Open AccessSerum N ‐glycan profiling as a diagnostic biomarker for the identification and assessment of psoriasis
Author(s) -
Zou Chengyun,
Huang Chenjun,
Yan Li,
Li Xin,
Xing Meng,
Li Bin,
Gao Chunfang,
Wang Haiying
Publication year - 2021
Publication title -
journal of clinical laboratory analysis
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.536
H-Index - 50
eISSN - 1098-2825
pISSN - 0887-8013
DOI - 10.1002/jcla.23711
Subject(s) - psoriasis , medicine , biomarker , receiver operating characteristic , glycan , gastroenterology , glycosylation , area under the curve , logistic regression , immunology , chemistry , microbiology and biotechnology , biology , biochemistry , glycoprotein
Abstract 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.