Introduction:Systemic Lupus Erythematosus (SLE) exhibits a pronounced sex bias, affecting females approximately nine times more frequently than males; however, males tend to experience a more severe clinical course yet the molecular basis for these differences remains unclear. Methods:Leveraging epigenomic, transcriptomic, and proteomic data from the whole blood of 720 SLE patients (679 females, 41males) and 84 healthy controls (77 females, 7 males), we conducted comprehensive multi-omic analyses to identify sex-specific molecular features of this disease. Specifically, differential expression analysis for each modality was conducted using a factorial design to identify differences between disease and healthy controls (SLE-HC) for each sex, as well as the interaction effects between sex and disease ([Male SLE - Male HC] - [Female SLE - Female HC]). Benjamini & Hochberg false discovery rate (FDR) was used for multiple test correction. Results:The strongest signal differentiating males and females with SLE was the aberrant expression of the long non-coding RNA, XIST, in males. This XIST expression in males with SLE was bimodal, with 54% of males having elevated XIST expression, and correlated with disease severity. Males with SLE also exhibited significant hypermethylation of the X chromosome and transcriptional silencing of X-linked genes - hallmarks of X-chromosome inactivation (XCI), a process typically restricted to females. Conclusion:These results suggest that X-chromosome silencing by XIST may contribute to SLE disease in males.

BACKGROUND:Baricitinib has previously been shown to improve clinical response in patients with juvenile idiopathic arthritis (JIA) in the JUVE-BASIS trial. In this post-hoc analysis we aimed to identify whether pharmacodynamic changes in serum biomarkers in response to baricitinib treatment could help reaffirm the clinical utility of baricitinib in patients with JIA. METHODS:JUVE-BASIS was a randomised, double-blind, placebo-controlled, withdrawal, efficacy, safety, phase 3 trial, done in 75 centres in 20 countries. Eligible patients were children and adolescents (aged 2 to <18 years), with polyarticular JIA (positive or negative for rheumatoid factor), extended oligoarticular JIA, enthesitis-related arthritis, or juvenile psoriatic arthritis, as per the International League of Associations for Rheumatology criteria and an inadequate response (≥12 weeks) or intolerance to one or more conventional synthetic or biological disease-modifying antirheumatic drugs (DMARDs). Here we report post-hoc analyses of serum samples from patients who received open-label baricitinib in the 12-week lead-in period of the JUVE-BASIS trial. Samples were assessed using an Olink Explore 3072 panel at baseline and week 12. Baricitinib-mediated pharmacodynamic changes in serum protein markers were measured as changes from baseline to week 12 derived from a mixed model with repeated measurement. Pearson correlations of the change in serum biomarkers and clinical disease activity (JADAS-27 scores) comparing baseline with week 12 were examined. Proportional changes in biomarkers were classified into three response subsets based on JIA-ACR response rates: JIA-ACR <30% (non-responders), JIA-ACR 30-70% (responders), and JIA-ACR 70-100% (super-responders). People with lived experience of JIA were not involved in the design or conduct of this study. The JUVE-BASIS trial was registered with ClinicalTrials.gov, NCT03773978, and is completed. FINDINGS:Between Dec 17, 2018 and March 3, 2021, 220 patients were enrolled in JUVE-BASIS and received at least one dose of baricitinib in the open-label lead-in period. In this post-hoc analysis, 168 serum samples from 84 patients were analysed: 67 (80%) of 84 patients were female, 17 (20%) were male, 67 (80%) were White and the mean age was 14 years (SD 2). 10 (12%) of 84 were non-responders, 27 (32%) were responders, and 47 (56%) were super-responders based on clinical response. Several serum biomarkers showed significant changes following 12 weeks of baricitinib treatment for all patients with higher magnitude changes seen in responders and super-responders. Changes in biomarkers associated with macrophage activation (CCL7, CCL18, and IL-6) and regulation of matrix composition (matrix metalloproteinase-3) were positively correlated with clinical response. INTERPRETATION:To our knowledge, this is the first study measuring serum protein markers in the context of an intervention trial with baricitinib in patients with JIA. Associated biomarker changes with clinical response might allow physicians to potentially identify patients who are most likely to be responsive to baricitinib treatment. FUNDING:Eli Lilly and Company under licence from Incyte.

Ixekizumab (IXE), an IL-17A antagonist, and guselkumab (GUS), an IL-23p19 antagonist, are common psoriasis treatments. This longitudinal analysis assessed gene expression profiles in IXE- and GUS-treated patients with plaque psoriasis through week 4. In IXORA-R (NCT03573323), a head-to-head phase 4 study, adults with moderate-to-severe plaque psoriasis were assigned 1:1 to receive IXE or GUS. RNA expression was assessed in lesional tissue (n=72) from IXE-treated patients, GUS-treated patients, and healthy control groups (199 samples in total). Empirical Bayes was used to model RNA-sequencing data; differential expression was analyzed by tissue type, treatment, and time point, correcting for random effects. At week 1, lesions from IXE-treated patients had greater numbers of differentially expressed genes (392 upregulated, 696 downregulated) than those from GUS-treated patients (0 upregulated 0 downregulated). By week 4, the numbers of differentially expressed genes increased in both groups (IXE: 1882 upregulated, 1649 downregulated; GUS: 318 upregulated, 131 downregulated). Molecular shifts from baseline to week 4 occurred earlier with greater magnitude in IXE- than in GUS-treated patients. Rapid normalization of transcriptomic changes in patients receiving an IL-17A antagonist reflected downregulation of key inflammatory genes in psoriatic epidermis. Differentially expressed genes involved in epidermal IL-17A and IL-36 responses correlated with PASI 100 response.

PT022 / #742 Topic: AS12 - Genetics, Epigenetics, Transcriptomics POSTER TOUR 05: SLE PATHOGENESIS 24-05-2025 10:00 AM - 10:20 AM Systemic lupus erythematosus (SLE) exhibits a pronounced female-biased imbalance in disease prevalence, with a female-to-male ratio of 9:1. Although the exact mechanisms remain unclear, the significant role of X-chromosome dosage is supported by karyotypic risks associated with SLE. This study utilizes paired transcriptomic (RNAseq), proteomic (Olink), and epigenomic (EMSeq) data from large phase 3 trials to gain mechanistic insights into the drivers behind the sexual bias in SLE. Baseline RNAseq, Olink, and EMseq data were collected from the whole blood of 722 SLE patients (680 female, 42 male) and 84 healthy controls (77 female, 7 male) from 2 phase 3 clinical trials (NCT03616964, NCT03616912). Differential expression analysis was performed using a factorial design to calculate the following comparisons for each modality: i) SLE vs healthy controls in females, ii) SLE vs healthy controls in males, and iii) interaction between sex and disease. Gene set enrichment analysis (GSEA) of patient subsets was conducted using Gene Ontology (GO) biological process terms. To ensure our cohort did not contain erroneous results due to Klinefelter’s males, we inferred X-chromosome heterozygosity by calculating the read depth of the X-chromosome from the EMseq bam files. To validate our results, we performed similar differential expression analysis on EMseq data from an independent cohort of SLE patients (241 females, 13 males) from 2 additional phase 3 clinical trials (NCT01205438, NCT01196091). The strongest changes differentiating how sexes respond to disease were observed in the expression of lncRNA XIST (X-inactive specific transcript) and epigenetics. Specifically, we noted an increased expression of XIST in males with SLE compared to healthy controls (Figure 1A), with this expression exhibiting a bimodal distribution (Figure 1B). GSEA indicated that males with high XIST expression exhibit enrichment in biological processes (GO) related to metabolism and immunoglobulin production, such as oxidative phosphorylation, B cell mediated immunity, and immunoglobulin production compared to XIST low males. Consistent with XIST’s known role in X-chromosome inactivation, we observed corresponding hypermethylation of the X-chromosome and downregulation of X-linked genes in males with SLE (Figure 1C). Lastly, we observed similar patterns of X-chromosome hypermethylation using EMseq data from an independent cohort of SLE patients. A) Violin plots of XIST expression (RNAseq) in women (left) and men (right). B) Density plot of the bimodal expression of XIST in men with SLE. Dashed red line indicates the separation between XIST high and XIST low groups. C) Distribution plots of significant changes (|FC| > 1.5; FDR < 0.1) in gene methylation (top), promoter methylation (middle), and gene expression (bottom) on the X chromosome in females (pink), XIST high males (green), and XIST low males (blue) compared to healthy controls. Figure 1. Partial X-chromosome inactivation in males with SLE. This study, which includes the most comprehensive and largest dataset of male SLE patients to date, shows that males with SLE express significantly higher levels of XIST, accompanied by hypermethylation of the X-chromosome and downregulation of X-linked genes compared to healthy controls, suggesting partial X-chromosome inactivation in males with SLE. Importantly, we have confirmed that these changes are not artifacts of Klinefelter’s patients within the cohort. We hypothesize that this X-chromosome inactivation may be driving SLE via several mechanisms, including: i) inactivation of immunoregulatory molecules, ii) inducing development of SLE autoantibodies, and/or iii) driving interferon production via TLR7.

O026 / #740 Topic:AS22 - SLE Heterogeneity Late-Breaking Abstract ABSTRACT CONCURRENT SESSION 04: ADVANCING LUPUS THERAPIES AND INSIGHTS 22-05-2025 1:40 PM - 2:40 PM Integrative omics approaches offer a powerful strategy to dissect the complex biological networks and pathways involved in disease pathophysiology. However, integrating diverse data types with varying scales, biological contexts, and feature numbers poses significant challenges. This study aims to: i) identify molecular subtypes of SLE patients via a multi-omic integrative approach, ii) characterize these clusters using molecular and clinical data, and iii) identify the most discriminant subset of features for patient classification. Similarity Network Fusion (SNF) was used to integrate baseline transcriptomic (RNAseq), proteomic (Olink), and epigenomic (EMseq) data from the whole blood of 722 SLE patients that were randomized to placebo plus standard of care in phase 3 clinical trials (NCT03616964,NCT03616912), and 84 healthy controls. Patient subgroups were identified via spectral clustering, and cluster robustness was determine using a bootstrapping approach (n = 30). Clusters were characterized with omics data via differential expression and gene set enrichment analysis (GSEA). Clusters were also characterized with clinical metrics via t-tests and random forest analysis. Finally, we utilized Data Integration Analysis for Biomarker Discovery using Latent cOmponents (DIABLO) modeling to identify potential biomarkers associated with these SLE classes. Integration of the omics datatypes identified 3 distinct clusters of individuals: cluster 1 (n = 176), cluster 2 (n = 299), and cluster 3 (n = 331). All 84 healthy controls were grouped within cluster 2 (Figure 1A). Notably, clustering based on individual datatypes failed to reproduce these distinct clusters. Clinical data revealed that SLE patients in cluster 2 exhibited significantly lower dsDNA, IFI44L, and SLEDAI scores, along with higher complement (C3) levels compared to the other clusters (Figure 1B), indicating a milder form of SLE. This is consistent with the fact that these SLE patients clustered with the healthy controls. Additional clinical measurements (Figure 1C) and pathway enrichment analysis (Figure 1D) revealed distinct signatures in the other 2 clusters: cluster 3 displayed an elevated adaptive immunity signature, while cluster 1 was characterized by innate immunity signatures. Finally, integrating all 3 datatypes using the DIABLO modeling approach identified 3 latent components with a minimal set of discriminating biomarkers for each cluster. A) Spectral clustering of patient-patient similarities calculated from the SNF-fused data. B) Distribution of conventional SLE metrics among the 3 SNF clusters (excluding healthy patients). Significant differences assessed with a t-test and false discover rate (FDR). C) Significant clinical differences between Cluster 1 and Cluster 3 using t-test and FDR. Fold change (C1/C3) greater than 1 indicates increased measurements in Custer 1 compared to Cluster 3. D) Normalized Enrichment Score (NES) of select GO terms from a GSEA analysis comparing C1 vs C3 using RNAseq. Positive NES indicates increased activity in C1, and vice-versa. Figure 1. SLE patient clusters and characterization. Multi-omic integration revealed 3 molecularly distinct clusters of SLE patients. Using orthogonal datatypes (clinical and omics), we characterized these clusters into 3 novel classifications: mild, innate-driven, and adaptive-driven immunity. This work helps our understanding of the complex heterogenous nature of SLE and will guide targeted treatment approaches with innate or adaptive involvement.

OBJECTIVE:Neutrophils play an important role in regulating immune and inflammatory responses in patients with rheumatoid arthritis (RA). We assessed whether baricitinib, a JAK1/JAK2 inhibitor, could reduce neutrophil activation and whether a neutrophil activation score could predict treatment response. METHODS:Markers of neutrophil activation, calprotectin, and neutrophil extracellular traps (NETs) were analyzed using enzyme-linked immunosorbent assay in plasma from patients with RA (n = 271) and healthy controls (n = 39). For patients with RA, neutrophil activation markers were measured at baseline, 12 weeks, and 24 weeks after receiving placebo and 2 and 4 mg baricitinib. Whole-blood RNA analyses from multiple randomized baricitinib RA trials were performed to study neutrophil-related transcripts (n = 1,651). RESULTS:Baseline levels of plasma neutrophil markers were elevated in patients with RA compared to healthy controls (P < 0.001). Receiving baricitinib reduced levels of soluble calprotectin at 12 and 24 weeks, especially in patients with RA responding to treatment, as determined by American College of Rheumatology 20% improvement criteria. Whole-blood RNA analysis revealed similar changes in the predominant neutrophil markers calprotectin and Fcα receptor I upon reception of baricitinib in three randomized clinical trials involving patients with at various stages of disease-modifying therapy. Clustering analysis of plasma activation markers showed elevated levels of calprotectin and NETs (eg, a neutrophil activation score, at baseline, could predict treatment response to baricitinib). In contrast, C-reactive protein levels could not distinguish between responders and nonresponders. CONCLUSION:Neutrophil activation markers may add clinical value in predicting treatment response to baricitinib and other drugs targeting RA. This study supports personalized medicine in treating patients with RA, not only based on symptoms but also based on immunophenotyping.

Unbiased informatics approaches have the potential to generate insights into uncharacterized signaling pathways in human disease. In this study, we generated longitudinal transcriptomic profiles of plaque psoriasis lesions from patients enrolled in a clinical trial of the anti-IL17A antibody ixekizumab (IXE). This dataset was then computed against a curated matrix of over 700 million data points derived from published psoriasis and signaling node perturbation transcriptomic and chromatin immunoprecipitation-sequencing datasets. We observed substantive enrichment within both psoriasis-induced and IXE-repressed gene sets of transcriptional targets of members of the MuvB complex, a master regulator of the mitotic cell cycle. These gene sets were similarly enriched for pathways involved in the regulation of the G2/M transition of the cell cycle. Moreover, transcriptional targets for MuvB nodes were strongly enriched within IXE-repressed genes whose expression levels correlated strongly with the extent and severity of the psoriatic disease. In models of human keratinocyte proliferation, genes encoding MuvB nodes were transcriptionally repressed by IXE, and depletion of MuvB nodes reduced cell proliferation. Finally, we made the expression and regulatory networks that supported this study available as a freely accessible, cloud-based hypothesis generation platform. Our study positions inhibition of MuvB signaling as an important determinant of the therapeutic impact of IXE in psoriasis.

OBJECTIVES:To elucidate the mechanism of action of baricitinib, a Janus kinase (JAK) 1/2 inhibitor, and describe immunological pathways related to disease activity in adults with systemic lupus erythematosus (SLE) receiving standard background therapy in a phase II trial.METHODS:Patients with SLE were treated with baricitinib 2 mg or 4 mg in a phase II randomised, placebo-controlled study. Sera from 239 patients (baricitinib 2 mg: n=88; baricitinib 4 mg: n=82; placebo: n=69) and 49 healthy controls (HCs) were collected at baseline and week 12 and analysed using a proximity extension assay (Target 96 Inflammation Panel (Olink)). Interferon (IFN) scores were determined using an mRNA panel. Analytes were compared in patients with SLE versus HCs and in changes from baseline at week 12 between baricitinib 2 mg, 4 mg and placebo groups using a restricted maximum likelihood-based mixed models for repeated measures. Spearman correlations were computed for analytes and clinical measurements.RESULTS:At baseline, SLE sera had strong cytokine dysregulation relative to HC sera. C-C motif chemokine ligand (CCL) 19, C-X-C motif chemokine ligand (CXCL) 10, tumour necrosis factor alpha (TNF-α), TNF receptor superfamily member (TNFRSF)9/CD137, PD-L1, IL-6 and IL-12β were significantly reduced in patients treated with baricitinib 4 mg versus placebo at week 12. Inflammatory biomarkers indicated correlations/associations with type I IFN (CCL19, CXCL10, TNF-α and PD-L1), anti-double stranded DNA (dsDNA) (TNF-α, CXCL10) and Systemic Lupus Erythematosus Disease Activity Index-2000, tender and swollen joint count and worst joint pain (CCL19, IL-6 and TNFRSF9/CD137).CONCLUSION:These results suggest that baricitinib 4 mg downregulated key cytokines that are upregulated in patients with SLE and may play a role in a multitargeted mechanism beyond the IFN signature although clinical relevance remains to be further delineated.TRIAL REGISTRATION NUMBER:NCT02708095.

In recent years, interest in RNA secondary structure has exploded due to its implications in almost all biological functions and its newly appreciated capacity as a therapeutic agent/target. This surge of interest has driven the development and adaptation of many computational and biochemical methods to discover novel, functional structures across the genome/transcriptome. To further enhance efforts to study RNA secondary structure, we have integrated the functional secondary structure prediction tool ScanFold, into IGV. This allows users to directly perform structure predictions and visualize results-in conjunction with probing data and other annotations-in one program. We illustrate the utility of this new tool by mapping the secondary structural landscape of the human MYC precursor mRNA. We leverage the power of vast 'omics' resources by comparing individually predicted structures with published data including: biochemical structure probing, RNA binding proteins, microRNA binding sites, RNA modifications, single nucleotide polymorphisms, and others that allow functional inferences to be made and aid in the discovery of potential drug targets. This new tool offers the RNA community an easy to use tool to find, analyze, and characterize RNA secondary structures in the context of all available data, in order to find those worthy of further analyses.

Background Clinical heterogeneity, a hallmark of systemic autoimmune diseases (SADs) impedes early diagnosis and effective treatment, issues that may be addressed if patients could be grouped into a molecular defined stratification. Methods With the aim of reclassifying SADs independently of the clinical diagnoses, unsupervised clustering of integrated whole blood transcriptome and methylome cross-sectional data of 918 patients with 7 SADs and 263 healthy controls was undertaken. An inception cohort prospectively followed for 6 and 14 months was studied to validate the results in early cases and analyze if cluster assignment was modified with time. Results Four clusters were identified Three aberrant clusters were ‘acute phase inflammatory’, ‘T cell immunity’, and ‘interferon’, each including all diagnoses, were defined by genetic, clinical, serological and cellular features. A fourth cluster showed no specific molecular pattern, to which 74% of healthy controls clustered with patients. The inception cohort showed that most patients were either assigned always to the same cluster or moved from the healthy-like cluster to a single aberrant cluster resembling the relapsing-remitting dynamic of these diseases, showing that single aberrant molecular signatures characterize each individual patient. Conclusions Patients with SADs share molecular signatures and can be therefore stratified into three disease clusters differentiating each patient into a specific molecular disease pathway. Such assignment is stable with time. These results have important implications for understanding disease progression and therapy design marking a paradigm shift in our view of SADs. Acknowledgment This work has been supported through a grant from the Innovative Medicines Initiative Joint Undertaking No. 115565 and in-kind and in-cash contributions from the EFPIA partners. G.B. is supported by the Instituto de Salud Carlos III (ISCIII, Spanish Health Ministry), through the Sara Borrell subprogram (CD18/00153). The authors would like to particularly express their gratitude to the patients, nurses and many others who helped directly or indirectly in the consecution of this study.

Background Baricitinib, an oral selective Janus kinase (JAK)1 and 2 inhibitor, resulted in significant clinical improvements in patients with active systemic lupus erythematosus (SLE) receiving standard background therapy in the phase 2 study JAHH (NCT02708095). Baricitinib may impact key cytokines implicated in the pathogenesis of SLE through effects on the JAK/signal transducer and activator of transcription (STAT) signaling pathway. The impact of baricitinib on STAT-related gene expression and associations with clinical response in SLE were evaluated. Methods 314 patients were randomized 1:1:1 to receive once-daily placebo, baricitinib 2-mg, or baricitinib 4-mg for 24 weeks in JAHH. Patients were ≥18 years of age, had a diagnosis of SLE, and had active disease involving skin or joints. RNA isolated from whole blood at baseline and weeks 2, 4, 12, and 24 was analyzed using Affymetrix HTA2.0 array. Results Gene expression profiling demonstrated a statistically significant elevation of STAT1 and STAT2 gene expression at baseline in SLE patients. There was a significant association between the overexpression of STAT1 and STAT2 at baseline. Baricitinib 4-mg treatment resulted in modest reduction in STAT1, STAT2, and STAT4 expression, and a statistically significant reduction in multiple genes downstream of STAT1, STAT2, and STAT4. The reduction in expression of STAT-associated genes with baricitinib treatment correlated with clinical improvement in SLE patients using SLEDAI-2K measurements (table 1). Conclusions Baricitinib may partially mediate its effect in SLE through changes in STAT-related gene expression, with changes associated with clinical improvement in SLE. Acknowledgements Funded by Eli Lilly and Company.

OBJECTIVE:To characterise the molecular pathways impacted by the pharmacologic effects of the Janus kinase (JAK) 1 and JAK2 inhibitor baricitinib in SLE.METHODS:In a phase II, 24-week, randomised, placebo-controlled, double-blind study (JAHH), RNA was isolated from whole blood in 274 patients and analysed using Affymetrix HTA2.0 array. Serum cytokines were measured using ultrasensitive quantitative assays.RESULTS:Gene expression profiling demonstrated an elevation of STAT1, STAT2 and multiple interferon (IFN) responsive genes at baseline in patients with SLE. Statistical and gene network analyses demonstrated that baricitinib treatment reduced the mRNA expression of functionally interconnected genes involved in SLE including STAT1-target, STAT2-target and STAT4-target genes and multiple IFN responsive genes. At baseline, serum cytokines IFN-α, IFN-γ, interleukin (IL)-12p40 and IL-6 were measurable and elevated above healthy controls. Treatment with baricitinib significantly decreased serum IL-12p40 and IL-6 cytokine levels at week 12, which persisted through week 24.CONCLUSION:Baricitinib treatment induced significant reduction in the RNA expression of a network of genes associated with the JAK/STAT pathway, cytokine signalling and SLE pathogenesis. Baricitinib consistently reduced serum levels of two key cytokines implicated in SLE pathogenesis, IL-12p40 and IL-6.

Background Tissue released blood-based biomarkers can provide insight into drug mode of action and response. To understand the changes in extracellular matrix turnover, we analyzed biomarkers associated with joint tissue turnover from a phase 3, randomized, placebo-controlled study of baricitinib in patients with active rheumatoid arthritis (RA). Methods Serum biomarkers associated with synovial inflammation (C1M, C3M, and C4M), cartilage degradation (C2M), bone resorption (CTX-I), and bone formation (osteocalcin) were analyzed at baseline, and weeks 4 and 12, from a subgroup of patients ( n = 240) randomized to placebo or 2-mg or 4-mg baricitinib (RA-BUILD, NCT01721057). Mixed-model repeated measure was used to identify biomarkers altered by baricitinib. The relationship between changes in biomarkers and clinical measures was evaluated using correlation analysis. Results Treatment arms were well balanced for baseline biomarkers, demographics, and disease activity. At week 4, baricitinib 4-mg significantly reduced C1M from baseline by 21% compared to placebo ( p < 0.01); suppression was sustained at week 12 (27%, p < 0.001). Baricitinib 4-mg reduced C3M and C4M at week 4 by 14% and 12% compared to placebo, respectively ( p < 0.001); they remained reduced by 16% and 11% at week 12 ( p < 0.001). In a pooled analysis including all treatment arms, patients with the largest reduction (upper 25% quartile) in C1M, C3M, and C4M by week 12 had significantly greater clinical improvement in the Simplified Disease Activity Index at week 12 compared to patients with the smallest reduction (lowest 25% quartile). Conclusion Baricitinib treatment resulted in reduced circulating biomarkers associated with joint tissue destruction as well as concomitant RA clinical improvement. Trial registration ClinicalTrials.gov NCT01721057 ; date of registration: November 1, 2012