Identifying Reliable Diagnostic/Predictive Biomarkers for Rheumatoid Arthritis

Abstract

Introduction and objective:
Elevated C-reactive protein is usually a good indicator of rheumatoid arthritis (RA); however, there are limitations that compromise its specificity and therefore there is an urgent need to identify more reliable diagnostic biomarkers to detect early stages of RA. In addition, identifying the correct therapeutic biomarker for the treatment of RA using methotrexate (MTX) would greatly increase the benefits experienced by the patients.

Materials and methods:
Primary normal synoviocytes human fibroblast-like synoviocytes (HFLS) and its phenotype rheumatic HFLS-RA cells were chosen for this study. The HFLS-RA–untreated and MTX-treated cells were subjected to microarray analysis.

Results:
Microarray data identified 74 differentially expressed genes. These genes were mapped against an RA inflammatory pathway, shortlisting 10 candidate genes. Gene expression profiling of the 10 genes were studied. Fold change (FC) was calculated to determine the differential expression of the samples.

Discussion:
The transcription profiles of the 10 candidate genes were highly induced in HFLS-RA cells compared with HFLS cells. However, on treating the HFLS-RA cells with MTX, the transcription profiles of these genes were highly downregulated. The most significant expression FC difference between HFLS and HFLS-RA (treated and untreated) was observed with HSPA6, MMP1, MMP13, and TNFSF10 genes.

Conclusions:
The data from this study suggest the use of HSPA6, MMP1, MMP13, and TNFSF10 gene expression profiles as potential diagnostic biomarkers. In addition, these gene profiles can help in predicting the therapeutic efficacy of MTX.