TY - JOUR

T1 - Immunoinflammatory Biomarkers in Serum Are Associated with Disease Severity in Atopic Dermatitis

AU - Holm, Jesper Grønlund

AU - Hurault, Guillem

AU - Agner, Tove

AU - Clausen, Maja Lisa

AU - Kezic, Sanja

AU - Tanaka, Reiko J.

AU - Thomsen, Simon Francis

PY - 2021

Y1 - 2021

N2 - Background: 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. Objective: To explore the relationship between various immunological markers in the serum and disease severity in a hospital cohort of AD patients. Methods: 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. Results: 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. Conclusions: 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.

AB - Background: 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. Objective: To explore the relationship between various immunological markers in the serum and disease severity in a hospital cohort of AD patients. Methods: 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. Results: 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. Conclusions: 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.

KW - Atopic dermatitis

KW - Biomarkers

KW - Disease severity

KW - Inflammation

U2 - 10.1159/000514503

DO - 10.1159/000514503

M3 - Journal article

C2 - 33730733

AN - SCOPUS:85102804880

VL - 237

SP - 513

EP - 520

JO - Dermatology

JF - Dermatology

SN - 1018-8665

IS - 4

ER -