The interferon-rich skin environment regulates Langerhans cell ADAM17 to promote photosensitivity in lupus.

The autoimmune disease lupus erythematosus (lupus) is characterized by photosensitivity, where even ambient ultraviolet radiation (UVR) exposure can lead to development of inflammatory skin lesions. We have previously shown that Langerhans cells (LCs) limit keratinocyte apoptosis and photosensitivity via a disintegrin and metalloprotease 17 (ADAM17)-mediated release of epidermal growth factor receptor (EGFR) ligands and that LC ADAM17 sheddase activity is reduced in lupus. Here, we sought to understand how the lupus skin environment contributes to LC ADAM17 dysfunction and, in the process, differentiate between effects on LC ADAM17 sheddase function, LC ADAM17 expression, and LC numbers. We show through transcriptomic analysis a shared IFN-rich environment in non-lesional skin across human lupus and three murine models: MRL/lpr, B6.Sle1yaa, and imiquimod (IMQ) mice. IFN-I inhibits LC ADAM17 sheddase activity in murine and human LCs, and IFNAR blockade in lupus model mice restores LC ADAM17 sheddase activity, all without consistent effects on LC ADAM17 protein expression or LC numbers. Anti-IFNAR-mediated LC ADAM17 sheddase function restoration is associated with reduced photosensitive responses that are dependent on EGFR signaling and LC ADAM17. Reactive oxygen species (ROS) is a known mediator of ADAM17 activity; we show that UVR-induced LC ROS production is reduced in lupus model mice, restored by anti-IFNAR, and is cytoplasmic in origin. Our findings suggest that IFN-I promotes photosensitivity at least in part by inhibiting UVR-induced LC ADAM17 sheddase function and raise the possibility that anifrolumab ameliorates lupus skin disease in part by restoring this function. This work provides insight into IFN-I-mediated disease mechanisms, LC regulation, and a potential mechanism of action for anifrolumab in lupus.

Clinical management of lupus in the United States: A claims-based analysis.

OBJECTIVES: To understand the evaluation and management of patients coded with lupus in the broad clinical community in the United States. METHODS: Claims data for diagnoses, procedures, medications, and physician specialties were evaluated for three lupus cohorts [lupus nephritis (LN), systemic lupus erythematosus excluding LN (SLE), and cutaneous lupus erythematosus excluding SLE and LN (CLE)] using the EVERSANA claims databases. Identification of patients was based upon the occurrence of lupus-specific codes, with the requirement that a single patient receive a lupus-related ICD code twice within a six-month period. RESULTS: Using ICD codes, we were able to identify 28,372 patients coded with LN, 82,744 patients coded with SLE, and 13,920 patients coded with CLE, and subsequently evaluate the journey of patients in each group in the year before and after being coded as having a diagnosis of lupus. For the three lupus cohorts, the basis of diagnosis was not always apparent, as clinical features of lupus were not often obtained, autoantibody testing was not usual, biopsies were uncommon and subspecialty involvement was not routine. In addition, a significant increase in laboratory testing, non-lupus diagnoses, emergency department visits and cost during the year before receiving a lupus code suggested uncertainty in disease recognition. Nevertheless, these patients received two separate lupus coding events within a six-month period, supporting a sustained or repeated diagnosis of lupus by the evaluating clinicians. When compared, the three lupus cohorts differed with regard to frequency of laboratory testing, subspecialty care, skin and renal biopsies, and medication management. Moreover, there was an increase in the cost of care of patients coded with lupus compared to a reference patient population both during the year before and after being coded with a diagnosis of lupus. CONCLUSION: The data present a comprehensive report of the care of patients coded as having a diagnosis of lupus in the United States, including those outside of specialty centers. Despite the unclear basis of diagnosis in some patients, evaluation and management of patients coded as having a diagnosis of lupus in the general care community does not closely follow the recommended guidelines set forth by professional societies.

Obesity fosters severe disease outcomes in a mouse model of coronavirus infection associated with transcriptomic abnormalities.

Obesity has been identified as an independent risk factor for severe outcomes in humans with coronavirus disease 2019 (COVID-19) and other infectious diseases. Here, we established a mouse model of COVID-19 using the murine betacoronavirus, mouse hepatitis virus 1 (MHV-1). C57BL/6 and C3H/HeJ mice exposed to MHV-1 developed mild and severe disease, respectively. Obese C57BL/6 mice developed clinical manifestations similar to those of lean controls. In contrast, all obese C3H/HeJ mice succumbed by 8 days postinfection, compared to a 50% mortality rate in lean controls. Notably, both lean and obese C3H/HeJ mice exposed to MHV-1 developed lung lesions consistent with severe human COVID-19, with marked evidence of diffuse alveolar damage (DAD). To identify early predictive biomarkers of worsened disease outcomes in obese C3H/HeJ mice, we sequenced RNA from whole blood 2 days postinfection and assessed changes in gene and pathway expression. Many pathways uniquely altered in obese C3H/HeJ mice postinfection aligned with those found in humans with severe COVID-19. Furthermore, we observed altered gene expression related to the unfolded protein response and lipid metabolism in infected obese mice compared to their lean counterparts, suggesting a role in the severity of disease outcomes. This study presents a novel model for studying COVID-19 and elucidating the mechanisms underlying severe disease outcomes in obese and other hosts.

Potential and pitfalls of repurposing the CAR-T cell regimen for the treatment of autoimmune disease.

Chimeric antigen receptors (CARs) are synthetic proteins designed to direct an immune response toward a specific target and have been used in immunotherapeutic applications through the adoptive transfer of T cells genetically engineered to express CARs. This technology received early attention in oncology with particular success in treatment of B cell malignancies leading to the launch of numerous successful clinical trials and the US Food and Drug Administration approval of several CAR-T-based therapies. Many CAR-T constructs have been employed, but have always been administered following a lymphodepletion regimen. The success of CAR-T cell treatment in targeting malignant B cells has led many to consider the potential for using these regimens to delete pathogenic B cells in autoimmune diseases. Preliminary results have suggested efficacy, but the sample size remains small, controlled trials have not been done, the role of immunodepletion has not been established, the most effective CAR-T constructs have not been identified and the most appropriate patient subsets for treatment have not been established.

Examination of the shared genetic architecture between multiple sclerosis and systemic lupus erythematosus facilitates discovery of novel lupus risk loci.

Systemic Lupus Erythematosus (SLE) is an autoimmune disease with heterogeneous manifestations, including neurological and psychiatric symptoms. Genetic association studies in SLE have been hampered by insufficient sample size and limited power compared to many other diseases. Multiple Sclerosis (MS) is a chronic relapsing autoimmune disease of the central nervous system (CNS) that also manifests neurological and immunological features. Here, we identify a method of leveraging large-scale genome wide association studies (GWAS) in MS to identify novel genetic risk loci in SLE. Statistical genetic comparison methods including linkage disequilibrium score regression (LDSC) and cross-phenotype association analysis (CPASSOC) to identify genetic overlap in disease pathophysiology, traditional 2-sample and novel PPI-based mendelian randomization to identify causal associations and Bayesian colocalization were applied to association studies conducted in MS to facilitate discovery in the smaller, more limited datasets available for SLE. Pathway analysis using SNP-to-gene mapping identified biological networks composed of molecular pathways with causal implications for CNS disease in SLE specifically, as well as pathways likely causal of both pathologies, providing key insights for therapeutic selection.

Knowledge of and Stated Adherence to the 2020 ACR Guideline for Gout Management: Results of a Survey of US Rheumatologists.

OBJECTIVE: This report evaluates rheumatologists' stated adherence to and agreement with the 2020 American College of Rheumatology (ACR) Guideline for the Management of Gout. METHODS: A 57-item questionnaire was administered to a sample of US rheumatologists. Stated adherence scores were based on several guideline recommendations reported to be followed by rheumatologists in practice, whereas stated agreement scores were based on whether respondents always followed the recommendations. RESULTS: All 201 rheumatologists approached completed the questionnaire. The mean overall stated adherence score was 11.5 (maximum 15), whereas the mean overall stated agreement score was 7.7 (maximum 14). Less experienced rheumatologists (≤ 8 yrs; n = 49) were likely to claim adherence to more individual ACR recommendations than those with more experience (> 8 yrs; n = 152; mean stated adherence score: 12.3 vs 11.3; P ≤ 0.05). Rheumatologists who claimed to see ≤ 75 patients with gout in 6 months (n = 66) had a mean stated adherence score of 12.1 vs 11.2 for those who claimed to have seen > 75 patients (P ≤ 0.05). Approximately 78% of rheumatologists claimed to follow the guideline for initiating urate-lowering therapy (ULT), and 89% were likely to prescribe allopurinol as a first-line ULT. Claimed adherence to recommendations for dosing was lower (febuxostat: 43%; allopurinol: 39%). Rheumatologists from academic settings were more likely to prescribe an interleukin-1 inhibitor for gout flares. CONCLUSION: The self-reported practice of the surveyed US rheumatologists was generally concordant with the 2020 ACR Guideline for the Management of Gout. However, there were gaps in guideline knowledge and stated adherence among rheumatologists, mainly concerning the dosing of treatment regimens.

Increased frequency of hepatic steatosis and fibrosis in patients with gout detected by transient elastography.

OBJECTIVES: It has been suggested that gout is associated with non-alcoholic fatty liver disease (NAFLD). Our aim was to assess NAFLD in gout patients using the validated non-invasive imaging technique, transient elastography (FibroScan). METHODS: FibroScans in consecutive gout patients in a single centre from 11/1/2016 to 11/1/2021 and reviewed retrospectively. FibroScan results include the E- score (kPA), measuring liver stiffness, and controlled attenuation parameter (CAP) score (dB/m), assessing steatosis. In addition, a FIB-4 fibrosis score was calculated. RESULTS: 47 gout patients (7 females, 14.9%; 40 males, 85.1%) underwent FibroScans. The mean age was 59.8 years, the mean body mass index (BMI) was 30.95 kg/m2, and gout duration 0-49 years. Tophi were present in 11 (26.2%). Comorbidities included dyslipidaemia (86.7%), diabetes mellitus (31.1%), known liver disease (33.3%), current alcohol consumption (46.8%), ALT or AST elevations (54.4%), and hyperuricaemia (53.7%). FibroScan results revealed hepatic steatosis (CAP >238 dB/m) in 40 (85.1%) and were significantly associated with BMI (r=0.53, p=0.0001) but not age, serum urate (SU), glucose, triglycerides, ALT, AST. FibroScan also revealed fibrosis (E score >7) in 9 (19.1%); severe fibrosis (cirrhosis) in 8. Fibrosis was significantly associated with age (p=0.03) and known liver disease (p=0.003) but not BMI, SU, or comorbidities. The FIB-4 score was significantly associated with the fibrosis score (r2=0.24, p=0.0009) but not with CAP, ALT, or AST. CONCLUSIONS: Despite not being associated with common gout comorbidities, fatty liver and liver fibrosis were common in this gout cohort, suggesting FibroScan screening in gout patients to assess NAFLD, irrespective of serum transaminase levels.

2023 International Consensus Guidance for the use of Tripterygium Wilfordii Hook F in the treatment of active rheumatoid arthritis.

BACKGROUND: Rheumatoid arthritis (RA) is a chronic autoimmune disorder that affects the joints and produces pain, swelling, and stiffness. It has a lifetime prevalence of up to 1% worldwide. An extract of Tripterygium wilfordii Hook F (TwHF), a member of the Celastraceae herbal family widely available in south China, has been used for treatment of RA since 1960s. METHODS: The current consensus practice guidance (CPG) aims to offer guidance on the application of TwHF in the clinical management of active RA. The CPG followed World Health Organisation (WHO)'s recommended process, carried out three systematic reviews to synthesize data from 19 randomised controlled trials (RCT) involving 1795 participants. We utilized Grading of Recommendations, Assessment, Development and Evaluation (GRADE) to evaluate certainty of evidence and derive recommendations. We rigorously followed The Appraisal of Guidelines for Research and Evaluation II (AGREE II) as conduct guides to minimise bias and promote transparency. RESULTS: There was no obvious difference between TwHF monotherapy and methotrexate (MTX) monotherapy on ACR20 (RCT = 2, N = 390, RR = 1.06, 95%CI 0.90-1.26, moderate certainty), ACR50 (RCT = 3, N = 419, RR = 1.03, 95%CI 0.80-1.34, moderate certainty), ACR70 (RCT = 2, N = 390, RR = 1.12, 95%CI 0.69-1.79, low certainty). TwHF monotherapy may be better than salicylazosulfapyridine monotherapy on ACR20 and the effect may be similar on ACR50 and ACR70. Seven RCTs compared MTX combined with TwHF versus MTX monotherapy, and the meta-analysis results favoured combination therapy group on ACR20 (RCT = 3, N = 470, RR = 1.44, 95%CI 1.28-1.62, moderate certainty), ACR50 (RCT = 4, N = 500, RR = 1.88, 95%CI 1.56-2.28, moderate certainty) and ACR70 (RCT = 2, N = 390, RR = 2.12, 95%CI 1.40-3.19, low certainty). We found no obvious difference between groups on critical safety outcomes, including infection (RCT = 3, N = 493, RR = 1.37, 95%CI 0.84-2.23), liver dysfunction (RCT = 5, N = 643, RR = 1.14, 95%CI 0.71-1.85), renal damage (RCT = 3, N = 450, RR = 2.20, 95%CI 0.50-9.72). CONCLUSION: Upon full review of the evidence, the guidance panel reached consensus on recommendations for the use of TwHF in people with active RA, either as monotherapy or as combination therapy with MTX.

Single-cell RNA sequencing analysis reveals the heterogeneity of IL-10 producing regulatory B cells in lupus-prone mice.

Introduction: B cells can have both pathogenic and protective roles in autoimmune diseases, including systemic lupus erythematosus (SLE). Deficiencies in the number or immunosuppressive function of IL-10 producing regulatory B cells (Bregs) can cause exacerbated autoimmune inflammation. However, the exact role of Bregs in lupus pathogenesis has not been elucidated. Methods: We carried out gene expression analysis by scRNA-seq to characterize differences in splenic Breg subsets and molecular profiles through stages of disease progression in lupus-prone mice. Transcriptome-based changes in Bregs from mice with active disease were confirmed by phenotypic analysis. Results: We found that a loss of marginal zone (MZ) lineage Bregs, an increase in plasmablast/plasma cell (PB-PC) lineage Bregs, and overall increases in inflammatory gene signatures were characteristic of active disease as compared to Bregs from the pre-disease stage. However, the frequencies of both MZ Bregs and PB-PCs expressing IL-10 were significantly decreased in active-disease mice. Conclusion: Overall, we have identified changes to the repertoire and transcriptional landscape of Breg subsets associated with active disease that provide insights into the role of Bregs in lupus pathogenesis. These results could inform the design of Breg-targeted therapies and interventions to restore Breg suppressive function in autoimmunity.

An interpretable machine learning pipeline based on transcriptomics predicts phenotypes of lupus patients.

Machine learning (ML) has the potential to identify subsets of patients with distinct phenotypes from gene expression data. However, phenotype prediction using ML has often relied on identifying important genes without a systems biology context. To address this, we created an interpretable ML approach based on blood transcriptomics to predict phenotype in systemic lupus erythematosus (SLE), a heterogeneous autoimmune disease. We employed a sequential grouped feature importance algorithm to assess the performance of gene sets, including immune and metabolic pathways and cell types, known to be abnormal in SLE in predicting disease activity and organ involvement. Gene sets related to interferon, tumor necrosis factor, the mitoribosome, and T cell activation were the best predictors of phenotype with excellent performance. These results suggest potential relationships between the molecular pathways identified in each model and manifestations of SLE. This ML approach to phenotype prediction can be applied to other diseases and tissues.

Analysis of transcriptomic features reveals molecular endotypes of SLE with clinical implications.

BACKGROUND: Systemic lupus erythematosus (SLE) is known to be clinically heterogeneous. Previous efforts to characterize subsets of SLE patients based on gene expression analysis have not been reproduced because of small sample sizes or technical problems. The aim of this study was to develop a robust patient stratification system using gene expression profiling to characterize individual lupus patients. METHODS: We employed gene set variation analysis (GSVA) of informative gene modules to identify molecular endotypes of SLE patients, machine learning (ML) to classify individual patients into molecular subsets, and logistic regression to develop a composite metric estimating the scope of immunologic perturbations. SHapley Additive ExPlanations (SHAP) revealed the impact of specific features on patient sub-setting. RESULTS: Using five datasets comprising 2183 patients, eight SLE endotypes were identified. Expanded analysis of 3166 samples in 17 datasets revealed that each endotype had unique gene enrichment patterns, but not all endotypes were observed in all datasets. ML algorithms trained on 2183 patients and tested on 983 patients not used to develop the model demonstrated effective classification into one of eight endotypes. SHAP indicated a unique array of features influential in sorting individual samples into each of the endotypes. A composite molecular score was calculated for each patient and significantly correlated with standard laboratory measures. Significant differences in clinical characteristics were associated with different endotypes, with those with the least perturbed transcriptional profile manifesting lower disease severity. The more abnormal endotypes were significantly more likely to experience a severe flare over the subsequent 52 weeks while on standard-of-care medication and specific endotypes were more likely to be clinical responders to the investigational product tested in one clinical trial analyzed (tabalumab). CONCLUSIONS: Transcriptomic profiling and ML reproducibly separated lupus patients into molecular endotypes with significant differences in clinical features, outcomes, and responsiveness to therapy. Our classification approach using a composite scoring system based on underlying molecular abnormalities has both staging and prognostic relevance.

Letter to the editor: testing the effectiveness of MyPROSLE in classifying patients with lupus nephritis.

Because of the clinical heterogeneity among patients with systemic lupus erythematosus (SLE), developing molecular profiles that predict clinical features can be useful in creating a personalized approach to treatment. Toro-Domínguez et al. created a web tool to aid in therapeutic decision making for clinicians that predicts clinical features associated with SLE from blood transcriptomic data. Specifically, they present a machine learning model that predicts the presence of proliferative nephritis from blood transcriptomics. Here, we report use of the tool in independent datasets and found that it did not perform sufficiently well to consider replacement of the standard kidney biopsy as a diagnostic procedure.

Efficacy and safety of tripterygium wilfordii Hook F plus TNF inhibitor for active rheumatoid arthritis: A multicentre, randomized, double-blind, triple-dummy controlled trial.

An investigator-initiated, multicentre, randomized, double-blind, triple-dummy, controlled trial was conducted at 14 tertiary rheumatology centers in China to evaluate the efficacy and safety of Tripterygium wilfordii Hook F (TwHF) with recombinant human TNF receptor IgGFc fusion protein (rhTNFR-Fc) in active Rheumatoid Arthritis (RA). Primary endpoint was the proportion of patients achieved a 50% improvement of American College of Rheumatology criteria (ACR50) in TwHF+rhTNFR-Fc vs. methotrexate (MTX) group at week 12. ACR50 was achieved in 57.1% (72/126), 41.3% (52/126), 23.0% (29/126), and 26.2% (33/126) patients receiving TwHF+rhTNFR-Fc, MTX + rhTNFR-Fc, TwHF and MTX monotherapy, respectively, at week 12 (TwHF+rhTNFR-Fc vs. other three groups, all p < 0.05). No statistical difference in serious adverse events or adverse events leading to discontinuation of study across all groups was documented. TwHF+rhTNFR-Fc was superior to MTX for active RA, and was more effective than MTX + rhTNFR-Fc on ACR50, with a similar safety profile. Trial registration:ClinicalTrials.govNCT03589833.

Differential regulation of the interferon response in systemic lupus erythematosus distinguishes patients of Asian ancestry.

OBJECTIVES: Type I interferon (IFN) plays a role in the pathogenesis of systemic lupus erythematosus (SLE), but insufficient attention has been directed to the differences in IFN responses between ancestral populations. Here, we explored the expression of the interferon gene signatures (IGSs) in SLE patients of European ancestry (EA) and Asian ancestry (AsA). METHODS: We used gene set variation analysis with multiple IGS encompassing the response to both type 1 and type 2 IFN in isolated CD14+ monocytes, CD19+B cells, CD4+T cells and Natural Killer (NK) cells from patients with SLE stratified by self-identified ancestry. The expression of genes upstream of the IGS and influenced by lupus-associated risk alleles was also examined. Lastly, we employed machine learning (ML) models to assess the most important features classifying patients by disease activity. RESULTS: AsA patients with SLE exhibited greater enrichment in the IFN core and IFNA2 IGS compared with EA patients in all cell types examined and, in the presence and absence of autoantibodies. Overall, AsA patients with SLE demonstrated higher expression of genes upstream of the IGS than EA counterparts. ML with feature importance analysis indicated that IGS expression in NK cells, anti-dsDNA, complement levels and AsA status contributed to disease activity. CONCLUSIONS: AsA patients with SLE exhibited higher IGS than EA patients in all cell types regardless of autoantibody status, with enhanced expression of genetically associated genes upstream of the IGS potentially contributing. AsA, along with the IGS in NK cells, anti-dsDNA and complement, independently influenced SLE disease activity.

Glucose oxidation-dependent survival of activated B cells provides a putative novel therapeutic target for lupus treatment.

Aberrant metabolic demand is observed in immune/inflammatory disorders, yet the role in pathogenesis remains unclear. Here, we discover that in lupus, activated B cells, including germinal center B (GCB) cells, have remarkably high glycolytic requirement for survival over T cell populations, as demonstrated by increased metabolic activity in lupus-activated B cells compared to immunization-induced cells. The augmented reliance on glucose oxidation makes GCB cells vulnerable to mitochondrial ROS-induced oxidative stress and apoptosis. Short-term glycolysis inhibition selectively reduces pathogenic activated B in lupus-prone mice, extending their lifespan, without affecting T follicular helper cells. Particularly, BCMA-expressing GCB cells rely heavily on glucose oxidation. Depleting BCMA-expressing activated B cells with APRIL-based CAR-T cells significantly prolongs the lifespan of mice with severe autoimmune disease. These results reveal that glycolysis-dependent activated B and GCB cells, especially those expressing BCMA, are potentially key lupus mediators, and could be targeted to improve disease outcomes.

Meeting report: the ALPHA project: a stakeholder meeting on lupus clinical trial outcome measures and the patient perspective.

Drug development in lupus has improved over the past 10 years but still lags behind that of other rheumatic disease areas. Assessment of prospective lupus therapies in clinical trials has proved challenging for reasons that are multifactorial including the heterogeneity of the disease, study design limitations and a lack of validated biomarkers which greatly impacts regulatory decision-making. Moreover, most composite outcome measures currently used in trials do not include patient-reported outcomes. Given these factors, the Addressing Lupus Pillars for Health Advancement Global Advisory Committee members who serve on the drug development team identified an opportunity to convene a meeting to facilitate information sharing on completed and existing outcome measure development efforts. This meeting report highlights information presented during the meeting as well as a discussion on how the lupus community may work together with regulatory agencies to simplify and standardise outcome measures to accelerate development of lupus therapeutics.

Interleukin-1ß inhibitors for the management of acute gout flares: a systematic literature review.

OBJECTIVES: The objective of this systematic review was to assess the effects of interleukin-1ß (IL-1ß) inhibitors on gout flares. METHODS: Studies published between 2011 and 2022 that evaluated the effects of IL-1ß inhibitors in adult patients experiencing gout flares were eligible for inclusion. Outcomes including pain, frequency and intensity of gout flares, inflammation, and safety were assessed. Five electronic databases (Pubmed/Medline, Embase, Biosis/Ovid, Web of Science and Cochrane Library) were searched. Two independent reviewers performed study screening, data extraction and risk of bias assessments (Cochrane Risk of Bias Tool 2 for randomised controlled trials [RCTs] and Downs and Black for non-RCTs). Data are reported as a narrative synthesis. RESULTS: Fourteen studies (10 RCTs) met the inclusion criteria, with canakinumab, anakinra, and rilonacept being the three included IL-1ß inhibitors. A total of 4367 patients with a history of gout were included from the 14 studies (N = 3446, RCTs; N = 159, retrospective studies [with a history of gout]; N = 762, post hoc analysis [with a history of gout]). In the RCTs, canakinumab and rilonacept were reported to have a better response compared to an active comparator for resolving pain, while anakinra appeared to be not inferior to an active comparator for resolving pain. Furthermore, canakinumab and rilonacept reduced the frequency of gout flares compared to the comparators. All three medications were mostly well-tolerated compared to their comparators. CONCLUSION: IL-1ß inhibitors may be a beneficial and safe medication for patients experiencing gout flares for whom current standard therapies are unsuitable. REVIEW PROTOCOL REGISTRATION: PROSPERO ID: CRD42021267670.

Molecular pathways identified from single nucleotide polymorphisms demonstrate mechanistic differences in systemic lupus erythematosus patients of Asian and European ancestry.

Systemic lupus erythematosus (SLE) is a multi-organ autoimmune disorder with a prominent genetic component. Individuals of Asian-Ancestry (AsA) disproportionately experience more severe SLE compared to individuals of European-Ancestry (EA), including increased renal involvement and tissue damage. However, the mechanisms underlying elevated severity in the AsA population remain unclear. Here, we utilized available gene expression data and genotype data based on all non-HLA SNP associations in EA and AsA SLE patients detected using the Immunochip genotyping array. We identified 2778 ancestry-specific and 327 trans-ancestry SLE-risk polymorphisms. Genetic associations were examined using connectivity mapping and gene signatures based on predicted biological pathways and were used to interrogate gene expression datasets. SLE-associated pathways in AsA patients included elevated oxidative stress, altered metabolism and mitochondrial dysfunction, whereas SLE-associated pathways in EA patients included a robust interferon response (type I and II) related to enhanced cytosolic nucleic acid sensing and signaling. An independent dataset derived from summary genome-wide association data in an AsA cohort was interrogated and identified similar molecular pathways. Finally, gene expression data from AsA SLE patients corroborated the molecular pathways predicted by SNP associations. Identifying ancestry-related molecular pathways predicted by genetic SLE risk may help to disentangle the population differences in clinical severity that impact AsA and EA individuals with SLE.