Purpose (the aim of the study): Osteoarthritis (OA) exerts a profound impact on quality of life. In the absence of disease-modifying OA drugs (DMOADs), there is a critical need to unravel the molecular drivers of the disease and discern potential variations among individuals. The advent of large-scale, high-throughput omics-related biotechnologies enable us to address this need at an unprecedented scale. The STEpUP OA (Synovial Fluid To Define Molecular Endotypes by Unbiased Proteomics in Osteoarthritis) consortium was established to answer a primary question of whether distinct molecular OA endotypes exist using large-scale proteomics of knee OA synovial fluid (SF). We hypothesised that molecular endotypes may delineate specific patient groups, thereby influencing diagnosis, predicting disease course, and guiding treatment response.

Purpose (the aim of the study): The molecular mechanisms of osteoarthritis (OA) remain largely unexplained. STEpUP OA (Synovial Fluid To Define Molecular Endotypes by Unbiased Proteomics in Osteoarthritis) is an international consortium which has used SomaLogic SomaScan technology to measure over 7000 proteins in the synovial fluid (SF) from >1700 individuals with OA or following joint injury. This has generated an unprecedented molecular and clinical data resource with which to interrogate molecules and pathways associated with disease. As part of this work, we set out to compare the SF proteomic profiles of individuals with advanced and non-advanced radiographic knee OA.

Background Osteoarthritis (OA) has a lifetime risk of over 40%, imposing a huge societal burden. Clinical variability suggests that it could be more than one disease. Synovial fluid To detect Endotypes by Unbiased Proteomics in OA (STEpUP OA) was established to test the hypothesis that there are detectable distinct molecular endotypes in knee OA. Methods OA knee synovial fluid (SF) samples (N=1361) were from pre-existing OA cohorts with cross-sectional clinical (radiographic and pain) data. Samples were divided into Discovery (N = 708) and Replication (N=653) datasets. Proteomic analysis was performed using SomaScan V4.1 assay (6596 proteins). Unsupervised clustering was performed using k-means, assessed using the f(k) metric, with and without adjustments for potential confounders. Regression analyses were used to assess protein associations with radiographic (Kellgren and Lawrence) and knee pain (WOMAC pain), with and without stratification by body mass index (BMI) or biological sex. Adjustments were made for cohort (random intercept) or intracellular protein, using an intracellular protein score (IPS). Analyses were carried out in R according to a pre-published plan. Results No distinct SF molecular endotypes were identified in OA but two indistinct clusters were defined in non-IPS regressed data which were stable across subgroup analyses. Clustering was lost after IPS regression adjustment. Strong, replicable protein associations were observed with radiographic disease severity, which were retained after adjustment for cohort or IPS. Pathway analysis identified a strong epithelial to mesenchymal transition (EMT) pathway, and weaker associations with angiogenesis, complement and coagulation. The latter were variably lost after adjustment for BMI or biological sex. Associations with patient reported pain were weaker. Conclusion These data support knee OA as a biologically continuous disease in which disease severity is associated with a strong, robust, tissue remodelling signature. Subtle differences were found in pathways after stratification by BMI or sex.### Competing Interest StatementTAP, YD, PH, SL, AS, NKA, AJP, DF, MK, BM, AMV and SK declare no conflicts of interest. FW has received consultancy fees from Pfizer. LSL has received consultancy fees from Arthro Therapeutics AB, and is an advisory board member of AstraZeneca. LJD has received consultancy fees from Nightingale Health PLC. TLV has no conflicts to declare with the exception of grant income for STEpUP OA from industry partners (see above). RAM is a shareholder of AstraZeneca. SB and JM are employees and shareholders of Novartis. CTA has received consultancy fees from Novartis, and has received honoraria for educational purposes also from Novartis. TJW is a shareholder of Chondropeptix BV. DAW has received consultancy fees from GlaxoSmithKline plc, AKL Research & Development Limited, Pfizer Ltd, Eli Lilly and Company, Contura International, and AbbVie Inc, has received honoraria for educational purposes from Pfizer Ltd and AbbVie Inc, is a board member (Director) of UKRI and Versus Arthritis Advanced Pain Discovery Platform. ### Funding StatementThe study was supported by Kennedy Trust for Rheumatology Research (grant number: 171806), Versus Arthritis (grant number: 22473), Centre for Osteoarthritis Pathogenesis Versus Arthritis (grant numbers: 21621, 20205), Galapagos, Biosplice, Novartis, Fidia, UCB, Pfizer (non-consortium member) and Somalogic (in kind contributions). The funders Kennedy Trust for Rheumatology Research, Versus Arthritis and Pfizer had no role in the study design, data collection and analysis, decision to publish or preparation of the manuscript. The funders Galapagos, Biosplice, Novartis, Fidia, UCB and SomaLogic were all active consortium members, attending consortium meetings. As such they made contributions to the study design and support of data collection, decision to publish and review and commenting on the manuscript. In addition, SomaLogic, UCB and Novartis were members of the Data Analysis Group.### Author DeclarationsI confirm all relevant ethical guidelines have been followed, and any necessary IRB and/or ethics committee approvals have been obtained.YesThe details of the IRB/oversight body that provided approval or exemption for the research described are given below:University of Oxford Medical Sciences Central University Research Ethics Committee (CUREC) granted ethical approval for the processing, storage and use of samples and linked data for this project on 1st November 2019 (R67029/RE001).I confirm that all necessary patient/participant consent has been obtained and the appropriate institutional forms have been archived, and that any patient/participant/sample identifiers included were not known to anyone (e.g., hospital staff, patients or participants themselves) outside the research group so cannot be used to identify individuals.YesI understand that all clinical trials and any other prospective interventional studies must be registered with an ICMJE-approved registry, such as ClinicalTrials.gov. I confirm that any such study reported in the manuscript has been registered and the trial registration ID is provided (note: if posting a prospective study registered retrospectively, please provide a statement in the trial ID field explaining why the study was not registered in advance).YesI have followed all appropriate research reporting guidelines, such as any relevant EQUATOR Network research reporting checklist(s) and other pertinent material, if applicable.YesThe minimal datasets upon which this data relies and all R code, including the html vignette, are available at https://github.com/ndorms-tperry/STEpUP-OA-Primary-Manuscript. The full STEpUP OA dataset may be made available by application to the Data Access and Publication Group of STEpUP OA (stepupoa@kennedy.ox.ac.uk) once the primary analysis manuscript is published, in accordance with what is stipulated in our Consortium Agreement. This may attract an access fee to cover administrative processing. Neither the minimal dataset nor the full STEpUP OA dataset include patient identifiable data.

Objectives To develop a protocol for largescale analysis of synovial fluid proteins, for the identification of biological networks associated with subtypes of osteoarthritis. Methods Synovial Fluid To detect molecular Endotypes by Unbiased Proteomics in Osteoarthritis (STEpUP OA) is an international consortium utilising clinical data (capturing pain, radiographic severity and demographic features) and knee synovial fluid from 17 participating cohorts. 1746 samples from 1650 individuals comprising OA, joint injury, healthy and inflammatory arthritis controls, divided into discovery (n = 1045) and replication (n = 701) datasets, were analysed by SomaScan Discovery Plex V4.1 (>7000 SOMAmers/proteins). An optimised approach to standardisation was developed. Technical confounders and batch-effects were identified and adjusted for. Poorly performing SOMAmers and samples were excluded. Variance in the data was determined by principal component (PC) analysis. Results A synovial fluid standardised protocol was optimised that had good reliability (<20% co-efficient of variation for >80% of SOMAmers in pooled samples) and overall good correlation with immunoassay. 1720 samples and >6290 SOMAmers met inclusion criteria. 48% of data variance (PC1) was strongly correlated with individual SOMAmer signal intensities, particularly with low abundance proteins (median correlation coefficient 0.70), and was enriched for nuclear and non-secreted proteins. We concluded that this component was predominantly intracellular proteins, and could be adjusted for using an ‘intracellular protein score’ (IPS). PC2 (7% variance) was attributable to processing batch and was batch-corrected by ComBat. Lesser effects were attributed to other technical confounders. Data visualisation revealed clustering of injury and OA cases in overlapping but distinguishable areas of high-dimensional proteomic space. Conclusions We have developed a robust method for analysing synovial fluid protein, creating a molecular and clinical dataset of unprecedented scale to explore potential patient subtypes and the molecular pathogenesis of OA. Such methodology underpins the development of new approaches to tackle this disease which remains a huge societal challenge.

Purpose: The STEpUP OA consortium (Synovial Fluid To Define Molecular Endotypes by Unbiased Proteomics in Osteoarthritis) was set up with a primary objective to address whether OA is a single disease or made up of multiple distinct molecular endotypes, when examining large scale (SomaLogic) proteomic profiling of synovial fluid (SF) from multiple cohorts. Assay of SF as a discovery matrix using this technology (as opposed to serum/plasma) has not been previously reported other than in small sample numbers and early versions of the array.

Regulatory T cells (Treg cells) are instrumental in establishing immunological tolerance. However, the precise effector mechanisms by which Treg cells control a specific type of immune response in a given tissue remains unresolved. By simultaneously studying Treg cells from different tissue origins under systemic autoimmunity, in the present study we show that interleukin (IL)-27 is specifically produced by intestinal Treg cells to regulate helper T17 cell (TH17 cell) immunity. Selectively increased intestinal TH17 cell responses in mice with Treg cell-specific IL-27 ablation led to exacerbated intestinal inflammation and colitis-associated cancer, but also helped protect against enteric bacterial infection. Furthermore, single-cell transcriptomic analysis has identified a CD83+CD62Llo Treg cell subset that is distinct from previously characterized intestinal Treg cell populations as the main IL-27 producers. Collectively, our study uncovers a new Treg cell suppression mechanism crucial for controlling a specific type of immune response in a particular tissue and provides further mechanistic insights into tissue-specific Treg cell-mediated immune regulation.

Chronic airway diseases including chronic obstructive pulmonary disease (COPD) and asthma are heterogenous in nature and endotypes within are underpinned by complex biology. This study aimed to investigate the utility of proteomic profiling of plasma combined with bioinformatic mining, and to define molecular endotypes and expand our knowledge of the underlying biology in chronic respiratory diseases. The plasma proteome was evaluated using an aptamer-based affinity proteomics platform (SOMAscan®), representing 1238 proteins in 34 subjects with stable COPD and 51 subjects with stable but severe asthma. For each disease, we evaluated a range of clinical/demographic characteristics including bronchodilator reversibility, blood eosinophilia levels, and smoking history. We applied modified bioinformatic approaches used in the evaluation of RNA transcriptomics. Subjects with COPD and severe asthma were distinguished from each other by 365 different protein abundancies, with differential pathway networks and upstream modulators. Furthermore, molecular endotypes within each disease could be defined. The protein groups that defined these endotypes had both known and novel biology including groups significantly enriched in exosomal markers derived from immune/inflammatory cells. Finally, we observed associations to clinical characteristics that previously have been under-explored. This investigational study evaluating the plasma proteome in clinically-phenotyped subjects with chronic airway diseases provides support that such a method can be used to define molecular endotypes and pathobiological mechanisms that underpins these endotypes. It provided new concepts about the complexity of molecular pathways that define these diseases. In the longer term, such information will help to refine treatment options for defined groups.

Innate lymphoid cells (ILCs) are enriched in mucosae and have been described as tissue-resident. Interestingly, ILCs are also present within lymph nodes (LNs), in the interfollicular regions, the destination for lymph-migratory cells. We have previously shown that LN ILCs are supplemented by peripheral tissue-derived ILCs. Using thoracic duct cannulations, we here enumerate the intestinal lymph ILCs that traffic from the intestine to the mesenteric LNs (MLNs). We provide, for the first time, a detailed characterisation of these lymph-migratory ILCs. We show that all ILC subsets migrate in lymph, and while global transcriptional analysis reveals a shared signature with tissue-resident ILCs, lymph ILCs express migration-associated genes including S1PRs, SELL (CD62L) and CCR7. Interestingly, we discovered that while Salmonella Typhimurium infections do not increase the numbers of migrating ILCs, infection changes their composition and cytokine profile. Infection increases the proportions of RORyt+ T-bet+ ILCs, levels of IFNγ, and IFNγ/GM-CSF co-expression. Infection-induced changes in migratory ILCs are reflected in colon-draining MLN ILCs, where RORyt+ T-bet+ ILCs accumulate and display corresponding increased cytokine expression. Thus, we reveal that ILCs respond rapidly to intestinal infection and can migrate to the MLN where they produce cytokines.

Background The airway epithelium is a major target tissue in respiratory infections, and its antiviral response is mainly orchestrated by the interferon regulatory factor-3 (IRF3), which subsequently induces type I (β) and III (λ) interferon (IFN) signalling. Dual specificity mitogen-activated protein kinase kinase (MEK) pathway contributes to epithelial defence, but its role in the regulation of IFN response in human primary airway epithelial cells (AECs) is not fully understood. Here, we studied the impact of a small-molecule inhibitor (MEKi) on the IFN response following challenge with two major respiratory viruses rhinovirus (RV2) and respiratory syncytial virus (RSVA2) and a TLR3 agonist, poly(I:C). Methods The impact of MEKi on viral load and IFN response was evaluated in primary AECs with or without a neutralising antibody against IFN-β. Quantification of viral load was determined by live virus assay and absolute quantification using qRT-PCR. Secretion of cytokines was determined by AlphaLISA/ELISA and expression of interferon-stimulated genes (ISGs) was examined by qRT-PCR and immunoblotting. A poly(I:C) model was also used to further understand the molecular mechanism by which MEK controls IFN response. AlphaLISA, siRNA-interference, immunoblotting, and confocal microscopy was used to investigate the effect of MEKi on IRF3 activation and signalling. The impact of MEKi on ERK and AKT signalling was evaluated by immunoblotting and AlphaLISA. Results Here, we report that pharmacological inhibition of MEK pathway augments IRF3-driven type I and III IFN response in primary human AECs. MEKi induced activation of PI3K-AKT pathway, which was associated with phosphorylation/inactivation of the translational repressor 4E-BP1 and activation of the protein synthesis regulator p70 S6 kinase, two critical translational effectors. Elevated IFN-β response due to MEKi was also attributed to decreased STAT3 activation, which consequently dampened expression of the transcriptional repressor of IFNB1 gene, PRDI-BF1. Augmented IFN response translated into inhibition of rhinovirus 2 replication in primary AECs but not respiratory syncytial virus A2. Conclusions Our findings unveil MEK as a key molecular mechanism by which rhinovirus dampens the epithelial cell’s antiviral response. Our study provides a better understanding of the role of signalling pathways in shaping the antiviral response and suggests the use of MEK inhibitors in anti-viral therapy against RV.

Epithelial cell proliferation, division, and differentiation are critical for barrier repair following inflammation, but the initial trigger for this process is unknown. Here we define that sensing of apoptotic cells by the TAM receptor tyrosine kinase Axl is a critical indicator for tracheal basal cell expansion, cell cycle reentry, and symmetrical cell division. Furthermore, once the pool of tracheal basal cells has expanded, silencing of Axl is required for their differentiation. Genetic depletion of Axl triggers asymmetrical cell division, leading to epithelial differentiation and ciliated cell regeneration. This discovery has implications for conditions associated with epithelial barrier dysfunction, basal cell hyperplasia, and continued turnover of dying cells in patients with chronic inflammatory pulmonary diseases.

Introduction HRV infections cause asthma exacerbations, while HRV-induced wheezing in pre-school children is associated with asthma development in later life. Molecular mechanisms underlying this pathophysiology remain elusive, while HRV-C is increasingly associated with disease severity. Transcriptomic analysis of human respiratory (nasal) epithelia from an in vivo HRV-C infection model revealed changes in expression of cellular Serine/Arginine Protein Kinase 1 (SRPK1) and its substrates, the Serine/Arginine Splicing Factors (SRSFs) suggesting that HRV infection targets pre-mRNA splicing and/or its regulating factors. Hypothesis 1) HRV splicing modulation results in host transcriptome changes, leading to impaired anti-viral responses and/or immunoregulation; 2) HRV-induced changes to SR proteins result in enhanced HRV-translation and replication. Methods HRV-A RNA was synthesised by in-vitro transcription from pRV16.11. HRV replication was measured by RT-qPCR and titration in HeLa cells. Protein expression was monitored by western blotting and confocal microscopy. SPRIN340 was used as a specific SRPK1 inhibitor. Alternatively, SRPK1 was depleted via siRNA interference. Results 1) SRPK1, SRSF1-6 and SRSF9 are expressed in both A549 and HeLa cells; levels were greater in the latter. 2) SRPIN340 and siSRPK1 treatments decrease the levels of SRPK1 leading to decreased expression of SRSFs in HeLa and A549 cells. 3) HRV16 infection decreased SRPK1, SRSF1-6 and SRSF9 expression in HeLa and A549 cells. Conclusion Our initial data suggest that HRV-infection specifically alters molecules involved in pre-mRNA splicing, providing us with insights into the molecular mechanisms underlying the distinct pathology of HRV infection, as well as the aetiology of HRV-associated asthma.

Asthma exacerbations are triggered by rhinovirus infections. We employed a systems biology approach to delineate upper-airway gene network patterns underlying asthma exacerbation phenotypes in children. Cluster analysis unveiled distinct IRF7hi versus IRF7lo molecular phenotypes, the former exhibiting robust upregulation of Th1/type I IFN responses and the latter an alternative signature marked by upregulation of cytokine and growth factor signaling and downregulation of IFN-γ. The two phenotypes also produced distinct clinical phenotypes. For IRF7lo children, symptom duration prior to hospital presentation was more than twice as long from initial symptoms (p = 0.011) and nearly three times as long for cough (p < 0.001), the odds ratio of admission to hospital was increased more than 4-fold (p = 0.018), and time to recurrence was shorter (p = 0.015). In summary, our findings demonstrate that asthma exacerbations in children can be divided into IRF7hi versus IRF7lo phenotypes with associated differences in clinical phenotypes.