Macrophages and CD4 T-cells in rheumatoid arthritis and their modulation by JAK inhibitors

Background: Rheumatoid arthritis (RA) is a chronic inflammatory arthritis that causes significant morbidity and mortality and has no cure. Although early treatment strategies and biologic therapies such as TNFα blocking antibodies have revolutionised treatment, there still remains considerable unmet need. JAK kinase inhibitors, which target multiple inflammatory cytokines, have shown efficacy in treating RA although their exact mechanism of action remains to be determined. Stratified medicine promises to deliver the right drug to the right patient at the right time by using predictive ‘omic biomarkers discovered using bioinformatic and “Big Data” techniques. Therefore, knowledge across the realms of clinical rheumatology, applied immunology, bioinformatics and data science is required to realise this goal. Aim: To use bioinformatic tools to analyse the transcriptome of CD14 macrophages derived from patients with inflammatory arthritis and define a JAK/STAT signature. Thereafter to investigate the role of JAK inhibition on inflammatory cytokine production in a macrophage cell contact activation assay. Finally, to investigate JAK inhibition, following RA synovial fluid stimulation of monocytes. Methods and Results: Using bioinformatic software such as limma from the Bioconductor repository, I determined that there was a JAK/STAT signature in synovial CD14 macrophages from patients with RA and this differed from psoriatic arthritis samples. JAK inhibition using a JAK1/3 inhibitor tofacitinib reduced TNFα production when macrophages were cell contact activated by cytokine stimulated CD4 T-cells. Other pro-inflammatory cytokines such as IL-6 and chemokines such as IP-10 were also reduced. RA synovial fluid failed to stimulate monocytes to phosphorylate STAT1, 3 or 6 but CD4 T-cells activated STAT3 with this stimulus. RNA sequencing of synovial fluid stimulated CD4 T-cells showed an upregulation of SOCS3, BCL6 and SBNO2, a gene associated with RA but with unknown function and tofacitinib reversed this. Conclusion: These studies demonstrate that tofacitinib is effective at reducing inflammatory mediator production in a macrophage cell contact assay and also affects soluble factor mediated stimulation of CD4 T-cells. This suggests that the effectiveness of JAK inhibition is due to inhibition of multiple cytokine pathways such as IL-6, IL-15 and interferon. RNA sequencing is a useful tool to identify non-coding RNA transcripts that are associated with synovial fluid stimulation and JAK inhibition but these require further validation. SBNO2, a gene that is associated with RA, may be biomarker of tofacitinib treatment but requires further investigation and validation in wider disease cohorts

The liver X receptor pathway is highly upregulated in rheumatoid arthritis synovial macrophages and potentiates TLR-driven cytokine release

<p>Objectives: Macrophages are central to the inflammatory processes driving rheumatoid arthritis (RA) synovitis. The molecular pathways that are induced in synovial macrophages and thereby promote RA disease pathology remain poorly understood.</p> <p>Methods: We used microarray to characterise the transcriptome of synovial fluid (SF) macrophages compared with matched peripheral blood monocytes from patients with RA (n=8).</p> <p>Results: Using in silico pathway mapping, we found that pathways downstream of the cholesterol activated liver X receptors (LXRs) and those associated with Toll-like receptor (TLR) signalling were upregulated in SF macrophages. Macrophage differentiation and tumour necrosis factor α promoted the expression of LXRα. Furthermore, in functional studies we demonstrated that activation of LXRs significantly augmented TLR-driven cytokine and chemokine secretion.</p> <p>Conclusions: The LXR pathway is the most upregulated pathway in RA synovial macrophages and activation of LXRs by ligands present within SF augments TLR-driven cytokine secretion. Since the natural agonists of LXRs arise from cholesterol metabolism, this provides a novel mechanism that can promote RA synovitis.</p&gt

MiR-155 has a protective role in the development of non-alcoholic hepatosteatosis in mice

Hepatic steatosis is a global epidemic that is thought to contribute to the pathogenesis of type 2 diabetes. MicroRNAs (miRs) are regulators that can functionally integrate a range of metabolic and inflammatory pathways in liver. We aimed to investigate the functional role of miR-155 in hepatic steatosis. Male C57BL/6 wild-type (WT) and miR-155−/− mice were fed either normal chow or high fat diet (HFD) for 6 months then lipid levels, metabolic and inflammatory parameters were assessed in livers and serum of the mice. Mice lacking endogenous miR-155 that were fed HFD for 6 months developed increased hepatic steatosis compared to WT controls. This was associated with increased liver weight and serum VLDL/LDL cholesterol and alanine transaminase (ALT) levels, as well as increased hepatic expression of genes involved in glucose regulation (Pck1, Cebpa), fatty acid uptake (Cd36) and lipid metabolism (Fasn, Fabp4, Lpl, Abcd2, Pla2g7). Using miRNA target prediction algorithms and the microarray transcriptomic profile of miR-155−/− livers, we identified and validated that Nr1h3 (LXRα) as a direct miR-155 target gene that is potentially responsible for the liver phenotype of miR-155−/− mice. Together these data indicate that miR-155 plays a pivotal role regulating lipid metabolism in liver and that its deregulation may lead to hepatic steatosis in patients with diabetes

The mannose receptor (CD206) identifies a population of colonic macrophages in health and inflammatory bowel disease

To understand the contribution of mononuclear phagocytes (MNP), which include monocyte-derived intestinal macrophages, to the pathogenesis of inflammatory bowel disease (IBD), it is necessary to identify functionally-different MNP populations. We aimed to characterise intestinal macrophage populations in patients with IBD. We developed 12-parameter flow cytometry protocols to identify and human intestinal MNPs. We used these protocols to purify and characterize colonic macrophages from colonic tissue from patients with Crohn’s disease (CD), ulcerative colitis (UC), or non-inflamed controls, in a cross-sectional study. We identify macrophage populations (CD45+CD64+ HLA-DR+) and describe two distinct subsets, differentiated by their expression of the mannose receptor, CD206. CD206+ macrophages expressed markers consistent with a mature phenotype: high levels of CD68 and CD163, higher transcription of IL-10 and lower expression of TREM1. CD206− macrophages appear to be less mature, with features more similar to their monocytic precursors. We identified and purified macrophage populations from human colon. These appear to be derived from a monocytic precursor with high CCR2 and low CD206 expression. As these cells mature, they acquire expression of IL-10, CD206, CD63, and CD168. Targeting the newly recruited monocyte-derived cells may represent a fruitful avenue to ameliorate chronic inflammation in IBD

JAK inhibitors disrupt T cell-induced pro-inflammatory macrophage activation

No abstract available

miR-155^−/− mice have altered expression of inflammatory and metabolic genes in liver.

<p>(<b>A</b>) FACS quantification of the % CD45⁺F4/80⁺ macrophages in livers fed HFD and representative F4/80⁺ macrophage staining (brown) and isotype controls (inset) in liver (40x magnification, scale bar 5 µm). qRT-PCR analysis of expression of inflammatory genes (<i>Socs1, Il1b, Il6, Tnf, and Nos2</i>) (<b>B</b>), and metabolic genes (<i>Pck1, Ppargc1a, Pparg, Cebpa, Cebpb, Hmgcr, Ldlr, Srebf1, Cd36, Cyp7a1, Fas, Acc, Fabp4, Ampk, Cpt1a, Crot</i>) (<b>C</b>) relative to WT control. Data are Means ± SEM pooled from 2 independent experiments, n = 3–5 mice/group. * p<0.05, ** p<0.01 Student’s unpaired <i>t</i>-test compared to WT fed HFD.</p

Association of liver weight with murine clinical parameters.

<p>Livers were collected from mice at 24 wk of age fed either normal chow or high fat diet (HFD). Alanine transaminase (ALT), cholesterol, triglyceride and insulin values were determined in serum. Data are Means ± SEM pooled from 2 independent experiments: n = 13–21 mice/group.</p>*<p>p<0.05 Student’s unpaired <i>t</i>-test.</p

Liver expression of miR-155 is increased in murine models of obesity.

<p>Expression of miR-155 by qRT-PCR in: (<b>A</b>) Tissues from 8-week old WT mice fed normal chow (n = 3)(WAT: white adipose tissue); (<b>B</b>) Livers from WT mice fed either normal chow or HFD for 24 weeks; (<b>C</b>) Livers from WT and <i>ob/ob</i> mice fed normal chow for 5 weeks. Data are Means ± SEM, n = 3–5 mice/group. (<b>D</b>) Representative sections showing localization of miR-155 in livers by <i>in situ</i> hybridization (purple stain, 40x magnification, scale bar 5 µm). Sections counterstained with nuclear red. Scrambled oligo probe was used as a negative control (inset). (<b>E</b>) Quantification of miR-155 <i>in situ</i> staining in livers from WT mice fed either chow or HFD for 24 weeks (n = 5–7/group). ** p<0.01 Mann-Whitney test. (<b>F</b>) Expression of miR-155 in bead-sorted CD11b⁺ macrophages and CD11b⁻ cells from livers of WT mice fed HFD for 24 weeks (n = 3). *p<0.05 Student’s unpaired <i>t</i>-test.</p

Identification of miR-155 direct targets in liver.

<p>(<b>A</b>) Interaction map showing liver mRNA that are direct targets of miR-155 by Ingenuity Pathway Analysis that shows genes involved in Lipid Metabolism, Molecular Transport, and Small Molecule Biochemistry. miR-155 direct targets that are up-regulated in miR-155^−/− livers are marked in red. (<b>B</b>) Expression of the identified target genes <i>Abcd2, Agtrap, Lpl, Nr1h3</i> (LXRα) and <i>Pla2g7</i> validated by qRT-PCR in WT vs miR-155^−/− livers fed HFD (n = 3). Expression is shown relative to WT control. *** p<0.001 Student’s unpaired <i>t</i>-test.</p

miR-155^−/− mice are susceptible to hepatic steatosis.

<p>WT or miR-155^−/− mice were fed either normal chow or HFD and livers examined at 24 weeks. (<b>A</b>) Liver weights (g). (<b>B</b>) Gross morphology. (<b>C</b>) Total cholesterol (TC), free cholesterol (FC) and cholesterol ester (CE) measurements in liver (µg/mg of cell protein). (<b>D</b>) Triglyceride measurements in liver (µg/mg of cell protein). (<b>E</b>) Representative H&E, and Oil Red O staining of the livers (40x magnification, scale bar 5 µm). Data are Means ± SEM pooled from 2 independent experiments, n = 13–21 mice/group. ** p<0.01, *** p<0.001 Student’s unpaired <i>t</i>-test compared to WT fed HFD.</p