TMT and PRM-Based Quantitative Proteomics Identify Potential Biomarkers for Behçet Syndrome

Background: Development of reliable, noninvasive clinical markers is crucial for early diagnosis of Behçet syndrome (BS). In this study, we aimed to identify potential serum biomarkers and construct a diagnostic panel for BS.Methods: Sera from 26 BS patients and 26 healthy controls (HCs) were collected and candidate biomarkers were explored using an untargeted shotgun proteomics approach based on tandem mass tags (TMTs) and a parallel reaction monitoring (PRM) analysis. ELISAs were further used for quantification of identified markers in 40 BS, 41 HCs, 20 rheumatoid arthritis (RA) and 20 Systemic lupus erythematosus (SLE). A random forest model and logistic regression algorithm were used for predictive model construction and validation.Results: TMT analysis identified 55 serum proteins differentially expressed between HC and BS patients. Using PRM and ELISA, we further identified 2 proteins which were significantly expressed between HC, BS, RA and SLE patients. By random forest modeling, 2 proteins TPM4, FLNA and individual age were selected as a diagnostic panel. A predictive model was built by logistic regression algorithm, which yielded area under the curve (AUC) values of 86.2%. The corresponding nomogram calibration curves showed good consistency. Additionally, this combinational diagnostic panel showed good predictive performance with an AUC of 0.74, specificity of 84.6%, sensitivity of 68.8% and accuracy of 75.8% in a blinded validation cohort.Conclusions: BS patients have distinct differences in serum proteomics profile compared to HCs. A predictive panel of TPM4, FLNA and age maybe used for BS diagnosis after validation in larger multiethnic cohorts.Clinical Trial: This study was registered on Chinese Clinical Trial Registry(ChiCTR2100048988).Funding: This research was funded by the National Natural Science Foundation of China (No. 81770101, 81403041), 1.3.5 project for disciplines of excellence, West China Hospital, Sichuan University (Project No. ZYJC18024; ZYJC18003; ZYGD18015).Declaration of Interest: None to declare. Ethical Approval: The study procedure was approved by the Biomedical Research Ethics Committee, West China Hospital of Sichuan University (No.593, 2019）