Whole blood microRNA expression pattern differentiates patients with rheumatoid arthritis, their seropositive first-degree relatives, and healthy unrelated control subjects
Abstract Background Epigenetic mechanisms can integrate gene-environment interactions that mediate disease transition from preclinical to clinically overt rheumatoid arthritis (RA). To better understand their role, we evaluated microRNA (miRNA, miR) expression profile in indigenous North American patients with RA who were positive for anticitrullinated protein antibodies; their autoantibody-positive, asymptomatic first-degree relatives (FDRs); and disease-free healthy control subjects (HCs). Methods Total RNA was isolated from whole blood samples obtained from HC (n = 12), patients with RA (n = 18), and FDRs (n = 12). Expression of 35 selected relevant miRNAs, as well as associated downstream messenger RNA (mRNA) targets of miR-103a-3p, was determined by qRT-PCR. Results Whole blood expression profiling identified significantly differential miRNA expression in patients with RA (13 miRNAs) and FDRs (10 miRNAs) compared with HCs. Among these, expression of miR-103a-3p, miR-155, miR-146a-5p, and miR-26b-3p was significantly upregulated, whereas miR-346 was significantly downregulated, in both study groups. Expression of miR-103a-3p was consistently elevated in FDRs at two time points 1 year apart. We also confirmed increased miR-103a-3p expression in peripheral blood mononuclear cells from patients with RA compared with HCs. Predicted target analyses of differentially expressed miRNAs in patients with RA and FDRs showed overlapping biological networks. Consistent with these curated networks, mRNA expression of DICER1, AGO1, CREB1, DAPK1, and TP53 was downregulated significantly with miR-103a-3p expression in FDRs. Conclusions We highlight systematically altered circulating miRNA expression in at-risk FDRs prior to RA onset, a profile they shared with patients with RA. Prominently consistent miR-103a-3p expression indicates its utility as a prognostic biomarker for preclinical RA while highlighting biological pathways important for transition to clinically detectable disease.
Arthritis Research & Therapy. 2017 Nov 10;19(1):249