2 research outputs found

    LLDAS is an attainable treat-to-target goal in childhood-onset SLE

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    Objectives To study whether clinical remission (CR) and Low Lupus Disease Activity State (LLDAS) are achievable goals in childhood-onset SLE. Methods Data on medication use and disease activity were prospectively collected. LLDAS was defined as Safety of Estrogen in Lupus Erythematosus National Assesment-SLE disease Activity Index (SELENA-SLEDAI) ≤4 with zero scores for renal, Central Nervous System (CNS), serositis, vasculitis and constitutional components, no increase in any SLEDAI component since the previous visit, PGA ≤1, and prednisone dose ≤7.5 mg/day. CR on treatment (Tx) was defined as a Physician Global Assessment 50% of time. 52.9% children achieved CR on Tx, and only 21.6% children achieved CR off Tx. Conclusions LLDAS is an attainable treat-to-target goal in contrast to CR on and off Tx. Even more, LLDAS can be reached with limited use of corticosteroids with early introduction of immunosuppressives

    Targeted multiomics in childhood-onset SLE reveal distinct biological phenotypes associated with disease activity: results from an explorative study

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    Objective To combine targeted transcriptomic and proteomic data in an unsupervised hierarchical clustering method to stratify patients with childhood-onset SLE (cSLE) into similar biological phenotypes, and study the immunological cellular landscape that characterises the clusters.Methods Targeted whole blood gene expression and serum cytokines were determined in patients with cSLE, preselected on disease activity state (at diagnosis, Low Lupus Disease Activity State (LLDAS), flare). Unsupervised hierarchical clustering, agnostic to disease characteristics, was used to identify clusters with distinct biological phenotypes. Disease activity was scored by clinical SELENA-SLEDAI (Safety of Estrogens in Systemic Lupus Erythematosus National Assessment-Systemic Lupus Erythematosus Disease Activity Index). High-dimensional 40-colour flow cytometry was used to identify immune cell subsets.Results Three unique clusters were identified, each characterised by a set of differentially expressed genes and cytokines, and by disease activity state: cluster 1 contained primarily patients in LLDAS, cluster 2 contained mainly treatment-naïve patients at diagnosis and cluster 3 contained a mixed group of patients, namely in LLDAS, at diagnosis and disease flare. The biological phenotypes did not reflect previous organ system involvement and over time, patients could move from one cluster to another. Healthy controls clustered together in cluster 1. Specific immune cell subsets, including CD11c+ B cells, conventional dendritic cells, plasmablasts and early effector CD4+ T cells, differed between the clusters.Conclusion Using a targeted multiomic approach, we clustered patients into distinct biological phenotypes that are related to disease activity state but not to organ system involvement. This supports a new concept where choice of treatment and tapering strategies are not solely based on clinical phenotype but includes measuring novel biological parameters
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