Frontiers in allergy · 2026
Integrative skin-blood transcriptomic analysis identifies circulating biomarkers reflecting disease activity in atopic dermatitis.
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Fernández-Bernaldez Alberto, Jiménez-Sánchez Ana, Chicharro Pablo, González-Agudo Celia, Sánchez-Cabo Fátima, Vara Alicia, Llamas-Velasco Mar, Gómez Manuel José, de la Fuente Hortensia
Аннотация
BACKGROUND: Atopic dermatitis (AD) is characterized by complex immune dysregulation primarily studied in lesional skin. Identifying circulating molecular signatures that mirror cutaneous inflammation could enable non-invasive disease monitoring.
METHODS: Transcriptomic data from lesional skin and peripheral blood T lymphocytes of patients with AD were analyzed using differential expression, pathway enrichment, upstream regulator prediction, and protein-protein interaction network modeling. Genes dysregulated in both compartments were prioritized and validated in serum samples from patients with moderate-to-severe AD.
RESULTS: Despite limited concordance at the individual gene level, skin and blood shared a common inflammatory regulatory landscape, including activation of Th2- and Th17-related cytokine signaling, together with a consistently prediction of ESR1 inhibition across both compartments. Network analysis identified key hub genes and a neuro-immune signaling module. Among shared molecules, serum S100A8 levels positively correlated with disease severity, while SOCS3 showed a negative association. LCN2 and CTLA4 displayed trends toward correlation.
CONCLUSIONS: Systemic molecular alterations in AD partially reflect cutaneous inflammation and support circulating S100A8 and SOCS3 as potential biomarkers of disease activity.
METHODS: Transcriptomic data from lesional skin and peripheral blood T lymphocytes of patients with AD were analyzed using differential expression, pathway enrichment, upstream regulator prediction, and protein-protein interaction network modeling. Genes dysregulated in both compartments were prioritized and validated in serum samples from patients with moderate-to-severe AD.
RESULTS: Despite limited concordance at the individual gene level, skin and blood shared a common inflammatory regulatory landscape, including activation of Th2- and Th17-related cytokine signaling, together with a consistently prediction of ESR1 inhibition across both compartments. Network analysis identified key hub genes and a neuro-immune signaling module. Among shared molecules, serum S100A8 levels positively correlated with disease severity, while SOCS3 showed a negative association. LCN2 and CTLA4 displayed trends toward correlation.
CONCLUSIONS: Systemic molecular alterations in AD partially reflect cutaneous inflammation and support circulating S100A8 and SOCS3 as potential biomarkers of disease activity.