Predictive Ability of Serum IL-27 Level for Assessing Activity of Antineutrophil Cytoplasmic Antibody-Associated Vasculitis.
Taejun YoonSung Soo AhnJung Yoo PyoLucy Eunju LeeJason Jungsik SongYong-Beom ParkSang-Won LeePublished in: Mediators of inflammation (2021)
Serum interleukin- (IL-) 27 level has been reported to increase in patients with several autoimmune diseases; however, its significance in patients with antineutrophil cytoplasmic antibody- (ANCA-) associated vasculitis (AAV) is unknown. In this study, we investigated the associations between serum IL-27, laboratory features, and activity of AAV and evaluate the predictive ability of serum IL-27 level for disease activity. This study included 77 AAV patients, and we collected clinical and laboratory data at blood sampling. Inflammation-related variables included white blood cell, neutrophil, lymphocyte and platelet counts, serum albumin, erythrocyte sedimentation rate, and C-reactive protein levels. Serum IL-27 and IL-18 levels were measured from stored sera using Human Magnetic Luminex® assay. High disease activity of AAV was defined as the highest tertile of Birmingham vasculitis activity score (BVAS) (≥11). The mean age of the enrolled patients was 59.9 years, and 38 (49.4%) were diagnosed as microscopic polyangiitis. In the multivariable analysis, serum albumin (β = -0.419) and serum IL-27 level (β = 0.221) were significantly associated with BVAS. Furthermore, patients with renal manifestation exhibited higher serum IL-27 (mean 308.7 pg/mL vs. 105.8 pg/mL) and IL-18 levels (mean 376.7 pg/mL vs. 270.4 pg/mL) than those without. On applying the optimal cut-off of serum IL-27 level for predicting high activity, AAV patients with serum IL - 27 level ≥ 300.8 pg/mL had a significantly higher risk for having high disease activity than those with serum IL - 27 level < 300.8 pg/mL (relative risk 3.380, 95% confidence interval 1.223, 9.345, P = 0.016). These results suggest that serum IL-27 level is associated with the cross-sectional activity and the presence of renal manifestation and could be used to predict high disease activity in patients with AAV.
Keyphrases
- disease activity
- rheumatoid arthritis
- systemic lupus erythematosus
- rheumatoid arthritis patients
- ankylosing spondylitis
- cross sectional
- juvenile idiopathic arthritis
- ejection fraction
- endothelial cells
- gene therapy
- mesenchymal stem cells
- prognostic factors
- chronic kidney disease
- deep learning
- big data
- artificial intelligence
- electronic health record
- cell therapy