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Immunoinflammatory Biomarkers in Serum Are Associated with Disease Severity in Atopic Dermatitis

斯科拉德 CCL17型 医学 特应性皮炎 生物标志物 内科学 疾病严重程度 免疫学 疾病 嗜酸性粒细胞 趋化因子受体 趋化因子 炎症 哮喘 生物 皮肤科生活质量指数 生物化学
作者
Jesper Grønlund Holm,Guillem Hurault,Tove Agner,Maja Lisa Clausen,Sanja Kežić,Reiko Tanaka,Simon Francis Thomsen
出处
期刊:Dermatology [Karger Publishers]
卷期号:237 (4): 513-520 被引量:15
标识
DOI:10.1159/000514503
摘要

A growing body of evidence links various biomarkers to atopic dermatitis (AD). Still, little is known about the association of specific biomarkers to disease characteristics and severity in AD.To explore the relationship between various immunological markers in the serum and disease severity in a hospital cohort of AD patients.Outpatients with AD referred to the Department of Dermatology, Bispebjerg Hospital, Copenhagen, Denmark, were divided into groups based on disease severity (SCORAD). Serum levels of a preselected panel of immunoinflammatory biomarkers were tested for association with disease characteristics. Two machine learning models were developed to predict SCORAD from the measured biomarkers.A total of 160 patients with AD were included; 53 (33.1%) with mild, 73 (45.6%) with moderate, and 34 (21.3%) with severe disease. Mean age was 29.2 years (range 6-70 years) and 84 (52.5%) were females. Numerous biomarkers showed a statistically significant correlation with SCORAD, with the strongest correlations seen for CCL17/thymus and activation-regulated chemokine (chemokine ligand-17/TARC) and CCL27/cutaneous T cell-attracting-chemokine (CTACK; Spearman R of 0.50 and 0.43, respectively, p < 0.001). Extrinsic AD patients were more likely to have higher mean SCORAD (p < 0.001), CCL17 (p < 0.001), CCL26/eotaxin-3 (p < 0.001), and eosinophil count (p < 0.001) than intrinsic AD patients. Predictive models for SCORAD identified CCL17, CCL27, serum total IgE, IL-33, and IL-5 as the most important predictors for SCORAD, but with weaker associations than single cytokines.Specific immunoinflammatory biomarkers in the serum, mainly of the Th2 pathway, are correlated with disease severity in patients with AD. Predictive models identified biomarkers associated with disease severity but this finding warrants further investigation.

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