Background
Gout is the most prevalent inflammatory arthritis, its gold standard of diagnosis is detection of monosodium urate crystals in joints. However, the invasive test limited its use in the diagnosis of gout. Thus, there is an urgent need to exploit a novel biomarker to predict and early diagnose the gout flare.
Methods
In this study, we aimed to screen out the potential biomarkers of gout from GEO database (GSE178825) through bioinformatics analysis.
Results
The results showed that 4994 DEGs (43 up-regulated genes and 13 down-regulated genes) were identified between gout patients and healthy control. DEGs were mostly enriched in DNA repair, sphingolipid biosynthetic process, membrane. MAN1A2 was the most important hub genes in the PPI network.And then a series of enrichment bioinformatics methods were performed, cricMAN1A2 was selected as novel biomarker, which levels was measured in 30 gout patients, 30 hyperuricemia patients and 30 healthy controls by qRT-PCR. Subsequently, ROC (receiver operating characteristic cuver) were used to evaluated the potential role of cricMAN1A2 as biomarker for gout. The levels of circMAN1A2 was significantly lower in the gout patients than those in healthy controls, with higher diagnostic efficiency(AUC(area under the ROC curve) = 0.86).
Conclusions
Our results provide key cricRNAs related to gout, and cricMAN1A2 could be a novel serum biomarker for gout diagnosis.