Myeloid marker S100A8/A9 and lymphocyte marker, soluble interleukin 2 receptor: biomarkers of hidradenitis suppurativa disease activity?
- 5 June 2013
- journal article
- research article
- Published by Oxford University Press (OUP) in British Journal of Dermatology
- Vol. 168 (6) , 1252-1258
- https://doi.org/10.1111/bjd.12234
Abstract
Hidradenitis suppurativa (HS) is a chronic inflammatory and debilitating disease of the skin. No biomarkers for this disease exist. We set out to test whether angiotensin-converting enzyme (ACE), lysozyme, soluble interleukin 2 receptor (sIL-2R) and S100A8/A9 (calprotectin) are elevated in patients with HS. Serum was collected from 29 patients with HS at different stages of the disease, and from 51 controls. ACE, lysozyme, sIL-2R and S100A8/A9 levels were measured. Clinical observation of disease activity was scored according to the Hurley grading system and by a physician global score (PGS) of disease severity. Serum levels of lysozyme and ACE were not increased above the normal reference values in controls or patients with HS. Levels of sIL-2R and S100A8/A9 were significantly higher in patients with HS than in controls (P<0·001 for both sIL-2R and S100A8/A9). Based on the receiver operating characteristic curves, the optimum sIL-2R and S100A8/A9 cut-off values were 375 U mL(-1) and 680 ng mL(-1), respectively, with a sensitivity of 0·79 and specificity of 0·78 for sIL-2R, and 0·86 and 0·88, respectively, for S100A8/A9. No correlations with Hurley classification scores were found. However, when using PGS of disease activity to categorize patients, levels of S100A8/A9, but not sIL-2R, tended to be higher in patients with more active disease. Levels of S100A8/A9 and sIL-2R, but not ACE or lysozyme, are elevated in the serum of patients with HS. However, there is no correlation between S100A8/A9 or sIL-2R levels and disease stage according to the Hurley classification system. Further research is needed to study the potential of S100A8/A9 to score disease activity in larger cohorts of patients and to predict disease flares.Keywords
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