Biomarkers and clinical indicators of disease activity in vitiligo. Issue 5 (9th December 2022)

• Record Type: Journal Article
• Authors: Delbaere, Liesbeth; Speeckaert, Reinhart; Herbelet, Sandrine; Belpaire, Arno; Duponselle, Jolien; van Geel, Nanja
• Other Names: Gupta Somesh guestEditor.; Mysore Venkatram guestEditor.
• Is Part Of: Dermatological reviews. Volume 3:Issue 5(2022)
• Page Start: 289
• Page End: 307
• Publication Date: 2022-12-09
• Subjects: biomarkers -- disease activity -- visible clinical signs -- vitiligo; Dermatology -- Periodicals; Electronic journals; 616.5
• DOI: 10.1002/der2.168
• Languages: English
• ISSNs: 2637-7489

Abstract

Abstract: Background : The management of vitiligo is guided by the assessment of disease activity. However, this assessment is hampered by the absence of a highly feasible and reliable single marker to evaluate activity. Furthermore, the need for an objective, easy, preferably noninvasive marker is further stressed by the increased amount of research performed on new treatment strategies for vitiligo. Objectives : In this review, the available research on clinical signs linked to disease activity, and biomarkers in tissues and blood are summarized. Results : In the group of clinical signs, the Koebner phenomenon has the strongest evidence of an association with disease activity, while confetti‐like depigmentation is gaining importance and seems to outweigh this role. For the tissue markers, the most evidence is available for histopathological findings, such as epidermal spongiosis with vacuolar degeneration in the basal cells and inflammatory infiltrate. Circulating biomarkers such as interleukin‐1β (IL‐1β), IL‐17, interferon‐γ, tumor growth factor‐β, soluble cluster of differentiation 25, autoantibodies, and oxidative stress markers show the most promising results. Nevertheless, none of them are currently regarded as the gold standard. Discussion : In conclusion, we encourage researchers to investigate various biomarkers and clinical signs in their trials in a standardized manner to get insight into their exact value, so they can be used to optimize treatment selection, gain insight into the disease, and predict future disease progression.