Novel biomarkers of a peripheral blood interferon signature associated with drug-naïve early arthritis patients distinguish persistent from self-limiting disease course.

ABSTRACT

We profiled gene expression signatures to distinguish rheumatoid arthritis (RA) from non-inflammatory arthralgia (NIA), self-limiting arthritis (SLA), and undifferentiated arthritis (UA) as compared to healthy controls as novel potential biomarkers for therapeutic responsiveness. Global gene expression profiles of PBMCs from 43 drug-naïve patients presenting with joint symptoms were evaluated and differentially expressed genes identified by comparative analysis with 24 healthy volunteers. Patients were assessed at presentation with follow up at 6 and 12 months. Gene ontology and network pathway analysis were performed using DAVID Bioinformatics Resources v6.7. Gene expression profiles were also determined after disease-modifying anti-rheumatic drug (DMARD) treatment in the inflammatory arthritis groups (i.e. RA and UA) and confirmed by qRT-PCR. Receiver operating characteristic (ROC) curves analysis and Area Under the Curve (AUC) estimation were performed to assess the diagnostic value of candidate gene expression signatures. A type I interferon (IFN) gene signature distinguished DMARD-naïve patients who will subsequently develop persistent inflammatory arthritis (i.e. RA and UA) from those with NIA. In patients with RA, the IFN signature is characterised by up-regulation of SIGLEC1 (p = 0.00597) and MS4A4A (p = 0.00000904). We also identified, EPHB2 (p = 0.000542) and PDZK1IP1 (p = 0.0206) with RA-specific gene expression profiles and elevated expression of the ST6GALNAC1 (p = 0.0023) gene in UA. ROC and AUC risk score analysis suggested that MSA4A (AUC 0.894, 0.644, 0.720), PDZK1IP1 (AUC 0.785, 0.806, 0.977), and EPHB2 (AUC 0.794, 0.723, 0.620) at 0, 6, and 12 months follow-up can accurately discriminate patients with RA from healthy controls and may have practical value for RA diagnosis. In patients with early inflammatory arthritis, ST6GALNAC1 is a potential biomarker for UA as compared with healthy controls whereas EPHB2, MS4A4A, and particularly PDZK1IP1 may discriminate RA patients. SIGLEC1 may also be a useful marker of disease activity in UA.