J Rheum Dis.  2022 Jan;29(1):33-39. 10.4078/jrd.2022.29.1.33.

Serum miR-3620-3p as a Novel Biomarker for Ankylosing Spondylitis

Affiliations
  • 1Department of Rheumatology, Chonnam National University Medical School and Hospital, Gwangju, Korea

Abstract


Objective
Using microRNA (miR) as a biomarker has been a new way for diagnosing many diseases. Although many studies on miR-biomarker have been published, researches on miR-biomarker in ankylosing spondylitis (AS) are limited. Therefore, the objective of this study was to valiate a candidate serum miR as a novel disease-specific novel miR for AS.
Methods
Total RNAs were extracted from sera samples of patients with AS (n=57), patients with rheumatoid arthritis (RA) (n=37), or healthy controls (HC) (n=19). Through serum miR screening by microarray, differential levels of miR were subsequently validated by real time PCR. At the time of serum sampling, clinical values such as sex, age, disease duration, AS-disease activity score, uveitis, peripheral arthritis, enthesitis, human leukocyte antigen-B27 presence, and recent medication were evaluated.
Results
We found that the expression level of serum miR-3620-3p in AS was notably lower than that in RA or HC. The receiver–operator characteristics curve for determining the diagnostic accuracy showed an area under the curve of 0.919 (p<0.001) with a sensitivity of 87.1% and a specificity of 86.0%. Correlation studies showed that the expression level of miR-3620-3p was only associated with the development of uveitis (p<0.05).
Conclusion
Serum miR-3620-3p can be as a new biomarker for diagnosing AS.

Keyword

Spondylitis; ankylosing; Circulating microRNA; Biomarker

Figure

  • Figure 1 Expression levels of microRNA (miR)‐3620-3p between groups. Serum samples from healthy controls (HCs), ankylosing spondylitis (AS), and rheumatoid arthritis (RA) were obtained. RNAs was extracted from serum samples. Quantitative polymerase chain reaction (qPCR) was performed with a miScript System (Qiagen Inc., Valencia, CA, USA) using specific primers for miRs. Cycle threshold values were converted to copy numbers by drawing a standard curve using a chemical synthetic spike‐in standard. Values are shown as the mean±standard error of the mean. One‐way analysis of variance was used to compare gene expression between groups.

  • Figure 2 Analyses of the diagnostic potential for discerning ankylosing spondylitis (AS). ROC curve analysis of microRNA (miR)-3620-3p signature was performed to assess its potential as a diagnostic biomarkers for AS. A cut-off value with higher specificity and sensitivity was selected. ROC curve analysis of miR was carried out to assess the potential as diagnostic biomarkers. AUC: area under the curve, ROC: receiver operator characteristic.

  • Figure 3 Analysis of the relationship of microRNA (miR)‐3620-3p with sex (A), the disease‐specific variables (B∼E) and use of tumor necrosis factor (TNF) blocker (F). Patients with a history of uveitis had significant higher levels of miR-3620-3p than those without a history of uveitis. Clinical comparisons were carried out using Wilcoxon’s rank sum tests for continuous measures that showed non-normally distribution. Student t-tests were performed for normally distributed values. HLA: human leukocyte antigen.

  • Figure 4 Correlation analysis between microRNA (miR)‐3620-3p and clinical variables. Correlation results showed that miR‐3620-3p levels were not associated with age (A), Ankylosing spondylitis disease activity score (ASDAS) with C-reactive protein (CRP) (B), bath ankylosing spondylitis functional index (BASFI) (C), or bath ankylosing spondylitis radiographgic index (BASRI score) (D). Kendall’s correlation coefficient for non‐normally distributed continuous data and Pearson’s correlation coefficient for normally distributed continuous data were determined to test statistical dependency between parameters.


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