Unsupervised machine learning identifies distinct SLE patient endotypes with differential response to belimumab

Objective To determine SLE endotypes according to B cell immunophenotyping and serological profile and assess endotypes' response to belimumab. Methods We analysed data from 796 patients with SLE from the phase III trial BLISS-SC. Unsupervised machine learning employing factor analysis of mixed data (FAMD) and subsequent clustering determined endotypes based on B cell immunophenotyping and serological profiles. Cox regression was used to assess belimumab efficacy on inducing lupus low disease activity state (LLDAS) and definitions of remission in SLE (DORIS) remission within clusters. Results Three endotypes were determined. Compared with each other, cluster 1 (n = 191) displayed higher proportions of CD19+CD24b+CD27+ regulatory B cells (mean ± SD: 35.9%±12.6%), CD19+CD20+CD27+ bulk memory B cells (32.2%±9.9%), CD19+CD20+CD69+ activated B cells (0.2%±0.3%), CD19+CD20-CD138+ long-lived plasma cells (0.7%±1.0%) and CD19+CD38b+CD27b+ SLE-associated plasma cells (6.6%±7.0%). Cluster 2 (n = 366) displayed higher proportions of CD19+CD24bbrightCD38bbrightCD27- transitional B cells (6.3%±9.0%) and CD19+CD20+CD27- naïve B cells (85.4%±7.2%), and lower proportions of CD19+CD20-CD138+ peripheral long-lived plasma cells (0.2%±0.3%) and CD19+CD38b+CD27b+ SLE-associated plasma cells (1.6%±2.0%). Cluster 3 (n = 239) displayed a higher proportion of CD19+CD20+CD138+ short-lived plasma cells (0.1%±0.1%) and higher serological activity, being enriched in anti-double stranded(ds)DNA, anti-ENAs, antiphospholipid antibodies and hypocomplementemia. Use of belimumab was superior to placebo in inducing sustained LLDAS [hazard ratio (HR): 2.22; 95% CI: 1.18-4.17; P = 0.014] and DORIS remission (HR: 3.45; 95% CI: 1.2-9.94; P = 0.022) in cluster 2. Conclusion Three distinct SLE endotypes were identified based on B cell immunophenotyping and serological profiles, showing differential benefit from belimumab therapy.