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Objective: Mechanisms underpinning clinical evolution to systemic lupus erythematosus (SLE) from preceding antinuclear antibodies (ANA) positivity are poorly understood. This study aimed to understand blood immune cell transcriptional signatures associated with subclinical ANA positivity, and progression or non-progression to SLE., Methods: Bulk RNA-sequencing of peripheral blood mononuclear cells isolated at baseline from 35 ANA positive (ANA+) subjects with non-diagnostic symptoms was analysed using differential gene expression, weighted gene co-expression network analysis, deconvolution of cell subsets and functional enrichment analyses. ANA+ subjects, including those progressing to classifiable SLE at 12 months (n=15) and those with stable subclinical ANA positivity (n=20), were compared with 15 healthy subjects and 18 patients with SLE., Results: ANA+ subjects demonstrated extensive transcriptomic dysregulation compared with healthy controls with reduced CD4+naïve T-cells and resting NK cells, but higher activated dendritic cells. B-cell lymphopenia was evident in SLE but not ANA+ subjects. Two-thirds of dysregulated genes were common to ANA+ progressors and non-progressors. ANA+ progressors showed elevated modular interferon signature in which constituent genes were inducible by both type I interferon (IFN-I) and type II interferon (IFN-II) in vitro. Baseline downregulation of mitochondrial oxidative phosphorylation complex I components significantly associated with progression to SLE but did not directly correlate with IFN modular activity. Non-progressors demonstrated more diverse cytokine profiles., Conclusions: ANA positivity, irrespective of clinical trajectory, is profoundly dysregulated and transcriptomically closer to SLE than to healthy immune function. Metabolic derangements and IFN-I activation occur early in the ANA+ preclinical phase and associated with diverging transcriptomic profiles which distinguish subsequent clinical evolution., Competing Interests: Competing interests: LMC has received consultancy fees from UCB and Alumis. MYMY has received consultancy fees from Aurinia Pharmaceuticals and UCB and speaker fees from Alumis, Roche and Novartis. EMV has received consultancy fees from Roche, GSK, AstraZeneca, Aurinia Pharmaceuticals, Lilly and Novartis. He has also received research grants paid to his employer from Roche, AstraZeneca and Sandoz. All other authors have declared no competing interests., (© Author(s) (or their employer(s)) 2024. No commercial re-use. See rights and permissions. Published by BMJ on behalf of EULAR.)

Efficacy to biologics in rheumatoid arthritis (RA) patients is variable and is likely influenced by each patient's circulating drug levels. Using modelling and simulation, the aim of this study was to investigate whether adalimumab and etanercept biosimilar dosing intervals can be altered to achieve therapeutic drug levels at a faster/similar time compared to the recommended interval. RA patients starting subcutaneous Amgevita or Benepali (adalimumab and etanercept biosimilars, respectively) were recruited and underwent sparse serum sampling for drug concentrations. Drug levels were measured using commercially available kits. Pharmacokinetic data were analysed using a population approach (popPK) and potential covariates were investigated in models. Models were compared using goodness-of-fit criteria. Final models were selected and used to simulate alternative dosing intervals. Ten RA patients starting the adalimumab biosimilar and six patients starting the etanercept biosimilar were recruited. One-compartment PK models were used to describe the popPK models for both drugs; no significant covariates were found. Typical individual parameter estimates were used to simulate altered dosing intervals for both drugs. A simulation of dosing the etanercept biosimilar at a lower rate of every 10 days reached steady-state concentrations earlier than the usual dosing rate of every 7 days. Simulations of altered dosing intervals could form the basis for future personalised dosing studies, potentially saving costs whilst increasing efficacy.

Objective: There is growing evidence that genetic data are of benefit in the rheumatology outpatient setting by aiding early diagnosis. A genetic probability tool (G-PROB) has been developed to aid diagnosis has not yet been tested in a real-world setting. Our aim was to assess whether G-PROB could aid diagnosis in the rheumatology outpatient setting using data from the Norfolk Arthritis Register (NOAR), a prospective observational cohort of patients presenting with early inflammatory arthritis., Methods: Genotypes and clinician diagnoses were obtained from patients from NOAR. Six G-probabilities (0%-100%) were created for each patient based on known disease-associated odds ratios of published genetic risk variants, each corresponding to one disease of rheumatoid arthritis, systemic lupus erythematosus, psoriatic arthritis, spondyloarthropathy, gout, or "other diseases." Performance of the G-probabilities compared with clinician diagnosis was assessed., Results: We tested G-PROB on 1,047 patients. Calibration of G-probabilities with clinician diagnosis was high, with regression coefficients of 1.047, where 1.00 is ideal. G-probabilities discriminated clinician diagnosis with pooled areas under the curve (95% confidence interval) of 0.85 (0.84-0.86). G-probabilities <5% corresponded to a negative predictive value of 96.0%, for which it was possible to suggest >2 unlikely diseases for 94% of patients and >3 for 53.7% of patients. G-probabilities >50% corresponded to a positive predictive value of 70.4%. In 55.7% of patients, the disease with the highest G-probability corresponded to clinician diagnosis., Conclusion: G-PROB converts complex genetic information into meaningful and interpretable conditional probabilities, which may be especially helpful at eliminating unlikely diagnoses in the rheumatology outpatient setting., (© 2023 The Authors. Arthritis & Rheumatology published by Wiley Periodicals LLC on behalf of American College of Rheumatology.)

Objectives: Biologic DMARDs (bDMARDs) are widely used in patients with RA, but response to bDMARDs is heterogeneous. The objective of this work was to identify pretreatment proteomic biomarkers associated with RA clinical outcome measures in patients starting bDMARDs., Methods: Sequential window acquisition of all theoretical fragment ion spectra mass spectrometry (SWATH-MS) was used to generate spectral maps of sera from patients with RA before and after 3 months of treatment with the bDMARD etanercept. Protein levels were regressed against RA clinical outcome measures, i.e. 28-joint DAS (DAS28) and its subcomponents and DAS28 <2.6 (i.e. remission). The proteins with the strongest evidence for association were analysed in an independent, replication dataset. Finally, subnetwork analysis was carried out using the Disease Module Detection algorithm and biological plausibility of identified proteins was assessed by enrichment analysis., Results: A total of 180 patients with RA were included in the discovery dataset and 58 in the validation dataset from a UK-based prospective multicentre study. Ten individual proteins were found to be significantly associated with RA clinical outcome measures. The association of T-complex protein 1 subunit η with DAS28 remission was replicated in an independent cohort. Subnetwork analysis of the 10 proteins from the regression analysis identified the ontological theme, with the strongest associations being with acute phase and acute inflammatory responses., Conclusion: This longitudinal study of 180 patients with RA commencing etanercept has identified several putative protein biomarkers of treatment response to this drug, one of which was replicated in an independent cohort., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Objective: To investigate the association between socioeconomic deprivation and outcomes following TNF inhibitor (TNFi) treatment., Methods: Individuals commencing their first TNFi in the British Society for Rheumatology Biologics Register for RA (BSRBR-RA) and Biologics in RA Genetics and Genomics Study Syndicate (BRAGGSS) cohort were included. Socioeconomic deprivation was proxied using the Index of Multiple Deprivation and categorized as 20% most deprived, middle 40% or 40% least deprived. DAS28-derived outcomes at 6 months (BSRBR-RA) and 3 months (BRAGGSS) were compared using regression models with the least deprived as referent. Risks of all-cause and cause-specific drug discontinuation were compared using Cox models in the BSRBR-RA. Additional analyses adjusted for lifestyle factors (e.g. smoking, BMI) as potential mediators., Results: 16 085 individuals in the BSRBR-RA were included (mean age 56 years, 76% female), of whom 18%, 41% and 41% were in the most, middle and least deprived groups, respectively. Of 3459 included in BRAGGSS (mean age 57, 77% female), proportions were 22%, 36% and 41%, respectively. The most deprived group had 0.3-unit higher 6-month DAS28 (95% CI 0.22, 0.37) and were less likely to achieve low disease activity (odds ratio [OR] 0.76; 95% CI 0.68, 0.84) in unadjusted models. Results were similar for 3-month DAS28 (β = 0.23; 95% CI 0.11, 0.36) and low disease activity (OR 0.77; 95% CI 0.63, 0.94). The most deprived were more likely to discontinue treatment (hazard ratio 1.18; 95% CI 1.12, 1.25), driven by ineffectiveness rather than adverse events. Adjusted estimates were generally attenuated., Conclusion: Socioeconomic deprivation is associated with reduced response to TNFi. Improvements in determinants of health other than lifestyle factors are needed to address socioeconomic inequities., (© The Author(s) 2023. Published by Oxford University Press on behalf of the British Society for Rheumatology.)

Objective: Genome-wide association studies have successfully identified more than 100 loci associated with susceptibility to rheumatoid arthritis (RA). However, our understanding of the functional effects of genetic variants in causing RA and their effects on disease severity and response to treatment remains limited., Methods: In this study, we conducted expression quantitative trait locus (eQTL) analysis to dissect the link between genetic variants and gene expression comparing the disease tissue against blood using RNA-Sequencing of synovial biopsies (n=85) and blood samples (n=51) from treatment-naïve patients with RA from the Pathobiology of Early Arthritis Cohort., Results: This identified 898 eQTL genes in synovium and genes loci in blood, with 232 genes in common to both synovium and blood, although notably many eQTL were tissue specific. Examining the HLA region, we uncovered a specific eQTL at HLA-DPB2 with the critical triad of single-nucleotide polymorphisms (SNPs) rs3128921 driving synovial HLA-DPB2 expression, and both rs3128921 and HLA-DPB2 gene expression correlating with clinical severity and increasing probability of the lympho-myeloid pathotype., Conclusions: This analysis highlights the need to explore functional consequences of genetic associations in disease tissue. HLA-DPB2 SNP rs3128921 could potentially be used to stratify patients to more aggressive treatment immediately at diagnosis., Competing Interests: Competing interests: None declared., (© Author(s) (or their employer(s)) 2024. Re-use permitted under CC BY. Published by BMJ.)