Clinical and molecular markers of vitiligo: a narrative review of early-stage insights into disease activity and treatment response.

Abstract

Vitiligo fluctuates between progressive and quiescent states, complicating decisions about when to intervene, how to select therapy and how to monitor response. In this review, we integrate bedside phenotypes with multilevel molecular readouts to summarize emerging evidence linking clinical signs and biologic signals to disease activity and treatment response in clinical studies. For staging, tool-free and standardized assessments such as Koebner phenomenon, confetti-like depigmentation, Wood's lamp and dermoscopy provide visible clues associated with active disease. Measurements from blood, suction blister fluid and tissue offer complementary insights into local and systemic immune activation, suggesting how molecular signals may relate to progression. For stratification, factors such as age, lesion site, disease stability, comorbidities and dermoscopic border features have been tentatively associated with differential responses to therapies such as phototherapy or transplantation. Similarly, lower baseline levels of inflammatory, chemotactic and cytotoxic markers have been informally aligned with better outcomes in clinical studies. For monitoring, the response phase typically mirrors a reversal of progression: waning inflammatory signalling, reduced effector-cell burden and partial recovery of melanogenic programmes provide molecular parallels to clinical improvement. Across these domains, the interferon-γ-CXCL9/CXCL10-CD8+ T-cell axis emerges as the most recurrent immune signature, demonstrating reproducible associations with activity, prognosis and treatment response. Future work should prioritize harmonized definitions of disease activity, standardized sampling standards and multicentre validation of integrated biomarker panels. It is equally critical to determine whether proposed biomarker thresholds relate to clinically meaningful endpoints, thereby translating early-stage discoveries into reliable frameworks for staging, stratification and monitoring.