Disease activity drives transcriptomic heterogeneity in early untreated rheumatoid synovitis.

ABSTRACT:

Objectives

Transcriptomic profiling of synovial tissue from patients with early, untreated rheumatoid arthritis (RA) was used to explore the ability of unbiased, data-driven approaches to define clinically relevant subgroups.

Methods

RNASeq was performed on 74 samples, with disease activity data collected at inclusion. Principal components analysis (PCA) and unsupervised clustering were used to define patient clusters based on expression of the most variable genes, followed by pathway analysis and inference of relative abundance of immune cell subsets. Histological assessment and multiplex immunofluorescence (for CD45, CD68, CD206) were performed on paraffin sections.

Results

PCA on expression of the (n=894) most variable genes across this series did not divide sample

SUBMITTER: Triaille C 

PROVIDER: S-EPMC10646909 | biostudies-literature | 2023 Dec

REPOSITORIES: biostudies-literature