: In sarcoidosis granulomas, monocyte-derived macrophages are activated by pro-inflammatory cytokines including TNF and IL-6. Current drug treatment for sarcoidosis aims to suppress inflammation but disabling side effects can ensue. The macrolide azithromycin may be anti-inflammatory. We aimed to determine whether treatment with azithromycin affects blood inflammatory gene expression and monocyte functions in sarcoidosis.

Methods: Blood samples were collected from patients with chronic pulmonary sarcoidosis enrolled in a single arm, open label clinical trial who received oral azithromycin 250 mg once daily for 3 months. Whole blood inflammatory gene expression with or without LPS stimulation was measured using a 770-mRNA panel. Phenotypic analysis and cytokine production were conducted by flow cytometry and ELISA after 24h stimulation with growth factors and TLR ligands. mTOR activity was assessed by measuring phosphorylated S6RP.

Results: Differential gene expression analysis indicated a state of heightened myeloid cell activation in sarcoidosis. Compared with controls, sarcoidosis patients showed increased LPS responses for several cytokines and chemokines. Treatment with azithromycin had minimal effect on blood gene expression overall, but supervised clustering analysis identified several chemokine genes that were upregulated. At the protein level, azithromycin treatment increased LPS-stimulated TNF and unstimulated IL-8 production. No other cytokines showed significant changes following azithromycin. Blood neutrophil counts fell during azithromycin treatment whereas mononuclear cells remained stable. Azithromycin had no detectable effects on mTOR activity or activation markers.

Conclusion: Blood myeloid cells are activated in sarcoidosis, but azithromycin therapy did not suppress inflammatory gene expression or cytokine production in blood.

Trial registration: EudraCT 2019-000580-24 (17 May 2019).

Keywords: Cough; Cytokines; Inflammation; Innate immunity; Monocyte; Sarcoidosis.

Fig. 1

Expression of 770 inflammation-associated genes in whole blood. A Volcano plot comparing sarcoidosis patients (n = 8) and healthy controls (n = 8). The plot displays each gene's log2 fold change (x axis) and adjusted -log10(p-value) (y axis). Highly statistically significant genes fall at the top of the plot above the horizontal line, and highly differentially expressed genes fall to either side. The horizontal line indicates a false discovery rate (FDR) of 1%, and the vertical lines indicate fold changes of −1.5 and 1.5. B Heatmap of pathway scores. The plot compares pathway score changes across individual samples. Orange indicates high scores; blue indicates low scores. C Pathway analysis summarizing differential expression between sarcoidosis and controls. Each gene set's most differentially expressed genes are identified and the extent of differential expression in each gene set is summarized as a directed global significance score

Fig. 2

Comparison of changes in blood gene expression in response to LPS stimulation. A Venn diagram comparing number of genes significantly up-regulated (red arrows), down-regulated (blue arrows), or contra-regulated (both arrows) in response to stimulation with 100 ng/ml LPS for 24h between patients with sarcoidosis (n = 8) and healthy controls (n = 8). Included genes were those with at least 1.5 × fold change with LPS stimulation compared with no LPS that was statistically significant (q < 0.01). In addition, regulated genes in only controls or only sarcoidosis had to have measurable counts in both and at least 1.5 × fold change difference between the disease states. B Heatmap illustrates fold changes in cytokine and chemokine gene expression following LPS stimulation comparing blood samples from subjects with sarcoidosis (s1–s8) and healthy controls (c1–c8). On the right, columns show averaged changes in gene expression in response to LPS for subjects with sarcoidosis and controls. Scale bar represents Log2 fold changes. Gene names in bold showed statistically significant higher upregulation in response to LPS in sarcoidosis compared with controls (* p < 0.05, unpaired t-tests)

Fig. 3

Gene expression in whole blood in sarcoidosis patients before and 1 month into azithromycin therapy. A Volcano plot comparing unstimulated blood pre and 1 month post azithromycin treatment. The plot shows log2 fold change (x axis) and adjusted -log10 p-value (y axis) comparing mRNA abundance post vs pre-treatment using paired (repeated measures) analyses (n = 8). The horizontal line indicates a false discovery rate of 5%, and the vertical lines indicate FC < −1.5 and > 1.5. B Volcano plot comparing LPS-stimulated blood pre and 1 month post azithromycin treatment. The plot shows log2 fold change (x axis) and adjusted −log10 p-value (y axis) comparing mRNA abundance post vs pretreatment using paired (repeated measures) analyses (n = 8). The horizontal line indicates a false discovery rate of 5%, and the vertical lines indicate FC < −1.5 and > 1.5. C Heatmap showing selected differentially upregulated genes after azithromycin therapy (without LPS stimulation). Chemokine genes (CCL2, CCL3, CXCL2) were identified following PLS-DA and pathway analysis with variable influence scoring. CD40, FCRL1, and SRC were upregulated > twofold with unadjusted p-values < 0.05. Gene expression is illustrated in 8 subjects with sarcoidosis before (pre) and after (post) treatment with azithromycin for 1 month. Scale bar represents Log2 normalised counts

Fig. 4

Effect of azithromycin on TNF and IL-6 concentrations in response to ex vivo stimulation of whole blood. A TNF and B IL-6 were measured in supernatants from whole blood stimulated ex vivo for 24h at 37°C under 10 conditions: PBS (control), M-CSF (CSF1 3ng/ml and 300ng/ml), GM-CSF (3 ng/ml and 300ng/ml), FSL1 (3 ng/ml and 300 ng/ml), lipopolysaccharide (LPS 1µg/ml and LPS 10ng/ml), or phytohemagglutinin (PHA 100 μg/ml). Individual patient data are plotted as dots and connecting lines (n = 21). Patients taking oral corticosteroid therapy are plotted in orange. Bars represent mean concentrations in plasma supernatants from samples taken at baseline (green) and following 1 month (blue) and 3 months (purple) of azithromycin therapy. Data were analyzed using a repeated measures linear mixed effects model. p values were corrected for multiple comparisons. Statistically significant results are shown on the plot

Fig. 5

Blood cell counts and subsets in sarcoidosis patients taking azithromycin. Blood lymphocyte and monocyte subsets were assessed by expression of cell surface markers using flow cytometry. Individual patient data are plotted as dots and connecting lines (n = 21). Patients taking oral corticosteroid therapy are plotted in orange. Bars represent mean results in blood samples taken at baseline (green) and following 1 month (blue) and 3 months (purple) of azithromycin therapy. Data were analyzed using a linear mixed effects model. p values were corrected for multiple comparisons. Statistically significant results are shown on the plot