Abstract: 【Abstract】 Objective To analyze serum inflammatory factors associated with antihistamine resistance in patients with chronic spontaneous urticaria （CSU）. Methods A total of 88 CSU patients were enrolled from Guangzhou Dermatology Hospital from January 2022 to December 2024. All patients received antihistamine treatment according to the “Guideline for diagnosis and treatment of urticaria in China （2022）”. Based on the 7-day urticaria activity score （UAS7） after 4-week treatment, these patients were divided into an antihistamine-sensitive group and an antihistamine-resistant group. Serum levels of inflammatory factors at the initial visit were analyzed using the Olink-targeted proteomics technology. Specific biomarkers associated with antihistamine resistance were identified, and Spearman correlation analysis was carried out to analyze correlations among differentially expressed proteins. A logistic regression model was constructed based on the Olink proteomics data, and the predictive performance of the model was evaluated using receiver operating characteristic （ROC） curve analysis. Measurement data were expressed as mean ± standard deviation or median （lower quartile, upper quartile）. Results The 88 CSU patients aged 12 to 81 （38.78 ± 13.89） years, with the disease duration being 18 （7.00, 60.00） months. There were 32 patients in the antihistamine-sensitive group and 56 in the antihistamine-resistant group. No significant differences were found between the two groups in terms of age, disease duration, gender, or history of allergic diseases （all P > 0.05）. After 4 weeks of antihistamine treatment, the UAS7 score was significantly higher in the antihistamine-resistant group （25.00 ［15.25, 31.00］ points） than in the antihistamine-sensitive group （0.50 ［0.00, 4.00］ points; Z = -7.08, P < 0.001）. The Olink-targeted proteomics identified 5 differentially expressed proteins between the two groups: compared with the antihistamine-sensitive group, the antihistamine-resistant group showed > 2-fold higher expression of fibroblast growth factor 19 （FGF19）, interleukin-15 receptor subunit alpha （IL-15RA）, eotaxin （CCL11）, and monocyte chemoattractant protein-1 （MCP-1）; in contrast, the expression of sulfotransferase 1A1 （ST1A1） in the antihistamine-sensitive group was 2.54 times that in the antihistamine-resistant group. Among the differentially expressed proteins, MCP-1 showed the highest specificity （1.00） for predicting antihistamine resistance, followed by CCL11 （0.97）. Correlation analysis revealed a significant positive correlation between MCP-1 and CCL11, and a significant negative correlation between IL-15RA and ST1A1. ROC curve analysis showed that MCP-1 and CCL11 had area under the curve values of 0.603 and 0.630, respectively, in predicting antihistamine resistance. Conclusion MCP-1 and CCL11 may be potential biomarkers for predicting antihistamine resistance in CSU patients.

Key words: Chronic urticaria, Proteomics, Histamine H1 antagonists, non-sedating, Chemokine CCL2, Chemokine CCL11, Chronic spontaneous urticaria