Insights into adult atopic dermatitis heterogeneity derived from circulating biomarker profiling in patients with moderate-to-severe disease

Abstract

Atopic dermatitis (AD) is a heterogeneous systemic inflammatory skin disease associated with dysregulated immune responses, barrier dysfunction and activated sensory nerves. To characterize circulating inflammatory profiles and underlying systemic disease heterogeneity within AD patients, blood samples from adult patients (N = 123) with moderate-to-severe AD in a phase 2 study of baricitinib (JAHG) were analysed. Baseline levels of 131 markers were evaluated using high-throughput and ultrasensitive proteomic platforms, patient clusters were generated based on these peripheral markers. We implemented a novel cluster reproducibility method to validate cluster outcomes within our study and used publicly available AD biomarker data set (73 markers, N = 58 patients) to validate our findings. Cluster reproducibility analysis demonstrated best consistency for 2 clusters by k-means, reproducibility of this clustering outcome was validated in an independent patient cohort. These unique JAHG patient subgroups either possessed elevated pro-inflammatory mediators, notably TNFβ, MCP-3 and IL-13, among a variety of immune responses (high inflammatory) or lower levels of inflammatory biomarkers (low inflammatory). The high inflammatory subgroup was associated with greater baseline disease severity, demonstrated by greater EASI, SCORAD Index, Itch NRS and DLQI scores, compared with low inflammatory subgroup. African-American patients were predominantly associated with the high inflammatory subgroup and increased baseline disease severity. In patients with moderate-to-severe AD, heterogeneity was identified by the detection of 2 disease subgroups, differential clustering amongst ethnic groups and elevated pro-inflammatory mediators extending beyond traditional polarized immune responses. Therapeutic strategies targeting multiple pro-inflammatory cytokines may be needed to address this heterogeneity.

Keywords: Th1-Th2 balance; atopic; biomarkers; computational biology; dermatitis; population heterogeneity.