ArticleClinical immunology (Orlando, Fla.)2019
Compendium of synovial signatures identifies pathologic characteristics for predicting treatment response in rheumatoid arthritis patients.
Article in Clinical immunology (Orlando, Fla.), 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 20 papers, 1 of them a synthesis that pooled it.
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
20 citing papers in PubMed, 1 synthesis or guideline pooled it, 30 citations in OpenAlex.
- Machine learning for predicting treatment response to biologic and targeted synthetic disease-modifying antirheumatic drugs in rheumatoid arthritis: a scoping review.BMC rheumatology · 2025Pooled it
- Immunological heterogeneity in rheumatoid arthritis: challenges in early-stage stratification, non-response to targeted therapy, and the restoration of immune tolerance.Frontiers in immunology · 2026Review
- BACH1 as a key driver in rheumatoid arthritis fibroblast-like synoviocytes identified through gene network analysis.Life science alliance · 2025Article
- The molecular subtypes of autoimmune diseases.Computational and structural biotechnology journal · 2024Review
- Unveiling Artificial Intelligence's Power: Precision, Personalization, and Progress in Rheumatology.Journal of clinical medicine · 2024Review
- Application of artificial intelligence in rheumatic disease: a bibliometric analysis.Clinical and experimental medicine · 2024Article
- Gene Network Analyses Identify Co-regulated Transcription Factors and BACH1 as a Key Driver in Rheumatoid Arthritis Fibroblast-like Synoviocytes.bioRxiv : the preprint server for biology · 2024Article
- Advancing precision rheumatology: applications of machine learning for rheumatoid arthritis management.Frontiers in immunology · 2024Review
- Cell-specific gene networks and drivers in rheumatoid arthritis synovial tissues.Frontiers in immunology · 2024Article
- Transcriptional profiling upon T cell stimulation reveals down-regulation of inflammatory pathways in T and B cells in SLE versus Sjögren's syndrome.NPJ systems biology and applications · 2023Article
- Diagnosing growing pains in children by using machine learning: a cross-sectional multicenter study.Medical & biological engineering & computing · 2022Article
- Artificial Intelligence in Rheumatoid Arthritis: Current Status and Future Perspectives: A State-of-the-Art Review.Rheumatology and therapy · 2022Review
- Structural Strength Analyses for Low Brass Filler Biomaterial with Anti-Trauma Effects in Articular Cartilage Scaffold Design.Materials (Basel, Switzerland) · 2022Article
- The differential diagnosis of IgG4-related disease based on machine learning.Arthritis research & therapy · 2022Article
- Precision Medicine for Rheumatoid Arthritis: The Right Drug for the Right Patient-Companion Diagnostics.Diagnostics (Basel, Switzerland) · 2021Review
- Data-Driven Patient Clustering and Differential Clinical Outcomes in the Brigham and Women's Rheumatoid Arthritis Sequential Study Registry.Arthritis care & research · 2021Observational
- Machine Learning in Rheumatic Diseases.Clinical reviews in allergy & immunology · 2021Review
- An Efficient CNN for Hand X-Ray Classification of Rheumatoid Arthritis.Journal of healthcare engineering · 2021Article
- Machine learning in rheumatology approaches the clinic.Nature reviews. Rheumatology · 2020Review
- Integrated systems analysis of salivary gland transcriptomics reveals key molecular networks in Sjögren's syndrome.Arthritis research & therapy · 2019Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
4 authors at 2 institutions in 2 countries.
Funding
Abstract
Rheumatoid arthritis (RA) is therapeutically challenging due to patient heterogeneity and variability. Herein we describe a novel integration of RA synovial genome-scale transcriptomic profiling of different patient cohorts that can be used to provide predictive insights on drug responses. A normalized compendium consisting of 256 RA synovial samples that cover an intersection of 11,769 genes from 11 datasets was build and compared with similar datasets derived from OA patients and healthy controls. Differentially expression genes (DEGs) that were identified in three independent methods were fed into functional network analysis, with subsequent grouping of the samples based on a non-negative matrix factorization method. RA-relevant pathway activation scores and four machine learning classification techniques supported the generation of a predictive model of patient treatment response. We identified 876 up-regulated DEGs including 24 known genetic risk factors and 8 drug targets. DEG-based subgrouping revealed 3 distinct RA patient clusters with distinct activity signatures for RA-relevant pathways. In the case of infliximab, we constructed a classifier of drug response that was highly accurate with an AUC/AUPR of 0.92/0.86. The most informative pathways in achieving this performance were the NFκB-, FcεRI- TCR-, and TNF signaling pathways. Similarly, the expression of the HMMR, PRPF4B, EVI2A, RAB27A, MALT1, SNX6, and IFIH1 genes contributed in predicting the patient outcome. Construction and analysis of normalized synovial transcriptomic compendia can provide useful insights for understanding RA-related pathway involvement and drug responses for individual patients.
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.