High-dimensional analysis of T-cell profiling variations following belimumab treatment in systemic lupus erythematosus

Efficacy and safety of belimumab in refractory and newly diagnosed active lupus nephritis patients: a real-world observational study

Background

Lupus nephritis (LN), one of the common manifestations of systemic lupus erythematosus, continues to be a principal cause of morbidity and mortality. According to the 2024 Kidney Disease: Improving Global Outcomes guidelines, belimumab has been recommended as adjunct therapy for active LN. However, the differences in its efficacy and safety between refractory and newly diagnosed active LN are unknown. This study aimed to evaluate them in a real-world clinical setting in China.

Methods

We enrolled active LN patients who initiated belimumab as adjunct therapy in our centre between June 2021 and January 2024 and divided them into a refractory group and a newly diagnosed group according to previous immunosuppressive therapy. They were followed up for ≥3 months. Renal manifestations, serologic features, Systemic Lupus Erythematosus Disease Activity Index 2000 (SLEDAI-2K) score and steroids dosage were recorded. We used generalized estimating equations to compare time series data for each group and analyse the change tendency of variables over time. Efficacy endpoints were complete renal response (CRR) and primary efficacy renal response (PERR). Logistic regression models were used to analyse factors associated with renal response.

Results

Of 116 LN patients receiving belimumab in our centre, a total of 89 active LN patients were included in the analysis, with a median treatment duration of 13 months (range 7-22). Among them 47 were in the newly diagnosed group and 42 were in refractory group. At the initiation of belimumab there is no statistical difference in age, gender, SLEDAI-2K score, renal-related markers (proteinuria, serum albumin, estimated glomerular filtration rate and renal histological classification) and serologic features (positive anti-double-stranded DNA, C3, C4) between the two groups. Compared with refractory patients, newly diagnosed patients had significantly shorter LN duration (P < .001) and a larger dosage of steroids (P < .01). During the follow-up period, proteinuria, SLEDAI-2K score and dosage of steroids decreased overall and in each group. The decrease was significantly more pronounced in the newly diagnosed group (P < 0.01, P < 0.001, P < 0.001). For the refractory active LN patients, the estimated probability of CRR and PERR at 12 months was 58.3% and 65.4%, respectively, which was comparable to newly diagnosed patients by logrank test (P = .10, P = .51). No difference was found in adverse event rates (P = .08), time to first renal flare (P = .79) or renal-related events (P = .77). Proteinuria levels at belimumab initiation [odds ratio (OR) 1.306, P = .02] and belimumab treatment duration (OR 0.896, P = .01) were independently associated with renal response.

Conclusion

Compared with refractory LN patients, the add-on treatment with belimumab provides remarkable improvement in newly diagnosed active LN patients, with faster steroids decrease. Our data support the efficacy of early introduction of belimumab in Chinese active LN patients in a real-life setting.

Diversity and function of regulatory T cells in health and autoimmune diseases

Regulatory T cell (Treg) play a pivotal role in immune regulation and maintaining host immune homeostasis. Treg heterogeneity, characterized by diverse gene expression profiles and functional states, is complex in both health and disease. Research reveals that Tregs are not a uniform population but exhibit diversity based on their origin, location, and functional status. This heterogeneity is crucial for understanding Treg roles in various pathological conditions. Dysfunctional Tregs are closely linked to the pathogenesis of autoimmune diseases, although the precise mechanisms remain unclear. The phenotypic and functional heterogeneity of Tregs is particularly significant in diseases such as systemic lupus erythematosus, multiple sclerosis, rheumatoid arthritis, inflammatory bowel disease, type 1 diabetes, psoriasis and autoimmune liver diseases. This review explores Treg origins, classifications, and heterogeneity in these conditions, aiming to provide new perspectives and strategies for diagnosis and treatment. Understanding Treg heterogeneity and plasticity promises to reveal novel therapeutic targets and advance precision immunotherapy development.

Molecular basis for the disease-modifying effects of belimumab in systemic lupus erythematosus and molecular predictors of early response: blood transcriptome analysis implicates the innate immunity and DNA damage response pathways

OBJECTIVES

Belimumab is a putative disease-modifying agent in systemic lupus erythematosus (SLE), yet the molecular underpinnings of its effects and the ability to predict early clinical response remain unexplored. To address these, we undertook a longitudinal, in-depth blood transcriptome study.

METHODS

RNA-sequencing was performed in the blood of active SLE patients at baseline and following 6 months of belimumab treatment (n=45 paired samples). Clinical response was determined according to the SLE Responder Index (SRI)-4 and Lupus Low Disease Activity State (LLDAS). Weighted correlation network analysis (WGCNA) was used to uncover gene module trait associations. Reversibility of SLE susceptibility and severity gene signatures was assessed. Machine learning was used to build models predictive of response.

RESULTS

Belimumab induced widespread transcriptome changes with downregulation of pathways related to B cells, type I/II interferon, IL-6/STAT3 and neutrophil activation. These effects were more pronounced among patients with LLDAS+ compared with to SRI-4+/LLDAS- response, with amelioration of the SLE 'susceptibility' signature observed in the former group. Unsupervised analysis unveiled gene modules enriched in neutrophil degranulation, type I interferon signalling and cytokine production to correlate positively with response at 6 months. Using neural networks, a set of 50 genes (including CCL4L2, CARD10, MMP15 and KLRC2) predicted response to belimumab with a cross-validated 84% specificity (test set). Lack of response was linked to perturbations of the cell cycle checkpoints, PI3K/ Akt/mammalian target of rapamycin and TGF-beta signalling pathways.

CONCLUSION

Belimumab treatment ameliorates multiple innate and adaptive immunity dysregulations of SLE and may reverse the disease signature, consistent with the drug effects on reducing activity and preventing flares. Fingerprints of innate immunity correlate with robust improvement whereas DNA damage response with less responsive disease to BAFF inhibition.

Mass cytometry: exploring the immune landscape of systemic autoimmune and inflammatory diseases in the past fourteen years

Auto-immune and inflammatory diseases are heterogenous in their clinical manifestations and prognosis, even among individuals presenting with the same pathology. Understanding the immunological alterations involved in their pathogenesis provides valuable insights in different clinical phenotypes and treatment responses. Immunophenotyping could lead to significant improvements in diagnosis, monitoring, initial treatment decisions and follow-up in autoimmune and inflammatory diseases. Mass cytometry provides measurement of over 40 simultaneous cellular parameters at single-cell resolution, and therefore holds immense potential to evaluate complex cellular systems and for high-dimensional single-cell analysis. The high dimensionality of mass cytometry provides better coverage of immune populations dynamics, with sufficient power to identify rare cell types compared to flow cytometry. In this comprehensive review, we explore how mass cytometry findings contributed in the past decade to a deeper understanding of the cellular actors involved in systemic auto-immune and auto-inflammatory diseases with their respective therapeutic and prognostic impact. We also delve into the bioinformatical approaches applied to mass cytometry to analyze the high volumes of data generated, as well as the impact of the use of complementary single cell RNA sequencing, and their spatial modalities. Our analysis highlights the fact that mass cytometry captures major information on cell populations providing insights on the complex pathogenesis of autoimmune diseases. Future research designs could include mass cytometry findings in association to other -omics to stratify patients in adequate therapeutic arms and provide advancements in personalized therapies in the field of auto-immune and inflammatory diseases.

Systemic lupus in the era of machine learning medicine

Artificial intelligence and machine learning applications are emerging as transformative technologies in medicine. With greater access to a diverse range of big datasets, researchers are turning to these powerful techniques for data analysis. Machine learning can reveal patterns and interactions between variables in large and complex datasets more accurately and efficiently than traditional statistical methods. Machine learning approaches open new possibilities for studying SLE, a multifactorial, highly heterogeneous and complex disease. Here, we discuss how machine learning methods are rapidly being integrated into the field of SLE research. Recent reports have focused on building prediction models and/or identifying novel biomarkers using both supervised and unsupervised techniques for understanding disease pathogenesis, early diagnosis and prognosis of disease. In this review, we will provide an overview of machine learning techniques to discuss current gaps, challenges and opportunities for SLE studies. External validation of most prediction models is still needed before clinical adoption. Utilisation of deep learning models, access to alternative sources of health data and increased awareness of the ethics, governance and regulations surrounding the use of artificial intelligence in medicine will help propel this exciting field forward.