Background: Establishing the diagnosis and determining disease activity of Takayasu arteritis (TA) remains challenging. Novel biomarkers might help to solve this problem.
Methods: In the screening phase, by using large-scale protein arrays detecting samples from 90 subjects (TA active, 29; TA inactive 31; and controls, 30). In the validation phase, by using enzyme-linked immunosorbent assay (ELISA), potential biomarkers for TA diagnosis, and activity classification were measured in independent cohorts, respectively.
Results: In the screening phase, 18 cytokines significantly differentially enriched between TA patients and controls and another 15 cytokines significantly differentially enriched between TA patient in active and inactive status were identified (adjusted P<0.05). In the validation phase, TIMP (tissue inhibitor of metalloproteinases)-1 was identified as a specific biomarker for TA diagnosis that a cutoff value of 221.86 μg/L could provide a specificity of 89.58% and a positive predictive value of 0.92. Meanwhile, we found it unreliable to use a single biomarker for TA activity classification. Considering this, we further built a logistic regression model based on multiple cytokines, including CA (cancer antigen) 125, FLRG (follistatin-related protein), IGFBP (insulin-like growth factor-binding protein)-2, CA15-3, GROa (growth-regulated alpha protein), LYVE (lymphatic vessel endothelial hyaluronic acid receptor)-1, ULBP (UL16-binding protein)-2, and CD (cluster of differentiation) 99, with an area under the curve reaching 0.909 for discriminating TA activity status.
Conclusions: This study suggested TIMP-1 as a specific biomarker for TA diagnosis with a cutoff value of 221.86 μg/L. Furthermore, we provided a logistic regression model based on 8 biomarkers for the precisive activity classification of TA with an area under the curve of 0.909.
Keywords: arteritis; biomarker; cytokines; proteomics.