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Background:  Behçet’s disease (BD) is a chronic autoimmune disease. The early diagnosis of BD is very important to avoid serious and/or fatal complications such as eye damage, severe neurological involvement, and large vessel occlusion. New, sensitive biomarkers would aid in rapid diagnosis, the monitoring of disease activity, and the response to treatment.   Methods:  This study’s aim is to identify two immune system-related BD biomarkers. We measured long non-coding RNAs (lncRNAs)  NEAT1  (nuclear-enriched abundant transcript 1), and  lnc-DC  (lncRNA in dendritic cells) in serum by real-time polymerase chain reaction (RT-PCR) in 52 BD patients and 52 controls. We analyzed the association between  NEAT1  and  lnc-DC  and the clinical parameters of BD. Receiver operating characteristic (ROC) curve analysis was performed to explore the diagnostic performance of the studied genes.   Results:  Compared to controls, the significant upregulation of  NEAT1  {median [interquartile range (IQR)] = 1.68 (0.38–7.7),  p &amp;lt;  0.0001} and downregulation of  lnc-DC  [median (IQR) = 0.2 (0.12–1.39),  p =  0.03] were detected in the sera collected from BD patients. Higher serum expression levels of  NEAT1  and  lnc-DC  were significantly associated with the following clinical presentations: cutaneous lesions, vascular manifestations, articular manifestations, neurological manifestations, and higher disease activity score. Also, high  NEAT1  levels were significantly associated with a negative pathergy test, while higher  lnc-DC  was significantly associated with a positive family history. ROC curves showed that  NEAT1  and  lnc-DC  levels in serum could be used as predictors of BD with high specificity and fair sensitivity.  NEAT1  had an area under the curve (AUC) of 0.692 (95% CI: 0.591–0.794,  p  = 0.001), and  lnc-DC  had an AUC of 0.615 (95% CI: 0.508–0.723,  p  = 0.043).   Conclusion:  Serum lncRNAs  NEAT1  and  lnc-DC  are biomarkers for BD.

Expression of lncRNAs NEAT1 and lnc-DC in Serum From Patients With Behçet’s Disease Can Be Used as Predictors of Disease