ArticleLupus science & medicine2023
Targeted multiomics in childhood-onset SLE reveal distinct biological phenotypes associated with disease activity: results from an explorative study.
Article in Lupus science & medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
8 citing papers in PubMed.
- Distinct peripheral B-cell immunophenotypes define clinical heterogeneity in childhood-onset systemic lupus erythematosus.World journal of pediatrics : WJP · 2026Article
- [New biomarker-based diagnostic tests : Early and precise diagnosis of rheumatological diseases].Zeitschrift fur Rheumatologie · 2026Review
- Insights into the pathogenesis of childhood-onset SLE in the past decade.Nature reviews. Rheumatology · 2026Review
- Immune ontogeny in childhood-onset systemic lupus erythematosus: effect of immune maturity on disease phenotype and therapeutic responses.Frontiers in immunology · 2026Review
- Anti-mitochondrial antibodies as markers of disease activity in childhood-onset systemic lupus erythematosus: a longitudinal cohort study.Rheumatology (Oxford, England) · 2025Article
- Childhood-Onset Systemic Lupus Erythematosus (cSLE): An International Perspective.Current allergy and asthma reports · 2024Review
- Emerging insights into atypical B cells in pediatric chronic infectious diseases and immune system disorders: T(o)-bet on control of B-cell immune activation.The Journal of allergy and clinical immunology · 2024Review
- Automated EuroFlow approach for standardized in-depth dissection of human circulating B-cells and plasma cells.Frontiers in immunology · 2023Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
12 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
objectiveTo 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.
methodsTargeted 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.
resultsThree 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.
conclusionUsing 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.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.