Background/PurposeSystemic lupus erythematosus (SLE) is an autoimmune disease often characterized by multiorgan involvement with pain as a prevalent symptom. However, pain severity can differ greatly in each presentation.1 While multi-factorial, one mechanism is related to inflammatory processes which cause nociceptive receptor activation and central nervous system alteration.2 Given the multitude of possible signaling pathways, there are still additional contributing mechanisms and factors that have yet to be fully determined. To add to the growing literature, we analyzed the inflammatory markers of SLE patients to explore their relation to varying degrees of pain.MethodsData from 83 patients was obtained including clinical measurements of: erythrocyte sedimentation rate (ESR), C-reactive protein (CRP), complement component 3 (C3), complement component 4 (C4), antinuclear antibody (ANA), and anti-double stranded DNA (anti-dsDNA). Whole blood analysis of 6 interferon stimulated genes (ISG) from RNA Paxgene tubes was conducted by qPCR. Pain frequency was also recorded using the Thrive Quality of Life Questionnaire, a clinically validated QOL assessment tool.3Patients were stratified into a low-pain group (n = 44) if they reported pain ‘none of the time’ or ‘a little of the time’, or into a high-pain group (n = 39) if they reported pain ‘some of the time’ or ‘all the time’. Analysis was done using unpaired t-tests or chi-squared test as appropriate. Demographics including age of SLE onset and smoking history were also analyzed.ResultsAnalysis showed significant differences in ISG score, CRP, C4, and C3 mean levels between patients reporting high pain compared to low pain. ISG (11.53 vs 8.516, P value 0.0003), CRP (3.710 vs 1.150, P value < 0.0001), and C3 (113.8 vs 95.50, P value 0.0233) mean levels were higher in the high-pain group. C4 (3.710 vs 20.97, P value <0.0001) mean level was lower in the high-pain group. ESR (27.39 vs 27.56, P value 0.9712), ANA (97.80 vs 119.0, P value 0.7350), anti-dsDNA (22.07 vs 16.97, P value 0.2664), and age of onset (26.10 vs 24.46, P value 0.5521). Interestingly, smoking history (ever smoked) was associated with pain (relative risk = 1.74, 95% CI 1.04 to 2.72, P value 0.0136) (figure 1 and table 1).ConclusionOur data shows that higher pain levels were associated with higher ISG scores, a surrogate of immunologic and type I IFN activity in SLE. Studies show that IFNs may cause both analgesia and hyperalgesia by nervous system regulation.4 While looking at other diseases, IFN inhibition correlates with improved pain. For example, in the RA-BEAM trial, baricitinib, a Janus kinase inhibitor which causes known IFN inhibition, had improved pain relief with evidence possibly suggesting at least some effect may be independent of inflammation activity.5 Another notable point is that other markers of disease activity such as high CRP and low C4, were also associated with pain scores. In other studies unrelated to SLE, both smoking and higher CRP levels were seen with increased pain sensitivity.6 Our findings are consistent with data from existing non-SLE pain literature. With the significant difference seen in ISG score, C4, and CRP, it indicates that there is a role for inflammation and potentially type I IFNs in pain experienced by SLE patients. Future work will further explore IFNs as well as additional markers and their relation to SLE pain. 309 Figure 1Scatter dot plot representation of the blood and serum variables between the SLE high-pain and low-pain groups 309 Table 1Demographics information for the SLE high-pain and low-pain groupsReferencesWaldheim, Eva, et al. ‘Variation in Pain Related to Systemic Lupus Erythematosus (SLE): A 7-Year Follow-up Study.’ Clinical Rheumatology, 2018:37(7);1825–1834, https://doi.org/10.1007/s10067-018-4079-1.Nichilatti, Louise P, et al. ‘Physiopathology of Pain in Systemic Erythematosus Lupus.’ Lupus, 2020:29(7);721–726, https://doi.org/10.1177/0961203320919872.Wicks P, McCaffrey S, Goodwin K, Black R, Hoole M, Heywood J. A modular health-related quality of life instrument for electronic assessment and treatment monitoring: web-based development and psychometric validation of core thrive items. J Med Internet Res. 2019 Jan 25:21(1);e12075. doi: 10.2196/12075. PMID: 30681962; PMCID: PMC6367664.Tan, Ping-Heng, et al. ‘Interferons in Pain and Infections: Emerging Roles in Neuro-Immune and Neuro-Glial Interactions.’ Frontiers in Immunology, 2021:12, https://doi.org/10.3389/fimmu.2021.783725.Taylor, Peter C, et al. ‘Achieving pain control in rheumatoid arthritis with baricitinib or adalimumab plus methotrexate: results from the RA-Beam Trial.’ Journal of Clinical Medicine, 2019:8(6);831, https://doi.org/10.3390/jcm8060831.Afari, Niloofar, et al. ‘C-reactive protein and pain sensitivity: findings from female twins.’ Annals of Behavioral Medicine, 2011:42(2);277–283, https://doi.org/10.1007/s12160-011-9297-6.

BackgroundPericarditis is a frequent complication of systemic lupus erythematosus (SLE) with potential for important compromise of cardiac function. Pericarditis is characterized by chest pain, pericardial friction rub, and detectable changes on electrocardiography or transthoracic echocardiogram. Its prevalence in SLE patients ranges from 12% to 56%, and its underlying mechanisms remain poorly understood. Treatment with glucocorticoids is commonly used to resolve pericardial effusions.Methods263 SLE patients with a minimum of 5-years of follow-up were studied, identifying individuals with a history of pericarditis based on clinical presentation and/or documented moderate to severe effusion. Gene expression analysis was conducted on prospectively collected longitudinal blood samples from 15 SLE patients with pericarditis history and 51 SLE patients without such history as controls, totaling 329 blood samples (an average of 5 samples per patient in each group). Differentially expressed genes were identified using limma and lme4 models to account for random effects.ResultsThere were no prominent demographic differences between the patient groups. However, patients of African ancestry were more represented in the pericarditis group (40% vs. 32%). The pericarditis group showed a higher rate of class IV lupus nephritis (27% vs. 16%) and increased incidence of myocardial infarction (4% vs. 1%), cardiomyopathy (6% vs. 1%), and deforming or erosive arthritis (14% vs. 9%), but a lower incidence of diabetes (1% vs. 6%). Gene expression analysis identified 82 differentially expressed genes between the groups (FDR 5%), with the COX7A1 mitochondrial gene being the most significantly downregulated gene in pericarditis patients. Notably, purine metabolism-related genes (FHIT, PAPSS1, PDE9A, GUCY1A2, NT5C3B) were affected among pericarditis patients according to KEGG pathway enrichment analysis. Laboratory data also indicated higher uric acid levels among pericarditis patients (OR 1.68 (0.54–2.81), p=0.006).DiscussionPericarditis has known associations with uremia in gout disease and kidney failure, but a role for uric acid as a primary factor in predisposing SLE patients to pericarditis remains unreported. Interestingly, colchicine, recommended for acute and recurrent pericarditis in the general population, has shown success in treating SLE patients with pericarditis. Moreover, the downregulation of COX7A1 in peripheral blood might reflect the inflamed pericardium and its impaired serosal tissue function among SLE patients with pericarditis.

BackgroundLupus nephritis (LN) is a complication of SLE characterised by immune dysfunction and oxidative stress (OS). Limited options exist for LN. We aimed to identify LN-related OS, highlighting the need for non-invasive diagnostic and therapeutic approaches.MethodsLN-differentially expressed genes (DEGs) were extracted from Gene Expression Omnibus datasets (GSE32591, GSE112943 and GSE104948) and Molecular Signatures Database for OS-associated DEGs (OSEGs). Functional enrichment analysis was performed for OSEGs related to LN. Weighted gene co-expression network analysis identified hub genes related to OS-LN. These hub OSEGs were refined as biomarker candidates via least absolute shrinkage and selection operator. The predictive value was validated using receiver operating characteristic (ROC) curves and nomogram for LN prognosis. We evaluated LN immune cell infiltration using single-sample gene set enrichment analysis and CIBERSORT. Additionally, gene set enrichment analysis explored the functional enrichment of hub OSEGs in LN.ResultsThe study identified four hub genes, namely STAT1, PRODH, TXN2 and SETX, associated with OS related to LN. These genes were validated for their diagnostic potential, and their involvement in LN pathogenesis was elucidated through ROC and nomogram. Additionally, alterations in immune cell composition in LN correlated with hub OSEG expression were observed. Immunohistochemical analysis reveals that the hub gene is most correlated with activated B cells and CD8 T cells. Finally, we uncovered that the enriched pathways of OSEGs were mainly involved in the PI3K-Akt pathway and the Janus kinase-signal transducer and activator of transcription pathway.ConclusionThese findings contribute to advancing our understanding of the complex interplay between OS, immune dysregulation and molecular pathways in LN, laying a foundation for the identification of potential diagnostic biomarkers and therapeutic targets.

BackgroundCranial neuropathies (CN) are a rare neuropsychiatric SLE (NPSLE) manifestation. Previous studies reported that antibodies to the kinesin family member 20B (KIF20B) (anti-KIF20B) protein were associated with idiopathic ataxia and CN. We assessed anti-KIF20B as a potential biomarker for NPSLE in an international SLE inception cohort.MethodsIndividuals fulfilling the revised 1997 American College of Rheumatology (ACR) SLE classification criteria were enrolled from 31 centres from 1999 to 2011 and followed annually in the Systemic Lupus Erythematosus International Collaborating Clinics inception cohort. Anti-KIF20B testing was performed on baseline (within 15 months of diagnosis or first annual visit) samples using an addressable laser bead immunoassay. Logistic regression (penalised maximum likelihood and adjusting for confounding variables) examined the association between anti-KIF20B and NPSLE manifestations (1999 ACR case definitions), including CN, occurring over the first 5 years of follow-up.ResultsOf the 1827 enrolled cohort members, baseline serum and 5 years of follow-up data were available on 795 patients who were included in this study: 29.8% were anti-KIF20B-positive, 88.7% female, and 52.1% White. The frequency of anti-KIF20B positivity differed only for those with CN (n=10) versus without CN (n=785) (70.0% vs 29.3%; OR 5.2, 95% CI 1.4, 18.5). Compared with patients without CN, patients with CN were more likely to fulfil the ACR haematological (90.0% vs 66.1%; difference 23.9%, 95% CI 5.0%, 42.8%) and ANA (100% vs 95.7%; difference 4.3%, 95% CI 2.9%, 5.8%) criteria. In the multivariate analysis adjusting for age at baseline, female, White race and ethnicity, and ACR haematological and ANA criteria, anti-KIF20B positivity remained associated with CN (OR 5.2, 95% CI 1.4, 19.1).ConclusionAnti-KIF20B is a potential biomarker for SLE-related CN. Further studies are needed to examine how autoantibodies against KIF20B, which is variably expressed in a variety of neurological cells, contribute to disease pathogenesis.

ObjectiveTo evaluate the impact of the different types of neoplasms and lineages on mortality of patients with SLE.MethodsRetrospective and observational comparison of the neoplasm-related deaths in patients with SLE and the general Spanish population reported in the Spanish Hospital Discharge Database. To determine the impact of SLE on the risk of dying from each neoplasm lineage, a binary logistic regression considering age, female sex, tobacco and alcohol consumption, was performed.ResultsDuring 2016–2019, 139 531 in-hospital deaths from neoplasms were certified in Spain (91 in patients with SLE). Patients with SLE presented a lower mortality rate from solid organ neoplasms, (80.2% vs 91.1%, OR 0.393), linked to their lower risk of colorectal carcinoma (1.1% vs 10.8%, OR 0.110). By contrast, gynaecological neoplasms presented a higher risk (8.8% vs 3%, OR 3.039) in the deceased patients with SLE, associated with the higher frequency of vulvar neoplasms (2% vs 0.2%, OR 14.767) and cervical carcinomas (3.3% vs 0.5%, OR 3.809). Haematological neoplasm-related deaths were also more prevalent in patients with SLE (19.8% vs 8.9%, OR 2.546), mostly attributable to the higher proportion of deaths due to non-Hodgkin’s lymphoma (11% vs 2.9%, OR 4.060) of B cell lineage (9.9% vs 2.5%, OR 4.133).ConclusionsPatients with SLE present a higher risk of death from vulvar neoplasms, cervical carcinomas and B-cell non-Hodgkin’s lymphoma in comparison with the general Spanish population. In addition to developing strategies that might help to attenuate their occurrence and impact, such as decreasing the immunosuppressive burden, specific early detection programmes for these conditions should be investigated and considered carefully.

To cite: Parodis I. Enhancing lupus outcomes by means of biology beyond overt clinical features, exemplified in an indepth investigation of the effects of circadian rhythm disruption.

ObjectivesX chromosome has been considered as a risk factor for SLE, which is a prototype of autoimmune diseases with a significant sex difference (female:male ratio is around 9:1). Our study aimed at exploring the association of genetic variants in X chromosome and investigating the influence of trisomy X in the development of SLE.MethodsX chromosome-wide association studies were conducted using data from both Thai (835 patients with SLE and 2995 controls) and Chinese populations (1604 patients with SLE and 3324 controls). Association analyses were performed separately in females and males, followed by a meta-analysis of the sex-specific results. In addition, the dosage of X chromosome in females with SLE were also examined.ResultsOur analyses replicated the association of TMEM187-IRAK1-MECP2, TLR7, PRPS2 and GPR173 loci with SLE. We also identified two loci suggestively associated with SLE. In addition, making use of the difference in linkage disequilibrium between Thai and Chinese populations, a synonymous variant in TMEM187 was prioritised as a likely causal variant. This variant located in an active enhancer of immune-related cells, with the risk allele associated with decreased expression level of TMEM187. More importantly, we identified trisomy X (47,XXX) in 5 of 2231 (0.22%) females with SLE. The frequency is significantly higher than that found in the female controls (0.08%; two-sided exact binomial test P=0.002).ConclusionOur study confirmed previous SLE associations in X chromosome, and identified two loci suggestively associated with SLE. More importantly, our study indicated a higher risk of SLE for females with trisomy X.

Systemic lupus erythematosus (SLE) causes a wide range of immune-mediated manifestations in most organ-systems. The presentation of SLE is highly heterogeneous in terms of affected systems, type, and severity of disease features, both between- and within- patients over disease course (SLE disease activity). This complexity hinders the development of Clinical Outcome Assessments (COA) for SLE. Lupus clinical trials evaluate the efficacy of drugs that directly reduce or control disease activity through a mode-of-action that modifies immune processes. Clinical expertise is required to identify and quantify appropriately the treatment-related changes in SLE disease activity. Therefore, a Clinician-Reported Outcome Measure (ClinRO) is required as COA for primary assessment of efficacy in SLE clinical trials. Importantly, the primary endpoint in clinical trials should be patient-focused, that is, must be associated with meaningful impact in the main health aspects of importance to patients that are affected by SLE disease activity. Notably, there is an indirect association between how the patients fell and function and SLE disease activity. The primary endpoint for SLE clinical trials should be a precisely defined variable that is cumulatively able to: (1) capture a direct effect of the study drug in changing the SLE disease activity (with a ClinRO); (2) associate with a meaningful (indirect) impact in the patients’ main health aspects; (3) be statistically analised to address the research question of drug efficacy in the context of use.However, the primary endpoints currently used in SLE clinical trials have well recognized limitations that may have hampered the demonstration of efficacy of many promising drugs in SLE clinical trials. These endpoints are defined as a dichotomous response variable obtained through composite responder indexes, namely the SLE Responder Index (SRI) and the British Isles Lupus Assessment Group (BILAG) Composite Lupus Assessment (BICLA), both aggregating the BILAG, the SLE Disease Activity Index (SLEDAI), and the Physician Global Assessment (PGA). Therefore, novel COA are needed to provide an optimal primary endpoint for lupus clinical trials.The Treatment Response Measure for SLE (TRM-SLE) consortium is in the early phases of a project to develop and validate a novel COA for use in SLE clinical trials. The SLE Disease Activity Score (SLE-DAS) is a novel, easy to use (http://sle-das.eu/), validated ClinRO COA instrument, with high accuracy and sensitivity to change in SLE disease activity. New evidence with validation of thresholds in the context of clinical trials support the interpretation of the SLE-DAS scores into categories of SLE disease activity and treatment targets. These SLE-DAS score categories are concordant with a wide range of health aspects impacted by SLE assessed in Patient-Reported Outcomes (PRO). Importantly, differences in the SLE-DAS scores are sensitive to clinically meaningful and interpretable changes within patients over time in SLE disease activity and reflect an expected impact on patients’ health experiences. There is promising evidence that SLE-DAS is a fit-for-purpose COA and may provide an optimised primary endpoint for lupus clinical trials.

ObjectivesTo assess the minimum effective duration of clinical remission capable of protecting against damage accrual and development of impaired kidney function (IKF) in lupus nephritis (LN)MethodsPatients with biopsy-proven LN and at least 5 years follow-up were enrolled in this study. Sustained Clinical remission (sCR) (henceforth: remission) was defined as eGFR>60 ml/min/1.73m2, proteinuria <0.5g/24h and clinical SLE-disease activity index (cSLEDAI)=0 lasting for at least one year. The duration of remission to prevent IKF (eGFR <60 ml/min per 1.73 m2 (32) for at least 3 months) was estimated through Kaplan-Meier curves and compared by log-rank. Spearman correlation analysis was performed to assess the potential correlation between the yearly increase in SLICC damage index (SD) and the percentage of follow-up spent in remission.Results303 LN patients were included (median follow-up: 14.8 (9.8–22) years) of whom 84.8% achieved sCR lasting 8.6±6.9 years. At the last observation, the increase in SDI from baseline was significantly higher in patients who never achieved vs. those who achieved remission (median: 2 (1–3) vs. 1 (0–1), p=0.003). Consistently, the higher the percentage of follow-up spent in remission, the lower the yearly SDI increase (r=-0.3285, p<0.00001), figure 1. Two-hundred-twenty-five patients had ≥10 years of observation. Among them, 127 were in remission at last observation. Of the remaining 98 patients, 49 (50%) developed IKF. We found that at least 3 years of remission significantly differentiated patients who developed IKF from those who did not: the IKF-free survival at 10 and at 20 years were 93% and 79% in patients with at least 3 years remission in comparison to 67% and 40% in those with less than 3 years of remission (p<0.0001), figure 2.ConclusionsThree years was the minimum duration of sustained remission capable of protecting against development of IKF in patients with LN. Remission protects from overall damage, and the longer the remission the lower the SDI increase. O43 Figure 1Spearman correlation between yearly SDI values and the percent of follow-up in clinical remission for each patient O43 Figure 2CKD free survival curves in patients with at least 3 years of clinical remission and in those with less than 3 years of complete remission

ObjectiveThe assessment and treatment of fatigue remains a major challenge in Systemic Lupus Erythematosus (SLE), especially in patients with no or low disease activity. The aim of session is to provide physicians with a practical algorithm1 for the management of fatigue in SLE, incorporating the patient’s perspective.MethodsData regarding fatigue and common predictors of fatigue, including self-reported disease activity, anxiety, depression, stress, pain and fibromyalgia, levels of physical activity were analyzed in various cohorts of SLE patients, including the use of the novel digital tool Lupus Expert System for the Assessment of Fatigue (LEAF2).ResultsFirst, the intensity and main characteristics of fatigue should be assessed using validated Patient Reported Outcomes Measures (PROMs). Then, common but non-SLE-related causes of fatigue should be ruled out based on medical history, clinical examination and simple laboratory tests. Presence of disease activity or organ damage should be assessed and may explain fatigue in some patients. In those with active disease, remission is the most appropriate therapeutic target while symptomatic support is needed in case of damage. Both anxiety and depression are major independent predictors of fatigue in SLE and require dedicated assessment and care with psychological counselling and pharmacological intervention if needed. ConclusionsIncorporating the patient’s perspective and individuality is key to the successful management of fatigue in SLE. Using a structured algorithm as well as digital tools such as LEAF may help improving the management of one the most common and complex patient complaints in SLE.AcknowledgementsWe would like to thank all participants with Lupus who have been involved in our various studies on fatigue, with a special thanks to Lupus Europe.References Mertz P, Schlencker A, Schneider M, et al. Towards a practical management of fatigue in systemic lupus erythematosus. Lupus Sci Med 2020;7(1):e000441. Kawka L, Sarmiento-Monroy JC, Mertz P, et al. Assessment and personalised advice for fatigue in systemic lupus erythematosus using an innovative digital tool: the Lupus Expert system for the Assessment of Fatigue (LEAF) study. RMD Open 2023;9(4):e003476.