ArticleAnnals of the rheumatic diseases2023
Machine learning identifies clusters of longitudinal autoantibody profiles predictive of systemic lupus erythematosus disease outcomes.
Article in Annals of the rheumatic diseases, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 39 papers, 1 of them a synthesis that pooled it.
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Who cites it
39 citing papers in PubMed, 1 synthesis or guideline pooled it, 69 citations in OpenAlex.
- Diagnostic accuracy of machine learning approaches to identify psoriatic arthritis: a meta-analysis.Clinical and experimental medicine · 2025Pooled it
- A machine learning-based classification model for interstitial lung disease in rheumatoid arthritis.Frontiers in medicine · 2026Trial
- Efficacy of Risankizumab across distinct PsA phenotypes identified with machine learning analytics using data from biologic DMARD-Naïve patients in two phase 3 clinical trials.Arthritis research & therapy · 2025Trial
- Unsupervised machine learning identifies distinct SLE patient endotypes with differential response to belimumab.Rheumatology (Oxford, England) · 2025Trial
- An explainable machine learning model for predicting in-hospital infection in patients with systemic lupus erythematosus.Renal failure · 2026Article
- From pathogenesis to precision medicine in systemic lupus erythematosus: Emerging biomarkers and targeted interventions.iScience · 2026Review
- Clotting the Gap Between Mitochondria-Mediated Immunity and Mitochondrial Transfer.Circulation research · 2026Review
- Unsupervised clustering of clinical and laboratory features of systemic lupus erythematosus: insights from a multicentre cohort.Lupus science & medicine · 2026Article
- Antimitochondrial antibodies in systemic lupus erythematosus are associated with and predict nephritis, arterial vascular events, and mortality.Annals of the rheumatic diseases · 2026Article
- Applications of artificial intelligence in systemic lupus erythematosus: integrating multi-omics data for precision medicine.Frontiers in immunology · 2026Review
- Immunophenotypic Stratification of Primary Sjögren's Syndrome Reveals Distinct Lymphocyte Profiles and Clinical Manifestations.Journal of immunology research · 2026Article
- Serologic evidence of orthomarburgviruses and an orthoebolavirus in frugivorous Malagasy bats.One health outlook · 2025Article
- Observational
- Data-Driven Cluster Analysis of Cerebrospinal Fluid Proteome and Associations with Clinical Phenotypes in Systemic Lupus Erythematosus.ACR open rheumatology · 2025Article
- Dialogue: Validation of eight endotypes of lupus based on whole-blood RNA profiles.Lupus science & medicine · 2025Article
- Potential Biomarkers in Systemic Lupus Erythematosus.JMA journal · 2025Review
- Defining immune reset: achieving sustained remission in autoimmune diseases.Nature reviews. Immunology · 2025Review
- Immune cell aberrations in Systemic Lupus Erythematosus: navigating the targeted therapies toward precision management.Cellular & molecular biology letters · 2025Review
- Identification of Three Distinct Subgroups in Antiphospholipid Syndrome: Implication for Sex Differences and Prognostic Outcomes from a Multicenter Study.Advanced science (Weinheim, Baden-Wurttemberg, Germany) · 2025Article
- Hearing Loss in Connective Tissue Diseases: A Systematic Review.European journal of rheumatology · 2025Article
Corrections and comments
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Authors and funding
41 authors at 20 institutions in 10 countries.
Funding
Abstract
objectivesA novel longitudinal clustering technique was applied to comprehensive autoantibody data from a large, well-characterised, multinational inception systemic lupus erythematosus (SLE) cohort to determine profiles predictive of clinical outcomes.
methodsDemographic, clinical and serological data from 805 patients with SLE obtained within 15 months of diagnosis and at 3-year and 5-year follow-up were included. For each visit, sera were assessed for 29 antinuclear antibodies (ANA) immunofluorescence patterns and 20 autoantibodies. K-means clustering on principal component analysis-transformed longitudinal autoantibody profiles identified discrete phenotypic clusters. One-way analysis of variance compared cluster enrolment demographics and clinical outcomes at 10-year follow-up. Cox proportional hazards model estimated the HR for survival adjusting for age of disease onset.
resultsCluster 1 (n=137, high frequency of anti-Smith, anti-U1RNP, AC-5 (large nuclear speckled pattern) and high ANA titres) had the highest cumulative disease activity and immunosuppressants/biologics use at year 10. Cluster 2 (n=376, low anti-double stranded DNA (dsDNA) and ANA titres) had the lowest disease activity, frequency of lupus nephritis and immunosuppressants/biologics use. Cluster 3 (n=80, highest frequency of all five antiphospholipid antibodies) had the highest frequency of seizures and hypocomplementaemia. Cluster 4 (n=212) also had high disease activity and was characterised by multiple autoantibody reactivity including to antihistone, anti-dsDNA, antiribosomal P, anti-Sjögren syndrome antigen A or Ro60, anti-Sjögren syndrome antigen B or La, anti-Ro52/Tripartite Motif Protein 21, antiproliferating cell nuclear antigen and anticentromere B). Clusters 1 (adjusted HR 2.60 (95% CI 1.12 to 6.05), p=0.03) and 3 (adjusted HR 2.87 (95% CI 1.22 to 6.74), p=0.02) had lower survival compared with cluster 2.
conclusionFour discrete SLE patient longitudinal autoantibody clusters were predictive of long-term disease activity, organ involvement, treatment requirements and mortality risk.
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Registered trials
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