Serum N-glycan profiling as a diagnostic biomarker for the identification and assessment of psoriasis

被引:10
|
作者
Zou, Chengyun [1 ]
Huang, Chenjun [2 ]
Yan, Li [3 ]
Li, Xin [4 ]
Xing, Meng [4 ]
Li, Bin [4 ]
Gao, Chunfang [2 ]
Wang, Haiying [3 ]
机构
[1] Shanghai Univ Tradit Chinese Med, Shanghai, Peoples R China
[2] Naval Med Univ, Affiliated Hosp 3, Dept Lab Med, Shanghai, Peoples R China
[3] Shanghai Univ Tradit Chinese Med, Yueyang Hosp Integrated Tradit Chinese & Western, Dept Clin Lab, 110 Gan He Rd, Shanghai 200437, Peoples R China
[4] Shanghai Univ Tradit Chinese Med, Yueyang Hosp Integrated Tradit Chinese & Western, Dept Dermatol, Shanghai, Peoples R China
关键词
biomarker; diagnostic model; glycosylation; N-glycan profiling; psoriasis;
D O I
10.1002/jcla.23711
中图分类号
R446 [实验室诊断]; R-33 [实验医学、医学实验];
学科分类号
1001 ;
摘要
Background: Glycosylation is an important post-translational modification of protein. The change in glycosylation is involved in the occurrence and development of various diseases, and this study verified that N-glycan markers might be a diagnostic marker in psoriasis. Methods: A total of 76 psoriasis patients were recruited. We used Psoriasis Area Severity Index (PASI) scores to evaluate the state of psoriasis, 41 of whom were divided into three subgroups: mild, moderate, and severe. At the same time, 76 healthy subjects were enrolled as a control group. We used DNA sequencer-assisted fluorophore-assisted carbohydrate electrophoresis (DSA-FACE) to analyze serum N-glycan profiling. Results: Compared with the healthy controls, the relative abundance of structures in peaks 5(NA2), 9(NA3Fb), 11(NA4), and 12(NA4Fb) was elevated (p < .05), while that in peaks 3(NG1A2F), 4(NG1A2F), 6(NA2F), and 7(NA2FB) was decreased (p < .05) in the psoriasis group. The abundance of peak 5 (NA2) increased gradually with the aggravation of disease severity though there was no statistically significant, was probably correlated with the disease severity. The best area under the receiver operating characteristic (ROC) curve (AUC) of the logistic regression model (PglycoA) to diagnose psoriasis was 0.867, with a sensitivity of 72.37%, a specificity of 85.53%, a positive predictive value(PPV) of 83.33%, a negative predictive value(NPV) of 75.58%, and an accuracy of 78.95%. Conclusions: Our study indicated that the N-glycan-based diagnostic model would be a new, valuable, and noninvasive alternative for diagnosing psoriasis. Furthermore, the characteristic distinctive N-glycan marker might be correlated with the severity gradation of the psoriasis disease.
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页数:10
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