Systemic lupus erythematosus (SLE) is a heterogeneous disease with unpredictable patterns of activity measured using mostly SLE disease activity index (SLEDAI). However, patients with similar SLEDAI scores have different molecular abnormalities and prognosis. We reported the longitudinal stratification of SLE into three clusters based on correlation between gene expression and SLEDAI.¹ Each of the clusters showed differences in the molecular pathways involved, the clinical manifestations, and how cell populations evolved with activity. In two clusters, the SLEDAI increase was linked to neutrophil increases, while in the third it was linked to increased lymphocyte counts. The neutrophil-driven clusters showed increased risk to develop proliferative nephritis. This presentation will show how the stratification was estimated and its clinical utility.

For drug analysis we used two cohorts from previous work¹ selecting gene expression data of one visit/patient with active SLE (SLEDAI>5). We compared patient gene signatures with drug derived gene signatures from the CLUE database, giving a connectivity score. The magnitude of the score reflects the potential efficacy of the drug.

Patient stratification based on drug connectivity scores revealed the same cluster structure previously described,¹ implying that differential treatment depends on the cluster to which patients belong. Drugs commonly used in SLE showed different connectivity values for each cluster and this depend on the cell-specific expression of the drug targets, suggesting that expression of target genes may provide insight in the prioritization of compounds. New drugs were also found.

We next constructed a model to classify patients to inform on drug use and predict nephritis applied to three new longitudinal cohorts. A meta-analysis showed a significantly higher incidence of nephritis in patients classified to a neutrophil-driven cluster.

Learning objectives

• Describe the possibility of stratifying patients with lupus using molecular transcriptome data

• Discuss how stratification of lupus can be of clinical use and help identify and prioritize new drugs

• Describe the most recent results on disease stratification

• Explain how unsupervised clustering integrating transcriptome and methylome data can be used to stratify SLE and other systemic autoimmune diseases

Reference

1. Toro-Dominguez D, Martorell-Marugan J, Goldman D, et al. Stratification of Systemic Lupus Erythematosus Patients Into Three Groups of Disease Activity Progression According to Longitudinal Gene Expression. Arthritis & Rheumatology (Hoboken, NJ) 2018;70(12):2025–35.