Neutrophils play a key role in the pathophysiology of rheumatoid arthritis (RA) where release of ROS and proteases directly causes damage to joints and tissues. Neutrophil function can be modulated by Janus Kinase (JAK) inhibitor drugs, including tofacitinib and baricitinib, which are clinically effective treatments for RA. However, clinical trials have reported increased infection rates and transient neutropenia during therapy. The subtle differences in the mode of action, efficacy and safety of JAK inhibitors have been the primary research topic of many clinical trials and systematic reviews, to provide a more precise and targeted treatment to patients. The aim of this study was to determine both the differences in the metabolome of neutrophils from healthy controls and people with RA, and the effect of different JAK inhibitors on the metabolome of healthy and RA neutrophils. Isolated neutrophils from healthy controls (HC) (n = 6) and people with RA (n = 7) were incubated with baricitinib, tofacitinib or a pan-JAK inhibitor (all 200 ng/mL) for 2 h. Metabolites were extracted, and ¹H nuclear magnetic resonance (NMR) was applied to study the metabolic changes. Multivariate analyses and machine learning models showed a divergent metabolic pattern in RA neutrophils compared to HC at 0 h (F1 score = 86.7%) driven by energy metabolites (ATP, ADP, GTP and glucose). No difference was observed in the neutrophil metabolome when treated with JAK inhibitors. However, JAK inhibitors significantly inhibited ROS production and baricitinib decreased NET production (p < 0.05). Bacterial killing was not impaired by JAK inhibitors, indicating that the effect of JAK inhibitors on neutrophils can inhibit joint damage in RA without impairing host defence. This study highlights altered energy metabolism in RA neutrophils which may explain the cause of their dysregulation in inflammatory disease.

Objectives: Activation of neutrophils and release of neutrophil extracellular traps (NETs), proteases and reactive oxygen species (ROS) is pathogenic in immune-mediated inflammatory diseases like rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), driving inflammation and damaging host tissues. The aim of this research was to identify small molecule inhibitors of NET production using a highly curated panel of narrow-spectrum small molecule kinase inhibitors termed the kinase chemogenomic set (KCGS). Methods: Neutrophils were isolated from healthy controls (HC) and people with RA or SLE. Over 220 small molecules were screened for their ability to inhibit NET production and decrease ROS production without impairing neutrophil apoptosis or killing of Staphylococcus aureus bacteria. Results: Fifty compounds, nominally targeting 29 individual protein kinases, were found to inhibit NADPH oxidase 2 (NOX2) -dependent (phorbol 12-myristate 13-acetate-stimulated) and NOX2-independent (A23187-stimulated) NET production (P < 0.05, n = 5 HC, RA and SLE). Of these, seven compounds did not significantly impair ROS production or apoptosis. The deconvoluted targets of these small molecules inhibit kinases that operate in three cellular pathways: autophagy, cell cycle checkpoint and epidermal growth factor tyrosine kinase signalling. Of these, only inhibitors of ULK1, JNK and ROCK1/2, broadly implicated in the regulation of autophagy, did not significantly impair bacterial killing (n = 5 HC, P > 0.05). Autophagy inhibitors were also able to inhibit immune-complex driven NET production (P < 0.05, n = 5 HC, RA and SLE). Conclusion: We propose that autophagy signalling pathways represent novel and exciting targets for the development of small molecule therapeutics to block unwanted neutrophil activation and NET release in immune-mediated inflammatory disease.

Neutrophils play a key role in the pathophysiology of rheumatoid arthritis (RA) where release of ROS and proteases directly causes damage to joints and tissues. Neutrophil function can be modulated by Janus Kinase (JAK) inhibitor drugs, including tofacitinib and baricitinib, which are clinically effective treatments for RA. However clinical trials have reported increased infection rates and transient neutropenia during therapy. The subtle differences in the mode of action, efficacy and safety of JAK inhibitors has been the primary research topic of many clinical trials and systematic reviews, to provide a more precise and targeted treatment to patients. The aim of this study was to determine both the differences in the metabolome of neutrophils from healthy controls and people with RA, and the effect of different JAK inhibitors on the metabolome of healthy and RA neutrophils. Isolated neutrophils from healthy controls (HC) (n=6) and people with RA (n=7) were incubated with baricitinib, tofacitinib or a pan-JAK inhibitor (all 200ng/mL) for 2h. Metabolites were extracted and ¹ H nuclear magnetic resonance (NMR) was applied to study the metabolic changes. Multivariate analyses and machine learning models showed a divergent metabolic pattern in RA neutrophils compared to HC at 0h (F1 score = 86.7%) driven by energy metabolites (ATP, ADP, GTP and glucose). No difference was observed in the neutrophil metabolome when treated with JAK inhibitors. However, JAK inhibitors significantly inhibited ROS production and baricitinib decreased NET production (p<0.05). Bacterial killing was not impaired by JAK inhibitors, indicating the effect of JAK inhibitors on neutrophils can inhibit joint damage in RA without impairing host defence. This study highlights altered energy metabolism in RA neutrophils which may explain the cause of their dysregulation in inflammatory disease.

Objectives: Activation of neutrophils and release of neutrophil extracellular traps (NETs), proteases and reactive oxygen species (ROS) is pathogenic in immune-mediated inflammatory diseases like rheumatoid arthritis (RA) and systemic lupus erythematosus (SLE), driving inflammation and damaging host tissues. The aim of this research was to identify small molecule inhibitors of NET production using a highly-curated panel of narrow-spectrum small molecule kinase inhibitors termed the Kinase Chemogenomic Set (KCGS). Methods: Neutrophils were isolated from healthy controls (HC) and people with RA or SLE. Over 220 small molecules were screened for their ability to inhibit NET production and decrease ROS production without impairing neutrophil apoptosis or killing of S. aureus bacteria. Results: Fifty compounds, nominally targeting 29 individual protein kinase targets, were found to inhibit NOX2-dependent (PMA-stimulated) and NOX2-independent (A23187-stimulated) NET production (p0.05). Autophagy inhibitors were also able to inhibit immune-complex driven NET production (p<0.05, n=5 HC, RA and SLE). Conclusion: We propose that autophagy signalling pathways represent novel and exciting targets for the development of small molecule therapeutics to block unwanted neutrophil activation and NET release in immune-mediated inflammatory disease.

Background/Aims Janus kinase inhibitors (JAKi) including baricitinib and tofacitinib target the JAK/STAT pathway and are clinically effective in treating rheumatoid arthritis (RA). Neutrophils play a key role in the pathophysiology of RA and their function is directly affected by these drugs as shown by clinical trials of JAKi which report increased infection rates and transient neutropenia during therapy. The aim of this work is to determine difference in the metabolome of neutrophils from healthy controls and patients with RA, and the effect of JAKi on the metabolome of healthy and RA neutrophils. Methods Neutrophils were isolated from healthy controls (HC) (n = 10) and patients with RA (n = 10 DMARD-naïve, n = 10 Biologics-naive) and pre-incubated with baricitinib, tofacitinib or a pan-JAK inhibitor (all 200ng/mL) for 2h before snap-freezing. Metabolites were extracted by 50:50 v/v AcN:H₂O and analysed by ¹H NMR spectroscopy using a 700 MHz Avance IIIHD Bruker NMR spectrometer equipped with a TCI cryoprobe. Chenomx, Bruker TopSpin and tameNMR software were used to identify metabolites and process spectra. Statistical analysis and machine learning models were implemented using R and the Mixomics package. Pathway analysis was carried out using Ingenuity (IPA). ROS production in response to 15 min fMLP stimulation was measured using DHR-123 and flow cytometry. Results At 0h, changes in levels of NADP+, NADPH and hypoxanthine in RA neutrophils indicated increased production of ROS via NADPH oxidase and xanthine oxidase compared to HC. Lower levels of glucose and increased levels of lactic acid also suggested increased glycolysis in RA neutrophils compared to HC. However after 2h incubation with JAKi, a difference in the response to these drugs was observed. 80 metabolites were higher in RA neutrophils compared to HC following 2h JAKi treatment. IPA analysis revealed the metabolites higher in RA neutrophils were involved in NAD biosynthesis, NAD phosphorylation/dephosphorylation, amino acid synthesis and transport, and carbohydrate metabolism. Changes in the levels of NADP+, NADPH and hypoxanthine in RA neutrophils indicate that JAKi inhibit ROS production. We therefore confirmed experimentally that JAKi inhibit ROS production in response to fMLP (p < 0.05). IPA also predicted altered neutrophil cell functions including cell death and cell-to-cell signalling. We previously showed that JAKi did not affect the constitutive rate of neutrophil apoptosis, however JAKi significantly inhibit the delay in apoptosis induced by GM-CSF (p < 0.05). No significant difference in the metabolome was observed when comparing tofacinib-treatment and baricitinib-treatment in either the HC or RA patient group. Conclusion The metabolome of RA and HC neutrophils is different at baseline. JAKi alter the levels of intracellular metabolites involved in neutrophil activation and ROS production in RA. This may explain, in part, the efficacy of JAKi in decreasing disease activity and joint damage in RA. Disclosure M. Fresneda Alarcon: None. R. Grosman: None. S. Chokesuwattanaskul: None. M. Phelan: None. H. Wright: None.

Background/Aims Neutrophils contribute to disease pathology in inflammatory diseases including rheumatoid arthritis (RA). Activated RA neutrophils release ROS and proteases which damage joints, and produce neutrophil extracellular traps (NETs) that expose citrullinated nuclear proteins leading to the development of ACPA auto-antibodies. We previously described an altered gene expression signature in RA patients compared to healthy controls. This aim of this work was to use computational modelling of neutrophil transcriptomes to provide novel insight into the physiological factors controlling neutrophil phenotype in RA. Methods RNA from peripheral blood neutrophils (RA patients (DAS28>5.1, cohort 1 n = 23, cohort 2 n = 53), healthy controls (n = 11)) was sequenced using RNAseq. Reads were mapped to the human genome (hg38) using Tophat2 and read counts generated using featureCounts. Partial least squares discriminant analysis (PLS-DA) was carried out using mixOmics (with random sampling and ‘leave one out’ cross-validation). Gene expression network analysis was carried out using tmod, ARACNE2 and GALGO. Gene networks were visualised using Cytoscape. Functional annotation was carried out using Ingenuity Pathway Analysis (IPA) and DAVID. Results PLS-DA modelling discriminated RA and HC neutrophil transcriptomes with an F1 score of 98.2% +/- 1.6% over 5 repetitions using a model with 1 component. Blood transcriptional modular (tmod) enrichment analysis of gene expression in RA and HC neutrophils from cohort 1 identified the gene networks activated in RA and absent in HC as: myeloid cells activated via NFκB, innate antiviral response, type I interferon response, inflammasome receptors and cell signalling (FDR0.8). Cell cycle and growth arrest was also considerably more enriched in RA compared to HC (RA AUC=0.82, HC AUC=0.57). Activation of type I interferon and inflammasome signalling pathways in cohort 1 was confirmed by IPA and correlated closely with data from a second cohort of RA patients (cohort 2). ARACNE2 identified five major gene modules activated in RA neutrophils (MI threshold 0.5, p < 10^-20). IPA and DAVID predicted that Module 1 gene networks regulated amino acid, nucleic acid, carbohydrate and lipid metabolism as well as initiation of gene expression. Module M2 contained a network of genes regulated by integrins and cytokine receptors (e.g. IL-8, JAK/STAT, TNF/NFκB). Module 3 also contained genes activated by NFκB as well as by AMP-protein kinase. Module M4 genes were regulated by activation of type I interferon receptors and pattern recognition receptors (e.g. IRFs, STATs). Module M5 genes regulated amino acid metabolism. Multivariate modelling using GALGO identified genes that predict clinical characteristics, including genes involved in NFκB signalling, apoptosis and kinase activation which were associated with disease activity (DAS28), and cellular stress response genes and chromatin modification that was associated with raised inflammatory markers (ESR, CRP). Conclusion The results of the computational analyses are currently being validated experimentally. Disclosure M. Fresneda Alarcon: None. E. Caamano-Gutierrez: None. P. Antczak: None. R.J. Moots: None. H.L. Wright: Grants/research support; H.W. has received funding from Versus Arthritis and the Masonic Charitable Fund.